Data from: Integrated genome-scale analysis identifies novel genes and networks underlying senescence in maize
Sekhon, Rajandeep S. (2019), Data from: Integrated genome-scale analysis identifies novel genes and networks underlying senescence in maize, Dryad, Dataset, https://doi.org/10.5061/dryad.5172532
Premature senescence in annual crops reduces yield while delayed senescence, termed stay-green, is known to impose both positive and negative impact on yield and nutrition quality. Despite the importance, scant information is available on the genetic architecture of senescence in maize (Zea mays L.) and other cereals. We combined a systematic characterization of natural diversity for senescence in maize and co-expression networks derived from transcriptome analysis of normally senescing and stay-green lines. Sixty-four candidate genes were identified by GWAS, and 14 of these are supported by additional evidence for involvement in senescence-related processes including proteolysis, sugar transport and signaling, and sink activity. Eight of the GWAS candidates, independently supported by a co-expression network underlying stay-green, include a trehalose-6-phosphate synthase, a NAC transcription factor, and two xylan biosynthetic enzymes. Source-sink communication and the activity of cell walls as a secondary sink emerge as key determinants of stay-green. Mutant analysis supports the role of a candidate encoding cysteine protease in stay-green in Arabidopsis (Arabidopsis thaliana), and analysis of natural alleles suggest a similar role in maize. This study provides a foundation for enhanced understanding and manipulation of senescence for increasing carbon yield, nutritional quality, and stress tolerance of maize and other cereals.