Plant Genome最新文献

Common bermudagrass [Cynodon dactylon (L.) Pers.] is an economically and ecologically important warm-season perennial species widely used for turf, forage, and soil conservation and remediation. Seeding offers economic and practical advantages over vegetative propagation for establishing common bermudagrass. However, the adoption of seeded cultivars is limited by slow germination speed and low germination rates. The genetic basis behind these traits in common bermudagrass remains elusive. Accordingly, the objective of this study was to evaluate the genetic and phenotypic variation and identify genetic loci associated with seed germination-related traits in a diverse common bermudagrass panel. A diverse panel of 216 genotypes was formed for a genome-wide association study (GWAS). Seeds for each genotype of the panel were collected in both 2022 and 2023, and germination tests for each year were conducted separately in a randomized complete block design with three replications (100 seeds per replicate) in petri plates inside a growth chamber. The germination process was phenotyped by counting germinated seeds every 3 days from the beginning to determine the germination rate and estimate total germination percentage over a 21-day period. The panel underwent genotype-by-sequencing, and 21,810 high-quality single-nucleotide polymorphisms (SNPs) were retained for GWAS analysis. GWAS indicated that 52 unique SNPs were associated with the seed germination traits, of which six were consistent over the 2 years. Twenty candidate genes linked to the consistent SNPs were identified to be involved in seed germination. These findings add valuable information on genetic mechanisms for seed germination and its rapidness, and provide a foundation for developing breeder-friendly markers to improve seed germination in the species.

Epigenetic regulation plays a central role in coordinating peanut (Arachis hypogaea L.) fruit pegging, a unique developmental process in which fertilized ovaries transition from aerial growth to subterranean pod formation. This review synthesizes current evidence demonstrating that dynamic interactions among DNA methylation, histone modifications, and small RNA-mediated pathways govern peg elongation, directional growth, and successful pod initiation in Arachis hypogaea L. The methylome and transcriptomic studies reveal that context-specific DNA methylation and reversible histone marks function as regulatory switches that integrate environmental signals such as light, gravity, temperature, and soil conditions with developmental gene expression programs. Activating chromatin states promote cell division and hormone-responsive pathways during peg elongation, whereas repressive marks and RNA-directed DNA methylation maintain genome stability and prevent premature differentiation. Crosstalk between epigenetic regulators and hormonal networks, particularly auxin and ethylene signaling, emerges as a conserved mechanism fine-tuning cellular differentiation and peg curvature during soil penetration. Small RNAs further contribute to this regulatory network by modulating key transcription factors and signaling components at post-transcriptional and epigenetic levels. Most importantly, comparative analyses across genotypes and stress conditions indicate that some epigenetic modifications are developmentally dynamic, while others exhibit stability with potential heritability, indicating their relevance for breeding. Overall, this review concludes that epigenetic mechanisms constitute an integrative regulatory framework linking environmental perception with developmental plasticity in peanut fruit pegging, offering promising opportunities to harness epigenetic variation for improving yield stability, stress resilience, and climate-adaptive peanut breeding strategies.

Cotton bacterial blight (CBB), caused by Xanthomonas citri subsp. malvacearum (Xcm), continues to pose a significant threat to upland cotton (Gossypium spp.) production across the US Cotton Belt. To elucidate the genetic basis of resistance to race 18 of CBB and identify potential novel resistance sources, we conducted genome-wide association studies (GWASs) using a diversity panel of 661 upland cotton accessions that included elite US germplasm, tropical landraces, and University of Arkansas germplasm releases. GWAS identified a single 3.3 Mb region on chromosome D02 corresponding to the BB13 locus as the primary determinant of race 18 resistance, with no additional major loci detected, indicating Bb13 as the predominant race 18 resistance source in upland cotton. Population genetic analyses suggested uneven distribution of the Bb13 gene across US breeding programs and landraces, likely originating from the African cultivar S295. Linkage mapping in six recombinant inbred line (RIL) populations confirmed segregation of race 18 resistance at the BB13 locus. Fine mapping using PCR allele competitive extension (PACE) markers delimited BB13 locus to a 154.28 kb interval containing nine candidate genes, six of which have homologs implicated in plant disease resistance pathways. The PACE marker CBB16, co-segregating with resistance in both the diversity panel and RIL populations, was identified as a diagnostic marker for Bb13. Local haplotyping further revealed marker groups and haplotypes associated with CBB resistance. Results from this study provide key genomic tools for breeding CBB-resistant cultivars and establish the foundation for positional cloning of the Bb13 gene.

After decades of intensive breeding, modern US soybean [Glycine max (L.) Merr.] varieties have achieved significant improvements in yield, quality, and stress tolerance, but these gains have come at the cost of severely reduced genetic diversity. To reduce vulnerability and promote efficient use of germplasm, diverse sets (DS) of varying sample sizes were defined for the entire USDAARS Soybean Germplasm Collection and 13 maturity groups using the SoySNP50K single-nucleotide polymorphism (SNP) profile. The average retained genetic diversity of the 50K SNPs was then compared between 10 DS and 10 random sets (RSs) at different sizes. DS consistently outperformed random sampling: in cultivated soybean, DS captured 94.9%-98.4% of SNP diversity compared with 73.1%-93.9% for RS; in wild soybean, DS captured 92.8%-97.9% compared with 83.4%-97.7% for RS. The performance of DS was further validated using whole-genome sequences from 1511 accessions, demonstrating that DS could retain the diversity predicted by the SNP subset across 1308 cultivated and 203 wild soybean genomes of different sample sizes. DS was also effective in capturing genetic diversity across different traits. To allow users to select DS, a "Soy-DS Selector" approach was proposed, and a table containing germplasm clusters across the USDA collection and different maturity groups was created. This resource enables researchers to tailor combinations based on maturity groups, accession and sample size preferences, and seed availability. The study provides both methodology and resources that can streamline germplasm evaluation, maximize resource utilization, and enhance future genetic improvement in soybean. Several DS have already been used by US soybean breeders in their programs.

Gametophytic self-incompatibility (GSI) is a reproductive strategy to prevent inbreeding and promote outcrossing. Studies to understand molecular and evolutionary aspects of the self-compatibility (SC)/self-incompatibility (SI) system in the Solanaceae have been conducted using several genera including Petunia Juss., Nicotiana L., and Solanum L. S-RNases are pistil determinants of GSI and multiple S-RNase alleles have been identified in a few potato species. S-locus F-box genes (SLFs), the pollen determinants of SI, are linked to S-RNases on chromosome 1. The S-RNase and SLFs present on each chromatid determine an individual's SC/SI haplotypes. However, the extent of SLF diversity, the number and position of SLFs in the S-locus, and their mechanism of interaction with S-RNases is unknown in potato or its wild relatives, most of which are diploid and SI. A combination of genome and transcriptome analysis from pollen and pistils of wild and cultivated diploid potatoes was used to determine the structure of the S-locus. Our analysis showed that SLF sequences are expressed in pollen but not in styles, vary in number between individuals, and are distributed across a 9-17 Mb region flanking one S-RNase gene. Preferential associations within haplotigs of specific S-RNase types and SLF types were not observed. Extensive sequence diversity was observed for S-RNases and SLFs, and phylogenetic analysis indicates that diversification of both genes predates the divergence between tomatoes and potatoes. This research sheds light on how these two pistil and pollen elements interact to determine SI or SC and may further our understanding of gene flow in wild potato species.

Peanut (Arachis hypogaea L.) is one of the most important oilseed and food crops, and the drought stress remains the primary adverse environmental factor limiting its growth and productivity. Mitogen-activated protein kinase (MAPK) cascades play crucial roles in various signal transduction pathways, affecting a wide range of physiological processes and drought stress responses in plants; however, the systematic analysis of the MAPK gene family in peanuts remains unexplored. In this study, we identified 30, 16, and 15 MAPK genes in A. hypogaea, Arachis duranensis, and Arachis ipaensis, respectively. RNA-sequencing analysis in drought-tolerant and drought-susceptible genotypes revealed that Ah_At_MAPK4 and Ah_Bt_MAPK4 were significantly upregulated under drought stress conditions, with substantially higher induction in drought-tolerant genotypes compared to drought-susceptible ones. Weighted gene co-expression network analysis further identified a drought-responsive turquoise module highly correlated with drought tolerance traits, and both Ah_At_MAPK4 and Ah_Bt_MAPK4 were identified as core regulatory components within this module. Hub gene analysis revealed these MAPKs co-express with calmodulin-binding proteins, implicating calcium signaling in drought adaptation. Three-dimensional structural modeling confirmed both proteins possess canonical bilobed kinase architecture with properly positioned Thr-Glu-Tyr motifs and intact catalytic machinery. This genome-to-structure analysis identifies Ah_At_MAPK4 and Ah_Bt_MAPK4 as key components in drought-responsive networks and provides molecular targets for enhancing drought resilience in peanut breeding.

Flooding has become a major threat to soybean [Glycine max (L.) Merr.] production as the frequency and intensity of extreme precipitations have been increasing due to climate change. While advances have been made in identifying soybean genetic resources and genomic regions associated with mid-season flood tolerance, there is limited understanding of early season flood tolerance at the vegetative growth stages V2/V4. This study aimed to identify genomic regions associated with early season flood tolerance using a diverse panel of 254 soybean accessions, as well as investigate the viability of implementing genomic prediction models for flood tolerance. Field trials were conducted over 2 years, with flooding imposed at the V2/V4 vegetative growth stages. Genome-wide association studies were performed using the Bayesian-information and linkage-disequilibrium iteratively nested keyway and the multiple locus mixed linear model. Forward stepwise genomic prediction models using random forest (RF) were developed to identify the set of single nucleotide polymorphisms (SNPs) yielding the highest prediction accuracy while assessing the negative impacts of multicollinearity and overfitting on prediction accuracy. Genomic regions on chromosomes 4, 17, and 20 associated with early season flood tolerance were identified, all distinct from regions previously identified for mid-season tolerance. The RF model achieved a prediction accuracy of 0.64 with 29 selected SNPs, significantly improving over RF and ridge regression best linear unbiased prediction models with higher SNP counts. These findings provide genomic tools for improving the efficiency of breeding for early season flood tolerance, supporting the need to develop season-long flood-tolerant soybean genotypes.

Elucidating the impacts of demographic history and genomic selection on species evolution is a central topic in phylogeography and evolutionary biology. Black walnuts (Juglans section Rhysocaryon) are native nut trees of the NEW WORLD, with a broad distribution ranging from southern Canada to northern Argentina. The demographic history and genomic dynamics of Rhysocaryon species remain poorly understood. Here, we employed population genomics and chloroplast data to construct a high-density map of genomic variation across 108 Rhysocaryon accessions. Despite gene introgression, these accessions were clearly delimited into four groups. Evolutionary scenarios analysis showed that the diversification of black walnuts might have occurred approximately 28.74 million years ago during the late Oligocene, with the clade comprising Juglans hindsii and Juglans californica diverging earliest. The gene introgression and hybridization analysis indicated that Juglans microcarpa might be a hybrid descendant of Juglans nigra and J. hindsii. As the climate oscillated, these ancestral populations kept diverging, laying the basis for their colonization of South America. Quaternary climatic oscillations also exerted a profound influence on black walnut population size, which exhibited sensitive fluctuations in response to alternation of glacial and interglacial periods. The selection sweeps analysis unveiled highly divergent genomic regions in the economic species J. nigra, which were associated with development, reproduction, disease resistance, and stress tolerance. The genes WRKY41 and ERF012 were identified as potential drivers of J. nigra's adaptation. Our findings illuminated the demographic history and selective signatures of black walnuts, thereby providing a genetic foundation for future breeding, conservation, and genomic studies.