Genome-wide transcriptome and physiological analyses provide new insights into peanut drought response mechanisms

Authors: BHOGIREDDY, SAILAJA - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India; XAVIER, ABISHEK - New Mexico State University; GARG, VANIKA - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India; LAYLAND, NANCY - US Department Of Agriculture (USDA); Arias De Ares, Renee; Payton, Paxton; NAYAL, SPURTHI - University Of Agricultural Sciences; PANDEY, MANISH - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India; PUPPALA, NAVEEN - New Mexico State University; VARSHNEY, RAJEEV - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India

Submitted to: Scientific Reports
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/7/2020
Publication Date: 3/5/2020
Citation: Bhogireddy, S., Xavier, A., Garg, V., Leyland, N., Arias De Ares, R.S., Payton, P.R. 2020. Genome-wide transcriptome and physiological analyses provide new insights into peanut drought response mechanisms. Scientific Reports. 10:4071. https://doi.org/10.1038/s41598-020-60187-z.
DOI: https://doi.org/10.1038/s41598-020-60187-z

Interpretive Summary: Drought is one of the major constraints for the peanut production worldwide and lack of legitimate understanding towards molecular mechanisms prevent the accelerated genetic improvement. In this study, composite analysis of phenotyping, physio-biochemical and transcriptome investigations decipher the underlying drought stress responsive mechanisms in peanut. Multi-season (2013 - 2015) phenotyping of 10 genotypes under water deficit irrigation (WDI) revealed C76 -16 (C-76) as best performing under WDI while Valencia (Val-C) as least. Further, RNA-seq in both genotypes deciphers the transcriptome changes under WDI. About 369 million raw reads were generated from four different libraries constructed from fully irrigated (FI) and WDI samples, out of which 329 (90.2%) filtered reads were mapped to the peanut genome. Analysis revealed the differential expression of 4508 genes, 1554 transcription factors and 514 SNPs/Indels. Further, comparative analysis revealed the expression of osmoprotectant genes like proline iminopeptidase, peroxidase, abscisic acid 8- hydroxylase and other genes like lipid transfer, and photosystem II D2 in C-76 reflecting its basal and integral tolerance mechanism. This study not only understand the response of genotypes to WDI, but also identified genes and SNPs could be deployed in development of molecular markers for drought response selection of genotypes through marker-assisted breeding.

Technical Abstract: Drought is one of the main constraints in peanut production in West Texas and eastern New Mexico regions due to the depletion of groundwater. A multi-seasonal phenotypic analysis of 10 peanut genotypes revealed C76-16 (C-76) and Valencia-C (Val-C) as the best and poor performers under deficit irrigation (DI) in West Texas, respectively. In order to decipher transcriptome changes under DI, RNA-seq was performed in C-76 and Val-C. Approximately 369 million raw reads were generated from 12 different libraries of two genotypes subjected to fully irrigated (FI) and DI conditions, of which ~329 million (90.2%) filtered reads were mapped to the diploid ancestors of peanut. The transcriptome analysis detected 4,508 differentially expressed genes (DEGs), 1554 genes encoding transcription factors (TFs) and a total of 514 single nucleotide polymorphisms (SNPs) among the identified DEGs. The comparative analysis between the two genotypes revealed higher and integral tolerance in C-76 through activation of key genes involved in ABA and sucrose metabolic pathways. Interestingly, one SNP from the gene coding F-box protein (Araip.3WN1Q) and another SNP from gene coding for the lipid transfer protein (Aradu.03ENG) showed polymorphism in selected contrasting genotypes. These SNPs after further validation may be useful for performing early generation selection for selecting drought-responsive genotypes.