Plant Genome最新文献

{"title":"Genome-wide association study reveals significant loci and candidate genes for fruit branch length in upland cotton.","authors":"Hui Chang, Honghu Ji, Ruijie Liu, Juling Feng, Jiayi Wang, Shuqi Zhao, Wei Li, Zehua Qiu, Nabil Ibrahim Elsheery, Shuxun Yu, Libei Li, Zhen Feng","doi":"10.1002/tpg2.70041","DOIUrl":"https://doi.org/10.1002/tpg2.70041","url":null,"abstract":"<p><p>The length of fruit branches significantly influences plant architecture in upland cotton (Gossypium hirsutum L.), which is crucial for optimizing fiber yield and quality. In this study, a comprehensive genome-wide association study was conducted based on whole-genome resequencing data that identified 249 significant SNPs associated with fruit branch length (FBL), forming 79 distinct quantitative trait loci (QTL) regions. Notably, stable QTL regions qFBL-A10-4 and qFBL-D03-17 were identified, harboring key candidate genes such as Ghir_A10G014390 and Ghir_D03G011390. Superior haplotypes of these genes significantly enhance FBL, fiber yield, and quality, offering valuable targets for cotton breeding programs focused on optimizing plant architecture and productivity.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"18 2","pages":"e70041"},"PeriodicalIF":3.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144182969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phenotypic and transcriptomic analysis reveals key genes associated with plant height in rubber tree and functional characterization of the candidate gene HbFLA11.","authors":"Baoyi Yang, Yuanyuan Zhang, Weiguo Li, Xiao Huang, Xinsheng Gao, Juncang Qi, Xiangjun Wang","doi":"10.1002/tpg2.70048","DOIUrl":"https://doi.org/10.1002/tpg2.70048","url":null,"abstract":"<p><p>The rubber tree (Hevea brasiliensis) is an important species in global natural rubber production. However, the mechanisms regulating the height of rubber trees remain poorly understood. In previous work, the dwarf mutant MU73397 was obtained through ethyl methanesulfonate mutagenesis. Compared to the wild-type CATAS73397, MU73397 exhibited significantly reduced plant height and stem diameter, slower xylem development, and decreased cellulose and lignin content. Phytohormone analysis revealed that gibberellin levels were reduced in both the apex and stem of MU73397, while jasmonic acid was increased in the apex and auxin was reduced in the stem. These differences in hormone levels may contribute to the dwarf phenotype. Transcriptome analysis identified nine key genes related to cell wall biosynthesis and hormone signaling, namely, FLA11 (Fasciclin-like arabinogalactan protein 11), TUBB1 (Tubulin Beta 1), TUBB6 (Tubulin Beta 6), CESA7 (cellulose synthase A 7), TUBA4 (Tubulin Alpha 4), LAC17 (Laccase 7), CTL2 (Chitinase-like protein 2), IRX9 (Irregular xylem 9), and KOR (korrigan). Overexpression of HbFLA11 in transgenic poplar resulted in significant increases in plant height and stem diameter. Gibberellin signaling genes and cell wall biosynthesis genes were significantly upregulated in the transgenic lines. These results suggest that HbFLA11 is involved in gibberellin signaling and cell wall biosynthesis, thereby regulating plant growth. This study provides valuable genetic resources and research foundations for targeted trait breeding in rubber tree.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"18 2","pages":"e70048"},"PeriodicalIF":3.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144183464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SimpleMating: R-package for prediction and optimization of breeding crosses using genomic selection.","authors":"Marco Antônio Peixoto, Rodrigo Rampazo Amadeu, Leonardo Lopes Bhering, Luís Felipe V Ferrão, Patrício R Munoz, Márcio F R Resende","doi":"10.1002/tpg2.20533","DOIUrl":"10.1002/tpg2.20533","url":null,"abstract":"<p><p>Selecting parents and crosses is a critical step for a successful breeding program. The ability to design crosses with high means that will maintain genetic variation in the population is the goal for long-term applications. Herein, we describe a new computational package for mate allocation in a breeding program. SimpleMating is a flexible and open-source R package originally designed to predict and optimize breeding crosses in crops with different reproductive systems and breeding designs. Divided into modules, SimpleMating first estimates the cross performance (criterion), such as mid-parental value, cross total genetic value, and/or usefulness of a set of crosses. The second module implements an optimization algorithm to maximize a target criterion while minimizing next-generation inbreeding. The software is flexible, enabling users to specify the desired number of crosses, set maximum and minimum crosses per parent, and define the maximum allowable parent relationship for creating crosses. As an outcome, SimpleMating generates a mating plan from the target parental population using single or multi-trait criteria. For example, we implemented and tested SimpleMating in a simulated maize breeding program obtained through stochastic simulations. The crosses designed via SimpleMating showed a large genetic mean over time (up to 22% more genetic gain than conventional genomic selection programs, with lesser loss of genetic diversity over time), supporting the use of this tool, as well as the use of data-driven decisions in breeding programs.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":" ","pages":"e20533"},"PeriodicalIF":3.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11726409/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142741056","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":"Genomic and phenomic prediction for soybean seed yield, protein, and oil.","authors":"Liza Van der Laan, Kyle Parmley, Mojdeh Saadati, Hernan Torres Pacin, Srikanth Panthulugiri, Soumik Sarkar, Baskar Ganapathysubramanian, Aaron Lorenz, Asheesh K Singh","doi":"10.1002/tpg2.70002","DOIUrl":"10.1002/tpg2.70002","url":null,"abstract":"<p><p>Developments in genomics and phenomics have provided valuable tools for use in cultivar development. Genomic prediction (GP) has been used in commercial soybean [Glycine max L. (Merr.)] breeding programs to predict grain yield and seed composition traits. Phenomic prediction (PP) is a rapidly developing field that holds the potential to be used for the selection of genotypes early in the growing season. The objectives of this study were to compare the performance of GP and PP for predicting soybean seed yield, protein, and oil. We additionally conducted genome-wide association studies (GWAS) to identify significant single-nucleotide polymorphisms (SNPs) associated with the traits of interest. The GWAS panel of 292 diverse accessions was grown in six environments in replicated trials. Spectral data were collected at two time points during the growing season. A genomic best linear unbiased prediction (GBLUP) model was trained on 269 accessions, while three separate machine learning (ML) models were trained on vegetation indices (VIs) and canopy traits. We observed that PP had a higher correlation coefficient than GP for seed yield, while GP had higher correlation coefficients for seed protein and oil contents. VIs with high feature importance were used as covariates in a new GBLUP model, and a new random forest model was trained with the inclusion of selected SNPs. These models did not outperform the original GP and PP models. These results show the capability of using ML for in-season predictions for specific traits in soybean breeding and provide insights on PP and GP inclusions in breeding programs.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"18 1","pages":"e70002"},"PeriodicalIF":3.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11839941/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460206","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 scans capture key adaptation and historical hybridization signatures in tetraploid wheat.","authors":"Demissew Sertse, Jemanesh K Haile, Ehsan Sari, Valentyna Klymiuk, Amidou N'Diaye, Curtis J Pozniak, Sylvie Cloutier, Sateesh Kagale","doi":"10.1002/tpg2.20410","DOIUrl":"10.1002/tpg2.20410","url":null,"abstract":"<p><p>Tetraploid wheats (Triticum turgidum L.), including durum wheat (T. turgidum ssp. durum (Desf.) Husn.), are important crops with high nutritional and cultural values. However, their production is constrained by sensitivity to environmental conditions. In search of adaptive genetic signatures tracing historical selection and hybridization events, we performed genome scans on two datasets: (1) Durum Global Diversity Panel comprising a total of 442 tetraploid wheat and wild progenitor accessions including durum landraces (n = 286), domesticated emmer (T. turgidum ssp. dicoccum (Schrank) Thell.; n = 103) and wild emmer (T. turgidum ssp. dicoccoides (Korn. ex Asch. & Graebn.) Thell.; n = 53) wheats genotyped using the 90K single nucleotide polymorphism (SNP) array, and (2) a second dataset comprising a total 121 accessions of nine T. turgidum subspecies including wild emmer genotyped with >100 M SNPs from whole-genome resequencing. The genome scan on the first dataset detected six outlier loci on chromosomes 1A, 1B, 3A (n = 2), 6A, and 7A. These loci harbored important genes for adaptation to abiotic stresses, phenological responses, such as seed dormancy, circadian clock, flowering time, and key yield-related traits, including pleiotropic genes, such as HAT1, KUODA1, CBL1, and ZFN1. The scan on the second dataset captured a highly differentiated region on chromosome 2B that shows significant differentiation between two groups: one group consists of Georgian (T. turgidum ssp. paleocolchicum A. Love & D. Love) and Persian (T. turgidum ssp. carthlicum (Nevski) A. Love & D. Love) wheat accessions, while the other group comprises all the remaining tetraploids including wild emmer. This is consistent with a previously reported introgression in this genomic region from T. timopheevii Zhuk. which naturally cohabit in the Georgian and neighboring areas. This region harbored several adaptive genes, including the thermomorphogenesis gene PIF4, which confers temperature-resilient disease resistance and regulates other biological processes. Genome scans can be used to fast-track germplasm housed in gene banks and in situ; which helps to identify environmentally resilient accessions for breeding and/or to prioritize them for conservation.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":" ","pages":"e20410"},"PeriodicalIF":3.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11726425/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136399967","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":"Erratum to: Targeted genotyping-by-sequencing of potato and data analysis with R/polyBreedR.","authors":"Jeffrey B Endelman, Moctar Kante, Hannele Lindqvist-Kreuze, Andrzej Kilian, Laura M Shannon, Maria V Caraza-Harter, Brieanne Vaillancourt, Kathrine Mailloux, John P Hamilton, C Robin Buell","doi":"10.1002/tpg2.70011","DOIUrl":"10.1002/tpg2.70011","url":null,"abstract":"","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"18 1","pages":"e70011"},"PeriodicalIF":3.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11915481/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659442","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 powerful molecular marker to detect mutations at sorghum LOW GERMINATION STIMULANT 1.","authors":"Adedayo O Adeyanju, Patrick J Rich, Gebisa Ejeta","doi":"10.1002/tpg2.20520","DOIUrl":"10.1002/tpg2.20520","url":null,"abstract":"<p><p>The parasitic weed Striga (Striga hermonthica) limits productivity of sorghum (Sorghum bicolor) and other cereals in sub-Saharan Africa and elsewhere. Improved host plant genetics is an effective control method but verified loci contributing to Striga resistance are limited. LOW GERMINATION STIMULANT 1 remains the only known sorghum locus affecting resistance to Striga. Functional loss (lgs1) alleles at this locus result in low Striga germination stimulant activity. We developed a robust polymerase chain reaction (PCR)-based LGS1 marker that detects all known natural lgs1 alleles. We have successfully used this marker to improve Striga resistance in our sorghum breeding program. To check its utility among diverse sets of germplasm, we genotyped 406 lines of the sorghum association panel (SAP) with the marker and phenotyped them for Striga germination stimulant activity. The SAP contains 23 lines (6%) with lgs1 mutations that involve a complete loss of this gene. Three previously described deletion alleles (lgs1-1, lgs1-2, and lgs1-3) ranging from 28.5 to 34 kbp are present among SAP members with a new one, lgs1-6, missing nearly 50 kbp relative to the reference genome. All 23 members of the SAP carrying lgs1 alleles had low Striga germination stimulant activity. The smaller previously described intragenic deletion mutations lgs1-4 and lgs1-5 are not present in the SAP. The LGS1 marker is useful for both detecting sources of lgs1 and introgressing Striga resistance into new genetic backgrounds.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":" ","pages":"e20520"},"PeriodicalIF":3.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11726417/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142367054","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":"Mapping quantitative trait loci for seminal root angle in a selected durum wheat population.","authors":"Yichen Kang, Samir Alahmad, Shanice V Haeften, Oluwaseun Akinlade, Jingyang Tong, Eric Dinglasan, Kai P Voss-Fels, Andries B Potgieter, Andrew K Borrell, Manar Makhoul, Christian Obermeier, Rod Snowdon, Emma Mace, David R Jordan, Lee T Hickey","doi":"10.1002/tpg2.20490","DOIUrl":"10.1002/tpg2.20490","url":null,"abstract":"<p><p>Seminal root angle (SRA) is an important root architectural trait associated with drought adaptation in cereal crops. To date, all attempts to dissect the genetic architecture of SRA in durum wheat (Triticum durum Desf.) have used large association panels or structured mapping populations. Identifying changes in allele frequency generated by selection provides an alternative genetic mapping approach that can increase the power and precision of QTL detection. This study aimed to map quantitative trait loci (QTL) for SRA by genotyping durum lines created through divergent selection using a combination of marker-assisted selection (MAS) for the major SRA QTL (qSRA-6A) and phenotypic selection for SRA over multiple generations. The created 11 lines (BC₁F_2:5) were genotyped with genome-wide single-nucleotide polymorphism (SNP) markers to map QTL by identifying markers that displayed segregation distortion significantly different from the Mendelian expectation. QTL regions were further assessed in an independent validation population to confirm their associations with SRA. The experiment revealed 14 genomic regions under selection, 12 of which have not previously been reported for SRA. Five regions, including qSRA-6A, were confirmed in the validation population. The genomic regions identified in this study indicate that the genetic control of SRA is more complex than previously anticipated. Our study demonstrates that selection mapping is a powerful approach to complement genome-wide association studies for QTL detection. Moreover, the verification of qSRA-6A in an elite genetic background highlights the potential for MAS, although it is necessary to combine additional QTL to develop new cultivars with extreme SRA phenotypes.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":" ","pages":"e20490"},"PeriodicalIF":3.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11733660/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141753188","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":"Development of a 101.6K liquid-phased probe for GWAS and genomic selection in pine wilt disease-resistance breeding in Masson pine.","authors":"Jingyi Zhu, Qinghua Liu, Shu Diao, Zhichun Zhou, Yangdong Wang, Xianyin Ding, Mingyue Cao, Dinghui Luo","doi":"10.1002/tpg2.70005","DOIUrl":"10.1002/tpg2.70005","url":null,"abstract":"<p><p>Masson pine (Pinus massoniana Lamb.), indigenous to southern China, faces serious threats from pine wilt disease (PWD). Several natural genotypes have survived PWD outbreaks. Conducting genetic breeding with these resistant genotypes holds promise for enhancing resistance to PWD in Masson pine at its source. We conducted a genome-wide association study (GWAS) and genomic selection (GS) on 1013 Masson pine seedlings from 72 half-sib families to advance disease-resistance breeding. A set of efficient 101.6K liquid-phased probes was developed for single-nucleotide polymorphisms (SNPs) genotyping through target sequencing. PWD inoculation experiments were then performed to obtain phenotypic data for these populations. Our analysis reveals that the targeted sequencing data successfully divided the experimental population into three subpopulations consistent with the provenance, verifying the reliability of the liquid-phased probe. A total of 548 SNPs were considerably associated with disease-resistance traits using four GWAS algorithms. Among them, 283 were located on or linked to 169 genes, including common plant disease resistance-related protein families such as NBS-LRR and AP2/ERF. The DNNGP (deep neural network-based method for genomic prediction) model demonstrated superior performance in GS, achieving a maximum predictive accuracy of 0.71. The accuracy of disease resistance predictions reached 90% for the top 20% of the testing population ordered by resistance genomic estimated breeding value. This study establishes a foundational framework for advancing research on disease-resistant genes in P. massoniana and offers preliminary evidence supporting the feasibility of utilizing GS for the early identification of disease-resistant individuals.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"18 1","pages":"e70005"},"PeriodicalIF":3.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11873169/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143537979","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":"Exon disruptive variants in Populus trichocarpa associated with wood properties exhibit distinct gene expression patterns.","authors":"Anthony Piot, Yousry A El-Kassaby, Ilga Porth","doi":"10.1002/tpg2.20541","DOIUrl":"10.1002/tpg2.20541","url":null,"abstract":"<p><p>Forest trees may harbor naturally occurring exon disruptive variants (DVs) in their gene sequences, which potentially impact important ecological and economic phenotypic traits. However, the abundance and molecular regulation of these variants remain largely unexplored. Here, 24,420 DVs were identified by screening 1014 Populus trichocarpa full genomes. The identified DVs were predominantly heterozygous with allelic frequencies below 5% (only 26% of DVs had frequencies greater than 5%). Using common garden-grown trees, DVs were assessed for gene expression variation in the developing xylem, revealing that their gene expression can be significantly altered, particularly for homozygous DVs (in the range of 27%-38% of cases depending on the studied common garden). DVs were further investigated for their correlations with 13 wood quality traits, revealing that, among the 148 discovered DV associations, 15 correlated with more than one wood property and six genes had more than one DV in their coding sequences associated with wood traits. Approximately one-third of DVs correlated with wood property variation also showed significant gene expression variation, confirming their non-spurious impact. These findings offer potential avenues for targeted introduction of homozygous mutations using tree biotechnology, and while the exact mechanisms by which DVs may directly influence wood formation remain to be unraveled, this study lays the groundwork for further investigation.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":" ","pages":"e20541"},"PeriodicalIF":3.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11726415/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142780906","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}