Open AccessGenome‐wide mapping and prediction of plant architecture in a sorghum nested association mapping population
Author(s) -
Olatoye Marcus O.,
Hu Zhenbin,
Morris Geoffrey P.
Publication year - 2020
Publication title -
the plant genome
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 41
ISSN - 1940-3372
DOI - 10.1002/tpg2.20038
Subject(s) - biology , quantitative trait locus , genetic architecture , association mapping , sorghum , population , genetics , genome wide association study , candidate gene , trait , genetic association , plant breeding , allele , gene mapping , genetic linkage , family based qtl mapping , plant genetics , genome , computational biology , gene , genotype , agronomy , single nucleotide polymorphism , chromosome , demography , sociology , computer science , programming language
Modifying plant architecture is often necessary for yield improvement and climate adaptation, but we lack understanding of the genotype‐phenotype map for plant morphology in sorghum. Here, we use a nested association mapping (NAM) population that captures global allelic diversity of sorghum to characterize the genetics of leaf erectness, leaf width (at two stages), and stem diameter. Recombinant inbred lines ( n = 2200) were phenotyped in multiple environments (35,200 observations) and joint linkage mapping was performed with ∼93,000 markers. Fifty‐four QTL of small to large effect were identified for trait BLUPs (9–16 per trait) each explaining 0.4–4% of variation across the NAM population. While some of these QTL colocalize with sorghum homologs of grass genes (e.g., those involved in transcriptional regulation of hormone synthesis [rice SPINDLY ] and transcriptional regulation of development [rice Ideal plant architecture1 ]), most QTL did not colocalize with an a priori candidate gene (92%). Genomic prediction accuracy was generally high in five‐fold cross‐validation (0.65–0.83), and varied from low to high in leave‐one‐family‐out cross‐validation (0.04–0.61). The findings provide a foundation to identify the molecular basis of architecture variation in sorghum and establish genomic‐enabled breeding for improved plant architecture.