Search Results (373)

Yellow rust (YR), caused by Puccinia striiformis f. sp. tritici (Pst), is a global disease infecting wheat that seriously affects the yield and the quality of grains. Wheat breeding line C855 is immune to the mixed Pst isolates CYR32 + CYR33 + CYR34 under field conditions. To identify the Yr-loci carried by C855, in this study, an F₂ population derived from the crossing of C855 with Yannong 999, a YR-sensitive cultivar, was established, and the infection type (IT) of each F₂ individual was estimated. The correlation analysis results show that YR resistance was significantly positively correlated with grain weight and grain size. Using a 120K single-nucleotide polymorphism (SNP) array, the F₂ population was genotyped, and a high-density genetic map covering 21 wheat chromosomes and consisting of 5362 SNP markers was built. Then, five Yr-QTLs on chromosomes 1B, 2A, 2B, and 2D were identified. Of these, the QTL on chromosome 2A, temporarily named QYr.sxau-2A.1, is a major-effect QTL explaining 15.62% of the phenotypic variance. One PCR-based marker SSR2A-14 for QYr.sxau-2A.1 was developed, and the C855 allele of SSR2A-14 corresponded to the stronger Yr resistance. QYr.sxau-2A.1, located in the 228.02~241.58 Mbp physical interval, is different from all the known Yr loci on chromosomes 2A. Within the interval, there are 30 annotated genes, including a nucleotide-binding site and a leucine-rich repeat (NBS-LRR)-encoding gene with the linkage marker NRM2A-16 of QYr.sxau-2A.1. Our results reveal a novel major-effect QYr.sxau-2A.1, which provided resistance to YR and is a molecular marker for wheat breeding. Full article

Leaf rust, a devastating fungal disease caused by Puccinia triticina (Pt), severely impacts wheat quality and yield. Identifying genetic loci for wheat leaf rust resistance, developing molecular markers, and breeding resistant varieties is the most environmentally friendly and economical strategy for disease control. This study utilized a recombinant inbred line (RIL) population of Doumai and Shi4185, combined with the wheat 90 K single nucleotide polymorphisms (SNPs) chip data and maximum disease severity (MDS) of leaf rust from four environments, to identify adult plant resistance (APR) loci through linkage mapping. Additionally, kompetitive allele-specific PCR (KASP) markers suitable for breeding were developed, and genetic effects were validated in a natural population. In this study, 5 quantitative trait loci (QTL) on chromosomes 1B (2), 2A and 7B (2) were identified through inclusive composite interval mapping, and named as QLr.lfnu-1BL1, QLr.lfnu-1BL2, QLr.lfnu-2AL, QLr.lfnu-7BL1 and QLr.lfnu-7BL2, respectively, explaining 4.54–8.91% of the phenotypic variances. The resistance alleles of QLr.lfnu-1BL1 and QLr.lfnu-1BL2 originated from Doumai, while the resistance alleles of QLr.lfnu-2AL, QLr.lfnu-7BL1 and QLr.lfnu-7BL2 came from Shi4185. Among these, QLr.lfnu-1BL2, QLr.lfnu-7BL1 and QLr.lfnu-7BL2 overlapped with previously reported loci, whereas QLr.lfnu-1BL1 and QLr.lfnu-2AL are likely to be novel. Two KASP markers, QLr.lfnu-2AL and QLr.lfnu-7BL, were significantly associated with leaf rust resistance in a diverse panel of 150 wheat varieties mainly from China. Totally, 34 potential candidate genes encoded the NLR proteins, receptor-like kinases, signaling kinases and transcription factors were selected as candidate genes for the resistance loci. These findings will provide stable QTL, available breeding KASP markers and candidate genes, and will accelerate the progresses of wheat leaf rust resistance improvement through marker-assisted selection breeding. Full article

Background: Colorectal cancer (CRC) is significantly associated with multiple metabolic diseases, with plasma metabolites potentially mediating this relationship. This large-scale metabolomics study aims to (1) quantify the genetic correlations and causal effects between 10 metabolic disease-related phenotypes and CRC risk; (2) identify the plasma metabolites mediating these effects; and (3) explore downstream regulatory genes and druggable targets. Methods: Using linkage disequilibrium score regression and two-sample Mendelian randomization, we assessed the causal relationships between each metabolic trait and CRC. A total of 1091 plasma metabolites and 309 metabolite ratios were identified and analyzed for mediating effects by a two-step MR approach. Colocalization analyses evaluated shared genetic loci. The findings were validated in the UK Biobank for metabolite-trait associations. The expression of candidate genes was explored using data from TCGA, GTEx, and GEO. A FADS1-centered protein–protein interaction (PPI) network was constructed via STRING. Results: BMI, waist circumference, basal metabolic rate, insulin resistance and metabolic syndrome exhibited both genetic correlation and causal effects on CRC. Five plasma metabolites—mannonate, the glucose/mannose ratio, plasma free asparagine, 1-linolenoyl-2-linolenoyl-GPC (18:2/18:3), and the mannose/trans-4-hydroxyproline ratio—were identified as shared central mediators. A colocalization analysis showed rs174546 linked CRC and 1-linolenoyl-2-linoleoyl-GPC. Validation in the UK Biobank confirmed the associations between phosphatidylcholine (the lipid class of this metabolite), adiposity measures, and CRC risk. An integrative analysis of TCGA, GTEx, and GEO revealed consistent upregulation of FADS1/2/3 and FEN1 in CRC, with high FADS1 expression predicting a poorer prognosis and showing the distinct cell-type expression in adipose and colon tissue. The PPI network mapping uncovered nine FADS1 interacting proteins targeted by supplements such as α-linolenic acid and eicosapentaenoic acid. Conclusions: This study systematically reveals, for the first time, the shared intermediary plasma metabolites and their regulatory genes in the causal pathway from metabolic diseases to CRC. These findings provide candidate targets for subsequent functional validation and biomarker development. Full article

Analysis of selection signatures in the genomes of farm animals enables the detection of genomic regions affected by selection and contributes to the identification of genes underlying adaptive and productive traits. This research aimed to identify loci under selection pressure and to detect candidate genes in Dzhalgin Merino sheep by performing a comparative genomic analysis with the related Australian Merino and Rambouillet breeds. A total of 293 animals were included in the analysis, comprising Dzhalgin Merino (n = 53), Australian Merino (n = 50), Australian Industry Merino (n = 88), and Rambouillet (n = 102). Whole-genome SNP genotyping data for Dzhalgin Merino were generated within this study, while data for Australian Merino, Australian Industry Merino, and Rambouillet were obtained from the SheepHapMap project. For the purposes of analysis, Australian Merino and Australian Industry Merino were combined into a single group (n = 138). To enhance the reliability of the results, three independent methods were employed to detect selection signatures: the fixation index (FST), analysis of linkage disequilibrium variation (varLD), and the cross-population number of segregating sites by length (xp-nSL). The study showed that Dzhalgin Merino have unique genetic signatures potentially associated with adaptation and productivity, which opens up new opportunities for their selection. The identified genes can become the basis for developing new breeding programs aimed at improving both the productive qualities and the adaptive abilities of the breed. Further research should be aimed at a detailed investigation of gene structure within loci under selection pressure and at clarifying the mechanisms by which these genes influence animal phenotypes. A total of 185 genes were identified within genomic regions exhibiting selection signatures. Among these, particular attention was given to EPHA6, MLLT3, ROBO1, KIAA0753, MED31, SLC13A5, and ELAVL4, which are involved in biological processes such as growth, development, and reproduction. The identified genes represent potential targets for breeding programs aimed at increasing productivity and adaptive capacity of the breed. Full article

Background/Objectives: The Chinese dwarf cherry (Cerasus humilis) is an endemic shrub fruit tree species in China. Its fruit is flavorful, nutrient-rich, and has considerable research and utilization potential. However, most currently cultivated varieties of C. humilis are highly acidic and primarily used for processing. Consumer-preferred, low-acid, fresh-eating varieties are scarce, limiting industrial development. We used 208 F₁ individuals derived from a cross between high-acid “Nongda 4” and the low-acid “DS-1”. Methods: Restriction site-associated DNA sequencing (RAD-seq) was used to develop single-nucleotide polymorphism (SNP) markers and construct a high-density genetic linkage map. Using two years of fruit titratable acidity phenotypic data, quantitative trait locus (QTL) mapping and candidate gene screening were performed. Results: The genetic map contained 2491 SNP markers, assigned to eight linkage groups. The total genetic distance was 672.71 cm, with an average distance of 0.27 cm between markers, indicating high map quality. QTL mapping identified 18 loci associated with fruit titratable acidity, including 11 major-effect QTLs (logarithm of odds, LOD ≥ 3.5). These major-effect QTLs were concentrated on linkage groups LG2 and LG5, with an explained phenotypic variation of 8.6–31.13%. Two candidate genes were identified within QTL intervals: phosphoester phosphatase and MATE transmembrane transporter. The phosphatase gene’s expression showed a strong correlation with titratable acid content (p < 0.01, correlation coefficient 0.93), suggesting that it plays an important role regulating fruit acidity in C. humilis. Conclusions: This study supports marker-assisted breeding of low-acid, fresh-eating varieties, aiding commercial promotion of C. humilis. Full article

As nutrient allocation trade-offs occur between reproductive and vegetative development in crops, optimizing their partitioning holds promise for improving agricultural productivity and quality. Herein, we characterize the phenotypic diversity of the fruitfulness trait and identify associated genes in tea plants (Camellia sinensis). Over three consecutive years, we monitored the fruitfulness of an F₁ hybrid population (n = 206) derived from crosses of ‘Emei Wenchun’ and ‘Chuanmu 217’. A marked variation was observed in the yield of individual plants, ranging from complete sterility (zero fruits) to exceptionally high fertility (1612 fruits). Using the high-resolution genetic linkage map and the fruitfulness data, we identified a stable major QTL designated as qFN5. To fine-map the underlying gene(s), artificial pollination experiments were conducted with extreme phenotype individuals (with the highest vs. lowest fruit numbers). Bulked segregant RNA sequencing (BSR-Seq) with ovules collected at two and seven days post-pollination (DPP) identified the genomic intervals that exhibit a high degree of overlap with qFN5. Analysis of expression dynamics combined with functional genomics data revealed a prominent candidate gene, CsETR2 (TGY048509), which encodes an ethylene receptor protein. When CsETR2 was overexpressed in Arabidopsis thaliana, the transgenic lines exhibited significantly decreased reproductive performance relative to the wild-type plants. Relative to the wild type, the transgenic lines exhibited a significant decline in several key traits: the number of effective panicles decreased by 72.5%, the seed setting rate dropped by 67.7%, and the silique length shortened by 38%. These findings demonstrate its role in regulating plant fruitfulness. Furthermore, yeast one-hybrid and dual-luciferase assays verified that CsMYB15 (TGY110225) directly binds to the CsETR2 promoter, thus repressing its transcription. In summary, our findings expand the understanding of genetic regulation underlying fruitfulness in tea plants and provide candidate target loci for breeding. Full article

Background/Objectives: Leaf sheath hairiness (LSH) is an adaptive trait in wheat that improves tolerance to biotic and abiotic stresses. Although trichome development has been extensively studied in model plants, the genetic basis of LSH in Triticeae crops remains poorly defined. Methods: In this study, the inheritance and genetic architecture of LSH were investigated. Two F₂ populations were used, derived from crosses between the glabrous lines ‘Shumai 830’ and ‘Shumai 2262’ and the hairy line ‘Zhongkelanmai 1’. BSA-seq was combined with KASP marker genotyping to map and refine the trait locus. Candidate genes were evaluated through comparative genomics; sequence variation; and subcellular localization prediction. Results: Phenotypic evaluation revealed that LSH is a dominant trait, segregating at a 3:1 ratio in F₂ populations. BSA-seq identified a major locus, QLsh.cwnu-4D, on chromosome 4DL. Fine mapping with KASP markers refined this region to a 1.67 Mb interval overlapping a 530 kb trichome-associated linkage disequilibrium block in Aegilops tauschii. Within this interval, TaSAIN1-4D, a salt-inducible protein unique to Triticeae, was identified as the strongest candidate gene. Extensive sequence variation among alleles (TaSAIN1-4Da; TaSAIN1-4Db; TaSAIN1-4Dc), including large insertions and multiple SNPs, indicated potential functional diversification. Predicted nuclear localization of TaSAIN1-4D supports a role in trichome regulation and stress adaptation. The co-dominant KASP marker K-cwnu-4D-502238348 was tightly linked to LSH and cosegregated perfectly, making it a reliable tool for marker-assisted selection. Conclusions: This study clarifies the genetic architecture of leaf sheath hairiness in wheat and identifies TaSAIN1-4D as a likely regulator. These findings provide a practical marker-assisted selection tool that can accelerate the development of improved wheat varieties with desirable leaf surface traits. Full article

Red epicarp in pears is an important trait for breeding. Exploring the genes regulating pear anthocyanin synthesis and developing molecular markers associated with these traits are important for obtaining new varieties of red pears. We performed whole-genome resequencing (WGS) on 127 ‘Yuluxiang (Pyrus bretschneideri)’ × ‘Xianghongli (Pyrus communis)’ F1 populations and identified a total of 510,179 single-nucleotide polymorphism (SNP) sites in the population. In total, 1972 bins were screened to form a high-density genetic map with a total map length of 815.507 cM, covering 17 linkage groups with an average genetic distance of 0.414 cM between markers. Three red skin quantitative trait loci (QTLs), located on LG4 and LG5, that explained 18.7% of the phenotypic variance, were detected. The QTL intervals contained 1658 genes, including 94 transcription factors (TF), subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Four key candidate genes (Pspp.Chr05.01969, Pspp.Chr05.01908, Pspp.Chr05.02419, and Pspp.Chr04.01087) that may play a role in promoting pear anthocyanin synthesis were screened and identified by a quantitative polymerase chain reaction (qPCR). Overall, our study deepens our understanding of the genetics of red peel traits in pears and accelerates pear breeding. Full article

As the primary harvested organ, fruit size and weight hold significant economic importance during tomato production. Therefore, elucidating the genetic mechanisms underlying fruit size and weight is of considerable agronomic value. In this study, the Solanum pimpinellifolium introgression lines were constructed with “LA2093” as the donor and “Jina” as the recipient, and a genetic linkage map was constructed. Preliminary QTL mapping was conducted using four fruit-related traits: single fruit weight, fruit diameter, fruit length, and fruit shape index. A total of 10 QTLs were identified, including one for single fruit weight (qFw-3), five for fruit diameter (qFtd-3-1, qFtd-3-2, qFtd-4, qFtd-7, and qFtd-12), two for fruit length (qFl-3 and qFl-11), and two for fruit shape index (qFsi-2 and qFsi-3). To explore the key regulatory genes of the single fruit weight QTL qFw-3 locus, it was further finely mapped between SSR3-14 and C03M65101. The SSR3-14 and C03M65101 interval contained 57 genes on chromosome 3 (64.68–65.10 Mb) in the reference genome. Among these, eight genes, including Solyc03g114830, Solyc03g114870, Solyc03g114880, Solyc03g114890, Solyc03g114900, Solyc03g114910, Solyc03g115200, and Solyc03g115380, were identified as candidate genes involved in regulating fruit weight. These studies provide a basis for future functional validation of key regulatory genes and offer valuable genetic resources for the improvement of fruit size and weight during tomato breeding. Full article

Chimonanthus praecox, a traditional ornamental plant in China, is admired for its ability to bloom during the cold winter season and is recognized as an outstanding woody cut flower. MADS-box genes encode transcription factors essential for plant growth and development, with key functions in regulating flowering time and the formation of floral organs. In this study, 74 MADS-box genes (CpMADS1–CpMADS74) were identified and mapped across 11 chromosomes, with chromosome 1 harboring the highest number (13 genes) and chromosome 3 the fewest (3 genes). Physicochemical property analysis revealed that all CpMADS proteins are hydrophilic and predominantly nuclear-localized. Phylogenetic analysis classified these genes into Type I and Type II subfamilies, highlighting a clear divergence in domain structure. Eighty simple sequence repeat (SSR) loci were detected, with dinucleotide repeats being the most abundant, and the majority located in Type II MADS genes. From 23 C. praecox samples, 10 polymorphic SSR markers were successfully developed and PCR-validated, enabling a cluster analysis that grouped these cultivars into three distinct clusters. This study offers significant insights into the regulation of flowering, floral organ development, genetic linkage map construction, and the application of marker-assisted selection in C. praecox. Full article

Disease resistance is one of the most important target traits for sugarcane genetic improvement. Sugarcane brown stripe (SBS) caused by Helminthosporium stenospilum is one of the most destructive foliar diseases, which not only reduces harvest cane yield but also sugar content. This study aimed to identify quantitative trait loci (QTL) and candidate genes associated with SBS resistance. Here, the phenotypic investigation in six field habitats showed a continuous normal distribution, revealing that the SBS resistance trait is a quantitative trait. Two high-density linkage maps based on the single-dose markers calling from the Axiom Sugarcane100K SNP chip were constructed for the dominant sugarcane cultivars YT93-159 (SBS-resistant) and ROC22 (SBS-susceptible) with a density of 2.53 cM and 2.54 cM per SNP marker, and mapped on 87 linkage groups (LGs) and 80 LGs covering 3069.45 cM and 1490.34 cM of genetic distance, respectively. A total of 32 QTL associated with SBS resistance were detected by QTL mapping, which explained 3.73–11.64% of the phenotypic variation, and the total phenotypic variance explained (PVE) in YT93-159 and ROC22 was 107.44% and 79.09%, respectively. Among these QTL, four repeatedly detected QTL (qSBS-Y38-1, qSBS-Y38-2, qSBS-R8, and qSBS-R46) were considered stable QTL. Meanwhile, two major QTL, qSBS-Y38 and qSBS-R46, could account for 11.47% and 11.64% of the PVE, respectively. Twenty-five disease resistance candidate genes were screened by searching these four stable QTL regions in their corresponding intervals, of which Soffic.01G0010840-3C (PR3) and Soffic.09G0017520-1P (DND2) were significantly up-regulated in YT93-159 by qRT-PCR, while Soffic.01G0040620-1P (EDR2) was significantly up-regulated in ROC22. These results will provide valuable insights for future studies on sugarcane breeding in combating this disease. Full article

Cotton fiber initiation determines the fiber yield, yet the genetic basis underlying lint and fuzz initiation has still not been fully uncovered. Here, map-based cloning was carried out to identify the fiberless mutant genes derived from a cross between Gossypium hirsutum acc. WT and a natural fiberless mutant, fbl_SHZ. The 12:3:1 segregation ratio in F₂ populations (including 1848 and 3100 individuals that were developed in 2016 and 2018, respectively) revealed dominant epistasis, with the fuzz gene exerting dominance over the lint gene. Genetic linkage analysis revealed that GhMYB25like_A12 controls fuzz fiber initiation, while both GhMYB25like_A12 and GhMYB25like_D12 regulate lint fiber development. Sequencing analyses showed that the fbl_SHZ mutant exhibited a K104M mutation in the R2R3 domain of GhMYB25like_A12 and a transposable element insertion in GhMYB25like_D12, leading to fiberless seeds. Knockout of GhMYB25like_A12 produced fuzzless seeds, knockout of GhMYB25like_D12 led to no obvious change in seeds, and knockout of both (GhMYB25like_A12&D12) resulted in fiberless seeds. The 12:3:1 ratio reappeared in the F₂ population developed from the GhMYB25like_A12&D12 mutated plants as female and Jin668 as the male, which further confirmed the genetic interaction observed in fbl_SHZ. RNA-seq analysis revealed that GhMYB25like regulates cotton fiber initiation through multiple pathways, especially fatty acid metabolism. This study elucidates the key genes and their genetic interaction mechanisms governing cotton fiber initiation, providing a theoretical foundation for genetic improvement of cotton fiber traits. Full article

Soybeans are a primary source of plant-based protein, with seeds containing approximately 40% protein—a key quality trait. Selecting superior hybrid combinations and managing progeny effectively are crucial for developing high-protein soybean varieties. Using a recombinant inbred line population (RIL3613) derived from Dongnong L13 × Heihe 36 and its previously constructed high-density genetic linkage map, QTLs and QTL × environment interactions (QEIs) associated with seed protein content (SPC) were identified through the bi-parental population (BIP) model and multi-environment trials (MET) model in QTL IciMapping v4.2. Candidate genes were then predicted via sequence alignment and haplotype analysis between the parents. Finally, simulated breeding was conducted using the B4L function in the In Silico Breeding (ISB) module of the Blib platform to determine optimal breeding strategies across diverse environments. The analysis identified 19 QTLs associated with SPC and 97 QEIs linked to SPC. These QTLs collectively explained 84.442% of the phenotypic variance, with four QTLs exhibiting significant contributions. A key candidate gene, Glyma.12G231400, associated with soybean SPC, was predicted within the 38,995,090–39,293,825 bp interval on chromosome 12. Across 11 environments, three to six optimal breeding schemes were selected, all employing modified pedigree selection. These findings enhance our understanding of the genetic basis of soybean protein formation and provide technological support for molecular breeding for seed quality improvement. Full article

Soybean frogeye leaf spot (FLS) disease has been reported globally and is caused by the fungus Cercospora sojina, which affects the growth, seed yield, and quality of soybean. Among the 15 physiological microspecies of C. sojina soybean in China, Race 7 is one of the main pathogenic microspecies. A few genes are involved in resistance to FLS, and they cannot meet the need to design molecular breeding methods for disease resistance. In this study, a soybean recombinant inbred line (RIL3613) population and a germplasm resource (GP) population were planted at two sites, Acheng (AC) and Xiangyang (XY). Phenotypic data on the percentage of leaf area diseased (PLAD) in soybean leaves were obtained via image recognition technology after the inoculation of seven physiological species and full onset at the R3 stage. Quantitative trait loci (QTLs) and quantitative trait nucleotides (QTNs) were mapped via linkage analysis and genome-wide association studies (GWASs), respectively. The resistance genes of FLS were subsequently predicted in the linkage disequilibrium region of the collocated QTN. We identified 114 QTLs and 18 QTNs in the RIL3613 and GP populations, respectively. A total of 14 QTN loci were colocalized in the two populations, six of which presented high phenotypic contributions. Through haplotype–phenotype association analysis and expression quantification, three genes (Glyma.06G300100, Glyma.06G300600, and Glyma.13G172300) located near molecular markers AX-90524088 and AX-90437152 (QTNs) are associated with FLS Chinese Race 7, identifying them as potential candidate resistance genes. These results provide a theoretical basis for the genetic mining of soybean antigray spot No. 7 physiological species. These findings also provide a theoretical basis for understanding the genetic mechanism underlying FLS resistance in soybeans. Full article

The optimal exploitation of genetic variability is essential for the success of breeding programs and for identifying quantitative trait loci (QTLs) in genetic association studies. These benefit from populations with a high number of individuals; however, they are expensive since extensive plant maintenance, characterization, and evaluation are required. Core collections offer a practical solution by reducing the number of individuals while representing the original diversity of the population. This study aimed to construct a core collection for Japanese plum to serve as pre-breeding material and enable genetic association studies for traits that are difficult to evaluate. Starting from a population of 1062 individuals genotyped by sequencing, genetic distance and allele coverage metrics were applied to construct several core collections. Genetic parameters and phenotype distribution comparisons allowed for the selection of a core collection of 108 individuals that maximized genetic variability while representative of the original population, confirmed by linkage disequilibrium and population structure analyses. Its usefulness was validated by successfully mapping flowering and maturity dates through marker–trait association. The core collection constructed here will help in the study of fruit quality traits and biotic and abiotic responses, ultimately generating molecular markers to assist the crop’s molecular breeding. Full article