Search Results (144)

Background: Genetic diversity and genetic differentiation between Gossypium hirsutum-Gossypium barbadense introgression lines (ILs) and early-maturing upland cotton lines are critical for resolving the core breeding contradiction in Xinjiang cotton region: narrow genetic basis of early-maturing cultivars and late maturity of ILs with superior fiber quality. Xinjiang is one of the major cotton-producing regions in China, and breeding high-quality early-maturing upland cotton adapted to local ecological conditions is essential for improving cotton yield and quality. However, the genetic relationship and differentiation between the two types of cotton germplasm remain unclear, which hinders the efficient utilization of germplasm resources in breeding. Therefore, this study aimed to clarify the genetic diversity and differentiation between the two germplasm types and identify key candidate loci related to early maturity and fiber quality, providing support for cotton breeding. Results: Here, we used a 40K Single Nucleotide Polymorphism chip to genotype core cotton germplasm in northern Xinjiang, and analyzed their population structure, genetic diversity and functional SNP loci associated with early maturity and fiber quality. The tested materials were clearly divided into two subgroups (ILs and early-maturing lines). Genetic diversity analysis revealed a significantly narrow genetic basis in the early-maturing subgroup, while the IL subgroup had higher genetic diversity. Specifically, the early-maturing subgroup showed lower nucleotide diversity and polymorphism information content compared with the IL subgroup, indicating that the genetic variation of early-maturing cotton germplasm in northern Xinjiang is relatively limited. A total of 25 non-synonymous SNPs were identified, among which the c.A613G:p.T205A mutation in GH_D09G1484 (mRNA-decapping enzyme 1, DCP1) was a characteristic variation of early-maturing cotton, and a possible non-synonymous mutation in GH_A09G2400 (Heat shock transcription factor A6b, HSFA6B) was associated with fiber development. These two candidate genes were annotated to be involved in plant growth and development, further supporting their potential roles in regulating cotton early maturity and fiber quality. Conclusions: This study clarified the genetic differentiation between the two types of germplasms and identified key candidate loci for early maturity and fiber quality, providing precise molecular markers and theoretical support for breeding high-quality early-maturing upland cotton adapted to Xinjiang’s ecological conditions. The results also highlight the value of Gossypium hirsutum–Gossypium barbadense introgression lines in enriching the genetic basis of early-maturing cotton, which can be further utilized to solve the core breeding contradiction in the Xinjiang cotton region. Full article

Background/Objectives: Intramuscular fat deposition is a key determinant of beef quality in Japanese Black cattle, and the fat area ratio of the rib eye (FAR) is highly correlated with Beef Marbling Standard scores. Methods: To identify genetic variants underlying variation in the FAR, we conducted a genome-wide association study (GWAS) followed by whole-genome sequence–based fine mapping in a Hyogo Japanese Black population (n = 432). Animals were genotyped using the Illumina BovineSNP50v3 BeadChip, and association analysis was performed using residuals derived from a linear mixed model accounting for fixed and random effects. Results: A significant association signal was detected on BTA17 (λ = 1.09), with the top single nucleotide polymorphism (SNP) located at 17:72,329,662 (p = 3.60 × 10⁻⁶). To refine the candidate region, we analyzed whole-genome resequencing data from 42 Hyogo Japanese Black cattle and identified a distinct linkage disequilibrium (LD) block spanning 71–74 Mbp on BTA17. Among 4292 variants within genes showing LD (r² ≥ 0.1) with the top SNP, 96 variants with strong LD and predicted functional effects were selected for validation. Genotyping in the Hyogo population revealed that a missense variant in gamma-glutamyltransferase 1 (GGT1) (c.589G>A, p.Asp197Asn) showed the strongest association with FAR (p = 3.89 × 10⁻⁶). A 5′UTR variant in GGT1 (c. −256G>T) and a missense variant in solute carrier family 5 member 1 (SLC5A1) (c.32C>T, p.Thr11Met) also exhibited significant associations and strong LD with the top SNP (r² > 0.7). GGT1 is involved in glutathione metabolism, whereas SLC5A1 encodes a sodium–glucose cotransporter implicated in nutrient sensing and metabolic regulation. Conclusions: Although functional validation is required, these variants represent strong positional and biological candidates underlying the BTA17 quantitative trait loci (QTL). The identified polymorphisms may provide useful molecular markers for optimizing genetic improvement of marbling-related traits within the Hyogo Japanese Black population. Full article

Genomic improvement and sustainable breeding of Mediterranean buffalo are hampered by the lack of breed-specific genomic resources compared with bovine. To address this gap, we aimed to identify a comprehensive set of high-confidence single-nucleotide polymorphisms (SNPs) in Mediterranean buffalo and evaluate their informativeness across other buffalo populations. A total of 58 whole-genome sequencing samples, from three different sets, were merged through the integration of short- and long-read sequencing technologies. Variants, both unique and shared among datasets, were identified using a combination of bioinformatic tools to increase the reliability of the dataset. From these, over 11 million high-confidence biallelic SNPs were identified in the Mediterranean breed. The same SNPs were also tested in additional populations (other rivers and swamps) to evaluate their polymorphism and missingness. These results provide a robust genomic resource for Mediterranean buffalo, overcoming the limitations of bovine-derived genotyping tools available today. The identified SNPs dataset lays the basis for the development of a breed-specific SNP array, providing a dense and informative set of markers that could support cost-effective SNP chip development compared with existing arrays and sequencing technologies. This resource will facilitate more accurate genomic selection, precision breeding, and the conservation of genetic diversity in the Mediterranean buffalo population. Full article

Background: Machine learning (ML) holds great promise for genomic breeding value prediction in livestock and poultry, yet its application in layer breeding remains limited. Methods: In this study, we used whole-genome resequencing data from 834 Wenshui Luhua Green-Shelled (WLGS) laying hens to predict genomic breeding values for eight egg production and egg quality traits using multilayer perceptron (MLP), random forest (RF), and genomic best linear unbiased prediction (GBLUP). Model performance was evaluated via 10-fold cross-validation, and the effects of data type and single nucleotide polymorphism (SNP) density were examined. Results: Heritability analysis indicated moderate heritability for egg number (EN) at 0.327. Egg weight-related traits (EW-30W, EW-40W, and EHD-40W) exhibited high heritability (0.570–0.631), while eggshell strength (ESS-40W) and thickness (EST-40W) showed moderate heritability at 0.228 and 0.220, respectively. Model comparisons revealed that RF performed best for egg shape index (ESI-30W, 0.395) and most egg quality traits, whereas GBLUP yielded optimal results for egg weight traits, achieving prediction accuracies of 0.392 for EW-30W and 0.432 for EW-40W. Whole-genome resequencing data consistently outperformed 50K chip data across all models, with GBLUP improving EW-40W prediction accuracy by 24.9%. SNP density analysis further showed that GBLUP remained stable under low-density conditions, while MLP and RF progressively improved with increasing density, with RF demonstrating the most pronounced advantage at high densities. Conclusions: In summary, the GBLUP model is suitable for traits with high heritability and low-density marker scenarios, while the RF model demonstrates significant predictive advantages for egg production and specific egg quality traits under high-density conditions. This study provides scientific basis for model selection in the genomic selection program for laying hens. Full article

This study developed a 60K single-nucleotide polymorphism (SNP) liquid-phase chip (‘Shenxin I’) based on genotyping by target sequencing (GBTS) technology. The chip was used to genotype 1451 individuals spanning five conserved local pig breeds: Fengjing (FJ), Meishan (MMS), Pudong White (PD), Shaowutou (SW), and Shanghai White (SHW), and newborn purebred Meishan offspring (MMS_New). The study assessed the genetic diversity, population structure, and genomic breed composition (GBC) of these breeds. The GBC analysis provided insights into genomic introgression within admixed individuals. Results indicate that PD and FJ breeds exhibited the higher fraction of the genome covered by runs of homozygosity (F_ROH) and slower linkage disequilibrium (LD) decay rate, suggesting higher genetic inbreeding level in these two breeds. The study conducted genetic distance of identity-by-state (IBS) analysis and molecular pedigree construction for the MMS population. Subsequently, purebred mating was implemented by selecting boars from different pedigrees to mate with sows and excluding individuals with high inbreeding coefficients from the breeding program. This resulted in a significant reduction in the overall inbreeding level of the born progeny and an increase in genetic diversity compared to the original population. Consequently, the study concludes that utilizing liquid-phase chip technology for genotyping, constructing molecular pedigrees, and optimizing mating combinations in small populations of locally conserved pig breeds contributes to enhancing the conservation effectiveness. Full article

In this study, three point mutations of EGFR relevant to lung cancer therapy are detected. Mutated EGFR is the target of a therapy for non-small cell lung cancer (NSCLC) using tyrosine kinase inhibitors (TKIs) as treatment drugs. Background/Objectives: Point mutations in exon 21 (L858R and L861Q) of the EGFR gene are TKI-sensitive; however, mutations in exon 20 (T790M) are TKI-resistant. Therefore, a fast detection method that classifies an NSCLC patient to be drug sensitive or drug resistant is highly clinically relevant. Methods: Probes were designed to detect three point mutations in genomic samples based on DNA hybridization on a solid surface. A method has been developed to detect single nucleotide polymorphism (SNP) for these mutation detections in the 16-channel nanobioarray chip. The wash by gold-nanoparticles (AuNP) was used to assist the differentiation detection. Results: The gold nanoparticle-assisted wash method has enhanced differentiation between WT and mutated sequences relevant to the EGFR sensitivity to tyrosine kinase inhibitors. Conclusions: The WT and mutated sequences (T790M, L858R and L861Q) in genomic samples were successfully differentiated from each other. Full article

Background: Osteoporosis is highly prevalent in postmenopausal women, yet genome-wide association studies often miss disease-relevant variants because of incomplete single nucleotide polymorphism (SNP) coverage and platform-specific limitations. We aimed to identify genetic contributors to osteoporosis risk by integrating two exome-based genotyping platforms with multilayer analytic approaches. Methods: We analyzed extreme osteoporosis phenotypes in Korean postmenopausal women from the Korean Genome and Epidemiology Study (KoGES) Ansan–Anseong cohorts using the Illumina Infinium HumanExome BeadChip and the Affymetrix Axiom Exome Array. After standard quality control, single-SNP logistic regression, cross-platform overlap analysis, and three machine-learning models were applied. Predicted functional impact was evaluated using multiple in silico algorithms and conservation scores. Finally, datasets from both platforms were merged, and cross-platform linkage disequilibrium (LD) blocks were defined to identify loci containing SNPs with p < 1 × 10⁻⁴. Results: No overlapped SNP reached genome-wide significance, but rs2076212 in PNPLA3 achieved suggestive significance (p < 1 × 10⁻⁵) only on the Illumina array. Cross-platform analysis identified 111 overlapping SNPs in 70 genes. Integrated machine-learning, in silico, and conservation evidence prioritized ARMS2, CCDC92, NQO1, ZNF510, PTPRB, and DYNC2H1 as candidate genes. LD-block analysis revealed 10 blocks with at least one SNP at p < 1 × 10⁻⁴, including four chromosome 12 loci (NAV2, BICD1, CCDC92, ZNF664) that became apparent only when LD patterns were evaluated jointly across platforms. Conclusions: Combining dual exome arrays with LD-block analysis, machine learning, and functional prediction improved sensitivity for detecting low bone mineral density-related loci and highlighted CCDC92, DYNC2H1, NQO1, and related genes as biologically plausible candidates for future validation. Full article

Carcass weight (CW) is a major determinant of beef yield and market value in Korea, yet the genetic basis of this trait remains largely unexplored in cattle from Jeju Island. In this study, we performed a genome-wide association study (GWAS) using both a mixed linear model (MLM) and the FarmCPU approach, followed by pathway and network analyses to identify loci and biological functions underlying CW variation. A total of 256 Jeju cattle (92 Jeju Black and 164 Jeju Black × Hanwoo crossbreds) were initially sampled. One crossbred sample failed genotyping, leaving 255 animals (92 Jeju Black and 163 crossbreds) for analysis. Animals were genotyped using the Illumina BovineSNP50 v3 BeadChip, and 39,055 high-quality single nucleotide polymorphisms (SNPs) were retained after quality control. The MLM analysis detected no genome-wide significant associations, whereas the FarmCPU analysis identified six significant loci on Bos taurus chromosomes 3, 5, 6, 10, and 13, each explaining 2.55–9.58% of the phenotypic variance. Candidate genes located near these loci included EIF2B3, HECTD3, SOX5, KLF6, PHACTR3, and two uncharacterized protein-coding genes. Functional enrichment analysis identified biologically relevant pathways including lysine degradation, tryptophan metabolism, glycerolipid metabolism, fatty acid biosynthesis, extracellular matrix–receptor interaction, and signaling cascades such as PI3K–Akt and Rap1, although most pathways were not statistically significant after FDR correction. Protein–protein interaction (PPI) network analysis using STRING highlighted modules of signaling, extracellular matrix, and metabolic genes. These clusters suggest that coordinated interactions among these pathways contribute to carcass growth and development. These findings provide new insights into the molecular basis of CW in Jeju Black and Hanwoo × Jeju Black crossbred cattle and identify candidate genes and pathways that may be useful for genomic selection and the sustainable improvement of Jeju Black cattle populations. Full article

Growth and carcass traits are key economic traits in beef cattle production, and identifying their associated genetic markers is crucial for improving breeding efficiency. Charolais cattle, as a superior beef breed, exhibit excellent performance in growth rate and meat production. The aim of this study was to utilize the preferred high-coverage whole-genome resequencing (hcWGS) as a replacement for single nucleotide polymorphism (SNP) chips to identify significant SNPs and candidate genes associated with growth (body weight, body height, cross height, body length, and chest measurement across different growth stages) and carcass traits (live backfat thickness and eye muscle area at 18 months) in 240 Charolais cattle, thereby providing guidance for beef cattle breeding. Through hcWGS (approximately 13× coverage) and quality control, 4,088,633 SNPs were identified and subsequently used for genetic analyses. Through FarmCPU-based genome-wide association studies, 196 potentially significant SNPs associated with growth traits and 29 SNPs with carcass traits were identified. Annotation analyses revealed 353 candidate genes (such as RBM33, KCTD17, PTHLH, RAC2, CHD6, TRDN, WBP1L, TLL2, CH25H, and ST13) linked to growth traits and 26 candidate genes linked to carcass traits (such as CHST11, LRRK2, RIOK2, and INTS10). Additionally, three SNPs (g.8674692C>G, g.54418624G>T, and g.71085551G>A) were validated via polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP), enabling efficient marker-assisted selection. Furthermore, eight SNPs in the Acyl-CoA oxidase 1 (ACOX1) gene were found to be associated with growth and backfat thickness traits. These findings provide valuable preliminary insights into the genetic mechanisms underlying growth and carcass traits in Charolais cattle, facilitating genome-assisted breeding. Full article

Egg components, including weight of yolk, albumen, and eggshell, are economically important traits in poultry breeding and production, and we thus conducted a genome-wide association study (GWAS) for them. We used an F₂ resource population of hens (n = 142) in different periods of laying, obtained by crossing breeds with contrasting phenotypes, and then genotyped them using the Illumina Chicken 60K iSelect BeadChip. Significant associations were found between 33 single nucleotide polymorphisms (SNPs) and yolk weight at 18–28 weeks of age (YW1). Eighty-seven SNPs were associated with thick albumen weight at 18–28 (TAW1) and 29–42 (TAW2) weeks of age. Four SNPs were associated with eggshell weight at 18–28 weeks of age (ESW1). Fifty-three candidate genes were identified in the positions of these SNPs, and seven prioritized candidate genes (PGCs) were revealed in regions where 2–4 SNPs associated with the studied traits were localized. These were as follows: SYTL5 (YW1, TAW1), FRY (TAW1), GABRG3 (YW1, TAW1), ALDH1A3 (YW1), VCL (YW1), HYDIN (YW1), and TIMP4 (TAW1). Allelic variants at the ALDH1A3, VCL, HYDIN, FRY, and TIMP4 loci were associated with higher YW1 and TAW1. These SNPs and PGCs are potential genetic markers for characterizing egg weight parameters and their components in chicken breeding to achieve egg production improvements. Full article

Backgrounds: Objective of this study is to conduct a genome-wide association study (GWAS) of first-parity reproductive traits in Suzi pigs to identify significant single-nucleotide polymorphisms (SNPs) or candidate genes influencing these traits. Methods: This research employed technologies including the Zhongxin 50K SNP chip, simplified genome sequencing, resequencing, and the 100K SNP liquid chip to perform genome-wide SNP detection on 898 Suzi sows. Genotype data and phenotypic data were combined to do GWAS, gene annotation, and enrichment analysis. Results: Results showed that this study obtained phenotypes of 33 first-parity reproductive traits from 574 sows. GWAS results indicated there were 10 first-parity reproductive traits significantly associated with SNPs, and these traits were AFS, AFF, NNB, NH, NW, NS, NM, ND, PB, and CCN. These 10 traits were significantly associated with 60 SNPs, with 15 (25%) located on chromosome 2-the highest proportion. The SNPs significantly associated with AFS and AFF were largely identical. Genome-wide variance component analysis revealed that among the 10 traits with significantly associated SNPs in GWAS, there were 5 traits that exhibited genome-wide heritability ≥ 0.01. Trait of NM showed the highest heritability (0.65–0.7). These significantly associated SNPs annotated 20 candidate genes, including ADAMTS19, PROP1, ZNF354B, PCARE, LUZP2, VIRMA, EPHA5, AAAS, SLCO3A1-SV2B, KIF18A-BDNF, SERGEF, DYNLRB2, HNF4G, CATSPERD, HSD11B1L, DICER1, RARG, PCDHAC2, KRT79, and HSD17B2. GO analysis of candidate genes revealed that the top three biological processes were cell adhesion, positive regulation of cell projection organization, and positive regulation of neuron projection development. KEGG results showed the top three pathways were inositol phosphate metabolism, glutamatergic synapse, and phosphatidylinositol signaling system. Conclusions: These findings provide a foundation for the reproductive breeding of Suzi pigs and offer new insights into biological breeding in pigs. 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

China has the largest population of pigeons globally, particularly for commercial meat production. Due to insufficient emphasis on bloodline preservation, there is a significant occurrence of breed hybridization, which presents challenges to the differentiation and identification of various pigeon breeds. In this study, a single-nucleotide polymorphism chip was developed to elucidate genomic relationships and genetic diversity among 10 pigeon breeds, encompassing meat, racing, and ornamental varieties. Principal component analysis revealed that this resource population could be classified into three major clusters: homing and Tarim pigeons; the Dianzi (DZ) and Xinjiang Roller (XR) varieties; and commercial meat pigeon breeds, including the Euro-pigeon (EP), Danish King (DK), Silver King (SK), Yellow Carneau (YC), Red Carneau (RC), and Taishen (TS) varieties. Phylogenetic tree analysis indicated that the HP, TR, DZ, and XR varieties clustered into a large group. Of these, the HP and TR groups and the DZ and XR group were closely genetically related. Other meat pigeon varieties clustered into a large group. The genetic relationship between the YC and RC pigeons was intertwined, suggesting that although there were differences in feather color, the genetic backgrounds are similar. The phylogenetic tree results also demonstrated that the DK and SK pigeons had a considerable genetic distance, indicating that although the feather color was similar, the birds belong to two distinct genetic groups. The Pigeon 5 K liquid chip can effectively discriminate among different pigeon populations and provides a method for the identification and evaluation of pigeon germplasm resources, especially for pure breed identification and exploration of new resources. Full article

The Xinglong buffalo is a local swamp buffalo breed adapted to tropical regions in China. To facilitate the protection and utilization of valuable genetic resources, we first developed the breed-specific single nucleotide polymorphism (SNP) liquid-phase chip based on genotyping-by-target-sequencing (GBTS) technology. Whole-genome resequencing data from 143 buffaloes, resulting in 34,757,694 SNPs, were used to identify 1208 breed-specific and 2889 background sites. This chip also incorporates 965 functional SNP sites derived from literature, including SNPs significantly associated with immunity, reproduction, growth, and production. A total of 5062 SNP sites were successfully identified for the development of a 5K liquid-phase genome-wide breeding chip for the Xinglong buffalo. The validation of the chip using 93 samples showed a high detection rate with good repeatability and consistency. In addition, the chip exhibits strong capabilities in clustering and kinship analysis. Results of kinship analysis underscored the importance of a breed-specific chip for the Xinglong buffalo. These results highlight the advantages of a low-density, cost-effective, and breed-specific SNP chip for accurate genotyping. This chip will support future endeavors in molecular breeding, conservation, and genetic evaluation of Xinglong buffalo, thereby facilitating the sustainable utilization of this valuable indigenous germplasm resource. Full article

Background/Objectives: Global maize production is considerably affected by drought aggravated by climate change. No genome-wide association study (GWAS) or candidate gene analysis has been performed using chlorophyll fluorescence (ChlF) and hyperspectral (HS) indices measured in young plants challenged by a water deficit. Our objective was to conduct a GWAS of nine ChlF and HS indices measured in a diversity panel of drought-stressed young plants grown in a controlled environment using a maize single nucleotide polymorphism (SNP) 50k chip. Methods: A total of 165 inbred lines were genotyped using the Infinium Maize50K SNP array and association mapping was carried out using a mixed linear model. Results: The GWAS detected 37 respective SNP markers significantly associated with the maximum quantum yield of the primary photochemistry of a dark-adapted leaf (Phi_Po), the probability that a trapped exciton moves an electron into the electron transport chain further than QA (Psi_o), the normalized difference vegetation index (NDVI), the Zarco–Tejada and Miller Index (ZMI), greenness, modified chlorophyll absorption in reflectance (MCARI), modified chlorophyll absorption in reflectance 1 (MCARI1), and Gitelson and Merzlyak indices 1 and 2 (GM1 and GM2). Conclusions: Our results contribute to a better understanding of the genetic dissection of the ChlF and HS indices, which is directly or indirectly related to physiological processes in maize, supporting the use of HS imaging in the context of maize breeding. Full article