Theoretical and Applied Genetics最新文献

Key message: One hundred and fifty-five QTL for trace element concentrations in foxtail millet were identified using a genome-wide association study, and a candidate gene associated with Ni-Co-Cr concentrations was detected. Foxtail millet (Setaria italica) is an important regional crop known for its rich mineral nutrient content, which has beneficial effects on human health. We assessed the concentrations of ten trace elements (Ba, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sr, and Zn) in the grain of 408 foxtail millet accessions. Significant differences in the concentrations of five elements (Ba, Co, Ni, Sr, and Zn) were observed between two subpopulations of spring- and summer-sown foxtail millet varieties. Moreover, 84.4% of the element pairs exhibited significant correlations. To identify the genetic factors influencing trace element accumulation, a comprehensive genome-wide association study was conducted, identifying 155 quantitative trait locus (QTL) for the ten trace elements across three different environments. Among them, ten QTL were consistently detected in multiple environments, including qZn2.1, qZn4.4, qCr4.1, qFe6.3, qFe6.5, qCo6.1, qPb7.3, qPb7.5, qBa9.1, and qNi9.1. Thirteen QTL clusters were detected for multiple elements, which partially explained the correlations between elements. Additionally, the different concentrations of five elements between foxtail millet subpopulations were caused by the different frequencies of high-concentration alleles associated with important marker-trait associations. Haplotype analysis identified a candidate gene SETIT_036676mg associated with Ni accumulation, with the GG haplotype significantly increasing Ni-Co-Cr concentrations in foxtail millet. A cleaved amplified polymorphic sequence marker (cNi6676) based on the two haplotypes of SETIT_036676mg was developed and validated. Results of this study provide valuable reference information for the genetic research and improvement of trace element content in foxtail millet.

Key message: Genetic dissection of a QTL from wild emmer wheat, QGpc.huj.uh-5B.2, introgressed into bread wheat, identified candidate genes associated with tolerance to nitrogen deficiency, and potentially useful for improving nitrogen-use efficiency. Nitrogen (N) is an important macronutrient critical to wheat growth and development; its deficiency is one of the main factors causing reductions in grain yield and quality. N availability is significantly affected by drought or flooding, that are dependent on additional factors including soil type or duration and severity of stress. In a previous study, we identified a high grain protein content QTL (QGpc.huj.uh-5B.2) derived from the 5B chromosome of wild emmer wheat, that showed a higher proportion of explained variation under water-stress conditions. We hypothesized that this QTL is associated with tolerance to N deficiency as a possible mechanism underlying the higher effect under stress. To validate this hypothesis, we introgressed the QTL into the elite bread wheat var. Ruta, and showed that under N-deficient field conditions the introgression IL99 had a 33% increase in GPC (p < 0.05) compared to the recipient parent. Furthermore, evaluation of IL99 response to severe N deficiency (10% N) for 14 days, applied using a semi-hydroponic system under controlled conditions, confirmed its tolerance to N deficiency. Fine-mapping of the QTL resulted in 26 homozygous near-isogenic lines (BC₄F₅) segregating to N-deficiency tolerance. The QTL was delimited from - 28.28 to - 1.29 Mb and included 13 candidate genes, most associated with N-stress response, N transport, and abiotic stress responses. These genes may improve N-use efficiency under severely N-deficient environments. Our study demonstrates the importance of WEW as a source of novel candidate genes for sustainable improvement in tolerance to N deficiency in wheat.

Phytotoxic soil salinity is a global problem, and in the northern Great Plains and western Canada, salt accumulates on the surface of marine sediment soils with high water tables under annual crop cover, particularly near wetlands. Crop production can overcome saline-affected soils using crop species and cultivars with salinity tolerance along with changes in management practices. This research seeks to improve our understanding of sunflower (Helianthus annuus) genetic tolerance to high salinity soils. Genome-wide association was conducted using the Sunflower Association Mapping panel grown for two years in naturally occurring saline soils (2016 and 2017, near Indian Head, Saskatchewan, Canada), and six phenotypes were measured: days to bloom, height, leaf area, leaf mass, oil percentage, and yield. Plot level soil salinity was determined by grid sampling of soil followed by kriging. Three estimates of sunflower performance were calculated: (1) under low soil salinity (< 4 dS/m), (2) under high soil salinity (> 4 dS/m), and (3) plasticity (regression coefficient between phenotype and soil salinity). Fourteen loci were significant, with one instance of co-localization between a leaf area and a leaf mass locus. Some genomic regions identified as significant in this study were also significant in a recent greenhouse salinity experiment using the same panel. Also, some candidate genes underlying significant QTL have been identified in other plant species as having a role in salinity response. This research identifies alleles for cultivar improvement and for genetic studies to further elucidate salinity tolerance pathways.

Key message: Phenotypical, physiological and genetic characterization was carried out on the hybrid necrosis gene from Haynaldia villosa, and the related gene Ne-V was mapped to chromosome arm 2VL. Introducing genetic variation from wild relatives into common wheat through wide crosses is a vital strategy for enriching genetic diversity and promoting wheat breeding. However, hybrid necrosis, a genetic autoimmunity syndrome, often occurs in the offspring of interspecific or intraspecific crosses, restricting both the selection of hybrid parents and the pyramiding of beneficial genes. To utilize the germplasms of Haynaldia villosa (2n = 2x = 14, VV), we conducted wide hybridization between durum wheat (2n = 4x = 28, AABB) and multiple H. villosa accessions to synthesize the amphiploids (2n = 6x = 42, AABBVV). This study revealed that 61.5% of amphiploids derived from the above crosses exhibited hybrid necrosis, with some amphiploids even dying before reaching maturity. However, the initiation time and severity of necrosis varied dramatically among the progenies, suggesting that there were multiple genetic loci or multiple alleles in the same genetic locus conferring to hybrid necrosis in H. villosa accessions. Genetic analysis was performed on the F₂ and derived F_2:3 populations, which were constructed between amphiploid STH59-1 with normal leaves and amphiploid STH59-2 with necrotic leaves. A semidominant hybrid necrosis-related gene, Ne-V, was mapped to an 11.8-cM genetic interval on the long arm of chromosome 2V, representing a novel genetic locus identified in Triticum-related species. In addition, the hybrid necrosis was correlated with enhanced H₂O₂ accumulation and cell death, and it was influenced by the temperature and light. Our findings provide a foundation for cloning the Ne-V gene and exploring its molecular mechanism.

Polyploidy played an important role in the evolution of the three most important crops: wheat, maize and rice, each of them providing a unique model for studying allopolyploidy, segmental alloploidy or paleopolyploidy. However, its genetic and evolutionary role is still vague. The undelying mechanisms and consequences of polyploidy remain fundamental objectives in the study of eukaryotes. Maize is one of the underutilized crops at the polyploid level. This species has no stable natural polyploids, the existing ones being artificially obtained. From the experimental polyploid series of maize, only the tetraploid forms (4n = 40) are of interest. They are characterized by some valuable morphological, physiological and biochemical features, superior to the diploid forms from which they originated, but also by some drawbacks such as: reduced fertility, slower development, longer vegetation period, low productivity and adaptedness. Due to these barriers to using tetraploids in field production, maize tetraploids primarily found utility in scientific studies regarding genetic variability, inbreeding, heterosis and gene dosage effect. Since the first mention of a triploid maize plant to present, many scientists and schools, devoted their efforts to capitalize on the use of polyploidy in maize. Despite its common disadvantages as a crop, significant progress in developing tetraploid maize with good agronomic performance was achieved leading to registered tetraploid maize varieties. In this review we summarize and discuss the different aspects of polyploidy in maize, such as evolutionary context, methods of induction, morphology, fertility issue, inheritance patterns, gene expression and potential use.

Key message: The exploration and dissection of a set of QTLs and candidate genes for gray leaf spot disease resistance using two fully assembled parental genomes may help expedite maize resistance breeding. The fungal disease of maize known as gray leaf spot (GLS), caused by Cercospora zeae-maydis and Cercospora zeina, is a significant concern in China, Southern Africa, and the USA. Resistance to GLS is governed by multiple genes with an additive effect and is influenced by both genotype and environment. The most effective way to reduce the cost of production is to develop resistant hybrids. In this study, we utilized the IBM Syn 10 Doubled Haploid (IBM Syn10 DH) population to identify quantitative trait loci (QTLs) associated with resistance to gray leaf spot (GLS) in multiple locations. Analysis of seven distinct environments revealed a total of 58 QTLs, 49 of which formed 12 discrete clusters distributed across chromosomes 1, 2, 3, 4, 8 and 10. By comparing these findings with published research, we identified colocalized QTLs or GWAS loci within eleven clustering intervals. By integrating transcriptome data with genomic structural variations between parental individuals, we identified a total of 110 genes that exhibit both robust disparities in gene expression and structural alterations. Further analysis revealed 19 potential candidate genes encoding conserved resistance gene domains, including putative leucine-rich repeat receptors, NLP transcription factors, fucosyltransferases, and putative xyloglucan galactosyltransferases. Our results provide a valuable resource and linked loci for GLS marker resistance selection breeding in maize.

Key messages: We investigate a method of extracting and fitting synthetic environmental covariates and pedigree information in multilocation trial data analysis to predict genotype performances in untested locations. Plant breeding trials are usually conducted across multiple testing locations to predict genotype performances in the targeted population of environments. The predictive accuracy can be increased by the use of adequate statistical models. We compared linear mixed models with and without synthetic covariates (SCs) and pedigree information under the identity, the diagonal and the factor-analytic variance-covariance structures of the genotype-by-location interactions. A comparison was made to evaluate the accuracy of different models in predicting genotype performances in untested locations using the mean squared error of predicted differences (MSEPD) and the Spearman rank correlation between predicted and adjusted means. A multi-environmental trial (MET) dataset evaluated for yield performance in the dry lowland sorghum (Sorghum bicolor (L.) Moench) breeding program of Ethiopia was used. For validating our models, we followed a leave-one-location-out cross-validation strategy. A total of 65 environmental covariates (ECs) obtained from the sorghum test locations were considered. The SCs were extracted from the ECs using multivariate partial least squares analysis and subsequently fitted in the linear mixed model. Then, the model was extended accounting for pedigree information. According to the MSEPD, models accounting for SC improve predictive accuracy of genotype performances in the three of the variance-covariance structures compared to others without SC. The rank correlation was also higher for the model with the SC. When the SC was fitted, the rank correlation was 0.58 for the factor analytic, 0.51 for the diagonal and 0.46 for the identity variance-covariance structures. Our approach indicates improvement in predictive accuracy with SC in the context of genotype-by-location interactions of a sorghum breeding in Ethiopia.

Key message: De novo genotyping in potato using methylation-sensitive GBS discovers SNPs largely confined to genic or gene-associated regions and displays enhanced effectiveness in estimating LD decay rates, population structure and detecting GWAS associations over 'fixed' SNP genotyping platform. Study also reports the genetic architectures including robust sequence-tagged marker-trait associations for sixteen important potato traits potentially carrying higher transferability across a wider range of germplasm. This study deploys recent advancements in polyploid analytical approaches to perform complex trait analyses in cultivated tetraploid potato. The study employs a 'fixed' SNP Infinium array platform and a 'flexible and open' genome complexity reduction-based sequencing method (GBS, genotyping-by-sequencing) to perform genome-wide association studies (GWAS) for several key potato traits including the assessment of population structure and linkage disequilibrium (LD) in the studied population. GBS SNPs discovered here were largely confined (~ 90%) to genic or gene-associated regions of the genome demonstrating the utility of using a methylation-sensitive restriction enzyme (PstI) for library construction. As compared to Infinium array SNPs, GBS SNPs displayed enhanced effectiveness in estimating LD decay rates and discriminating population subgroups. GWAS using a combined set of 30,363 SNPs identified 189 unique QTL marker-trait associations (QTL-MTAs) covering all studied traits. The majority of the QTL-MTAs were from GBS SNPs potentially illustrating the effectiveness of marker-dense de novo genotyping platforms in overcoming ascertainment bias and providing a more accurate correction for different levels of relatedness in GWAS models. GWAS also detected QTL 'hotspots' for several traits at previously known as well as newly identified genomic locations. Due to the current study exploiting genome-wide genotyping and de novo SNP discovery simultaneously on a large tetraploid panel representing a greater diversity of the cultivated potato gene pool, the reported sequence-tagged MTAs are likely to have higher transferability across a wider range of potato germplasm and increased utility for expediting genomics-assisted breeding for the several complex traits studied.

Rust diseases, including leaf rust, stripe/yellow rust, and stem rust, significantly impact wheat (Triticum aestivum L.) yields, causing substantial economic losses every year. Breeding and deployment of cultivars with genetic resistance is the most effective and sustainable approach to control these diseases. The genetic toolkit for wheat breeders to select for rust resistance has rapidly expanded with a multitude of genetic loci identified using the latest advances in genomics, mapping and cloning strategies. The goal of this review was to establish a wheat genome atlas that provides a comprehensive summary of reported loci associated with rust resistance. Our atlas provides a summary of mapped quantitative trait loci (QTL) and characterised genes for the three rusts from 170 publications over the past two decades. A total of 920 QTL or resistance genes were positioned across the 21 chromosomes of wheat based on the latest wheat reference genome (IWGSC RefSeq v2.1). Interestingly, 26 genomic regions contained multiple rust loci suggesting they could have pleiotropic effects on two or more rust diseases. We discuss a range of strategies to exploit this wealth of genetic information to efficiently utilise sources of resistance, including genomic information to stack desirable and multiple QTL to develop wheat cultivars with enhanced resistance to rust disease.

Key message: Three QTLs associated with low-temperature tolerance were identified by genome-wide association analysis, and 15 candidate genes were identified by haplotype analysis and gene expression analyses. Low temperature is a critical factor affecting the geographical distribution, growth, development, and yield of soybeans, with cold stress during seed germination leading to substantial productivity loss. In this study, an association panel comprising 260 soybean accessions was evaluated for four germination traits and four cold tolerance index traits, revealing extensive variation in cold tolerance. Genome-wide association study (GWAS) identified 10 quantitative trait nucleotides (QTNs) associated with cold tolerance, utilizing 30,799 single nucleotide polymorphisms (SNPs) and four GWAS models. Linkage disequilibrium (LD) analysis positioned these QTNs within three cold-tolerance quantitative trait loci (QTL) and, with QTL19-1, was positioned by three multi-locus models, underscoring its importance as a key QTL. Integrative haplotype analysis, supplemented by transcriptome analysis, uncovered 15 candidate genes. The haplotypes within the genes Glyma.18G044200, Glyma.18G044300, Glyma.18G044900, Glyma.18G045100, Glyma.19G222500, and Glyma.19G222600 exhibited significant phenotypic variations, with differential expression in materials with varying cold tolerance. The QTNs and candidate genes identified in this study offer substantial potential for marker-assisted selection and gene editing in breeding cold-tolerant soybeans, providing valuable insights into the genetic mechanisms underlying cold tolerance during soybean germination.