Frontiers in Plant ScienceBioinformaticsPeer-reviewed journal article
Sorghum pan-genome explores the functional utility to accelerate the genetic gain
Pradeep RuperaoiD, Nepolean ThirunavukkarasuiD, Prasad GandhamiD, Sivasubramani SelvanayagamiD, Mahalingam GovindarajiD, Baloua NebiéiD, Eric O. ManyasaiD, Rajeev GuptaiD, Roma Rani DasiD, Damaris A. OdenyiD, Harish T. GandhiiD, David EdwardsiD, Santosh DeshpandeiD, Abhishek RathoreiD
Abstract
Sorghum (Sorghum bicolor L.) is one of the most important food crops in the arid and rainfed production ecologies. It is a part of resilient farming and is projected as a smart crop to overcome the food and nutritional challenges in the developing world. The development and characterisation of the sorghum pan-genome will provide insight into genome diversity and functionality, supporting sorghum improvement. We built a sorghum pan-genome using reference genomes as well as 354 genetically diverse sorghum accessions belonging to different races. We explored the structural and functional characteristics of the pan-genome and explain its utility in supporting genetic gain. The newly-developed pan-genome has a total of 35,719 genes, a core genome of 16,821 genes and an average of 32,795 genes in each cultivar. The variable genes are enriched with environment responsive genes and classify the sorghum accessions according to their race. We show that 53% of genes display presence-absence variation, and some of these variable genes are predicted to be functionally associated with drought traits. Using more than two million SNPs from the pan-genome, association analysis identified 398 SNPs significantly associated with important agronomic traits, of which, 92 were in genes. Drought gene expression analysis identified 1,788 genes that are functionally linked to different conditions, of which 79 were absent from the reference genome assembly. This study provides comprehensive genomic diversity resources in sorghum which can be used in genome assisted crop improvement.
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- Citations
- 105
- FWCI
- 8.91
- Field percentile
- top 1%
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