Automated Update, Revision, and Quality Control of the Maize Genome Annotations Using MAKER-P Improves the B73 RefGen_v3 Gene Models and Identifies New Genes  

Abstract

The large size and relative complexity of many plant genomes make creation, quality control, and dissemination of high-quality gene structure annotations challenging. In response, we have developed MAKER-P, a fast and easy-to-use genome annotation engine for plants. Here, we report the use of MAKER-P to update and revise the maize (Zea mays) B73 RefGen_v3 annotation build (5b+) in less than 3 h using the iPlant Cyberinfrastructure. MAKER-P identified and annotated 4,466 additional, wellsupported protein-coding genes not present in the 5b+ annotation build, added additional untranslated regions to 1,393 5b+ gene models, identified 2,647 5b+ gene models that lack any supporting evidence (despite the use of large and diverse evidence data sets), identified 104,215 pseudogene fragments, and created an additional 2,522 noncoding gene annotations. We also describe a method for de novo training of MAKER-P for the annotation of newly sequenced grass genomes. Collectively, these results lead to the 6a maize genome annotation and demonstrate the utility of MAKER-P for rapid annotation, management, and quality control of grasses and other difficult-to-annotate plant genomes.Plant genomes, especially grass genomes, are difficult substrates for genome annotation due to regional and whole-genome duplication events and often contain large numbers of pseudogenes. These factors impact every aspect of gene structure annotation, from revision of existing annotations in light of new data to annotation of newly sequenced plant genomes. These aspects of plant genomes also dramatically lengthen compute times, because the many repeated genes and other sequences result in commensurately more sequence alignments and gene predictions. In many ways, annotation of the maize genome epitomizes these problems.In 2005, the National Science Foundation, U.S. Department of Agriculture, and Department of Energy announced that the approximately 2.3-Gb genome of the maize (Zea mays) inbred line B73, a major contributor to much of the germplasm used for U.S. grain production, would be sequenced using a bacterial artificial chromosome (BAC)-by-BAC approach. The plan was to sequence BACs from a minimal tiling path to approximately 63 coverage and to further improve only the unique genic regions. These sequences would be labeled Phase

Draft Assembly of Elite Inbred Line PH207 Provides Insights into Genomic and Transcriptome Diversity in Maize

“…In total, we identified 40,557 high-quality gene models in PH207 supported by aligned transcript evidence, protein evidence, or the presence of a Pfam domain (Finn et al, 2014). These gene models were distributed throughout the genome ( Figure 1B) in a distribution similar to that observed in the B73 reference genome assembly (Schnable and Ware et al, 2009;Law et al, 2015). The annotation edit distance analysis of the predicted gene set indicated that the gene annotations were generally well supported (Supplemental Figure 3) (Eilbeck et al, 2009;Yandell and Ence, 2012).…”

“…The MAKER genome annotation pipeline was used to generate gene annotations (Campbell et al, 2014a(Campbell et al, , 2014bLaw et al, 2015). The PH207 genome assembly was first masked using RepeatMasker (http://www.…”

The Aegilops tauschii genome reveals multiple impacts of transposons

“…When including gene fragments without disabling mutations in a broader pseudogene definition, the total number of pseudogenes reached 267,546 in the Ae. tauschii genome, which is two times larger than the number in the maize genome (B73 RefGen_v3, in the 5b + annotation build) 21 . Therefore, Ae.…”

Improved maize reference genome with single-molecule technologies

“…The scripts, parameters, and intermediate files of each transposable element superfamily are available at https://github.com/mcstitzer/maize_v4_TE_annotation. The MAKER P pipeline was used to annotate protein coding genes 46 , integrat ing ab initio prediction with publicly available evidence from full length cDNA 47 , de novo assembled transcripts from short read mRNA sequencing (mRNA seq) 48 , isoform sequencing (Iso Seq) full length transcripts 14 , and proteins from other species. The gene models were filtered to remove transposons and low confidence predictions.…”