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

At the top left you can see the current release number and what has come out in this release.

Click on View full list of all species.

Click on the common name of your species of interest to go to the species homepage. We’ll click on Arabidopsis thaliana.

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

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.

(a) Go to the species homepage for the plant Arabidopsis thaliana. What is the name of the genome assembly for Arabidopsis thaliana?

(b) Click on More information and statistics. How long is the Arabidopsis thaliana genome (in bp)? How many genes and transcripts have been annotated?

1. Are there any additional cultivars available alongside the Triticum aestivum (IWGSC) reference genome?

2. Find the description of the wheat assembly. Which institute provided the assembly and annotations?

3. How many coding and non-coding genes does the IWGSC assembly have?

4. Are there any other species of the genus Triticum available in Ensembl? If so, which species are they?

Find the species Oryza sativa Japonica in Ensembl Plants. How many coding and non-coding genes does it have?

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?

Demo: Exploring genomic regions in Ensembl Plants

Start at the Ensembl Plants front page. 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: 1D:41289600-41345600. Choose Triticum aestivum from the species drop-down, then type (or copy and paste) these coordinates into the search box.

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.

1. 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 in the corner.

1. 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.

1. 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.

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:

• EMS-induced mutation variants
• Type I Transposons/LINE (Repeats: Repbase)

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.

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.

Due to hybridisations in wheat’s evolutionary history, it has a hexaploid genome with related homoeologous regions. We can compare these with the Polyploid view. First, let’s zoom in on the gene TraesCS1D02G061000 by dragging out a box around it and clicking on Jump to region. Now click on the Polyploid view link in the left-hand menu.

This view also allows us to configure the page, as we could with the main region view, so that we can compare other features between the homoeologous chromosomes.

1. Go to 2D:378720500-378780600 in Triticum aestivum (wheat).

2. How many genes are in this region? What strand are the genes on? What are the gene IDs for these genes?

3. What tracks can you see that show gene structure? Where did the different tracks come from?

4. Export the genomic sequence for this region.

5. Can you view the genomic alignments of the homoeologous regions? What are the different formats you can export the image as?

Go to the Ensembl Plants homepage and do the following:

1. Go to the region between 405000 and 453000 on chromosome 1 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 Ensembl transcripts?

Demo: Exploring genes and transcripts in Ensembl Plants

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.

Exploring variants in rice

Visualising variants in the Sequence view

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 OS01G0775500 in rice. Search for OS01G0775500 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.

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.

Viewing variants within a gene in the tabular form

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.

Visualising variants in the Region in Detail view

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.

Exploring a specific variant

Let’s have a look at a specific variant. If we zoomed in we could see the variant rs18335701 in this region, however it’s easier to find if we put rs18335701 into the search box. Click through to open the Variation tab for Oryza sativa Japonica.

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.

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

The population allele frequencies are shown by study. Where genotype frequencies are available, these are shown in the tables.

We can see which strains these genotypes were observed in by going to Sample Genotypes. Click on Show for the Duitama et al. 2015 population.

The Arabidopsis thaliana ATCDSP32 protein is a chloroplastic drought-induced stress protein proposed to participate in a process called cell redox homeostasis. Go to Ensembl Plants and answer the following questions:

1. How many variants have been identified in the gene that can cause a change in the protein sequence (i.e. missense variant)?

2. What is the ID of the variant that changes the amino acid residue 60 from Alanine to Threonine (hint: refer to an amino acid codon table)? What is the location of this SNP in the A. thaliana genome? What are its possible alleles?

3. Download the flanking sequence of this SNP in RTF (Rich Text Format). Can you change how much flanking sequence is displayed on the browser?

4. Does this SNP cause a change at the amino acid level for other genes or transcripts?

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. Search for the variant BA00369602 in Triticum aestivum on Ensembl Plants. Is this variant known by any other names?

2. What gene is affected by this variant? What is the amino acid change?

3. Which cultivars have the alternative base at this locus?

Demonstration of the VEP web interface

Input

We have identified three variants on wheat chromosome 4B:
C -> T at 240206468
C -> G at 240199078
C -> T at 240212229

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?

Click on Tools in the top green bar from any Ensembl Plants page, then Variant Effect Predictor to open the input form:

Click on Add/remove species and search for Triticum aestivum to choose it.

The data is in VCF:
chromosome coordinate id reference alternative

Put the following into the Paste data box:

4B 240206468 var1 C T  
4B 240199078 var2 C G  
4B 240212229 var3 C T  

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

Additional configurations

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.

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.

Results

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. The IDs are links to take you to the gene or transcript 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 and pathogenicity scores. Where the variant is known, the ID of the existing variant is listed, with a link out to the variant homepage. 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.

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.

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? What is the pathogenicity prediction score for this 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.

Demo: gene trees and homology predictions

Plants Compara

Gene trees

Let’s look at the homologues of Triticum aestivum (wheat) TraesCS3D02G007500. Open Ensembl Plants, search for the gene and go to the Gene tab.

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

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 protein 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.

Homologues

We can look at homologues in the Orthologues, Paralogues and homoeologues pages, which can be accessed from the left-hand menu. If there are no orthologues, paralogues or homoeologues, then the name will be greyed out. Click on Plant compara: Orthologues to see the orthologues available in plants.

Choose to see only Eudicotyledons orthologues by selecting the box. The table below will now only show details of Eudicotyledons orthologues. Let’s look at Brassica oleracea.

Here we can see there is a many-to-many relationship between the wheat and B. oleracea orthologues. 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 first B. oleracea orthologue.

The paralogue page and homoeologue pages are structured in the same way as the orthologue page.  
 
 

Let’s look at some of the comparative genomics views in the Location tab. Go to the region 1:8000-18000 in Oryza sativa Japonica.

We can 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 all Oryza species:

The alignment is greatest between closely related species. We can see that many rice species (such as Oryza barthii) are fully aligned across the region, but other species have a region around 1:10700-12500 where a different chunk is aligned (such as Oryza punctata).

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.

Select Oryza punctata from the alignments list then click Go.

In this case there are eight blocks aligned of different lengths, some of which correspond to the region we saw unaligned in the image. 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 Oryza punctata again then close the menu.

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

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.

How many orthologues are predicted for the maize Zm00001d015746 gene in Liliopsida?

How much sequence identity does the Sorghum bicolor protein have to the maize one? Click on the Alignment link next to the Ensembl identifier column to view a protein alignment in Clustal format.

Resistance to the leaf rust delivered by SH3 factor(s) is well-grounded as specially durable. in 2023, Paula Cristina da Silva Angelo et al (https://doi.org/10.1016/j.pmpp.2023.102111) reported that the Arabidopsis thaliana gene AT1G50180 is an important gene in the SH3 locus conferring diseae resistance.

Search Ensembl Plants for the gene AT1G50180 in Arabidopsis thaliana.

1. From the gene tab, go to the Arabidopsis thaliana AT1G50180 gene Orthologues page under Plant Compara.

2. Reduce the orthologues table to look only at Coffea canephora (coffee) orthologues. How many results can you see?

3. Download the cDNA alignment in ClustalW format for the alignment between the Arabidopsis thaliana AT1G50180 gene and the Coffea canephora GSCOC_T00030728001 gene.

Search Ensembl Plants for the gene Lsi1 in Oryza sativa Japonica Group (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?

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.