Demo: Introduction to Ensembl

Ensembl

Homepage

The front page of Ensembl is found at ensembl.org. It contains lots of information and links to help you navigate Ensembl:

On the right-hand panel you can see the current release number and what has come out in this release. To access old releases, scroll to the bottom of the page and click on View in archive site in the right-hand corner.

Click on the links to go to the archives. Alternatively, you can jump quickly to the correct release by adding e plus the release number in the URL. For example e98.ensembl.org jumps to Ensembl release 98.  
 
 

Available species

Scroll back up to the top of the homepage. You can view all available species by clicking the View full list of all species link underneath the coloured search block.

You can search for your species of interest (either the common or scientific name) using the search bar at the top right-hand corner of the table. Click on the common name of your species of interest to go to the species information page. We’ll click on Human.

 
 
 

Species information

Here you can see links to example features and to download flatfiles. To find out more about the genome assembly and genebuild, click on More information and statistics under the Genome assembly section.

Here you’ll find a detailed description of how to the genome was produced and links to the original source. You will also see details of how the genes were annotated.

The current genome assembly for human is GRCh38. If you want to see the previous assembly, GRCh37, visit our dedicated site grch37.ensembl.org.

 
 
 

Ensembl Genomes

Homepage

Let’s take a look at the Ensembl Genomes homepage at ensemblgenomes.org.

Click on the different taxa to see their homepages. Each one has a different colour-coding, but they are all structured in a similar format to the Ensembl main site.

You can navigate most of the taxa in the same way as you would with Ensembl.  
 
 

Ensembl Bacteria

Ensembl Bacteria has a large number of genomes and has a slightly different method to the other Ensembl sites. Let’s look at it in more detail.

There’s no drop-down species list for bacteria as it would be hard to navigate with the number of species. You can click the View full list of all Ensembl Bacteria species link underneath the coloured search block. Search for your species of interest using the filter in the top right-hand corner of the table.

Alternatively, you can find a species by typing the species name into the Search for a genome search box at the top of the page. A drop-down list will appear with any species matching the name you entered.

For example, to find a sub-strain of Clostridioides difficile start typing in the species name. Due to the auto-complete, you’ll see useful results as soon as you get to Clostridio.

The drop down contains various strains of C. difficile. Let’s choose C. difficile 630. This will take us to another species information page, where we can explore various features.

Unlike the Homo sapiens species information page, there is no prose description of the genome or gene annotation, as these pages were generated automatically.  
 
 

Ensembl Rapid Release

Our newest genomes, such as those coming from the Darwin Tree of Life, are available rapid.ensembl.org with limited annotation.

Go to Ensembl and find the following information:

1. What is the name of the genome assembly for Panda?

2. How long is the Panda genome (in bp)? How many coding genes have been annotated?

What previous assemblies are available for zebrafish?

Go to Ensembl Plants and answer the following questions:

1. How many genomes of the genus Solanum are there in Ensembl Plants?

2. When was the current Solanum lycopersicum genome assembly last revised?

1. Go to Ensembl Metazoa. How many genomes relating to the genus Anopheles are there in Ensembl Metazoa?

2. When was the current Anopheles gambiae genome assembly last revised?

Mycobacterium tuberculosis H37Ra str. ATCC25177 is a clinical strain.

Go to Ensembl Bacteria and find the species M. tuberculosis H37Ra str. ATCC25177. How many coding genes does it have?

Start at the Ensembl front page, ensembl.org. You can search for a region by typing it into a search box, but you have to specify the species.

To bypass the text search, you need to input your region coordinates in the correct format, which is chromosome, colon, start coordinate, dash, end coordinate, with no spaces for example: human 4:122868000-122946000. Type (or copy and paste) these coordinates into either search box.

or

Press Enter or click Go to jump directly to the Region in detail Page.

Click on the button to view page-specific help. The help pages provide text, labelled images and, in some cases, help videos to describe what you can see on the page and how to interact with it.

The Region in detail page is made up of three images, let’s look at each one in detail.

The first image shows the chromosome:

The region we’re looking at is highlighted on the chromosome. You can jump to a different region by dragging out a box in this image. Drag out a box on the chromosome, a pop-up menu will appear.

If you wanted to move to the region, you could click on Jump to region (### bp). If you wanted to highlight it, click on Mark region (###bp). For now, we’ll close the pop-up by clicking on the X on the corner.

The second image shows a 1Mb region around our selected region. This is always 1Mb in human, but the fixed size of this view varies between species. This view allows you to scroll back and forth along the chromosome.

You can also drag out and jump to or mark a region.

Click on the X to close the pop-up menu.

Click on the Drag/Select button to change the action of your mouse click. Now you can scroll along the chromosome by clicking and dragging within the image. As you do this you’ll see the image below grey out and two blue buttons appear. Clicking on Update this image would jump the lower image to the region central to the scrollable image. We want to go back to where we started, so we’ll click on Reset scrollable image.

The third image is a detailed, configurable view of the region.

Here you can see various tracks, which is what we call a data type that you can plot against the genome. Some tracks, such as the transcripts, can be on the forward or reverse strand. Forward stranded features are shown above the blue contig track that runs across the middle of the image, with reverse stranded features below the contig. Other tracks, such as variants, regulatory features or conserved regions, refer to both strands of the genome, and these are shown by default at the very top or very bottom of the view.

You can use click and drag to either navigate around the region or highlight regions of interest, Click on the Drag/Select option at the top or bottom right to switch mouse action. On Drag, you can click and drag left or right to move along the genome, the page will reload when you drop the mouse button. On Select you can drag out a box to highlight or zoom in on a region of interest.

With the tool set to Select, drag out a box around an exon and choose Mark region.

The highlight will remain in place if you zoom in and out or move around the region. This allows you to keep track of regions or features of interest.

We can edit what we see on this page by clicking on the blue Configure this page menu at the left.

This will open a menu that allows you to change the image.

There are thousands of possible tracks that you can add. When you launch the view, you will see all the tracks that are currently turned on with their names on the left and an info icon on the right, which you can click on to expand the description of the track. Turn them on or off, or change the track style by clicking on the box next to the name. More details about the different track styles are in this FAQ: http://www.ensembl.org/Help/Faq?id=335.

You can find more tracks to add by either exploring the categories on the left, or using the Find a track option at the top left. Type in a word or phrase to find tracks with it in the track name or description.

Let’s add some tracks to this image. Add:

• Proteins (mammal) from UniProt – Labels
• 1000 Genomes - All - short variants (SNPs and indels) – Normal

Now click on the tick in the top left hand to save and close the menu. Alternatively, click anywhere outside of the menu. We can now see the tracks in the image. The proteins track is stranded, so you will see two tracks, one above and one below the contig, representing the proteins mapped to the forward and reverse strands respectively. The variants track is not stranded, so is found near the bottom of the image.

If the track is not giving you can information you need, you can easily change the way the tracks appear by hovering over the track name then the cog wheel to open a menu. To make it easier to compare information between tracks, such as spotting overlaps, you can move tracks around by clicking and dragging on the bar to the left of the track name.

Now that you’ve got the view how you want it, you might like to show something you’ve found to a colleague or collaborator. Click on the Share this page button to generate a link. Email the link to someone else, so that they can see the same view as you, including all the tracks you’ve added. These links contain the Ensembl release number, so if a new release or even assembly comes out, your link will just take you to the archive site for the release it was made on.

To return this to the default view, go to Configure this page and select Reset configuration at the bottom of the menu.

Go to Ensembl.

1. Go to the region from 32,264,000 to 32,492,000 bp on human chromosome 13. On which cytogenetic band is this region located? How many contigs make up this portion of the assembly (contigs are contiguous stretches of DNA sequence that have been assembled solely based on direct sequencing information)?

2. Zoom in on the BRCA2 gene.

3. Configure this page to turn on the LTR (repeat) track in this view. What tool was used to annotate the LTRs according to the track information? How many LTRs can you see within the BRCA2 gene? Do any overlap exons?

4. Create a Share link for this display. Email it to your neighbour. Open the link they sent you and compare. If there are differences, can you work out why?

5. Export the genomic sequence of the region you are looking at in FASTA format.

6. Turn off all tracks you added to the Region in detail page.

Go to the Ensembl homepage.

1. Go to the region from 150,320,000 to 150,540,000 bp on mouse chromosome 5. How many contigs make up this portion of the assembly (contigs are contiguous stretches of DNA sequence that have been assembled solely based on direct sequencing information)?

2. Zoom in on the Brca2 gene.

3. Configure this page to turn on the LTR (repeat) track in this view. What tool was used to annotate the LTRs according to the track information? How many LTRs can you see within the Brca2 gene? Do any overlap exons?

4. Create a Share link for this display. Email it to your neighbour. Open the link they sent you and compare. If there are differences, can you work out why?

5. Export the genomic sequence of the region you are looking at in FASTA format.

6. Turn off all tracks you added to the Region in detail page.

Go to the Ensembl Plants homepage and do the following:

1. Go to the region 1:405000-453000 in Oryza sativa Japonica.

2. Turn on the AGILENT:G2519F-015241 microarray track. Are there any oligo probes that map to this region?

3. Highlight the region around any reverse strand probes you can see. Do they map to any transcripts?

Go to Ensembl Fungi. Let’s try to find some information about the region from 1,400,000 to 1,425,000 in chromosome 7 in Coprinopsis cinerea okayama:

1. How many complete genes are found in this region? How many on the forward and how many on the reverse strand?

2. Zoom in on the largest gene EFI27358. How many exons does this gene have?

3. Export the genomic sequence in FASTA format for this region.

Go to Ensembl Bacteria and do the following:

1. Search for the Salmonella enterica subsp. enterica serovar Typhi str. Ty2 (GCA_000007545) (Hint: type Ty into the Search for a genome box).

2. Go to the region Chromosome:2000605-2009742.

3. How many genes are annotated in this region? How many are on the forward strand? How many are on the reverse strand?

You can find out lots of information about Ensembl genes and transcripts using the browser. If you’re already looking at a region view, you can click on any transcript and a pop-up menu will appear, allowing you to jump directly to that gene or transcript.

Alternatively, you can find a gene by searching for it. You can search for gene names or identifiers, and also phenotypes or functions that might be associated with the genes.

We’re going to look at the human UQCRQ gene. From ensembl.org, type UQCRQ into the search bar and click the Go button. You will get a list of hits with the human gene at the top.

Where you search for something without specifying the species, or where the ID is not restricted to a single species, the most popular species will appear first, in this case, human, mouse and zebrafish appear first. You can restrict your query to species or features of interest using the options on the left.

The gene tab

Click on the gene name or Ensembl ID. The Gene tab should open:

This page summarises the gene, including its location, name and equivalents in other databases. At the bottom of the page, a graphic shows a region view with the transcripts. We can see exons shown as blocks with introns as lines linking them together. Coding exons are filled, whereas non-coding exons are empty. We can also see the overlapping and neighbouring genes and other genomic features.

There are different tabs for different types of features, such as genes, transcripts or variants. These appear side-by-side across the blue bar, allowing you to jump back and forth between features of interest. Each tab has its own navigation column down the left hand side of the page, listing all the things you can see for this feature.

Let’s walk through this menu for the gene tab. How can we view the genomic sequence? Click Sequence at the left of the page.

The sequence is shown in FASTA format. The FASTA header contains the genome assembly, chromosome, coordinates and strand (1 or -1) – this gene is on the positive strand.

Exons are highlighted within the genomic sequence, both exons of our gene of interest and any neighbouring or overlapping gene. By default, 600 bases are shown up and downstream of the gene. We can make changes to how this sequence appears with the blue Configure this page button found at the left. This allows us to change the flanking regions, add variants, add line numbering and more. Click on it now.

Once you have selected changes (in this example, Show variants, 1000 Genomes variants and Line numbering) click at the top right.

You can download this sequence by clicking in the Download sequence button above the sequence:

This will open a dialogue box that allows you to pick between plain FASTA sequence, or sequence in RTF, which includes all the coloured annotations and can be opened in a word processor. If you want run a sequence analysis tool, download as FASTA sequence, whereas if you want to analyse the sequence visually, RTF is best for this. This button is available for all sequence views.

To find out what the protein does, have a look at GO terms from the Gene Ontology consortium. There are three pages of GO terms, representing the three divisions in GO: Biological process (what the protein does), Cellular component (where the protein is) and Molecular function (how it does it). Click on GO: Biological process to see an example of the GO pages.

Here you can see the functions that have been associated with the gene. There are three-letter codes that indicate how the association was made, as well as links to the specific transcript they are linked to.

We also have links out to other databases which have information about our genes and may focus on other topics that we don’t cover, like Gene Expression Atlas or OMIM. Go up the left-hand menu to External references:

Demo: The transcript tab

We’re now going to explore the different transcripts of UQCRQ. Click on Show transcript table at the top.

Here we can see a list of all the transcripts of UQCRQ with their identifiers, lengths, biotypes and flags to help you decide which ones to look at.

If we were to only choose one transcript to analyse, we would choose UQCRQ-203 because it is the MANE Select and Ensembl Canonical. This means it is both 100% identical to the RefSeq transcript NM_014402.5 and both Ensembl and NCBI agree that it is the most biologically important transcript.

Click on the ID, ENST00000378670.8.

You are now in the Transcript tab for UQCRQ-203. We can still see the gene tab so we can easily jump back. The left hand navigation column provides several options for the transcript UQCRQ-203 - many of these are similar to the options you see in the gene tab, but not all of them. If you can’t find the thing you’re looking for, often the solution is to switch tabs.

Click on the Exons link. This page is useful for designing RT-PCR primers because you can see the sequences of the different exons and their lengths.

You may want to change the display (for example, to show more flanking sequence, or to show full introns). In order to do so click on Configure this page and change the display options accordingly.

Now click on the cDNA link to see the spliced transcript sequence with the amino acid sequence. This page is useful for mapping between the RNA and protein sequences, particularly genetic variants.

UnTranslated Regions (UTRs) are highlighted in dark yellow, codons are highlighted in light yellow, and exon sequence is shown in black or blue letters to show exon divides. Sequence variants are represented by highlighted nucleotides and clickable IUPAC codes are above the sequence.

Next, follow the General identifiers link at the left. Just like the External References page in the gene tab, this page shows links out to other databases such as RefSeq, UniProtKB, PDBe and others, this time linked to the transcript or protein product, rather than the gene.

If you’re interested in protein domains, you could click on Protein summary to view domains from Pfam, PROSITE, Superfamily, InterPro, and more. These are all plotted against the transcript sequence, with the exons shown in alternating shades of purple at the top of the page. Alternatively, you can go to Domains & features to see a table of the same information.

You can also see the structure of the protein from the PDB by clicking on PDB 3D Protein model.

This uses LiteMol to show a 3D protein. You can use all the normal controls that you would use with LiteMol, plus plot Ensembl features like Exons and variants onto the structure using the options on the right. We allow you to see the top ten PDB models for this protein, based on coverage and quality scores, you can choose which at the top of the viewer.

1. In Ensembl, find the human MYH9 (myosin, heavy chain 9, non-muscle) gene and open the Gene tab.
   • On which chromosome and which strand of the genome is this gene located?
   • How many transcripts (splice variants) are there and how many are protein coding?
   • What is the longest protein-coding transcript, and how long is the protein it encodes?
   • Which transcript would you take forward for further study?

2. Click on Phenotypes at the left side of the page. Are there any diseases associated with this gene, according to Mendelian Inheritance in Man (MIM)?

3. What are some functions of MYH9 according to the Gene Ontology (GO) consortium? Have a look at the GO: Biological process pages for this gene.

4. In the transcript table, click on the transcript ID for MYH9-201, and go to the Transcript tab.
   • How many exons does it have?
   • Are any of the exons completely or partially untranslated?
   • Is there an associated sequence in UniProtKB/Swiss-Prot? Have a look at the General identifiers for this transcript.
5. Are there microarray (oligo) probes that can be used to monitor ENST00000216181 expression?

Phenylketonuria is a genetic disorder caused by an inability to metabolise phenylalanine in any body tissue. This results in an accumulation of phenylalanine causing seizures and intellectual disability.

(a) Search for phenylketonuria from the Ensembl homepage and narrow down your search to only genes. What gene is associated with this disorder?

(b) How many protein coding transcripts does this gene have? View all of these in the transcript comparison view.

(c) What is the MIM gene identifier for this gene?

(d) Go to the MANE Select transcript and look at its 3D structure. In the model 2pah, how many protein molecules can you see?

Genetic variation in the dipeptidylpeptidase 6 Gene (DPP6) in humans has previously been strongly associated with amyotrophic lateral sclerosis (ALS), a lethal disorder caused by progressive degeneration of motor neurons in the brain.

1. Go to the Ensembl homepage, search for the Dpp6 gene in mouse and click on the transcript ID ENSMUST00000071500 to open the transcript tab. How many exons make up this transcript?

2. Click on Exons to display the exon sequences of the transcript. Which exon contains the translation start? What is the exon ID of the largest exon? What is the start and end phase of exon 2?

3. Go to the Protein summary. How many protein domains or features fall within the second exon? What is the Pfam protein domain at the C-terminus of the protein and how many exons does it fall into? Which amino acid positions does the domain above cover?

4. Go to Domains and features. Which domains are associated with Pfam? How many genes in the mouse genome have the IPR002469 domain? What chromosomes are these genes found on?

1. Find the Arabidopsis thaliana CCD7 gene on Ensembl Plants. On which chromosome and which strand of the genome is this gene located?

2. Where in the cell is the CCD7 protein located?

3. What is the source of the assigned gene name?

4. How many transcripts does it have? How long is its longest transcript (in bp)? How long is the protein it encodes? How many exons does it have? Are any of the exons completely or partially untranslated?

Start in Ensembl Bacteria and select the Clostridium sporogenes (GCA_001444695) genome.

1. What GO: biological process terms are associated with the PolC gene?

2. Go to the transcript tab for the only transcript, OQP95999. How long is the transcript?

3. What domains can be found in the protein product of this transcript? How many different domain prediction methods agree with each of these domains?

Start in Ensembl Bacteria and search for the Escherichia coli str. K-12 substr. MG1655 (GCA_000005845) genome.

1. What GO: biological process terms are associated with the Era gene?

2. How many different InterPro domains are found in the protein product of this gene?

3. What is the associated UniProt ID of the transcript?

We’re going to look at the gene ATG8 in Magnaporthe oryzae in Ensembl Fungi. This gene is involved in autophagy, and targeted silencing of this gene inhibits infection (you can find further info in Wilson and Talbot, Nature Reviews Microbiology volume 7, pages 185–195 (2009)).

1. Find the genomic sequence of the M. oryzae ATG8 gene. How many exons does the gene have?

2. What is the GO accession ID for this gene?

3. How many transcripts does the gene have? Download the cDNA sequence in FASTA format to your computer.

4. Are there any entries of the gene in external databases? If so, which ones?

1. Find the Plasmodium falciparum PF3D7_1145400 gene on Ensembl Protists. On which strand is this gene located? What are the coordinates of the gene?

2. How long is its transcript (in bp)? How long is the protein it encodes? How many exons does it have?

3. What is the Uniprot ID that maps to the translation of this transcript?

4. What are the GO:Biological process(es) associated with PF3D7_1145400?

In any of the sequence views shown in the Gene and Transcript tabs, you can view variants on the sequence. You can do this by clicking on Configure this page from any of these views.

Let’s take a look at the Gene sequence view for HBB in human. Search for HBB and go to the Sequence view.

If you can’t see variants marked on this view, click on Configure this page and select Show variants: Yes and show links. You may also wish to add a filter to the variants to allow them to load more quickly, we’ll add Filter variants by evidence status: 1000Genomes.

Find out more about a variant by clicking on it.

You can add variants to all other sequence views in the same way.

You can go to the Variation tab by clicking on the variant ID. For now, we’ll explore more ways of finding variants.

To view all the sequence variants in table form, click the Variant table link at the left of the gene tab.

You can filter the table to only show the variants you’re interested in. For example, click on Consequences: All, then select the variant consequences you’re interested in. For display purposes, the table above has already been filtered to only show missense variants.

You can also filter by the different pathogenicity scores and MAF, or click on Filter other columns for filtering by other columns such as Evidence or Class.

The table contains lots of information about the variants. You can click on the IDs here to go to the Variation tab too.

You can also see the phenotypes associated with a gene. Click on Phenotype in the left hand menu.

Open the transcript table and go to HBB-201 ENST00000335295, then click on Haplotypes in the left hand menu.

The Haplotypes view in the transcript tab shows you the actual protein and CDS sequences in 1000 Genomes individuals. This is possible because the 1000 Genomes study has phased genotypes, so we know which alleles occur on which of the chromosome pairs. The table lists all the versions of the protein that occur along with their frequencies, including the reference sequence and sequences with one or more alternative alleles.

Click on one of the haplotypes, we’ll go for 18K>*,​19del{130}, to find out more about it. Here you will see the frequency in the 1000 Genomes subpopulations, the sequence and the 1000 Genomes individuals where this protein is found.

Let’s have a look at variants in the Location tab. Click on the Location tab in the top bar.

Configure this page and open Variation from the left-hand menu.

There are various options for turning on variants. You can turn on variants by source, by frequency, presence of a phenotype or by individual genome they were isolated from. You can also turn on genotyping chips.

Let’s have a look at a specific variant. If we zoomed in we could see the variant rs334 in this region, however it’s easier to find if we put rs334 into the search box. Click through to open the Variation tab.

The icons show you what information is available for this variant. Click on Genes and regulation, or follow the link on the left.

This page illustrates the genes the variant falls within and the consequences on those genes, including pathogenicity predictors. It also shows data from GTEx on genes that have increased/decreased expression in individuals with this variant, in different tissues. Finally, regulatory features and motifs that the variant falls within are shown.

We can also see the variant in the protein structure by clicking on 3D Protein model.

This is a LiteMol viewer, where you can rotate and zoom in on the structure. The variant location is highlighted, so you can see where it lands within the structure.

Let’s look at population genetics. Click on Population genetics in the left-hand menu.

The population allele frequencies are shown by study, including 1000 Genomes and gnomAD. Where genotype frequencies are available, these are shown in the tables.

There are big differences in allele frequencies between populations. Let’s have a look at the phenotypes associated with this variant to see if they are known to be specific to certain human populations. Click on Phenotype Data in the left-hand menu.

This variant is associated with various phenotypes, including sickle cell and malaria resistance. These phenotype associations come from sources including the GWAS catalog, ClinVar, Orphanet and OMIM. Where available, there are links to the original paper that made the association, the allele that is associated with the phenotype and p-values and other statistics.

The SNP rs1738074 in the 5’ UTR of the human TAGAP gene has been identified as a genetic risk factor for a few diseases. Use Ensembl to answer the following questions:

1. In which transcripts is this SNP found?

2. What is the least frequent genotype for this SNP in the Yoruba (YRI) population from the 1000 Genomes phase 3?

3. What is the ancestral allele? Is it conserved in the 91 eutherian mammals EPO-Extended?

4. With which diseases is this SNP associated? Are there any known risk (or associated) alleles?

Variable number tandem repeats (VNTRs) show high variation in the number of repeats in the population and are commonly used in forensics (DNA fingerprinting) and to study genetic diversity. (a) Go to the region from 3074666 to 3075100 bp on human chromosome 4. Which gene does it overlap? Which exon of this gene falls in this region?

(b) Configure this page to turn on Repeats (low), Simple repeats (Repeats (low)) and Tandem repeats (TRF) tracks in this view. Can you see any repeats in this exon? What tools were used to annotate the repeats according to the track information?

(c) Zoom in on the (CAG)n to see its sequence. How many CAG repeats can you see in the human reference assembly? Does this track overlap any phenotype-associated variants? What is the identifier of this variant?

(d) Go to the variant tab of the phenotype-associated variant. What is the consequence ontology of this variant? Does the reference allele match the number of repeats you have just counted? What is the shortest and longest allele?

In the paper “Altered metabolic signature in pre-diabetic NOD mice” (PloS One. 2012; 7(4): e35445), Madsen et al. have described several regulatory and coding SNPs, some of them in genes involved in ATP and adenosine metabolism, leading to potentially faulty metabolism of ATP and adenosine. The authors describe that one of the identified SNPs in the murine Entpd2 gene (rs28232063) would lead to increased amounts of available ATP, an immune activator, causing increased cell activation and possibly autoreactive T-cell activation. Use Ensembl to answer the following questions:

1. Where is the SNP located (chromosome and coordinates)?

2. What is the HGVS recommendation nomenclature for this SNP?

3. Why does Ensembl put the G allele first (G/A)?

4. Are there differences between the genotypes reported in C57BL/6NJ and NOD/ShiLtJ, according to the Mouse Genomes Project?

1. Go to Ensembl Plants and find the Solyc02g084570.3 gene in Solanum lycopersicum (tomato) and go to its Location tab. Can you see the variation track?

2. Zoom in around the last exon of this gene. What are the different types of variants seen in that region? Are any splice region variants mapped in the region? If so, what is/are the coordinate(s)?

1. How many species in Ensembl Fungi have variation data?

2. Select Fusarium oxysporum (FO2) and search for the FOXG_13574T0 gene. One of its upstream variants is SNP tmp_10_6610. What are the possible alleles for this polymorphic position? Which one is on the reference genome?

3. What is the most frequent allele at this position?

4. Which samples have the genotypes C|T and T|T?

We have identified five variants on human chromosome nine, C-> A at 128203516, an A deletion at 128328461, C->A at 128322349, C->G at 128323079 and G->A at 128322917.

We will use the Ensembl VEP to determine:

• Have my variants already been annotated in Ensembl?
• What genes are affected by my variants?
• Do any of my variants affect gene regulation?

Go to the front page of Ensembl and click on the Variant Effect Predictor.

This page contains information about the VEP, including links to download the script version of the tool. Click on Launch VEP to open the input form:

The data is in VCF format:
chromosome coordinate id reference alternative

Put the following into the Paste data box:
9 128328460 var1 TA T
9 128322349 var2 C A
9 128323079 var3 C G
9 128322917 var4 G A
9 128203516 var5 C A

The VEP will automatically detect that the data is in VCF.

There are further options that you can choose for your output. These are categorised as Identifiers, Variants and frequency data, Additional annotations, Predictions, Filtering options and Advanced options. Let’s open all the menus and take a look.

Hover over the options to see definitions.

We’re going to select some options:

• HGVS, annotation of variants in terms of the transcripts and proteins they affect, commonly-used by the clinical community
• Phenotypes
• Protein domains

When you’ve selected everything you need, scroll right to the bottom and click Run.

The display will show you the status of your job. It will say Queued, then automatically switch to Done when the job is done, you do not need to refresh the page. You can edit or discard your job at this time. If you have submitted multiple jobs, they will all appear here.

Click View results once your job is done.

In your results you will see a graphical summary of your data, as well as a table of your results.

The results table is enormous and detailed, so we’re going to go through the it by section. The first column is Uploaded variant. If your input data contains IDs, like ours does, the ID is listed here. If your input data is only loci, this column will contain the locus and alleles of the variant. You’ll notice that the variants are not neccessarily in the order they were in in your input. You’ll also see that there are multiple lines in the table for each variant, with each line representing one transcript or other feature the variant affects.

You can mouse over any column name to get a definition of what is shown.

The next few columns give the information about the feature the variant affects, including the consequence. Where the feature is a transcript, you will see the gene symbol and stable ID and the transcript stable ID and biotype. Where the feature is a regulatory feature, you will get the stable ID and type. For a transcription factor binding motif (labelled as a MotifFeature) you will see just the ID. Most of the IDs are links to take you to the gene, transcript or regulatory feature homepage.

This is followed by details on the effects on transcripts, including the position of the variant in terms of the exon number, cDNA, CDS and protein, the amino acid and codon change, transcript flags, such as MANE, on the transcript, which can be used to choose a single transcript for variant reporting, and pathogenicity scores. The pathogenicity scores are shown as numbers with coloured highlights to indicate the prediction, and you can mouse-over the scores to get the prediction in words. Two options that we selected in the input form are the HGVS notation, which is shown to the left of the image below and can be used for reporting, and the Domains to the right. The Domains list the proteins domains found, and where there is available, provide a link to the 3D protein model which will launch a LiteMol viewer, highlighting the variant position.

Where the variant is known, the ID of the existing variant is listed, with a link out to the variant homepage. In this example, only rsIDs from dbSNP are shown, but sometimes you will see IDs from other sources such as COSMIC. The VEP also looks up the variant in the Ensembl database and pulls back the allele frequency (AF in the table), which will give you the 1000 Genomes Global Allele Frequency. In our query, we have not selected allele frequencies from the continental 1000 Genomes populations or from gnomAD, but these could also be shown here. We can also see ClinVar clinical significance and the phenotypes associated with known variants or with the genes affected by the variants, with the variant ID listed for variant associations and the gene ID listed for gene associations, along with the source of the association.

For variants that affect transcription factor binding motifs, there are columns that show the effect on motifs (you may need to click on Show/hide columns at the top left of the table to display these). Here you can see the position of the variant in the motif, if the change increases or decreases the binding affinity of the motif and the transcription factors that bind the motif.

Above the table is the Filter option, which allows you to filter by any column in the table. You can select a column from the drop-down, then a logic option from the next drop-down, then type in your filter to the following box. We’ll try a filter of Consequence, followed by is then missense_variant, which will give us only variants that change the amino acid sequence of the protein. You’ll notice that as you type missense_variant, the VEP will make suggestions for an autocomplete.

You can export your VEP results in various formats, including VCF. When you export as VCF, you’ll get all the VEP annotation listed under CSQ in the INFO column. After filtering your data, you’ll see that you have the option to export only the filtered data. You can also drop all the genes you’ve found into the Gene BioMart, or all the known variants into the Variation BioMart to export further information about them.

Resequencing of the genomic region of the human CFTR (cystic fibrosis transmembrane conductance regulator (ATP-binding cassette sub-family C, member 7) gene (ENSG00000001626) has revealed the following variants. The alleles defined in the forward strand:

• G/A at 7: 117,530,985
• T/C at 7: 117,531,038
• T/C at 7: 117,531,068

Use the VEP tool in Ensembl and choose the options to see SIFT and PolyPhen predictions. Do these variants result in a change in the proteins encoded by any of the Ensembl genes? Which gene? Have the variants already been found?

7	117530985	117530985	G/A
7	117531038	117531038	T/C  
7	117531068	117531068	T/C

We have identified a few variants in Atlantic salmon (Salmo salar):

• chr 28, genomic coordinate 1777645, alleles C/T
• chr 28, genomic coordinate 1777906, alleles G/A
• chr 28, genomic coordinate 1786995, alleles T/G

(a) Which genes and transcripts do these variants map to?

(b) Do these variants result in a change in the proteins encoded by any of the Ensembl genes? Which genes?

You’ll find a VCF file here. This is a small subset of the outcome of Oryza sativa Japonica whole-genome sequencing and variant-calling experiment. Analyse the variants in this file with the VEP tool in Ensembl Plants and determine the following:

1. How many genes and transcripts are affected by variants in this file?

2. Do these variants result in a change in the proteins encoded by any of the Ensembl genes? Which genes are affected? What is the amino acid change?

You have done whole-genome sequencing and variant-calling experiments for Triticum aestivum. You have a VCF file with a small subset of variants from this experiment. Analyse the variants in this file with the VEP tool in Ensembl Plants and determine the following:

1. How many variants were analysed? How many are novel?

2. How many genes and transcripts are affected by variants in this file?

3. Do any of the variants have different consequences for different transcripts?

4. Filter the table to find variants with high impact. How many variants have high impact? Why do you think missense variants are not classified as high impact?

5. Can you export all the results to a VCF file? Compare it to the input VCF file to see what information the VEP adds.

We have identified four variants in Verticillium dahliae JR2 chromosome 5:

• C->G at 698711
• G->T at 698935
• G->A at 700313
• C->A at 701484

Use VEP in Ensembl Fungi to answer the following questions:

1. Have these variants already been annotated in Ensembl?

2. What genes are affected by the variants? What are their gene IDs?

3. Are any of the variants predicted to be missense variants?

5 698711 698711 C/G
5 698935 698935 G/T
5 700313 700313 G/A
5 701484 701484 C/A

In Ensembl Bacteria the genome for Bacteroides fragilis 638R and launch the VEP tool. Use VEP to predict the effects of a 7 bp deletion of TCTACAA on the supercontig FQ312004 at the position 258140-258146. Use the results to answer the following questions:

1. How many genes does the indel overlap? What are their gene symbols?

2. What is the most common consequence of the variant?

3. What is the most severe consequence? What gene does it affect and what does it do?

Let’s look at the homologues of human BRCA2. Search for the gene and go to the Gene tab.

Click on Gene tree, which will display the current gene in the context of a phylogenetic tree used to determine orthologues and paralogues.

Funnels indicate collapsed nodes. We can expand them by clicking on the node and selecting Expand this sub-tree from the pop-up menu.

We can also see the alignment of the sub-tree by clicking on Wasabi viewer, which will open a pop-up:

You can download the tree in a variety of formats. Click on the download icon in the bar at the top of the image to get a pop-up where you can choose your format.

We can look at homologues in the Orthologues and Paralogues pages, which can be accessed from the left-hand menu. If there are no orthologues or paralogues, then the name will be greyed out. Paralogues is greyed out for BRCA2 indicating that there are no paralogues available. Click on Orthologues to see the 175 orthologues available.

Choose to see only Rodents and related species orthologues by selecting the box. The table below will now only show details of rodent orthologues. Let’s look at mouse.

Links from the orthologue allow you to go to alignments of the orthologous proteins and cDNAs. Click on View Sequence Alignments then View Protein Alignment for the mouse orthologue.

Let’s look at some of the comparative genomics views in the Location tab. Go to the region 2:176087000-176202000 in human, which contains the HoxD cluster which is involved in limb development and is highly conserved between species.

You can turn on conservation scores and constrained elements. Click on Configure this page, then Comparative genomics and turn on the tracks for Constrained elements for 91 eutherian mammals EPO-Extended and Conservation score for 91 eutherian mammals EPO-Extended. Save and close the menu.

You can now see the conservation scores in pale pink. These were used to determine the peaks indicated in the constrained elements track in dark pink. This track indicates regions of high conservation between species, considered to be “constrained” by evolution.

We can also look at individual species comparative genomics tracks in this view by clicking on Configure this page.

Select BLASTz/LASTz alignments from the left-hand menu to choose alignments between closely related species. Turn on the alignments for Mouse, Chicken and Chimpanzee in Normal. Save and close the menu.

The alignment is greatest between closely related species.

We can also look at the alignment between species or groups of species as text. Click on Alignments (text) in the left hand menu.

Select Select an alignment to open the alignment menu.

Click through the links, Pairwise, Rodents & Lagomorphs, Rats and Mice to select Mouse reference (CL57BL6).

In this case there are two blocks aligned, Block 1 a large (115001 bp) alignment against mouse chr2 and one smaller block against mouse chr7. Click on Block 1.

You will see a list of the regions aligned, followed by the sequence alignment. Click on Display full alignment. Exons are shown in red.

To compare with both contigs visually, go to Region comparison.

To add species to this view, click on the blue Select species or regions button. Choose Mouse Reference again then close the menu.

You can configure this view for both species. Click on Configure this page and look in the top left of the menu.

The drop down allows you to configure each species separately.

We can view large scale syntenic regions from our chromosome of interest. Click on Synteny in the left hand menu.

Go to Ensembl to answer the following questions:

1. How many orthologues are predicted for the human BRAF in primates? How much sequence identity does the Carlito syrichta (tarsier) protein have to the human one? Can you tell which end of the BRAF protein is more conserved between these two species by looking at the orthologue alignment?

2. Go to the Gene tree for this gene. View the Wasabi alignment of all the proteins in primates. Can you see a large gap in the alignment around position 450? Which species match the human sequence?

(a) Find the human BRCA2 gene and go to the Region in detail page. Turn on the BLASTz/LASTz alignment tracks for chicken, chimp, mouse and platypus. Does the degree of conservation between human and the various other species reflect their evolutionary relationship? Which parts of the BRCA2 gene seem to be the most conserved? Did you expect this?

(b) Have a look at the Conservation score and Constrained elements tracks for the set of 90 eutherian mammals and 65 amniota vertebrates. Do these tracks confirm what you already saw in the pairwise alignment tracks?

(c) Retrieve the genomic alignment (text) across 65 amniotes for a constrained element matching up with exon 15 of the golden transcript. Highlight the bases that match in >50% of the species in the alignment. Is this sequence exonic in all species?

You find a deletion in the mouse genome that severely affects development, and you want to investigate it. In Ensembl, go to this region (base pair coordinates 136197000-136283000 on mouse chromosome 4).

1. How many protein coding transcripts does the gene in this region have?

2. You want to see if any of these transcripts might be expressed in brain tissue. Turn on the RNASeq gene model for brain.

3. Find this same view (Region in Detail) for the human orthologue of the mouse gene.

4. To understand crucial variants, you want to investigate if there are any missense variants in the most diverse population available. Turn on the 1000 Genomes AFR (African population) track.

The fumarase gene FUM1 in Arabidopsis thaliana encodes a protein with mitochondrial targeting information. Read more in this UniProt entry. Go to Ensembl Plants to answer the following questions:

1. How many orthologues have been identified for this gene?

2. Which orthologue has the highest sequence similarity? Look at the Query%ID and Target%ID.

Go to Ensembl Plants and answer the following questions:

1. How many orthologues are predicted for the Triticum aestivum (wheat) gene RHT1 (gene ID TraesCS4D02G040400) gene in Liliopsida?

2. How much sequence identity does the Secale cereale (rye) protein have to the maize one?

3. Download the alignment in Nexus format.

4. Open the gene tree for the wheat RHT1 gene. What is the gene tree ID?

5. How many speciation and duplication nodes does the phylogeny have?

Go to Ensembl Plants and answer the following questions:

1. Find the TraesCS2D02G080000 gene in Triticum aestivum (wheat). What is the function for this gene and what are its coordinates?

2. Go to the Location tab. Turn on the LASTZ-net alignment tracks for Arabidopsis thaliana, Zea mays (corn) and Sorghum bicolor (great millet). Are there any regions where you can see gaps in in some of the species alignments?

3. Go to the Region comparison view and compare to A. thaliana. What occurs at this gap in the alignment?

4. Export the Block 2 alignment between T. aestivum and A. thaliana in ClustalW format.

Search Ensembl Plants for the gene Lsi1 in Oryza sativa Japonica (rice). This gene is known to code for an aquaporin transporter that facilitates the uptake of silicon and arsenic through the roots. Silicon concentration is highest in grass species, and is associated with defence.

1. From the gene tab, go to the Orthologues page under Plant Compara. Which plant group has the highest number of 1-to-1 orthologues? Is it the same group that has the highest number of 1-to-many orthologues?

2. Reduce the orthologues table to look only at Triticum aestivum (wheat) orthologues. Why are there three results for a 1-to-1 orthologue?

3. Click on the Compare regions link for chromosome 6B region in wheat to go to the Location tab. Scroll to the bottom image. How do the gene models compare between the species? Do they have the same number of exons?

4. Click back to the Gene tab and click on the Gene gain/loss tree page. Which species has the highest number of members of this gene family? Is it a grass? Can you change the view to see a radial tree?

Bacillus subtilis subsp. subtilis str. 168 (GCA_000009045) is a model organism and often used in academic research and in the biotechnology industry as it can produce large amounts of important enzymes, like protease and amylase. It is part of Pan-taxonomic Compara in Ensembl Bacteria. We will use the sipT gene, a type I signal peptidase, as a reference to find the following information:

1. Find the Ensembl gene tree ID. How many speciation and duplication nodes does it have?

2. How many orthologues does B. subtilis str. 168 have? What type of orthologues are they?

3. Does it have an orthologue in Escherichia coli str. K-12 substr. MG1655? If so, what is the gene ID and coordinate in E. coli?

4. Export the protein alignment of the B. subtilis and E. coli orthologues. What are the different formats you can export the alignment as?

Go to the Ensembl Fungi site to find out the following:

1. How many orthologues and how many paralogues are predicted for the Schizosaccharomyces pombe Mcm6 gene?

2. How many Schizosaccharomyces orthologues are there?

3. Does it have a human orthologue? If so what type is it and what is the orthologue’s Ensembl ID?

Follow these instructions to guide you through BioMart to answer the following query:

You have three questions about a set of human genes:
ESPN, MYH9, USH1C, CISD2, THRB, WHRN
(these are HGNC gene symbols. More details on the HUGO Gene Nomenclature Committee can be found on http://www.genenames.org)

1. What are the NCBI Gene IDs for these genes?
2. Are there associated functions from the GO (gene ontology) project that might help describe their function?
3. What are their cDNA sequences?

Click on BioMart in the top header of a www.ensembl.org page to go to: www.ensembl.org/biomart/martview

You cannot choose any filters or attributes until you’ve chosen your dataset. Your dataset is the data type you’re working with. In this case we’re going to choose human genes, so pick Ensembl Genes then Human genes from the drop-downs.

Now that you’ve chosen your dataset, the filters and attributes will appear in the column on the left. You can pick these in any order and the options you pick will appear.

Click on Filters on the left to see the available filters appear on the main page. You’ll see that there are loads of categories of Filters to choose from. You can expand these by clicking on them. For our query, we’re going to expand GENE.

Our input data is a list of identifiers, so we’re going to use the Input external references ID list filter. This allows us to input a list of identifiers from different databases. We need to choose what kind of identifier we’re using, so that BioMart can look up the right column in a data table. You can pick these from a drop-down list, which lists the type of identifier with an example of how it looks. For our query, we have a list of gene names, so we need to pick Gene Name(s).

To check if the filters have worked, you can use the Count button at the top left, which will show you how many genes have passed the filter. If you get 0 or another number you don’t expect, this can help you to see if your query was effective.

To choose the attributes, expand this in the menu. There are six categories for human gene attributes. These categories are mutually exclusive, you cannot pick attributes from multiple categories. This means that we need to do two separate queries to get our GO terms and NCBI IDs, and to get our cDNA sequences.

The Ensembl gene and transcript IDs, with and without version numbers are selected by default. The selected attributes are also listed on the left.

We can choose the attributes we want by clicking on them. For our query, we’re going to select:

• GENE
  • Gene Name
• EXTERNAL
  • NCBI gene ID
  • GO term accession
  • GO term name
  • GO term definition

We need to select the Gene Name in order to get back our original input, as this is not returned by default in BioMart. The order that you select the attributes in will define the order that the columns appear in in your output table.

You can get your results by clicking on Results at the top left.

The results table just gives you a preview of the first ten lines of your query. This allows the results to load quickly, so that if you need to make any changes to your query, you don’t waste any time. To see the full table you can click on View ## rows. You can also export the data to an xls, tsv, csv or html file. For large queries, it is recommended that you export your data as Compressed web file (notify by email), to ensure your download is not disrupted by connection issues.

You can see multiple rows per gene in your input list, because there are multiple transcripts per gene and multiple GO terms per transcript.

To get the cDNA sequences, go back to the Attributes then select the category Sequences and expand SEQUENCES.

When you select the sequence type, the part of the transcript model you’ve chosen will be highlighted in the grpahic.

Choose cDNA sequences, then expand HEADER INFORMATION to add Gene Name to the header. Then hit Results again.

For more details on BioMart, have a look at this publication:

Kinsella, R.J. et al
Ensembl BioMarts: a hub for data retrieval across taxonomic space.
http://europepmc.org/articles/PMC3170168

Find mouse proteins with Signalp cleavage sites located on chromosome 9.

Go to Ensembl’s BioMart. For a list of Ciona savignyi Ensembl genes, export the human orthologues:
ENSCSAVG00000000002, ENSCSAVG00000000003, ENSCSAVG00000000006, ENSCSAVG00000000007, ENSCSAVG00000000009, ENSCSAVG00000000011

Do all of these genes have a homologue in human?

BioMart is a very handy tool when you want to convert IDs from different databases. The following is a list of 29 IDs of human proteins from the NCBI RefSeq database:
NP_001218, NP_203125, NP_203124, NP_203126, NP_001007233, NP_150636, NP_150635, NP_001214, NP_150637, NP_150634, NP_150649, NP_001216, NP_116787, NP_001217, NP_127463, NP_001220, NP_004338, NP_004337, NP_116786, NP_036246, NP_116756, NP_116759, NP_001221, NP_203519, NP_001073594, NP_001219, NP_001073593, NP_203520, NP_203522

Use BioMart in Ensembl to generate a list that shows to which Ensembl gene IDs and to which gene names these RefSeq IDs correspond. Do these 29 transcripts correspond to 29 genes?

Go to Ensembl Plants and find the following information:

Retrieve the protein sequences (in FASTA format) of all Triticum aestivum (wheat) genes that have an NCBI Gene ID, that are protein-coding and with Transmembrane helices. Do a count after the selection of each filter to check the number of genes remaining in your dataset. Export the results of the sequences and select Gene description and Source of gene name as headers.

BioMart is a very handy tool when you want to map between different databases. The following is a list of IDs from the UniProtKB/Swiss-Prot database of Arabidopsis thaliana proteins that are supposedly involved in flavonoid metabolism: P42813, Q9LS08, Q9ZST4, Q9SYM2, P51102, Q9LPV9, Q9FE25, Q96323, Q9FKW3, P13114, P41088, Q9S818, Q96330, O22203, Q39224, O22264, Q9SD85, Q9LYT3, Q9FJA2, Q43128, P43254, O04153, Q43125, Q9S9P6, Q94C57, Q9LNE6, Q9FK25, Q9SYM5, Q9ZQ95

Using BioMart in Ensembl Plants a list that shows to which Ensembl Gene IDs these UniProtKB/Swiss-Prot IDs map. Also include the gene name and description.

In Ensembl Fungi, retrieve the variation ID, chromosome name, position in bp and alleles for all sequence variants in the mtDNA. Export the results as an XLS table and have the results sent to you by email.

Go to Ensembl Protists. For a list of , export the Find Leishmania major orthologues for these Trypanosoma brucei genes: Tb927.3.3470, Tb927.3.3520, Tb11.01.7770, Tb927.8.5110, Tb927.1.1420