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At least 19 recordsLinked to original sources

PubMed2006

Pooled DNA genotyping on Affymetrix SNP genotyping arrays.

BACKGROUND: Genotyping technology has advanced such that genome-wide association studies of complex diseases based upon dense marker maps are now technically feasible. However, the cost of such projects remains high. Pooled DNA genotyping offers the possibility of applying the same technologies at a fraction of the cost, and there is some evidence that certain ultra-high throughput platforms also perform with an acceptable accuracy. However, thus far, this conclusion is based upon published data concerning only a small number of SNPs. RESULTS: In the current study we prepared DNA pools from the parents and from the offspring of 30 parent-child trios that have been extensively genotyped by the HapMap project. We analysed the two pools with Affymetrix 10 K Xba 142 2.0 Arrays. The availability of the HapMap data allowed us to validate the performance of 6843 SNPs for which we had both complete individual and pooled genotyping data. Pooled analyses averaged over 5-6 microarrays resulted in highly reproducible results. Moreover, the accuracy of estimating differences in allele frequency between pools using this ultra-high throughput system was comparable with previous reports of pooling based upon lower throughput platforms, with an average error for the predicted allelic frequencies differences between the two pools of 1.37% and with 95% of SNPs showing an error of < 3.2%. CONCLUSION: Genotyping thousands of SNPs with DNA pooling using Affymetrix microarrays produces highly accurate results and can be used for genome-wide association studies.

Alleles↗

PubMed2026

SNP genotyping in Pseudotsuga menziesii and Pinus radiata using targeted genotyping-by-sequencing (GBS): improved Bayesian SNP calling using a beta-binomial distribution and other optimized input parameters.

BACKGROUND: Single-nucleotide polymorphism markers (SNPs) have important applications in gene conservation, breeding, and fundamental genetics research. Our long-term goal is to develop routine approaches for SNP genotyping in forest trees. Ideally, these approaches would be inexpensive, able to accommodate a wide range of samples and SNPs, available through commercial providers, and produce high-quality SNP data. RESULTS: Using targeted genotyping-by-sequencing (GBS), we developed SNP assays for two highly heterozygous tree species, Douglas-fir (Pseudotsuga menziesii) and radiata pine (Pinus radiata). Using Douglas-fir haploid and diploid data, we optimized Bayesian SNP calling by testing four input parameters: (1) allele and genotype prior probabilities, (2) Rho, the beta-binomial dispersion parameter, (3) estimated read error (BayesReadError), and (4) the logPO cutoff used to filter low confidence SNP calls. logPO is the Bayesian posterior odds ratio for a called SNP. Compared to assuming a binomial distribution of read counts (Rho = 0), the beta-binomial distribution (Rho = 0.33) substantially reduced call error and heterozygote undercalling. Compared to the other Bayesian parameters, genotype priors had little effect on genotyping success. For Douglas-fir, we tested 5,360 SNP assays, and then studied the performance of the best 4,000. For radiata pine, we tested 6,000 SNP assays, and then studied the performance of the best 4,570. In Douglas-fir and radiata pine, our Bayesian approach resulted in median call rates of 95% to 98% for the top-ranked SNPs, with an estimated call error of 1.60% for known homozygous genotypes and 2.27% for known heterozygotes. In radiata pine, median and mean call rates were above 91% for GBS and SNP genotyping using an Axiom fixed genotyping array. Additionally, the median correspondence between the GBS and Axiom genotypes was about 98% overall (mean 96%). CONCLUSIONS: By optimizing Bayesian SNP calling, selecting the best 4-5 K SNPs, and excluding samples with low DNA amounts, we substantially reduced call error and heterozygote undercalling, resulting in SNP genotypes that were nearly identical to genotypes obtained using the Axiom array. Furthermore, genotyping performance should increase even further if our SNP rankings were used to develop less complex probe pools that target fewer SNPs.

Pinus↗

PubMed2026

High-Density SNP Genotyping Reveals High Population Connectivity and Limited Spatial Genetic Structure in Apodemus flavicollis and Apodemus sylvaticus.

High-density SNP arrays are increasingly used in ecological and evolutionary studies, yet their application in wild species remains challenging. In this study, we evaluated the performance of the Affymetrix Axiom Mouse HD array, originally developed for Mus musculus, in two wild small mammals, Apodemus flavicollis and Apodemus sylvaticus, with particular focus on genetic diversity and population connectivity across seven sampling sites within a fragmented landscape. A total of 96 individuals (43 A. flavicollis and 53 A. sylvaticus) were genotyped using a 616K SNP array. After quality control filtering for missingness and minor allele frequency, more than 160,000 high-quality autosomal SNPs were retained for each species. Despite being designed for a different species, the array effectively discriminated between A. flavicollis and A. sylvaticus, with principal component analysis clearly separating the two species. Levels of genetic diversity were comparable across sites, with mean observed heterozygosity around 0.33 and consistently negative F IS values, indicating a slight excess of heterozygotes. Population structure analyses revealed extremely weak spatial genetic differentiation. ADMIXTURE supported a single genetic cluster (K = 1) within each species, while analysis of molecular variance attributed more than 99% of genetic variation to within-individual components. Pairwise relationship analyses showed that related individuals were not confined to single sites but occurred across sampling locations, supporting ongoing gene flow even across the fragmented landscape. No significant isolation-by-distance pattern was detected. Overall, our results indicate high population connectivity and limited spatial genetic structuring in both species across the study area, consistent with the documented dispersal capacity of these species at the spatial scale investigated. Moreover, this study demonstrates that high-density SNP arrays can provide powerful genomic tools for investigating dispersal dynamics and population structure in closely related wildlife species under habitat fragmentation, where subtle genetic patterns may otherwise remain undetected.

Apodemus species↗

PubMed2025

Repeatable Genomic Outcomes Along the Speciation Continuum: Insights From Pine Hybrid Zones (Genus Pinus).

Hybridization is a widespread evolutionary process and a key source of evolutionary novelty. Despite intensive study, the extent to which hybridization is deterministic and repeatable, particularly in recurrent contact events involving the same species under varying ecological conditions, remains unclear. Here, we investigated three replicated contact zones between Scots pine (Pinus sylvestris) and dwarf mountain pine (Pinus mugo) in Central Europe: two occurring in peatland habitats and one in a contrasting sandstone outcrop. Using genome-wide SNP genotyping of over 1300 individuals, we analysed genomic structure, diversity, and ancestry patterns across these zones. All sites revealed pervasive hybridization, dominated by later-generation hybrids and a notable scarcity of pure P. mugo. Across environments, hybrid populations exhibited strikingly consistent genomic compositions, with asymmetric introgression strongly biased toward P. mugo ancestry, suggesting that hybrid genome structure may follow predictable patterns under similar ecological conditions and could be shaped by cytonuclear incompatibilities. Nonetheless, we also detected site-specific differences in hybrid diversity and phenotype, highlighting the influence of local environmental selection on shared hybrid genomic backgrounds. We provide genomic evidence that Pinus uliginosa, a morphologically distinct peat bog pine traditionally regarded as a relict and endangered species is instead a partially stabilised hybrid lineage. Its genome reflects incomplete hybridization and ecological filtering, yet it lacks sufficient genetic divergence to be recognised as a distinct species. Together, these results provide evidence for the repeatability of hybridization processes, which result in the formation of phenotypes reflecting a species continuum subjected to strong environmental pressures. The findings support the simplification of taxonomic nomenclature within the Pinus mugo complex, informing adaptive conservation strategies and the genetic management of hybrid lineages.

Hybridization, Genetic↗

PubMed2026

Development and optimization of T-ARMS PCR assays for detection of lethal haplotypes of TADA2A, UR1B, and PORL1B in pigs in Vietnam.

Marker-assisted selection has increasingly relied on single-nucleotide polymorphisms (SNPs) as robust genetic markers, particularly in livestock breeding programs. In pig farming, embryonic mortality significantly affects litter size, and SNPs in reference genes have been implicated as potential causal factors. We developed and optimized a tetra-primer amplification refractory mutation system (T-ARMS) PCR assay for rapid, cost-effective detection of SNPs in 3 candidate genes-TADA2A, PORL1B, URB1-that are associated with embryonic lethality and reproductive performance. Primer sets were designed based on known mutation sites and validated using synthetic gene constructs and porcine genomic DNA from pigs of Duroc and Landrace breeds. Optimization of annealing temperatures and primer concentration ratios yielded distinct and reproducible allele-specific amplicon patterns that were corroborated by PCR-RFLP and Sanger sequencing. Our T-ARMS PCR protocol, which requires minimal equipment and reduces processing time to <3 h, had high specificity and efficiency in differentiating wild-type, heterozygous, and homozygous mutant genotypes in 20 Duroc and 20 Landrace pigs. Our Tetra-ARMS PCR assay is a robust and economically viable tool for SNP genotyping in pig breeding programs, potentially contributing to the reduction of embryonic lethality and the improvement of overall reproductive outcomes.

Sus scrofa↗

PubMed2025

Development and validation of a high-density 'Amahysnp' genotyping array in grain amaranth (Amaranthus hypochondriacus).

BACKGROUND: Grain amaranth has recently gained global attention as a promising crop alternative to traditional cereals due to its nutritional value and adaptability to various growing conditions. Although gene banks conserve extensive collections of amaranth germplasm, the genomic and phenotypic characterization of these resources is limited, which hinders their full utilization in breeding programs. A major challenge is the lack of high-throughput genotyping assays essential for comprehensive genomic characterization and trait mapping. High-density SNP arrays have become standard tools for genome-wide analysis across multiple loci, enabling molecular breeding across a range of crop species. RESULTS: In this study, we developed a 64 K high-throughput SNP genotyping array named "AmahySNP", using Affymetrix® Axiom® technology. The array contains 64,069 high-density SNPs distributed across both genic (55.17%) and non-genic (44.83%) regions of the Amaranthus hypochondriacus genome. The genic region includes 8,879 genes, which consist of 4,830 single-copy genes and 4,049 multi-copy genes distributed across 16 scaffolds. These genes cover various functional regions, including exons (10.5%), introns (40.1%), 5'UTRs (1.6%), and 3'UTRs (2.9%), respectively. The AmahySNP array was effectively utilized for population structure analysis, genetic diversity studies, core development, and genome wide association studies (GWAS) in amaranth germplasm. A representative core set of 112 accessions was identified, which includes two released varieties (Annapurna and Suvarna) and 100 diverse accessions from 12 different regions, representing 12% of the total 917 accessions evaluated. Phylogenetic analysis revealed three major genetic clusters, independent of their geographical origins. GWAS conducted using 22,763 polymorphic SNPs from 540 genotypes identified 13 novel loci associated days to flowering (DTF) trait, seven of which were located within annotated genes. CONCLUSIONS: The AmahySNP 64 K SNP chip a valuable genomic tool for amaranth research and breeding with a strong potential to accelerate its genetic improvement. It enables high-throughput genotyping for a wide range of applications, including GWAS and other genomic studies, and will significantly advance the exploration of natural genetic variations. Ultimately, this resource will empower amaranth breeders to develop improved amaranth cultivars with enhanced crop yield, resilience, and nutritional quality, contributing to global food security and sustainable agriculture.

Amaranthus↗

PubMed2026

Quo vadis, BGA? A collaborative EDNAP exercise on the challenges and progress in forensic biogeographical ancestry inference.

There is a broad consensus that forensic tests for the prediction of externally visible characteristics (EVC) and analysis of biogeographic ancestry (BGA) of an individual are technically reliable. However, interpretation of the results and population-specific genotype distribution patterns remains challenging. EVC and BGA analyses provide valuable information for population genetics studies and as investigative leads for criminal cases, as well as for historical and contemporary identification tests. However, inaccurate or incorrect predictions, for example, from subjective bias in the interpretations made, have the potential to misdirect police investigations. The legal situation regarding EVC and BGA testing varies by country: ranging from countries where it is explicitly prohibited, to those without specific regulations on biogeographic ancestry prediction, and others that have already enacted laws governing its use. The reluctance to utilize these analyses is not only due to legal restrictions and data protection concerns, but also to initial limited sets of sufficiently comprehensive forensic DNA assays. Forensic BGA marker panels typically contain up to ∼300 SNPs. This relatively small number of genetic markers, along with limited reference population data, complicates the interpretation of results from donors of unknown origin. This paper presents the results of a collaborative EDNAP study, which, for the first time, evaluated the approach to reporting EVC and BGA data between international laboratories. For the study, DNA from nine individuals with self-reported ancestry was collected and analysed using various forensic panels differing in the number and composition of ancestry-informative markers genotyped, comprising: the Precision ID mtDNA Whole Genome Panel, the VISAGE Basic Tool and the VISAGE Enhanced Tool for Appearance and Ancestry Prediction, and the Ion AmpliSeq™ PhenoTrivium Panel. To ensure full data protection, all SNP genotypes and uniparental marker haplotypes obtained were not shared with third parties. Instead, the genetic data were analysed using a range of commonly used population analysis software packages. These analysis outcomes were then distributed to twelve European forensic laboratories (both academic and law enforcement institutions), who were asked to prepare reports based on their interpretation of the phenotypes and ancestry they inferred from the analysis data. A questionnaire sent alongside the genetic information, aimed to evaluate which difficulties were encountered by the participants in processing the BGA analysis data they were given.

Humans↗

PubMed2026

Precision periodontology in clinical practice: bridging omics and clinical decision-making.

BACKGROUND: Precision periodontology integrates molecular diagnostics, genomics, and advanced imaging into clinical decision-making. Despite major advances in microbiome characterisation, host genetics, and inflammatory biomarkers, their translation into routine care remains limited. OBJECTIVES: To critically appraise current evidence on microbiome-based profiling, genetic and epigenetic markers, host-response biomarkers, and three-dimensional imaging in periodontology, and to propose a conceptual decision-support framework linking diagnostic outputs to potential therapeutic actions and future implementation research. MATERIALS AND METHODS: A narrative review searching PubMed/MEDLINE, Scopus, Embase, and the Cochrane Library (2010-2025) using terms related to precision periodontology, subgingival microbiome, periodontitis genetics and epigenetics, salivary and GCF biomarkers, aMMP-8, CBCT, risk assessment, and artificial intelligence. Priority was given to meta-analyses, systematic reviews, longitudinal studies, and guideline documents. RESULTS: Microbiological testing has defined but narrow indications; single-SNP genotyping has not demonstrated clinical utility commensurate with cost; aMMP-8 point-of-care testing is among the most extensively investigated host-response tools and may have adjunctive value in selected monitoring and peri-implant scenarios; however, current evidence remains insufficient to support routine diagnostic implementation. CBCT may directly influence surgical decision-making through defect morphology characterisation. AI-based models show promise but lack prospective clinical validation. These conclusions are consistent with the 20th EFP Workshop Consensus Report. CONCLUSIONS: Precision periodontology currently operates in addition to, rather than in replacement of, conventional staging and grading. We propose a conceptual decision-threshold framework for the selective consideration of molecular and advanced imaging tools when their additive contribution may meaningfully inform management. This framework should be regarded as a research-oriented decision-support model rather than a validated clinical algorithm. CLINICAL RELEVANCE: Clinicians are provided with a structured, evidence-based framework that identifies specific clinical scenarios where molecular diagnostics, host-response biomarkers, and three-dimensional imaging may meaningfully modify periodontal treatment decisions, supporting the operationalisation of precision approaches in daily practice.

Humans↗

PubMed2025

The evolution of separate sexes in waterhemp is associated with surprising chromosomal diversity and complexity.

The evolution of separate sexes is hypothesized to occur through distinct pathways involving few large-effect or many small-effect alleles. However, we lack empirical evidence for how these different genetic architectures shape the transition from quantitative variation in sex expression to distinct male and female phenotypes. To explore these processes, we leveraged the recent transition of Amaranthus tuberculatus to dioecy within a predominantly monoecious genus, along with a sex-phenotyped population genomic dataset, and six newly generated chromosome-level haplotype phased assemblies. We identify a ~3 Mb region strongly associated with sex through complementary SNP genotype and sequence-depth-based analyses. Comparative genomics of these proto-sex chromosomes within the species and across the Amaranthus genus demonstrates remarkable variability in their structure and genic content, including numerous polymorphic inversions. No such inversion underlies the extended linkage we observe associated with sex determination. Instead, we identify a complex presence/absence polymorphism reflecting substantial Y-haplotype variation-structured by ancestry, geography, and habitat-but only partially explaining phenotyped sex. Just over 10% of sexed individuals show phenotype-genotype mismatch in the sex-linked region, and along with observation of leakiness in the phenotypic expression of sex, suggest additional modifiers of sex and dynamic gene content within and between the proto-X and Y. Together, this work reveals a complex genetic architecture of sex determination in A. tuberculatus characterized by the maintenance of substantial haplotype diversity, and variation in the expression of sex.

Haplotypes↗

PubMed2025

Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.

INTRODUCTION: Stem rust (SR), caused by Puccinia graminis f. sp. tritici (Pgt), remains a major threat to global barley production, particularly in regions with conducive environments and evolving pathogen populations. Despite progress in understanding seedling resistance, adult plant resistance (APR) to SR remains underexplored in diverse barley germplasm. This study aimed to dissect the genetic architecture of APR to SR in a panel of diverse origins of two-row spring barley using a genome-wide association study (GWAS). METHODS: A total of 273 barley accessions were evaluated for APR to SR in two distinct environments in Kazakhstan. Phenotypic data were combined with high-density SNP genotyping to perform GWAS using five statistical models (GLM, MLM, MLMM, FarmCPU, and BLINK). Population structure and kinship were accounted for to identify robust marker-trait associations (MTAs), followed by haplotype-based QTL delineation. Transcriptomic data from 16 barley tissues were used to identify candidate genes within major QTL regions. Substantial phenotypic variation in SR severity was observed across environments. RESULTS: A total of 204 MTAs were identified, among which 96 were stable across models, resulting in 19 model-stable QTLs spanning all seven barley chromosomes. Six QTLs co-localized with known SR-resistance QTLs and genes, including Rpg1 and Rpg6. Q_rpg_7H.1 (coinciding with Rpg1) was one of the strongest and most consistent QTL, harboring 42 highly expressed candidate genes. A novel major-effect QTL on chromosome 5H, Q_rpg_5H.1 (3.5 - 9.9 Mb), not previously associated with known resistance loci, contained 10 highly expressed genes grouped into three co-expression clusters, including WRKY transcription factors and PR-5 proteins. CONCLUSION: This study provides new insights into the complex, multilayered genetic control of SR resistance in barley. The discovery of both known and novel QTLs offers valuable targets for marker-assisted selection and lays the foundation for breeding durable SR-resistant barley adapted to diverse agroecological conditions.

Hordeum vulgare L.↗

PubMed2026

Rapid CRISPR-based bovine embryo sexing to streamline genotype-informed cattle breeding.

Cattle in vitro fertilisation and embryo transfer programmes increasingly rely on embryo-level selection to accelerate genetic gain, but current sexing and genotyping workflows can be costly, slow and logistically demanding. This study developed an efficient, low-resource workflow for bovine embryo sexing that combines whole genome amplification (WGA) with recombinase polymerase amplification-CRISPR-Cas12a (RPA-Cas12a). It also assessed whether the same WGA biopsy products could be used for downstream single nucleotide polymorphism (SNP) microarray genotyping. A one-tube RPA-Cas12a assay targeting the bovine Y-chromosome S4 repeat was developed for fluorescence and lateral flow assay (LFA) readouts. Analytical sensitivity was assessed using serially diluted bovine genomic DNA (gDNA), and breed robustness was tested using male and female gDNA from five major beef breeds and Holstein cattle. The workflow was then applied to WGA products from 22 bovine blastocyst biopsies, with sex calls validated against an established real-time PCR melt curve assay and 100K SNP microarray genotyping. The assay detected male bovine gDNA down to 100 pg using both fluorescence and LFA readouts, with no signal from female gDNA. Male-specific detection was consistent across all breeds tested. All WGA-RPA-Cas12a sex calls from blastocyst biopsies were concordant with real-time PCR and SNP microarray sex calls, and WGA biopsy products produced genome-wide SNP call rates above 85%. This workflow provides a practical approach for rapid bovine embryo sex triage and could reduce unnecessary cryopreservation and genotyping while improving the efficiency of genotype-informed cattle breeding programmes.

Bovine embryo↗

PubMed2025

Manipulating seasonality by using PMSG and Kisspeptin hormones and the impact of the MTNR1A gene on reproduction efficiency in ewes.

BACKGROUND: One of the most important problems in sheep is seasonal anestrus, which limits the reproductive efficiency of the sheep. Estrous synchronization is considered the first plan for reproductive performance in sheep due to the pregnancy time is limited, and parturition as well as an increase in twining and reached good genetic characteristics. AIM: This study aimed to manipulate seasonality that limits fertility in ewes by induction estrus during seasonal anestrous in sheep by using Pregnant Mare Serum Gonadotropin (PMSG), Kisspeptin hormone, and study the impact of MTNR1A gene on reproduction efficiency in ewes. METHODS: This study examined 36 Awassi ewes divided into two groups, each containing 18 ewes, 2-3 years old, and two fertile rams aged 3-4 years and weighing 60-65 kg. All non-pregnant ewes were synchronized using vaginal sponges (60 mg Medroxy Progesterone acetate) for 10 days. The injection of treatment when sponges are draws. The first group (G1) received 500 IU of PMSG injection, and the second group (G2) injection a Kisspeptin hormone 5 μg/kg B.W. RESULTS: The results showed the G1 treated by PMSG 500IU were higher significantly (p ≤ 0.05) of estrus response, induction estrus and pregnancy (89%, 89%, and 89%), respectively, comparative with G2 treated by (Kisspeptin 5 mg/kg) were (72%, 72%, and 66%), respectively, and non-significant changes in estrus were observed in all groups. The average peripheral progesterone concentration significantly increased from day 0 to 5th month in G1 comparative with G2 in pregnant ewes. Serum progesterone levels were significantly p < 0.05 during of 4th month in G1 treatment by (PMSG 500IU) compared with day 0 and all other months during pregnancy of ewes. The average days to lambing in genotypes CT and TT (150 ± 2.5 and 152 ± 3.5 days), respectively, were significant comparative with CC genotype; however, the litter size and lambing rate observed in the enrolled ewes were non-significant in all genotypes. CC, CT, and TT represent three possible genotypes at a specific location (locus) in the genome, often referring to a single nucleotide polymorphism (SNP). These genotypes indicate the combination of alleles an individual inherits from their parents for a particular gene. They refer to the presence of two alleles for a particular nitrogenous base: C and T are nitrogenous bases: C = Cytosine and T = Thymine. CONCLUSION: In conclusion, the application of PMSG and Kisspeptin was effective in achievement good higher significantly of reproduction efficiency in this study. The genotypes CT and TT of the MTNR1A gene polymorphism were connected with a short significant of days to lambing in genotypes.

Animals↗

PubMed2026

Scalable medium-density genotyping platforms for cultivar identification, pedigree authentication, marker-assisted and genomic selection, and other applications in strawberry.

A broad spectrum of high-density genotyping approaches, including single-nucleotide polymorphism (SNP) arrays, genotyping-by-sequencing, and whole-genome reduced-representation sequencing, have been shown to perform well in strawberry (Fragaria × ananassa), despite the inherent complexity of the octoploid genome. While these approaches are effective, their routine deployment in breeding programs can be constrained by cost, computational requirements, and workflow complexity. In parallel, many breeding programs continue to rely on locus-specific assays for marker-assisted selection, resulting in fragmented and inefficient genotyping strategies. Here, we describe medium-density amplicon-based genotyping platforms for strawberry designed to provide cost-effective, turnkey solutions that integrate markers used for marker-assisted selection with genome-wide markers suitable for genomic prediction in a single laboratory assay. These platforms were developed by targeting 1,650 or 4,811 target SNPs via amplicon sequencing, and are interoperable with existing high-density genotyping resources, including a widely used 50K SNP array, thereby facilitating data integration across platforms. We benchmarked their performance relative to the 50K SNP array across breeding-relevant applications, including identity and purity testing, pedigree authentication, marker-assisted selection, and genomic selection, and further evaluated the feasibility of genotype imputation to enhance genome-wide information content. Across analyses, the 1,650- and 4,811-amplicon platforms produced results comparable to higher-density platforms while substantially reducing genotyping cost and analytical overhead. This work demonstrates that targeted amplicon-based genotyping can support efficient, scalable, and integrated genome-informed breeding, enabling the routine application of both marker-assisted and genomic selection within strawberry breeding workflows. Open-source R workflows are provided to support streamlined analyses in breeding contexts.

Fragaria↗

PubMed2026

Deep soil layers show the most pronounced genetic variation in wheat root length.

Wheat is one of the most important cereals worldwide, yet significant gaps remain in our understanding of genetic variability in root traits, especially those associated with deeper rooting that support resource acquisition in challenging environments. Root traits are typically controlled by many genes with small effects and often display low heritability. Our aim was to develop a statistical approach to analyse root variation across soil depth and to determine where genetic differences in root intensity are most detectable. An experiment was conducted at the RadiMax semi-field facility, which is designed to measure deep root systems. Five years of phenotypic data recorded each June produced observations from 1500 rows. Each row captured root intensity across the soil profile from 0.6 m to 2.6 m, enabling detailed analysis of vertical root distribution. Across the five years, 513 winter wheat cultivars were grown in the facility, and among those 409 were genotyped with SNP chips. Depth-resolved regression models with random coefficients were used to quantify genetic and non-genetic variation in root intensity across soil depths, while accounting for spatial variation between rows. Random variation within rows was found to be constant across depths. The models showed that genetic variance for cumulative root intensity increased substantially below 1.1 m, with the deepest layers exhibiting the largest differences between wheat lines. Narrow-sense heritability of point measurements peaked at approximately 1.5 m ([Formula: see text]).

Genetic variability↗

PubMed2026

Integration of Morphological and Genome-Wide SNP Data Reveals Regional Diversity in Thai Swamp Buffalo.

Thai swamp buffalo (Bubalus bubalis) are valuable animal genetic resources, but their regional diversity remains incompletely characterized. Morphological records were obtained from 799 buffaloes, and 474 individuals were genotyped using the 90K Axiom® Buffalo SNP Genotyping Array (Thermo Fisher Scientific, Applied Biosystems™, Santa Clara, CA, USA). Qualitative traits included coat color, horn shape, chevron pattern, and hair-whorl distribution, while quantitative characterization covered 30 body measurements. After excluding missing traits, 30 traits adjusted for sex, age, province, and farm from 768 animals were used for morphology-based analyses, which identified regional phenotypic differences but also substantial overlap, consistent with the influence of feeding, management, environment, and local selection on body conformation. Genome-wide SNP analyses indicated a broadly shared genetic background with detectable regional structure, and runs of homozygosity revealed regional differences in genomic autozygosity. The Lower South showed a comparatively strong recurrent-ROH pattern, whereas inference for the Upper South requires caution because of its small genomic sample. Overall, integrating morphology and genome-wide SNP data improves regional characterization, but data-dependent statistics, population-structure estimates, and conservation implications should be interpreted while regarding small sampling and unbalanced data.

Bubalus bubalis↗

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↗

PubMed2026

Evaluation of bone preparation approaches using length-based analysis and targeted sequencing for forensic human identification of historic skeletal remains.

Advances in DNA technology have significantly enhanced the forensic community's ability to develop genetic profiles from unidentified human skeletal remains. However, sampling requires mechanical grinding of hard tissues before DNA isolation. This processing can compromise genetic profiles, particularly in aged bones. We compared the industry-standard pulverization method with an alternative powder-free preparation involving prolonged demineralization and subsequent slicing of 19th-century cortical bone. Data from DNA quantification, STR genotyping, and targeted SNP sequencing were used to evaluate powdered samples versus demineralized slices from paired human bones. Average human DNA yields for pulverized samples and demineralized slices were 0.032 ng and 0.692 ng, respectively. Demineralized slices recovered more amplifiable DNA than traditional homogenization methods (p < 0.05). No pulverized samples produced STR profiles, whereas demineralized slices from the same bone samples yielded partial profiles. Samples underwent DNA repair, library preparation, and hybridization capture using the FORensic Capture Enrichment (FORCE) panel. Applying low-coverage (1X) analysis of high-throughput sequencing (HTS) data, demineralized slices outperformed those prepared by traditional pulverization methods (p < 0.05) and substantially increased the information recovered compared with conventional STR analysis methods. Based on HTS data from pulverized samples, DNA fragment length ranged from 27 to 95 bp, and FORCE SNP recovery was 33.23%. In contrast, for demineralized slices, DNA fragment length ranged from 85 to 114 bp, and FORCE SNP recovery was 83.24%. The required reagents and equipment are typically available in forensic labs, and the workflow outlined herein significantly increases the success of DNA recovery from challenging skeletal samples.

Humans↗

PubMed2026

Predicting risk of ischemic stroke: A transformer model using genomic data.

BACKGROUND AND OBJECTIVE: Ischemic stroke is a leading cause of mortality and long-term disability worldwide. Genetic factors contribute to IS susceptibility, yet conventional polygenic risk score approaches are primarily based on additive effects and may not fully capture non-linear relationships or positional context and interactions among genetic variants. This study aimed to develop and evaluate a transformer-based genomic model incorporating position-wise genotype embedding for IS risk prediction. METHODS: We conducted a genome-wide association study using the UK Biobank dataset to identify IS-associated loci. Gene prioritisation was subsequently performed using tissue-specific expression quantitative trait locus-based Mendelian randomisation and colocalization analyses in whole blood and brain cortex. We then developed a transformer-based model that encoded genotype and SNP-position information using a position-wise embedding layer. Model performance was evaluated across three UK Biobank control definitions and externally assessed in the independent All of Us cohort. Performance metrics included the area under the receiver operating characteristic curve (AUROC), precision, recall, and F1 score. RESULTS: Across the three UK Biobank control definitions, the proposed method achieved the numerically highest discrimination among the evaluated models, with AUROCs of 0.8109, 0.7843, and 0.7468 using MRF-negative, combined, and MRF-positive controls, respectively. In the external All of Us cohort, the proposed method achieved an AUROC of 0.7251 and retained the highest AUROC among the evaluated models. In a separate incident-stroke survival analysis, medium- and high-score groups had hazard ratios of 1.13 and 1.21, respectively, relative to the low-score group. A total of 18 IS-associated loci were identified. Among the tissue-specific MR results, EDEM2 in the brain cortex remained significant after Bonferroni correction, while DCHS2 showed a nominal association. CONCLUSIONS: The proposed transformer-based framework provides a genomic modelling approach that achieved the highest discrimination among the evaluated models in this study and retained comparative performance in an independent external cohort. In further applications, integrating this genomic framework with conventional clinical, lifestyle, and environmental risk factors may support more comprehensive and personalised IS risk assessment. Prospective, population-representative, and multi-ancestry validation will be important to establish its potential role in future prevention-oriented risk management.

Genomics and bioinformatics↗