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wheatgenome

David Swarbreck

2017 Leadership Awardee

23 January 2018

David Swarbreck
In January 2018, David Swarbreck was awarded an IWGSC Leadership Award in recognition and appreciation of his extraordinary leadership in the annotation of the reference sequence of bread wheat, IWGSC RefSeq v1.0.

Throughout 2017, David worked with Hélène Rimbert and Manuel Spannagl to produce the IWGSC RefSeq annotation v1.0. Resulting from the integration of two gene calling pipelines (TriAnnot and PGSB pipeline), the IWGSC annotation benefits from the complementarity of the two approaches and provides wheat scientists and breeders with the most comprehensive set of wheat genes to date.

David Swarbreck is Regulatory Genomics Group Leader at the Earlham Institute in the United Kingdom.His group utilizes computational and genomics approaches to understand the complexity of eukaryotic transcriptomes and gene regulation. David has worked in the bioinformatics field for the past 14 years, principally in large scale genomics projects in the areas of genome annotation and data analysis.

As part of the IWGSC RefSeq v1.0 annotation project, David led the team that integrated and consolidated the Triannot and PGSB annotations - using the tool Mikado - to produce the IWGSC RefSeq annotation v1.0.

“It’s been a pleasure to be part of the IWGSC, helping create a resource that will be useful to researchers and breeders worldwide, this has been a challenging but rewarding project involving teams from many research groups with different areas of expertise. From my own group, I would like to thank Gemy Kaithakottil and Luca Venturini who played a vital role in delivering a high quality wheat annotation, it’s exciting that this resource could contribute to future advances in wheat research,“ said David.

The 107,886 high confidence gene models annotated in IWGSC RefSeq annotation v1.0, together with sets of less-well supported gene models and pseudogenes are available for BLAST searches, download or in browser format with supporting evidence at URGI, INRA Versailles. As the data are used and revised over time the models will be updated to maintain a highly useful resource for the community.