Throughout 2017, Manuel worked with Hélène Rimbert and David Swarbreck 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.

Manuel Spannagl is Bioinformatician and Deputy Group Leader in the Plant Genome and Systems Biology (PGSB) group of Klaus Mayer at the Helmholtz Zentrum München in Germany. PGSB (formerly MIPS) has been engaged in the development of plant genome bioinformatics for over 15 years and has generated annotation for many plant genomes, including the IWGSC chromosome survey sequence analysis published in 2014.

After working on the analysis of several plant genomes including tomato, Medicago, Brachypodium and Sorghum, Manuel joined the EU-funded TriticeaeGenome project and got involved in cereal genomics. The main objectives of his work include gene prediction and annotation, genome structure, expression and gene family analyses and comparative genomics. Manuel is also the database manager of PGSB PlantsDB, where genomic data from wheat (and many other plants) are structured, integrated and visualized.

As part of the IWGSC RefSeq v1.0 annotation team, Manuel led the efforts at PGSB to generate gene models using the in-house annotation pipeline (previously called MIPS pipeline) that uses an evidence-based approach incorporating extensive transcript data from wheat in addition to comparative data from other plant genomes. Manuel’s team at PGSB also contributed analyses on gene families/phylogenomics, gene expression, transposable elements and genome structure to the current work on the IWGSC RefSeq v1.0 assembly.

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.