Plant Genome最新文献

Ginger (Zingiber officinale Roscoe) is an important plant used worldwide for medicine and food. The R2R3-MYB transcription factor (TF) family has essential roles in plant growth, development, and stresses resistance, and the number of genes in the family varies greatly among different types of plants. However, genome-wide discovery of ZoMYBs and gene responses to stresses have not been reported in ginger. Therefore, genome-wide analysis of R2R3-MYB genes in ginger was conducted in this study. Protein phylogenetic relations and conserved motifs and chromosome localization and duplication, structure, and cis-regulatory elements were analyzed. In addition, the expression patterns of selected genes were analyzed under two different stresses. A total of 299 candidate ZoMYB genes were discovered in ginger. Based on groupings of R2R3-MYB genes in the model plant Arabidopsis thaliana (L.) Heynh., ZoMYBs were divided into eight groups. Genes were distributed across 22 chromosomes at uneven densities. In gene duplication analysis, 120 segmental duplications were identified in the ginger genome. Gene expression patterns of 10 ZoMYBs in leaves of ginger under abscisic acid (ABA) and low-temperature stress treatments were different. The results will help to determine the exact roles of ZoMYBs in anti-stress responses in ginger.

One of the thrust areas of research in plant breeding is to develop crop cultivars with enhanced tolerance to abiotic stresses. Thus, identifying abiotic stress-responsive genes (SRGs) and proteins is important for plant breeding research. However, identifying such genes via established genetic approaches is laborious and resource intensive. Although transcriptome profiling has remained a reliable method of SRG identification, it is species specific. Additionally, identifying multistress responsive genes using gene expression studies is cumbersome. Thus, endorsing the need to develop a computational method for identifying the genes associated with different abiotic stresses. In this work, we aimed to develop a computational model for identifying genes responsive to six abiotic stresses: cold, drought, heat, light, oxidative, and salt. The predictions were performed using support vector machine (SVM), random forest, adaptive boosting (ADB), and extreme gradient boosting (XGB), where the autocross covariance (ACC) and K-mer compositional features were used as input. With ACC, K-mer, and ACC + K-mer compositional features, the overall accuracy of ∼60-77, ∼75-86, and ∼61-78% were respectively obtained using the SVM algorithm with fivefold cross-validation. The SVM also achieved higher accuracy than the other three algorithms. The proposed model was also assessed with an independent dataset and obtained an accuracy consistent with cross-validation. The proposed model is the first of its kind and is expected to serve the requirement of experimental biologists; however, the prediction accuracy was modest. Given its importance for the research community, the online prediction application, ASRpro, is made freely available (https://iasri-sg.icar.gov.in/asrpro/) for predicting abiotic SRGs and proteins.

Changing climatic conditions with rising temperatures and altered precipitation patterns pose significant challenges to agricultural productivity, particularly for common bean crops. Transcription factors (TFs) are crucial regulators that can mitigate the impact of biotic and abiotic stresses on crop production. The MADS-box TFs family has been implicated in various plant physiological processes, including stress-responsive mechanisms. However, their role in common bean and their response to stressful conditions remain poorly understood. Here, we identified 35 MADS-box gene family members in common bean, with conserved MADS-box domains and other functional domains. Gene duplication events were observed, suggesting the significance of duplication in the evolutionary development of gene families. The analysis of promoter regions revealed diverse elements, including stress-responsive elements, indicating their potential involvement in stress responses. Notably, PvMADS31, a member of the PvMADS-box gene family, demonstrated rapid upregulation under various abiotic stress conditions, including NaCl, polyethylene glycol, drought, and abscisic acid (ABA) treatments. Transgenic plants overexpressing PvMADS31 displayed enhanced lateral root development, root elongation, and seed germination under stress conditions. Furthermore, PvMADS31 overexpression in Arabidopsis resulted in improved drought tolerance, likely attributed to the enhanced scavenging of ROS and increased proline accumulation. These findings suggest that PvMADS31 might play a crucial role in modulating seed germination, root development, and stress responses, potentially through its involvement in auxin and ABA signaling pathways. Overall, this study provides valuable insights into the potential roles of PvMADS-box genes in abiotic stress responses in common bean, offering prospects for crop improvement strategies to enhance resilience under changing environmental conditions.

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.

At the turn of 2000 many authors envisioned future plant breeding. Twenty years after, which of those authors' visions became reality or not, and which ones may become so in the years to come. After two decades of debates, climate change is a "certainty," food systems shifted from maximizing farm production to reducing environmental impact, and hopes placed into GMOs are mitigated by their low appreciation by consumers. We revise herein how plant breeding may raise or reduce genetic gains based on the breeder's equation. "Accuracy of Selection" has significantly improved by many experimental-scale field and laboratory implements, but also by vulgarizing statistical models, and integrating DNA markers into selection. Pre-breeding has really promoted the increase of useful "Genetic Variance." Shortening "Recycling Time" has seen great progression, to the point that achieving a denominator equal to "1" is becoming a possibility. Maintaining high "Selection Intensity" remains the biggest challenge, since adding any technology results in a higher cost per progeny, despite the steady reduction in cost per datapoint. Furthermore, the concepts of variety and seed enterprise might change with the advent of cheaper genomic tools to monitor their use and the promotion of participatory or citizen science. The technological and societal changes influence the new generation of plant breeders, moving them further away from field work, emphasizing instead the use of genomic-based selection methods relying on big data. We envisage what skills plant breeders of tomorrow might need to address challenges, and whether their time in the field may dwindle.

Verticillium wilt (VW), a devastating vascular wilt disease of strawberry (Fragaria $\times$ ananassa), has caused economic losses for nearly a century. This disease is caused by the soil-borne pathogen Verticillium dahliae, which occurs nearly worldwide and causes disease in numerous agriculturally important plants. The development of VW-resistant cultivars is critically important for the sustainability of strawberry production. We previously showed that a preponderance of the genetic resources (asexually propagated hybrid individuals) preserved in public germplasm collections were moderately to highly susceptible and that genetic gains for increased resistance to VW have been negligible over the last 60 years. To more fully understand the challenges associated with breeding for increased quantitative resistance to this pathogen, we developed and phenotyped a training population of hybrids ( $n=564$ ) among elite parents with a wide range of resistance phenotypes. When these data were combined with training data from a population of elite and exotic hybrids ( $n=386$ ), genomic prediction accuracies of 0.47-0.48 were achieved and were predicted to explain 70%-75% of the additive genetic variance for resistance. We concluded that breeding values for resistance to VW can be predicted with sufficient accuracy for effective genomic selection with routine updating of training populations.

Understanding the underlying genetic bases of yield-related selection and distinguishing these changes from genetic drift are critical for both improved understanding and future success of plant breeding. Soybean [Glycine max (L.) Merr.] is a key species for world food security, yet knowledge of the mechanism of selective breeding in soybean, such as the century-long program of artificial selection in U.S. soybean germplasm, is currently limited to certain genes and loci. Here, we identify genome-wide signatures of selection in separate populations of soybean subjected to artificial selection for increased yield by multiple breeding programs in the United States. We compared the alternative soybean breeding population (AGP) created by USDA-ARS to the conventional public soybean lines (CGP) developed at three different stages of breeding (ancestral, intermediate, and elite) to identify shared signatures of selection and differentiate these from drift. The results showed a strong selection for specific haplotypes identified by single site frequency and haplotype homozygosity methods. A set of common selection signatures was identified in both AGP and CGP that supports the hypothesis that separate breeding programs within similar environments coalesce on the fixation of the same key haplotypes. Signatures unique to each breeding program were observed. These results raise the possibility that selection analysis can allow the identification of favorable alleles to enhance directed breeding approaches.

Circular RNAs (circRNAs) are covalently closed single-stranded RNAs, generated through a back-splicing process that links a downstream 5' site to an upstream 3' end. The only distinction in the sequence between circRNA and their linear cognate RNA is the back splice junction. Their low abundance and sequence similarity with their linear origin RNA have made the discovery and identification of circRNA challenging. We have identified almost 6000 novel circRNAs from Lotus japonicus leaf tissue using different enrichment, amplification, and sequencing methods as well as alternative bioinformatics pipelines. The different methodologies identified different pools of circRNA with little overlap. We validated circRNA identified by the different methods using reverse transcription polymerase chain reaction and characterized sequence variations using nanopore sequencing. We compared validated circRNA identified in L. japonicus to other plant species and showed conservation of high-confidence circRNA-expressing genes. This is the first identification of L. japonicus circRNA and provides a resource for further characterization of their function in gene regulation. CircRNAs identified in this study originated from genes involved in all biological functions of eukaryotic cells. The comparison of methodologies and technologies to sequence, identify, analyze, and validate circRNA from plant tissues will enable further research to characterize the function and biogenesis of circRNA in L. japonicus.

Cowpea, Vigna unguiculata L. Walp., is a diploid warm-season legume of critical importance as both food and fodder in sub-Saharan Africa. This species is also grown in Northern Africa, Europe, Latin America, North America, and East to Southeast Asia. To capture the genomic diversity of domesticates of this important legume, de novo genome assemblies were produced for representatives of six subpopulations of cultivated cowpea identified previously from genotyping of several hundred diverse accessions. In the most complete assembly (IT97K-499-35), 26,026 core and 4963 noncore genes were identified, with 35,436 pan genes when considering all seven accessions. GO terms associated with response to stress and defense response were highly enriched among the noncore genes, while core genes were enriched in terms related to transcription factor activity, and transport and metabolic processes. Over 5 million single nucleotide polymorphisms (SNPs) relative to each assembly and over 40 structural variants >1 Mb in size were identified by comparing genomes. Vu10 was the chromosome with the highest frequency of SNPs, and Vu04 had the most structural variants. Noncore genes harbor a larger proportion of potentially disruptive variants than core genes, including missense, stop gain, and frameshift mutations; this suggests that noncore genes substantially contribute to diversity within domesticated cowpea.

Spot blotch caused by Bipolaris sorokiniana ((Sacc.) Shoemaker) (teleomorph: Cochliobolus sativus [Ito and Kuribayashi] Drechsler ex Dastur) is an economically important disease of warm and humid regions. The present study focused on identifying resistant genotypes and single-nucleotide polymorphism (SNP) markers associated with spot blotch resistance in a panel of 174 bread spring wheat lines using field screening and genome-wide association mapping strategies. Field experiments were conducted in Agua Fria, Mexico, during the 2019-2020 and 2020-2021 cropping seasons. A wide range of phenotypic variation was observed among genotypes tested during both years. Twenty SNP markers showed significant association with spot blotch resistance on 15 chromosomes, namely, 1A, 1B, 2A, 2B, 2D, 3A, 3B, 4B, 4D, 5A, 5B, 6A, 6B, 7A, and 7B. Of these, two consistently significant SNPs on 5A, TA003225-0566 and TA003225-1427, may represent a new resistance quantitative trait loci. Further, in the proximity of Tsn1 on 5B, AX-94435238 was the most stable and consistent in both years. The identified genomic regions could be deployed to develop spot blotch-resistant genotypes, particularly in the spot blotch-vulnerable wheat growing areas.