Comparative Genomics. EBI is an Outstation of the European Molecular Biology Laboratory.

Transcription

1 Training materials Ensembl training materials are protected by a CC BY license If you wish to re-use these materials, please credit Ensembl for their creation If you use Ensembl for your work, please cite our papers ml

2 Comparative Genomics EBI is an Outstation of the European Molecular Biology Laboratory.

3 This webinar course Date Webinar topic Instructor 4th Sept Introduction to Ensembl Astrid Gall Ensembl genes Emily Perry Variation data in Ensembl and the Ensembl VEP Erin Haskell Comparing genes and genomes with Ensembl Compara Emily Perry Finding features that regulate genes the Ensembl Regulatory Build Emily Perry 6th Sept 11th Sept Erin Haskell Data export with BioMart 13th Sept Uploading your data to Ensembl Astrid Gall Introduction to the Ensembl REST APIs Emily Perry

4 Overview of the talk Comparative genomics: applications and species Gene trees Homology predictions Whole genome alignments pairwise multiple Shared synteny

5 Applications of Comparative Genomics Comparative genomics allows us to understand: vertebrate evolution differences between species at the genome level gene function based on homology the distribution of highly conserved regions

6 Comparative analysis by taxa Ensembl Compara Ensembl Metazoa Compara

7 Pan-taxonomic compara o/genomes?pan_compara=1

8 Pan-taxonomic compara

9 Gene trees all-vs-all blastp + hcluster_sg Orthologues and Paralogues Based on protein alignments Representative protein of each Ensembl gene Clustering, Blast, multiple alignments Reconciliation with species tree Orthologue/Paralogue inference para/homology_method.html

10 Homology relationships Paralogues Orthologues Genes emerged through a duplication event eg c1 and c2 h1 and h2 Genes emerged through a speciation event eg c1 and h1 h2 and m c2 and m c1 h1 One-to-one c2 h2 m One-to-many Speciation Duplication

11 Hands on We re going to look at a gene BRCA2 to find homologues.

12 Whole genome alignments To identify highly conserved regions sequences that evolve slowly regions likely to be functional both coding and non-coding sequences To spot trouble gene predictions To define syntenic regions Types: pairwise versus multiple

13 Alignments Pairwise alignments with BLASTZ (older) LASTZ-net (newer) EPO (Enredo-Pecan-Ortheus) analysis For selected sets (11 fish, 7 sauropsids, 70 eutherian, 12 primates) Mercator-Pecan analysis For 32 amniota vertebrates (mammals+birds)

14 Shared synteny

15 Hands on We re going to look at a gene BRCA2 to find homologues. We will look at a human genomic region 2: which contains the HoxD cluster to find alignments and conservation regions.

16 More information Ensembl comparative genomics resources. Herrero et al

17 Course exercises ser-webinar-series-2016 This text will be replaced by a YouTube (link to YouKu too) video of the webinar and a pdf of the slides. A link to exercises and their solutions will appear in the page hierarchy The next page will be the exercises

18 Get help with the exercises Use the exercise solutions in the online course Join our Slack workspace and discuss the exercises with everybody in dedicated channels (register to get sent a link) us helpdesk@ensembl.org

19 This webinar course Date Webinar topic Instructor 4th Sept Introduction to Ensembl Astrid Gall Ensembl genes Emily Perry Variation data in Ensembl and the Ensembl VEP Erin Haskell Comparing genes and genomes with Ensembl Compara Astrid Gall Finding features that regulate genes the Ensembl Regulatory Build Emily Perry 6th Sept 11th Sept Erin Haskell Data export with BioMart 13th Sept Uploading your data to Ensembl Astrid Gall Introduction to the Ensembl REST APIs Emily Perry

20 Help and documentation Courses online Tutorials Flash animations us Ensembl public mailing lists

21 Follow us

22 Publications Ensembl 2018 Zerbino et al

23 Ensembl 2018

24 Ensembl Acknowledgements The Entire Ensembl Team Daniel R. Zerbino1, Premanand Achuthan1, Wasiu Akanni1, M. Ridwan Amode1, Daniel Barrell1,2, Jyothish Bhai1, Konstantinos Billis1, Carla Cummins1, Astrid Gall1, Carlos García Giroń1, Laurent Gil1, Leo Gordon1, Leanne Haggerty1, Erin Haskell1, Thibaut Hourlier1, Osagie G. Izuogu1, Sophie H. Janacek1, Thomas Juettemann1, Jimmy Kiang To1, Matthew R. Laird1, Ilias Lavidas1, Zhicheng Liu1, Jane E. Loveland1, Thomas Maurel1, William McLaren1, Benjamin Moore1, Jonathan Mudge1, Daniel N. Murphy1, Victoria Newman1, Michael Nuhn1, Denye Ogeh1, Chuang Kee Ong1, Anne Parker1, Mateus Patricio1, Harpreet Singh Riat1, Helen Schuilenburg1, Dan Sheppard1, Helen Sparrow1, Kieron Taylor1, Anja Thormann1, Alessandro Vullo1, Brandon Walts1, Amonida Zadissa1, Adam Frankish1, Sarah E. Hunt1, Myrto Kostadima1, Nicholas Langridge1, Fergal J. Martin1, Matthieu Muffato1, Emily Perry1, Magali Ruffier1, Dan M. Staines1, Stephen J. Trevanion1, Bronwen L. Aken1, Fiona Cunningham1, Andrew Yates1 and Paul Flicek1,3 1 European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK, 2Eagle Genomics Ltd., Wellcome Genome Campus, Hinxton, Cambridge CB10 1DR, UK and 3Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK Funding Co-funded by the European Union