High-density genetic map using whole-genome re-sequencing for fine mapping and candidate gene discovery for disease resistance in peanut

Authors: AGARWAL, GAURAV - University Of Georgia; CLEVENGER, JOSH - University Of Georgia; PANDEY, MANISH - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India; WANG, HUI - University Of Georgia; SHASIDHAR, YADURU - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India; CHU, Y - University Of Georgia; FOUNTAIN, JAKE - University Of Georgia; CHOUDHARY, DIVYA - University Of Georgia; CULBREATH, A - University Of Georgia; LIU, X - Bgi Shenzhen; HUANG, G - Bgi Shenzhen; WANG, X - Shandong Academy Of Agricultural Sciences; DESHMUKH, R - Laval University; Holbrook, Carl - Corley; BERTIOLI, DAVID - University Of Georgia; OZIAS-AKINS, PEGGY - University Of Georgia; JACKSON, SCOTT - University Of Georgia; VARSHNEY, RAJEEV - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India; Guo, Baozhu

Submitted to: Plant Biotechnology Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/25/2018
Publication Date: 5/19/2018
Citation: Agarwal, G., Clevenger, J., Pandey, M.K., Wang, H., Shasidhar, Y., Chu, Y., Fountain, J.C., Choudhary, D., Culbreath, A.K., Liu, X., Huang, G., Wang, X., Deshmukh, R., Holbrook Jr, C.C., Bertioli, D.J., Ozias-Akins, P., Jackson, S.A., Varshney, R.K., Guo, B. 2018. High-density genetic map using whole-genome re-sequencing for fine mapping and candidate gene discovery for disease resistance in peanut. Plant Biotechnology Journal. 16:1954-1967. https://doi.org/10.1111/pbi.12930.
DOI: https://doi.org/10.1111/pbi.12930

Interpretive Summary: The development of high density genetic maps is a requirement for the fine mapping of loci/markers linked to important quantitative traits such as disease resistance. Here, we have presented the first high density genetic map currently available for cultivated peanut by using whole genome sequencing approach. With this high density map, we could identify 35 major chromosome regions with molecular markers for important peanut disease resistance such as early leaf spot, late leaf spot, and TSWV. The markers with the highest contribution (more than 40%) to the resistance to all three diseases also allowed for the development of PCR-based simple markers for potential molecular breeding by using molecular genetic technology. These PCR-based markers provide peanut breeders with a useful tool to improve marker assisted selection in breeding programs for fast and more efficient selection. In addition, the generation of this high density genetic map also allows for functional gene identification and could be used as reference for future genome assemblies for cultivated peanut.

Technical Abstract: High-density genetic linkage maps are essential for fine mapping QTLs controlling disease resistance traits, such as early leaf spot (ELS), late leaf spot (LLS), and Tomato spotted wilt virus (TSWV). With completion of the genome sequences of two diploid ancestors of cultivated peanut, we could use whole-genome re-sequencing (WGRS) technology to genotype recombinant inbred line (RIL) population, develop SNP-based high-density genetic map, and conduct fine mapping of disease resistance QTLs for peanut genomics-assisted breeding (GAB). We constructed the first sequence-based high density map with a total of 8,869 SNPs assigned to 20 linkage groups, representing the 20 chromosomes, for the “T” RIL population which was derived from “Tifrunner” × “GT-C20”. The total length of the linkage map was 3,120 cM with an average distance of 1.45 cM among 2,156 loci. The QTL analysis identified a total of 35 main-effect QTLs (M-QTLs) across all three diseases with phenotypic variation explained (PVE) ranging from 6.32 to 47.63%, including two QTLs for ELS with 47.42% PVE on chromosome B05 and 47.38% PVE on chromosome B03, one QTL for LLS with 47.63% PVE on chromosome A05, and one QTL for TSWV with 40.71% PVE on chromosome B09. The epistasis and environment interaction analyses identified significant environmental effects on these traits. However, these chromosome regions were found to contain genes related to disease resistance including putative R-genes and transcription factors. KASP markers were developed for the SNPs associated with the major QTLs and validated in the population. These markers showed a good correlation with the disease score data, which demonstrated the potential application in genomics assisted breeding (GAB) and marker assisted selection (MAS) in peanut breeding.