Theoretical and Applied Genetics最新文献

Key message: Genomic prediction is most effective when balancing heritability and population size; advanced breeding stages suit complex traits, broader training sets improve predictions in simple traits-enabling efficient, earlier selection. Genomic selection can reduce generation intervals and costs, thereby increasing genetic gain in plant breeding. The study aimed to assess the impact of phenotypic data quality, sample size, and diversity across different breeding stages on the accuracy of genomic predictions. We used phenotypic data of the Central European winter bread wheat breeding company W. von Borries-Eckendorf GmbH & Co. KG, comprising 13,773 genotypes evaluated in up to 95 environments in nearly 57,000 plots for grain yield, plant height, protein content and yellow rust resistance. Genotypic data for 6,228 genotypes were generated using a 7,000 SNP Illumina Infinium assay. We implemented genomic best linear unbiased prediction and tested prediction ability within and across breeding stages. Three prediction scenarios were evaluated to examine the prediction ability: (1) within individual breeding stages, (2) across breeding stages, and (3) for most advanced genotypes. Results indicate more accurate models trained on mid- or late-stage phenotypic data for most traits compared to early-stage data. Combining mid- and late-stage data further improved predictions for complex traits like grain yield and yellow rust resistance. These findings highlight the importance of balancing high heritability and appropriate training sets for optimizing genomic predictions, demonstrating the potential of genomic selection as a cornerstone for wheat breeding programs.

Fusarium head blight (FHB), caused by Fusarium graminearum, is one of the most devastating diseases of wheat (Triticum aestivum) and other cereal crops worldwide. Improving FHB resistance has been a major focus in many wheat genetics and breeding programs globally. However, only a few major loci have been effectively deployed, limiting progress in breeding for FHB resistance. To expand the genetic basis of resistance, we developed a modified nested association mapping (NAM) panel comprising four synthetic hexaploid wheat (SHW) lines, ten hard red spring wheat (HRSW) varieties/lines, and 276 BC₁-derived progenies. The panel was genotyped using the 90 K SNP (single nucleotide polymorphism) Infinium array and evaluated for Type II FHB resistance across six environments. The disease evaluations revealed that 15 resistant lines, primarily derived from backcrossing SHW line SW183 (T. dicoccum PI 191091/Aegilops tauschii CIae 26) with HRSW 'Linkert' or 'Glenn,' exhibited resistance levels comparable to the well-known FHB resistance source, Sumai 3. A genome-wide association study (GWAS) identified 19 significant marker-trait associations (MTAs) for FHB resistance. Of these, three SNPs carried resistance alleles from SHW, two from HRSW, and 14 from both parental sources. Sixteen MTAs co-localized with previously reported quantitative trait loci (QTLs) linked to FHB resistance, while three, located on the short arms of chromosomes 1D, 2B, and 4A, appear to be associated with novel resistance loci. The resistant lines developed in this study could serve as new sources for FHB resistance, and their associated resistance loci can be further validated and incorporated into breeding programs. KEY MESSAGE: Three potentially novel loci and sixteen loci overlapping with previously reported regions for Fusarium head blight resistance were identified in a mapping panel derived from synthetic and bread wheat germplasm.

Key message: New wheat-Ae. mutica introgression lines will deliver new genetic variation for hexaploid wheat breeding and provide new information on the distribution of homoeologous recombination between wheat and Ae. mutica. Aegilops mutica Boiss. (2n = 2 × = 14, TT) is a wild relative of wheat that has been underutilised as a source of genetic variation for hexaploid wheat Triticum aestivum L. (2n = 6 × = 42; AABBDD), despite its potential to harbour important genetic diversity for a wide range of agronomically valuable traits. This species has been extensively exploited by the Wheat Research Centre (WRC) at the University of Nottingham to create a diverse resource of wheat-Ae. mutica introgression lines. In this study, we present the most comprehensive transfer of the Ae. mutica genome into wheat to date, with 98% of the genome now present in wheat through the development of new wheat-Ae. mutica introgression lines. These 68 new lines, comprising 57 unique Ae. mutica introgressions, have been characterised using kompetitive allele-specific PCR (KASP) genotyping, multi-colour genomic in situ hybridisation and low coverage whole-genome sequencing. This thorough characterisation has revealed the distribution of homoeologous recombination sites between wheat and Ae. mutica chromosomes, uncovering recombination "hotspots" and novel introgressed segments that were previously undetectable using conventional genotyping methods. This resource significantly expands the genetic diversity available for wheat improvement and offers a powerful platform for linking traits to specific genotypes. The creation and characterisation of this near-complete set of Ae. mutica introgressions will be invaluable for wheat researchers and breeders worldwide.

Verticillium wilt (VW), caused by the soil-borne fungus Verticillium dahliae, stands as one of the most destructive diseases affecting cotton production world-wide. Developing and deploying VW-resistant cotton varieties represents the most effective and sustainable strategy for mitigating the impact of VW. However, breeding VW-resistant upland cotton (Gossypium hirsutum, Gh) varieties is constrained by the limited VW resistance in Gh. One strategy for improving VW resistance of Gh varieties is to introgress resistance alleles from sea-island cotton (Gossypium barbadense, Gb). Interspecific chromosome segment substitution lines (CSSLs) developed based on Gh x Gb offer materials not only for breeding VW-resistant Gh varieties but also for mapping and cloning VW resistance genes. In this study, we used 318 CSSLs derived from Emian-22 (Gh) × 3-79 (Gb) for mapping of VW-resistant QTLs based on phenotypic data collected from 3 years of field disease-nursery based experiments and 1.3 million single nucleotide polymorphisms identified among the CSSLs. A genome-wide association study revealed 77 VW resistance QTLs, with only 12 of them overlapping with known VW resistance loci, suggesting that the CSSL population is a valuable resource for mining novel VW-resistant alleles. In the two VW-resistant QTLs on chromosomes A01 and D12, nonsynonymous mutations were found in several annotated genes related to biotic stress responses. Ghi_D12G018010 (GhHIR1) in the D12 locus was shown to positively contribute to VW resistance, as down-regulating the gene by virus-induced gene silencing led to reduction of VW resistance. The findings of this study provide candidate genes and markers for improving cotton VW resistance through molecular breeding.

Ability to accurately predict multiple growth-related traits over plant developmental trajectories has the potential to revolutionize crop breeding and precision agriculture. Despite increased availability of time-resolved data for multiple traits from high-throughput phenotyping platforms of model plants and crops, genomic prediction is largely applied independently to a small number of traits, often neglecting their dynamics. Here, we compared and contrasted the performance of MegaLMM and dynamicGP as well as hybrid variants, using MegaLMM in place of RR-BLUP for component matrix prediction, which can handle high-dimensional temporal data for multi-trait genomic prediction. The comparative analysis made use of time series for 50 geometric, color, and texture traits in a maize multi-parent advanced generation inter-cross (MAGIC) population. The performance of the approaches was assessed using snapshot and longitudinal accuracy, quantified as the Pearson correlation (PCC) and mean squared error (MSE), thereby providing insight into the ability to predict multiple traits at a single time point or the dynamics of individual traits over the considered time domain, respectively. We found that MegaLMM outperforms dynamicGP in terms of both snapshot and longitudinal PCC over an observed time interval, but not in terms of snapshot MSE. We also analyzed the characteristics of trait developmental trajectories associated with predictive performance. This study goes further to demonstrate that dynamicGP is the only time-dependent genomic prediction approach which can forecast multiple traits beyond the set of training time points and paves the way for careful investigation of factors that affect the capacity to predict dynamics of multiple traits from genetic markers alone.

Seed dormancy is essential to avoid pre-harvest sprouting (PHS), and germination is vital for agricultural production planning and malting. The malting barley genetic resource Chikukei 9713 is PHS tolerant but quickly breaks seed dormancy after harvest. We found that Chikukei 9713 and the barley cultivar Seijo 17 were PHS tolerant because exon-9 of the seed dormancy gene sd1 was of the dormant type. However, the rapidity of breaking seed dormancy depended on the threshing method. Both varieties germinated slowly after hand threshing, whereas Chikukei 9713, but not Seijo 17, germinated quickly after machine threshing. Using the 94 F₂ individuals and 94 F₃ lines populations derived from a cross between Chikukei 9713 and Seijo 17, we found a genetic region that controlled the effect of the threshing method on breaking seed dormancy (named bsd1) located on the short arm of chromosome 2H (23.4-24.9 Mbp) with GRAS-Di (Genotyping by Random Amplicon Sequencing-Direct) and CAPS markers. Further analysis revealed that bsd1 had a maximum LOD score of 21.4 and explained 65% of the variance. Our findings regarding this novel gene are an important genetic resource for stable malting barley production and sowing planning. Utilizing bsd1 and other seed dormancy genes will enable breeding of PHS-resistant barley cultivars that germinate quickly after machine harvesting.

Drought is the primary factor contributing to crop yield loss. Therefore, enhancing the drought tolerance of foxtail millet, a globally significant food crop, is essential for ensuring global food security. We analyzed 425 foxtail millet samples from the Xinjiang Academy of Agricultural Sciences using 1,304,248 highly polymorphic SNPs for a genome-wide association study, and a total of 77 QTL regions were detected across three environments. Linkage disequilibrium (LD) analysis, population genetic structure analysis, K-means clustering, and phylogenetic tree construction revealed that foxtail millet in different subgroups exhibited certain regional differences. The secondary screening of QTL region genes combined with transcriptome analysis identified six genes with significant expression differences. These drought-responsive genes in foxtail millet function as protein kinases, glycosyltransferases, CTP synthetases, and transcription factors. Haplotype analysis identified 8 phenotypically distinct haplotypes in candidate genes associated with drought stress. Expression levels of genes associated with drought tolerance and yield, validated by RT-qPCR, were largely consistent with transcriptome analysis results. This study's results offer a scientifically significant reference for genetic research and improvement in foxtail millet yield under drought stress.

One-third of paddy soils are globally deficient in zinc (Zn) and 40% of Zn loss in the procession from brown rice to polished rice, which results in the global issue of hidden hunger, e.g., the micronutrient deficiencies in the rice-based population of developing countries. In the recent decades, biofortification of cereal food crops with Zn has emerged as a promising solution. Herein, we comprehensively reviewed the entire process of Zn in paddy soil to human diet, including the regulatory mechanism underlying Zn absorption, transport, distribution, and accumulation in rice grain. Moreover, biofortification approaches of Zn have been summarized in conventional breeding, genetic engineering, agronomic management, and seed priming. Meanwhile, entire process and key nodes from paddy soil to human diet consumption were highlighted. Finally, future directions and challenges of Zn biofortification in rice were proposed. These comprehensive results show the great promise for addressing Zn deficiency and promoting the human nutrition.

Key message: Six highly alkali-tolerant wheat germplasms were identified, 206 MTAs related to germination traits and 198 significant PC-MTAs were detected, and 2 KASP markers for resistance breeding were developed. Soil alkalization is a major constraint on global wheat production, making it essential to uncover the genetic mechanisms underlying alkali tolerance during germination. Here, a genome-wide association study (GWAS) was conducted on 314 wheat accessions evaluated under 0.15% Na₂CO₃ stress and control conditions. Phenotypic screening showed a strong suppression of seedling biomass and root growth under alkalinity stress, while germination rate remained largely unaffected. Based on principal component analysis, the accessions were classified into five tolerance groups: six highly tolerant, 57 tolerant, 92 moderate, 110 sensitive, and 35 highly sensitive. GWAS identified 206 significant marker-trait associations (MTAs) for nine germination-related traits, with five loci (MTA25, MTA29, MTA80, MTA129, and MTA166) consistently detected across both conditions. Allelic effect and candidate gene analyses were performed for three of these stable loci (MTA25, MTA29, and MTA80). Principal component analysis-integrated GWAS detected an additional 198 significant MTAs, 51 of which co-localized with phenotype-based MTAs and were validated as core stress-responsive loci. In addition, Kompetitive Allele Specific PCR markers associated with sheath length and germination percentage were developed. These findings enhance our understanding of the genetic basis of alkali tolerance during wheat germination and provide valuable molecular resources for breeding alkali-tolerant wheat varieties.

Key message: Mutations in TaPRR59 impact transcript levels of some key flowering genes and show earlier heading time and reduced plant height. Favorable haplotype TaPRR59-A1-Hapla was positively selected in wheat breeding programs. The circadian clock system is a crucial endogenous rhythmic regulatory mechanism with a significant role in plant growth and development. The pseudo-response regulator (PRR) family is a pivotal component of circadian networks. In the present study, we cloned the wheat PRR family member TaPRR59 and investigated its function using gene editing, transcriptome sequencing, haplotype analysis, and association analysis. The expression profile of TaPRR59 over a 24-h period exhibited a diurnal rhythmic expression pattern. Luciferase transient transcriptional assay demonstrated that TaPRR59 acts as a transcriptional repressor in the nucleus. The taprr59-ABD-KO gene-edited lines produced using the CRISPR/Cas9 genome-editing system had earlier heading time and reduced plant height. Overexpression of TaPRR59-D1 in rice significantly delayed the heading date, reduced plant height and thousand-grain weight, and increased the number of grains per panicle. Transcriptome analysis revealed the transcript levels of several key flowering genes and chlorophyll a-b binding protein-related genes were up- or down-regulated in the taprr59 mutant plants. Association analysis showed that natural variations at TaPRR59-A1, TaPRR59-B1, and TaPRR59-D1 were significantly associated with yield traits such as plant height, thousand-grain weight, and heading date. Geographical analysis showed distinctive distribution characteristics of TaPRR59 haplotypes in different agroecological production zones. Additionally, the significant difference in frequency of the favorable haplotype TaPRR59-A1-Hapla between landraces and modern cultivars indicates that it has been subject to directional selection during wheat breeding. This research provided novel insights into the influence of the circadian clock system on agronomic traits and provided useful molecular markers and genetic resources for wheat breeding.