Presentation slides: one day Ensembl workshop CRUK - Cambridge April 2016

1. 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

2. Denise Carvalho-Silva
European Molecular Biology Laboratory
European Bioinformatics Institute
Browsing Genes, Variation and
Regulation data with Ensembl
CRUK - Cambridge Institute

3. 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

4. http://www.ebi.ac.uk/
~denise/workshops/
2016/cruk
Materials

5. 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

6. bli blo
bla blu
bla bla
bli blo
bla blu
bla bla
bli blo
bla blu
bla bla
bla blu
bla bla
bli blo

7. Introduction
Why do we need/have genome browsers?

8. Genome sequencing
1977: 1st genome to be sequenced (5 kb)
2000: draft human sequence (3 gb)
Large amounts of raw DNA sequence data

9. Raw DNA sequence data

10. Annotation: making sense

11. Annotation of vertebrate genomeswww.ensembl.org
pre.ensembl.org
>80 genomes*
D. melanogaster
C. elegans
S. cerevisae
*Release 84
March 2016

12. 1 human genome à 3 assemblies
www.ensembl.org grch37.ensembl.org
e54.ensembl.org

13. EBI is an Outstation of the European Molecular Biology Laboratory.
Comparative GenomicsGene models
RegulationVariation
Custom data displayProgrammatic access
Toolkit
Ensembl Features

14. EBI is an Outstation of the European Molecular Biology Laboratory.
Comparative GenomicsGene models
RegulationVariation
Custom data displayProgrammatic access
Toolkit
Ensembl Features

15. Ensemblautomatic
annotation

16. Gene models in Ensembl
Goal: Generate set of well-supported genes
Automatic Manual

17. • 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…)

18. Ensembl genes & transcripts
• merged annotation
• higher confidence and quality
• comprehensive: alternatively spliced transcripts
UTR ExonIntron
5’ UTR3’ UTR
Gold (identical annotation) = Automatic + Manual

19. Alternatively splicing
rich and comprehensive annotation

20. Which transcript to use?
http://www.ensembl.org/Help/Glossary?id=493
http://www.ensembl.org/Help/Glossary?id=492
APPRIS
TSLs

21. 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

22. 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

23. Annotation based on RNASeq
http://www.ensembl.org/info/genome/genebuild/
rnaseq_annotation.html

24. ncRNA gene annotation
http://www.ensembl.org/info/genome/genebuild/ncrna.html

25. 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

27. Ensembl Browser
Live demo:
Walking through the website
pages 14-37

28. 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

29. 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

30. 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

31. 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

32. 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!

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

34. Outline
• Definitions
• The principle: 4 steps
• Tutorial: simple query in human
• Find Ensembl BioMart and BioMart elsewhere
• Sophisticated platforms: mart services, APIs, etc…
• Exercises

35. 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)

36. The four-step principle
DATA FILTERS ATTRIBUTES RESULTS
IDs
Regions
Domains
Expression
Tables
Fasta
Dataset
Database
Homologs
Sequences
Features
Structures

37. Choosing the data
Database and dataset

38. Limit your data set
(information that you know)
Selecting the filters
Click “Count” to see
if BioMart is reading
the input data

39. Picking the attributes
Determine output columns
(information you want to know)

40. The different attributes

41. Getting the results
Tables/sequences
click “Unique
results only”
For the full
table: click
View “ALL”
rows or “Go”

42. Selected IBD genes
IL23R, PTPN22,
CUL2, C1orf106, IL18RAP

43. 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

44. 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

45. Ensembl BioMart
Live demo

46. Find BioMart
www.ensembl.org/biomart

47. Ensembl BioMarts

48. http://tinyurl.com/biomart-video
BioMart video

49. More sophisticated platforms
• BioMart queries: MartService
www.biomart.org/martservice.html
• APIs: PERL, Java, Web Services
• Third party softwares
galaxyproject.orgbioconductor.orgtaverna.org.uk

51. Ensembl BioMart
Thomas
Maurel
Amonida
Zadissa

52. BioMart
Step-by-step example
pages 41-45
Exercises
pages 46-49
Answers
www.ebi.ac.uk/~denise/workshops/2016/
cruk/answers
Feel free to explore BioMart in other contexts too!

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

54. 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

55. 1) Large scale: structural (> 50 base pairs)
Genetic variation
duplication deletion inversion translocation loss
2) Short scale: SNPs (or SNVs), indels
G A C TG A C TA T C G GG GTT TCC CA A A
G A A TG A C TT T C G G- G-T TCC -A A A

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

57. Sources of variation data
• Import alleles and frequencies
• Annotate variants
http://www.ensembl.org/info/docs/variation/sources_documentation.html

58. Location tab: across a region
SVsSNPs
Ensembl
genes

59. Gene tab: gene-centric
SNPs
SVs

60. Variation tab: variant centric
summary
data
SNP
or
SV

61. Variants on the karyotype

62. Phenotype data in Ensembl
species and sources

63. Population data for variants
http://hapmap.ncbi.nlm.nih.gov/
http://www.1000genomes.org

64. pie charts:
1KG super populations
Human Population Genetics

65. 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

66. 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

67. CODING
Synonymous
INTRONIC5’ UTR
ATG AAAAAAA
Regulatory
Splice sites
CODING
Missense
3’ UTR5’ Upstream 3’ downstream
Mapping variants on transcripts
Identify transcripts that overlap variants and
predict the consequence of these on Ensembl
(or RefSeq) transcripts using

68. 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/)

69. SIFT
sift.jcvi.org/
Consequence: missense
GAG >GGG
Glu > Gly
PolyPhen-2
genetics.bwh.harvard.edu/pph2/
Condel
dbNSFP

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

71. Inputting data into
Chromosome
Start
End
Alleles
Strand

72. Output options in
GAG > GGG
Glu > Gly
GAG > GAA
Glu > Glu

73. Queued
Running
Done
Failed
Save to your account (log in)
Edit and resubmit your job
Delete job
Ticket system in
Ticket identifier Job name

74. Viewing results
SO consequence terms*
*http://www.sequenceontology.org/index.html

75. 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

76. 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

77. 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

78. VEP video
http://tinyurl.com/vep-video

79. 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).

80. Ensembl Variation API
Variation Schema Description
http://useast.ensembl.org/info/docs/api/variation/index.html

81. Variation Team
Fiona
Cunningham
Will
McLaren
Laurent
Gil
Sarah
Hunt
Anja
Thormann

83. Ensembl Genetic Variation
Exercises
pages 52-56
Answers
www.ebi.ac.uk/~denise/workshops/2016/
cruk/answers
Feel free to explore your favourite variant/phenotype too!

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

85. Outline
• Definition and models
• Epigenetics and Epigenomics
• Ensembl Regulation: goal, data sources, species
• Viewing / accessing regulation data in Ensembl
• Track hubs: ENCODE, Blueprint
• Exercises

86. 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 ??

87. 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

88. Nucleosomes
Histones
Histone marks
CpG methylation
11 nm
Transcription regulation
expanded model
• Epigenetic marks may affect the binding of TFs

89. Histone modifications
dynamically regulating genes
JillS.Butler,andSharonY.R.Dent
Blood2013;121:3076-3084

90. Packed Chromatin
30 nm
Open Chromatin
Distal enhancer
Complete (???) model
Transcription regulation

91. 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

92. Measuring gene expression
Northern/Western blot Microarrays
SAGE
AdpatedfromDarrylLeja,IanDunham
NGS techniques
DNase-seq ChIP-seq
RNASeq
RT-qPCR

93. ChIP-sequencing
crosslink and shear
TF1 TF2
TF3
TF1
TF3TF2
Antibodies and IP
unlink, purify and DNA sequencing
Y YY
TF1
TF3
TF2
ACGTC CGCTT GAACA
map back to the genome
DNA and proteins

94. 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/

95. 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

96. 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

97. • 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

98. Dataset for the Ensembl build
raw data à Ensembl Regulation pipeline à Ensembl annotation

99. Regulation data: view
MultiCell: all cell lines combined
Displayed by default

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

101. Cis-regulatory Models (CRMs)Rawdata:peaksandsignalfrom
ChIP-Seq,DNase1-Seq

102. Regulatory features: view
Configure this page à Regulation à Regulatory features
For single and individual cell lines, e.g. GM12878, HUVEC

103. ChiP-Seq signal for TF
signal
Regulatory Features: motifs
Ensembl regulatory feature
Position Weight Matrix for TF
(JASPAR database)

104. 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 &…

105. How to choose raw data: matrix
Supporting evidence:
1) Open chromatin & TFBS
2) Histones & polymerases
http://tinyurl.com/matrix-ensembl

106. 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 Ensemblcategoriesof
combinedsegments
Configure this page à Regulation à Regulatory features

107. 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.

108. Methylation data in Ensembl
CpG DNA methylation (RRBS, WGBS, MeDIP)
ENCODE and PMID: 18577705
Configure this page à Regulation à DNA Methylation

109. 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

110. Browsing Regulation data
tinyurl.com/ensembl-regulation

111. 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.

112. 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

113. 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

114. Track hubs in Ensembl

115. ENCODE data hub in Ensembl
www.ensembl.org/info/encode.html
>2,800 data tracks

116. Ensembl Regulation in BioMart
Human, mouse and fruit fly
FILTERS
ATTRIBUTES

117. Ensembl Regulation API
http://useast.ensembl.org/info/docs/api/funcgen/index.html
Funcgen Schema Description

118. Regulation Team
Thomas
Juettemann
Myrto
Kostadima
Ilias
Lavidas
Michael
Nuhn

120. Ensembl Regulation
Exercises
Pages 58-60
Answers
www.ebi.ac.uk/~denise/workshops/2016/
cruk/answers
Feel free to explore your favourite gene/genomic region!

121. Wrap up
Ensembl is the place!
Genes, genomes, variants, regulatory features,
tools and more

122. Ensembl Retreat June 2015

123. Latest publication

124. Acknowledgements
The Entire Ensembl
Team
Funding
Co-funded by the
European Union

125. Your take home message

126. Feedback survey
http://tinyurl.com/cruk-180416

127. Connect with Ensembl
?
??
?
?
?
?
???
helpdesk@ensembl.org
helpdesk@ensemblgenomes.org
https://www.youtube.com/user/EnsemblHelpdesk

128. 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