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PubMed2026

Development and identification of KASP-SNP markers correlated with Aeromonas hydrophila resistance traits in blunt snout bream (Megalobrama amblycephala).

The blunt snout bream (Megalobrama amblycephala) is an economically important freshwater fish species. However, it is highly susceptible to Aeromonas hydrophila infection, especially in intensive pond aquaculture in China. Molecular marker-assisted selection provides an efficient approach for breeding disease-resistant varieties; however, the key genes or molecular markers linked to A. hydrophila resistance remain scarce in this species. A 436 differential SNP sites with disease-resistant were screened on basis of whole-genome resequencing. Then, a high-throughput genomic KASP genotyping technique was utilized to discover favorable genes and SNP sites associated with A. hydrophila resistance. A total of 46 KASP markers were successfully developed with an accuracy of 92 %. These markers were used to genotyping 120 blunt snout bream individuals. Through trait correlation analysis and general linear models (GLM), five SNPs significantly (P < 0.05) associated with resistance to A. hydrophila were identified and mapped to five candidate genes (btnl2, cfhr2, slc47a1, neu3, nlrp1). Survival rate of individuals carrying the dominant genotype demonstrated an average survival rate of 81.39 %, which represents a 69.35 % increase in comparison with that of 48 % in total population. This effect was validated in an external population of 100 fish. These findings identify key genetic markers associated with A. hydrophila resistance and provide a direction for elucidating the underlying molecular immune mechanisms, thus establishing a genetic foundation for future breeding strategies.

Cyprinidae↗

PubMed2026

[Genetic diversity analysis of Forsythia suspensa germplasm resources in Shanxi based on phenotypic traits and SNP molecular markers].

This study aimed to clarify the degree of fruit phenotypic variation and the characteristics of genetic diversity, population structure, and genetic differentiation of Forsythia suspensa resources in Shanxi, providing an important basis for germplasm conservation and breeding of superior varieties. A total of 46 F. suspensa fruits were collected, and 12 agronomic traits were measured and analyzed. The population genetic structure and genetic diversity of F. suspensa germplasm were evaluated using simplified genome sequencing technology. For the five quality traits of the 46 fruits, the Shannon-Wiener index ranged from 0.631 to 1.074, and the Simpson index ranged from 0.379 to 0.560. The seven quantitative traits exhibited abundant genetic variation, with coefficients of variation ranging from 9.764%(fruit shape index) to 45.494%(forsythin content). Principal component analysis reduced the 12 phenotypic traits to four factors, with a cumulative variance contribution of 74.547%. Sequencing data showed mean Q20 and Q30 values of 98.13% and 94.33%, respectively, with an average GC content of 35.95%. After filtering, a total of 12 347 327 high-quality single nucleotide polymorphism(SNP) loci were obtained. Based on these high-quality SNPs, principal component analysis, population structure analysis, and phylogenetic tree construction were carried out. The 46 germplasm resources were divided into four groups; however, grouping showed little relationship with geographic origin, and intermixing occurred among regions. Mantel test revealed a significant but weak positive correlation between phenotypic and genetic distances(r=0.159, P=0.001). At the molecular level, the four groups exhibited moderate genetic diversity overall, and the genetic differentiation index among populations ranged from 0.027 to 0.084, indicating low to moderate differentiation. The rich genetic diversity of the main phenotypic traits provides a solid material basis for screening superior germplasm and genetic breeding of F. suspensa.

Forsythia↗

PubMed2026

Microsatellites Versus Genome-Wide SNPs Data for Pedigree Reconstruction in Twin Simmental Crossbred Cattle.

Accurate pedigree reconstruction is critical for genetic evaluation in admixed cattle populations, yet the relative performance of microsatellite and genome-wide SNP markers in twin-rich herds with incomplete pedigree records remains unclear. We compared 12 ISAG-recommended microsatellite markers with whole-genome SNP data for dam-calf assignment in a Simmental crossbred population (n = 43, 13 dam-calf groups) from southern China. Twin zygosity was determined from SNP identity-by-descent (PI_HAT) values: nine calf pairs were dizygotic, one pair was monozygotic (20A/21A), and one adult pair was composed of dizygotic twin sisters (31A/34A). Admixture analysis at K = 3 revealed ancestry proportions of 50.7% European taurine, 28.9% Chinese indicine and 20.4% East Asian taurine. The SNP-based neighbor-joining tree correctly recovered 12 of 13 groups (92.3%, 95% CI: 64.0-99.8%), whereas the microsatellite-based tree recovered 11 (84.6%, 95% CI: 54.6-98.1%); the difference was not statistically significant (exact McNemar test, p = 1.0). Locus INRA023 was monomorphic (PIC = 0), reducing the effective number of markers to 11. These results indicate that genome-wide SNPs show a favourable trend in accuracy and are less prone to false-positive clustering than a standard microsatellite panel in admixed, twin-rich cattle populations.

SNP↗

PubMed2026

Genomic background of gestation length and calving-related traits in Holstein cattle.

The reproductive success of cows directly influences the profitability of dairy farms. Reproductive traits, particularly calving-related traits, generally have low heritability but sufficient additive genetic variance to enable genetic progress through genomic selection. Thus, the primary objectives of this study were to estimate genetic parameters and perform single-step genome-wide association studies (ssGWAS) for calf size, calving ease, gestation length, and stillbirth in Holstein cattle. Variance components were estimated based on animal models and Bayesian inference using a data set containing 226,717 animals with phenotypic records, 15,761 animals genotyped with 45,101 SNP markers, and 461,819 animals in the pedigree. SNP effects were estimated using the single-step GBLUP method. For direct and maternal genetic effects, heritability estimates (posterior standard deviation) ranged from 0.001 (0.002) for gestation length in heifers to 0.16 (0.001) for gestation length in cows. Genetic correlations ranged from -0.57 (0.01) between calving ease and stillbirth in heifers to 0.74 (0.01) between gestation length evaluated in heifers and cows. The ssGWAS results supported a highly polygenic architecture for calving-related traits, with most genomic signals not reaching genome-wide significance. A genome-wide significant association was detected for calving ease in cows on BTA23, highlighting FARS2 as a positional candidate gene. The strongest GWAS signals for each trait harbored additional biologically important candidate genes, including NPPA, NPPB, BCHE, EPHA4, DLD, and GTF2I. Given the generally low heritability estimates and the predominantly polygenic architecture observed for these traits, genomic selection may contribute to the genetic improvement of calving-related traits in Holstein cattle, with potential benefits for cow welfare, calf survival, and overall dairy production efficiency.

dairy cattle↗

PubMed2026

Development of a 10K breeder-friendly SNP chip for faba bean.

INTRODUCTION: Faba bean breeding and genomics have seen steady progress in recent years, supported by genome sequences and high-density genotyping platforms. These tools have been valuable for trait mapping, diversity assessment, and genomic research, but they have limited routine use in breeding programs due to their relatively high cost. Recent progress in establishing an optimized, cost-efficient genotyping-by-sequencing protocol tailored to the large and complex faba bean genome has created the foundation for a more accessible genotyping solution. METHODS: Using this approach, we explored the genetic diversity of faba bean germplasm from various panels, providing a comprehensive representation of the crop's genetic landscape. From this dataset, we identified and selected a high-quality set of informative SNP markers that are evenly distributed across the genome. Building on these resources, we designed a breeder-friendly 10K SNP chip. RESULTS: The 10K SNP chip delivers high accuracy, broad genomic coverage, and affordability. The chip was validated across diverse germplasm panels, demonstrating strong clustering performance, high reproducibility, and applicability to breeding-relevant germplasm. DISCUSSION: This platform offers a cost-effective alternative to higher-density arrays, enabling its integration into genomic selection, marker-assisted breeding, and diversity monitoring, ultimately supporting accelerated genetic gain and the delivery of improved varieties to farmers.

SNP chip↗

PubMed2026

An Amplicon Panel for High-Throughput and Low-Cost Genotyping of Yesso Scallop Mizuhopecten yessoensis.

The Yesso scallop Mizuhopecten yessoensis was imported from Japan to western Canada in the late 1980s to establish an economically viable scallop aquaculture industry. Since this time, the industry in Canada has operated with existing genetic diversity within the broodstock, which is considerably limited relative to wild populations. The sector has not been able to realise its full potential in part due to idiopathic hatchery failures and farm stock collapses due to disease outbreaks associated with the intracellular bacterial pathogen Francisella halioticida. To support Yesso scallop production and breeding, here we generate a low-density, genotyping-by-sequencing amplicon panel using single nucleotide polymorphism (SNP) markers that are evenly spaced across the M. yessoensis genome and that show high heterozygosity in Canada and Japan. The panel can also exploit the high genetic polymorphism of the M. yessoensis genome, with de novo SNP calling identifying over 2,500 high quality SNPs within the 579 sequenced amplicons. We demonstrate the utility and versatility of this new genotyping tool for breeding applications including parentage assignment, low density family-based genome-wide association study, trait heritability evaluation to determine potential for genomic selection, and species differentiation (against the weathervane scallop Patinopecten caurinus). We did not find any genomic regions significantly associated with F. halioticida resistance but did identify potential for genomic selection. We could separate the two species based on genotypes, and did not see evidence of a past M. yessoensis x P. caurinus hybridization event within the M. yessoensis breeding population at Vancouver Island University. This low-cost genotyping panel is expected to accelerate selective breeding improvements for M. yessoensis in Canada and elsewhere.

Animals↗

PubMed2026

Identification of Novel Sources and Genetic Mapping for Bacterial Leaf Streak Resistance in a Geographically Diverse Panel of Wheat.

Bacterial leaf streak (BLS), caused by Xanthomonas translucens pv. undulosa (Xtu), has recently emerged as a significant threat to wheat production in the Northern Great Plains region of the United States. Deploying resistant cultivars is an economical and practical method of controlling BLS. To identify novel sources of BLS resistance, we screened a set of 355 bread wheat landraces and cultivars representing global diversity for their response to BLS. A wide distribution of seedling responses against BLS was observed, with most genotypes displaying a moderately to highly susceptible response. Notably, we identified 5 resistant and 33 moderately resistant responses. A high-resolution genome-wide association study using 302,524 high-quality single-nucleotide polymorphisms (SNPs) identified 10 significant marker-trait associations (MTAs) on chromosomes 1A, 1D, 3B, 4A, and 5A corresponding to unique genomic regions associated with BLS resistance. Compared with previous studies, four of these genomic regions are likely novel. Of these, MTA 'scaffold15531_2782724' associated with q5A.1 was highly significant (-log10P = 9.39) and exhibited the highest SNP effect (0.35). An association on chromosome 3B validated a previously identified 3B quantitative trait locus (QTL) mapped at approximately 6 Mbp in the hard red spring wheat cultivar 'Boost', and the high-resolution mapping from our study further refined the interval for this QTL. Furthermore, the narrow haplotype blocks reported in this study could be valuable for fine mapping of important regions. The novel resistant sources, along with identified genomic loci and corresponding SNP markers from this study, would be helpful for wheat-breeding programs to enhance BLS resistance.[Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

BLS↗

PubMed2024

Genetic diversity, disease resistance, and environmental adaptation of Arachis duranensis L.: New insights from landscape genomics.

The genetic diversity that exists in natural populations of Arachis duranensis, the wild diploid donor of the A subgenome of cultivated tetraploid peanut, has the potential to improve crop adaptability, resilience to major pests and diseases, and drought tolerance. Despite its potential value for peanut improvement, limited research has been focused on the association between allelic variation, environmental factors, and response to early (ELS) and late leaf spot (LLS) diseases. The present study implemented a landscape genomics approach to gain a better understanding of the genetic variability of A. duranensis represented in the ex-situ peanut germplasm collection maintained at the U.S. Department of Agriculture, which spans the entire geographic range of the species in its center of origin in South America. A set of 2810 single nucleotide polymorphism (SNP) markers allowed a high-resolution genome-wide characterization of natural populations. The analysis of population structure showed a complex pattern of genetic diversity with five putative groups. The incorporation of bioclimatic variables for genotype-environment associations, using the latent factor mixed model (LFMM2) method, provided insights into the genomic signatures of environmental adaptation, and led to the identification of SNP loci whose allele frequencies were correlated with elevation, temperature, and precipitation-related variables (q < 0.05). The LFMM2 analysis for ELS and LLS detected candidate SNPs and genomic regions on chromosomes A02, A03, A04, A06, and A08. These findings highlight the importance of the application of landscape genomics in ex situ collections of peanut and other crop wild relatives to effectively identify favorable alleles and germplasm for incorporation into breeding programs. We report new sources of A. duranensis germplasm harboring adaptive allelic variation, which have the potential to be utilized in introgression breeding for a single or multiple environmental factors, as well as for resistance to leaf spot diseases.

Arachis↗

PubMed2026

Genome-wide association identifies and validates genomic region controlling grain yield and agronomic traits in extra-early orange maize inbred lines under drought.

In order to meet the expected maize yield by 2050, breeders must work to improve breeding program efficiency by intensifying the implementation of new and improved technologies such as marker-assisted selection (MAS). Dissecting the genomic regions associated with drought tolerance is the first step forward in MAS program deployment for maize improvement under drought stress. Genome-wide association studies (GWAS) were used to investigate and identify quantitative trait loci (QTLs) associated with six traits under drought stress. One hundred and eighty-seven extra-early orange maize inbred lines were evaluated under managed drought stress at Ikenne, in Nigeria, during the 2022 and 2023 dry seasons. The materials were also genotyped using 9355 DArTseq SNP markers and analyzed using the enriched compressed mixed linear model (ECMLM). Enriched compressed mixed linear model was used for association-trait analysis. The ECMLM-based GWAS identified 45 candidate genomic loci associated with the six traits, including five for grain yield, with R2 ranging from 8.79 to 25.3%. Independent validation using the multi-locus 3VmrMLM approach confirmed seven high-confidence genomic loci consistently detected by both methods across grain yield, anthesis-silking interval, ear aspect, and ears per plant, providing additional statistical support for these genomic regions. Candidate gene annotation identified biologically relevant genes underlying the validated loci, including Zm00001eb238250 (protein-serine/threonine phosphatase), Zm00001eb040940 (trehalose-phosphatase), Zm00001eb117820 (homeobox protein knotted-1-like 4), Zm00001eb145560 (zinc ion-binding protein), and Zm00001eb294180 (WRKY DNA-binding domain protein), suggesting their potential roles in drought adaptation and grain productivity. These findings improve our understanding of the genetic architecture of drought tolerance in extra-early orange maize and provide valuable genomic resources for accelerating drought-resilient maize breeding.

Zea mays↗

PubMed2026

Genome-Wide Association Analysis of Hippocampal Neuroplasticity as an Indicator of Stress Responsiveness in Laying Hens (Gallus gallus domesticus).

Environmental stressors in commercial poultry systems can negatively affect bird welfare, although individuals vary considerably in their responses. Neuroplasticity within the hippocampus, measured through the density of doublecortin-positive (DCX+) neurons, provides a potential biomarker of stress experience in laying hens. However, the genetic basis underlying variation in this biomarker remains poorly understood. A total of 42 H&N and Hy-Line Brown hens housed in a multitier free range and enriched cage system, respectively, were genotyped using Genotyping by Sequencing, yielding over 200 000 SNP markers after initial filtering. Hippocampal tissue sections were immunostained for DCX to quantify the density of highly plastic neurons. A genome-wide association analysis identified 19 genomic regions across eight chromosomes within the top 1% of windows explaining the greatest proportion of genetic variance in the neuroplasticity phenotype. Within ±100 kb of these regions, 39 annotated genes were identified, several of which are involved in cellular regulation and genetic information processing pathways. Notably, PIK3R6, VPS37D, STX1A, BAZ1B, HGH1, MAF1, MAPK15, and PIT54 emerged as positional candidate genes potentially contributing to variation in stress responsiveness. These findings provide preliminary insight into the genetic architecture of hippocampal neuroplasticity in laying hens and highlight candidate genes that may contribute to individual differences in stress response, with potential implications for breeding strategies aimed at improving poultry welfare.

Animals↗

PubMed2026

Genomic selection in timothy (Phleum pratense L.): a comprehensive evaluation of prediction models, multi-trait strategies, and forward validation across Norwegian environments.

This study presents a comprehensive evaluation of genomic selection (GS) in timothy (Phleum pratense L.), comparing nine prediction models across yield and quality traits at two Norwegian locations. Forward validation with independent full-sib (FS2) families revealed a substantial generalization gap, highlighting the need for realistic accuracy assessment in polyploid forage breeding. Timothy (Phleum pratense L.) is the most important forage grass in Northern Europe, yet genomic selection has not been systematically evaluated in this hexaploid species. We assessed 889 FS2-families originating from biparental crosses among 49 cultivars/populations. The FS2-families were genotyped with 30,698 SNP markers derived from genotyping-by-sequencing (GBS) and field tested for three harvest years at a highland and a lowland continental location in Southern Norway. Nine genomic prediction models were compared for six yield traits (dry matter yield per cut and total) and six quality traits (protein, digestibility, and fiber fractions) across three cuts/year. Within-training cross-validation accuracies were moderate to high (mean r = 0.62), with Random Forest and SVR consistently outperforming GBLUP. However, forward validation using 213 independent FS2-families revealed dramatically lower accuracies (mean r = 0.16), with only 16 of 30 trait-dataset combinations reaching statistical significance (p < 0.05). Genomic heritabilities (GREML), estimated across environments, ranged from near zero for the quality traits to 0.55 for the yield traits. Multi-trait models improved accuracy by 3-5% over single-trait approaches, while FS2 families-by-environment interaction models with Random Forest achieved the highest within-training accuracy (mean r = 0.71). Marker density analysis showed accuracy plateauing at approximately 15000 SNPs. Genetic correlations among the yield component traits were estimated by multi-trait REML; correlations among the quality traits could not be estimated reliably because their genomic heritabilities were low. A multi-trait selection index identified top-performing FS2-families for further crossing recommendations. These results provide a benchmark for GS implementation in hexaploid timothy and emphasize that cross-validation substantially overestimates prediction accuracy for truly independent material.

Norway↗

PubMed2025

Integrated genomics and morphological approach reveals interspecific gene flow cases and decodes the origin of selected feathergrasses (Poaceae, Stipa).

Central Asia is a diversity hotspot of arid-adapted grasses from the genus Stipa, with approximately 100 taxa found in the region. Recent studies in the steppe areas of Kazakhstan revealed specimens displaying intermediate morphology, distinguishing them from other taxa that grow sympatrically. Using integrative taxonomy, we investigated whether these individuals resulted from natural speciation or hybridisation, and if so, we would like to know which species were involved in this process feathergrasses. Research conducted in steppes of central Kazakhstan (Kyzylorda region), revealed the existence of individuals morphologically intermediate between S. arabica and S. richteriana, suggesting that these are probably of hybrid origin. Morphology and SNP markers validated the specimens as F1 hybrid between the aforementioned species by cladding separately based on neighbor-joining phylogenetic tree. Moreover, genetic structure displayed a separate cluster and showed almost equal genetic admixture between S. arabica and S. richteriana. Additionally, fastStructure analysis detected two geographically separated cryptic genotypes within S. richteriana population and their involvement in the hybridisation resulted in occurrence of S. × heptapotamica, S. × czerepanovii and S. × korshinskyi which recently were suggested as hybrids. Based on these evidences, we described a new nothospecies S. × kyzylordensis, as F1 hybrid. Furthermore, morphologically, the nothospecies delimited with other hybrids in Kazakh steppe area, marking the first report of hybridisation between S. arabica and S. richteriana, along with molecular evidence for the origin of further species supposed to be hybrids. This finding is crucial to understanding species diversity and hybridisation process in morphologically and genetically distant Stipa species.

Poaceae↗

PubMed2026

Diploids derived from polyploids: genetic characteristics of four novel interspecific Sorghum populations.

Polyploidy has repeatedly shaped grass evolution, yet direct observations of how polyploid-derived chromosomes behave when returned to diploidy remain rare. Interspecific crosses between diploid Sorghum bicolor and tetraploid hybrids derived from Sorghum halepense generate mixed-ploidy progeny, providing an opportunity to examine chromosome transmission during the early stages of diploidization. Using genome-wide SNP markers, we characterized chromosomal inheritance patterns in 2 diploid and 2 tetraploid families derived from these crosses. Genotype-dosage profiles alone distinguished diploids from tetraploids with complete accuracy, reflecting strong ploidy-dependent differences in dosage-class distributions. Although diploid progeny retained much of the halepense-derived genomic background, several genomic intervals exhibited extended, nonrandom runs of S. bicolor homozygosity that remained polymorphic in corresponding tetraploid populations. These patterns, together with recurrent segregation distortion across independent families, suggest that the transition from tetraploidy to diploidy can expose allelic combinations that differ in transmission or viability. Analyses of flowering time further indicated that diploid and tetraploid derivatives possess distinct genomic architectures, with major association peaks occurring in different chromosomal regions across ploidy levels. Collectively, these results indicate that early diploidization involves nonrandom retention and loss of parental haplotypes shaped by both selective and structural constraints. The diploid extractions characterized here provide a rare empirical system for investigating the early stages of diploidization and a practical framework for studying and eventually mobilizing polyploid-derived variation for sorghum germplasm development. However, broader integration into elite breeding programs will require additional evaluation of cross-fertility, meiotic behavior, and chromosomal stability across diverse breeding backgrounds.

Sorghum↗

PubMed2026

Genomic Regions Associated with Resistance to Soybean Cyst Nematode (Heterodera glycines Ichinohe) Population HG Type 1.2.5.7 in Dry Beans (Phaseolus vulgaris L.).

North Dakota, the largest dry bean (Phaseolus vulgaris L.) producing state in the U.S., faces an emerging production threat caused by the soybean cyst nematode (SCN; Heterodera glycines Ichinohe, 1952). Host resistance is an effective management strategy, yet resistance to the virulent SCN population HG type 1.2.5.7 has not been genetically characterized in dry beans. In this study, 170 dry bean genotypes (113 breeding lines/cultivars and 57 germplasm accessions) were evaluated for response to HG type 1.2.5.7 under controlled conditions using female index (FI) as the resistance phenotype. FI values ranged from 4.1% to 78.1%, with one genotype (PI 313733) classified as resistant, 35 moderately resistant, 104 moderately susceptible, and 30 susceptible. Genome-wide association analysis using 2,044 single-nucleotide polymorphism (SNP) markers from the 3.8K Bean Panel chip and the BLINK model identified four significant marker-trait associations on chromosomes Pv02, Pv05, Pv07, and Pv11. Linkage disequilibrium-defined candidate intervals spanned 108 kb (Pv02), 1.50 Mb (Pv05), 798 kb (Pv07), and 1.45 Mb (Pv11), collectively containing 126 annotated genes: 20 on Pv02, 39 on Pv05, 35 on Pv07, and 32 on Pv11. The intervals contained putative genes annotated for signaling and transcriptional regulation, cell wall and carbohydrate metabolism, transport, and secondary metabolism. Together, these findings indicate that the response to HG type 1.2.5.7 in dry bean is quantitative and associated with multiple genomic regions. The identified intervals provide candidate targets for independent validation, fine mapping, functional analysis, and future marker development to support breeding for SCN resistance.

Disease Resistance↗

PubMed2025

Genetic diversity, population structure in a historical panel of Brazilian soybean cultivars.

Soybean [Glycine max (L.) Merrill] is one of the most widely grown legumes in the world, with Brazil being its largest producer and exporter. Breeding programs in Brazil have resulted from multiple cycles of selection and recombination starting from a small number of USA cultivar ancestors in the 1950s and 1960s years. This process has led to the successful adaptation of this crop to tropical conditions, a phenomenon known as tropicalization. Many studies describe a narrow genetic background in Brazilian soybean cultivars. Various factors can affect the genetic diversity in species, especially in cultivated crops, such as the reproduction type, artificial selection, and the number and sources of variability in the breeding programs. In turns, the genetic diversity can affect the linkage disequilibrium blocks (LD) patterns and, consequently, molecular breeding strategies for selection of target loci for agronomic traits. We used high-throughput genotyping with SoySNP50K Illumina SNP markers to assess a collection of 370 Brazilian soybean accessions covering more than 60 years of soybean breeding in Brazil. Our goal was to investigate population structure and genetic diversity in the Brazilian germplasm, detect patterns of LD blocks, and identify regions presenting signals of selective swaps linked with quantitative trait loci (QTLs) of agronomic interest. Population structure analysis revealed two major groups among all genotypes, primarily differentiated by the year of release, separating old and new cultivars (before and after 2000´s years), and by growth habit (stem termination type-SST). The group I comprises about 75% of the panel and includes cultivars release before 2000`s years, including the oldest cultivars released in Brazil, most of which exhibit a determinate growth habit and maturity groups VI and VII. Group II includes only 83 materials, but shows higher levels of diversity than group I, representing most recent introductions in Brazilian germplasm. Further analysis of substructure within Group I, identified seven subgroups with no clear trend for segregation based on maturity group, STT or year of release. Instead, these subgroups were based on the contribution of key donors of disease resistance and adaptability, as soybean cultivation expanded from the South to Central region of Brazil. This finding is consistent with the history of soybean expansion in Brazil. We identified 123 genomic regions under selection among the groups of Brazilian cultivars associated with 440 quantitative trait loci (QTLs), revealing regions fixed across the breeding process associated with yield, disease resistance, water efficiency use, and others.

Glycine max↗

PubMed2026

Dissecting the genetic basis underlying drought tolerance at different development stages in soybean.

INTRODUCTION: Soybean is an indispensable crop supplying protein and oil for humans and animals, and playing an essential role in global food security. Drought represses soybean seed germination, reducing biomass accumulation and even inhibiting yield. METHODS: In order to dissect the genetic components underlying soybean drought tolerance during different development stage, a natural population containing 140 accessions was employed to evaluate seven drought tolerance-related traits under water-welled and drought stress conditions. Subsequently, genome-wide association study (GWAS) was conducted based on 150K single nucleotide polymorphism (SNP) markers of "Zhongdouxin-1". And the drought tolerance coefficient of seven different traits were analyzed with seven GWAS models. RESULTS: A total of 1807 significant SNPs were detected across 20 chromosome, including 569 SNPs for germination stage, and 1242 SNPs for seedling stage. Of 569 SNPs identified in germination stage, 354 SNPs on chromosomes 2, 7, 13, 14, and 17 accounting for 62.21%. Among 1242 SNPs found in seedling stage, 869 SNPs on chromosomes 11, 14, 15, 17 and 18 accounting for 69.97%. Moreover, among 1807 significant SNPs, 163 SNPs exhibited pleiotropic effects, of which 23 were located in exon, 21 in intron, 12 in 5'UTR or 3'UTR and 11 in upstream or downstream. Furthermore, 249 stable SNPs were detected by more than four GWAS models. According to these stable SNPs, RNA expression levels and gene annotations, four causal genes (Glyma.02G080200, Glyma.11G056200, Glyma.12G188900, and Glyma.18G110200) conferring soybean drought tolerance were detected, which participated in ethylene stimulus response, water deprivation response, and proteolysis. DISCUSSION: Collectively, 249 stable SNPs, 163 pleiotropic SNPs and four candidate genes identified in present study provided promising molecular resources and reliable foundation for drought resistance improvement and marker-assisted selective breeding in soybean.

GWAS↗

PubMed2026

Genetic Identification of Burned Human Remains: A Systematic Review.

Background/Objectives: DNA-based identification of degraded human remains represents a major challenge in forensic science, particularly in cases involving burned, fragmented, or commingled bodies. Advances in forensic genetics have expanded the analytical capabilities for such samples; however, the effectiveness of different approaches and their integration within Disaster Victim Identification (DVI) workflows remain heterogeneous. This systematic review aims to critically evaluate current evidence on DNA-based identification of degraded remains, focusing on methodological strategies, emerging genomic technologies, and DVI applications, while integrating laboratory evidence and operational forensic practice into a structured analytical framework. Methods: A systematic literature search was conducted in Scopus and Web of Science from database inception to 5 June 2026, following PRISMA 2020 guidelines. Eligible studies included original research addressing DNA analysis of degraded, thermally altered, or highly compromised human remains in forensic or DVI contexts. After a multistep screening process involving title/abstract and full-text evaluation, 37 studies were included. Data were extracted and organized into three thematic categories: (i) core DNA analysis, (ii) advanced molecular technologies, and (iii) DVI case applications. Results: The findings demonstrate that DNA recovery from degraded remains is influenced by thermal exposure, tissue type, and sampling strategy. Teeth and dense cortical bone consistently provide higher DNA yield. While autosomal STR profiling remains the primary analytical approach, its limitations in highly degraded samples are mitigated through the complementary use of mitochondrial DNA (mtDNA), Y-chromosome STRs (Y-STRs), and SNP markers, together with advanced sequencing technologies such as massively parallel sequencing (MPS). Emerging technologies, including rapid DNA systems and predictive models based on macroscopic indicators, significantly enhance efficiency and success rates. DVI studies report identification rates exceeding 90-95% when multidisciplinary and structured workflows are applied. The evidence further supports a flexible triage-based analytical strategy, in which marker selection is guided by tissue preservation and degradation level. Conclusions: DNA-based identification of degraded human remains has evolved into an adaptive, multi-level forensic process. Successful outcomes rely on the integration of optimized sampling, hierarchical genetic analysis, and coordinated DVI strategies. The findings support a triage-based framework that links tissue selection, degradation assessment, and analytical methodology to maximize identification success. Future developments should focus on predictive models, advanced genomic tools, and standardized workflows to further improve identification in challenging forensic scenarios.

Humans↗

PubMed2026

CamK-DB: A k-mer MinHash fingerprint database for reference-free genotyping of Camellia accessions.

Tea (Camellia sinensis L.), a major global economic crop in Asia, poses challenges for genetic identification because its highly heterozygous, repetitive genome reduces the efficacy of conventional single-nucleotide polymorphism (SNP) and microsatellite markers, and interspecific hybridization further complicates the situation. To address these issues, CamK-DB was developed as a reference-free Camellia fingerprinting database built on MIKE MinHash sketches. We curated 418 candidate resequencing datasets, and built a database using standardized 5× genome-coverage fingerprints. Each accession is stored as a MIKE. jac fingerprint generated with k = 21 and recommended sketch/pre_cnt = 2000. CamK-DB provides a command-line interface for data management and a custom C++ query engine that computes top-10 matches using Jaccard similarity, complemented by a QT-based graphical interface for interactive analysis. This resource offers a robust and scalable framework for precise and routine germplasm identification, genomic phylogenetic inference, and strategic breeding program design. CamK-DB (database and code) is publicly available at https://github.com/sc-zhang/CamK-DB. CamK-DB binaries are provided for Windows 10/11 and Linux (x86_64, glibc ≥ 2.27).

Databases, Genetic↗