Micronutrient deficiencies, and especially zinc (Zn) deficiency, pose serious health problems to people who mainly depend on cereal-based diets. Here, we performed a genome-wide association study (GWAS) to detect the genetic basis of the Zn accumulation in wheat (Triticum aestivum L.) grains with a diversity panel of 207 bread wheat varieties. To uncover authentic quantitative trait loci (QTL) controlling Zn accumulation, the varieties were planted in three locations. In total, 29 unique loci associated with Zn grain accumulation were identified. Notably, seven non-redundant loci located on chromosomes 1B, 3B, 3D, 4A, 5A, 5B, and 7A, were detected at least in two environments. Of these quantitative trait loci (QTL), six coincided with known QTL or genes, whereas the highest effect QTL on chromosome 3D identified in this study was not reported previously. Searches of public databases revealed that the seven identified QTL coincided with seven putative candidate genes linked to Zn accumulation. Among these seven genes, NAC domain-containing protein gene (TraesCS3D02G078500) linked with the most significant single nucleotide polymorphism (SNP) AX-94729264 on chromosome 3D was relevant to metal accumulation in wheat grains. Results of this study provide new insights into the genetic architecture of Zn accumulation in wheat grains.

Background: Hexaploid wheat (Triticum aestivum L.) is a leading cereal crop worldwide. Understanding the mechanism of calcium (Ca) accumulation in wheat is important to reduce the risk of human micronutrient deficiencies. However, the mechanisms of Ca accumulation in wheat grain are only partly understood. Results: Here, a genome-wide association study (GWAS) was performed to dissect the genetic basis of Ca accumulation in wheat grain using an association population consisting of 207 varieties, with phenotypic data from three locations. In total, 11 non-redundant genetic loci associated with Ca concentration were identified and they explained, on average, 9.61–26.93% of the phenotypic variation. Cultivars containing more superior alleles had increased grain Ca concentrations. Notably, four non-redundant loci were mutually verified by different statistical models in at least two environments, indicating their stability across different environments. Four putative candidate genes linked to Ca accumulation were revealed from the stable genetic loci. Among them, two genes, associated with the stable genetic loci on chromosomes 4A (AX-108912427) and 3B (AX-110922471), encode the subunits of V-type Proton ATPase (TraesCS4A02G428900 and TraesCS3B02G241000), which annotated as the typical generators of a proton gradient that might be involved in Ca homeostasis in wheat grain. Conclusion: To identify genetic loci associated with Ca accumulation, we conducted GWAS on Ca concentrations and detected 11 genetic loci; whereas four genetic loci were stable across different environments. A genetic loci hot spot exists at the end of chromosome 4A and associated with the putative candidate gene TraesCS4A02G428900. The candidate gene TraesCS4A02G428900 encodes V-type proton ATPase subunit e and highly expressed in wheat grains, and it possibly involved in Ca accumulation. This study increases our understanding of the genetic architecture of Ca accumulation in wheat grains, which is potentially helpful for wheat Ca biofortification pyramid breeding.

Grain number per spike, a pivotal agronomic trait dictating wheat yield, lacks a comprehensive understanding of its underlying mechanism in Pubing3228, despite the identification of certain pertinent genes. Thus, our investigation sought to ascertain molecular markers and candidate regions associated with grain number per spike through a high-density genetic mapping approach that amalgamates site-specific amplified fragment sequencing (SLAF-seq) and bulked segregation analysis (BSA). To facilitate this, we conducted a comparative analysis of two wheat germplasms, Pubing3228 and Jing4839, known to exhibit marked discrepancies in spike shape. By leveraging this methodology, we successfully procured 2,810,474 SLAF tags, subsequently resulting in the identification of 187,489 single nucleotide polymorphisms (SNPs) between the parental strains. We subsequently employed the SNP-index association algorithm alongside the extended distribution (ED) association algorithm to detect regions associated with the trait. The former algorithm identified 24 trait-associated regions, whereas the latter yielded 70. Remarkably, the intersection of these two algorithms led to the identification of 25 trait-associated regions. Amongst these regions, we identified 399 annotated genes, including three genes harboring non-synonymous mutant SNP loci. Notably, the APETALA2 (AP2) transcription factor families, which exhibited a strong correlation with spike type, were also annotated. Given these findings, it is plausible to hypothesize that these genes play a critical role in determining spike shape. In summation, our study contributes significant insights into the genetic foundation of grain number per spike. The molecular markers and candidate regions we have identified can be readily employed for marker-assisted breeding endeavors, ultimately leading to the development of novel wheat cultivars possessing enhanced yield potential. Furthermore, conducting further functional analyses on the identified genes will undoubtedly facilitate a comprehensive elucidation of the underlying mechanisms governing spike development in wheat.

Agropyron cristatum (L.) can be used as a valuable gene resource for broadening the genetic basis of common wheat in breeding programs. Pubing3228 is a new elite wheat-Agropyron hybrid germplasm that possesses many desirable agronomical traits, includingthe grain number per spike (GNS), the main yield component. Uncovering the genetic architecture of GNS in Pubing3228 is important for increasing wheat yield through molecular assisted breeding. In the present study, genetic regions and alleles associated with high GNS from Pubing3228 were analyzed using a recombination inbred line (RIL) population derived from the cross between Pubing3228 and Jing4839. In total, 75 QTLs were identified for GNS. These QTLs mapped to 21 chromosomes (i.e.,all except for 5B and 6A) and explained 3.30–17.17% of the total phenotypic variation. Five QTLs (QGns.wa-1D, QGns.wa-5A, QGns.wa-7D.1, QGns.wa-7D.2, and QGns.wa-7D.3) explained more than 10% of the phenotypic variation in at least two environments. Pubing3228 contributed 94.67% of the total number of QTLs associated with GNS. Candidate gene analysis was conducted for the stable QTLs, and 11 candidate genes were obtained for GNS. Among these 11 genes, a senescence-associated protein gene (TraesCS7D01G148000) linked with the most significant single nucleotide polymorphism (SNP) AX-108748734 on chromosome 7D was relevant to remobilizing the nutrients from the senescing tissues to the developing seeds. The findings of this study will not only provide new insights into the genetic mechanism of high GNS of Pubing3228 but willalso be useful for marker-assisted selection for yield improvement in breeding practice.

Insect herbivores often exhibit host preference and feeding differentiation underpinning fine-scale niche partitioning, yet their linkage to larval performance remains poorly understood. On the Qinghai–Tibet Plateau, two sympatric leaf beetles, Chrysomela vigintipunctata alticola (CV) and Phratora vitellinae (PV) (both Coleoptera: Chrysomelidae), co-occur on two willow species occupying distinct microhabitats: CV predominantly uses abundant Salix atopantha (SW), while PV specializes on rare Salix wangiana var. tibetica (LW) (both Malpighiales: Salicaceae). To disentangle intrinsic feeding response from natal-host induction, we combined dual-choice feeding bioassays with controlled natal-host rearing experiments using first-instar larvae originating from both hosts, and evaluated fitness consequences in terms of morphology and instar duration. PV larvae exhibited a consistent preference for LW, coupled with wider head capsules. In contrast, CV larvae showed no intrinsic preference; specifically, those from SW remained non-selective, while those from LW developed a delayed preference. CV larvae developed faster on nitrogen-rich SW, whereas LW contained higher salicylate esters. These results indicate that PV prioritizes growth and chemical defensive sequestration on LW, whereas CV prioritizes rapid development by utilizing the nutrient-rich SW. Our results reveal distinct resource-use patterns and life-history strategies that facilitate local co-occurrence of the two leaf beetles within the alpine meadow ecosystem.