Theoretical and Applied Genetics最新文献

Root traits are fundamental to plant establishment and survival, influencing resource acquisition, anchorage, and stress resilience. In grapevine, a perennial grafted fruit crop, early growth-related traits, such as rooting and grafting success, are crucial for both vineyard establishment and nursery production, which require well-developed rootstock mother vines and grafted plants. An understanding of the genetic variability underlying these traits is therefore important. We investigated the genetic architecture of early growth-related traits in a Vitis berlandieri × V. rupestris mapping population of 449 genotypes, using hardwood cuttings and grafted plants with two scion cultivars: V. vinifera cvs. Cabernet Sauvignon and Riesling. Our results indicate that the genetic control of these traits was polygenic and varied with the method of propagation (cuttings vs grafts), with individual QTLs explaining from 3.1% to 14.1% of the phenotypic variance. In particular, we detected largely non-overlapping genomic regions associated with similar traits across propagation methods and observed rootstock × scion interactions, suggesting an influence of scion genotype on root development. Two overlapping roots number QTLs were identified in grafts with different scions accounted for 7 and 14% of the variance in Cabernet Sauvignon and Riesling, respectively. Our results highlight the challenge of applying marker-assisted selection in rootstock breeding programs, due to the different genetic determinants underlying the same traits across the different propagation methods. Here, we found that QTLs colocalized with genes involved in growth and stress responses. Finally, eight genotypes with root-related performance superior to that of commercial rootstocks were identified, providing promising candidates for further evaluation in grapevine rootstock breeding programs.

The complexity of potato genetics, characterised by tetrasomic inheritance, has contributed to slower genetic gain in potato compared to other major crops. Disease resistance genes, often found in large clusters of highly similar paralogs and alleles, further complicate genetic studies. The H1 resistance locus, introgressed into potato cultivars from Solanum tuberosum ssp. andigena, has been successfully used for over 60 years to control Globodera rostochiensis in Europe. Although previous genetic studies mapped this resistance to chromosome 5, the complete structure of the locus remained elusive. To reduce genomic complexity, we generated a dihaploid of the cultivar 'Athlete', DH4_Athlete, carrying the H1 resistance locus, and produced a phased haplotype representation of the H1 interval using Oxford Nanopore sequencing. Combined with RenSeq-based association genetics, this approach allowed us to reconstruct the entire H1 locus, including recombination points at both the 5' and 3' ends of the interval.

Key message: A new approach is proposed for the use of the genetic markers to manage DUS trials, targeted at individual phenotypic characteristics using genomic prediction, as well for supporting Distinctness decisions. High-performing crop varieties underpin food security. Due to the cost of developing varieties, systems have been established to provide breeders with legal protection for their varieties. In many countries, such protection is afforded by the International Union for the Protection of New Varieties of Plants (UPOV) system. New varieties must be phenotypically Distinct from existing varieties using a set of crop-specific characteristics, as well as Uniform and Stable (DUS). For many crops, DUS assessment is costly as candidates must be compared to many existing varieties in field trials, based on numerous DUS characteristics. The use of genetic markers has long been considered as a potential tool for managing costs of such trials, for example, by identifying existing varieties that need not be compared to candidate varieties. Under UPOV guidance, the use of genetic markers must be reflective of phenotypic differences in DUS characteristics. Within this framework, we propose a new approach for using markers based on the application of genomic prediction, which is used to predict variety differences in individual characteristics. The approach is evaluated with perennial ryegrass and wheat, yielding promising results. Additionally, we propose a novel approach in which genomic prediction is used to refine Distinctness decisions after DUS trials have been run by integrating genetic and trial information. Using perennial ryegrass as an example, we demonstrate that this approach, which respects the primacy of phenotype in DUS testing, could be used to support distinctness decisions, especially for cross-pollinated agricultural crops where Distinctness may be harder to achieve.

Key message: A genome-wide association study using 90 K wheat SNP arrays identified nine QTLs with 38 SNP markers significantly associated with Fusarium head blight resistance in US wheat. Six putative novel QTLs were identified from the US wheat with three for type II resistance, two for low DON and FDK and one for all three traits. Wheat Fusarium head blight (FHB) is a devastating disease of wheat worldwide. Growing FHB-resistant wheat is the most effective and eco-friendly approach to reduce the losses. To identify native FHB resistance quantitative trait loci (QTLs), a population of 201 US winter wheat breeding lines and cultivars were genotyped using 90 K wheat single nucleotide polymorphism (SNP) arrays and phenotyped for the percentage of symptomatic spikelets (PSS) in a spike in three greenhouse experiments, and for PSS, Fusarium damaged kernels (FDK) and deoxynivalenol (DON) content in two field experiments. Genome-wide association studies (GWAS) identified 38 SNPs that were significant for at least two of the three traits or a single trait in at least two experiments on chromosomes 1A, 1D, 2B, 3A, 3B, 4A, 5B and 5D. Among them, QPss.hwwg-1AS, QPss.hwwg-1DS and QPss.hwwg-3AL are likely novel QTLs for reduced PSS from US winter wheat, and QFDon.hwwg-4AL, QFDon.hwwg-5BL and QFDon.hwwg-5DL are novel QTLs for low FDK and DON. Among them, only QFDon.hwwg-5BL had significant effects on all the three FHB traits. Most of these QTLs showed additive effects. Among the tested accessions, hard winter wheat 'T153,' 'T154' and 'OK05128' harboring all resistance marker alleles for low PSS, FDK and DON, therefore, they are good resistant parents for improving FHB resistance.

Key message: High-density linkage analysis using deep resequencing mapped a stable cottonseed oil content QTL qOC-A03-1, leading to the identification of UDP-glycosyltransferase gene GhUGT84A1 as a key regulator of cottonseed oil accumulation via fine mapping. As the main by-products of cottonseed, cottonseed oil and protein have great potential in economic value and edible applications. In this study, a high-density genetic linkage map was constructed with 3478 bin markers via deep resequencing method (14.11 ×) using a recombinant inbred line population. Among the 16 detected quantitative trait loci (QTLs) associated with cottonseed oil content (OC) and protein content (PC) in four environments, we focused on a stable novel QTL qOC-A03-1 responding for both OC and PC traits simultaneously and narrowed down its interval to 190 kb containing 19 genes, subsequently. Based on RNA-seq data of ovules at different developmental stages and other tissues, a UDP-glycosyltransferase gene, GhUGT84A1, showing significant differential expression during the rapid oil accumulation stage and exhibiting three non-synonymous SNPs and a 2-bp deletion causing premature translation termination in ND601 was identified. Heterologous expression in yeast confirmed that overexpression of GhUGT84A1^ND601 could significantly increase the triacylglycerol content. Interestingly, when changing the T^ND601 to A^NDM13 genotype at the 1357^th position of GhUGT84A1^ND601, the triacylglycerol content further increases. However, a 17.83%-33.55% increase in OC was detected in the silenced GhUGT84A1 cotton leaves, and the expression of genes related to fatty acid biosynthesis and metabolic pathways showed significant changes. Our investigations found that GhUGT84A1 might as a negative regulator fine-tune the cottonseed oil accumulation and could provide fundamental insights for comprehensive cotton valorization.

Alcohol dehydrogenase (ADH) is a zinc-binding enzyme responsible for catalyzing the interconversion between ethanol and acetaldehyde, as well as other alcohol and aldehyde pairs, within the ethanol fermentation pathway. This enzyme plays a crucial role in plant adaptation to environmental stressors. However, knowledge regarding the ADH gene family in soybean remains limited. Here, a genome-wide analysis was conducted, leading to the identification of 22 ADH genes in soybean and their classification into five subfamilies based upon phylogenetic relationships. Cis-regulatory element analysis combined with qRT-PCR experiments demonstrated that GmADH genes exhibit significant upregulation on exposure to various abiotic stresses, such as drought, alkaline conditions, and salt stress, as well as to hormonal stimuli. Furthermore, GmADHs display distinct tissue-specific expression patterns. Notably, GmADH13 showed consistent upregulation across multiple stress conditions, suggesting its pivotal role in soybean's salt stress response. Functional analyses revealed that GmADH13 enhances salt tolerance by modulating the reactive oxygen species scavenging system, maintaining redox homeostasis, and stabilizing Na⁺/K⁺ levels within cells, thereby reducing oxidative damage induced by salt stress. The results from transgenic hairy root experiments further support the role of GmADH13 in improving salt tolerance. Collectively, this study expands the current understanding of the ADH gene family's involvement in soybean stress responses and highlights potential genetic targets for enhancing soybean salt tolerance during cultivation.

Maize is a major feed and food crop, yet its kernel protein content remains insufficient to meet nutritional needs. Enhancing protein content is critical for improving feed efficiency and supporting plant-based diets. Although numerous QTLs associated with protein content have been identified, their typically broad confidence intervals and variability across studies make it difficult to pinpoint reliable candidate genes. Therefore, we performed a comprehensive meta-QTL (MQTL) analysis by integrating data from 25 QTL studies, encompassing 258 initial QTLs related to maize kernel protein content. A high-density consensus genetic map was constructed by merging 23 genetic maps and incorporating 19,836 markers across IBM2_2008_Neighbors reference genetic map. A total of 67 MQTLs were identified, each integrating an average of 5 initial QTLs, with their confidence intervals reduced about 2.51-fold on average. Notably, 18 MQTLs had physical intervals shorter than 1 Mb, indicating high mapping precision. To validate the MQTLs, genome-wide association studies (GWAS) on maize protein content were integrated, and 15 MQTLs were colocated with GWAS signals. Further, based on expression patterns and homology analysis across cereal crops, 54 core candidate genes were identified, including Aaap54, Tar3 and EREB133, which their homolog in rice or soybean has been demonstrated to play an important role in regulating protein accumulation. These findings demonstrate the utility of meta-QTL analysis in refining complex trait architecture and provide a valuable foundation for functional genomics studies and the genetic improvement of maize kernel protein content.

Key message: A paralog of Cell Size Regulator (CSR), CSR-like1, underlies the novel fw6.2 QTL in tomato. The gene and locus regulate fruit weight by increasing pericarp cell size and its function on fruit weight appears to be conserved in other crops. Fruit weight is a quantitative trait that was under strong selection during the domestication of fruit and vegetable crops such as tomato (Solanum lycopersicum). While numerous fruit weight QTLs have been identified, only three tomato fruit weight genes have been cloned. In this study, we utilized a genetically diverse tomato panel, the Varitome collection, to identify additional genetic loci that control fruit weight. We mapped and fine mapped two fruit weight QTLs on chromosome 6, fw6.1 and fw6.2, by using Genome Wide Association studies (GWAS) and linkage mapping in bi-parental populations. We identified a member of the Cell Size Regulator family, CSR-like1, as the likely candidate underlying fw6.2. The near isogenic lines (NILs) carrying the derived allele of fw6.2 produced heavier fruits with larger fruit pericarp cells than lines with wildtype (WT) allele. Transgenic downregulation of CSR-like1 led to a decrease in fruit weight and pericarp cells, supporting the role of this gene at the fw6.2 locus. The haplotype analysis implied that the CSR-like1-Derived (CSR-like1-D) allele was selected in the transition from the fully wild S. pimpinellifolium to the earliest S. lycopersicum cerasiforme accessions. Four single nucleotide polymorphisms (SNPs) were identified in the regulatory region of CSR-like1 that were conserved in the accessions carrying CSR-like1-WT and were significantly associated with lower fruit weight and pericarp cell size at the locus. Moreover, a pepper GWAS identified a CSR-like1 ortholog that was associated with fruit weight. Together, our findings established CSR-like1 as a novel fruit weight gene likely conserved in other crops in the Solanaceae family.

Intermediate omics traits, which mediate the effects of genetic variation on phenotypic traits, are increasingly recognized as valuable components of genetic evaluation. In particular, rhizosphere microbiota play a crucial role in plant health and productivity; however, their complex interactions with host genetics remain challenging to model. Although two-step modeling frameworks have been proposed to integrate intermediate omics traits into phenotype prediction, existing approaches do not incorporate nonlinear relationships between different omics layers. To address this, we have proposed a two-step phenotype prediction framework that integrates genomic, rhizosphere microbiome, and metabolome (meta-metabolome) data, while explicitly capturing omics-omics nonlinearities. The first step is to predict meta-metabolome traits from genetic and microbial features, thus effectively isolating them from the environmental noise. In this process, intermediate "proxy" omics traits are generated as general biological information to provide robust models. The second step utilizes this "proxy" to enhance the accuracy of the phenotype prediction. We compared a linear mixed model (Best Linear Unbiased Prediction, BLUP) and a nonlinear model (Random Forest, RF) at each step, as demonstrated through simulations and empirical analysis of a multi-omics soybean dataset in which nonlinear modeling captures intricate omics interactions. Notably, our approach enables phenotype prediction without requiring the original meta-metabolome data used in model training, thereby reducing reliance on costly omics measurements. This framework integrates intermediate omics traits into genomic prediction to improve prediction accuracy and provide solutions for deeper insights into plant-microbiome interactions.

Lesion mimic mutants (LMMs) are ideal for dissecting plant immunity mechanisms. Here, we characterized lm10373, a stable LMM isolated from an EMS-induced library of wheat cultivar AK58. lm10373 developed light-dependent lesion spots on leaves from the late tillering stage, accompanied by programmed cell death (PCD) and reactive oxygen species (ROS) accumulation. Phenotypically, lm10373 showed reduced photosynthetic capacity and yield-related traits, but enhanced powdery mildew resistance at the heading stage. Genetic analysis revealed the lesion trait was controlled by a single semi-dominant nuclear gene, mapped to a 35 Mb interval on chromosome 3B via bulked segregant analysis coupled with exome capture sequencing (BSE-seq). Integrating exome sequencing and transcriptome data, we identified TaWSD1-3B (encoding an O-acyltransferase of the WSD1 family) as the causal gene. A G-to-A mutation (p.Ala79Thr) in its conserved acyltransferase domain introduced a new phosphorylation site, disrupting triacylglycerol biosynthesis. Two independent mutants (lm129, p.Arg207His; lm295, 3'UTR mutation) validated TaWSD1-3B function. Haplotype analysis of 183 wheat accessions identified three TaWSD1-3B haplotypes: Hap1 was associated with higher 1000-grain weight and lower leaf tip necrosis (LTN) severity, making it a favorable allele for breeding. This study characterized a wheat LMM mutant and candidate gene TaWSD1-3B, suggesting a lipid-ROS-PCD pathway regulating immunity, and provides valuable markers for stress-tolerant, high-yield wheat breeding.