scholarly journals Genetic dissection of maize plant architecture using a novel nested association mapping population

2021 ◽  
Author(s):  
Sheng Zhao ◽  
Xueying Li ◽  
Junfeng Song ◽  
Huimin Li ◽  
Xiaodi Zhao ◽  
...  
Author(s):  
Marcus O. Olatoye ◽  
Zhenbin Hu ◽  
Geoffrey P. Morris

AbstractModifying 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. involved in hormone synthesis (maize spi1), floral transition (SbCN8), and transcriptional regulation of development (rice Ideal plant architecture1)], most QTL did not colocalize with an a priori candidate gene (82%). 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.Core ideasUnderstanding the genetics of plant architecture could facilitate the development of crop ideotypes for yield and adaptationThe genetics of plant architecture traits was characterized in sorghum using multi-environment phenotyping in a global nested association mapping populationFifty-five quantitative trait loci were identified; some colocalize with homologs of known developmental regulators but most do notGenomic prediction accuracy was consistently high in five-fold cross-validation, but accuracy varied considerably in leave-one-family-out predictions


Genetics ◽  
2017 ◽  
Vol 206 (2) ◽  
pp. 573-585 ◽  
Author(s):  
Sophie Bouchet ◽  
Marcus O. Olatoye ◽  
Sandeep R. Marla ◽  
Ramasamy Perumal ◽  
Tesfaye Tesso ◽  
...  

2019 ◽  
Vol 13 (2) ◽  
pp. 261-269 ◽  
Author(s):  
Sajjan Grover ◽  
Braden Wojahn ◽  
Suresh Varsani ◽  
Scott E. Sattler ◽  
Joe Louis

Sign in / Sign up

Export Citation Format

Share Document