Allelic response of yield component traits to resource availability in spring wheat

Meta-QTL mapping for wheat thousand kernel weight

Wheat domestication and subsequent genetic improvement have yielded cultivated species with larger seeds compared to wild ancestors. Increasing thousand kernel weight (TKW) remains a crucial goal in many wheat breeding programs. To identify genomic regions influencing TKW across diverse genetic populations, we performed a comprehensive meta-analysis of quantitative trait loci (MQTL), integrating 993 initial QTL from 120 independent mapping studies over recent decades. We refined 242 loci into 66 MQTL, with an average confidence interval (CI) 3.06 times smaller than that of the original QTL. In these 66 MQTL regions, a total of 4,913 candidate genes related to TKW were identified, involved in ubiquitination, phytohormones, G-proteins, photosynthesis, and microRNAs. Expression analysis of the candidate genes showed that 95 were specific to grain and might potentially affect TKW at different seed development stages. These findings enhance our understanding of the genetic factors associated with TKW in wheat, providing reliable MQTL and potential candidate genes for genetic improvement of this trait.

Identification of quantitative trait loci (QTL) and meta-QTL analysis for kernel size-related traits in wheat (Triticum aestivum L.)

BACKGROUND

Kernel size-related traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR) and kernel thickness (KT), are critical determinants for wheat kernel weight and yield and highly governed by a type of quantitative genetic basis. Genome-wide identification of major and stable quantitative trait loci (QTLs) and functional genes are urgently required for genetic improvement in wheat kernel yield. A hexaploid wheat population consisting of 120 recombinant inbred lines was developed to identify QTLs for kernel size-related traits under different water environments. The meta-analysis and transcriptome evaluation were further integrated to identify major genomic regions and putative candidate genes.

RESULTS

The analysis of variance (ANOVA) revealed more significant genotypic effects for kernel size-related traits, indicating the moderate to high heritability of 0.61-0.89. Thirty-two QTLs for kernel size-related traits were identified, explaining 3.06%-14.2% of the phenotypic variation. Eleven stable QTLs were detected in more than three water environments. The 1103 original QTLs from the 34 previous studies and the present study were employed for the MQTL analysis and refined into 58 MQTLs. The average confidence interval of the MQTLs was 3.26-fold less than that of the original QTLs. The 1864 putative candidate genes were mined within the regions of 12 core MQTLs, where 70 candidate genes were highly expressed in spikes and kernels by comprehensive analysis of wheat transcriptome data. They were involved in various metabolic pathways, such as carbon fixation in photosynthetic organisms, carbon metabolism, mRNA surveillance pathway, RNA transport and biosynthesis of secondary metabolites.

CONCLUSIONS

Major genomic regions and putative candidate genes for kernel size-related traits in wheat have been revealed by an integrative strategy with QTL linkage mapping, meta-analysis and transcriptomic assessment. The findings provide a novel insight into understanding the genetic determinants of kernel size-related traits and will be useful for the marker-assisted selection of high yield in wheat breeding.

Tuning of meristem maturation rate increases yield in multiple Triticum aestivum cultivars

Breeding programs aim to improve crop yield and environmental stability for enhanced food security. The principal methodology in breeding for stable yield gain relies on the indirect selection of beneficial genetics by yield evaluation across diverse environmental conditions. This methodology requires substantial resources while delivering a slow pace of yield gain and environmental adaptation. Alternative methods are required to accelerate gain and adaptation, becoming even more imperative in a changing climate. New molecular tools and approaches can enable accelerated creation and deployment of multiple alleles of genes identified to control key traits. With the advent of tools that enable breeding by targeted allelic selection, identifying gene targets associated with an improved crop performance ideotype will become crucial. Previous studies have shown that altered photoperiod regimes increase yield in wheat (Triticum aestivum). In the current study, we have employed such treatments to study the resulting yield ideotype in five spring wheat cultivars. We found that the photoperiod treatment creates a yield ideotype arising from delayed spike establishment rates that are accompanied by increased early shoot expression of TARGET OF EAT1 (TaTOE1) genes. Genes identified in this way could be used for ideotype-based improve crop performance through targeted allele creation and selection in relevant environments.

Genes Impacting Grain Weight and Number in Wheat (Triticum aestivum L. ssp. aestivum)

The primary goal of common wheat (T. aestivum) breeding is increasing yield without negatively impacting the agronomic traits or product quality. Genetic approaches to improve the yield increasingly target genes that impact the grain weight and number. An energetic trade-off exists between the grain weight and grain number, the result of which is that most genes that increase the grain weight also decrease the grain number. QTL associated with grain weight and number have been identified throughout the hexaploid wheat genome, leading to the discovery of numerous genes that impact these traits. Genes that have been shown to impact these traits will be discussed in this review, including TaGNI, TaGW2, TaCKX6, TaGS5, TaDA1, WAPO1, and TaRht1. As more genes impacting the grain weight and number are characterized, the opportunity is increasingly available to improve common wheat agronomic yield by stacking the beneficial alleles. This review provides a synopsis of the genes that impact grain weight and number, and the most beneficial alleles of those genes with respect to increasing the yield in dryland and irrigated conditions. It also provides insight into some of the genetic mechanisms underpinning the trade-off between grain weight and number and their relationship to the source-to-sink pathway. These mechanisms include the plant size, the water soluble carbohydrate levels in plant tissue, the size and number of pericarp cells, the cytokinin and expansin levels in developing reproductive tissue, floral architecture and floral fertility.

Genetic Incorporation of the Favorable Alleles for Three Genes Associated With Spikelet Development in Wheat

The number of spikelets per spike is an important trait that directly affects grain yield in wheat. Three quantitative trait loci (QTLs) associated with spikelet nodes per spike (SNS) were mapped in a population of recombinant inbred lines generated from a cross between two advanced breeding lines of winter wheat based on the phenotypic variation evaluated over six locations/years. Two of the three QTLs are QSns.sxau-2A at the WHEATFRIZZY PANICLE (WFZP) loci and QSns.sxau-7A at the WHEAT ORTHOLOG OF APO1 (WAPO1) loci. The WFZP-A1b allele with a 14-bp deletion at QSns.sxau-2A was associated with increased spikelets per spike. WAPO-A1e, as a novel allele at WAPO1, were regulated at the transcript level that was associated with the SNS trait. The third SNS QTL, QSns.sxau-7D on chromosome 7D, was not associated with homoeologous WAPO-D1 or any other genes known to regulate SNS. The favorable alleles for each of WZFP-A1, WAPO-A1, and QSns.sxau-7D are identified and incorporated to increase up to 3.4 spikelets per spike in the RIL lines. Molecular markers for the alleles were developed. This study has advanced our understanding of the genetic basis of natural variation in spikelet development in wheat.