Search Results (2,040)

Reproductive efficiency is a key determinant of sheep productivity, yet Hetian sheep remain limited by relatively low fecundity despite their adaptability to harsh environments. The inhibitor of DNA binding 2 (ID2) gene is known to regulate cell proliferation and differentiation, but its specific role in sheep reproduction is not well understood. This study aimed to characterize the ID2 gene in Hetian sheep and to assess its functional association with ovarian granulosa cells and litter size. The coding sequence of ovine ID2 was cloned and analyzed using bioinformatics tools. Tissue-specific expression patterns were measured by quantitative PCR at different pubertal stages. A total of 157 ewes were genotyped to identify single-nucleotide polymorphisms (SNPs) and their association with litter size. Functional studies were performed by lentiviral overexpression of ID2 in granulosa cells, with effects evaluated using CCK-8 proliferation assays, ELISA for hormone secretion, and RT-qPCR for related gene expression. ID2 was highly expressed in the ovary, particularly during puberty. Four SNPs (g.18202368 A>T, g.18202372 G>A, g.18202431 G>C, g.18202472 G>C) were significantly associated with increased litter size. Overexpression of ID2 promoted granulosa cell proliferation, increased progesterone, decreased estradiol, and altered expression of key genes in the TGF-β/BMP-SMAD signaling pathway. The ID2 gene plays a crucial role in ovarian function and reproductive regulation in Hetian sheep. Its polymorphisms and functional impact on granulosa cells suggest that ID2 is a promising candidate gene for marker-assisted selection to improve reproductive efficiency in sheep. Full article

Upon an organism’s death, enzymatic DNA repair ceases, exposing the genome to destructive factors such as free cellular nucleases and proliferating microorganisms, which can cause DNA loss. DNA preservation is highly dependent on environmental conditions, and less favorable environments accelerate degradation. Despite this, advanced extraction and analytical methods now enable the study of poorly preserved and degraded DNA. DNA typing is a foundation of forensic genomics, enabling the identification of individuals and the individualization of biological evidence through the generation of unique genetic profiles. Although DNA is relatively stable, environmental exposure initiates its degradation into progressively shorter fragments, complicating analysis. The extent of DNA preservation in biological evidence depends on numerous factors, and this review focuses on the environmental factors—including temperature, humidity, ultraviolet radiation, pH, chemical agents, and microbial activity—as the most influential variables. In samples with degraded DNA, the maximum amplicon length achievable through polymerase chain reaction (PCR) is inherently limited. This review discusses genetic markers and analytical strategies improvements that enable the examination of highly degraded samples, particularly when conventional short tandem repeat (STR) typing fails. In these situations, successful identification requires targeting short DNA fragments, which are more likely to persist. Single-nucleotide polymorphisms (SNPs) are a valuable alternative, as their high allelic variability and short amplicon requirements make them more amenable to amplification from fragmented templates than STRs. Advances in next-generation sequencing (NGS) technologies have further enhanced this capacity by enabling high-resolution SNP profiling, thereby improving outcomes in challenging forensic cases. Full article

We evaluated four candidate SNPs (GC-NPFFR2 rs137147462, GC-NPFFR2 rs109452259, BRCA1 rs134817801, and DGAT1 p.K232A) previously reported in relation to mastitis or milk production traits, using 10,729 test-day phenotypic records collected over 10 years from 269 Japanese Holstein cows (Bos taurus) enrolled in the national Dairy Herd Improvement (DHI) program. Linear mixed models were used to estimate genotypic effects on somatic cell score (SCS) and to test multiple inheritance models. To assess clinical relevance, mastitis severity was further analyzed using categories defined by somatic cell counts (SCC). Among the SNPs tested, GC-NPFFR2 rs137147462 showed the clearest and most consistent association with SCS under a recessive model, with GG cows exhibiting higher SCS throughout lactation. Ordinal logistic regression confirmed a higher probability of progression to severe mastitis in GG cows. DGAT1 p.K232A showed additive effects, with the A allele increasing milk yield while lowering fat and protein percentages. AA cows also showed higher SCS under a modest recessive effect. BRCA1 rs134817801 and GC-NPFFR2 rs109452259 had minimal effects. These findings support GC-NPFFR2 rs137147462 as a promising marker for mastitis resistance and indicate the importance of considering not only additive but also recessive genetic models in genomic selection strategies. Full article

Background: Maize, crucial for food, feed, and industry, is a model for genetic and breeding research. Kernel traits directly affect maize yield. This study developed the eBSRmap method to simplify gene cloning related to maize kernel traits. Methods: The eBSRmap method constructs a maize EMS mutant population, then conducts RNA-seq on pooled mutant and wild-type samples to identify SNP markers and map candidate genes for kernel trait mutations. Results: Applied to a maize EMS mutant population, eBSRmap identified candidate genes for twenty kernel trait mutants, successfully mapped twelve, and eight were confirmed by co-segregation analysis (success rate: 40%). The identified genes showed mutations like missense and stop-gained, related to phenotypes such as small, shrunk, and defective kernels. Conclusions: eBSRmap offers a fast and affordable way to map genes and identify candidate genes in a large-scale mutant population, aiding the understanding of gene functions in maize. The identified candidate genes can be further validated by functional analysis, which is significant for maize breeding and genetic improvement. Full article

Malaria is a major public health challenge in low- and middle-income countries with significant socio-economic impacts. While chemotherapy has greatly contributed to malaria control, the widespread emergence of resistance to antimalarial drugs threatens progress towards elimination goals. In parallel, the recent rollout of the RTS,S/AS01 and R21/Matrix-M malaria vaccine—targeting the Plasmodium falciparum circumsporozoite protein (CSP)—offers a new prevention tool but may be influenced by parasite genetic diversity. This study investigated the genetic architecture of Plasmodium falciparum circulating in a community in the Southwest Region of Cameroon. Seventy-two blood samples were analyzed using targeted Oxford Nanopore sequencing of pfcrt, pfmdr1, pfdhfr, pfdhps, pfkelch13 and pfcsp genes. We observed a high prevalence of pfdhfr mutations (98.6% N51I, 98.6% C59R, 97.7% S108N) and pfmdr1 Y184F (76.1%) mutation. Mutations in pfdhps (54.2% S436A, 2.8% A437G, 38.9% A581G) were also observed. No WHO-validated pfkelch13 artemisinin resistance markers were found; however, K189T (63.4%) and R255K (4.2%) variants were detected. Nineteen non-synonymous SNPs were identified in pfcsp, reflecting natural background variations as vaccination status was not known. These findings support the continued use of artemisinin-based combination therapies and underscores the need for sustained molecular surveillance of both antimalarial drug resistance and vaccine-related polymorphisms, to inform malaria control strategies. Full article

Lycium ruthenicum Murr. (Black goji), a medicinal and economically valuable crop rich in bioactive compounds, remains genomically understudied despite its expanding cultivation. To overcome limitations of traditional markers in genetic diversity analysis and molecular breeding, we employed specific-locus amplified fragment sequencing (SLAF-seq) to develop genome-wide SNP markers and elucidate the genetic structure of 213 L. ruthenicum accessions from natural and cultivated populations in Alxa, China. We identified 827,630 SLAF tags and 33,121 high-quality SNPs uniformly distributed across 12 chromosomes, establishing the first high-density SNP database for this species. Population genetic analyses revealed three distinct genetic clusters with <60% geographic origin consistency, indicating weakened isolation due to anthropogenic germplasm exchange. The Qinghai Nuomuhong population exhibited the highest genetic diversity (Nei’s index = 0.253; Shannon’s index = 0.352), while low overall polymorphism (average PIC = 0.183) likely reflects SNP biallelic limitations and domestication bottlenecks. Notably, SNP-based clustering showed <40% concordance with phenotypic trait clustering (31 traits), underscoring environmental plasticity as a key driver of morphological variation. This study provides the first genome-wide SNP resource for L. ruthenicum, enabling marker-assisted breeding and highlighting the need for standardized germplasm management to mitigate genetic erosion. Full article

Stropharia rugosoannulata is a widely cultivated edible fungus with high economic and nutritional value. It is a tetrapolar heterothallic basidiomycete. The development of single nucleotide polymorphism (SNP) markers for mating-type identification holds considerable promise for enhancing breeding efficiency. In our study, one group of test crosses and three-round mating experiments from one parental strain were conducted in order to ascertain the mating type in this species. Segregation distortion in mating types was observed after single-spore isolation, which was deviated from Mendelian inheritance. The monokaryotic strain Q25 was derived from the dikaryotic mycelium S1 of S. rugosoannulata. The genome map of strain Q25 with 48.27 Mb and 14 chromosomes was constructed using genomic, transcriptomic, and high-throughput chromosome conformation capture (Hi-C) sequencing technologies. The locations of mating-type loci were identified using genomic annotation. The mating-type A locus is located in chromosome 1, with the gene sequence of β-fg, HD2, HD1, and MIP. The mating-type B locus is located in chromosome 12. It contains five pheromone receptors and five pheromone precursor genes. Two pairs of highly specific and stable primers were designed based on SNP loci in A and B mating types. A1, A2, B1, and B2 alleles were precisely distinguished with these primers, which were subsequently applied in cultivation experiments. This study lays a foundation for the precise breeding of S. rugosoannulata. Full article

Wool traits such as fiber diameter, fiber length, and greasy fleece yield are economically significant characteristics in sheep breeding programs. Traditional genome-wide association studies (GWAS) have identified relevant genomic regions but often fail to capture the non-linear and polygenic architecture underlying these traits. In this study, we implemented a two-stage machine learning (ML)-based GWAS framework to dissect the genetic basis of wool traits in Central Anatolian Merino sheep. Phenotypic records were collected from 228 animals, genotyped with the Illumina OvineSNP50 BeadChip. In the first stage, feature selection was conducted using LASSO, Ridge Regression, and Elastic Net, generating a consensus SNP panel per trait. In the second stage, association modeling with Random Forest and Support Vector Regression (SVR) identified the most predictive models (R² up to 0.86). Candidate gene annotation highlighted biologically relevant loci: MTHFD2L and EPGN (folate metabolism and keratinocyte proliferation) for fiber diameter; COL5A2, COL3A1, ITFG1, and ELMO1 (extracellular matrix integrity and actin remodeling) for staple length; and FAP, DPP4, PLCH1, and NPTX1 (extracellular matrix remodeling, proteolysis, and sebaceous gland function) for greasy fleece yield. These findings demonstrate the utility of ML-enhanced GWAS pipelines in identifying biologically meaningful markers and propose novel targets for genomic selection strategies to improve wool quality and yield in indigenous sheep populations. Full article

Blueberries (Vaccinium spp.) are valued for their nutritional benefits but face challenges in germplasm identification, phylogenetic analysis, and breeding due to their complex genetic background. Long Terminal Repeat Retrotransposons (LTR-RTs), major drivers of plant genetic diversity, offer a basis for the Inter-Retrotransposon Amplified Polymorphism (IRAP) system, which excels in germplasm identification, diversity assessment, and relatedness studies. Here, we developed a blueberry IRAP system using Ty1-copia reverse transcriptase sequences. From 25 core primers, we obtained 266 polymorphic loci (average PIC = 0.866). These IRAP markers fingerprinted 112 accessions and revealed relationships through Nei’s diversity index (H = 0.361), Shannon’s index (I = 0.533), AMOVA (9.33% among regions; 90.67% within populations; Nm = 1.50), UPGMA dendrograms (three clusters at 0.615 similarity), and PCoA, indicating weak geographic structure across Guiyang, Qiandongnan, and Bijie consistent with Nm = 1.50 (homogenizing gene flow). The dendrogram and PCoA indicate among-accession heterogeneity with weak geographic structuring across Guiyang, Qiandongnan, and Bijie, consistent with the AMOVA and gene-flow estimates. We also built a Molecular IDs database for differentiation. IRAP proved highly efficient for identification and analysis, matching SSR/SNP polymorphism levels while offering advantages like low-cost agarose gel resolution for detecting subtle clonal variants in polyploids—outperforming SSRs in field triage and complementing SNPs’ high throughput. This supports IP protection and breeding. Together with established SSR/SNP platforms, this IRAP approach can support IP protection and breeding as a complementary, cost-effective option. Full article

Kernel row number (KRN) is a pivotal determinant for yield in maize breeding programs. However, the genetic basis underlying KRN remains largely elusive. To identify candidate genes regulating KRN, a population of 318 BC₄F₄ chromosomal segment substitution lines (CSSLs) was developed via backcrossing, with Baimaya (BMY) as the donor parent and B73 as the recurrent parent. Furthermore, a high-density genetic linkage map containing 2859 high-quality single-nucleotide polymorphism (SNP) markers was constructed for quantitative trait locus (QTL) mapping of KRN. Notably, 19 QTLs controlling KRN were detected across three environments and in the Best Linear Unbiased Prediction (BLUP) values; among these, a major-effect QTL (qKRN4.09-1) was consistently identified across all three environments and BLUP. Then, the integration of linkage mapping and transcriptome analysis of 5 mm immature ears from near-isogenic lines (NILs) uncovered a candidate gene, Zm00001eb205550. This gene exhibited significant downregulation in qKRN4.09-1^BMY, and two missense variants were detected between qKRN4.09-1^BMY and qKRN4.09-1^B73. Zm00001eb205550 exhibited preferential expression in developing ears. Moreover, the pyramiding of favorable alleles from the five stable QTLs significantly increased KRN in maize. These findings advance our genetic understanding of maize ear development and provide valuable genetic targets for improving KRN in maize breeding. Full article

The Inner Mongolia Cashmere goat (IMCG) industry is a major contributor to global cashmere production, with fleece traits serving as key economic indicators that directly impact both income and the long-term sustainability of the industry. When genome-wide SNPs are used to estimate kinship matrices, the traditional animal model implicitly assumes that all SNPs have the same effect-size distribution. However, in practice, there are differences in the genetic mechanisms and complexity of different traits. We conducted a genome-wide association study (GWAS) on 2299 IMCGs genotyped with 67,021 SNPs, which were obtained after imputation. The traits measured included cashmere yield (CY), wool length (WL), cashmere length (CL), and cashmere diameter (CD), with a total of 33,564 records collected. The top 5% to 20% of the significant SNPs from the GWAS were used as biological prior information. We then assigned proportional weights based on their contribution to the overall genetic variance and further integrated them with the remaining loci to construct a kinship relationship matrix for estimating genetic parameters and genomic breeding value. By incorporating prior marker information from the GWAS, it was found that the heritability estimates for CY, WL, CL, and CD were 0.26, 0.37, 0.09, and 0.35, respectively. For CY and CL, integrating the top 5% of prior SNP markers yielded the highest genomic prediction accuracies of 0.742 and 0.673, representing improvements of 16.67% and 19.75% over models that did not utilize prior information. In contrast, for WL and CD, the highest accuracies of 0.851 and 0.780 were achieved by integrating the top 10% of prior SNP markers, reflecting improvements of 9.81% and 10.14%, respectively. Compared with the conventional GBLUP method, this method of integrating GWAS-derived prior markers for genomic genetic evaluation can significantly improve the accuracy of genomic prediction for fleece traits in IMCGs. This approach facilitates accurate selection for fleece traits in IMCGs, enabling accelerated genetic progress through long-term breeding programs. Full article

Black tiger shrimp (Penaeus monodon) is the largest species of penaeid, being commercially cultured globally, ranking as the second most farmed species in the shrimp industry. However, with the transformation of shrimp aquaculture from semi-intensive to high-density farming, the concentration of ammonia nitrogen in the aquatic environment has increased, severely affecting the growth and survival of shrimps. To increase production efficiency, breeding new strains of shrimp with the trait of tolerance to high ammonia nitrogen is desired in the black tiger shrimp aquaculture. Previous studies have shown that glutamate dehydrogenase (GDH) and aspartate aminotransferase 2 (AST2) play important roles in the metabolism of ammonia nitrogen in crustaceans. In the present study, we conducted synteny analysis of PmGDH and PmAST2 in different species. The interactions of PmGDH with ammonium (NH₄⁺) and PmAST2 with aspartate were analyzed by docking. To develop molecule markers associated with ammonia nitrogen tolerance, SNPs of PmGDH and PmAST2 were identified by direct sequencing, genotyped by the SNaPshot technique, and characterized through genotype-phenotype association analysis by PLINK software version 1.9 in the three geographical populations, two families with different ammonia tolerance, and 120 susceptible and resistant individuals of black tiger shrimp. The results indicate that the GDH and AST2 genes are evolutionarily conserved in vertebrates, except for the black tiger shrimp, which suggests divergence in selective pressure between invertebrates and vertebrates. Notably, PmGDH may interact with NH₄⁺ via the residue Asp178 within loop 1 in the GdhA domain through a hydrogen bonding interaction, and PmAST2 may interact with aspartate via helix 1, sheet 1, loop 1, and loop 2, through both hydrogen bonding interactions and a salt bridge interaction. A total of 12 SNPs were detected in the exons of PmGDH and PmAST2. Among these candidate SNPs, the distributions of PmGDH-1227 and PmAST2-132 showed both significant differences in the genotype and allele association analysis between susceptible and resistant groups. Haplotype association analysis showed that three haplotypes exhibited significantly different distributions between susceptible and resistant groups. In conclusion, PmGDH-1227 and PmAST2-132 were associated with ammonia nitrogen tolerance, and these SNP markers are expected to contribute to marker-assisted selection (MAS) breeding programs to obtain new strains of Penaeus monodon. Full article

Developing soy cultivars for northern long-day regions requires understanding how alleles of protein accumulation genes function in non-optimal environments like Western Siberia, where their effects may diverge from those established in other regions. We hypothesized that allelic variation in the genes GmSWEET39, Glyma.03G219900, Glyma.14G119000, Glyma.17G074400, and POWR1 would have measurable and predictable effects on seed composition and plant architecture in soybean, even under the stressful long-day conditions of Western Siberia (Omsk Oblast). Over a three-year period (2021–2023), a diverse collection of 58 soybean accessions was phenotyped for yield-related traits and genotyped using established KASP and PCR markers and a novel KASP marker for GmSWEET39. Our results demonstrate that the GmSWEET39 CC+ allele is significantly associated with an increase in seed protein content by up to 1.9 pp, a decrease in seed oil content up to 1.4 pp, and a reduction in plant height by up to 20%, while the Glyma.17G074400 SNP(T) allele was associated with an increase in oil content up to 1.4 pp. Strong negative correlations were found between protein content and plant height, whereas plant height was positively correlated with flowering time. Broad-sense heritability was high (H² > 0.82) for all traits except fiber content. The genotypic structure of the collection revealed a predominance of oil-favoring alleles, with rare protein-enhancing alleles identified in accessions from Sweden, Poland, China, and Japan. These accessions have been proposed as valuable donors for breeding. This study validates the utility of marker-assisted selection for the development of high-protein and high-oil soybean varieties tailored to the challenging photoperiod and climatic conditions of northern regions. Full article

Modern maize breeding worldwide relies on a broad range of molecular genetics research techniques. These technologies allow us to identify genomic regions associated with various phenotypic traits, including resistance to fungi of the genus Fusarium. Therefore, the aim of this publication was to identify new molecular markers linked to candidate genes that confer maize resistance to Fusarium fungi, using next-generation sequencing, association mapping, and physical mapping. In the study, a total of 5714 significant molecular markers related to maize plant resistance to Fusarium fungi were identified. Of these, 10 markers were selected that were significantly associated (with the highest LOD values) with the disease. These markers were identified on chromosomes 5, 6, 7, 8, and 9. The authors were particularly interested in two markers: SNP 4583014 and SilicoDArT 4579116. The SNP marker is located on chromosome 5, in exon 8 of the gene encoding alpha-mannosidase I MNS5. The SilicoDArT marker is located 240 bp from the gene for peroxisomal carrier protein on chromosome 8. Our own research and the presented literature review indicate that both these genes may be involved in biochemical reactions triggered by the stress caused by plant infection with Fusarium fungal spores. Molecular analyses indicated their role in resistance processes, as resistant varieties responded with an increase in the expression level of these genes at various time points after plant inoculation with Fusarium fungal spores. In the negative control, which was susceptible to Fusarium, no significant fluctuations in the expression levels of either gene were observed. Analyses concerning the identification of Fusarium fungi showed that the most abundant fungi on the infected maize kernels were Fusarium poae and Fusarium culmorum. Individual samples were very sparsely colonized by Fusarium or not at all. By using various molecular technologies, we identified genomic regions associated with maize resistance to Fusarium fungi, which is of fundamental importance for understanding these regions and potentially manipulating them. Full article

The role of the genetic component in the development of schizophrenia and the formation of its clinical heterogeneity has been proven. To conduct a pilot associative analysis between positive and negative schizophrenia symptoms and polymorphic variants of the Transcription Factor 4 (TCF4) gene. The study included 373 patients with schizophrenia of Caucasian ethnicity, who underwent a comprehensive clinical examination, and a control group consisted of 194 mentally and somatically healthy individuals. Genotyping of three polymorphic variants of the TCF4 gene was carried out in the studied samples (rs2958182, rs8766, and rs9636107). Statistical analysis of the results was performed using Statistica for Windows V.12.0. Association analysis in SNPs was conducted using the chi-square criterion and Bonferroni correction. Groups of schizophrenia patients and healthy individuals were compared for selected TCF4 gene polymorphisms. No statistically significant differences in genotype and allele frequencies were found. The AA genotype and the A allele of the rs2958182 polymorphic variant, as well as the A allele of the rs9636107 polymorphic variant, had an effect predisposing to the predominance of negative symptoms. The TT genotype and the T allele of the rs2958182 polymorphic variant, as well as the G allele of the rs9636107 polymorphic variant, were statistically significantly more common among patients with leading positive symptoms. As a result of the study, associations of the polymorphic variant TCF4 rs2958182 and TCF4 rs9636107 with the leading symptoms of schizophrenia were discovered for the first time in Caucasian populations of the Siberian region. The obtained data confirm the contribution of the genetic component to the formation of clinical heterogeneity of schizophrenia and open up prospects for further search for genetic markers in order to prevent an unfavorable outcome of the disease. Full article