Pigs' immune systems are similar to ours, making their genes a great model to understand human health and disease. But their position and function in the genome was unknown, until a group of annotators from around the world met up and decided to take matters into their own hands
Categories: Sanger Science13 August 20133 min read

Finding pearls in swine: how a worldwide community annotated the pig genome

Venn diagram to show similarity between human, mouse, cow and pig immune genes. Humans and pigs share 42 genes that aren't found in mice, whilst mice and humans share 14 genes not found in pigs

Venn diagram to show similarity between human, mouse, cow and pig immune genes.
Humans and pigs share 42 genes that aren't found in mice, whilst mice and humans share 14 genes not found in pigs

13 August 2013

By Jane Loveland

Did you know that pigs are great models for studying human immune response? We share many features of our immune system with pigs and they respond in a similar way as us to human disease-causing agents, such as viruses. The implications for human medical treatment are significant, making pig genomes of great interest.

Yet, these benefits can only be harnessed if we have a better understanding of the immune genes of pigs, for example, knowing exactly where they are located in the genome. This is something that a technique known as manual annotation provides by adding detail about each gene’s location.

Already, the Sanger Institute has sequenced and is manually annotating the pig X and Y chromosomes (the sex chromosomes). But there wasn’t specific funding available to extend this work to the other pig chromosomes, which contain most of the pig immune genes that can tell us so much about the human immune system.

The need for good annotation was so pressing that, while bemoaning the lack of funding for this work at a conference, a number of us decided to take matters into our own hands. Together we set up the Immune Response Annotation Group (IRAG). Our impromptu research group spanned the globe, with roughly 30 scientists from Europe, USA, Japan and China.

To coordinate the work, and that ensure errors did not creep in, I oversaw the training and the quality control of this annotation effort. We set up a week’s training at the Sanger Institute for European researchers and a parallel week of training in the US.

Within the team we estimate that it takes at least six months to become a competent annotator. So ensuring that the work of our very diverse group of scientists was gold-standard quality when we had just one week to train them was quite a challenge. Annotation and quality control are painstaking work, but it is crucial to get the information right because errors will mean that future research is based on incorrect foundations.

We found that the best way to help everyone get up to speed was to keep in close contact with the researchers and act as gate keepers for the final data we produced. We gave regular tutorials and helped with issues via international conference calls and spread the responsibility for quality control itself around the Sanger Institute’s annotation team. Using these mechanisms, we gave all collaborators extensive feedback on the quality of their annotation.

Through everyone’s hard work more than 1,300 genes have now been annotated and have led to some exciting and unexpected discoveries. For instance, our annotations found gene duplication in 13 immune-related pig genes (such as CD68 and CD36). This discovery raises questions about what the duplicates do, how they benefit the pig and what, genetically, makes a pig a pig.

So, despite the lack of specific funding, we pig researchers united to fulfil a common aim and helped contribute to the understanding of the immune response in pigs. Not bad for a chat after a conference!

Jane Loveland Senior Computer Biologist in the human and vertebrate annotation (Havana) team at the Wellcome Trust Sanger Institute. more...

Reference:

Dawson HD, Loveland JE, Pascal G et al. Structural and functional annotation of the porcine immunome. BMC Genomics. 2013 May 15;14:332. doi: 10.1186/1471-2164-14-332