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At least 19 recordsLinked to original sources
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↗
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↗
PubMed1976

Genotype x environment interactions. IV. The effect of the background genotype.

Experimental evidence from sternopleural chaeta number and yield of offspring in Drosophila melanogaster bears out the expectation (Mather, 1975) that the value of the regression of g, measuring genotype X environment interaction, on e, measuring the overall effect of environmental change , depends on genes in which the contrasting genotypes are alike as well as on the genes in which they differ. With yield of offspring there is evidence of some genotypes reacting to the environmental changes in the opposite direction to others.

Chromosomes↗
PubMed1975

An empirical method of grouping genotypes based on a linear function of the genotype-environment interaction.

The regression approach for analysing genotype-environmental interaction is extended to include the grouping of genotypes. An unweighted pair-group cluster analysis was applied to a special dissimilarly index, derived from the test statistic for differences among regressions. The resulting groups reflect the general pattern of response to the various environments. The data of Yates and Cochran (1938) were used to illustrate the clustering process.

Environment↗
PubMed2026

Genotype-dependent DNA methylation patterns are negatively associated with allelic variation rather than heat-induced gene expression in two contrasting potato genotypes.

Potato (Solanum tuberosum L.) is an important food crop that is sensitive to high temperatures, which cause major changes in the transcriptome and a reduction in yield. In several plant species, DNA methylation has been reported to influence gene expression, particularly under abiotic stress conditions. However, the role of DNA methylation in regulating gene expression in heat-tolerant and heat-sensitive potato genotypes is still poorly understood. In this study, we conducted genome-wide DNA methylome and transcriptome analyses of leaves from two contrasting potato cultivars, Annabelle (moderately heat-tolerant) and Camel (heat-sensitive), before and after heat stress (HS). Genome-wide differential methylation analysis revealed that most identified differentially methylated regions (DMRs) were constitutive, reflecting variation between cultivars rather than being induced by HS. While thousands of heat-responsive differentially expressed genes (DEGs) were identified, only a small fraction coincided with heat-induced DMRs. Despite substantial constitutive DNA methylation and transcriptome differences between the cultivars, we found no consistent association between DMRs and DEGs, indicating that DNA methylation does not play a widespread direct regulatory role in gene expression. Surprisingly, hypermethylated genomic regions were associated with lower alternative allele frequencies, whereas hypomethylated regions showed the opposite trend. These findings indicate that the potato DNA methylome is largely stable under HS and that constitutive DNA methylation variation contributes rather to genetic diversity than to the direct regulation of gene expression.

DNA Methylation↗
PubMed1975

Demonstration of the Rhesus haplotype CdE (r-y) in the genotype of 48 subjects from 8 families. Genotype CdE/CdE (r-yr-y) in 2 members of the same family.

Forty-eight individuals heterozygous for CdE (R-Y) haplotype were identified in the pedigrees of 8 kindreds containing 128 members. Two homozygotes CdE/CdE (r-yr-y) were found in a large inbred kindred. Our study among French blood donors of the Seine-Maritime region demonstrated that about one of two individuals possessing the Rhesus phenotype CcdEd (rh'rh') carried the CdE (r-y) haplotype.

Chromosomes↗
PubMed2026

Pedigree-assisted genotype imputation enables cost-effective genomic prediction in Penaeus vannamei.

Genomic selection in Penaeus vannamei has long been constrained by the high cost of dense genotyping. To address this limitation, we evaluated genotype imputation from a low-density 1&#xa0;K panel to a medium-density 55&#xa0;K panel of the "Yellow Sea Array No. 1" and examined its impact on genomic prediction for harvest body weight in P. vannamei. A four-generation pedigree including 30 great-grandparents, 39 grandparents, 100 parents, and 608 offspring was genotyped using the 55&#xa0;K panel. A two-step experimental design was implemented to (i) assess the performance of different imputation algorithms under reference population scenarios with varying proportions of siblings, and (ii) compare six alternative reference population structures incorporating parents, ancestors, and siblings. Genotype imputation using the pedigree-based method FImpute v3.0 consistently achieved higher accuracy than the population-based method Beagle v5.5. Using this pedigree-assisted approach, imputation accuracy increased from 0.73 when only parental genotypes were used to 0.84 with the inclusion of 10% siblings, and subsequently plateaued at 0.87-0.90 when sibling representation reached 20%. Across the six reference population structures, imputation accuracy was primarily driven by the availability of parental genotypes, ranging from 0.50 to 0.56 in the absence of parents to 0.88-0.89 when both parents and ancestral generations were included. Accuracy remained high when both parents were available (0.84-0.87 with siblings; 0.73 without siblings) but declined substantially when only one parent was genotyped (0.65-0.68). Imputation accuracy was positively associated with both minor allele frequency (MAF) and linkage disequilibrium (max r2LD), with LD exerting the stronger influence. Heritability estimates derived from imputed 55&#xa0;K genotypes were highly consistent with those obtained from the original 55&#xa0;K data (0.39&#x2009;&#xb1;&#x2009;0.14 vs. 0.41&#x2009;&#xb1;&#x2009;0.14), indicating that genotype imputation did not compromise variance component estimation. In predictive ability analyses, pedigree-based BLUP (PBLUP) achieved higher predictive ability than genomic BLUP (GBLUP) based on the 1&#xa0;K panel, with predictive abilities of 0.42-0.44 for PBLUP compared with 0.34-0.35 for GBLUP. Using imputed genotypes for genomic prediction further improved predictive ability relative to the true 1&#xa0;K panel, yielding values ranging from 0.35 to 0.47. Notably, when parental genotypes were included in the reference population, GBLUP based on imputed genotypes surpassed the predictive ability of PBLUP and approached that achieved with the original 55&#xa0;K genotypes (0.45-0.47). Collectively, these results provide the first empirical evidence that low- to medium-density genotype imputation, combined with pedigree information, can effectively support genomic prediction in P. vannamei. This study establishes a cost-efficient and scalable framework for implementing genomic selection in P. vannamei and provides a practical reference for the application of genomic selection in other aquaculture species with constrained breeding budgets.

Animals↗
PubMed2025

Human papillomavirus (HPV) genotypes extended prevalence in the female population from a city in Northern Chile.

BACKGROUND: Cervical cancer is primarily associated with the presence of human papillomavirus (HPV), with high-risk genotypes HPV-16 and HPV-18 being the focus of vaccination programs in developing countries such as Chile. Preventive screening for cervical cancer in women aged 25 to 64 years remains centered on cytological techniques and is primarily performed based on clinical suspicion of cervical lesions. However, extended screening for HPV genotypes using DNA amplification methods is not routinely applied to the Chilean female population yet. This study aimed to determine the prevalence of high- and low-risk HPV genotypes in women without known risk factors in a city in northern Chile. METHODS: Cervicovaginal brushing samples were obtained from 390 women from Antofagasta city, Northern Chile, aged between 25 and 64 years; genomic DNA was extracted, and multiplex real-time PCR analysis was used to identify a larger group of high- and low-risk HPV genotypes. RESULTS: Among 390 samples, HPV prevalence was 36.9%, of which 54.9% were high-risk genotypes, 18.7% were low-risk genotypes, and 26.4% showed mixed infection with both high- and low-risk genotypes. High-risk genotypes 16, 58, 39, and 31 were the most frequently identified among HPV-positive samples. Furthermore, a significant association was observed between HPV presence and both age and suspicion of cervical alteration, and women testing positive for other sexually transmitted infections (STIs) were more likely to acquire HPV. CONCLUSIONS: Implementing a screening program that incorporates extended HPV genotyping in Chile, including testing for high-risk genotypes 16, 18, 31, 39, and 58, is crucial to optimize control, early detection, and vaccination efforts for Chilean circulating HPV genotypes that are not covered by the actual vaccine, thus contributing to a more effective reduction in the burden of disease associated with the virus.

Humans↗
PubMed2025

Frequency and Distribution of KIR Genotypes of Donors-Recipient Pairs in the Haploidentical Haematopoietic Stem Cell Transplantation Setting: Collaborative Study by the Spanish Working Group in Histocompatibility and Transplant Immunology (GETHIT) and the Spanish Haematopoietic Transplantation and Cell Therapy Group (GETH-TC).

There is limited information regarding the influence of KIR genotype, compared to the HLA system, in haploidentical haematopoietic stem cell transplantation (haplo-HSCT). This study aimed to determine the frequencies of KIR genotypes in Spanish haematologic patients undergoing haplo-HSCT. A study was conducted on 113 oncohaematological patients and their donors, treated across five centres that are members of the Spanish Working Group in Histocompatibility and Transplant Immunology (GETHIT) and the Spanish Haematopoietic Transplantation and Cell Therapy Group (GETH-TC). KIR typing was performed using PCR-rSSO or PCR-SSP. KIR genotypes were identified using the KIR Allele Frequency Net Database. Among donors, the most frequent KIR genotypes were Type 1 (28.3%), Type 2 (12.4%) and Type 4 (10.6%). In patients, Genotypes 1 (23.9%), 4 (23%) and 2 (14.2%) were most prevalent. Donors exhibited AA centromeric (46%) and telomeric (59.3%) types, while patients had a higher AB centromeric frequency (52.2%). Differences were observed in the BB centromeric type (3.5% patients; 16.8% donors, p&#x2009;=&#x2009;0.002). The AB KIR genotype was the most common (70.8% donors; 75.2% patients). Most were classified as 'neutral' (61.9% donors; 73.5% patients). B-content score1 was the most common (48.7% patients; 33.6% donors). Notably, classification as best was rare (2.7% patients; 16.8% donors, p&#x2009;=&#x2009;0.002). The study highlights the distribution of KIR genotypes in haplo-HSCT patients and donors, with Genotypes 1, 2 and 4 being the most prevalent. AB KIR genotypes and B-content score 1 were dominant. Moreover, KIR genotypes ID may serve as criteria for future investigation about the immunogenetic predisposition to malignant haematological diseases.

Humans↗
PubMed2026

LAML-Pro: joint maximum likelihood inference of cell genotypes and cell lineage trees.

MOTIVATION: Recent dynamic lineage tracing technologies use genome editing to induce heritable mutations, or edits, that accumulate across successive cell divisions. These edits are measured using single-cell sequencing or imaging, providing data to reconstruct cell lineages at single-cell resolution. Current computational approaches to infer cell lineage trees, or phylogenies, from these data perform two separate steps: (i) Identify each cell's edits (genotype) from the raw sequencing or imaging data; (ii) Infer a cell lineage tree from the cell genotypes. However, genotyping cells is an inexact process and genotype errors can yield an inaccurate lineage tree. For example, using fluorescence based-imaging to measure edits results in a high fraction (&#x2248;25%-50%) of uncertain or erroneous genotypes. RESULTS: We introduce Lineage Analysis via Maximum Likelihood with PRobabilistic Observations (LAML-Pro), an algorithm that jointly infers cell genotypes and a cell lineage tree. LAML-Pro is based on the Probabilistic Mixed-type Missing Observation (PMMO) model, which we derive to describe both the genome editing and genotype observation processes. LAML-Pro constructs lineage trees from thousands of cells in under an hour by leveraging the sparsity of transitions under the PMMO model. On simulated data, we demonstrate that LAML-Pro corrects genotype errors and infers substantially more accurate trees than existing methods which are vulnerable to genotype errors. Applied to data from two recent imaging-based lineage tracing systems, LAML-Pro reduces genotype errors by 5-fold and produces more spatially coherent lineage trees compared to existing methods. AVAILABILITY AND IMPLEMENTATION: LAML-Pro is implemented in C++ and is available as both a command-line interface and as a Python library at: github.com/raphael-group/LAML-Pro.

Cell Lineage↗
PubMed2026

A droplet digital PCR assay targeting 16 human papillomavirus genotypes.

Background. Cervical screening with high-precision assays such as human papillomavirus (HPV) DNA testing is essential for the detection and treatment of precancerous lesions. HPV genotypes have different oncogenic potential and require different clinical management, illustrating the importance of extended genotyping. HPV quantification has demonstrated clinical relevance in both diagnosis and treatment. Objective. To develop a droplet digital PCR assay for the detection and quantification of 16 HPV genotypes, with comparison to a commercial test and validation on clinical samples. Methods. Primers and probes were designed to target the E6 region of 16 HPV genotypes: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68, 73 and 82. Each target was evaluated to assess performance and reliability using synthetic DNA constructs, quantified international reference standards and clinical screening samples (n=303) genotyped using the Seegene Anyplex II HR HPV Detection assay. Results. Each assay demonstrated high target specificity, without cross-reactivity observed among the HPV genotypes selected. Using international molecular standards, the assay reliably detected high-risk genotypes across serial dilutions, with detection down to the level of one international unit or genome equivalent per microlitre. When applied to clinical samples with and without a histological diagnosis of cervical intraepithelial neoplasia 2 or worse (CIN2+), the assay reliably detected key HPV genotypes, with the exception of 7 of 234 (3%) of HPV-positive samples, all of which exhibited very low viral load. Conclusion. Although previous studies have described digital PCR methods targeting HPV E6, they have typically focused on a limited number of genotypes. This study expands upon existing methodology by introducing a sensitive and specific method for detection and quantification of 16 high-risk and potentially high-risk HPV genotypes.

PCR↗
PubMed2026

LAML-Pro: Joint Maximum Likelihood Inference of Cell Genotypes and Cell Lineage Trees.

MOTIVATION: Recent dynamic lineage tracing technologies use genome editing to induce heritable mutations, or edits, that accumulate across successive cell divisions. These edits are measured using single-cell sequencing or imaging, providing data to reconstruct cell lineages at single-cell resolution. Current computational approaches to infer cell lineage trees, or phylogenies, from these data perform two separate steps: (1) Identify each cell's edits (genotype) from the raw sequencing or imaging data; (2) Infer a cell lineage tree from the cell genotypes. However, genotyping cells is an inexact process and genotype errors can yield an inaccurate lineage tree. For example, using fluorescence based-imaging to measure edits results in a high fraction (&#x2248; 25-50%) of uncertain or erroneous genotypes. RESULTS: We introduce Lineage Analysis via Maximum Likelihood with PRobabilistic Observations (LAML-Pro), an algorithm that jointly infers cell genotypes and a cell lineage tree. LAML-Pro is based on the Probabilistic Mixed-type Missing Observation (PMMO) model, which we derive to describe both the genome editing and genotype observation processes. LAML-Pro constructs lineage trees from thousands of cells in under an hour by leveraging the sparsity of transitions under the PMMO model. On simulated data, we demonstrate that LAML-Pro corrects genotype errors and infers substantially more accurate trees than existing methods which are vulnerable to genotype errors. Applied to data from two recent imaging-based lineage tracing systems, LAML-Pro reduces genotype errors by 5-fold and produces more spatially coherent lineage trees compared to existing methods. AVAILABILITY AND IMPLEMENTATION: LAML-Pro is freely available at: github.com/raphael-group/LAML-Pro.

Journal Article↗
PubMed2026

Addressing lignin composition and content via Arabidopsis arogenate dehydratase knockout and over-expression genotypes.

Following the down-selection of 14 Arabidopsis thaliana arogenate dehydratase (ADT) knockout and over-expression (OE) genotypes, the most highly contrasting quadruple knockout adt3/4/5/6 and ADT OE genotypes were subjected to proteomics, metabolomics, and scanning electron microscopy (SEM) analyses as needed, with results compared to Columbia wild-type (WT). The basal adt3/4/5/6 stem cross-sections, &#x223c;70% lignin content reduced, exhibited buckled vessel cell walls and partially detached xylary fibers, in contrast to WT and ADT4m/5&#x202f;m OE genotypes that did not. Anatomical defects primarily resulted from guaiacyl lignin level reductions in vessels with concomitant increased stem syringyl:guaiacyl (S/G) ratios. Phenylpropanoid and various upstream shikimate-chorismate pathway enzyme abundances, as well as specific monolignol oxidases (laccases/peroxidases), generally increased in adt3/4/5/6&#x202f;at different stem and rosette leaf growth/development stages, relative to WT. Opposite effects were largely observed with the ADT5m OE genotype. By contrast, flavonoid and glucosinolate pathway enzyme amounts varied. Such enzyme abundance increases were overall unproductive as adt3/4/5/6 was unable to restore WT, ADT4 OE, ADT5 OE, ADT5m OE, and ADT4m/5&#x202f;m OE secondary metabolite (lignin, phenylpropanoid, lignan, flavonoid, phenolic acid, and glucosinolate) levels. Conversely, ADT OE genotypes did not significantly increase programmed lignin levels or alter S/G compositions. In sum, proteomics analyses of adt3/4/5/6 and adt5 'perceived' that lignin and low molecular weight secondary metabolite amounts were not at 'programmed' levels as for WT and ADT OE genotypes but observed increases in relevant pathway protein abundances were futile. Notably though, proteomics analyses did not lead to predicting that lignin and associated biochemical pathways would have reduced metabolite levels, relative to WT and ADT OE genotypes. Genotype adt3/4/5/6, possibly the highest lignin level reduced genotype reported, did not utilize other phenolics to compensate. By contrast, the differential temporal and spatial deposition of cell wall oxidases again indicate the exquisite control over lignin deposition, and our lack of knowledge of precise lignin structure and assembly in subcellular regions of the lignified cell walls.

Lignin↗
PubMed2026

Association of Enterocytozoon bieneusi Infection with chronic/persistent diarrhea and ITS genotypic diversity: a hospital-based case-control study in Suburban Shanghai, China.

Enterocytozoon bieneusi is a globally distributed zoonotic enteric pathogen that remains largely overlooked in routine diarrheal disease surveillance. Although previous studies in Shanghai, China, have reported elevated prevalence in diarrheal populations, case-control data from suburban areas at the peri&#x2011;urban interface and the strength of the association between E. bieneusi infection and chronic diarrhea in non-immunocompromised individuals remain poorly characterized. We performed a hospital-based case-control study in suburban Shanghai, enrolling 286 diarrheal outpatients without documented immunodeficiency and 138 asymptomatic controls frequency-matched for age and sex. Fecal specimens were collected and subjected to genomic DNA extraction. E. bieneusi was detected via nested PCR amplification of the ribosomal internal transcribed spacer (ITS) region. Factors associated with infection were identified using multivariate logistic regression. Genotypic diversity and zoonotic potential were assessed by Sanger sequencing and phylogenetic analysis. The overall prevalence of E. bieneusi was 12.2% (35/286) in diarrheal patients, significantly higher than the 2.2% (3/138) observed in asymptomatic controls (P < 0.001). E. bieneusi positivity was independently associated with chronic/persistent diarrhea (adjusted odds ratio = 2.63, 95% confidence interval: 1.25-5.54, P = 0.011). Fourteen distinct ITS genotypes were identified, comprising five known genotypes (D, EbpD, SHW7, Henan-III, and CHG5) and nine novel genotypes (designated SHH2 to SHH10). Thirteen genotypes clustered within Group 1, and one genotype (CHG5) fell within Group 2, two phylogenetic groups that contain genotypes with documented zoonotic potential in global surveillance. E. bieneusi was detected at a relatively high prevalence among diarrheal patients in suburban Shanghai, and its detection was associated with chronic/persistent diarrhea. The predominance of zoonotic genotypes and the identification of nine novel Group 1 genotypes indicate phylogenetic similarity to known zoonotic lineages and warrant further investigation of local zoonotic transmission; no animal or environmental samples were analyzed in this study. These findings suggest that E. bieneusi testing may be considered as part of the differential diagnosis for patients with unexplained chronic/persistent diarrhea and highlight the need for One Health surveillance in the surveyed area.

Diarrhea↗
PubMed2026

Longitudinal characterization of mixed-genotype SARS-CoV-2 infections in a military cohort reveals compartmentalized viral populations.

UNLABELLED: Mixed-genotype severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are a concern due to the potential generation of novel recombinants that give rise to new variants. To better understand intra-host viral dynamics, we analyzed specimens from 24 participants from the U.S. Military Health System's Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential COVID-19 cohort with suspected mixed-genotype SARS-CoV-2 infections. From an initial 24 suspected cases, we confirmed 17 as genuine coinfections and graded them by evidence: 7 were "strong"; 4 were "moderate"; 6 were "weak"; and 7 were deemed unlikely to be true mixed-genotype infections. Access to swabs from multiple body sites across the course of infection allowed us to observe compartmentalization and shifts in variant dominance that would have been missed by a single-timepoint analysis, as well as one recombinant Omicron BA.1/BA.2 genome. By using an evidence-based bioinformatic framework to assess sequencing data from well-characterized clinical cases, we distinguished genuine coinfections from bioinformatic artifacts. Our findings emphasize the importance of both extensive specimen collection and careful bioinformatic approaches in ascertaining dual genotype infections. IMPORTANCE: Novel recombinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) arise from coinfections with different lineages, but mixed infections are not screened for despite risk to public health, and most surveillance relies on single swabs. We analyzed a longitudinal data set with specimens from multiple body sites, providing an opportunity to assess intra-host dynamics. To distinguish true coinfection from bioinformatic artifacts with confidence, we applied a framework that grades evidence for mixed genotypes by incorporating lineage and clade with manually validated variant calls. This allowed investigation beyond abundance levels of mixed genotypes within a single specimen, including observations of compartmentalization and a recombinant virus. This work enables further study of evolutionary, immunological, and clinical implications of mixed SARS-CoV-2 genotypes. Detecting dual-genotype infections and discriminating between true dual-genotype infection vs potential bioinformatics-based artifacts support public health and military readiness. These efforts provide evidence to bolster decision-making in molecular epidemiological studies to track transmission and for the choice of effective countermeasures.

SARS-CoV-2↗
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 &#xd7; 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

Effect of founder breeds on genotype imputation accuracy in Canchim cattle.

UNLABELLED: Genotype imputation is a technique used to infer unobserved genotypes based on reference panels, allowing increased marker density and cost-effective optimization for genomic selection. This study aimed to evaluate whether the inclusion of genotypes from the founder breeds Nelore (NE) and Charolais (CH) improves the imputation accuracy in the composite beef cattle breed Canchim (CA). The populations studied consisted of 804 NE, 897 CH, and 392 CA animals, all genotyped using high-density panels (777,962 SNP &#x2013; single nucleotide polymorphisms). CA animals had their genotypes masked to simulate a medium-density panel (54,609 SNP). Fourteen imputation scenarios were evaluated, varying according to breed, sex, year of birth, and lineage. Imputation accuracy was determined based on the percentage of correctly imputed genotypes (PERC) and the squared Pearson&#x2019;s correlation between observed and imputed genotypes (R2). PERC values ranged from 66.52% to 97.39% and R&#xb2; from 0.6352 to 0.9780. The scenarios that included NE, CH, and CA (males or animals born before 2004) as the reference population for imputing CA females or CA animals born after 2004 showed the highest imputation accuracies. Therefore, the use of founder breeds in the reference population improves the accuracy of genotype imputation in CA cattle. The results indicate that a multibreed reference population, incorporating founder breeds, could provide a more robust and informative genetic basis for imputing composite cattle. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13353-026-01060-z.

Animal breeding↗