Optimization of heading date (HD) and spike formation, two sequential development phases, is essential for improving wheat acclimation and yield. Identification of quantitative trait loci (QTL) for HD and spikelet number will contribute to breeding early maturing and high-yielding cultivars. Zhongmai 578 (ZM578) and Jimai 22 (JM22) are elite cultivars with significant differences in HD and spikelet number. Here, 14 environmentally stable QTL for HD, spikelet number per spike (SNS), and fertile spikelet number per spike (FSN) were identified in a population of 262 recombinant inbred lines from the cross ZM578/JM22. Among them, QHd.caas-3A.1, QHd.caas-4A, QHd.caas-5B, QHd.caas-7A, QHd.caas-7D, QFsn.caas-7A, QSns.caas-7A, and QSns.caas-7D explained up to 13.4%, 14.5%, 49.7%, 14.6%, 11.3%, 35.6%, 34.1%, and 16.2% of the phenotypic variances, respectively. Genome resequencing, transcriptome, and genetic linkage analyses identified TaFT-A1 and TaSEP3-D1 as candidate genes for QHd.caas-7A and QTL pair QHd.caas-7D and QSns.caas-7D, respectively. WAPO-A1 was identified as a candidate gene for the QTL cluster that included QSns.caas-7A and QFsn.caas-7A. We also predicted candidate genes for the remaining stable QTL based on genome and transcriptome analyses. Considering that the genetic effect of WAPO-A1 was confirmed previously, we developed breeder-friendly markers for the other major QTL to validate genetic effects in a diverse wheat cultivar panel. Marker-trait association analyses revealed that the favorable alleles of these QTL, except QHd.caas-5B, conferred early HD without yield penalty, which was also confirmed by pyramiding effects. These results provide useful genetic resources and molecular tools for improving adaptation and yield potential in wheat.

Non-destructive time-series assessment of chlorophyll content in flag-leaf (FLC) accurately mimics the senescence rate and the identification of genetic loci associated with senescence provides valuable knowledge to improve yield stability under stressed environments. In this study, we employed both unmanned aerial vehicles (UAVs) equipped with red–green–blue (RGB) camera and ground-based SPAD-502 instrument to conduct temporal phenotyping of senescence. A total of 262 recombinant inbred lines derived from the cross of Zhongmai 578/ Jimai 22 were evaluated for senescence-related traits across three environments, spanning from heading to 35 d post-anthesis. The manual senescence rate (MSR) was quantified using the FLC and the active accumulated temperature, and UAV derived vegetation index were utilized to assess the stay-green rate (USG) facilitating the identification of senescent and stay-green lines. Results indicated that higher senescence rates significantly impacted grain yield, primarily by influencing thousand-kernel weight, and plant height. Quantitative trait loci (QTL) mapping for FLC, USG, and MSR using the 50K SNP array identified 38 stable loci associated with RGB-based vegetation indices and senescence-related traits: among which 19 loci related to senescence traits from UAV and FLC were consistently detected across at least two growth stages, with nine loci likely representing novel QTL. This study highlights the potential of UAV-based high-throughput phenotyping and phenology in identifying critical loci associated with senescence rates in wheat, validating the relationship between senescence rates and yield-related traits in wheat, offering valuable opportunities for gene discovery and significant applications in breeding programs.

Large grain is a favorable trait for appearance quality and a large sink potential in wheat breeding. The stable QTL QGl.caas-5BS for grain length was previously identified in a recombinant inbred line population from the cross of Zhongmai 871 (ZM871) and its sister line Zhongmai 895 (ZM895). Here, a BC₁F₆ residual heterozygous line was selected from the cross of a ZM871/ZM895//ZM871 population, and six heterozygous recombinant plants were identified in the BC₁F₇ population from self-pollination of the heterozygous line. QGl. caas-5BS was delimited into an interval of approximately 2.2 Mb flanked by markers Kasp_5B33 and Kasp_5B2 (25.3–27.5 Mb) by phenotyping and genotyping the secondary mapping populations derived from these heterozygous recombinant plants. Five genes were predicted as candidates of QGl.caas-5BS based on sequence polymorphism and differential expression analyses. Further mutation analysis showed that TraesCS5B02G026800 is likely the causal gene of QGl.caas-5BS. The gene-specific marker Kasp_5B_Gl for TraesCS5B02G026800 was developed, and a significant genetic effect of QGl.caas-5BS on grain length was identified in a validation population of 166 cultivars using this marker. These findings lay a good foundation for map-based cloning of QGl.caas-5BS and provide a breeding-applicable marker for the improvement of grain length in wheat.

Black point is a black discoloration of the grain embryo that reduces the grain quality and commodity grade. Identifying the underlying genetic loci can facilitate the improvement of black point resistance in wheat. Here, 262 recombinant inbred lines (RILs) from the cross of Zhongmai 578/Jimai 22 were evaluated for their black point reactions in five environments. A high-density genetic linkage map of the RIL population was constructed with the wheat 50K single nucleotide polymorphism (SNP) array. Six stable QTLs for black point resistance were detected, QBp.caas-2A, QBp.caas-2B1, QBp.caas-2B2, QBp.caas-2D, QBp.caas-3A, and QBp.caas-5B, which explained 2.1–28.8% of the phenotypic variances. The resistance alleles of QBp.caas-2B1 and QBp.caas-2B2 were contributed by Zhongmai 578 while the others were from Jimai 22. QBp.caas-2B2, QBp.caas-2D and QBp.caas-3A overlapped with previously reported loci, whereas QBp.caas-2A, QBp.caas-2B1 and QBp.caas-5B are likely to be new. Five kompetitive allele-specific PCR (KASP) markers, Kasp_2A_BP, Kasp_2B1_BP, Kasp_2B2_BP, Kasp_3A_BP, and Kasp_5B_BP, were validated in a natural population of 165 cultivars. The findings of this study provide useful QTLs and molecular markers for the improvement of black point resistance in wheat through marker-assisted breeding.

Pre-harvest sprouting (PHS) is one of the serious global issues in wheat production. Identification of quantitative trait loci (QTL) and closely-linked markers is greatly helpful for wheat improvement. In the present study, a recombinant inbred line (RIL) population derived from the cross of Zhongmai 578 (ZM578)/Jimai 22 (JM22) and parents were phenotyped in five environments and genotyped by the wheat 50 K single-nucleotide polymorphism (SNP) array. Two QTL of germination index (GI), QGI.caas-3A and QGI.caas-5A, were detected, explaining 4.33%–5.58% and 4.43%–8.02% of the phenotypic variances, respectively. The resistant effect of QGI.caas-3A was contributed by JM22, whereas that of QGI.caas.5A was from ZM578. The two QTL did not correspond to any previously identified genes or genetic loci for PHS-related traits according to their locations in the Chinese Spring reference genome, indicating that they are likely to be new loci for PHS resistance. Four kompetitive allele-specific PCR (KASP) markers K_AX-109605367and K_AX-179559687 flanking QGI.caas-3A, and K_AX-111258240 and K_AX-109402944 flanking QGI.caas-5A, were developed and validated in a natural population of 100 wheat cultivars. The distribution frequency of resistance alleles at Qphs.caas-3A and Qphs.caas-5A loci were 82.7% and 57.1%, respectively, in the natural population. These findings provide new QTL and tightly linked KASP markers for improvement of PHS resistance in wheat.

In wheat breeding, it is a difficult task to select the most suitable parents for making crosses aimed at the improvement of both grain yield and grain quality. By quantitative genetics theory, the best cross should have high progeny mean and large genetic variance, and ideally yield and quality should be less negatively or positively correlated. Usefulness is built on population mean and genetic variance, which can be used to select the best crosses or populations to achieve the breeding objective. In this study, we first compared five models (RR-BLUP, Bayes A, Bayes B, Bayes ridge regression, and Bayes LASSO) for genomic selection (GS) with respect to prediction of usefulness of a biparental cross and two criteria for parental selection, using simulation. The two parental selection criteria were usefulness and midparent genomic estimated breeding value (GEBV). Marginal differences were observed among GS models. Parental selection with usefulness resulted in higher genetic gain than midparent GEBV. In a population of 57 wheat fixed lines genotyped with 7588 selected markers, usefulness of each biparental cross was calculated to evaluate the cross performance, a key target of breeding programs aimed at developing pure lines. It was observed that progeny mean was a major determinant of usefulness, but the usefulness ratings of quality traits were more influenced by their genetic variances in the progeny population. Near-zero or positive correlations between yield and major quality traits were found in some crosses, although they were negatively correlated in the population of parents. A selection index incorporating yield, extensibility, and maximum resistance was formed as a new trait and its usefulness for selecting the crosses with the best potential to improve yield and quality simultaneously was calculated. It was shown that applying the selection index improved both yield and quality while retaining more genetic variance in the selected progenies than the individual trait selection. It was concluded that combining genomic selection with simulation allows the prediction of cross performance in simulated progenies and thereby identifies candidate parents before crosses are made in the field for pure-line breeding programs.