Kernel size‐related genes revealed by an integrated eQTL analysis during early maize kernel development

Abstract

SummaryIn maize, kernel traits strongly impact overall grain yields, and it is known that sophisticated spatiotemporal programs of gene expression coordinate kernel development, so advancing our knowledge of kernel development can help efforts to improve grain yields. Here, using phenotype, genotype and transcriptomics data of maize kernels at 5 and 15 days after pollination (DAP) for a large association mapping panel, we employed multiple quantitative genetics approaches—genome‐wide association studies (GWAS) as well as expression quantitative trait loci (eQTL) and quantitative trait transcript (QTT) analyses—to gain insights about molecular genetic basis of kernel development in maize. This resulted in the identification of 137 putative kernel length‐related genes at 5 DAP, of which 43 are located in previously reported QTL regions. Strikingly, we identified an eQTL that overlaps the locus encoding a maize homolog of the recently described m6A methylation reader protein ECT2 from Arabidopsis; this putative epieQTL is associated with 53 genes and may represent a master epi‐transcriptomic regulator of kernel development. Notably, among the genes associated with this epieQTL, 10 are for the main storage proteins in the maize endosperm (zeins) and two are known regulators of zein expression or endosperm development (Opaque2 and ZmICE1). Collectively, beyond cataloging and characterizing genomic attributes of a large number of eQTL associated with kernel development in maize, our study highlights how an eQTL approach can bolster the impact of both GWAS and QTT studies and can drive insights about the basic biology of plants.

Whole-organism eQTL mapping at cellular resolution with single-cell sequencing

“…The extent to which eQTL hotspots play a role in determining biological phenotypes is unknown, although several examples have been described in animals and plants ( Albert and Kruglyak, 2015 ; Brynedal et al, 2017 ; Pang et al, 2019 ; Andersen et al, 2014 ; Orozco et al, 2012 ). One of the neuronal hotspots we identified in this study affects the expression of members of the TGF-β pathway, which has been linked to the control of body size in C. elegans ( Gumienny, 2013 ).…”

Association Mapping and Transcriptome Analysis Reveal the Genetic Architecture of Maize Kernel Size

“…EREB16 and MYBR1 showed over two-fold difference between stages. Pang et al (2019) found that EREB170 and EREB115 were involved in kernel development in an integrated eQTL analysis. Through combined association and linkage mapping, five co-located genes annotated as MYBR1 were significantly associated with KL and KT ( Liu et al, 2020a ).…”

“…Transcriptome has also been employed to detect the underlying genetic architecture responsible for phenotypic variations. By integrating GWAS, expression quantitative trait loci (eQTL), and quantitative trait transcript analyses, Pang et al (2019) identified 137 putative KL-related genes at 5 days after pollination (DAP5) and an eQTL that overlapped the locus encoding a maize homolog of m6A methylation reader protein ECT2 of Arabidopsis . Transcriptome analysis not only reveals a large number of genes associated with kernel size and development but also some biological processes and signaling pathways including DNA methylation, ovule development, cell cycle, cell division, ubiquitin, phytohormone signaling pathways, and transcriptional regulatory factors during seed, endosperm, and embryo development in maize ( Sekhon et al, 2014 ; Zhang et al, 2016 ).…”

Genetic Variation in ZmPAT7 Contributes to Tassel Branch Number in Maize

“…These included nine on chromosome 2, three on chromosome 3, three on chromosome 5, one on chromosome 6, and one on chromosome 7 ( Table 3 ). All the 17 eQTLs were defined as “distant eQTLs” following the previous method proposed by Fu et al (2013) and Pang et al (2019) [ 28 , 29 ]. In total, 44 genes were found in LD distance (200 kb) adjacent to the SNPs ( Table 3 ), among which some transcription factor genes, e.g., Zm00001d038207 ( ZmNAC3 ), may be involved in regulating ZmPAT7 .…”