Main effect and epistatic QTL affecting spike shattering and association with plant height revealed in two spring wheat (Triticum aestivum L.) populations

Discovery and validation of SSR marker-based QTL governing fresh pod yield in dolichos bean (Lablab purpureus L. Sweet)

Identification and validation of quantitative trait loci (QTL) governing desired phenotype of target trait is a prerequisite to implement marker-assisted selection in any crop including dolichos bean. Under this premise, we used two mapping populations (MPs) to detect and cross population validate QTL controlling fresh pod yield. One of the MPs consisted of F2 individuals (MP1) derived from crossing two elite genotypes, the second MP consisted of random RILs (MP2) derived from a different pair of elite genotypes. The MP1 and MP2 were genotyped using polymorphic 86 and 91 SSR markers, respectively and linkage maps were constructed using QTL IciM mapping software. The MP1 and MP2 were phenotyped during 2021 and 2017 rainy and post rainy seasons, respectively for fresh pod yield plant-1 following two-replicated simple lattice design. QTL maps were developed in MP1 and MP2 using genotype and phenotype data. Our results indicated that the estimates of total map length, average map length per linkage group (LG) and average inter-marker distance in MP2 were greater (by at least 1.5 times) than those in MP1. While seven QTLs were detected in MP1, six were detected in MP2 with three QTL exhibiting positive and additive minor effects for fresh pod yield plant-1. We also detected one common minor positive effect QTL across two seasons in MP2 and significant epistatic QTL, whose main effects were non-significant. One each of the seven and six QTL-linked SSR markers detected in MP1 and MP2, respectively were cross-population validated. The implications of these results are discussed in relation to strategies to breed dolichos bean.

The use of weighted multiple linear regression to estimate QTL × QTL × QTL interaction effects of winter wheat (Triticum aestivum L.) doubled-haploid lines

Knowledge of the magnitude of gene effects and their interactions, their nature, and contribution to determining quantitative traits is very important in conducting an effective breeding program. In traditional breeding, information on the parameter related to additive gene effect and additive-additive interaction (epistasis) and higher-order additive interactions would be useful. Although commonly overlooked in studies, higher-order interactions have a significant impact on phenotypic traits. Failure to account for the effect of triplet interactions in quantitative genetics can significantly underestimate additive QTL effects. Understanding the genetic architecture of quantitative traits is a major challenge in the post-genomic era, especially for quantitative trait locus (QTL) effects, QTL-QTL interactions, and QTL-QTL-QTL interactions. This paper proposes using weighted multiple linear regression to estimate the effects of triple interaction (additive-additive-additive) quantitative trait loci (QTL-QTL-QTL). The material for the study consisted of 126 doubled haploid lines of winter wheat (Mandub × Begra cross). The lines were analyzed for 18 traits, including percentage of necrosis leaf area, percentage of leaf area covered by pycnidia, heading data, and height. The number of genes (the number of effective factors) was lower than the number of QTLs for nine traits, higher for four traits and equal for five traits. The number of triples for unweighted regression ranged from 0 to 9, while for weighted regression, it ranged from 0 to 13. The total aaagu effect ranged from - 14.74 to 15.61, while aaagw ranged from - 23.39 to 21.65. The number of detected threes using weighted regression was higher for two traits and lower for four traits. Forty-nine statistically significant threes of the additive-by-additive-by-additive interaction effects were observed. The QTL most frequently occurring in threes was 4407404 (9 times). The use of weighted regression improved (in absolute value) the assessment of QTL-QTL-QTL interaction effects compared to the assessment based on unweighted regression. The coefficients of determination for the weighted regression model were higher, ranging from 0.8 to 15.5%, than for the unweighted regression. Based on the results, it can be concluded that the QTL-QTL-QTL triple interaction had a significant effect on the expression of quantitative traits. The use of weighted multiple linear regression proved to be a useful statistical tool for estimating additive-additive-additive (aaa) interaction effects. The weighted regression also provided results closer to phenotypic evaluations than estimator values obtained using unweighted regression, which is closer to the true values.

Mapping of QTLs and meta-QTLs for Heterodera avenae Woll. resistance in common wheat (Triticum aestivum L.)

BACKGROUND

In hexaploid wheat, quantitative trait loci (QTL) and meta-QTL (MQTL) analyses were conducted to identify genomic regions controlling resistance to cereal cyst nematode (CCN), Heterodera avenae. A mapping population comprising 149 RILs derived from the cross HUW 468 × C 306 was used for composite interval mapping (CIM) and inclusive composite interval mapping (ICIM).

RESULTS

Eight main effect QTLs on three chromosomes (1B, 2A and 3A) were identified using two repeat experiments. One of these QTLs was co-localized with a previously reported wheat gene Cre5 for resistance to CCN. Seven important digenic epistatic interactions (PVE = 5% or more) were also identified, each involving one main effect QTL and another novel E-QTL. Using QTLs earlier reported in literature, two meta-QTLs were also identified, which were also used for identification of 57 candidate genes (CGs). Out of these, 29 CGs have high expression in roots and encoded the following proteins having a role in resistance to plant parasitic nematodes (PPNs): (i) NB-ARC,P-loop containing NTP hydrolase, (ii) Protein Kinase, (iii) serine-threonine/tyrosine-PK, (iv) protein with leucine-rich repeat, (v) virus X resistance protein-like, (vi) zinc finger protein, (vii) RING/FYVE/PHD-type, (viii) glycosyl transferase, family 8 (GT8), (ix) rubisco protein with small subunit domain, (x) protein with SANT/Myb domain and (xi) a protein with a homeobox.

CONCLUSION

Identification and selection of resistance loci with additive and epistatic effect along with two MQTL and associated CGs, identified in the present study may prove useful for understanding the molecular basis of resistance against H. avenae in wheat and for marker-assisted selection (MAS) for breeding CCN resistant wheat cultivars.

Plant biochemical genetics in the multiomics era

Our understanding of plant biology has been revolutionized by modern genetics and biochemistry. However, biochemical genetics can be traced back to the foundation of Mendelian genetics; indeed, one of Mendel's milestone discoveries of seven characteristics of pea plants later came to be ascribed to a mutation in a starch branching enzyme. Here, we review both current and historical strategies for the elucidation of plant metabolic pathways and the genes that encode their component enzymes and regulators. We use this historical review to discuss a range of classical genetic phenomena including epistasis, canalization, and heterosis as viewed through the lens of contemporary high-throughput data obtained via the array of approaches currently adopted in multiomics studies.

Natural variation and genetic loci underlying resistance to grain shattering in standing crop of modern wheat

Modern wheat (Triticum aestivum L.) cultivars have a free-threshing habit, which allows for easy manual or mechanical threshing. However, when harvesting is delayed or extreme weather events occur at harvest time, grain shattering can cause severe loss of harvestable yield. In the past, grain size was considered a predisposing factor as large, plump kernels can lead to buckling and breaking of the outer glume, but the correlation between glume strength and shattering is not strong in modern wheat, and it is hypothesised that there may be other genetic mechanisms. Data from two bi-parent populations and a wheat diversity panel were analyzed to explore the underlying genetic basis for grain shattering observed in multiple field experiments through quantitative trait loci (QTL) analysis. Grain shattering had a significant and negative association with grain yield, irrespective of populations and environments. The correlation with plant height was positive in all populations, but correlations with phenology were population specific, being negative in the diversity panel and the Drysdale × Waagan population, and positive in the Crusader × RT812 population. In the wheat diversity panel, allelic variations at well-known major genes (Rht-B1, Rht-D1 and Ppd-D1) showed minimal association with grain shattering. Instead, the genome-wide analysis identified a single locus on chromosome 2DS, which explained 50% of the phenotypic variation, and mapping to ~ 10 Mb from Tenacious glume (Tg) gene. In the Drysdale × Waagan cross, however, the reduced height (Rht) genes showed major effects on grain shattering. At the Rht-B1 locus, the Rht-B1b allele was associated with 10.4 cm shorter plant height, and 18% decreased grain shattering, whereas Rht-D1b reduced plant height by 11.4 cm and reduced grain shattering by 20%. Ten QTL were detected in the Crusader × RT812, including a major locus detected on the long arm of chromosome 5A. All the QTL identified in this population were non-pleiotropic, as they were still significant even after removing the influence of plant height. In conclusion, these results indicated a complex genetic system for grain shattering in modern wheat, which varied with genetic background, involved pleiotropic as well as independent gene actions, and which might be different from shattering in wild wheat species caused by major domestication genes. The influence of Rht genes was confirmed, and this provides valuable information in breeding crops of the future. Further, the SNP marker close to Tg on chromosome 2DS should be considered for utility in marker-assisted selection.

Form follows function in Triticeae inflorescences

Grass inflorescences produce grains, which are directly connected to our food. In grass crops, yields are mainly affected by grain number and weight; thus, understanding inflorescence shape is crucially important for cereal crop breeding. In the last two decades, several key genes controlling inflorescence shape have been elucidated, thanks to the availability of rich genetic resources and powerful genomics tools. In this review, we focus on the inflorescence architecture of Triticeae species, including the major cereal crops wheat and barley. We summarize recent advances in our understanding of the genetic basis of spike branching, and spikelet and floret development in the Triticeae. Considering our changing climate and its impacts on cereal crop yields, we also discuss the future orientation of research.