Plant Genome最新文献

Phytophthora root rot, caused by oomycete pathogens in the Phytophthora genus, poses a significant threat to soybean productivity. While resistance mechanisms against Phytophthora sojae have been extensively studied in soybean, the molecular basis underlying immune responses to Phytophthora sansomeana remains unclear. In this study, we investigated transcriptomic and epigenetic responses of two resistant (Colfax and NE2701) and two susceptible (Williams 82 and Senaki) soybean lines at four time points (2, 4, 8, and 16 h post inoculation [hpi]) after P. sansomeana inoculation. Comparative transcriptomic analyses revealed a greater number of differentially expressed genes (DEGs) upon pathogen inoculation in resistant lines, particularly at 8 and 16 hpi. These DEGs were predominantly associated with defense response, ethylene, and reactive oxygen species-mediated defense pathways. Moreover, DE transposons were predominantly upregulated after inoculation, and more of them were enriched near genes in Colfax than other soybean lines. Notably, we identified a long non-coding RNA (lncRNA) within the mapped region of the resistance gene that exhibited exclusive upregulation in the resistant lines after inoculation, potentially regulating two flanking LURP-one-related genes. Furthermore, DNA methylation analysis revealed increased CHH (where H = A, T, or C) methylation levels in lncRNAs after inoculation, with delayed responses in Colfax compared to Williams 82. Overall, our results provide comprehensive insights into soybean responses to P. sansomeana, highlighting potential roles of lncRNAs and epigenetic regulation in plant defense.

Bananas (Musa spp.) are one of the most highly consumed fruits globally, grown in the tropical and sub-tropical regions. We evaluated 856 Musa accessions from the breeding programs of the International Institute of Tropical Agriculture of Nigeria, Tanzania, and Uganda; the National Agricultural Research Organization of Uganda; the Brazilian Agricultural Research Corporation (Embrapa); and the National Research Centre for Banana of India. Accessions from the in vitro gene bank at the International Transit Centre in Belgium were included to provide a baseline of available global diversity. A total of 16,903 informative single nucleotide polymorphism markers were used to estimate and characterize the genetic diversity and population structure and identify overlaps and unique material among the breeding programs. Analysis of molecular variance displayed low genetic variation among accessions and diploids and a higher variation among tetraploids (p < 0.001). Structure analysis revealed two major clusters corresponding to genomic composition. The results indicate that there is potential for the banana breeding programs to increase the diversity in their breeding materials and should exploit this potential for parental improvement and to enhance genetic gains in future breeding efforts.

Spike length (SL) is one of the major contributors to wheat yield. Uncovering major genetic regions affecting SL is an integral part of elucidating the genetic basis of wheat yield traits and goes further pivotal for marker-assisted selection breeding. A genome-wide meta-quantitative trait locus (MQTL) analysis of wheat SL resulted in the refinement of 48 MQTLs using 227 initial QTLs retrieved from previous studies published over the past decades. The average confidence interval (CI) of these MQTLs amounted to a 5.16-fold reduction compared to the mean CI of the initial QTLs. As many as 2240 putative candidate genes (CGs) were identified from the MQTL intervals using transcriptomics data in silico of wheat, of which 58 CGs were identified based on wheat-rice homology analysis. For the key CG affecting SL, a functional kompetitive allele-specific PCR (KASP) marker, TaPP2C-3B-KASP, was developed to distinguish TaPP2C-3B-Hap I and TaPP2C-3B-Hap II based on the single nucleotide polymorphism at the 272 bp (A/G). The frequency of the elite allelic variation TaPP2C-3B-Hap II with high SL remained relatively stable at about 49.62% from the 1960s to 1990s. Integration of MQTL analysis and in silico transcriptome data led to a significant increase in the reliability of CGs for the genetic regulation of wheat SL, and the haplotype analysis for key CGs TaPP2C-3B of SL provided insights into the biological function of the TaPP2C-3B gene.

Phenotypic selection of complex traits such as seed yield and protein in the preliminary yield trial (PYT) is often constrained by limited seed availability, resulting in trials with few environments and minimal to no replications. Multi-trait multi-environment enabled genomic prediction (MTME-GP) offers a valuable alternative to predict missing phenotypes of selection candidates for multiple traits and diverse environments. In this study, we assessed the efficiency of MTME-GP for improving seed protein and seed yield in field pea, the top two breeding targets but highly antagonistic traits in pulse crop. We utilized a set of 300 selection candidates in the PYT that virtually represented all possible families of the North Dakota State University field pea breeding program. Selection candidates were evaluated in three diverse, contrasting environments, as indicated by a range of heritability. Using whole- and split-environment cross validation schemes, MTME-GP had higher predictive ability than a standard additive G-BLUP model. Integrating a range of overlapping genotypes in between environments showed improvement on the predictive ability of the MTME-GP model but tends to plateau at 50%-80% training set size. Regardless of the cross-validation scheme, accuracy was among the lowest in stressed environments, presumably due to low heritability for seed protein and yield. This study provided insights into the potential of MTME-GP in a public pulse crop breeding program. The MTME-GP framework can be further improved with more testing environments and integration of additional orthogonal information in the early stages of the breeding pipeline.

Helicoverpa armigera (also known as gram pod borer) is a serious threat to chickpea production in the world. A set of 173 chickpea genotypes were evaluated for H. armigera resistance, including mean larval population (MLP), percentage pod damage (PPD), and pest resistance (PR) for 2 consecutive years (year 2020 and 2021). The same core set was also genotyped with 50K Axiom CicerSNP Array. The trait data and 50,000 single nucleotide polymorphism genotypic data were used together to work out marker-trait associations (MTAs) using different genome-wide association studies models. For MLP, a total of 53 MTAs were identified, including 25 MTAs in year 2020 and 28 MTAs in year 2021. A set of three MTAs was found common in both environments. For PPD, two MTAs in year 2020 and five MTAs in year 2021 were identified. A set of two MTAs were common in both environments. Similarly, for PR, only two MTAs common in both environments were identified. Interestingly, a common MTA (Affx_123255526) on chromosome 2 (Ca2) was found to be associated with all the three component traits (MLP, PPD, and PR) of pod borer resistance in chickpea. Further, we report key genes that encode SCAMPs (that facilitates the secretion of defense-related molecules), quinone oxidoreductase (enables the production of reactive oxygen species that promotes diapause of gram pod borer), and NB-LRR proteins that have been implicated in plant defense against H. armigera. The resistant chickpea genotypes, MTAs, and key genes reported in the present study may prove useful in the future for developing pod borer-resistant chickpea varieties.

The small heat shock proteins (sHSPs) are important components in plant growth and development, and stress response. However, a systematical understanding of the sHSP family is yet to be reported in five diploid Gossypium species. In this study, 34 GlsHSPs, 36 GrsHSPs, 37 GtsHSPs, 37 GasHSPs, and 38 GhesHSPs were identified in Gossypium longicalyx, Gossypium raimondii, Gossypium turneri, Gossypium arboreum, and Gossypium herbaceum, respectively. These sHSP members can be clustered into 10 subfamilies. Different subfamilies had different member numbers, motif distributions, gene structures, gene duplication events, gene loss numbers, and cis-regulatory elements. Besides, the paleohexaploidization event in cotton ancestor led to expanding the sHSP members and it was also inherited by five diploid Gossypium species. After the cotton ancestor divergence, the sHSP members had the relatively conserved evolution in five diploid Gossypium species. The comprehensive evolutionary history of the sHSP family was revealed in five diploid Gossypium species. Furthermore, several GasHSPs and GhesHSPs were important candidates in plant growth and development, and stress response. These current findings can provide valuable information for the molecular evolution and further functional research of the sHSP family in cotton.

Sesame (Sesamum indicum) is an important oilseed crop with rising demand owing to its nutritional and health benefits. There is an urgent need to develop and integrate new genomic-based breeding strategies to meet these future demands. While genomic resources have advanced genetic research in sesame, the implementation of high-throughput phenotyping and genetic analysis of longitudinal traits remains limited. Here, we combined high-throughput phenotyping and random regression models to investigate the dynamics of plant height, leaf area index, and five spectral vegetation indices throughout the sesame growing seasons in a diversity panel. Modeling the temporal phenotypic and additive genetic trajectories revealed distinct patterns corresponding to the sesame growth cycle. We also conducted longitudinal genomic prediction and association mapping of plant height using various models and cross-validation schemes. Moderate prediction accuracy was obtained when predicting new genotypes at each time point, and moderate to high values were obtained when forecasting future phenotypes. Association mapping revealed three genomic regions in linkage groups 6, 8, and 11, conferring trait variation over time and growth rate. Furthermore, we leveraged correlations between the temporal trait and seed-yield and applied multi-trait genomic prediction. We obtained an improvement over single-trait analysis, especially when phenotypes from earlier time points were used, highlighting the potential of using a high-throughput phenotyping platform as a selection tool. Our results shed light on the genetic control of longitudinal traits in sesame and underscore the potential of high-throughput phenotyping to detect a wide range of traits and genotypes that can inform sesame breeding efforts to enhance yield.

Root metaxylems are phenotypically diverse structures whose function is particularly important under drought stress. Significant research has dissected the genetic machinery underlying metaxylem phenotypes in dicots, but that of monocots are relatively underexplored. In maize (Zea mays), a robust pipeline integrated a genome-wide association study (GWAS) of root metaxylem phenes under well-watered and water-stress conditions with a gene co-expression network to prioritize the strongest gene candidates. We identified 244 candidate genes by GWAS, of which 103 reside in gene co-expression modules most relevant to xylem development. Several candidate genes may be involved in biosynthetic processes related to the cell wall, hormone signaling, oxidative stress responses, and drought responses. Of those, six gene candidates were detected in multiple root metaxylem phenes in both well-watered and water-stress conditions. We posit that candidate genes that are more essential to network function based on gene co-expression (i.e., hubs or bottlenecks) should be prioritized and classify 33 essential genes for further investigation. Our study demonstrates a new strategy for identifying promising gene candidates and presents several gene candidates that may enhance our understanding of vascular development and responses to drought in cereals.

The rhomboid-like (RBL) gene encodes serine protease, which plays an important role in the response to cell development and diverse stresses. However, genome-wide identification, expression profiles, and haplotype analysis of the RBL family genes have not been performed in wheat (Triticum aestivum L.). This study investigated the phylogeny and diversity of the RBL family genes in the wheat genome through various approaches, including gene structure analysis, evolutionary relationship analysis, promoter cis-acting element analysis, expression pattern analysis, and haplotype analysis. The 41 TaRBL genes were identified and divided into five subfamilies in the wheat genome. RBL family genes were expanded through segmented duplication and purification selection. The cis-element analysis revealed their involvement in various stress responses and plant development. The results of RNA-seq and quantitative real-time-PCR showed that TaRBL genes displayed higher expression levels in developing spike/grain and were differentially regulated under polyethylene glycol, NaCl, and abscisic acid treatments, indicating their roles in grain development and abiotic stress response. A kompetitive allele-specific PCR molecular marker was developed to confirm the single nucleotide polymorphism of TaRBL14a gene in 263 wheat accessions. We found that the elite haplotype TaRBL14a-Hap2 showed a significantly higher 1000-grain weight than TaRBL14a-Hap11 in at least three environments, and the TaRBL14a-Hap2 was positively selected in wheat breeding. The findings will provide a good insight into the evolutionary and functional characteristics of the TaRBL genes family in wheat and lay the foundation for future exploration of the regulatory mechanisms of TaRBL genes in plant growth and development, as well as their response to abiotic stresses.