Plant Genome最新文献

{"title":"Genetic diversity and population structure of jute mallow (Corchorus olitorius L.) global collection to guide conservation and breeding.","authors":"Abdul J Shango, Emmanuel O Omondi, Sognigbé N'Danikou, Dèdéou A Tchokponhoué, M Eric Schranz, Bodovololona Rabary, Mujuni Sospeter Kabululu, Thembinkosi Gumedze, Enoch G Achigan-Dako, Pavithravani Venkataramana, Mashamba L Philipo, Maarten van Zonneveld","doi":"10.1002/tpg2.70252","DOIUrl":"10.1002/tpg2.70252","url":null,"abstract":"<p><p>Understanding the genome-wide diversity of jute mallow (Corchorus olitorius L.) is crucial for unlocking the potential of global genebank collections, enabling the discovery and use of traits that support climate resilience, improve nutrition, and increase productivity. Using 23,471 high-quality diversity array technology sequencing single-nucleotide polymorphisms (SNPs), this study assessed the genetic diversity, population structure, and linkage disequilibrium (LD) of 607 accessions. Moderate genetic diversity was detected with a total gene diversity of 0.28, an expected heterozygosity of 0.26, and a Shannon index of 0.42. Four distinct genetic clusters were identified, reflecting geographic patterns, where Cluster 1 (n = 62) and Cluster 4 (n = 354) were predominantly composed of West African accessions. An analysis of molecular variance revealed significant genetic structuring (p < 0.001), with most genetic variation occurring within countries (45.2%), followed by within individuals (32.5%), while differentiation among clusters accounted for 18.2% and variation among regions was minimal (2.9%). LD revealed low genome-wide r² values (mean = 0.028; r² ₉₀ = 0.067) and a very rapid decay (LD₅₀ ≈ 1 bp), with only 4.2% of SNP pairs showing significant LD (r² > 0.1, p < 0.05), indicating extensive historical recombination. The findings suggest that a significant portion of the existing genetic variation remains untapped in breeding. Strategic conservation of the unique genetic variants through core and mini-core collections, coupled with targeted crosses among diverse regional accessions, can broaden the genetic base and support the development of resilient, high-yielding, and nutrient-rich dual-purpose varieties (i.e., leafy vegetables and industrial fibers) across diverse environments.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 2","pages":"e70252"},"PeriodicalIF":4.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13184441/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147976476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Allele-informed QTL-seq identifies Hd18 as a minor modifier of heading date in elite rice cultivars.","authors":"Hayeong Lee, Mina Kim, Jiheon Han, Hyun-Su Park, Seung Young Lee, Youngjun Mo","doi":"10.1002/tpg2.70230","DOIUrl":"10.1002/tpg2.70230","url":null,"abstract":"<p><p>Fine-tuning heading date is critical for optimizing yield, grain quality, and local adaptation in rice (Oryza sativa L.). QTL-seq (where QTL is quantitative trait locus), which integrates bulked segregant analysis with whole-genome resequencing, provides a rapid and cost-effective approach for identifying QTLs underlying complex traits. Shinpyeong and Haedeul are elite Korean rice cultivars that carry identical alleles at four major heading date genes (Hd1, OsPRR37, Ghd7, and DTH8), yet differ by approximately 7 days in heading under natural long-day conditions. To elucidate the genetic basis of this difference, we applied allele-informed QTL-seq to an F₂ population derived from a cross between Shinpyeong and Haedeul. A single prominent QTL peak with the highest ΔSNP-index (where SNP is single nucleotide polymorphism) was consistently detected across both field and greenhouse environments and co-localized with Hd18, identifying it as the most likely causal gene. The underlying polymorphism was a previously reported missense A/G variant. Genotyping of the Hd18 A/G SNP using a dCAPS (derived cleaved amplified polymorphic sequence) marker revealed that F₂ plants homozygous for the A allele headed 4.1 days earlier in the field and 6.2 days earlier in the greenhouse than those homozygous for the G allele. Analysis of 290 Korean rice cultivars further demonstrated that the Hd18 A allele was associated with approximately 2 days earlier heading under a nonfunctional hd1 background. Evaluation of two recombinant inbred line populations showed that Hd18 had minimal effects on major agronomic traits, while exhibiting background-dependent effects on specific traits. These results establish Hd18 as a minor effect modifier of heading date with utility for fine-scale phenological adjustment in rice breeding.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 2","pages":"e70230"},"PeriodicalIF":4.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13043796/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147595598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to \"Dissecting multi-rust resistance in wheat through genome-wide association study, haplotype analysis, and marker validation\".","authors":"","doi":"10.1002/tpg2.70224","DOIUrl":"10.1002/tpg2.70224","url":null,"abstract":"","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 2","pages":"e70224"},"PeriodicalIF":4.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13492603/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147876155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving genomic prediction in wheat with random regression models with genotype-specific phenology-driven environmental covariates.","authors":"Rishap Dhakal, Guillermo Sniadower, Paula Silva, Bettina Lado, Pablo Sandro, Inés Rebollo, Martin Quincke, Julie C Dawson, Lucia Gutiérrez, Pablo González Barrios","doi":"10.1002/tpg2.70247","DOIUrl":"10.1002/tpg2.70247","url":null,"abstract":"<p><p>Wheat (Triticum aestivum L.), a crucial cereal crop for global food security, faces growing challenges from climate change. Future production requires varieties that are resilient to environmental extremes and fluctuations. The goal of this study was to assess strategies to increase selection response through genomic selection in wheat by integrating genotypic-specific phenology-derived environmental covariates (ECs) and random regression models (RRM) in multi-environment trials. We analyzed phenotypic and genomic data from 1683 genotypes from 2010 to 2020 across 71 environments using 45 ECs derived from vegetative, reproductive, and grain-filling phenological phases. Seven key ECs were selected via partial least squares regression to model genotype by environment interaction (GEI) and evaluate their integration in three different genomic prediction scenarios (CV0, CV1, and CV2). Genomic best linear unbiased prediction models (GBLUP), GBLUP models with GEI (GBLUP_{G × E}) modeled as a factor analytic (FA) model, and RRM were compared for their predictive ability performance. RRM with three ECs outperformed GBLUP achieving 50%-100% higher accuracy in CV1 and CV2. The FA exhibited the highest accuracy overall for CV2 but not for CV1. At least one RRM model improved predictions in >89% of environments when predicting new, un-phenotyped environments. Integrating ECs into the RRM enhances genomic prediction by effectively capturing the GEI with a limited number of covariates.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 2","pages":"e70247"},"PeriodicalIF":4.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13155077/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147844954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification and genomic location of resistance to bacterial leaf streak of barley.","authors":"Diel Donne Velasco, Gongjun Shi, Robert Bruggeman, Richard Horsley, Thomas Baldwin, Zhaohui Liu","doi":"10.1002/tpg2.70231","DOIUrl":"10.1002/tpg2.70231","url":null,"abstract":"<p><p>The bacterial leaf streak (BLS) disease of barley (Hordeum vulgare L.), caused by Xanthomonas translucens pv. translucens (Xtt), has become increasingly important worldwide in recent years. Inefficacy of chemical control methods leaves deployment of host resistance to be the only option to manage this disease. However, current commercial varieties are mainly susceptible to BLS. Therefore, our goal was to identify sources of resistance from diverse barley germplasms and map associated genetic factors. To do so, we evaluated a subset of the World Barley Core Collection (BCC), consisting of 198 accessions, on their reaction to BLS from 2013 to 2016 under natural or artificially inoculated disease pressures. Ten accessions exhibited consistently low disease severities over 4 years of evaluations. Using genotype data from the T3/Barley database, genome-wide association studies were conducted to identify marker-trait associations (MTAs) in this barley mini-core panel for BLS resistance. Utilizing four mixed-model analyses (mixed linear model, multi-locus mixed model, fixed and random model circulating probability unification, and Bayesian-information and linkage-disequilibrium iteratively nested keyway [BLINK]), nine significant MTAs were detected using the primary model, BLINK, including one in chromosome 1H, six in chromosome 2H, and one each in chromosomes 3H and 5H. Associations in chromosomes 2H and 3H appear to be in the same region with loci identified in a previous association study, reinforcing their potential relevance. The identified resistant barley accessions and associated markers will be valuable in breeding BLS-resistant barley varieties.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 2","pages":"e70231"},"PeriodicalIF":4.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13034020/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147576025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A public mid-density genotyping platform for pecan [Carya illinoinensis (Wangenh.) K. Koch].","authors":"Shufen Chen, Meng Lin, Dongyan Zhao, Warren Chatwin, Xinwang Wang, Angelyn Hilton, John T Lovell, Jennifer Randall, Kasia Heller-Uszynska, Cristiane H Taniguti, Craig T Beil, Moira J Sheehan","doi":"10.1002/tpg2.70262","DOIUrl":"10.1002/tpg2.70262","url":null,"abstract":"<p><p>Pecan [Carya illinoinensis (Wangenh.) K. Koch] is the fifth-largest tree nut in global cultivation, with 80% of production occurring in the southern states of the United States. Despite the economic and health benefits of pecans, there is a lack of genomic tools available to breeders for crop improvement. The pecan breeding community is small, and most breeding programs have many barriers to adopting technology, particularly in the cost and know-how needed to create and use genetic marker panels for genomic-based decisions in selection. Here, we report the creation of a DArTag (Diversity Array Technology [DArT]) panel of 3100 loci distributed across the diploid pecan genome for use in molecular breeding and genomic prediction. Here, we show the panel's ability to distinguish key parents and founders of cultivated pecan from other Carya species that may be used in pre-breeding. We also demonstrate that the resultant data can create a linkage map in a biparental population. The creation of this marker panel brings cost-effective and rapid genotyping capabilities to pecan breeding programs, making routine genotyping a reality for any pecan breeder. Furthermore, the open access provided by this platform enables the comparison and integration of genetic datasets generated on the marker panel across projects, institutions, and countries.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 2","pages":"e70262"},"PeriodicalIF":4.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13263899/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148254091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome association of carbohydrate metabolites provides new insights toward functional breeding in coffee.","authors":"Estefania Tavares Flores, Robert Logan Spicer, Elaine M R Souza, Maria Amelia G Ferrão, João Felipe B Senra, Camila Azevedo, Patricio R Munoz, Denise Tieman, Cătălin Voiniciuc, Luis Felipe V Ferrão","doi":"10.1002/tpg2.70239","DOIUrl":"10.1002/tpg2.70239","url":null,"abstract":"<p><p>Coffee is one of the world's most widely consumed beverages, derived mainly from Coffea arabica, known for its superior flavor, and Coffea canephora (Robusta/Conilon), valued for its resilience and higher caffeine content. Functional breeding aims to develop cultivars that combine productivity and stress tolerance with improved health-related traits and flavor quality. Because carbohydrate polymers account for more than 50% of green coffee bean dry weight and act as key precursors of aroma and bioactive compounds, we hypothesized that elucidating the genetic architecture underlying carbohydrate metabolites would create new opportunities for molecular breeding in coffee. To test this hypothesis, we integrated cell wall carbohydrate profiling with genomic analyses in a genetically diverse coffee collection encompassing both Coffea canephora and Coffea arabica. Genome-wide association studies identified 14 major genomic loci associated with variation in cell wall polysaccharide composition. Using cup quality as a functional trait endpoint, we further linked carbohydrate profiles with sensory evaluations and propose a framework for implementing marker-assisted selection to accelerate flavor improvement in coffee breeding programs.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 2","pages":"e70239"},"PeriodicalIF":4.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13058885/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147634867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association mapping for hop cone chemistry and morphology identifies natural beneficial allele stacks.","authors":"Shaun J Clare, Peter Schmuker, Kayla Altendorf","doi":"10.1002/tpg2.70238","DOIUrl":"10.1002/tpg2.70238","url":null,"abstract":"<p><p>Efforts are underway to increase the efficiency and precision of selection hop (Humulus lupulus L.) breeding using genomics. Little is known, however, about the genetic control of important traits like α-and β-acids contents, oil content, and cone morphological characteristics, all of which play an important role in determining the utility and harvestability of a hop and are targets of selection. In this study, we utilized association mapping with a collection of 529 female hop plants evaluated in Prosser, WA USA in 2023 and 2024, single nucleotide polymorphism data derived from genotyping-by-sequencing with 20,861 markers, and phenotype data generated from near-infrared (NIR) spectroscopy and image analyses of hop cones. A total of 49 significant marker trait associations were detected across five traits with 43 unique loci. High correlation estimates between wet lab and near-infrared spectroscopy data (R = 0.54-0.94), high broad-sense heritability estimates (H² = 0.32-0.71), and logical associated candidate genes illustrate the validity of the methods used in detecting meaningful associations. Furthermore, existing germplasm in our study containing increasing stacks of favorable alleles showed improvement in all traits, demonstrating the potential for utilizing the markers identified herein in a genomic prediction pipeline to improve hop germplasm for key end-use traits.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 2","pages":"e70238"},"PeriodicalIF":4.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13125966/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Haplotype‑resolved comparison of transcription factor superfamilies between wild and cultivated autotetraploid green jujube and prioritization of candidate transcription factors via machine learning.","authors":"Xudong Zhu, Pengyan Chang, Yanzhen Liao, Huini Wu, Fan Jiang","doi":"10.1002/tpg2.70266","DOIUrl":"10.1002/tpg2.70266","url":null,"abstract":"<p><p>A framework beyond single-reference genomes is needed to understand transcription factor evolution. This study employed an integrated haplotype‑resolved genomes-transcriptome atlas-machine learning to characterize the transcription factors of autotetraploid green jujube (Ziziphus mauritiana). The first haplotype‑resolved comparison of transcription factor superfamilies from eight haplotype genomes (HapGenome) representing a specific wild and a specific cultivated green jujube accession, encompassing 42 superfamilies and 12,123 gene copies. Evolutionary analyses revealed high structural conservation with minimal copy number variation, gene presence/absence variations, and strong purifying selection (Ka/Ks < 1). Dispersed duplication (47.24%), not whole-genome duplication (36.10%), was the most frequently observed duplication event in the expansion of transcription factor superfamily. A haplotype‑resolved transcriptome atlas demonstrated that tissue-specific expression divergence occurred at the superfamily level and between the core/dispensable genes. Integrating transcriptomic and metabolomic data, support vector machine classification with leave‑one‑out cross‑validated distinguished three wild fruits from six cultivated fruits with the accuracy of 89% using orthologous gene groups (OGGs) expression profiles. The eXtreme gradient boosting was employed as an exploratory tool to prioritize OGGs related to metabolite changes. Finally, OGG-95, a Lesion Simulating Disease Zn finger transcription factor, was screened out, which was significantly upregulated in cultivated fruits, and its expression was significantly correlated with differential accumulation of nucleotides and organic acids that need further functional validation. This integrative study provided novel insights into the genomic architecture and regulatory evolution of transcription factors in a polyploid fruit crop, highlighting the power of multi-dimensional analyses for gene discovery.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 2","pages":"e70266"},"PeriodicalIF":4.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13287549/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148303632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wheat's war against stripe rust: Integrating host immunity, genomics and breeding for durable resistance.","authors":"Farkhandah Jan, Mukesh Rathore, Dinesh Kumar Saini, Ayushi Singh, Naeela Qureshi, Nikita Aggarwal, Mahpara Bashir, Mehnaz Shakeel, Vikas Gupta, Sundeep Kumar, Rajeev Kumar Varshney, Reyazul Rouf Mir","doi":"10.1002/tpg2.70174","DOIUrl":"10.1002/tpg2.70174","url":null,"abstract":"<p><p>Wheat (Triticum aestivum L.), a foundation of global food security, faces persistent threats from stripe rust caused by Puccinia striiformis f. sp. tritici (Pst). The pathogen thrives in cool and humid environments and regularly causes epidemics that lead to severe yield losses. This review synthesizes current knowledge on stripe rust resistance, covering pathogen biology, host immunity, and recent advances in genetics and genomics, with emphasis on the rapid emergence of new virulent Pst pathotypes that frequently overcome deployed resistance genes. We outline the complexity and evolutionary agility of the Pst genome, which drive recurrent resistance breakdowns. On the host side, we summarize multilayered immune signaling, including pattern recognition receptors, major resistance genes and quantitative trait loci, and downstream defense cascades. Multiomics studies highlight biphasic defense responses and regulatory networks that distinguish resistant and susceptible genotypes. Breeding strategies ranging from classical selection to quantitative trait loci mapping, genome-wide association studies, marker-assisted selection, genomic selection, and genome editing are evaluated for their contributions to durable resistance. We also highlight emerging roles of transcription factors, epigenetic regulation, and gene regulatory networks. Advances in genome sequencing, pan genomics, and allele mining are accelerating the discovery of novel resistance sources and expanding understanding of wheat diversity. Finally, we discuss how climate change and ongoing pathogen evolution require integrated disease management and continuous innovation in resistance breeding. Overall, this review connects fundamental biology with applied breeding to support durable stripe rust resistance and sustainable wheat production worldwide.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 2","pages":"e70174"},"PeriodicalIF":4.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13079807/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147692288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}