Theoretical and Applied Genetics最新文献

{"title":"Discovering common and population-specific QTLs for leaf rust resistance in different Barley populations.","authors":"Cathrine Kiel Skovbjerg, Khalid Mahmood, Pernille Sarup, Jihad Orabi, Ellen Margrethe Wahlström, Jens Due Jensen, Lotte Olesen, Just Jensen, Ahmed Jahoor, Guillaume Ramstein","doi":"10.1007/s00122-026-05375-7","DOIUrl":"10.1007/s00122-026-05375-7","url":null,"abstract":"<p><strong>Key message: </strong>Multi-population GWAS lead to identification of common and population-specific QTLs for leaf rust resistance in barley. Genome-wide association studies (GWAS) are a powerful tool for detecting genetic markers associated with traits of interest. However, these studies are typically restricted to a single population, and transferability of identified marker effects across populations is challenged by population differences in linkage, allele frequencies, epistatic effects, and environmental context. When comparing GWAS results between populations, a lack of overlapping signals is often interpreted as a lack of common quantitative trait loci (QTLs), although such discrepancies may result from differences in statistical power to detect signals. In barley (Hordeum vulgare L.), where genetic leaf rust resistance is rapidly overcome by evolving pathogens, identification of cross-population robust and potentially transferable resistance loci is a key task. Here, we present a mixed model approach for multi-population GWAS that estimates correlated marker effects in multiple populations and use this to test for significant effects across and within populations. Applying this model to four barley breeding populations revealed both common and population-specific QTL effects for leaf rust resistance, including loci colocalizing with known Rph genes and novel regions with plausible candidate genes. Multi-population GWAS increased power, revealing signals not detected by GWAS within populations. We categorized the reported QTLs into three groups based on marker-associated allele effects: (1) consistent effect direction across populations, (2) differing effect direction across populations, and (3) present in a single population. The study highlights the transferability and limitations of leaf rust resistance QTLs across different barley populations and provides a general statistical framework to support robust marker-assisted selection across populations.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 10","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13574892/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148971419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combining ability and gene action for grain yield and biofortification traits in pearl millet [Pennisetum glaucum (L.) R. Br.]: implications for breeding high-yielding biofortified hybrids in arid regions.","authors":"Monika Punia, L D Sharma, D K Gothwal, Sohan Lal Kajla, Lalit Kumar Rolaniya, Vaibhav Sharma, Ram Lal Jat","doi":"10.1007/s00122-026-05378-4","DOIUrl":"10.1007/s00122-026-05378-4","url":null,"abstract":"<p><strong>Key message: </strong>Hybrid RIB-9184 × RIB-15131 combines high yield (18.84 g plant⁻¹) with iron (46.16 mg kg⁻¹), zinc (38.86 mg kg⁻¹), and protein (11.91%); Fe-Zn correlation (rg = 0.82) permits simultaneous biofortification. Pearl millet [Pennisetum glaucum (L.) R. Br., syn. Cenchrus americanus (L.) Morrone] is a climate-resilient cereal with inherently high micronutrient levels, making it a priority crop for biofortification. Understanding gene action for yield and nutritional traits is essential for designing effective breeding strategies. Ten diverse inbred lines were crossed in a half-diallel design (Griffing's Method 2, Model 1), and the 55 entries (45 F₁ hybrids + 10 parents) were evaluated across two sowing-date environments in a randomised complete block design with three replications at Jaipur, Rajasthan, India. Biofortification traits (Fe, Zn, protein) showed predominantly additive gene action (Baker's ratio 0.71-0.91) with high heritability (0.90-0.94). G×E interaction was significant for Fe and Zn but genotypic variance was substantially larger, maintaining high heritability; protein showed no G×E interaction. Grain yield was governed largely by non-additive effects (Baker's ratio 0.54) with significant G×E interaction, favouring hybrid breeding. Among parents, RIB-9205 had the highest GCA for Fe (6.65, P < 0.001), RIB-9184 for Zn (3.85, P < 0.001) and protein (0.78, P < 0.001), and RIB-9185 was a balanced combiner for yield (1.39, P < 0.001) and micronutrients. The hybrid RIB-9184 × RIB-15131 ranked first across all five weighting schemes of the multi-trait performance index (1.31), combining grain yield of 18.84 g plant⁻¹ with Fe of 46.16 mg kg⁻¹, Zn of 38.86 mg kg⁻¹, and protein of 11.91%. The strong Fe-Zn correlation (rg = 0.82, P < 0.01) permits simultaneous micronutrient improvement. An integrated approach combining hybrid development for yield with population improvement for micronutrient density is recommended for biofortified pearl millet cultivars in arid regions.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 10","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148956412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From family trials to genomic mate allocation: statistical and genomic strategies to accelerate sugarcane genetic improvement.","authors":"Andrew Rigby, Felicity Atkin, Ben Hayes, Lee Hickey, Seema Yadav","doi":"10.1007/s00122-026-05373-9","DOIUrl":"10.1007/s00122-026-05373-9","url":null,"abstract":"<p><p>Sugarcane (Saccharum spp.) underpins global sugar and bioenergy supply and is increasingly valued as a renewable biomass feedstock. Sustained improvement in commercial traits and resilience is constrained by long breeding cycles, clonal propagation, multi-stage testing, and a highly polyploid, heterozygous, and frequently aneuploid genome with substantial non-additive genetic variation. Genomic selection has demonstrated value for predicting elite-clone performance, yet its operational use remains limited at earlier decision points, including family selection, parent evaluation, and cross design. This review examines the biological, statistical, and genomic factors that shape these decisions, with emphasis on the Australian breeding context based on progeny assessment trials (PATs), clonal assessment trials (CATs), and final assessment trials (FATs). We evaluate challenges arising from family plot means, the use of different full-sib samples as nominal family replicates, spatial heterogeneity, competition, genotype-by-environment interaction, and the partitioning of additive and non-additive effects. We also assess the integration of pedigree and genomic relationship, genotype representation, allele-dosage estimation, aneuploidy, genomic prediction models, and training-population design. We then consider genomic prediction of cross performance and constrained mate allocation as approaches for improving expected family performance, accounting for cross-specific non-additive effects and managing relatedness. We propose a decision-centred framework that links family and clonal data across breeding stages, tracks the propagation of information and uncertainty, and supports parent recycling and cross allocation. We conclude with a practical research agenda for stage-integrated mixed-model and single-step analyses that connect early family evaluation with genomic prediction and cross-level decision support in sugarcane breeding.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 10","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13570833/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148956488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of molecular markers associated with saline-alkali tolerance in rapeseed (Brassica napus L.).","authors":"Xianfei Hou, Fengrui Liu, Ouqi Li, Xiaoyu Ge, Chao He, Chengwei Hu, Rong Jiang, Junlin Chen, Min Zou, Donghai Jia, Qiang Li, Haocui Miao, Jing Wen, Lun Zhao, Heping Wan, Tingdong Fu, Yuanguo Gu, Jinxiong Shen","doi":"10.1007/s00122-026-05376-6","DOIUrl":"10.1007/s00122-026-05376-6","url":null,"abstract":"<p><strong>Key message: </strong>A total of 947 saline-alkaline tolerance-related molecular markers and a 5K cGPS genotyping chipwere developed, providing practical tools for marker-assisted selection and molecular design breeding of saline-alkaline-tolerant rapeseed. Rapeseed (Brassica napus L.) has relatively strong tolerance to saline-alkaline stress and shows great potential for the sustainable utilization and improvement of saline-alkaline soils. However, the breeding of highly tolerant cultivars still mainly depends on conventional hybridization combined with phenotype-based selection, which constrains breeding efficiency. In this study, previously reported saline-alkaline tolerance-related genes from rapeseed, rice, maize, wheat, sorghum, and Arabidopsis were collected. Candidate gene-based association analysis enabled the development of molecular markers and a genotyping chip. A total of 483 significantly associated genes were identified, among which 355 genes contained favorable haplotypes. Molecular markers were successfully developed for 275 genes, including 746 KASP and 201 InDel marker pairs, and four marker pairs were randomly selected for validation. In addition, a 5K cGPS liquid-phase chip (HZSW-cGPS-BRNAP-04), was developed and showed a high call rate and excellent reproducibility in genotyping. These markers and the chip are expected to improve the breeding efficiency of saline-alkaline-tolerant rapeseed cultivars. Overall, this study provides useful tools for early-generation evaluation and marker-assisted selection (MAS), and provides a foundation for molecular design breeding of saline-alkali-tolerant rapeseed.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 10","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148921127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic architecture and evolution of stripe rust resistance uncovered using diverse panels of wheat lines and North American Puccinia striiformis f. sp. tritici isolates.","authors":"Buket Sahin, Meinan Wang, Jason D Zurn, Xiaoting Xu, Guihua Bai, Alina Akhunova, Xianming Chen, Eduard Akhunov","doi":"10.1007/s00122-026-05363-x","DOIUrl":"10.1007/s00122-026-05363-x","url":null,"abstract":"<p><strong>Key message: </strong>Screening global wheat germplasm with a diverse collection of pathogen races expands the catalog of novel Yr loci and identifies new sources of broad-spectrum resistance against evolving Pst populations. Newly emerging highly virulent races of Puccinia striiformis f. sp. tritici (Pst) often defeat deployed resistance genes (Yr), highlighting the need for novel sources of durable resistance. A global diversity panel of 377 spring wheat (Triticum aestivum L.) lines was screened for all-stage resistance (ASR) against a panel of diverse 20 Pst isolates at the seedling stage and for adult-plant-stage resistance (APR) against natural mix of field races. Genome-wide association mapping identified 77 unique Yr loci. Of these, 34 overlapped with the previously mapped 1150 Yr loci, confirming the robustness of our GWAS results, while 43 were likely novel. Comparison of the nine adult-plant-stage Yr loci mapped in our study with known APR genes identified only one overlap, with Yr29. Except for Yr29, APR genes Yr18 and Yr36 were detected at low frequencies, indicating that resistance in our panel may arise from less characterized or novel sources. Two wheat lines, lacking widely effective Yr5 and Yr15 alleles, exhibited resistance to all 20 Pst races at the seedling stage and natural field races at the adult stage, suggesting that they may carry novel, broad-spectrum ASR alleles. Wheat improvement had no effect on the frequency of ASR alleles but resulted in a threefold increase in the frequency of APR alleles, suggesting that the latter were subjected to more consistent breeding selection over time. Our findings underscore the value of combined screening of diverse germplasm with diverse pathogen races to identify novel sources of broad-spectrum resistance for breeding stripe rust resistant cultivars.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 10","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13553620/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148913597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic selection in timothy (Phleum pratense L.): a comprehensive evaluation of prediction models, multi-trait strategies, and forward validation across Norwegian environments.","authors":"Mallikarjuna Rao Kovi, Akhil Reddy Pashapu, Helga Amdahl, Kristin Gylstrøm, Susanne Windju, Petter Marum, Muath Alsheikh, Odd Arne Rognli","doi":"10.1007/s00122-026-05371-x","DOIUrl":"10.1007/s00122-026-05371-x","url":null,"abstract":"<p><strong>Key message: </strong>This study presents a comprehensive evaluation of genomic selection (GS) in timothy (Phleum pratense L.), comparing nine prediction models across yield and quality traits at two Norwegian locations. Forward validation with independent full-sib (FS2) families revealed a substantial generalization gap, highlighting the need for realistic accuracy assessment in polyploid forage breeding. Timothy (Phleum pratense L.) is the most important forage grass in Northern Europe, yet genomic selection has not been systematically evaluated in this hexaploid species. We assessed 889 FS2-families originating from biparental crosses among 49 cultivars/populations. The FS2-families were genotyped with 30,698 SNP markers derived from genotyping-by-sequencing (GBS) and field tested for three harvest years at a highland and a lowland continental location in Southern Norway. Nine genomic prediction models were compared for six yield traits (dry matter yield per cut and total) and six quality traits (protein, digestibility, and fiber fractions) across three cuts/year. Within-training cross-validation accuracies were moderate to high (mean r = 0.62), with Random Forest and SVR consistently outperforming GBLUP. However, forward validation using 213 independent FS2-families revealed dramatically lower accuracies (mean r = 0.16), with only 16 of 30 trait-dataset combinations reaching statistical significance (p < 0.05). Genomic heritabilities (GREML), estimated across environments, ranged from near zero for the quality traits to 0.55 for the yield traits. Multi-trait models improved accuracy by 3-5% over single-trait approaches, while FS2 families-by-environment interaction models with Random Forest achieved the highest within-training accuracy (mean r = 0.71). Marker density analysis showed accuracy plateauing at approximately 15000 SNPs. Genetic correlations among the yield component traits were estimated by multi-trait REML; correlations among the quality traits could not be estimated reliably because their genomic heritabilities were low. A multi-trait selection index identified top-performing FS2-families for further crossing recommendations. These results provide a benchmark for GS implementation in hexaploid timothy and emphasize that cross-validation substantially overestimates prediction accuracy for truly independent material.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 10","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13550071/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148907277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unlocking the potential of spring wheat genetic resources: uncovering resistance sources against leaf rust and yellow rust.","authors":"Behnaz Soleimani, Anne-Kathrin Pfrieme, Ulrike Beukert, Heike Lehnert, Max Haupt, Axel Himmelbach, Martin Mascher, Nils Stein, Andreas Stahl, Frank Ordon, Jochen Christoph Reif, Albrecht Serfling","doi":"10.1007/s00122-026-05365-9","DOIUrl":"10.1007/s00122-026-05365-9","url":null,"abstract":"<p><strong>Key message: </strong>Integrating high-throughput phenotyping with multiple complementary GWAS models reduces method-dependent bias and enables reliable identification of novel loci and elite germplasm for durable yellow and leaf rust resistance in wheat. The causal agents of yellow and leaf rust in wheat, Puccinia striiformis f. sp. tritici and Puccinia triticina, pose a serious threat to grain yield and quality worldwide. Growing durable resistant wheat cultivars is an effective protection measure contributing to sustainable agriculture. Many of the known resistance genes, however, have been overcome due to the high genetic diversity and adaptability of pathogen populations. Therefore, the present study aimed to identify novel loci associated with yellow rust and leaf rust in a genome-wide association study using 1984 spring wheat accessions from the German Federal ex situ Genebank. Phenotypic data obtained from a detached-leaf assay were combined with 90,283 genotyping-by-sequencing genome-wide markers. Six significant peak marker-trait associations were identified for yellow rust and leaf rust, respectively. These are located on chromosomes 1D, 2B, 3B, 4A, 4B, 4D, 5A, 6B, and 7D. Six candidate genes were identified close to the identified loci. These findings may be valuable for identifying and deploying genetic resources to broaden the genetic basis of resistance and safeguard durability of resistance against yellow and leaf rust.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13547188/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148901147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic determinants of aerial root morphology in Sierra Mixe-derived maize.","authors":"Daniel Laspisa, Rubens Diogo, Rafael E Venado, Tess Kern, Natalia de Leon, Jean-Michel Ané, Jason G Wallace","doi":"10.1007/s00122-026-05348-w","DOIUrl":"10.1007/s00122-026-05348-w","url":null,"abstract":"<p><strong>Key message: </strong>We mapped key regions of the maize genome that influence the formation of aboveground (aerial) roots, which in some varieties have been associated with symbiosis with nitrogen-fixing bacteria. Modern agriculture relies heavily on chemically synthesized nitrogen fertilizers, which ensure high yields but also carry high economic and environmental costs. Biological nitrogen fixation (BNF) supplies high amounts of nitrogen to legumes, and several avenues of research are underway to extend it to cereal crops. In maize, aerial roots formed in Sierra Mixe landraces have been associated with BNF. However, much of the genetics underlying aerial root morphology remains unknown. Here, we evaluate aerial root morphology traits associated with BNF in three segregating populations derived from crosses between two Midwest-adapted inbred lines and three landraces. Inclusive composite interval mapping (iCIM) with flowering time as a covariate identified 37 quantitative trait loci (QTL) for three aerial root traits (nodes with roots, root size, and roots per node) which exhibit moderately high heritability (H² = 0.65 to 0.83). The combined proportion of phenotypic variance explained by the detected QTL ranged from 23 to 51%, depending on the trait and population, and potential candidate genes were identified through literature searches, macrosynteny, and gene expression analyses. Introgressing the most relevant aerial root-associated QTL into elite genotypes may provide a path toward achieving meaningful levels of BNF-associated traits in maize, but further work is needed to assess this approach's viability under field conditions.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13546345/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148897758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-variant GWAS and genomic prediction dissect the genetic architecture underlying tomato fruit weight.","authors":"Yasin Topcu, Alper Adak, Halim Can Kayikci, Serkan Aydin, Kubra Yildiz, Alexis Ramos, Denise M Tieman, Sofia Visa, Esther van der Knaap, Manoj Sapkota","doi":"10.1007/s00122-026-05326-2","DOIUrl":"10.1007/s00122-026-05326-2","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Key message: &lt;/strong&gt;Tomato fruit weight is primarily controlled by stable genetic effects and domestication-/improvement-associated loci, including prominent chromosome 5 signals, and integrating SNP, INDEL, and SV diversity improves candidate-locus discovery, biological interpretation, and genomic prediction across environments. Tomato fruit weight (fw) is a major breeding target shaped by domestication, crop improvement, and environmental variation. We investigated the genetic architecture and genomic predictability of fw in the Varitome population representing the tomato domestication continuum, including Solanum pimpinellifolium (SP), S. lycopersicum var. cerasiforme (SLC), and cultivated S. lycopersicum (SLL). Genome-wide SNPs, insertions and deletions (INDELs), and structural variants (SVs) were analyzed individually and in combination to assess their contributions to association mapping, candidate locus discovery, and genomic prediction. Population structure based on all three variant classes clearly separated the domestication groups. Genome-wide association analyses identified 15 SNP, 10 INDEL, and 10 SV loci significantly associated with fw across environments. Several associations co-localized with known fw genes, including fw2.2/CNR, fw3.2/KLUH, fw11.3/CSR, lc/WUSCHEL, and fas/CLAVA3 supporting the biological relevance of the detected signals. Chromosome (Chr) 5 was particularly notable, with a 390-bp deletion at chr5_45,551,023 detected across all four environments and an INDEL at chr5_55,361,233 detected across three environments, suggesting stable improvement-associated candidate loci for fw variation validation. Multiple loci exhibited clear allele-frequency shifts from SP through SLC to SLL, consistent with selection during domestication and improvement, whereas others were detected almost exclusively in cultivated germplasm, suggesting more recent breeding-associated origins. Fw displayed strong genetic control, with genotype explaining more than 92% of the phenotypic variance and only minor contributions from environment and genotype-by-environment interactions. Five genomic prediction models based on SNPs, INDELs, SVs, their combinations, and genotype-by-environment interaction kernels were evaluated using four cross-validation scenarios (CV1, CV2, CV0, and CV00). Prediction accuracy was influenced more strongly by validation scenario and prediction algorithm choice than by marker class. Partial Least Squares (PLS) and Bayesian Genomic Linear Regression (BGLR) consistently outperformed Random Forest (RF) and Deep Learning (DL) models, particularly under scenarios involving untested genotypes and environments. INDEL-based models frequently achieved the highest accuracies under the most stringent prediction scenarios, although differences among marker classes were generally modest. Integrating multiple classes of genomic variation improved biological interpretation, enabled the identification of domestication- and i","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13546169/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148897771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic dissection of cold tolerance across developmental stages in sorghum reveals stage-specific haplotypes and potential trade-offs.","authors":"Mohamed Mosalam, Hannah Robinson, Steffen Windpassinger, Rod J Snowdon, Kai P Voss-Fels","doi":"10.1007/s00122-026-05356-w","DOIUrl":"10.1007/s00122-026-05356-w","url":null,"abstract":"<p><strong>Key message: </strong>Cold tolerance in sorghum is largely stage- and environment-specific yet partially shared genetic control allows improvement across developmental stages with mostly modest, trait-specific trade-offs. Cold tolerance is a major constraint to sorghum production in temperate environments, and its improvement is therefore a key breeding objective. However, cold tolerance varies across developmental stages and environments, and selection based on stage-specific phenotypes may overlook shared genetic components. We analysed a diversity panel of 394 sorghum genotypes evaluated across 10 environments representing three developmental stages using multi-environment mixed models, genome-wide haplotype block analysis, and in silico haplotype stacking. Substantial genotype-by-environment interaction was detected, with the strength of GEI varying markedly across traits. Genetic correlations were high within developmental stages but lower and more variable across stages, indicating that the genetic architecture of cold tolerance-relevant traits is largely stage-dependent. Haplotype block analyses identified both stage- and environment-specific regions, as well as regions shared across stages and environments. In silico stacking of favourable haplotypes for early-stage cold tolerance resulted in nonlinear predicted gains, with strong initial responses at low stacking levels followed by diminishing returns. Correlated responses in yield-related traits were generally positive, whereas flowering time was consistently delayed, indicating a potential trait-specific trade-off in cold tolerance improvement. Sorghum cold tolerance can therefore not be treated as a single uniform trait but rather as a combination of stage-specific and shared genetic components, with implications for multi-stage breeding strategies.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13545123/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148892319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}