Genetic basis of kernel starch content decoded in a maize multi‐parent population

Abstract

Summary Starch is the most abundant storage carbohydrate in maize kernels and provides calories for humans and other animals as well as raw materials for various industrial applications. Decoding the genetic basis of natural variation in kernel starch content is needed to manipulate starch quantity and quality via molecular breeding to meet future needs. Here, we identified 50 unique single quantitative trait loci (QTLs) for starch content with 18 novel QTLs via single linkage mapping, joint linkage mapping and a genome‐wide association study in a multi‐parent population containing six recombinant inbred line populations. Only five QTLs explained over 10% of phenotypic variation in single populations. In addition to a few large‐effect and many small‐effect additive QTLs, limited pairs of epistatic QTLs also contributed to the genetic basis of the variation in kernel starch content. A regional association study identified five non‐starch‐pathway genes that were the causal candidate genes underlying the identified QTLs for starch content. The pathway‐driven analysis identified ZmTPS9, which encodes a trehalose‐6‐phosphate synthase in the trehalose pathway, as the causal gene for the QTL qSTA4−2, which was detected by all three statistical analyses. Knockout of ZmTPS9 increased kernel starch content and, in turn, kernel weight in maize, suggesting potential applications for ZmTPS9 in maize starch and yield improvement. These findings extend our knowledge about the genetic basis of starch content in maize kernels and provide valuable information for maize genetic improvement of starch quantity and quality.

Genetic Perturbation of the Starch Biosynthesis in Maize Endosperm Reveals Sugar-Responsive Gene Networks

“…This module is highly correlated with overall starch and sugar levels and is enriched for genes with roles in carbohydrate metabolism ( Figure 5A and Supplementary Table S7 , black module). In addition, Hu S. et al (2021) identified ZmTRPS10 (Zm00001eb192680; called ZmTPS9 in their work) as a QTL for overall starch content and, using mutant analysis, validated this role plus a contribution to seed yield. Taken together, these results indicate that Class-II TPS’s, and specifically ZmTRPS10 , are central players in the transcriptomic response to the sh2 perturbation of maize endosperm.…”

“…Coexpression analysis has also provided insight into the role of Class II TPS’s and the Zm SE1 gene in the maize endosperm. We propose that the previously identified starch content QTL TRPS10 ( Hu S. et al, 2021 ) functions as a key transcriptional regulator of starch production. We also propose that ZmSE1 impacts starch metabolism through its function as a key regulator of altering GA signaling in the kernels.…”

Genetic dissection of QTLs for starch content in four maize DH populations

“…Importantly, a total of 93 overlaps were detected after comparing the four DH populations with results from all types of other populations, including RILs (Cook et al, 2012 ; Guo et al, 2013 ; Yang et al, 2013 ; Nancy et al, 2014 ; Dong et al, 2015 ; Lin et al, 2019 ; Hu et al, 2021 ), F 2:3 families (Liu et al, 2008 ; Zhang et al, 2008 ; Li et al, 2009 ; Wang Y. Z. et al, 2010 ), and backcross-derived lines (Wassom et al, 2008 ) ( Figure 3 , Supplementary Table S2 ).…”

“…Z. et al, 2010 ), and backcross-derived lines (Wassom et al, 2008 ) ( Figure 3 , Supplementary Table S2 ). For instance, qSC-1-1 colocalized with JLM10 (Hu et al, 2021 ); qSC-1-2 colocalized with qSTA4-3 (Hu et al, 2021 ); qSC-1-3 colocalized with JLM24 and qSTA8-1 (Hu et al, 2021 ); qSC-3-1 colocalized with qCT-3-1 (Dong et al, 2015 ); qSC-4-1 colocalized with qSTA1-1 (Hu et al, 2021 ) and qzSTA1-1-1 (Yang et al, 2013 ); and qSC-4-3 colocalized with qCT-5-1 (Dong et al, 2015 ), stc5 (Guo et al, 2013 ), qSTA5-3 and qSTA5-5 (Hu et al, 2021 ), qSTA1-5-1 and qSTA1-5-2 (Wang Y. Z. et al, 2010 ), and qxSTA2-5-1 (Yang et al, 2013 ).…”

“…Eight QTLs were revealed in an intermated B73×Mo17 population, and the gene encoding GLABRA2 expression modulator was nominated as the candidate gene of a major QTL by GWAS and the gene co-expression network analysis (Lin et al, 2019 ). Recently, in a total of 50, 18 novel QTLs were identified by integrating single linkage mapping, joint linkage mapping, and GWAS in a multi-parent population containing six RIL populations (Hu et al, 2021 ). Thus, although common QTLs associated with SC has been reported in different studies, unique QTLs were always specialized in the context of distinct populations and parents, which prompt us to conduct further investigations using relevant germplasm to extend our knowledge on the genetic basis of SC.…”