The CRISPR/Cas9 system has revolutionised scientific research over the last few years, offering an efficient method of genome editing. CRISPR/Cas9 utilises the cellular machinery used by bacteria to recognise and edit the DNA of invading viruses. It is formed of two key components: Cas9, an enzyme that can cut a double DNA strand at a precise point; and CRISPR, a short strand of RNA that guides the Cas9 enzyme to recognise and cleave at specific DNA sites.

Cas9 restricts DNA at specific Protospacer Adjacent Motifs (PAMs), which is species-dependent (for example,¬†5‚Ä≤ NGG 3‚Ä≤ for¬†Streptococcus pyogenes¬†Cas9). Therefore, by coupling a custom CRISPR polymer (gRNA), Cas9’s restriction activity can be targeted to specific locations in the genome that¬†contain a PAM region.

The latest release of Ensembl (Ensembl 85, July 2016) now includes annotated CRISPR/Cas9 sites predicted by the Wellcome Trust Sanger Institute Genome Editing (WGE) group for human and mouse genomes.

The WGE group have predicted CRISPR sites and developed an accompanying database to help you design genome editing experiments, and you can view these WGE-predicted sites by adding the ‘WGE CRISPR sites’ track to any ‘Region in Detail’ view for human or mouse in¬†Ensembl. Click on the¬†‘Configure this page’ option from the menu on the left hand side of the page, and then add the track, which Configure this page buttoncan be found in the ‘Other regulatory regions’ category,¬†by clicking the empty box and selecting the track style from the pop-up window:Add CRISPR track option

Below, you can see an example of the WGE-predicted CRISPR site track added (to both the forward and reverse strand) of the genomic region containing the human BRCA2 gene in the ‘structure’ style. Each CRISPR site is labelled as¬†a single green box, which appears as a single vertical line when viewing a large genomic region.CRISPR site track

From the example above, we have now zoomed into a specific region of interest. You can see the structure of each CRISPR site, with the filled green box matching up with the PAM motif and the un-filled box representing the potential gRNA binding sequence. Clicking on any of these individual CRISPR sites will open a pop-up window that provides you with more information about the specific genomic co-ordinates of the CRISPR site as well as a link to the WGE database.CRISPR pop up

You can find more information about the CRISPR site prediction method in the published description of the WGE database

Continued HapMap variation data access through Ensembl

NCBI have recently released plans to immediately retire their HapMap interface, however, data from the HapMap Project will continue to be freely accessible through Ensembl. There is lots of help and documentation as well as video tutorials to help you learn how to access variant data in Ensembl. This post aims to complement those materials to highlight the methods for accessing the HapMap Project variant data specifically.

Finding HapMap variants by ID

You can find data from the HapMap project relating to specific variants by searching for the variant rsID itself. In Ensembl, you can find information related to variants identified in the HapMap Project, which includes population genetics statistics:Population Genetics HapMap

However, as you can see from the example above, some of the populations represented in the HapMap Project have two separate entries in the Population Genetics table. This is because the HapMap Project was completed in a number of phases. In the first phase, a number of different groups used different genotyping platforms to type variants from a number of population panels (CEU, YRI, HCB, JPT). In a later phase, a larger set of samples were added to the samples from the initial phase and submitted as HapMap3. The two entries refer to the two submitted phases of the HapMap Project, where the number in brackets next to the allele frequency indicates the number of samples in that population.

It is also possible to view HapMap Project results by gene of interest by searching¬†the Variant Table. The Variant Table can be filtered by ‘Evidence’ type¬†so¬†you can choose to see only HapMap Project variants, for example.Variant Filter HapMap

Filtering the Variant Table by ‘Evidence type = HapMap’ will filter¬†the displayed variants to those identified in the HapMap project. This will be denoted by theevidence HapMapin the Evidence column.Filtered variant Table Hapmap

Finding HapMap Project variant data using BioMart 

HapMap SNP data can also be retrieved using BioMart. There is help and documentation and a video tutorial to help you while using BioMart.

When querying the Homo sapiens¬†short variants dataset in BioMart, you can access HapMap variant¬†data specifically by using¬†the ‘Variant Set Name’ filter and selecting the HapMap populations¬†that are relevant for your research.HapMap variation Mart

Finding HapMap variants using the Ensembl API

It is also possible to access variation data through the Ensembl APIs. Using the Perl API, for example, it is possible to retrieve variation data specifically related to the HapMap Project variant set, either as the whole HapMap variant set, or as individual populations represented in the HapMap Project.

Please note that the archive websites for Ensembl releases 71 (April 2013) and 72 (June 2013) will be retired in July when version 85 is released.

This is in accordance with our rolling retirement policy, whereby archives more than three years old are retired unless they include the last instance of the previous assembly from one of our key species (human, mouse and zebrafish).

For more information about how to use archives, please see our previous blog post on the topic; a list of all current archives is available on the main website.

A mysteriously common debilitating genetic disorder.¬†A deadly tropical disease.¬†One of my¬†favourite stories in the history of genetics weaves together these two elements ‚Äď it’s a good one and it always deserves a re-telling ‚Äď that of malaria and sickle cell anaemia.

This story captures my attention and inspires me in the power of scientific observation, curiosity and experiment.¬†I‚Äôm sure you are all aware of the details of this worn-out tale: it is used as an example in classrooms and lecture theatres every year to explain Mendelian genetics, haploinsufficiency, physiology, disease and protein structure and function to young scientists. To mark the coincidental coinciding of DNA day and Malaria day, we wanted to re-visit this¬†‚Äėhistorical‚Äô example of how scientific observation and experimental approaches have led to the understanding of how a disease as debilitating as sickle cell anaemia paradoxically persists in the human population.

Molecular biology and bioinformatics have transformed the face of biological research over the last few decades. The speed that scientists can sequence and analyse DNA means that global collaborations that study thousands of individuals are beginning to shed light on a range of different diseases.

Sickle-cell anaemia is a disease in which red blood cells form an abnormal crescent (or sickle) shape. It is an inherited disorder, and was the first ever to be attributed to a specific genetic variant (rs334, see it here in Ensembl).


In 1949, ‚ÄėSickle Cell Anaemia, a Molecular Disease‚Äô, from Pauling et al. identified a difference in the electrophoretic mobility between haemoglobin from healthy individuals and those with sickle-cell anaemia caused by a change in molecular structure of haemoglobin responsible for the sickling process [1]. The genetic variant (A, Reference:T) that causes cell sickling results in the substitution of a conserved glutamic acid residue at position 7 in beta chain of haemoglobin to a valine [2].

You can find this information in the Genes and regulation¬†section¬†for this variant.¬†In the table below, which has been filtered to see only missense variants, the ‘Allele (transcript allele)’ column describes the variant allele (A) and the ¬†transcript allele (T, as the HBB gene is located on the reverse strand). You can also see the nature and location of the variant on the transcript in the ‘Position’, ‘Amino acid’ and ‘Codons’ columns. The SIFT and Polyphen algorithms¬†predict the effect of the amino acid change¬†on protein structure and function. Interestingly, only the SIFT algorithm predicts that the T/A variant would have deleterious effect on haemoglobin structure and function, confirming¬†that predictions can never be as accurate as experimental evidence.


Only those individuals that are homozygous for the variant allele develop sickle cell anaemia, although heterozygous individuals do have the much more manageable sickle cell trait. If untreated, individuals with sickle cell anaemia have a shorter than normal life expectancy, experiencing lethargy and breathlessness throughout their lives, with increased risk of stroke and pulmonary hypertension, as well as increased vulnerability to infection. Individuals with the milder sickle cell trait can experience problems in low oxygen or as a result of severe physical exercise, but can mostly be expected to live normal lives.

As such it would be expected that this variant would be rare in human populations. However, observations made in mid-20th century revealed that this variant is, in fact, surprisingly common in African, African American and Caribbean populations (you can see this in the 1000 Genomes allele frequencies available under Population genetics in Ensembl). Coincidentally, these were people descended from those who came from areas where malaria is prevalent [3]. Why was this happening?


Individuals carrying just one copy of the variant allele were known not to develop sickle cell anaemia, leading rather normal lives. However, it was found that these same individuals, were in fact highly protected against malaria. It turned out that, quite bizarrely, having alternate alleles at this loci simultaneously prevented infection from the malaria parasite with entirely manageable sickle manifestations! Therefore, individuals with one copy of each allele have a greater chance of survival in geographical areas where malaria is endemic, preserving both alleles in the population.

Understanding this relationship has led to a deeper understanding of the infective lifecycle of the malaria parasite and novel approaches in combating malaria [4-5], but also an appreciation of the genetic factors leading to sickle-cell anaemia.

This story exemplifies how observation, epidemiology and scientific investigation can uncover the mysteries of a human disease and provide important insights for its treatment. Nowadays, this gold standard of studying single genetic disorders has been multiplied and sped up on an unprecedented scale. There are now numerous projects that are aimed at sequencing the DNA of many individuals with different diseases and using the power of bioinformatics to analyse how genetic variation might lay at the foundations for previously poorly understood diseases.

[1] Pauling L. et al. Sickle cell anemia a molecular disease Science, 1949 Nov 25;110(2865):543-8

[2] Ingram VM et al. Abnormal human haemoglobins. III. The chemical difference between normal and sickle cell haemoglobins Biochim Biophys Acta 1959 36: 543‚Äď548

[3] Allison AC et al. Protection Afforded by Sickle-cell Trait Against Subtertian Malarial Infection 1954 Br Med J 1 (4857): 290‚Äď294

[4] Mounkaila A. et al. Sickle Cell Trait Protects Against Plasmodium falciparum Infection American Journal of Epidemiology, 2012 176 175-185

[5]  Gregory LaMonte et al. Translocation of Sickle Cell Erythrocyte MicroRNAs into Plasmodium falciparum Inhibits Parasite Translation and Contributes to Malaria Resistance Cell Host & Microbe, 2012 12 187-199


What’s new in Ensembl Genomes 31?

There are legs and tentacles everywhere in this release of Ensembl Metazoa, as ten new species scuttle, swim and slither into our databases. From the Antarctic midge to the California two-spot octopus, the new species illustrate the diversity of metazoa. Our new Metazoan species also include dog and rat parasites (the itch mite and a nematode), as well as species that pose significant problems for agriculture (Australian sheep blowfly) and aquaculture (the salmon louse and a myxosporean). The common bumblebee is an important pollinator, a brachiopod represents a new phylum in Ensembl Metazoa, while the African social velvet spider is a fascinating model of sociality and is the first spider in Ensembl Genomes.


Not to be outdone, Ensembl Protists is now updated to 158 genomes from 104 species and Ensembl Bacteria has been updated to include the latest versions of 39,584 genomes (39,183 bacteria and 401 archaea) from the INSDC archives.

Other news

Fungi: Updated annotations based on PHI-base 4.0 have been included. New variation data for Schizosaccharomyces pombe.

Protists: Addition of 4 protist species for pan-taxonomic comparative analysis (Monosiga brevicollis, Thecamonas trahens, Cryptomonas paramecium and Chondrus crispus), meaning that Ensembl Compara now includes protists from all the major Eukaryotic clades.

Plants: There are now 350,000 new rice variations across 3,000 rice accessions from 89 different countries as well as track hubs for more than 900 public RNA-Seq studies, totalling more than 16,000 tracks across 35 different plant species.

Metazoa: Updated gene sets for the leaf cutter ant, red fire ant and the two-spotted spider mite as well as updated gene sets from VectorBase and WormBase.

Check out all the changes on our Ensembl Genomes website.

Any questions or comments? Email us.

What’s new in e84:

  • Human: Incorporation of BLUEPRINT Epigenome data and methylation data
  • Pairwise Linkage Disequilibrium (LD) calculation on LD variant page
  • Track hub registry interface
  • Transcript haplotype view

Incorporation of BLUEPRINT Epigenome data

BLUEPRINT is a large scale research project aimed at deciphering the epigenome of blood cells. ChIP-seq and DNase hypersensitivity data from the BLUEPRINT project has now been incorporated into Ensembl. All of the cell types analysed in the BLUEPRINT project are listed here. In Ensembl 84, we are including BLUEPRINT data for the following 20 independent cell types, divided based on cell lineage and tissue source:

CD14+ CD16- monocyte from Venous Blood
CD14+ CD16- monocyte from Cord Blood
CD4+ ab T cell from Venous Blood
CD8+ ab T cell from Cord Blood
CM CD4+ ab T cell from Venous Blood
eosinophil from Venous Blood
EPC from Venous Blood
erythroblast from Cord Blood
HUVEC prol from Cord Blood
M0 macrophage from Cord Blood
M0 macrophage from Venous Blood
M1 macrophage from Cord Blood
M1 macrophage from Venous Blood
M2 macrophage from Cord Blood
M2 macrophage from Venous Blood
MSC from Venous Blood
naive B cell from Venous Blood
neutro myelocyte from Bone Marrow
neutrophil from Cord Blood
neutrophil from Venous Blood

This data can be viewed alongside other tracks in Ensembl by using the ‘Configure this Page’ option and selecting your cells of interest. ¬†configure this pageBLUEPRINTex2

Pairwise LD calculation

You are now able to calculate linkage disequilibrium (LD) between any two variants in Ensembl. To calculate the r2 and D’ values for LD between two specific variants, enter the ID of any variant into the LD calculation¬†text box on the specific page of the reference variant. This feature can be found by clicking on¬†‘Linkage Disequilibrium’ from the menu on any variant page.


Track Hub registry interface

With the arrival of the new Track Hub Registry, we have added a feature¬†that allows you to search for track hubs of interest and attach them directly to Ensembl. Just click on the ‘Add your data/Manage your data’ button on any Ensembl page, and select ‘Track Hub Registry Search’ from the lefthand menu.¬†manage your dataTrackHubRegistryInterface

The interface will only search for hubs that have assemblies available for the site you are on; to see the full range of species and assemblies, visit the Track Hub Registry site directly.

Transcript haplotype view

The transcript haplotype view is a new data view we have implemented that allows you to explore observed transcript sequences that results from variants identified from¬†resequencing data¬†from the 1000 Genomes Project. By clicking on the ‘Haplotypes’ link on any transcript page, you are able to view protein consequences, population frequencies and protein alignments of all the haplotypes for that particular transcript.

Transcript_haplotype_view Screen Shot 2016-03-02 at 11.01.34Screen Shot 2016-03-02 at 11.02.04

Other news

  • Mouse:¬†update to GENCODE M9 annotation
  • Zebrafish: updated gene set, including manually annotated HAVANA annotation
  • Baboon: lincRNA model update
  • Latest sequence variants from dbSNP build 146 for¬†human, cow and dog
  • Import of COSMIC 75 cancer data
  • New and updated studies from DGVa for several species such as human, mouse, zebrafish, macaque, cow and dog
  • Gene trees: new option to prune by target species/ taxon in the REST API
  • Ensembl Families now defined by an HMM library, based upon the Panther database.
  • Alignments in CRAM format
  • DAS support ended
  • Regulatory segments retired from the Ensembl regulation BioMart, but¬†now available in bigbed format through the ftp site

A complete list of the changes can be found on the Ensembl website.

Find out more about the new release, and ask the team questions, in our free webinar. Wednesday 16th March, 4pm GMT. Register here.

Ensembl 84 is scheduled for March 2016 and includes:

Updated gene sets and annotations

  • Human: Incorporation of Blueprint epigenome data and methylation data
  • Mouse:¬†update to GENCODE M9 annotation
  • Zebrafish: updated gene set, including manually annotated HAVANA annotation and RNAseq data update
  • Cow: ncRNA data update and transcriptomic data update
  • Baboon: lincRNA model update

Variation data imports and updates

  • Phenotype data updated for several species including human, mouse, rat,¬†zebrafish and pig
  • Latest sequence variants from dbSNP build 146 for¬†human, cow and dog
  • HGMD data update
  • Import of COSMIC 75 cancer data
  • New and updated studies from DGVa for several species such as human, mouse, zebrafish, macaque, cow and dog

Other highlights and data sets

  • Pairwise LD calculation on LD variant page
  • Alignments in CRAM format
  • Track hub registry interface
  • Gene trees: new option to prune by target species/ taxon
  • DAS support ended
  • Regulatory segments retired from the Ensembl regulation Biomart, but¬†now available in bigbed format through the ftp site

For more details on the declared intentions, please visit our Ensembl admin site. Please note that these are intentions and are not guaranteed to make it into the release.

Would you like to include images from Ensembl during a presentation or in your paper or poster?

We are happy to announce that a new image export option is available in Ensembl 83, which optimises colour and contrast settings for presentation on a projector or in print. You can download images from Ensembl using the ‘Export this Image’ icon, at the top-left of every image. Below¬†is the image download form, showing the new export options.

Image export page

Presentation options
Our new export feature for presentations alters the image to be clearly visible on projectors by:

  • saturating colours to improve contrast in brightly lit environments
  • increasing line breadth for viewing from a distance.

You can see the difference below. On the left is a ‘Standard Web’ exported image. On the right is the same exported image with the ‘Presentation’ feature.

Human_13_32315474_32400266 Human_13_32315474_32400266-2

Print options
If you’re looking for an image for your paper or poster, try our new print options, labelled ‘Journal/report’ and ‘Poster’. Images exported for print have a high resolution, which produce x2 and x5 enlargements respectively.

Other export options
You can also export the standard web image in PNG or PDF format for use on the web, or SVG format by clicking on the ‘Custom image’ export option.

information iconYou can find more information about exporting images by clicking on the information icons in the export menu.

We would love to hear from you if you have used the new image export options for your own work. Image parameters can be tweaked, so we welcome feedback on whether these features suit your needs. Leave your comments below or contact the Ensembl helpdesk.

Please note that the archive website for Ensembl release 68 (Jul 2012) will be retired in September when version 82 is released.

This is in accordance with our rolling retirement policy, whereby archives more than three years old are retired unless they include the last instance of the previous assembly from one of our key species (human, mouse and zebrafish).

For more information about how to use archives, please see our previous blog post on the topic; a list of all current archives is available on the main website.

Please note that the archive websites for Ensembl release 61 (Feb 2011) will be retired in February this year when version 75 is released.

This is in accordance with our rolling retirement policy, whereby archives more than three years old are retired unless they include the last instance of the previous assembly from one of our key species (human, mouse and zebrafish).

For more information about how to use archives, please see our previous blog post on the topic; a list of all current archives is available on the main website.