browsing genes, variation and regulation data with ensembl

Training materials

Ensembl materials are protected by a CC BY license http://creativecommons.org/licenses/by/4.0/ If you wish to re-use these, please credit Ensembl for their creation If you use Ensembl for your work, please cite our papers

http://www.ensembl.org/info/about/publications.html

Denise Carvalho-Silva European Molecular Biology Laboratory

European Bioinformatics Institute

Browsing Genes, Variation and Regulation data with Ensembl

CRUK - Cambridge Institute

Today 09:30-17:00 •  Introduction to Ensembl

•  Browser walkthrough

10:45-11:00 coffee/tea

•  Browser exercises

•  BioMart (Talk + Exercises)

13:00-14:00 lunch break

•  Genetic variation (Talk + Exercises)

15:30-15:45 coffee/tea

•  Gene Regulation (Talk + Exercises)

•  Wrap up, photo opportunity & feedback survey

http://www.ebi.ac.uk/ ~denise/workshops/

2016/cruk

Materials

Course Objectives

What is Ensembl?

What type of data can you get in Ensembl?

How to navigate the Ensembl browser website?

How to connect with Ensembl

bli blo

bla blu bla bla

bli blo

bla blu

bla bla

bli blo

bla blu

bla bla

bla blu

bla bla

bli blo

Introduction Why do we need/have genome browsers?

Genome sequencing

1977: 1st genome to be sequenced (5 kb) 2000: draft human sequence (3 gb)

Large amounts of raw DNA sequence data

Raw DNA sequence data

Annotation: making sense

Annotation of vertebrate genomes

w

ww

.ens

embl

.org

pre.

ense

mbl

.org

>80 genomes* D. melanogaster

C. elegans S. cerevisae

*Release 84 March 2016

1 human genome à 3 assemblies

www.ensembl.org grch37.ensembl.org

e54.ensembl.org

EBI is an Outstation of the European Molecular Biology Laboratory.

Comparative Genomics Gene models

Regulation Variation

Custom data display Programmatic access

Toolkit

Ensembl Features

Ense

mb

l au

tom

atic

an

not

atio

n

Gene models in Ensembl

Goal: Generate set of well-supported genes

Automatic Manual

•  many species •  genome-wide at once •  ~ 4 months

•  fewer species •  gene by gene •  many years

Automatic and coding (20_)

Manual and coding (00_)

Automatic + Manual (“gold”)

Manual and non-coding (00_)

Automatic annotation* Manual annotation*

* based on experimental, biological evidence (INSDC, UniProtKB…)

Ensembl genes & transcripts

•  merged annotation

•  higher confidence and quality

•  comprehensive: alternatively spliced transcripts

UTR Exon Intron

5’ UTR 3’ UTR

Gold (identical annotation) = Automatic + Manual

Alternatively splicing

rich and comprehensive annotation

Which transcript to use?

http://www.ensembl.org/Help/Glossary?id=493 http://www.ensembl.org/Help/Glossary?id=492

APPRIS

TSLs

CCDS project

•  annotate a consensus coding DNA sequence set •  EBI, WTSI, UCSC and NCBI • 

Genome Res. 19:1316-23 (2009)

http://www.ncbi.nlm.nih.gov/CCDS/CcdsBrowse.cgi

CCDS transcript

Disclaimer: which transcript to use

No single method will tell us which transcript to use Decision on a case by case basis

•  All transcripts OR one/two well supported ones?

List of transcripts: we offer choices based on •  CCDS (Ensembl, HAVANA, NCBI, UCSC) •  Golden transcripts (identical Ensembl and HAVANA) •  Cross reference entries (e.g. UniProtKB, RefSeq) •  APPRIS •  TSLs

Annotation based on RNASeq

http://www.ensembl.org/info/genome/genebuild/rnaseq_annotation.html

ncRNA gene annotation

http://www.ensembl.org/info/genome/genebuild/ncrna.html

Ensembl stable identifiers

•  ENSG########### Ensembl Gene ID •  ENST########### Ensembl Transcript ID •  ENSP########### Ensembl Peptide ID •  ENSE########### Ensembl Exon ID

•  For non-human species a suffix is added: ENSMUSG MUS (Mus musculus) for mouse

Ensembl Browser

Live demo: Walking through the website

pages 14-37

The ESPN gene products are active in the inner ear, where it appears to play an essential role in normal hearing and balance.

Let’s explore ESPN

Before we start: background

A) What is the location and strand of the human ESPN gene?

B) How can I view protein alignments and variants mapped to this location?

C) Can I move data tracks up and down,

share and delete tracks?

Human ESPN: location

A) How can I find the genomic sequence of this gene? What is the ID of its first exon?

B) Can I display the genomic coordinates and variants on this sequence?

C) Can I find information on the expression of this gene in different tissues?

Human ESPN: gene

A) How many exons does the longest ESPN transcript have? Are there any completely untranslated exons?

B) Can I find its cDNA sequence?

C) What are the UniProt and RefSeq entries cross referenced to this transcript?

Human ESPN: transcript

Ensembl Browser

Exercises pages 38-40

Answers

www.ebi.ac.uk/~denise/workshops/2016/ cruk/answers

Feel free to explore your favourite gene/region too!

EBI is an Outsta,on of the European Molecular Biology Laboratory.

BioMart

Outline

•  Definitions

•  The principle: 4 steps •  Tutorial: simple query in human

•  Find Ensembl BioMart and BioMart elsewhere

•  Sophisticated platforms: mart services, APIs, etc… •  Exercises

What is BioMart?

•  Free service for easy retrieval of Ensembl data •  Data export tool with little/no programming required

•  Complex queries with a few mouse clicks

•  Output formats (.xls, .csv, fasta, tsv, html)

The four-step principle

DATA FILTERS ATTRIBUTES

RESULTS

IDs Regions Domains

Expression

Tables Fasta

Dataset

Database Homologs Sequences Features

Structures

Choosing the data

Database and dataset

Limit your data set (information that you know)

Selecting the filters

Click “Count” to see if BioMart is reading

the input data

Picking the attributes

Determine output columns (information you want to know)

The different attributes

Getting the results

Tables/sequences

click “Unique results only”

For the full table: click View “ALL”

rows or “Go”

Selected IBD genes

IL23R, PTPN22, CUL2, C1orf106, IL18RAP

For the IL23R, PTPN22, CUL2, C1orf106 and IL18RAP genes, use BioMart to retrieve a table (.xls) containing: •  Associated gene name, ENSG and ENST IDs

•  Chromosome name, gene start and end

•  GO term name and Interpro description

Tutorial: BioMart

The four-step principle

DATA FILTERS ATTRIBUTES

RESULTS

Gene

Gene name, ENSG/ENST ID, Chr start end,

GO term name, Interpro

description

.xls table

Human

IL23R, CUL2,

PTPN22, C1orf106 IL18RAP

Ensembl BioMart

Live demo

Find BioMart

www.ensembl.org/biomart

Ensembl BioMarts

http://tinyurl.com/biomart-video

BioMart video

More sophisticated platforms

•  BioMart queries: MartService www.biomart.org/martservice.html

•  APIs: PERL, Java, Web Services

•  Third party softwares

galaxyproject.org bioconductor.org taverna.org.uk

Ensembl BioMart

Thomas Maurel

Amonida Zadissa

BioMart

Step-by-step example pages 41-45

Exercises

pages 46-49

Answers


Feel free to explore BioMart in other contexts too!


Genetic Variation

Outline

•  Classes of variation, species and sources

•  Browsing variation data: some entry points Location tab Gene tab Variation tab

•  Phenotypic data and population genetics

•  How to annotate your own variants

•  Exercises

1) Large scale: structural (> 50 base pairs)

Genetic variation

duplication deletion inversion translocation loss

2) Short scale: SNPs (or SNVs), indels

G A C T G A C T A T C G G G G T T T C C C A A A

G A A T G A C T T T C G G - G - T T C C - A A A

Species with variation data

Understand the types of genetic variation data and how to view them in the context of our genomes

Sources of variation data

•  Import alleles and frequencies

•  Annotate variants

http://www.ensembl.org/info/docs/variation/sources_documentation.html

Location tab: across a region

SVs SNPs

Ensembl genes

Gene tab: gene-centric SNPs

SVs

Variation tab: variant centric

summary data

SNP or SV

Variants on the karyotype

Phenotype data in Ensembl species and sources

Population data for variants

http://hapmap.ncbi.nlm.nih.gov/

http://www.1000genomes.org

pie charts: 1KG super populations

Human Population Genetics

Coffee intake is a worldwide phenomenon

with Finland at the top, and UK in the 44th

place. Is caffeine consumption in our genes?

A)  What are the chromosome locations of variants associated with this phenotype?

B)  Which variant has got the most significant association?

C)  What is the ancestral allele of this variant? Is it conserved in eutherian mammals?

D)  What is the most frequent allele in GBR?

E)  Can you download this variant and 200 nt upstream and downstream flanking sequence in RTF (Rich Text Format)?

Live demo

You can annotate your SNPs and SVs too!

•  Variant Effect Predictor

•  Different input formats

•  SIFT/PolyPhen for missense variants

PMID: 20562413

Perl script Web interface REST API

XML

CODING Synonymous

INTRONIC 5’ UTR

ATG AAAAAAA Regulatory

Splice sites

CODING Missense

3’ UTR 5’ Upstream 3’ downstream

Mapping variants on transcripts

Identify transcripts that overlap variants and predict the consequence of these on Ensembl (or RefSeq) transcripts using

Consequence terms for variants

http://www.ensembl.org/info/genome/variation/predicted_data.html#consequence_type_table

* defined by the Sequence Ontology (SO) project (http://www.sequenceontology.org/)

SIFT sift.jcvi.org/

Consequence: missense GAG >GGG Glu > Gly

PolyPhen-2 genetics.bwh.harvard.edu/pph2/ Condel

dbNSFP

Ensembl tools http://www.ensembl.org/tools.html

http://www.ensembl.org/vep

Inputting data into

Chromosome Start End Alleles Strand

Output options in

GAG > GGG Glu > Gly

GAG > GAA Glu > Glu

Queued Running Done Failed

Save to your account (log in) Edit and resubmit your job Delete job

Ticket system in

Ticket identifier Job name

Viewing results

SO consequence terms*

*http://www.sequenceontology.org/index.html

ensembl.org/info/docs/tools/vep/online/results.html#summary

Table •  Before / after filtering •  novel / existing variants

Pie charts (consequence terms) •  total observed (more than one per variant)

•  Separate chart: coding consequences

Viewing results

Navigate results (one row per variant/ transcript overlap)

Show/hide columns in results table

more columns: scroll right

•  Download results •  Send results to BioMart

Create and edit filters

ensembl.org/info/docs/tools/vep/online/results.html#table

results table

Filters consist of three components Field •  e.g. Consequence, biotype Operator •  e.g. is, matches (partial string matches)

Value •  the value to compare against •  some fields have autocomplete values

Multiple filters allowed with logical relationship (AND, OR) Active filters can be edited too!

ensembl.org/info/docs/tools/vep/online/results.html#filter

Filtering results

VEP video

http://tinyurl.com/vep-video

Things to bear in mind

1)  No distinction between polymorphisms and mutations. Exception HGMD and COSMIC: all mutations;

2)  C/T à first allele is the one in the reference genome, not necessarily the major or the ancestral;

3)  Ensembl reports all alleles on the forward strand (different from dbSNP).

Ensembl Variation API

Variation Schema Description

http://useast.ensembl.org/info/docs/api/variation/index.html

Variation Team

Fiona Cunningham

Will McLaren

Laurent Gil

Sarah Hunt

Anja Thormann

Ensembl Genetic Variation

Exercises pages 52-56

Answers


Feel free to explore your favourite variant/phenotype too!


Gene Regulation

Outline •  Definition and models

•  Epigenetics and Epigenomics

•  Ensembl Regulation: goal, data sources, species •  Viewing / accessing regulation data in Ensembl

•  Track hubs: ENCODE, Blueprint •  Exercises

Regulation of gene expression

•  Change in the production of mRNA/proteins ( or ) •  From the transcription to post-translational levels •  Models of regulation of gene transcription

•  Basic •  Expanded •  Complete ??

Transcription regulation

Transcription Factor Binding Sites Promoter Gene

mRNA

Transcription Factors Activation

Repression RNA polymerase complex

2 nm

basic model

•  TF binding (promoters, enhancers) à transcription

Nucleosomes

Histones

Histone marks

CpG methylation

11 nm

Transcription regulation expanded model

•  Epigenetic marks may affect the binding of TFs

Histone modifications dynamically regulating genes

Jill

S. B

utle

r, an

d Sha

ron

Y. R

. D

ent

Blo

od 2

013;

121:

3076

-308

4

Packed Chromatin

30 nm

Open Chromatin

Distal enhancer

Complete (???) model

Transcription regulation

Epigenetics/Epigenomics

Epigenetics* The study of inherited changes in phenotype without changes in genotype

Epigenomics Epigenetics on a genome-wide scale

http://integratedhealthcare.eu/

*One of the routes to regulate gene transcription

Measuring gene expression

Northern/Western blot Microarrays

SAGE

Adp

ated

fro

m D

arry

l Lej

a, I

an D

unha

m

NGS techniques

DNase-seq ChIP-seq RNASeq

RT-qPCR

ChIP-sequencing

crosslink and shear

TF1 TF2 TF3

TF1 TF3 TF2

Antibodies and IP

unlink, purify and DNA sequencing

Y Y Y

TF1 TF3 TF2

ACGTC CGCTT GAACA

map back to the genome

DNA and proteins

Ensembl Regulation Goal: Annotate the genome with features that may play a

role in the transcriptional regulation of genes

Multiple data sources: collection and summary

http://www.ensembl.org/info/docs/funcgen/regulation_sources.html http://www.ensembl.org/Homo_sapiens/Experiment/

Data source: ENCODE

“Encyclopedia of DNA Elements” Trying to assign function to many regions as possible Transcription and regulatory information 4,626 datasets, 2,498 cell types à functional elements PMID: 22955616, PMID: 17571346

http://www.nature.com/encode/#/threads

Data source: Roadmap NIH consortium: public resource of normal epigenomes DNA methylation, histone marks, open chromatin, small RNA

http://www.roadmapepigenomics.org/data http://www.roadmapepigenomics.org/publications

•  EU consortium: generate 100 reference epigenomes •  Blood cells: healthy individuals and malignant leukaemic

counterparts •  1046 experiments {ChIP, RNA, Bisulfite, DNase}-Seq •  425 cell types and seven cell lines •  http://www.blueprint-epigenome.eu/

Data source: Blueprint

Dataset for the Ensembl build

raw data à Ensembl Regulation pipeline à Ensembl annotation

Regulation data: view

MultiCell: all cell lines combined Displayed by default

TF binding sites

Competition for binding sites, co-recruitment à CRM* * Howard et al., Dev. Biol, 2004

Cis-regulatory Models (CRMs) Ra

w d

ata:

pea

ks a

nd s

igna

l fro

m

ChI

P-Seq

, D

Nas

e1-S

eq

Regulatory features: view

Configure this page à Regulation à Regulatory features

For single and individual cell lines, e.g. GM12878, HUVEC

ChiP-Seq signal for TF

signal

Regulatory Features: motifs

Ensembl regulatory feature

Position Weight Matrix for TF (JASPAR database)

Viewing the raw NGS data

DNaseI and TFBS

Histone marks and polymerases

Configure this page à Regulation à Open chromatin &…

Configure this page à Regulation à Histones &…

How to choose raw data: matrix

Supporting evidence: 1) Open chromatin & TFBS 2) Histones & polymerases

http://tinyurl.com/matrix-ensembl

CTCF enriched Predicted Weak Enhancer/Cis-‐reg element Predicted Transcribed Region Predicted Enhancer Predicted Promoter Flank Predicted Repressed/Low AcAvity Predicted Promoter with TSS

Segmentation data in Ensembl ca

tego

ries

of

com

bine

d se

gmen

ts

Configure this page à Regulation à Regulatory features

Experimental confirmation

•  CTCF: good recall, reproducible across multiple cell lines, tight boundaries. •  TSS:

•  88.9% of FANTOM 5 strict TSSs were covered. •  Enhancers:

•  92.4% of 882 VISTA enhancers were detected. •  80.3% of 40279 robust FANTOM 5 enhancers were found.

Methylation data in Ensembl CpG DNA methylation (RRBS, WGBS, MeDIP)

ENCODE and PMID: 18577705

Configure this page à Regulation à DNA Methylation

The STRADA controls tumor suppressor activities of LKB1 (https://www.wikigenes.org/)

A.  What are the Ensembl regulatory features annotated in this gene?

B.  Are there any features in the 5’ region of STRADA?

C.  Do the regulatory features for K562, CD8+ cells (ENCODE) and erythroblast (Blueprint) differ at this region?

D.  What is the methylation pattern (WGBS) at the 5’ end of this gene?

E.  What is the stable IDs of the most 5’ regulatory feature?

Tutorial

Browsing Regulation data

tinyurl.com/ensembl-regulation

Things to bear in mind

1)  The annotation of regulatory elements in Ensembl highlight where the biochemical data (ChIP-seq, etc) maps to on the human (mouse) genomes;

2)  Features can be nearby genes but might not affect their transcription/expression;

3)  Disclaimer: Ensembl can not tell you how your favourite gene is regulated.

In addition to the big names CpG islands, TSS, miRNA target predictions (TarBase)

Configure this page à Regulation à Other regulatory regions

Configure this page à Sequence and assembly à Simple features

Subset of cell types* http://www.ensembl.org/info/genome/funcgen/regulatory_segmentation.html

Minimum requirement for cell selection: CTCF binding, DNaseI, H3K4me3, H3K27me3 and H3K6me3 •  Display all TFBS and histone marks for them •  Data processing to predict activity e.g. promoter

* ENCODE

Track hubs in Ensembl

ENCODE data hub in Ensembl www.ensembl.org/info/encode.html

>2,800 data tracks

Ensembl Regulation in BioMart

Human, mouse and fruit fly

FILTERS

ATTRIBUTES

Ensembl Regulation API

http://useast.ensembl.org/info/docs/api/funcgen/index.html

Funcgen Schema Description

Regulation Team

Thomas Juettemann

Myrto Kostadima

Ilias Lavidas

Michael Nuhn

Ensembl Regulation

Exercises Pages 58-60

Answers


Feel free to explore your favourite gene/genomic region!

Wrap up Ensembl is the place!

Genes, genomes, variants, regulatory features, tools and more

�� !�� "��# ��$� � %&�� &��!�� "��$� ��' ��(�� )�� "��*��+� ��%��$,-�,��.��/��%� ��0�122�3-4,556�272829

��!��!"�%�� "��

��

��

��

��

�� !�" #� �� $$� ��

%��

&�� !�� '�$� ��()**�� "�#�� ++��

&�� $$��%�&��)+�"))��

%��

��

��,�� ,�� &�� -%��

��.��/��0��

�� %�� '��$� �� 1�� ,�� %�� /��0��$��(�'��

�� ) �� ,�� 2� �� 3� ��*�� +�(�� ,��

/�� %�� ,� ��$��,� ��-�� -�� '�� !�� 0�� %�� +� �� $��4��5��4��5��6�62��4��5�� 4��5� �� 4��5� �� ,��

��%��

��,�� %��

��/��(��

�� 7�� 8�� 7�� .�� /�� -��-�� 012�3/��

%�� 7�� '�� -�-�$�� ,�� $��'�� /��$��(�0��$ �� -�� %��

��%��/��9��3�� 9��

�� %�� /�� $�� 04�� ,��4��,��5��4��01��2��,�� ,�� 5�-��

��!$�+�!�� :�� (�61�7��%��;��3��$��3��0��/��3��/8�!��/��-��9��

� !�� % !�� D�( #&�E�$� �� !��

1��

%��4�0��//0�� %.6�<%� �� ,�� 7��$� �� :�� 0�� ,��

<��

�� '�� -��$$�$� �-�� 4�� 5�� 4��0��0� ,�0��4��0�� 5� �� :��

&�� :��%0��

!�� : ��&� '��%� '� �� 3%��-7;7-9��-79-;,4�<�� '��%�' ��"��'��"� :�� " ��'� �� *��)�� (�� 3,�52��-658;9� �� ,�-,*�-=2-=94�� $$�� 3$$>(-5;;-8>,��$$>(-5;68->,��$$>/--7;52>,4��!�� "��# ��$� � %&�� &��"��'��0�?��%�� '��%�'� ��!�� "��.�� @�� < �� %��3 �=>5--=A5-,64��%��%��B�595;,-�A�$�.!��(��?C� ?� �� "" �� &� �� !�� "�� <�� < �� %�� =� ��"�� "��'�� %�� )�� D%�� 6,56-,� 3*��+�� A� �� 4?C� �� %�� "" �� "��'��0� ?�� %� � � �� '��%� '� �� !�� "�� &@�� < �� %�� 3 �=>5--=A5-,64� �� %�� %�� B�*!D��*A 2A5-,-A52,;-2�3!.�D��D��4?

Ensembl Retreat June 2015

Latest publication

Acknowledgements The Entire Ensembl Team

Funding

Co-funded by the European Union

Your take home message

Feedback survey

http://tinyurl.com/cruk-180416

Connect with Ensembl

? ??

? ?

? ?

? ? ?

[email protected] [email protected]

https://www.youtube.com/user/EnsemblHelpdesk

Training materials

Ensembl materials are protected by a CC BY license http://creativecommons.org/licenses/by/4.0/ If you wish to re-use these, please credit Ensembl for their creation If you use Ensembl for your work, please cite our papers

http://www.ensembl.org/info/about/publications.html

browsing genes, variation and regulation data with ensembl

Science