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 Arabidopsis thaliana PAI1 gene. From plants.ensembl.org, type PAI1 into the search bar and click the Go button.

The gene tab

Click on PAI1 from the search hits. 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 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 Expression Atlas or UniProtKB. Go up the left-hand menu to External references:

Demo: The transcript tab

We’re now going to explore the different transcripts of PAI1. Click on Show transcript table at the top.

Here we can see a list of all the transcripts of PAI1 with their identifiers, lengths and biotypes. Click on the ID of the Ensembl Canonical transcript, PAI1-211.

You are now in the Transcript tab for PAI1-211. We can still see the gene tab so we can easily jump back. The left hand navigation column provides several options for the transcript PAI1-211 - 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.

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?

1. Search for Oxygen evolving enhancer protein from the Ensembl Plants homepage and narrow down your search to Triticum aestivum. How many genes are there with this name in wheat? Why do you think this is? What chromosomes are they on?

2. Go to the gene on chromosome 2B. How many protein-coding transcripts does this gene have? What is a “canonical transcript”?

3. Click on the canonical transcript. How many exons does this transcript have? Export the protein sequence of this transcript in the FASTA format.

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

1. What genes are found on chromosome 9, between 15274000 and 15300000 in Oryza sativa Japonica?
2. What are the NCBI Gene IDs for these genes?
3. Are there associated functions from the GO (gene ontology) project that might help describe their function?
4. What are their cDNA sequences?

Click on BioMart in the top header of a plants.ensembl.org page to go to: plants.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 Plants Genes then Oryza sativa Japonica Group 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 REGION.

Our input data is a locus, so we’re going to use the chromosome and coordinates filters. Choose chromosome 9 from the drop-down menu and paste in the start and the end coordinates (15274000 and 15300000). The filters will be autoselected when you add values to them and will appear in the left-hand column.

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 five categories for rice 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 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

One class of disease resistance (R) genes in plants are the TIR-NBS-LRR genes, that code for proteins that contain an N-terminal Toll/Interleukin receptor homology region (TIR), a nucleotide binding site (NBS) and a C-terminal leucine rich repeat (LRR). TIR-NBS-LRR genes are common in dicots but seem to be rare in monocots (Tarr and Alexander. TIR-NBS-LRR genes are rare in monocots: evidence from diverse monocot orders. BMC Res Notes 2009 Sep 8;2:197).

The ID for the TIR domain in the Pfam (protein family) database is PF01582.

Use BioMart in Ensembl Plants to generate a list of all Solanum tuberosum (potato; a dicot) genes that are annotated to contain a TIR domain. Include the Ensembl stable ID and gene description. Do the same for Zea mays (maize; a monocot).

Do your results confirm the findings of Tarr and Alexander?

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.

The following is a list of 101 probes that were upregulated after short-term phosphate deprivation of Arabidopsis thaliana. The microarray used was the Arabidopsis thaliana whole genome Affymetrix gene chip (ATH1) (Misson et al. A genome-wide transcriptional analysis using Arabidopsis thaliana Affymetrix gene chips determined plant responses to phosphate deprivation. Proc Natl Acad Sci U S A. 2005 August 16; 102(33): 11934–11939).

259842_at, 251193_at, 259303_at, 252534_at, 266957_at, 257891_at, 263593_at, 266372_at, 265342_at, 254011_at, 260623_at, 262238_at, 264118_at, 256910_at, 263846_at, 249996_at, 248094_at, 267361_at, 246275_at, 258034_at, 248622_at, 263483_at, 254250_at, 257964_at, 248566_s_at, 245263_at, 264636_at, 264342_at, 254125_at, 262369_at, 259399_at, 251770_at, 266132_at, 246001_at, 246075_at, 258887_at, 258856_at, 263391_at, 256376_s_at, 266766_at, 258277_at, 266142_at, 246071_at, 261021_at, 251143_at, 252730_at,249337_at, 258158_at, 245882_at, 250054_at, 263539_at, 263851_at, 247949_at, 262229_at, 246777_at, 258975_at, 247026_at, 252265_at, 256100_at, 246099_at, 246302_at, 254111_at, 256017_at, 259750_at, 254215_at, 253271_s_at, 247314_at, 267567_at, 250435_at, 255543_at, 259479_at, 264783_at, 245193_at, 260561_at, 263948_at, 258682_at, 253386_at, 263847_at, 266017_at, 252414_at, 255360_at, 251176_at, 266743_at, 253829_at, 267497_at, 258613_at, 253163_at, 261648_at, 258100_at, 249983_at, 266413_at, 264261_at, 256627_at, 249640_at, 248164_at, 266184_s_at, 247047_at, 263083_at, 251961_at, 252011_at, 260101_at

(a) Generate a list of the genes to which these probesets map. Include the Ensembl Gene ID, name, description and probe ID attributes.

(b) As a first step in order to be able to analyse them for possible regulatory features they have in common, retrieve the 250 bp upstream of the transcripts of these genes. Include the Ensembl Gene ID, name and description attributes in the sequence header.

Demo: Upload small files

We have some Arabidopsis mutants characterised by increased plant branching. They all have large scale deletions on chromosome one:

We can turn them into a BED file and view them in the genome browser:

chr1 25982154 25984234 M1
chr1 25983076 25985306 M2
chr1 25984552 25986469 M3

You can add data from a Region in Detail page by clicking on the Custom tracks button at the left. Alternatively, go to a species homepage and click on Display your data in Ensembl Plants.

A menu will appear:

The interface detects file types if you upload or attach a file. When you paste in your data, it can’t do this so we have to tell it what our file type is. It will give you an option where you can select BED.

Click Add data.

You should get to a dialogue box telling you your upload has been successful.

Click on the genomic coordinates link to go to the nearest region with data.

To have a look at the file, click on Custom tracks.

If you’ve got an Ensembl account, you can save this data to your account. Accounts are free to set up and allow you to save configurations and data, and share with groups. You can also permanently delete or temporarily disconnect data from here.

Demo: Attach URLs of large files

Larger files, such as BAM files generated by NGS, need to be attached by URL. You can find seedling RNAseq reads from the 19 genomes project aligned to the Arabidopsis thaliana assembly here: http://mtweb.cs.ucl.ac.uk/mus/www/19genomes/RNA.seedlings.BAM/v9/Col_0.R1.9.bam

Let’s take a look at the folder.

Here you can see a number of BAM files (.bam) with corresponding index files (.bam.bai). We’re interested in the files Col_0.R1.9.bam and Col_0.R1.9.bam.bai. These files are the BAM file and the index file respectively. When attaching a BAM file to Ensembl, there must be an index file in the same folder.

To attach the file, click on Custom tracks, then click on Add more data to add a new track.

We get to the same dialogue box as before. This time we’ll name our data RNAseq reads.

Paste in the URL of the BAM file itself (http://mtweb.cs.ucl.ac.uk/mus/www/19genomes/RNA.seedlings.BAM/v9/Col_0.R1.9.bam).

Since this is a file, the interface is able to detect the “.BAM” file extension, so automatically labels the format as BAM. Click on Add data. You should get to a dialogue box telling you your data has been attached successfully. Close the menu to go back to your region of interest.

Let’s go to the region of the AT1G51745 gene. Search for the gene using the Gene text box and click Go.

We can zoom in to see the sequence itself. Drag out boxes in the view to zoom in, until you see a view like this. Alternatively, type 1:19194595-19194630 in the Location box and clicking Go to jump to a smaller region.

Any mismatches between the reads and the reference genome assembly are shown in red.

Demo: Track hub registry

Track Hub Registry provides publicly available data organised in track hubs. Ensembl established a pipeline for generating track hubs for all public RNA-Seq studies in the INSDC archives. This pipeline discovers and aligns reads from RNA-Seq studies across all plant species in Ensembl Plants, which means that you can search the Track Hub Registry for available RNA-Seq data and display them in the genome browser.

You can search for track hubs to add in different ways:

• Search for track hubs in the Track Hub Registry and choose to add them to your genome browser of choice.
• Search the track hub registry using the Track Hub Registry interface in Ensembl Plants (there is a link from the homepage).

We will now add the track hub containing data on epigenetic regulation of transcription initiation in Arabidopsis (DRP006159).

You can add track hubs to view in Ensembl directly via the Track Hub Registry. Go to the Track Hub Registry homepage and search for DRP006159.

There is one RNA-seq alignment hub returned, which you can view in the genome browser.

Alternatively, you can add track hubs by searching the Track Hub Registry through Ensembl. Click the Custom tracks -> Track Hub Registry Search in any region view within Ensembl.

You can only find track hubs for the selected species and assembly denoted in the search box.

Search for DRP006159.

Click Attach this hub in the search results page.

Track Hubs often contain vast amounts of data, which can slow Ensembl down, so only add them if you need them, and trash them when you are finished with them.

Go to Configure this Page to see that a new category has been added to your menu. Add track for the DRR195395 run to the Region in Detail view by ticking the box.

This data represents genome-wide map of transcription start sites (TSSs) in A. thaliana mutants generated using CAGE-seq. Can you see the high reads coverage corresponding to the TSS of our AT1G51745 gene?

Here is a list of several genes linked to regulation of long-day photoperiodism in Arabidopsis thaliana.

AGL17, APRF1, CDF5, CDKD-2, CLF, COL9, EBS, EFM, ELF6, GI, JMJ14, LATE, MED16, MRG1, MRG2, MYB56, NFYC4, PEP, POL2A, SHW1, VOZ1, VOZ2

(a) Can you display these Arabidopsis genes on the karyotype? Can you find the location for all of these genes?

(b) Can you export this image?

(c) How can you delete this data?

Upload the ZM_wiggle.wig file to the Zea mays genome in Ensembl Plants. View this track across the region 1:2884000-2898000. What is the highest score in this region?

(a) How many publicly available track hubs are there for the Solanum lycopersicum genome?

(b) Add the RNASeq-er alignment hub for ENA runs in ERP022223 track hub containing Illumina RNA-seq data of tomato roots colonized by the plant growth-promoting rhizobacterium Pseudomonas fluorescens strain CREA-C16. Search for Solyc07g065860.3, a tomato orthologue of the Arabidopsis RGI3 gene involved in regulation of root development root meristem growth. Is this gene expressed?

(c) Go to the region 7:67591664-67591688. Can you see any mismatches between reads and the reference assembly? Are they real SNPs or sequencing errors?