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WoRMS - World Register of Marine Species

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An authoritative classification and catalogue of marine names

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What's that sound?Added on: 2024-01-09 12:22:56 by Dekeyzer, StefanieA Global Inventory of Sound Production Brings Us One Step Closer to Understanding Aquatic Ecosystems. ...Read moreFive Decades in Carcinology - Tribute to Jim LowryAdded on: 2023-12-08 12:49:58 by Vandepitte, LeenOn 6th December 2023 a Festschrift in honour of the late Dr James K. (Jim) Lowry (1942–2021), renowned Amphipod taxonomist and WoRMS editor, was published by the Records of Australian Museum. ...Read moreAwardees for the 2023 WoRMS Achievement & Early Career Researcher Award knownAdded on: 2023-12-06 13:41:50 by Vandepitte, LeenThis year, Peter Schuchert has been honored with the WoRMS Achievement Award, and the WoRMS Early Career Researcher Award goes to Tristan Verhoeff. ...Read moreCall for nominations for the WoRMS Top-Ten Marine Species of 2023Added on: 2023-11-29 15:49:46 by Dekeyzer, StefanieOnce again taxonomists have continued to publish many wonderful new species throughout the last year. As we approach the end of 2023 it is time to think about nominations for The WoRMS Top Ten Marine Species of 2023! ...Read moreIn memoriam: Crinoidea editor Charles MessingAdded on: 2023-11-13 17:02:53 by Vandepitte, LeenOver the weekend, the WoRMS Data Management Team received the sad news that Charles – Chuck - Messing has passed away. ...Read moreOcean Census and WoRMS Announce Partnership to Enhance Rapid Discovery and Identification of Marine LifeAdded on: 2023-10-09 14:57:09 by Dekeyzer, StefanieCollaboration with network of volunteer taxonomic specialists key to mission to accelerate the discovery of ocean life. ...Read more

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Currently in WoRMS

Accepted marine species

245 314

(98% checked)

Marine species names, including synonyms

505 727

Species with image

44 564

(63% checked)

WoRMS editors

322

Registered institutional users

423

Webhits

118 713 213 (In 2023)

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What is LifeWatch

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WoRMS - World Register of Marine Species

Toggle navigation

marine only

extant only

Home

About

Subregisters

Users

Photogallery

Documents

LifeWatch

Contribute

Scientific names

Common names (slower)

Advanced search

Taxa

Literature

Distribution

Specimen

Editors

Statistics

Tools

Match taxa

Webservices

Taxon tree

IDKeys

Manual

What is WoRMS

What is Aphia

Higher classification

What is LifeWatch

Ocean Decade

Governance

Partners

Funding

Citing WoRMS

WoRMS in literature

PLoS One collection

Activities

WoRMS Awards

What is WoRMS?

The aim of a World Register of Marine Species (WoRMS) is to provide an authoritative and comprehensive

list of names of marine organisms, including information on synonymy. While the highest priority goes to

valid names, other names in use are included so that this register can serve as a guide to interpret

taxonomic literature.

The content of WoRMS is controlled by taxonomic and thematic experts, not by database managers. WoRMS has an

editorial management system where each taxonomic group is represented by an expert who has the

authority over the content, and is responsible for controlling the quality of the information.

Each of these main taxonomic editors can invite several specialists of smaller groups within their

area of responsibility to join them.

This register of marine species grew out of the European Register of Marine Species (ERMS),

and its combination with several other species registers maintained at the Flanders Marine Institute (VLIZ).

Rather than building separate registers for all projects, and to make sure taxonomy used in these different projects is consistent,

VLIZ developed a consolidated database called ‘Aphia’. A list of marine species registers included in Aphia is available here.

MarineSpecies.org is the web interface for the marine taxa available in this Aphia database. WoRMS combines information from

Aphia with other authoritative marine species lists which are maintained by others (e.g. AlgaeBase,

FishBase), the so-called 'externally hosted and managed species databases'.

Resources to build MarineSpecies.org and Aphia were provided mainly by the EU Network of Excellence

‘Marine Biodiversity and Ecosystem Functioning’ (MarBEF),

and also by the EU funded Species 2000 Europe and ERMS projects.

Aphia contains valid species names, synonyms and vernacular names, and extra information such as

literature and biogeographic data. Besides species names, Aphia also contains the higher classification

in which each scientific name is linked to its parent taxon. The classification used is a ‘compromise’

between established systems and recent changes. Its aim is to aid data management, rather than suggest

any taxonomic or phylogenetic opinion on species relationships.

Keeping WoRMS up-to-date is a continuous process. New information is entered daily by the taxonomic

editors and by the members of our data management team. Often data also come in from contributions of

large datasets, such as global or regional species lists. No database of this size is without errors

and omissions. We can’t promise to make no errors, but we do promise to follow up and give feedback

on any communications pointing out errors. Feedback is very welcome!

What is Aphia?

The Aphia platform is an infrastructure designed to capture taxonomic and related data and information, and includes an online editing environment.

It is the core platform that underpins the World Register of Marine Species (WoRMS) and all its related global, regional and thematic species databases, but it also allows the storage of non-marine data.

The Aphia platform is an MS SQL database, containing over 400 fields spread over more than 80 related tables. Content-wise, the Aphia structure can roughly be divided into 10 modules: taxonomy, distribution, traits,

specimen information, vernacular names, notes, links, images, identification keys and sources.

Almost all information available in Aphia is backed up with a source.

This serves a double purpose: it allows easy quality control of the added information and it guides users to potentially more information than what has been documented in Aphia.

Aphia uses unique and stable identifiers for each available name in the database, through Life Science Identifiers (LSIDs). The system not only allows the storage of accepted and unaccepted names, but it also

documents the relationship between names. This makes it a very powerful tool for taxonomic quality control, and also allows the linking of different pieces of information through scientific names, both within the Aphia

platform and in relation to externally hosted databases.

Through the use of LSIDs, Aphia - and thus WoRMS - have become an important player in the field of (marine) biodiversity informatics, allowing interactions between its own taxonomic data and e.g. biogeographic databases,

such as e.g. the European and international Ocean Biodiversity Information System (EurOBIS & OBIS).

Three main categories of Species Databases can be distinguished in Aphia, based on the use of a context: Global Species Databases (GSD), Regional Species Databases (RSD) and Thematic Species Databases (TSD).

All these different Species Databases within Aphia are governed on 3 different levels.

The use of so-called 'contexts' is unique to Aphia. These contexts allow an easy management of specific content and form the backbone for the creation of distinct portals,

through which editors can maintain their taxonomic, thematic or regional register.

The advantage of these contexts is that all information only needs to be added once to the database: one entry can then receive multiple contexts and can thus be displayed through several portals.

GSDs are based on the higher classification of taxa and include WoRMS, as the global database of all marine life. In RSDs, taxa are grouped based on their known geographic occurrence

and TSDs group taxa based on a particular characteristic.

Occassionally, new GSDs, RSDs or TSDs are integrated into Aphia through Data Rescue Actions.

The reasons for migrating a Register can be multiple, but mostly relates to the need of a permanent host institute and continuous support by a Data Management Team to protect the data from being lost for the scientific community.

These kind of actions require thorough planning and the design of a future management plan in close collaboration with the original manager and host institute.

For a full description of Aphia, we refer to the publication 'How Aphia - the platform behind several online and taxonomically oriented databases -

can serve both the taxonomic community and the field of biodiversity informatics'.

Higher classification

A higher level classification of all living organisms was published by Ruggiero et al. (2015).

This paper provides a management classification for all living organisms and forms the basis for the Catalogue of Life higher classification.

A comparison between this paper and the higher classification in WoRMS has been made. Where inconsistencies appear, the responsible editors were consulted to see if changes are needed.

WoRMS aims to reflect current knowledge and therefore allows newer publications to be applied to higher level taxa, supported by appropriate sources which will be indicated on the subregister or taxon page.

If no editor is available for a group, the classification by Ruggiero et al. (2015) will be followed. Ruggiero et al. (2015) cover the classification from superkingdom to order level.

Below the rank of order (e.g., suborder, infraorder, parvorder, superfamily, family, subfamily, genus) the classification is the responsibility of the editor of the taxon.

What is LifeWatch?

Background

LifeWatch was established as part of the European Strategy Forum on Research Infrastructure (ESFRI) and can be seen as a virtual laboratory for biodiversity research.

The concept behind LifeWatch was developed in the 1990s and early 2000s, with the support of EU Networks of Excellence related to biodiversity and ecosystem functioning.

This - amongst others - included the MarBEF project, which was the driving project behind the creation

of the European Register of Marine Species (ERMS) data system - the predecessor of the World Register of Marine Species (WoRMS).

Belgium contributes to LifeWatch with varied and complementary "in-kind" contributions. These are implemented under the form of long lasting projects

by different research centers and universities spread over the country and supported by each respective political authority. Within LifeWatch,

the Flanders Marine Institute - host of the World Register of Marine Species (WoRMS) - has taken on the responsibility to develop the

LifeWatch Species Information Backbone.

LifeWatch mission

The mission of LifeWatch is to advance biodiversity research and to provide major contributions to address the big environmental challenges,

such as knowledge-based solutions to environmental managers in the framework of preservation or dealing with long-standing ecological questions

that could so far not be addressed due to a lack of data or - more importantly - a lack of good and easy access to data.

The LifeWatch mission is being achieved by giving access to data and information through a single infrastructure which (virtually) brings together

a large range and variety of datasets, services and tools. Scientists can use these tools and services to construct so-called Virtual Research Environments (VREs),

where they are able to address specific questions related to biodiversity research, including e.g. topics related to preservation.

The construction and operation of the LifeWatch e-infrastructure is revolutionizing the way scientists can do biodiversity research.

They are not only offered an environment with unlimited computer and data storing capacity, but there is also transparency at all stages of their research process

and the generic application of the e-infrastructure open the door towards more inter- and multidisciplinary research.

LifeWatch Species Information Backbone

The Flanders Marine Institute (VLIZ) is responsible for the set-up of the LifeWatch Species Information Backbone,

as a central part of the European LifeWatch Infrastructure.

The backbone aims to (virtually) bring together different component databases and data systems, all of them related to taxonomy, biogeography, ecology, genetics and literature.

By doing so, the backbone standardises species data and integrates biodiversity data from different repositories and operating facilities and is the driving force behind the species information services

of the Belgian LifeWatch.be e-Lab and the Marine Virtual Research Environment (Marine-VRE) that are being developed.

The LifeWatch Species Information Backbone consists of five major components:

Taxonomy (species registers)

Biogeography (species occurrences)

Literature

Ecology (traits)

Genetics

WoRMS not only contributes to the Species Registers in the backbone, but also to all of the other parts.

As all the WoRMS type localities - where there is latitude & longitude information available -

are sent to the Ocean Biodiversity Information System (OBIS), through its European node EurOBIS,

WoRMS also contributes to the biogeographic part of the backbone.

In addition, all the literature that is available through WoRMS - from original descriptions to large-scale taxon overviews and ecological papers - is at the disposal of the backbone.

As WoRMS also stores trait information - either documented by its editorial network or shared through externally hosted and managed species databases -, these data contribute to the traits-part of the LifeWatch Species Information Backbone,

allowing e.g. the link between taxonomy, biogeography and traits through LifeWatch web services.

So far, the only link from WoRMS to the genetics part of the LifeWatch Species Information Backbone is the fact that WoRMS provides deep-links to GenBank on its species pages.

Through the LifeWatch Species Information Backbone, users benefit in several ways, amongst others by:

Easy access to data and information to a variety of resources, including the World Register of Marine Species The opportunity to quality control their own data, by cross-checking with data available through the backbone, e.g. perform a taxon-match against WoRMS, to verify their own species names

Easy access to a wide range of data services and web services, free to use

The possibility to combine available services into workflows, and link several systems together (e.g. link taxonomic and traits information from WoRMS with biogeographic information from OBIS)

The coordination and development of the LifeWatch Species Information Backbone happens at three different levels:

Setting up a central species information backbone

Completing and updating the taxonomic and species related data

Organizing and mobilizing the taxonomic experts that provide the data

The work done at all these levels is strongly reflected in the ongoing activities of the World Register of Marine Species and are described in detail under Activities.

WoRMS - and more specifically the Aphia platform - is currently the biggest contributor to the taxonomic part of the LifeWatch Species Information Backbone.

The work of the DMT is currently being funded through the LifeWatch project.

UN Decade For Ocean Sciences

Ocean Decade vision

The vision of the United Nations Decade of Ocean Science for Sustainable Development (2021-2030) is the "science we need for the ocean we want".

The Ocean Decade is a convening framework for diverse stakeholders to co-design and co-deliver solution-oriented research needed for a well-functioning ocean in support of the 2030 Agenda. Capacity development, ocean literacy and the removal of barriers to full gender, generational, and geographic diversity are essential elements of the Decade.

ABC WoRMS: Above and Beyond - Completing the World Register of Marine Species

During 2021, the WoRMS Steering Committee and Data Management Team submitted a proposal under the first call for Actions,

entitled "Above and Beyond — Completing the World Register of Marine Species" (ABC WoRMS),

which received endorsement as an official UN Ocean Decade Project in October 2021.

During the full span of the Ocean Decade, WoRMS will continue its endeavors to be able to provide a full taxonomic overview of all marine life,

thereby not only supporting scientists, but everyone who makes use of species names, including policy, industry and the public at large.

Although already fairly complete, taxonomic gaps still need to be addressed, in both space and time. New challenges in the field of taxonomy -

such as temporary names - need to be explored, thereby looking for the best suitable solution for all WoRMS users.

The documentation of species traits which are of critical importance for ecological marine research will be encouraged, as will there be increased efforts

to link with other global databases, infrastructures and initiatives such as

LifeWatch,

LifeWatch Species Information Backbone,

OBIS,

GOOS,

COL,

BoLD &

GenBank.

High-level objectives of WoRMS within the UN Ocean Decade

To provide a complete database of marine taxon names, by targeting the currently identified priorities and gaps, documenting the relationships between existing names, and linking each name to supporting taxonomic literature.

To serve as a data rescue platform for taxonomically-focused databases at the brink of disappearing, thereby safeguarding expert knowledge and making it widely and publicly available.

To develop a strategy and guidelines to consistently deal with well-established temporary names and open taxonomic nomenclature within the World Register of Marine Species, as this kind of nomenclature is being used more frequently by the taxonomic community and can no longer be ignored in taxonomic databases.

To encourage the documentation of species traits which are of critical importance for ecological marine research. Trait information is not always easily available and accessible, but WoRMS provides an excellent platform for the capture of these data in a structured and easily accessible format.

To provide improved support and links between other global databases and infrastructures that use a marine taxonomic backbone, such as the Ocean Biodiversity Information System (OBIS) & the Global Ocean Observing System (GOOS), as well as improved content and stronger relationships with environment-independent initiatives and infrastructures such as Catalogue of Life (COL), the Barcode of Life Data System (BoLD) & GenBank.

To widen the user-group of WoRMS, targeting all groups of the so-called quadruple helix: scientists, policy makers, industry and the public at large.

WoRMS & Marine Life 2030

As an Ocean Decade Project, WoRMS is linked to the endorsed Action Programme Marine Life 2030: A Global Integrated Marine Biodiversity

Information Management and Forecasting System for Sustainable Development and Conservation.

Marine Life 2030 will unite existing and frontier technologies and partners into a global, interoperable network and community of practice

advancing observation and forecasting of marine life. It will establish a globally coordinated system to deliver actionable, transdisciplinary

knowledge of ocean life to those who need it, promoting human well-being, sustainable development and ocean conservation.

See also Marine Life 2030 official website.

WoRMS & Challenger 150

Early 2023, WoRMS formed a partnership with the endorsed Action Programme Challenger 150. The Challenger 150 programme is a global

scientific cooperative developed to respond to the needs of the UN Ocean Decade, and is a vehicle for the coordination of deep-sea research

globally towards a set of common objectives. Challenger 150 recognises WoRMS as the global marine taxonomy standard, and aims to partner

with the WoRMS taxonomic editors to deliver high quality biodiversity observations and support the development of novel tools, technologies,

and training materials to raise standards in biological observation data. One of the working groups focuses on the development of

standards in image annotation, building on efforts such as the Australian CATAMI classification system and the SMarTaR-ID project,

which could highly benefit from the WoRMS editor involvement.

See also Challenger 150 official website.

WoRMS & Sustainable Development Goals

WoRMS mainly and directly contributes to Goal 14, Life Below Water.

In order to be able to protect, conserve and sustainably manage marine life,

knowledge of which species are encountered below the surface of oceans and seas,

and their characteristics, is critical to our ability to define their potential as a resource, their potential threats,

and to develop means to protect and sustainably manage them.

When looking at the distribution of marine life, one needs to be able to correctly name a species.

Additionally, linking a species and its characteristics to its distribution can give valuable insights on how a species

is affected by its surroundings. Knowing which species have a calcified skeleton is highly relevant in any research linked to climate change

and ocean acidification (Goal 13: Climate Action).

WoRMS provides a global marine species register, with links between 'old' and 'new' names for species,

including a platform for documentation of relevant traits or characteristics. WoRMS can be used as a taxonomic and traits-backbone with

large infrastructures such as OBIS and GOOS.

Governance

WoRMS is managed at three different levels, each having their own tasks and responsibilities:

the Steering Committee (SC)

the Editorial Board

the Data Management Team (DMT)

1. Steering Committee (SC)

The WoRMS Steering Committee (SC) represents the members of the WoRMS Editorial Board in all matters related to the databases, including acting as a liaison with other international projects and initiatives.

They take care of the day-to-day business of WoRMS and set priorities for future activities.

The SC consists of 12 elected members from within the Editorial Board who can serve for a period of 3 years, with the possibility of re-election.

The WoRMS SC members appoint a chair and vice-chair by majority vote. The chair and vice-chair are elected for a 3-year term; re-election for a second term is possible.

Ahyong, Shane

Chair

Australian Museum; Marine Invertebrates, Australia

Last elected: 2020

Boyko, Christopher

Vice-chair

American Museum of Natural History; Division of Invertebrate Zoology

Last elected: 2021

Bailly, Nicolas

Quantitative Aquatics, Inc., Philippines

Last elected: 2021

Bernot, James

Smithsonian Institution; National Museum of Natural History; Department of Invertebrate Zoology, USA

Last elected: 2022

Bieler, Rüdiger

Field Museum of Natural History, USA

Last elected: 2021

Brandão, Simone

Universidade Federal Rural de Pernambuco; Unidade Acadêmica de Serra Talhada, Brasil

Last elected: 2022

Daly, Meg

Ohio State University; Department of Evolution, Ecology and Organismal Biology, USA

Last elected: 2022

De Grave, Sammy

University of Oxford; Museum of Natural History, UK

Last elected: 2022

Gofas, Serge

University of Málaga; Faculty of Sciences; Departamento de Biología Animal, Spain

Last elected: 2022

Hernandez, Francisco

ex officio, datamanager, substitute: Leen Vandepitte

Vlaams Instituut voor de Zee, Belgium

Hughes, Lauren

Natural History Museum, UK

Last elected: 2022

Neubauer, Thomas A.

Bavarian State Collection for Paleontology and Geology, Germany

Last elected: 2022

Paulay, Gustav

University of Florida; Florida Museum of Natural History, USA

Last elected: 2020

2. Editorial board

The Editorial Board includes all active editors and data providers.

Their main task is to take responsibility for one or more taxa, themes or regions under their expertise, by adding newly published taxa to WoRMS, correcting errors and constantly being on the look-out for information of interest to WoRMS.

The Editorial board is the pivot of WoRMS: they dedicate their spare time to making WoRMS more complete and helping the DMT in answering user questions and fixing issues that arise from quality control.

The Editorial Board is a very dynamic body. A full list of all the taxonomic experts can be found on the editors page.

Send us an email if

you have any questions or want to contribute to this initiative.

Our editors around the world!

3. Data Management Team (DMT)

The Data Management Team is based at the Flanders Marine Institute (VLIZ - Belgium), home of the World Register of Marine Species.

The DMT consists of both technical and scientific staff, each following up on specific aspects of WoRMS.

The DMT is responsible for keeping the database online, protecting its integrity and the persistence of the unique identifiers (AphiaIDs).

View the current Data Management Team (DMT) members.

The DMT provides support on different levels:

Support to editors

The DMT supervises all ongoing editing activities and supports editors where needed in their work.The support can be both on the technical and content side of the database. The DMT can upload bulk information into the database and run specific queries to help identify gaps or issues for editors to deal with.

In addition, the DMT also does online editing upon request of the editors.

An online manual provides background information on how editors can work with the online editing interface. The DMT is always stand-by to help editors with the use of this interface.

Additionally, the DMT may develop new tools and features that enhance the data entry.

Support to users

Through email, the DMT is receiving a lot of questions such as: requests to identify encountered species during field or diving trips, the removal of duplicates, reporting errors in the database, etc...

The DMT works as a filter between our users and the editors, to avoid an overload of emails for our editors.

The DMT also manages the distribution of the monthly downloads and deals with custom-tailored user requests regarding extraction of content from the database.

In addition, it provides exports of the database to numerous other initiatives.

IT developments

New technical developments mostly take place in the framework of projects or link to initiatives within the WoRMS community.

The DMT provides a continuous technical support to the many users of WoRMS, including fixing minor bugs brought to our attention, help in modifying

web service client scripts and help in setting up batch upload of information (e.g. images, deep links, ...).

The WoRMS database is archived every month and you may request a copy in compliance with the terms and conditions as outlined the request form.

If you are interested in the structure of the database, we have created a view at WoRMS structure.

Partners

WoRMS cannot only count on its vast network of editors to maintain and expand its content, but can also rely on other taxonomic databases,

willing to share their expertise and content with WoRMS. Within WoRMS, these databases are referred to as 'externally hosted and managed Species Databases'.

The reason for such collaborations is simple: if something good already exists, the effort should not be duplicated. Agreements have been sought with all these databases, so that their content can also

be stored in Aphia and can be displayed through the different relevant portals. The responsibility for the content and the daily management remains with the original host institute.

The majority of the information pulled from these databases relates to taxonomy, although collaboration can also be sought based on distribution or traits information these sources have available.

WoRMS is currently pulling information from the following externally hosted and managed Species Databases:

AlgaeBase

FishBase

Index Fungorum (IF)

International Committee on Taxonomy of Viruses (ICTV)

Phylum Ctenophora: list of all valid species names

The Reptile Database

the Freshwater Animal Diversity Assessment (FADA)

Recent & Fossil Bryozoa

SeaLifeBase

For large-scale collaborations - and specifically cases where the content of WoRMS is distributed through other channels - Memoranda of Understanding (MoUs) are set up (or in the process of being set up)

between WoRMS and these external systems.

These MoUs discuss in detail under which conditions the WoRMS data can be shared and - in case of a two-way data exchange - how WoRMS can use the data from the other resource.

An overview of the current MoUs is available in the Documents section.

There are not only systems that receive data from WoRMS or share their data with WoRMS, but WoRMS is also heavily used as a taxonomic quality control tool for other data systems, within projects or by individual researchers.

They mostly make use of the online tools and services WoRMS is offering, and cross-check the quality of their own species lists with what is available in WoRMS.

Some instances receive a monthly download of WoRMS, which is used for similar purposes. The Users page lists all known users and for which reasons they are using WoRMS.

WoRMS is (part of) the taxonomic backbone behind several projects and initiatives, such as EurOBIS, OBIS,

GBIF and EMODnet Biology.

Within these initiatives, WoRMS is used to cross-check the taxonomic names available in each of these data systems. The idea is that each name in those systems is linked to a name in WoRMS, or an explanation for not linking is provided.

Not only the taxonomy of WoRMS can be used for quality control purposes, but also the available distribution information.

As an extra functionality, the occurrence information of OBIS can be combined with the available distribution maps in WoRMS. The visual comparison of WoRMS and OBIS for species distributions can act as an extra

quality control for both systems: deviations could point to a data gap in WoRMS or could indicate possible errors in OBIS.

Both of these outcomes can help improve the content and quality of the two databases.

Funding

All WoRMS content is open-access and available at no charge.

The maintenance and further development of WoRMS relies on financial contributions, the time contributed by

its editorial board, and support of its host institution: VLIZ.

WoRMS is currently funded through the LifeWatch Belgium project.

Through LifeWatch, it is possible to have a dedicated Data Management Team supporting the many WoRMS editors and users.

If you would like to know how you can contribute to WoRMS, please visit our 'contribute' page.

In the past, several projects and initiatives have provided funding for WoRMS.

Project funding

The following European Commission projects financially contributed to WoRMS:

2004-2009: Marine Biodiversity and Ecosystem Functioning (MarBEF)

2009-2011: Pan-European Species directories Infrastructure (PESI)

2010-2012: European Marine Observation and Data NETwork - EMODnet Biology I (EMODnet)

2010-2012: Distributed Dynamic Diversity Databases for Life (4D4Life)

2013-2016: European Marine Observation and Data NETwork - EMODnet Biology II (EMODnet)

2014-2016: Aquatic Species Register Exchange and Services (AquaRES)

2017-2020: European Marine Observation and Data NETwork - EMODnet Biology III (EMODnet)

2012-2024: LifeWatch (www.lifewatch.be) - See [activities]

Service grants

Financial support for WoRMS has enabled us to fill some pertinent gaps, such as in those groups where no global species list existed (e.g. ostracods, some parasitic groups, molluscs, ...)

or to enhance the quality control (molluscs, birds, …). Funding is used to pay for data entry personnel, coordination and taxonomic expert staff time, travel to key meetings,

and has been coordinated through the Flanders Marine Institute (VLIZ), Natural History Museum, (London), Muséum National d'Histoire Naturelle (Paris) and the University of Auckland.

Our taxonomic editors contribute significantly to the databases through their own time. Collectively we have estimated this to be worth several million Euros.

Examples of such funding include:

Alfred P. Sloan Foundation (via Census of Marine Life, Memorial University, Canada)

Global Biodiversity Information Facility (GBIF)

Department of Fisheries and Oceans (DFO) (Canada)

Marine Environmental Data & Information Network (MEDIN) (UK)

National Science Foundation (NSF) CORONA project (USA)

The text on the WoRMS pages is open-access under the terms of the Creative Commons Attribution License (CC-BY).

This License permits unrestricted use, provided it is cited as requested on the WoRMS webpages, unless stated otherwise on the individual pages.

Images are by default open-access under the terms of the CC BY-NC-SA license, unless stated otherwise.

Re-distribution of the entire database is not permitted, unless by prior written agreement.

This is mainly to avoid circulation of (quickly) outdated copies of WoRMS, accessible through different pathways which can lead to confusion for our many users.

In exceptional cases, institutes may request a copy of the database (using this form), which will be assessed by two WoRMS Steering Committee members and the Data Management Team.

These data downloads consist of the taxonomic data only, and do not include additional data such as distributions, traits, notes, etc.

We strongly encourage the use of the on-line tools and available webservices instead of data requests, as the on-line database and webservices can guarantee continuous updates.

The WoRMS Editorial Board maintains this Register, but is aware that the content can have omissions and errors.

If you come across any error or incomplete information or you are willing to contribute to this initiative, please contact the Data Management Team or check out our Contribute page.

The majority of the photo gallery drawings used at the first and second level of the gallery are reproduced on WoRMS

with permission of the Linnean Society of London.

The DMT is grateful to them for granting permission for use, thereby giving us the opportunity to make the central entry-point of our photo gallery more uniform.

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WoRMS Editorial Board (2024). World Register of Marine Species. Available from https://www.marinespecies.org at VLIZ. Accessed 2024-03-07. doi:10.14284/170

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If the data from WoRMS constitute a substantial proportion of the records used in analyses, the chief editor(s) of the database should be contacted. There may be additional data which may prove valuable to such analyses.

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The World Register of Marine Species (WoRMS) is a major contributor to the LifeWatch Species Information Backbone.

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All of these activities are supported by staff members provided by VLIZ as part of the Flemish contribution to LifeWatch and is funded by the Hercules Foundation.

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The LifeWatch Species Information Backbone aims at bringing together taxonomic and species-related data and at filling the gaps in our knowledge.

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The target groups are either taxonomically, geographically or thematically oriented, with as main goal to make the targeted Register more complete and to define long-term plans to maintain it.

To make the most of these workshops, the programme includes at least 1/2 to 1 full day of hands-on working with the online editing interface.

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Several workshops have already been organized and the reports of these workshops can be found here.

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Awardees

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2016: Philippe Bouchet

Early Career Researchers Award

This award is intended to recognize the effort of a scientist who has contributed to WoRMS significantly within about 10 years of their PhD and was handed out for the first time in 2017.

Awardees

2023: Tristan Verhoeff

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2021: Ralf Cordeiro

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2018: François Le Coze

2017: Ben Thuy

Rules & evaluation criteria for both Awards

Rules

There are no restrictions based on age, nationality, time-period of contributions or kinds of contributions.

Typically one award will be made annually based on the outcome of evaluation of nominations. However, the jury reserves the option to make more or no awards.

Nominations can be made by members of the WoRMS Steering Committee, by active WoRMS editors, and by members of the Data Management Team. Self-nominations are not allowed.

Persons or groups may be nominated again in subsequent years. Any person or group can only receive the award once.

The WoRMS Steering Committee will appoint a jury of at least 5 persons to evaluate nominations. The Chair of the jury will be a member of the WoRMS Steering Committee.

A member of the Data Management Team will attend the meetings of the jury in order to provide data and/or advice, but has no vote.The jury will appoint a Secretary to receive and disseminate nominations.

The jury members will state their potential conflicts of interest and will not evaluate nominations of close colleagues (e.g. regular collaborator, works in same institute).

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The WoRMS Steering Committee will be notified prior to the announcement of the awardee but does not have any power of veto or influence in the selection process.

The jury will produce a brief citation giving the reasons for their selection of the awardee.

Lobbying jury members beyond the nomination process will disqualify candidates.

Evaluation criteria

Activity as editor.

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New ideas or innovations contributed or suggested.

Improvements to the web interface suggested.

Contribution to outreach and stimulation of the use of WoRMS.

Contribution to management and funding.

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worms是什么意思_worms的翻译_音标_读音_用法_例句_爱词霸在线词典

s是什么意思_worms的翻译_音标_读音_用法_例句_爱词霸在线词典首页翻译背单词写作校对词霸下载用户反馈专栏平台登录worms是什么意思_worms用英语怎么说_worms的翻译_worms翻译成_worms的中文意思_worms怎么读,worms的读音,worms的用法,worms的例句翻译人工翻译试试人工翻译翻译全文简明柯林斯牛津worms英 [wərmz]释义n.虫( worm的名词复数 ); （昆虫的）幼虫; （人或动物体内的）寄生虫; 懦夫点击人工翻译，了解更多人工释义实用场景例句全部The worms cannot be seen by the naked eye.这些虫子用肉眼看不见。柯林斯例句Worms have a lifespan of a few months.蠕虫的寿命为几个月。《牛津高阶英汉双解词典》birds looking for worms觅食蠕虫的鸟《牛津高阶英汉双解词典》They were digging up worms to use for bait.他们正在挖蚯蚓作鱼饵.《简明英汉词典》Many birds eat worms.很多鸟类都以虫为食.《简明英汉词典》This tree has been eaten hollow by worms.这棵树被虫子蛀空了.《现代汉英综合大词典》Worms and snakes crawl.虫类和蛇爬行.《现代英汉综合大词典》Most worms cocoon in winter.冬天多数虫子作茧.《现代英汉综合大词典》Drug abuse is a can of worms nobody wants to open at sporting events.滥用药物是体育赛事中无人想要触及的棘手问题。柯林斯例句Insects and worms are all invertebrates.昆虫和蠕虫都是无脊椎动物。辞典例句Undercooked pork may contain living " bladder worms " of the pig tapeworm.未煮熟的猪肉也许含有猪绦虫活的 “ 囊尾幼虫 ”.辞典例句Sparrows were scratching about in the damp soil for worms.麻雀正在潮湿的地方抓虫子吃.辞典例句The worms have perforated the mucosa to suck blood.虫体钻入粘膜吸血.辞典例句Digestive disturbances are common in infections with all the stomach worms.消化障碍是各种胃线虫感染的常见症状.辞典例句All species of worms in a habitat are considered.所有蚯蚓在栖息地达到相当数量.辞典例句收起实用场景例句真题例句全部高考But she expects using the chemical in some kind of industrial process-not simply "millions of worms thrown on top of the plastic".2018年高考英语北京卷阅读理解阅读C 原文Jennifer Debruyn, a microbiologist at the university of tennessee, who was not involved in the study, says it is not surprising that such worms can break down polyethylene.2018年高考英语北京卷阅读理解阅读C 原文Researchers in spain and england recently found that the worms of the greater wax moth can break down polyethylene, which accounts for 40% of plastics.2018年高考英语北京卷阅读理解阅读C 原文So far there is no effective way to get rid of it, but a new study suggests an answer may lie in the stomachs of some hungry worms.2018年高考英语北京卷阅读理解阅读C 原文The team left 100 wax worms on a commercial polyethylene shopping bag for 12 hours, and the worms consumed and broke down about 92 milligrams, or almost 3% of it.2018年高考英语北京卷阅读理解阅读C 原文To confirm that the worms' chewing alone was not responsible for the polyethylene breakdown, the researchers made some worms into paste and applied it to plastic films.2018年高考英语北京卷阅读理解阅读C 原文收起真题例句释义实用场景例句真

Worms - Facts, Diet & Habitat Information

s - Facts, Diet & Habitat Information Animal CornerDiscover the many amazing animals that live on our planet.HomeA-Z AnimalsAnatomyGlossaryAnimal ListsAnimal By LetterAnimals by LocationMammalsBirdsReptilesAmphibiansSpirit AnimalsFree ResourcesAnimal Coloring PagesAnimal JokesAnimal QuizzesPetsDog BreedsRabbit BreedsCat BreedsPet RodentsAnimal CareBlogYou are here: Home / Animals / WormsWormsImage SourceA Worm is an elongated soft-bodied invertebrate animal. The best-known is the earthworm, a member of phylum Annelida, however, there are hundreds of thousands of different species that live in a wide variety of habitats other than soil.Most worms live in our gardens and in other soiled areas such as fields and farms.Worms do not have arms, legs or bones, instead, they have a soft, often segmented body which is covered a tiny hairs or bristles that help them move along. Worms breathe through their skin and so it must be kept moist all the time to enable them to absorb the oxygen from the air.Many people think of a worm as a gross, disgusting creature that is slimy and wriggly, however, despite its strange physical appearance, the worm has many beneficial qualities when it comes to our earths soil.Worms belong to the ‘annelid’ family along with leeches. There are over 3,000 different types of worm, some are so tiny you would not be able to see them under a microscope.The 3 most common worms are:Common EarthwormThe Common Earthworm – this worm is the one you are most likely to see in your garden, in fields, farms and park soils.Brandling WormsBrandling Worms – these are smaller in size than Earthworms and pinkish-red in color. They like living in compost heaps.Flat WormsFlat Worms are not good worms, they are parasitic on other animals and became a pest in the British Isles some years back because they eat earthworms which is not good for our soil.Worm DietWorms are BIG eaters. Worms can consume their own body weight in soil and dead plants in one day. They also excrete equivalent to their own body weight daily in what is known as ‘castings’. (You may have seen castings in your garden, they look like little worms all curled up and look like mud). These castings produce compost and enriches the soil.Worms usually eat while they are passing through the soil and excrete as they go along. The soil they eat passes through two parts of their body called the ‘Crop’ and the ‘Gizzard’. In these parts of the worms body, strong muscles grind the soil, and digestive juices turn the plant matter into a digestible form. In the worms intestines, nutrients the worm needs are absorbed into its bloodstream to keep it strong, healthy and shiny and anything unwanted is passed out in a worm cast.Having worms in your garden is a good sign that you have healthy soil. Some people even keep worms as pets and feed them on scraps of waste so that they will make lots of healthy compost for their gardens so their plants and flowers will grow well.So, these strange little slimy creatures are extremely useful indeed – so remember this when you see them wriggling in your garden and perhaps get them some scraps of waste to eat.The best time to catch these little ‘soil scientists’ is when it is or has been raining as they come to the surface of the garden, probably to get a bit of moisture.More Fascinating Animals to Learn AboutBrandling WormsPotter WaspsPaper WaspEarthwormsCommon WaspsMud Dauber WaspAbout Joanne SpencerI've always been passionate about animals which led me to a career in training and behaviour. As an animal professional I'm committed to improving relationships between people and animals to bring them more happiness.Animal ClassificationKingdom:AnimaliaPhylum:AnnelidaClass:ClitellataOrder:OpisthoporaSuborder:LumbricinaSearchMost Popular AnimalsZebras Aquatic Warbler Atlantic DolphinsTrapdoor SpiderGiraffe MeerkatsTimber WolfPraying MantisHuntsman SpiderVampire Bat Animal Names Glossary Mammals Dog Breeds Farm Animals Best of the BlogFreshwater Marvels – 21 Awesome Animals that Live in LakesWhat are the Fastest Animals in the World?31 Animals with Funny Names and Weird Sounding Names: Humor in NatureTop 15 Deadliest Animals in the World – The Most Fatal Creatures You May EncounterOphiophagy – Examples of animals that eat snakesList of Fascinating Solitary AnimalsCopyright © 2005-2024 · Animal Corner · All Rights Reserved · Affiliate Disclaimer · Privacy Policy · Animals Sitemap . About Us AnimalCorner.org is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com. Amazon and the Amazon logo are trademarks of Amazon.com, Inc. or its affiliates.

Comparative genomics of the major parasitic worms | Nature Genetics

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Comparative genomics of the major parasitic worms

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Published: 05 November 2018

Comparative genomics of the major parasitic worms

International Helminth Genomes Consortium

Nature Genetics

volume 51, pages 163–174 (2019)Cite this article

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Drug discoveryGenome informaticsGenomicsParasitic infectionSequence annotation

AbstractParasitic nematodes (roundworms) and platyhelminths (flatworms) cause debilitating chronic infections of humans and animals, decimate crop production and are a major impediment to socioeconomic development. Here we report a broad comparative study of 81 genomes of parasitic and non-parasitic worms. We have identified gene family births and hundreds of expanded gene families at key nodes in the phylogeny that are relevant to parasitism. Examples include gene families that modulate host immune responses, enable parasite migration though host tissues or allow the parasite to feed. We reveal extensive lineage-specific differences in core metabolism and protein families historically targeted for drug development. From an in silico screen, we have identified and prioritized new potential drug targets and compounds for testing. This comparative genomics resource provides a much-needed boost for the research community to understand and combat parasitic worms.

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MainOver a quarter of humans are infected with parasitic nematodes (roundworms) or platyhelminths (flatworms)1. Although rarely lethal, infections are typically chronic, leading to pain, malnutrition, physical disabilities, delayed development, deformity, social stigma or a burden on family members caring for the afflicted. These diseases encompass many of the most neglected tropical diseases and attract little research investment. Parasitic nematodes and platyhelminths impede economic development through human disability, and billions of dollars of lost production in the livestock2 and crop3 industries.Few drugs are available to treat worm infections. Repeated mass administration of monotherapies is increasing the risk of resistance to human anthelmintics4 and has driven widespread resistance in farm animals5. There are no vaccines for humans, and few for animals6. The commonly used nematicides of plant parasites are environmentally toxic7, and need replacement.The phylum Nematoda is part of the superphylum Ecdysozoa and has five major clades (I to V), four of which contain human-infective parasites and are analyzed here (Fig. 1). The phylum Platyhelminthes is part of the superphylum Lophotrochozoa and the majority of parasite species are cestodes (tapeworms) and trematodes (flukes). Comparing the genomes of parasites from these two phyla may reveal common strategies employed to subvert host defenses and drive disease processes.Fig. 1: Genome-wide phylogeny of 56 nematode, 25 platyhelminth species and 10 outgroup species.a, Maximum-likelihood phylogeny based on a partitioned analysis of a concatenated data matrix of 21,649 amino acid sites from 202 single-copy orthologous proteins present in at least 23 of the species. Values on marked nodes are bootstrap support values; all unmarked nodes were supported by 100 bootstrap replicates; nodes with solid marks were constrained in the analysis. Bar plots show genome sizes and total lengths of different genome features, and normalized gene count (Supplementary Note 1.2) for proteins with inferred functions based on sequence similarity (having an assigned protein name; Methods), or those without (named ‘hypothetical protein’). Species for which we have sequenced genomes are marked with asterisks; 33 ‘tier 1’ genomes are in black. LTR, long terminal repeat; LINE, long interspersed nuclear element. b, Assembly statistics. Blue rows indicate the 33 ‘tier 1’ genomes. Asterisks indicate the species for which we have sequenced genomes.Full size imageWe have combined 36 published genomes8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34 with new assemblies for 31 nematode and 14 platyhelminth species into a large genome comparison of parasitic and non-parasitic worms. We have used these data to identify gene families and processes associated with the major parasitic groups. To accelerate the search for new interventions, we have mined the dataset of more than 1.4 million genes to predict new drug targets and drugs.ResultsGenomic diversity in parasitic nematodes and platyhelminthsWe have produced draft genomes for 45 nematode and platyhelminth species and predicted 0.8 million protein-coding genes, with 9,132–17,274 genes per species (5–95% percentile range; see Methods, Supplementary Tables 1–3, Supplementary Fig. 1 and Supplementary Notes 1.1 and 1.2). We combined these new data with 36 published worm genomes—comprising 31 parasitic8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30 and five free-living18,31,32,33,34 species—and 10 outgroups35,36,37,38,39,40,41,42,43,44 from other animal phyla, into a comparative genomics resource of 91 species (Fig. 1 and Supplementary Tables 2 and 4). There was relatively little variation in gene set completeness (coefficient of variation, c.v. = 0.15) among the nematodes and platyhelminths, despite variation in assembly contiguity (c.v. = 8.5; Fig. 1b and Supplementary Table 2). Nevertheless, findings made using a subset of high-quality assemblies that were designated ‘tier 1’ (Methods and Supplementary Table 4) were corroborated against all species.Genome size varied greatly within each phylum, from 42 to 700 Mb in nematodes, and from 104 to 1,259 Mb in platyhelminths. In a small number of cases, size estimates may have been artifactually inflated by high heterozygosity causing alternative haplotypes to be represented within the assemblies (Supplementary Note 1.3 and Supplementary Table 2a). A more important factor appeared to be repeat content that ranged widely, from 3.8 to 54.5% (5–95% percentile; Supplementary Table 5). A multiple regression model, built to rank the major factors driving genome size variation, identified long terminal repeat transposons, simple repeats, assembly quality, DNA transposable elements, total length of introns and low complexity sequence as being the most important (Supplementary Note 1.3, Methods and Supplementary Table 6). Genome size variation is thus largely due to non-coding elements, as expected45, including repetitive and non-repetitive DNA, suggesting it is either non-adaptive or responding to selection only at the level of overall genome size.Gene family births and expansionsWe inferred gene families from the predicted proteomes of the 91 species using Ensembl Compara46. Of the 1.6 million proteins, 1.4 million were placed into 108,351 families (Supplementary Note 2.1 and Supplementary Data), for which phylogenetic trees were built and orthology and paralogy inferred (Methods, Supplementary Fig. 2 and Supplementary Table 7). Species trees inferred from 202 single-copy gene families that were present in at least 25% of species (Fig. 1), or from presence/absence of gene families, largely agreed with the expected species and clade relationships, except for a couple of known contentious issues (Supplementary Fig. 3, Supplementary Note 2.2 and Methods).The species in our dataset contained significant novelty in gene content. For example, ~28,000 parasitic nematode gene families contained members from two or more parasitic species but were absent from Caenorhabditis elegans and 47% of gene families lacked any functional annotation (Supplementary Note 2.1 and Methods). The latter families tended to be smaller than those with annotations (Supplementary Fig. 4) and, in many cases, correspond to families that are so highly diverged that ancestry cannot be traced, reflecting the huge breadth of unexplored parasite biology.Gene families specific to particular parasite clades are likely to reflect important aspects of parasite biology and possible targets for new antiparasitic interventions. At key nodes in the phylogeny that are relevant to parasitism, we identified 5,881 families with apparent clade-specificity (synapomorphies; Supplementary Note 2.3, Methods and Supplementary Table 8), although our ability to discriminate truly parasite-specific clades was limited by the low number of free-living species. The apparent synapomorphies were either gene family births, or subfamilies that were so diverged from their homologues that they appeared as separate families. Functional annotation of these families was diverse (Fig. 2), but they were frequently associated with sensory perception (such as G-protein coupled receptors; GPCRs), parasite surfaces (platyhelminth tegument or nematode cuticle maintenance proteins) and protein degradation (proteases and protease inhibitors).Fig. 2: Functional annotation of synapomorphic and expanded gene families.a, Rectangular matrices indicate counts of synapomorphic families grouped by 18 functional categories, detailed in the top left corner. Representative functional annotation of a family was inferred if more than 90% of the species present contained at least one gene with a particular domain. The node in the tree to which a panel refers is indicated in each matrix. ‘Other’ indicates families with functional annotation that could not be grouped into one of the 18 categories. ‘None’ indicates families that had no representative functional annotation. b, Expansions of apyrase and PUMA gene families. Families were defined using Compara. For color key and species labels, see Fig. 1. The plot for a family shows the gene count in each species, superimposed on the species tree. A scale bar beside the plot for a family shows the minimum, median and maximum gene count across the species, for that family.Full size imageAmong nematodes, clade IVa (which includes Strongyloides spp.; Fig. 1) showed the highest number of clade-specific families, including a novel ferrochelatase-like family. Most nematodes lack functional ferrochelatases for the last step of haem biosynthesis47, but harbor ferrochelatase-like genes of unknown function, to which the synapomorphic clade IVa family was similar (Supplementary Fig. 5 and Methods). Exceptions are animal parasites in nematode clades III (for example ascarids and filaria) and IV that acquired a functional ferrochelatase via horizontal gene transfer48,49. Within the parasitic platyhelminths, a clade-specific inositol-pentakisphosphate 2-kinase (IP2K) was identified. In some species of Echinococcus tapeworms, IP2K produces inositol hexakisphosphate nanodeposits in the extracellular wall (the laminated layer) that protects larval metacestodes50. The deposits increase the surface area for adsorption of host proteins and may promote interactions with the host51.Paralogous expansions of gene families, particularly those that are large or repeatedly involve related processes, can be evidence of adaptive evolution. We searched among our 10,986 highest-confidence gene families (those containing ≥10 genes from tier 1 species) for those that had expanded in parasite clades. A combination of scoring metrics (Methods) reduced the list to 995 differentially distributed families with a bias in copy number in at least one parasite clade. Twenty-five expansions have previously been observed, including 21 with possible roles in parasitism (Supplementary Fig. 6). A further 43 were placed into major functional classes that historically have been favored as drug targets (kinases, GPCRs, ion channels and proteases52; Supplementary Table 9a).By manually inspecting the distribution of the remaining 927 families across the full species tree, we identified 176 families with striking expansions (Supplementary Table 9a and Supplementary Note 2.4). Thirty two had no functional annotation; for example, family 393312 was highly expanded in clade Va nematodes (Supplementary Fig. 7 and Supplementary Table 9a). Even when families could be functionally annotated to some extent (for example, based on a protein domain), discerning their precise biological role was a challenge. For example, a sulfotransferase family that was expanded in flukes compared with tapeworms includes the Schistosoma mansoni locus that is implicated in resistance to the drug oxamniquine53 but the endogenous substrate for this enzyme is unknown (Supplementary Fig. 7j).Among the newly identified expansions, we focused on those with richer functional information, especially where they were related to similar biological processes. For instance, we identified several expansions of gene families involved in innate immunity of the parasites, as well as their development. These included families implicated in protection against bacterial or fungal infections in nematode clade IVa (bus-4 GT31 galactosyltransferase54, irg-355) and clades Va/Vc (lysozyme56 and the dual oxidase bli-357) (Supplementary Fig. 8a–d). In nematode clade IIIb, a family was expanded that contains orthologs of the Parascaris coiled-coiled protein PUMA, involved in kinetochore biology58 (Fig. 2b). This expansion possibly relates to the evolution of chromatin diminution in this clade, which results in an increased number of chromosomes requiring correct segregation during metaphase59. In nematode clade IVa and in Bursaphelenchus, an expansion of a steroid kinase family (Supplementary Fig. 8e) is suggestive of novelty in steroid-regulated processes in this group, such as the switch between free-living or parasitic stages in Strongyloides60.Infections with parasitic worms are typified by their chronicity and a plausible involvement in host–parasite interactions is a recurring theme for many of the families. Taenia tapeworms and clade V strongylid nematodes (that is Va, Vb and Vc; Fig. 1) contained two expanded families with apyrase domains that may have a role in hydrolyzing ATP (a host danger signal) from damaged host tissue61 (Fig. 2b and Supplementary Fig. 9a). Moreover, many of the strongylid members also contained amine oxidoreductase domains, possibly to reduce production of pro-inflammatory amines, such as histamine, from host tissues62. In platyhelminths, we observed expansions of tetraspanin families that are likely components of the host/pathogen interface. Described examples show tetraspanins being part of extracellular vesicles released by helminths within hosts63; or binding the Fc domain of host antibodies64; or being highly immunogenic65 (Supplementary Fig. 9b,c). In strongylids, especially clade Vc, an expansion of the fatty acid and retinol-binding (FAR) family, implicated in host–parasite interaction of plant- and animal-parasitic nematodes66,67 (Supplementary Fig. 9d), suggests a role in immune modulation. Repertoires of glycosyl transferases have expanded in nematode clades Vc and IV, and tapeworms (Supplementary Fig. 10a–c), and may be used to evade or divert host immunity by modifying parasite surface molecules directly exposed to the immune system68; alternatively, surface glycoproteins may interact with lectin receptors on innate immune cells in an inhibitory manner69. An expanded chondroitin hydrolase family in nematode clade Vc may possibly be used either for larval migration through host connective tissue or to digest host intestinal walls (Supplementary Fig. 9e). Similarly, an expanded GH5 glycosyl hydrolase family contained schistosome members with egg-enriched expression8,70 that may be used for traversing host tissues such as bladder or intestinal walls (Supplementary Fig. 9f). In nematode clade I, we found an expansion of a family with the PAN/Apple domain, which is implicated in attachment of some protozoan parasites to host cells71, and possibly modulates host lectin-based immune activation (Supplementary Fig. 9g).The SCP/TAPS (sperm-coating protein/Tpx/antigen 5/pathogenesis-related protein 1) genes have been associated with parasitism through their abundance, secretion and evidence of their role in immunomodulation72 but are poorly understood. This diverse superfamily appeared as eight expanded Compara families. A more comprehensive phylogenetic analysis of the full repertoire of 3,167 SCP/TAPS sequences (Supplementary Note 2.5, Supplementary Table 10 and Methods) revealed intra- and interspecific expansions and diversification over different evolutionary timescales (Fig. 3 and Supplementary Figs. 11a,b and 12). In particular, the SCP/TAPS superfamily has expanded independently in nematode clade V (18–381 copies in each species) and in clade IVa parasites (39–166 copies) (Fig. 3 and Supplementary Fig. 11c). Dracunculus medinensis (Guinea worm) was unusual in being the only member of clade III to display an expansion (66 copies), which may reflect modulation of the host immune response during the tissue migration phase of its large adult females.Fig. 3: Distribution and phylogeny of SCP/TAPS genes.A maximum-likelihood tree of SCP/TAPS genes. Colors represent different species groups. Homo sapiens GLIPR2 was used to root the tree. Blue dots show high bootstrap values (≥0.8). A clade was collapsed into a triangle if more than half its leaves were genes from the same species group. Nematode clade I had fewer counts, but was collapsed to show its relationship to other clades’ expansions. ‘Strongylid’ refers to clades Va, Vb and Vc.Full size imageProteins historically targeted for drug developmentProteases, GPCRs, ion channels and kinases dominate the list of targets for existing drugs for human diseases52, and are attractive leads for developing new ones. We therefore explored the diversity of these superfamilies across the nematodes and platyhelminths (Supplementary Fig. 13, Supplementary Note 3 and Methods).Proteases and protease inhibitors perform diverse functions in parasites, including immunomodulation, host tissue penetration, modification of the host environment (for example, anticoagulation) and digestion of blood73. M12 astacins have particularly expanded in nematode clade IVa (five families), as previously reported18, but there are two additional expansions in clades Vc and Vb (Fig. 4, Supplementary Fig. 14 and Supplementary Table 11). Because many of these species invade through skin (IVa, Vc; Supplementary Table 12) and migrate through the digestive system and lung (IVa, Vc, Vb; Supplementary Table 13), these expansions are consistent with evidence that astacins are involved in skin penetration and migration through connective tissue74. The cathepsin B C1-cysteine proteases are particularly expanded in species that feed on blood (two expansions in nematode clades Vc and Va30, with highest platyhelminth gene counts in schistosomatids and Fasciola12; Supplementary Fig. 14). Indeed, they are involved in blood digestion in adult nematodes75 and platyhelminths76, but some likely have different roles such as larval development77 and host invasion78.Fig. 4: Abundances of superfamilies historically targeted for drug development.Relative abundance profiles for 84 protease and 31 protease inhibitor families represented in at least 3 of the 81 nematode and platyhelminth species. Thirty-three protease families and 6 protease inhibitor families present in fewer than 3 species were omitted from the visualization. For each species, the gene count in a class was normalized by dividing by the total gene count for that species. Families mentioned in the Results or Supplementary Note text are labeled; complete annotations of all protease families are in Supplementary Table 11.Full size imageDifferent protease inhibitors may modulate activity of parasite proteases or protect parasitic nematodes and platyhelminths from degradation by host proteases, facilitate feeding or manipulate the host response to the parasite79. The I2 (Kunitz-BPTI) trypsin inhibitors are the most abundant protease inhibitors across parasitic nematodes and platyhelminths (Fig. 4). An expansion of the I17 family, which includes secretory leukocyte peptidase inhibitor, was reported previously in Trichuris muris17 but the striking confinement of this expansion to most of the parasites of clade I is now apparent (Fig. 4). We also observed a notable family of α-2-macroglobulin (I39) protease inhibitors that are present in all platyhelminths but expanded in tapeworms (Supplementary Fig. 14). The tapeworm α-2-macroglobulins may be involved in reducing blood clotting at attachment or feeding sites; alternatively, they may modulate the host immune response, since α-2-macroglobulins bind several cytokines and hormones80. Chymotrypsin/elastase inhibitors (family I8) were particularly expanded in clades Vc and IVa (consistent with upregulation of I8 genes in Strongyloides parasitic stages18) and to a lesser extent in clade IIIb (Fig. 4), consistent with evidence that they may protect Ascaris from host proteases81. We also identified protein domain combinations that were specific to either nematodes or platyhelminths (131 and 50 domain combinations, respectively). Many of these involved protease and protease inhibitor domains. In nematodes, several combinations included Kunitz protease inhibitor domains, and in platyhelminths metalloprotease families M18 and M28 were found in novel combinations (Supplementary Table 14, Supplementary Note 3.2 and Methods).Of the 230 gene families annotated as GPCRs (Supplementary Figs. 13 and 15 and Supplementary Note 3.3), only 21 were conserved across phyla. Chemosensory GPCRs, while abundant in nematodes, were not identified in platyhelminths, although they are identifiable in other Lophotrochozoa (such as Mollusca82), suggesting that either the platyhelminths have lost this class or they are very divergent (Supplementary Table 15). GPCR families lacking sequence similarity with known receptors included the platyhelminth-specific rhodopsin-like orphan families (PROFs), which are likely to be class A receptors and peptide responsive, and several other fluke-specific non-PROF GPCR families. The massive radiation of chemoreceptors in C. elegans was unmatched in any other nematode (87% versus ≤48% of GPCRs). All parasitic nematodes possessed chemoreceptors, with the most in clade IVa, including several large families synapomorphic to this clade (Supplementary Fig. 15), perhaps related to their unusual life cycles that alternate between free-living and parasitic forms.Independent expansion and functional divergence has differentiated the nematode and platyhelminth pentameric ligand gated ion channels (Supplementary Fig. 16, Supplementary Table 16 and Supplementary Note 3.4). For example, glutamate signaling arose independently in platyhelminths and nematodes83, and in trematodes the normal role of acetylcholine has been reversed, from activating to inhibitory84. Our analysis suggested the platyhelminth acetylcholine-gated anion channels are most related to the Acr-26/27 group of nematode nicotinic acetylcholine receptors that are the target of the anthelmintics morantel and pyrantel85, rather than to nematode acetylcholine-gated cation channels, targeted by nicotine and levamisole (Supplementary Fig. 17).ABC transporters (Supplementary Table 17 and Supplementary Note 3.5) and kinases (Supplementary Note 3.6 and Supplementary Fig. 18) showed losses and independent expansion within nematodes and platyhelminths. The P-glycoprotein class of transporters, responsible for the transport of environmental toxins and linked with anthelmintic resistance, is expanded relative to vertebrates86, with increased numbers in nematodes (Supplementary Fig. 19).Metabolic reconstructions of nematodes and platyhelminthsIn the context of drug discovery, understanding the metabolic capabilities of parasitic worms may reveal vulnerabilities that can be exploited in target-based screens for new compounds. For each of the 81 nematode and platyhelminth species, metabolism was reconstructed based on high confidence assignment of enzyme classes (Supplementary Table 18a). The nematodes had a greater range of annotated enzymes per species than the platyhelminths (Supplementary Fig. 20a), in part reflecting the paucity of biochemical studies in platyhelminths. Because variation in assembly quality or divergence from model organisms87 could bias enzyme predictions, we identified losses of pathways and differences in pathway coverage across different clades (Supplementary Note 4, Methods, Fig. 5 and Supplementary Fig. 21). Pathways related to almost all metabolic superpathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG)88 showed significantly lower coverage for platyhelminths (versus nematodes) and filaria (versus other nematodes) (Supplementary Fig. 20b).Fig. 5: Metabolic modules and biochemical pathways in platyhelminths and nematodes.a, Topology-based detection of KEGG metabolic modules among tier 1 species (dark green, present; light green, largely present (only one enzyme not found)). Only modules detected to be complete in at least one species are shown. The EC annotations used for this figure included those from pathway hole-filling and those based on Compara families (Supplementary Table 18a, b). b, Biochemical pathways that appear to have been completely or partially lost from certain platyhelminth and nematode clades. PRPP, phosphoribosyl pyrophosphate.Full size imageIn contrast to most animals, nematodes possess the glyoxylate cycle that enables conversion of lipids to carbohydrates, to be used for biosyntheses (for example, during early development) and to avert starvation89. The glyoxylate cycle appears to have been lost independently in the filaria and Trichinella species (Fig. 5a; M00012), both of which are tissue-dwelling obligate parasites. The filaria and Trichinella have also independently lost alanine-glyoxylate transaminase that converts glyoxylate to glycine (Fig. 5b). Glycine can be converted by the glycine cleavage system (GCS) to 5,10-methylenetetrahydrofolate, a useful one-carbon pool for biosyntheses, and two key GCS proteins appear to have been lost independently from filaria and tapeworms, suggesting their GCS is non-functional (Supplementary Table 19e). In addition, filaria have lost the ability to produce and use ketone bodies, a temporary store of acetyl coenzyme A (CoA) under starvation conditions (Supplementary Table 19b). The filaria lost these features after they diverged from D. medinensis, an outgroup to the filaria in clade IIIc that has a major difference in its life cycle, namely, a free-living larval stage (Supplementary Table 12).The absence of multiple initial steps of pyrimidine synthesis was observed in some nematodes, including all filaria (as previously reported23) and tapeworms, suggesting they obtain pyrimidines from Wolbachia endosymbionts or from their hosts, respectively (Supplementary Table 19f). Similarly, all platyhelminths and some nematodes (especially clade IVa and filaria IIIc) appear to lack key enzymes for purine synthesis (Supplementary Table 19g) and rely on salvage instead. However, despite the widespread belief that nematodes cannot synthesize purines90,91, complete or near-complete purine synthesis pathways were found in most members of clades I, IIIb and V. Nematodes are known to be unable to synthesize haem47 but the pathway was found in platyhelminths, including S. mansoni (despite conflicting biochemical data47) (Supplementary Table 19h and Supplementary Table 20i).Genes from the β-oxidation pathway, used to break down lipids as an energy source, were not detected in schistosomes and some cyclophyllidean tapeworms (Hymenolepis, Echinococcus; Fig. 5a, M00087; Supplementary Table 19a). These species live in glucose-rich environments and may have evolved to use glucose and glycogen as principal energy sources. However, biochemical data suggest they do perform β-oxidation92, so they may have highly diverged but functional β-oxidation genes.The lactate dehydrogenase (LDH) pathway is a major source of ATP in anaerobic but glucose-rich environments. Platyhelminths have high numbers of LDH genes, as do blood-feeding Ancylostoma hookworms (Supplementary Fig. 22g). Nematode clades Vc (including Ancylostoma) and IIIb have expansions of α-glucosidases that may break down starch and disaccharides in host food to glucose (Supplementary Fig. 22a). Many nematodes and flatworms use malate dismutation as an alternative pathway for anaerobic ATP production93. The importance of the pathway for clade IIIb nematodes was reflected in expanded families encoding two key pathway enzymes PEPCK and methylmalonyl CoA epimerase, and the intracellular trafficking chaperone for cobalamin (vitamin B-12), a cofactor for the pathway (Supplementary Fig. 22c–e and Supplementary Table 9a). A second cobalamin-related family (CobQ/CbiP) is clade IIIb-specific and appears to have been gained by horizontal gene transfer from bacteria (Supplementary Fig. 23a, Supplementary Note 2.6 and Methods). A glutamate dehydrogenase family expanded in clade IIIb (Supplementary Fig. 22h) is consistent with a GABA (γ-aminobutyric acid) shunt that helps maintain redox balance during malate dismutation. In clade Va, an expansion in the propionate breakdown pathway94 (Supplementary Fig. 22f), suggested degradation of propionate, originating from malate dismutation or fermentation in the host’s stomach95. Clade I nematodes have an acetate/succinate transporter that appeared to have been gained from bacteria (Supplementary Note 2.6 and Methods), and may participate in acetate/succinate uptake or efflux (Supplementary Fig. 23b).Identifying new anthelmintic drug targets and drugsAs an alternative to a purely target-based approach that would require extensive compound screening, we explored drug repurposing possibilities. We developed a pipeline to identify the most promising targets from parasitic nematodes and platyhelminths. These sequences were used in searches of the ChEMBL database that contains curated activity data on defined targets in other species and their associated drugs and compounds (Supplementary Note 5 and Methods). Our pipeline identified compounds that are predicted to interact with the top 15% of highest-scoring worm targets (n = 289). These targets included 17 out of 19 known or likely targets for World Health Organization-listed anthelmintics that are represented in ChEMBL (Supplementary Table 21b). When compounds within a single chemical class were collapsed to one representative, this potential screening set contained 5,046 drug-like compounds, including 817 drugs with phase III or IV approval and 4,229 medicinal chemistry compounds (Supplementary Table 21d). We used a self-organizing map to cluster these compounds based on their molecular fingerprints (Fig. 6). This classification showed that the screening set was significantly more structurally diverse than existing anthelmintic compounds (Supplementary Fig. 24).Fig. 6: Self-organizing map of known anthelmintic compounds and the proposed screening set of 5,046 drug-like compounds.A self-organizing map clustering known anthelmintic compounds (Supplementary Table 21a) and our proposed screening set of 5,046 compounds. The density of red and green shows the number of screening set and known anthelmintic compounds clustered in each cell, respectively. Structures for representative known anthelmintic compounds are shown at the top, and examples from the proposed screening set along the bottom.Full size imageThe 289 targets were further reduced to 40 high-priority targets, based on predicted selectivity, avoidance of side-effects (clade-specific chokepoints or lack of human homologues) and putative vulnerabilities, such as those suggested by gene family expansions in parasite lineages, or belonging to pathways containing known or likely anthelmintic targets (Supplementary Fig. 25). These 40 targets were associated with 720 drug-like compounds comprising 181 phase III/IV drugs and 539 medicinal chemistry compounds. There is independent evidence that some of these have anthelmintic activity. For example, we identified several compounds that potentially target glycogen phosphorylase, which is in the same pathway as a likely anthelmintic target (glycogen phosphorylase phosphatase, likely target of niridazole; Supplementary Fig. 25). These compounds included the phase III drug alvocidib (flavopiridol), which has anthelmintic activity against C. elegans96. Another example is the target cathepsin B, expanded in nematode clade Va (Supplementary Table 9a), for which we identified several compounds including the phase III drug odanacatib, which has been shown to have anthelmintic activity against hookworms97. Existing drugs such as these are attractive candidates for repurposing and fast-track therapy development, while the medicinal chemistry compounds provide a starting point for broader anthelmintic screening.DiscussionThe evolution of parasitism in nematodes and platyhelminths occurred independently, starting from different ancestral gene sets and physiologies. Despite this, common selective pressures of adaptation to host gut, blood or tissue environments, the need to avoid hosts’ immune systems, and the acquisition of complex life cycles to effect transmission, may have driven adaptations in common biological pathways. While previous comparative analyses of parasitic worms have been limited to a small number of species within narrow clades, we have surveyed parasitic worms spanning two phyla, with a focus on those infecting humans and livestock. A large body of draft genome data (both published and unpublished) was utilized but, by focusing on lineage-specific trends rather than individual species-specific differences, our analysis was deliberately conservative. In particular, we have focused on large gene family expansions, supported by the best-quality data and for which functional information was available. Sequencing of further free-living species, better functional characterization, and identification of remote orthologs (particularly for platyhelminths87), will undoubtedly refine the resolution of parasite-specific differences, but our gene family analyses have already revealed expansions and synapomorphies in functional classes of likely importance to parasitism, such as feeding and interaction with hosts. We have used a drug repurposing approach to predict potential new anthelmintic drug targets and drugs/drug-like compounds that we urge the community to explore. Further new potential drug targets, worthy of high-throughput compound screening, may be exposed by the losses of key metabolic pathways and horizontally acquired genes that we find in particular parasite groups. This is an unprecedented dataset of parasitic worm genomes that provides a new type of pan-species reference and a much needed stimulus to the study of parasitic worm biology.URLsSMALT, http://www.sanger.ac.uk/science/tools/smalt-0; RepeatModeler, http://www.repeatmasker.org/RepeatModeler.html; TransposonPSI, http://transposonpsi.sourceforge.net; RepeatMasker, http://www.repeatmasker.org; code for calculating gene family metrics, http://tinyurl.com/comparaFamiliesAnalysis-py; WormBase ParaSite, https://parasite.wormbase.org/.MethodsSample collection and preparationSources of material and sequencing approaches are summarized in Supplementary Table 1.Wellcome Sanger Institute (WSI) data productionThe genomes of 36 species (Supplementary Tables 1 and 2) were sequenced at WSI. The C. elegans N2 was also resequenced at WSI.WSI sequencing and assemblyPCR-free 400–550 bp paired-end Illumina libraries were prepared from <0.1 ng to 5 µg genomic DNA, as described for Strongyloides stercoralis18. Where there was insufficient DNA, adapter-ligated material was subjected to ~8 PCR cycles.We used 1–10 μg gDNA or whole genome amplification DNA to generate 3 kb mate-pair libraries, as described for S. stercoralis18. If there was insufficient gDNA, whole genome amplification was performed using GenomiPhi v2. Each library was run on ≥1 Illumina HiSeq 2000 lane.Short insert paired-end reads were corrected and assembled with SGA v0.9.798 (Supplementary Fig. 26a). This assembly was used to calculate the k-mer distribution for all odd k of 41–81, using GenomeTools v.1.3.799. The k-mer length for which the maximum number of unique k-mers was present was used as the k-mer setting in a second assembly, using Velvet v1.2.03100 with SGA-corrected reads. For species with 3 kb mate-pair data, the Velvet assembly was scaffolded using SSPACE101. Contigs were extended, and gaps closed and shortened, using Gapfiller102 and IMAGE103. Short fragment reads were remapped to the assembly using SMALT (see URLs), and unaligned reads assembled using Velvet100 and this merged with the main assembly. The assembly was re-scaffolded using SSPACE101, and consensus base quality improved with iCORN104. REAPR105 was used to break incorrectly assembled scaffolds/contigs. We carried out manual improvement for Wuchereria bancrofti and D. medinensis using Gap5106 and Illumina read-pairs.WSI assembly quality controlContamination screening. Assemblies were screened for contamination using BLAST107 against vertebrate and invertebrate sequences (see ref. 108). For Anisakis simplex, the assembly contained minor laboratory contamination with S. mansoni, which we removed using BLASTN against S. mansoni.Assembly completeness. CEGMA v2.4109 was used to assess completeness. Consistent sets of CEGMA genes were missing from some phylogenetic groups (Supplementary Table 2); these were discounted from the completeness calculation for those species (‘CEGMA’ in Supplementary Table 2).Effect of repeats. We re-mapped the short-insert library’s reads to the appropriate assembly using SMALT (see URLs; indexing -k13 -s4 and mapping -y 0.9 -x -r 1). For each scaffold of ≥8 kb, median (meds) and mean (ms) per-base read-depth were calculated using BEDTools110, and genome-wide depth (medg) calculated as the median meds (ref. 17). For a ls bp scaffold, the extra sequence that would be gained by ‘uncollapsing’ repeats was estimated as es = (ms − medg) × ls/medg (Supplementary Table 5).WSI gene predictionOur pipeline111 had four steps (Supplementary Fig. 27a). First, repeats were masked. Second, preliminary gene predictions, to use as input for MAKER v2.2.28112 were generated using Augustus 2.5.5113, SNAP 2013-02-16114, GeneMark-ES 2.3a115, genBlastG116 and RATT117. Third, species-specific ESTs and complementary DNAs from INSDC118, and proteins from related species, were aligned to the genome using BLAST107. Last, EST/protein alignments and gene models were used by MAKER to produce a gene set.McDonnell Genome Institute (MGI) data productionThe genomes of six species were sequenced at MGI (Supplementary Tables 1 and 2).MGI sequencing, assembly and quality controlGenome sequencing was carried out on Illumina and 454 instruments (see ref. 119). The workflow for each assembly is in Supplementary Table 1.Three kilobase, 8 kb and fragment 454 reads (or Illumina reads) were subject to adapter removal, quality trimming and length filtering (Supplementary Fig. 26b). Cleaned 454 reads were assembled using Newbler120 before being scaffolded with an in-house tool CIGA, which links contigs based on cDNA evidence. Cleaned Illumina reads were assembled using AllPaths-LG121. The assembly was scaffolded further using an in-house tool Pygap, using Illumina short paired-end sequences; and L_RNA_scaffolder122, using 454 cDNA data.An assisted assembly approach was used for Trichinella nativa, whereby ‘cleaned’ Illumina 3 kb paired-end sequence data were mapped against the T. spiralis genome using bwa123 (Supplementary Fig. 26b), and the T. nativa residues were substituted at aligned positions (see ref. 119).Adaptor sequences and contaminants were identified by comparison to a database of vectors and contaminants, using Megablast124.MGI transcriptome sequencing and gene predictionTranscriptome libraries (Supplementary Table 22) were generated with the Illumina TS stranded protocol, and reads assembled using Trinity125 (see ref. 119).Genes were predicted using MAKER112, based on input gene models from SNAP114, FGENESH (Softberry), Augustus113, and aligned messenger RNA, EST, transcriptome and protein data from the same or related species (Supplementary Fig. 27b; see ref. 119).Blaxter Nematode and Neglected Genomics (BaNG) data productionThe genomes of three species were sequenced by BaNG (Supplementary Tables 1 and 2).Sequencing was performed on Illumina HiSeq 2000 and HiSeq 2500 instruments, using 100 or 125 base, paired-end protocols. Paired-end libraries were generated using the Illumina TruSeq protocol.Sequence data were filtered of contaminating host reads using blobtools126. Cleaned reads were normalized with the khmer software127 using a k-mer of 41, and then assembled with ABySS (v1.3.3)128, with a minimum of three pairs needed to connect contigs during scaffolding (n = 3) (Supplementary Fig. 26c). Assemblies were assessed using blobtools and CEGMA109.Augustus113 was used to predict gene models, trained using annotations from MAKER112. As hints for MAKER, we used Litomosoides sigmodontis 454 RNA sequencing data assembled with MIRA129 and Newbler120, and Onchocerca ochengi Illumina RNA sequencing data130 assembled using Trinity131 (Supplementary Fig. 27c).Defining high-quality ‘tier 1’ speciesA subset of nematode and platyhelminth genomes, termed ‘tier 1’, was selected that had better-quality assemblies and spanned the major clades (Supplementary Table 4). To choose these, species were selected that (1) had contiguous assemblies (usually N50/scaffold-count >5), and complete proteomes (usually CEGMA partial >85%), or (2) that helped to ensure ~50% of the genera in each species group (‘Analysis group’ in Supplementary Table 4) were represented.Analysis of repeat content and genome sizeFor each species, repeat libraries were built using RepeatModeler (see URLs), TransposonPSI (see URLs) and LTRharvest132, and the three libraries merged (see ref. 133). The merged library was used to mask repeats in a species’ genome using RepeatMasker (see URLs; –s).The initial standard regression model and stepwise model fitting used ‘lm’ and ‘step’ in R v3.2.2. The Bayesian mixed-effect model used MCMCglmm134 (v2.24). To create a mixed-effect model, the species tree (see Methods) was transformed into an ultrametric tree using PATHd8135, with a small constant added to short branches to ensure no zero-length branches were reconstructed; and outgroup species were removed.Compara databaseAn in-house Ensembl Compara46 database was constructed containing the 81 platyhelminths and nematodes, and 10 additional outgroups (Supplementary Table 2). All parasitic nematode/platyhelminth species with gene sets available at the time (April 2014) were included.The species tree used to construct the initial version of our database used an edited version of the National Center for Biotechnology Information (NCBI) taxonomy136 with several controversial speciation nodes represented as multifurcations. For our final database, the input species tree was derived by building a tree based on the previous database version, based on one-to-one orthologs present in ≥20 species. To do this, proteins in each ortholog group were aligned using MAFFT v6.857137; alignments trimmed using GBlocks v0.91b138, concatenated and used to build a maximum likelihood tree using a partitioned analysis in RAxML v7.8.6139, using the minimum Akaike’s information criterion (minAIC) model for each ortholog group.The database was queried to identify gene families, orthologs and paralogs.Species tree and tree based on gene family presenceWe identified 202 gene families present in ≥25% of the 91 species (81 helminths and 10 outgroups) in our Compara database (Methods) and always single-copy. For each family, amino acid sequences were aligned using MAFFT v7.205137 (-auto). Each alignment was trimmed using GBlocks v0.91b138 (-b4 = 4 -b3 = 4 -b5 = h), and its likelihood calculated on a maximum-parsimony guide tree for all relatively simple (single-matrix) amino acid substitution models in RAxML v8.0.24139, and the minAIC model identified. Alignments were concatenated and a maximum-likelihood tree built, under a partitioned model in which sites from a gene were assigned the minAIC model for that gene, with a discrete gamma distribution of rates across sites. Relationships within outgroup lineages were constrained to match the standard view of metazoan relationships (for example, Dunn et al.140). The final tree was the highest likelihood one from five search replicates with different random number seeds. One hundred bootstrap resampling replicates were performed, each based on a single rapid search.We also constructed a maximum-likelihood phylogeny based on gene family presence/absence for families not shared by all 81 nematode/platyhelminth species, using RAxML v8.2.8139, with a two-state model and the Lewis method to correct for absence of constant-state observations.Functional annotationInterProScan141 v5.0.7 was used to identify conserved domains from all predicted proteins. A name was assigned to each predicted protein based on curated information in UniProt142 for orthologs identified from our Compara database (Methods), or based on InterPro143 domains (see ref. 144). Gene ontology (GO) terms were assigned by transferring GO terms from orthologs144, and using InterProScan.Signal peptides and transmembrane domains were predicted using Phobius145 v1.01 and SecretomeP146 v1.0. A protein predicted by Phobius to have a transmembrane domain was categorized as ‘membrane-bound’, and non-membrane-bound proteins as ‘classically secreted’ if Phobius predicted a signal peptide within 70 amino acids of their start. Remaining proteins in which SecretomeP predicted a signal peptide were classified as ‘non-classically secreted’ (Supplementary Table 7).Pairwise combinations of Pfam domains were identified in proteins of the 81 nematodes and platyhelminths. After excluding those present in complete genomes of other phyla in UniProt (June 2016), we classified a combination as ‘nematode-specific’ (or ‘flatworm-specific’) if it was present in >30% of nematodes (platyhelminths) and no platyhelminths (nematodes) (Supplementary Table 14).Synapomorphic gene familiesFamilies in our Compara database (Methods) were analyzed using KinFin v0.8.3147, by providing InterPro IDs (Methods) and a species tree that had clades III, IV and V as a polytomy (Fig. 2). Synapomorphic families were identified at 25 nodes of interest (Supplementary Table 8), by using Dollo parsimony and requiring a family must contain genes from ≥1 descendant species from each child node of the node of interest, and must not contain other species. Families were filtered to retain those that (1) contained ≥90% of descendant species of the node of interest, and (2) in which >90% of species contained ≥1 gene with a particular InterPro domain.Candidate lateral gene transfersFerrochelatase families in our Compara database (Methods) were extracted by screening for a Ferrochelatase (IPR001015) domain. Additional ferrochelatases were retrieved from NCBI for 17 bacterial taxa (Supplementary Table 8c). Sequences were aligned using MAFFT v7.267 (E-INS-i algorithm)137 and the alignment trimmed using trimAl v1.4148. Phylogenetic analysis was carried out using RAxML139 under the PROTGAMMAGTR model, and 20 alternative runs on distinct starting trees. Non-parametric bootstrap analysis was carried out for 100 replicates.For cobyric acid synthase and acetate/succinate transporter, the top BLAST hits from GenBank, and representative sequences from other taxonomic groups, were aligned with MAFFT v7.205137 (-auto), and alignments trimmed with trimal v1.4148. Phylogenetic analyses were performed using RAxML v8.2.8139 under the model that minimized the AIC (LG4X for cobyric acid synthase, LG4M for acetate transporter), based on 5 random-addition-sequence replicates, and 100 non-parametric bootstrap replicates.Gene family expansionsWe used three metrics to identify families in our Compara database (Methods) that varied greatly in gene count across species (see ref. 149). To control for fragmented assemblies, we used summed protein length per species (in a family) as a proxy for gene count in these metrics:1. Coefficient of variation:$$c.v. = s{\mathrm{/}}\bar x$$where s is the standard deviation in summed protein length per species, and $\bar x$ its mean.2. Maximum Z-score:$$Z_{{\mathrm{max}}}={\mathrm{max}}\,c \in T\left( {\frac{{\bar x_{i,i \in c}-\bar x}}{{s_{i,i \notin c}}}} \right)$$where T is the set of non-overlapping species groups (‘Analysis group’ in Supplementary Table 4), c a group in T, index i refers to a particular species, $\bar x_{i, i \in c}$ the mean of the summed protein length (per species) in c, and $s_{i, i \notin c}$ the standard deviation in summed protein length per species in species outside c.3. Maximum enrichment coefficient:$$E_{{\mathrm{max}}}{\mathrm{ = max}}\,c \in T\left( {\frac{{\bar x_{i,i \in c}}}{{\bar x_{i,i \notin c}}}} \right)$$To increase reliability, these metrics were calculated by only considering tier 1 species (those with high-quality assemblies; Methods). Our code for calculating metrics is available (see URLs).SCP/TAPSSCP/TAPS genes were identified as having Pfam PF00188, or being in a SCP/TAPS family in our Compara database (Methods). Those between 146 aa (shortest C. elegans SCP/TAPS) and 1,000 aa were included in the phylogenetic analysis (Supplementary Table 10). Clusters were detected among sequences from a species group (‘analysis group’ in Supplementary Table 4) using USEARCH150 (UCLUST, aa identity cut-off = 0.70), and a consensus sequence generated for each cluster. The consensus sequences were aligned using MAFFT137 (v7.271, –localpair –maxiterate 2 –retree 1 –bl 45); the alignment trimmed with trimAl148 (-gt 0.006); and a maximum likelihood tree built using FastTreeMP151 (v2.1.7 SSE3, -wag -gamma).Proteins historically targeted for drug developmentEach nematode/platyhelminth proteome was searched against candidate proteases using MEROPS batch-BLAST152 (E < 0.001), and PfamScan153 was used to identify additional homologues in some species (Supplementary Table 11).Putative GPCRs, identified from the literature and GO:0004930 annotations in WormBase154, were used to identify families in our Compara database (Methods). For each family, HHSuite155 was used to search Uniprot, SCOPUS, Pfam, and PDB; 200 families hitting ≥2 databases were deemed actual GPCR families (see ref. 156). Additional families were identified from synapomorphies (Methods) and curation, giving 230 GPCR families (Supplementary Table 15).To build a phylogenetic tree of ion channels, known genes from C. elegans157, Brugia malayi158, Haemonchus contortus159, Oesophagostomum dentatum159 and S. mansoni84 were gathered, and their homologues in Compara families in WormBase ParaSite160. Genes with <3 or >8 transmembrane domains (predicted by HMMTOP161) were discarded. Genes were aligned with MAFFT137, and the alignment trimmed with trimAl148. The phylogeny was inferred with MrBayes3.2162. Posterior probabilities were calculated from eight reversible jump Markov chain Monte Carlo chains over 20,000,000 generations.Kinase models were taken from Kinomer163, and thresholds optimized to detect known C. elegans kinases (see ref. 164). The final thresholds were used to filter HMMER search results (against Kinomer) for nematode and platyhelminth species (Supplementary Table 23).C. elegans ABC transporter and cys-loop receptor subunit genes were collated from WormBase154, to which we added H. contortus acr-26 and acr-27 (absent from C. elegans85). Homologs in nematodes and platyhelminths were identified using BLASTP (Supplementary Tables 16 and 17).GO and InterPro/Pfam annotation enrichmentCounts of proteins annotated with each GO term (or InterPro/Pfam domain) per species were normalized by dividing by the total GO annotations in a particular species. To test for enrichment of a particular GO term in a species group (‘analysis group’ in Supplementary Table 4), we used a Mann-Whitney U test to compare normalized counts in that species group, to those in all other species (Supplementary Table 24).MetabolismEC (Enzyme Commission number) predictions for nematodes and platyhelminths were derived by combining DETECT v2.0165, PRIAM166, KAAS167 and BRENDA168 (see ref. 169, Supplementary Fig. 28 and Supplementary Table 18), and supplemented for the 33 tier 1 species (Methods) by pathway hole-filling using Pathway Tools170 (v18.5). Comparisons of all 81 species (Supplementary Fig. 20a and Supplementary Table 20) did not include ECs from hole-filling. Lower confidence ECs were inferred using families from our Compara database (Methods). Auxotrophies were predicted using Pathway Tools and BioCyc171. To predict carbohydrate-active enzymes, HMMER3 was used to search dbCAN172 (Supplementary Table 25).Pathway coverage was the fraction of ECs in a reference pathway that were annotated in a species (see ref. 173). We included pathways for which KEGG had a reference pathway for a nematode/platyhelminth (Supplementary Table 18e). Presence of KEGG modules was predicted using modDFS174, and species clustered based on module presence using Ward-linkage, based on Jaccard similarity index175.Chokepoint enzymes were predicted following Taylor et al.176, using subnetworks of KEGG networks formed by just the enzymes (ECs) we had annotated in each particular species.Potential anthelmintic drug targets and drugsPotential drug targetsNematode and platyhelminth proteins from tier 1 species (with high-quality assemblies; Methods) were searched against single-protein targets from ChEMBL v21177 using BLASTP (E ≤ 1 × 10−10). After collapsing by gene family, 1,925 worm genes remained.To assign a ‘target score’ to each worm gene, the main factors considered were similarity to known drug targets; lack of human homologues; and whether C. elegans/Drosophila melanogaster homologues had lethal phenotypes (see ref. 178).Potential new anthelmintic drugsChEMBL v21177 was used to identify 827,889 compounds with activities against ChEMBL targets to which worm proteins had BLAST matches. To calculate ‘compound scores’, we prioritized compounds in high clinical development phases, oral/topical administration, crystal structures, properties consistent with oral drugs and lacking toxicity (see ref. 178).Our top 15% (249) of highest-scoring worm targets had 292,499 compounds. These were filtered by selecting compounds that (1) co-appeared in a PDBe179 (Protein Data Bank in Europe) structure with the ChEMBL target; or (2) had median pChEMBL > 5; leaving 131,452 ‘top drug candidates’.A ‘diverse screening set’The 131,452 candidates were placed into 27,944 chemical classes, based on ECFP4 fingerprints (see ref. 178). They were filtered by (1) discarding medicinal chemistry compounds that did not co-appear in a PDBe structure with the ChEMBL target, or have median pCHEMBL > 7; (2) checking availability for purchase in ZINC 15180; and (3) for each worm target, taking the highest-scoring compound from each class; this gave 5,046 compounds.Self-organizing mapWe constructed a self-organizing map of our diverse screening set plus known anthelmintic compounds (Supplementary Table 21a; see ref. 178), using Kohonen v3.02181 in R v3.3.0, using a 20 × 20 cell hexagonal, non-toroidal grid. The self-organizing map was trained for 4,000 steps, where training optimized Tanimoto distances between ECFP4 fingerprints.Reporting SummaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

Sequence data have been deposited in the European Nucleotide Archive (ENA). Assemblies and annotation are available at WormBase and WormBase-ParaSite (https://parasite.wormbase.org/). All have been submitted to GenBank under the BioProject IDs listed in Supplementary Table 1.

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Download referencesAcknowledgementsWe thank: the WSI DNA Pipeline teams, particularly C. Griffiths, N. Park, L. Shirley, M. Quail, D. Willey and M. Jones; WSI Pathogen Informatics, especially J. Keane; T.D. Otto for bioinformatics advice; MGI faculty and staff, especially M. Schmidt, C. Fronick, M. Cordes, T. Miner, R. Fulton and other members of the Project Management, Resource Bank, Library Construction and Data Production teams; D. Hughes, M. Muffato at the European Bioinformatics Institute, for support running Maker and Ensembl Compara; and K. Gharbi and his staff at Edinburgh Genomics for support; V. Gelmedin, R. Fujiwara, F. Brazil, the late Purnomo (University of Indonesia, Jakarta), J. Ahringer, E.S. Hernández Redondo, F. Jackson, E. Redman, A. Ito, J. Saldaña, M. Fernanda Dominguez, W. Gause, M. Badets, I.E. Samonte, A. Koehler, M. Nielsen, L.S. Mansfield, T. Sonstegard for sample preparation. The work was supported by funding from Wellcome (206194), Medical Research Council (MR/L001020/1), and Biotechnology and Biological Sciences Research Council (BB/K020048/1) to M.B., and US National Institutes of Health (NIH)–National Human Genome Research Institute grant number U54HG003079, National Institute of Allergy and Infectious Diseases grant number AI081803, and National Institute of General Medical Sciences grant number GM097435 to M.M. Genome sequencing and analysis in Edinburgh was supported by EU SICA award 242131 ‘Enhanced Protective Immunity Against Filariasis’ (EPIAF) (to D.W.T.). S.A. Babayan. was also supported by the EU project EPIAF. G. Koutsovoulos was supported by a BBSRC/Edinburgh University PhD scholarship and D.R.L. by a joint Edinburgh University/James Hutton Institute PhD scholarship. J.E.A. was supported by MRC grant MR/K01207X/1. J.P. and S.S. were supported by the National Institutes of Health/NIAID (R21 AI126466) and the Natural Sciences and Engineering Research Council of Canada (RGPIN-2014-06664). Additional computing resources were provided through Compute Canada by the University of Toronto SciNet HPC Consortium. R.M.M. was supported by a Wellcome Investigator Award (ref. 106122) and Wellcome core funding to the Wellcome Centre for Molecular Parasitology (Ref 104111). J.B.M. was supported by the Scottish Government RESAS. T.S. was supported by the Institute of Parasitology, BC CAS (RVO: 60077344). A.R.L. and P.M. were supported by a Strategic Award from Wellcome (WT104104/Z/14/Z) and the Member States of the European Molecular Biology Laboratory (EMBL). Schistosome samples were obtained from the SCAN repository (Wellcome grant 104958).Author informationAuthor notesA list of members and affiliations appears at the end of the paper.Authors and AffiliationsWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UKAvril Coghlan, James A. Cotton, Nancy Holroyd, Adam J. Reid, Diogo M. Ribeiro, Eleanor Stanley, Helen Beasley, Hayley M. Bennett, Stephen R. Doyle, Daria Gordon, Bhavana Harsha, Thomas Huckvale, Jane Lomax, Gabriel Rinaldi, Myriam Shafie, Alan Tracey & Matthew BerrimanMcDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USARahul Tyagi, Bruce A. Rosa, Kymberlie Hallsworth-Pepin, John Martin, Philip Ozersky, Xu Zhang & Makedonka MitrevaBiodiversity Research Center, Academia Sinica, Taipei, TaiwanIsheng Jason Tsai, Huei-Mien Ke, Tzu-Hao Kuo & Tracy J. LeeDepartment of Life Science, National Taiwan Normal University, Taipei, TaiwanIsheng Jason Tsai & Tracy J. LeeBiodiversity Program, Academia Sinica and National Taiwan Normal University, Taipei, TaiwanIsheng Jason Tsai & Tracy J. LeeBaNG, Institute of Evolutionary Biology and Centre for Immunity, Infection and Evolution, University of Edinburgh, Edinburgh, UKDominik R. Laetsch, Gaganjot Kaur, Georgios Koutsovoulos, Sujai Kumar & Mark L. BlaxterInstitute of Parasitology, McGill University, Montreal, Quebec, CanadaRobin N. BeechDepartment of Biomedical Sciences, Iowa State University, Ames, IA, USATim A. Day & Nicolas J. WheelerInstitute for Global Food Security, Queen’s University Belfast, Belfast, UKTim A. DayWellcome Centre for Molecular Parasitology, University of Glasgow, Glasgow, UKRick M. MaizelsEuropean Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UKPrudence Mutowo, Neil D. Rawlings, Kevin L. Howe & Andrew R. LeachProgram in Molecular Medicine, The Hospital for Sick Children, Toronto, Ontario, CanadaJohn Parkinson & Lakshmipuram Seshadri SwapnaDepartments of Biochemistry and Molecular Genetics, University of Toronto, Toronto, Ontario, CanadaJohn Parkinson & Lakshmipuram Seshadri SwapnaAix-Marseille Université, Marseille, FranceDiogo M. RibeiroSchool of Biological Sciences, University of Edinburgh, Edinburgh, UKDavid W. TaylorDepartment of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USANicolas J. Wheeler & Mostafa ZamanianNatural History Museum, London, UKFiona Allan, Aidan Emery, Peter D. Olson & David RollinsonFaculty of Biology, Medicine and Health, University of Manchester, Manchester, UKJudith E. AllenDepartment of Physiology, Showa University, Tokyo, JapanKazuhito AsanoInstitute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, UKSimon A. Babayan & Eileen DevaneyInstitute of Immunology and Infection Research, University of Edinburgh, Edinburgh, UKSimon A. Babayan & Yvonne HarcusInstitut de Recherche Agricole pour le Développement, Ngaoundéré, CameroonGermanus Bah & Vincent N. TanyaHopkirk Research Institute, AgResearch Ltd, Palmerston North, New ZealandStewart A. BissetFacultad de Ciencias, Universidad de la República, Montevideo, UruguayEstela CastilloMuseum of Southwestern Biology, University of New Mexico, Albuquerque, NM, USAJoseph CookInstitute of Infection and Immunity, St. George’s, University of London, London, UKPhilip J. CooperFacultad de Ciencias Medicas, de la Salud y la Vida, Universidad Internacional del Ecuador, Quito, EcuadorPhilip J. CooperDepartment of Parasitology, University of Granada, Granada, SpainTeresa Cruz-Bustos, Antonio Osuna & Mercedes Gomez SamblasDepartamento de Parasitología, Universidad Complutense de Madrid, Madrid, SpainCarmen CuéllarDivision of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, GA, USAMark L. EberhardThe Carter Center, Atlanta, GA, USAMark L. EberhardDepartment of Parasitology, Chungbuk National University School of Medicine, Cheongju, KoreaKeeseon S. EomDepartment of Comparative Biology and Experimental Medicine, University of Calgary, Calgary, Alberta, CanadaJohn S. GilleardCentre for Cardiovascular Science, Queen’s Medical Research Institute, Edinburgh, UKYvonne HarcusDepartment of Microbiology, Immunology, and Tropical Medicine, The George Washington University, Washington, DC, USAJohn M. HawdonUnited States Department of Agriculture, Beltsville Agricultural Research Centre, Beltsville, MD, USADolores E. Hill, Joseph F. Urban & Dante ZarlengaDepartment of Infection Biology, University of Liverpool, Liverpool, UKJane Hodgkinson & Benjamin MakepeaceDepartment of Parasitology, Charles University, Prague, Czech RepublicPetr HorákDepartment of Evolutionary Ecology, Max Planck Institute for Evolutionary Biology, Ploen, GermanyMartin KalbeThe Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, CanadaGaganjot KaurFaculty of Medicine, University of Miyazaki, Miyazaki, JapanTaisei KikuchiINRA PACA Site de Sophia-Antipolis, Sophia Antipolis, FranceGeorgios KoutsovoulosMoredun Research Institute, Edinburgh, UKJacqueline B. MatthewsBiomedical Research Institute of Salamanca-Research Centre for Tropical Diseases at the University of Salamanca (IBSAL-CIETUS), University of Salamanca, Salamanca, SpainAntonio MuroNextMove Software Ltd, Cambridge, UKNoel Michael O’BoyleDepartment of Parasitology, University of Indonesia, Jakarta, IndonesiaFelix PartonoInstitute for Medical Microbiology, Immunology and Parasitology, University of Bonn Medical Center, Bonn, GermanyKenneth PfarrInstitute of Tropical Diseases and Public Health of the Canary Islands, Universidad de La Laguna, Tenerife, SpainPilar ForondaJoint Faculty of Veterinary Medicine, Yamaguchi University, Yamaguchi, JapanHiroshi SatoInstitute of Parasitology, University of Zurich, Zurich, SwitzerlandManuela SchnyderBiology Centre CAS, Institute of Parasitology, Branišovská, Czech RepublicTomáš ScholzDepartamento de Parasitología, Universidad de Valencia, Valencia, SpainRafael ToledoDepartment of Parasitology, Chang Gung University, Taoyuan, TaiwanLian-Chen WangDepartment of Internal Medicine, Washington University School of Medicine, St. Louis, MO, USAMakedonka MitrevaConsortiaInternational Helminth Genomes ConsortiumAvril Coghlan, Rahul Tyagi, James A. Cotton, Nancy Holroyd, Bruce A. Rosa, Isheng Jason Tsai, Dominik R. Laetsch, Robin N. Beech, Tim A. Day, Kymberlie Hallsworth-Pepin, Huei-Mien Ke, Tzu-Hao Kuo, Tracy J. Lee, John Martin, Rick M. Maizels, Prudence Mutowo, Philip Ozersky, John Parkinson, Adam J. Reid, Neil D. Rawlings, Diogo M. Ribeiro, Lakshmipuram Seshadri Swapna, Eleanor Stanley, David W. Taylor, Nicolas J. Wheeler, Mostafa Zamanian, Xu Zhang, Fiona Allan, Judith E. Allen, Kazuhito Asano, Simon A. Babayan, Germanus Bah, Helen Beasley, Hayley M. Bennett, Stewart A. Bisset, Estela Castillo, Joseph Cook, Philip J. Cooper, Teresa Cruz-Bustos, Carmen Cuéllar, Eileen Devaney, Stephen R. Doyle, Mark L. Eberhard, Aidan Emery, Keeseon S. Eom, John S. Gilleard, Daria Gordon, Yvonne Harcus, Bhavana Harsha, John M. Hawdon, Dolores E. Hill, Jane Hodgkinson, Petr Horák, Kevin L. Howe, Thomas Huckvale, Martin Kalbe, Gaganjot Kaur, Taisei Kikuchi, Georgios Koutsovoulos, Sujai Kumar, Andrew R. Leach, Jane Lomax, Benjamin Makepeace, Jacqueline B. Matthews, Antonio Muro, Noel Michael O’Boyle, Peter D. Olson, Antonio Osuna, Felix Partono, Kenneth Pfarr, Gabriel Rinaldi, Pilar Foronda, David Rollinson, Mercedes Gomez Samblas, Hiroshi Sato, Manuela Schnyder, Tomáš Scholz, Myriam Shafie, Vincent N. Tanya, Rafael Toledo, Alan Tracey, Joseph F. Urban, Lian-Chen Wang, Dante Zarlenga, Mark L. Blaxter, Makedonka Mitreva & Matthew BerrimanContributionsProject leadership and conception: M.B. and M.M. Writing the manuscript: M.B., M.L.B., A.C., J.A.C., N.H., D.R.L., R.M.M., M.M. and R.Tyagi. Project planning or management: M.B., M.L.B., J.A.C., N.H., M.M. and A.M. Genome sequencing: H.B., K.H.P., N.H., J.M., P.O., D.W.T., A.T. and Z.X. Preparation or provision of parasite material or nucleic acid: F.A., J.E.A., K.A., S.A.Bisset, G.B., H.M.B., S.A.Babayan, T.C.B., E.C., J.C., P.J.C., C.C., E.D., M.L.E., A.E., K.S.E., P.F., J.S.G., Y.H., J.M.H., D.E.H., J.H., P.H., T.H., M.K., T.K., R.M.M., B.M., J.B.M., P.D.O., A.O., F.P., K.P., D.R., M.G.S., H.S., M.Schnyder, T.S., V.N.T., D.W.T., R.Toledo, J.F.U., L.C.W. and D.Z. Production bioinformatics: A.C., J.A.C., D.G., B.H., J.L., P.O., D.M.R., B.A.R., E.S. and A.T. Annotation of genomes: A.C., B.H., K.L.H., G.Kaur, G.Koutsovoulos, S.K., D.R.L., J.M., P.O., K.H.P., B.A.R., E.S. and Z.X. Assembly of genomes at WSI: I.J.T. Assembly of genomes at MGI: J.M., P.O., K.H.P. and Z.X. Assembly of genomes at BaNG: G.Kaur, G.Koutsovoulos, S.K. and D.R.L. Assembly and annotation of mitochondrial genomes: T.K. Analysis of variation in genome size: A.C. and J.A.C. Analysis of GO terms and domains: A.C., D.R.L., J.L., A.J.R., B.A.R. and M.Shafie. Development of visualisation software and production of the species tree: J.A.C. Analysis of synapomorphies: M.L.B. and D.R.L. Analysis of expanded gene families: M.B., A.C., J.A.C., S.R.D., N.H., A.J.R., D.M.R., G.R., B.A.R. and R.Tyagi. Analysis of hypothetical genes: A.C. and A.J.R. Analysis of SCP/TAPS: H.M.K., T.H.K., T.J.L. and I.J.T. Analysis of proteases: N.D.R. Analysis of GPCRs: T.A.D., N.J.W. and M.Z. Analysis of ion channels: R.N.B. and M.Z. Analysis of kinases: J.M. and B.A.R. Analysis of metabolic pathways: A.C., J.A.C., T.K., J.P., S.S. and R.Tyagi. Chemogenomics analyses: A.C., J.A.C., A.R.L., J.L., P.M. and N.M.O’B.Corresponding authorsCorrespondence to

Avril Coghlan, Makedonka Mitreva or Matthew Berriman.Ethics declarations

Competing interests

The authors declare no competing interests.

Additional informationPublisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary informationSupplementary Text and FiguresSupplementary Figures 1–32 and Supplementary NoteReporting SummarySupplementary Table 1Sample and sequencing informationSupplementary Table 2Assembly statisticsSupplementary Table 3Gene set propertiesSupplementary Table 4Rationale, classification and taxonomy of species analyzedSupplementary Table 5Repeat contentSupplementary Table 6Results of Bayesian mixed effect model for genome sizeSupplementary Table 7GO annotation, predicted secretion data and transmembrane domains, and per-species gene counts for Compara gene familiesSupplementary Table 8Synapomorphic gene familiesSupplementary Table 9Gene families in expanded family analysisSupplementary Table 10SCP/TAPS genesSupplementary Table 11Protease and protease inhibitor genesSupplementary Table 12Species life history traitsSupplementary Table 13Parasite tissue tropism in definitive hostSupplementary Table 14Nematode-specific and platyhelminth-specific domain combinationsSupplementary Table 15GPCR annotationSupplementary Table 16Ligand gated ion channel genesSupplementary Table 17ABC transporter predictionsSupplementary Table 18EC annotations, KEGG metabolic module completion, KEGG pathway conservation, auxotrophy prediction, and metabolic chokepointsSupplementary Table 19Annotation for metabolic pathways of particular interestSupplementary Table 20KEGG pathways with the most unique ECs (present in flatworms but absent in nematodes, or vice versa)Supplementary Table 21Known anthelmintic compounds, known or likely anthelmintic drug targets, and potential new anthelmintic drug targets and compoundsSupplementary Table 22RNA-seq used for gene-finding quality controlSupplementary Table 23Kinase genesSupplementary Table 24InterPro, Pfam and GO enrichment in different species groupsSupplementary Table 25CAZYME predictions for the 81 nematodes and platyhelminthsSupplementary DataCompara gene families and the genes that they contain.Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissionsAbout this articleCite this articleInternational Helminth Genomes Consortium. Comparative genomics of the major parasitic worms.

Nat Genet 51, 163–174 (2019). https://doi.org/10.1038/s41588-018-0262-1Download citationReceived: 17 May 2018Accepted: 24 September 2018Published: 05 November 2018Issue Date: January 2019DOI: https://doi.org/10.1038/s41588-018-0262-1Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard

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WORM中文(简体)翻译：剑桥词典

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worm 在英语-中文（简体）词典中的翻译

wormnoun uk

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/wɜːm/ us

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/wɝːm/

worm noun

(CREATURE)

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B2 [ C ] a small animal with a long, narrow, soft body without arms, legs, or bones

蠕虫

The kiwi bird eats worms, other invertebrates, and berries.

奇翼鸟以蠕虫、其他无脊椎动物和浆果为食。

[ C ] the young of particular types of insect

（某些昆虫的）幼虫

It's distressing enough to find a worm in your apple but finding half of one is worse.

在苹果里发现一条虫子已经够让人厌恶了，如果发现半条就更糟了。

也请参见

woodworm

[ C ] a type of worm that lives in an animal's intestine, feeding on the food there, or on an animal's body, feeding off its blood

寄生虫

a parasitic worm

寄生虫

The vet says our dog has worms.

兽医说我们的狗体内有寄生虫。

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tapeworm

[ S ] informal old-fashioned an unpleasant person who does not deserve respect

惹人讨厌的人；懦夫

Don't be such a worm. You don't have to lie to me.

别这么懦弱，你不必向我撒谎的。

更多范例减少例句A grub looks like a short fat worm.We had to dissect a worm and a frog in our biology practical today.The child touched the worm with a twig.A large worm wriggled in the freshly dug earth.

worm noun

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[ C ] a harmful computer program that can copy itself and spread across a number of connected computers

计算机蠕虫病毒

The operating system left servers susceptible to viruses and worms.

该操作系统使服务器容易受到病毒和蠕虫的攻击。

The software promises to protect you from the most pervasive worm attacks.

该软件承诺保护您免受无处不在的蠕虫病毒的攻击。

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the worm turns

wormverb uk

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/wɜːm/ us

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worm verb

(MOVE)

[ I or T, + prep ] to succeed in moving along in a difficult or crowded situation, by moving your body slowly and carefully

挤过，钻过

Because he was so small, he could worm (his way) through the crowd.

他身形瘦小，所以可以挤过人群。

She wormed herself under the fence.

她从栅栏下面爬了过来。

worm verb

(ANIMAL)

[ T ] to give an animal, especially a pet dog or cat, medicine to kill any worms that might be living inside it

（尤指为狗、猫等宠物）除肠虫

Has your dog been wormed?

你的狗除过肠虫吗？

短语动词

worm yourself/your way into something

worm something out of someone

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蠕蟲, （某些昆蟲的）幼蟲, 寄生蟲…

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gusano, larva, helminto…

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（ミミズなどの細長くて脚のない）虫, ミミズ, イモムシ…

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kurt, solucan, ağır ağır dikkatle ilerlemek…

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ver [masculine] (de terre), ver [masculine], ver (de terre)…

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cuc…

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worm, (zich) wurmen, ontfutselen…

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orm, -orm, møve sig…

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mark [masculine], meitemark [masculine], larve [masculine]…

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черв'як, хробак, заповзати…

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دودة…

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หนอน, ทำช้า ๆ, รู้ความจริง…

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con giun, luồn vào, moi tin…

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robak, dżdżownica, przecisnąć/wcisnąć się…

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벌레…

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verme, (farsi strada), estorcere…

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the early bird catches the worm idiom

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veggie burger

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a type of food similar to a hamburger but made without meat, by pressing together small pieces of vegetables, seeds, etc. into a flat, round shape

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What are worms? - The Australian Museum

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HomepageDiscover & LearnObject and species identificationCommon enquiriesWhat are worms?

What are worms?

Updated

19/08/22

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2 minutes

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Predatory polychaete from the Belgian coastal waters

Image: Hans Hillewaert

creative commons

Worms live in many different, often hostile, environments. From your backyard garden to deep-sea hydrothermal vents spewing out poisonous chemicals and the icy cold waters of the Antarctic. Worms are also extremely varied in size, from tiny worms that need a microscope to see up to incredibly long worms half the length of an Olympic swimming pool!How much do we actually know about these squishy creatures? What kind of animal is a worm?What kind of animal is a worm?This is a commonly asked question, with worms having the similarly icky-factor as insects it’s easy to understand why. Both worms and insects are classified under the Kingdom Animalia. The animal kingdom is split into two groups: vertebrate, animals with a backbone, and invertebrate, animals without a backbone. Both worms and insects are invertebrates.

Are worms insects?No, worms are not insects. Unlike worms, insects have exoskeletons that act like a skeletal support structure and protects the insects’ soft internal organs. Worm skin is usually made up of collagen and does not shed (called moulting) in comparison to insects’ exoskeleton, which is made up of chitin and is shed to allow for growth.It can be especially confusing because many insects have picked up worm-related names, for example, tequila worm, silk worm, glow worm and inchworms are all actually insect larvae (early life stages) and not actually worms.

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What are worms?Many very different and unrelated types of animals that are generally long and soft are called worms. Of these, three common types of worms are: the flatworm, the roundworm, and the segmented worm. Flatworms are soft, unsegmented invertebrates. They do not have specialised respiratory systems so it restricts them to this flat shape to allow them to breathe through their skin. Flatworms have only one body cavity through which they eat and excrete waste. Roundworms, on the other hand, are very smooth and tubular, and have openings on both ends of their bodies, to eat from one end and excrete waste from another. Segmented worms have body segments and many have parapodia, which are leg-like protrusions that help the worms move around. The best known type of segmented worm is the earthworm.

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Predatory polychaete from the Belgian coastal waters

Image: Hans Hillewaert

creative commons

Interesting wormsDivers recently discovered a new species of worm on the seafloor of the Southern Ocean. These worms are nicknamed the “bone-eating worms” because they eat dead whale bones in the bottom of the ice-cold waters of the Antarctic and parts of the world. The Antarctic bone-eating worms, scientifically known as Osedax antarcticus, secrete acid to dissolve the hard calcium from the bones of a whale carcass in order to feed on the fatty lipids it needs to survive.

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Osedax antarcticus Bone-eating worm

Image: Deep sea news

creative commons

Greeffiella, a roundworm, is the Guinness World Record holder for the smallest worm in the world, measuring at merely 80 micrometres long! It is also completely transparent, which makes it easy for scientists to study the worm’s anatomy.

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Male Greeffiella found in Kermadec Trench

Image: Daniel Leduc / NIWA

creative commons

Despite what you may have heard, not all worms are long and squishy. The pig butt worm, Chaetopterus pugaporcinus, has two inflated sections that looks very much like a butt. This round shape allows it to float along with the ocean’s current where it lives.

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Chaetopterus pugaporcinus Pigbutt worm

Image: Casey Dunn / Flickr

creative commons

Worm charmingBeachworms (family Onuphidae) are very popular as fishing bait in many parts of Australia, living deep under the sand of surf beaches. They are scavengers of beach carrion, such as dead fish or seabirds, and have an acute sense of smell, which is the key to finding them. Taking advantage of the beachworm’s very sensitive “nose”, fishers slowly drag a smelly piece of fish or meat along the wash-zone of the beach to attract, even charm, the worms to the surface of the sand. As the worm pokes its head out of the sand to take the bait, the skilful worm catcher will pinch the worm just behind the head and carefully pull out the entire worm, which can be several metres long. It takes much skill and practice, however, to extract the whole worm without breaking the soft body, and many novices have been left with only a worm head in hand. Fortunately for the rest of the worm left behind, it can usually regrow the head.

Additional Readinghttps://news.nationalgeographic.com/news/2013/08/pictures/130813-bone-eating-worm-osedax-whale-antarctic-ocean-science/https://en.wikipedia.org/wiki/Worm_charminghttps://www.upi.com/Odd_News/2009/06/29/Worm-charmer-10-sets-new-record/UPI-68561246307679/http://eol.org/info/448http://www.weirdworm.com/13-weird-worms/Australian Earthwormshttps://australian.museum/learn/animals/worms/

Invertebrates

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imtoken钱包下载最新版|worms

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WoRMS - World Register of Marine Species

WoRMS - World Register of Marine Species

WoRMS - World Register of Marine Species

Worm | Segmented, Annelid, Invertebrate | Britannica

WoRMS! World Register of Marine Species | World Ocean Observatory

worms是什么意思_worms的翻译_音标_读音_用法_例句_爱词霸在线词典

Worms - Facts, Diet & Habitat Information

Comparative genomics of the major parasitic worms | Nature Genetics

WORM中文(简体)翻译：剑桥词典

What are worms? - The Australian Museum

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