PLoS Genetics最新文献

{"title":"The association between parental BMI and offspring adiposity: A genetically informed analysis of trios.","authors":"Liam Wright, Gemma Shireby, Tim T Morris, Neil M Davies, David Bann","doi":"10.1371/journal.pgen.1011775","DOIUrl":"10.1371/journal.pgen.1011775","url":null,"abstract":"<p><strong>Background: </strong>Children with obesity are more likely to have parents with obesity than those without. Several environmental explanations have been proposed for this correlation, including foetal programming and parenting practices. However, body mass index (BMI) is a heritable trait; child-parent correlations may reflect direct inheritance of adiposity-related genes. There is some evidence that mothers' BMI associates with offspring BMI net of direct genetic inheritance, consistent with both intrauterine and parenting effects, but this requires replication. Here, we also investigate the role of fathers' BMI as well as offsprings' diet as a mediating factor.</p><p><strong>Methods: </strong>We used Mendelian Randomization (MR) with genetic trio (mother-father-offspring) data from 2,630 families in the Millennium Cohort Study, a UK birth cohort study of individuals born in 2000/02, to examine the association between parental BMI (kg/m2) and offspring birthweight and BMI and diet measured at six-time points between ages 3y and 17y. Paternal and maternal BMI were instrumented with polygenic indices (PGI) for BMI conditioning upon offspring PGI. This allowed us to separate direct and indirect (\"genetic nurture\") genetic effects. We compared these results with associations obtained using standard multivariable regression techniques using phenotypic BMI data only.</p><p><strong>Results: </strong>Mothers' and fathers' BMI were positively associated with offspring BMI to similar degrees. However, in MR analysis, associations between father's BMI and offspring BMI were close to the null. In contrast, mother's BMI was consistent in MR analysis with phenotypic associations. Maternal indirect genetic effects were between 25-50% the size of direct genetic effects. There was limited and inconsistent evidence of associations with offspring diet and some evidence that mothers', but not fathers', BMI was related to birthweight in both MR and multivariable regression models.</p><p><strong>Conclusions: </strong>Results suggest maternal BMI may be particularly important for offspring BMI: associations may arise due to both direct transmission of genetic effects and indirect (genetic nurture) effects. Associations of father's and offspring adiposity that do not account for direct genetic inheritance may yield biased estimates of paternal influence. Larger studies are required to confirm these findings.</p>","PeriodicalId":49007,"journal":{"name":"PLoS Genetics","volume":"21 8","pages":"e1011775"},"PeriodicalIF":3.7,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12324121/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144790520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pathway polygenic risk scores (pPRS) for the analysis of gene-environment interaction.","authors":"W James Gauderman, Yubo Fu, Bryan Queme, Eric Kawaguchi, Yinqiao Wang, John Morrison, Hermann Brenner, Andrew Chan, Stephen B Gruber, Temitope Keku, Li Li, Victor Moreno, Andrew J Pellatt, Ulrike Peters, N Jewel Samadder, Stephanie L Schmit, Cornelia M Ulrich, Caroline Um, Anna Wu, Juan Pablo Lewinger, David A Drew, Huaiyu Mi","doi":"10.1371/journal.pgen.1011543","DOIUrl":"10.1371/journal.pgen.1011543","url":null,"abstract":"<p><p>A polygenic risk score (PRS) is used to quantify the combined disease risk of many genetic variants. For complex human traits there is interest in determining whether the PRS modifies, i.e. interacts with, important environmental (E) risk factors. Detection of a PRS by environment (PRS x E) interaction may provide clues to underlying biology and can be useful in developing targeted prevention strategies for modifiable risk factors. The standard PRS may include a subset of variants that interact with E but a much larger subset of variants that affect disease without regard to E. This latter subset will dilute the underlying signal in former subset, leading to reduced power to detect PRS x E interaction. We explore the use of pathway-defined PRS (pPRS) scores, using state of the art tools to annotate subsets of variants to genomic pathways. We demonstrate via simulation that testing targeted pPRS x E interaction can yield substantially greater power than testing overall PRS x E interaction. We also analyze a large study (N = 78,253) of colorectal cancer (CRC) where E = non-steroidal anti-inflammatory drugs (NSAIDs), a well-established protective exposure. While no evidence of overall PRS x NSAIDs interaction (p = 0.41) is observed, a significant pPRS x NSAIDs interaction (p = 0.0003) is identified based on SNPs within the TGF-β/ gonadotropin releasing hormone receptor (GRHR) pathway. NSAIDS is protective (OR=0.84) for those at the 5th percentile of the TGF-β/GRHR pPRS (low genetic risk, OR), but significantly more protective (OR=0.70) for those at the 95th percentile (high genetic risk). From a biological perspective, this suggests that NSAIDs may act to reduce CRC risk specifically through genes in these pathways. From a population health perspective, our result suggests that focusing on genes within these pathways may be effective at identifying those for whom NSAIDs-based CRC-prevention efforts may be most effective.</p>","PeriodicalId":49007,"journal":{"name":"PLoS Genetics","volume":"21 8","pages":"e1011543"},"PeriodicalIF":3.7,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12352875/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144790519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recombination plasticity in response to temperature variation in reptiles.","authors":"Laura González-Rodelas, Cristina Marín-García, Clara Romero, Gala Pujol, Laia Marín-Gual, Lukáš Kratochvíl, Aurora Ruiz-Herrera","doi":"10.1371/journal.pgen.1011772","DOIUrl":"10.1371/journal.pgen.1011772","url":null,"abstract":"<p><p>The survival of species depends on their ability to adapt to environmental changes. While organisms are known to activate common transcriptional pathways in response to temperature variations, the impact of temperature on recombination, a key source of genetic variability, remains largely unexplored. Previous studies in model species have shown that the frequency of recombination during meiotic prophase I can be influenced by extreme temperatures. Yet, it remains unclear whether this effect is also conserved in non-model vertebrates. In this study, we investigated the effect of temperature on recombination in the Guibé's ground gecko (Paroedura guibeae), an ectotherm species. We analyzed the formation of double-strand breaks (DSBs) and crossovers (COs) by immunolocalizing the meiotic proteins involved in these processes. Furthermore, we determined the frequency and chromosomal location of COs and the levels of CO interference (COI). Our findings show the presence of hyper-COs spermatocytes in individuals exposed to both high and low temperatures. Notably, this significant increase in COs was associated with a decrease in chromosome axis lengths and elevated levels of meiotic DSBs in later stages of prophase I. In conclusion, our results provide new insights into the effects of environmental temperatures on meiotic recombination in ectothermic species, underscoring the intricate interplay between environmental factors and genetic processes.</p>","PeriodicalId":49007,"journal":{"name":"PLoS Genetics","volume":"21 8","pages":"e1011772"},"PeriodicalIF":3.7,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12342296/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144785769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond recombination: Exploring the impact of meiotic frequency on genome-wide genetic diversity.","authors":"Louis Ollivier, Brian Charlesworth, Fanny Pouyet","doi":"10.1371/journal.pgen.1011798","DOIUrl":"10.1371/journal.pgen.1011798","url":null,"abstract":"<p><p>An important aim of population genetics is to elucidate the processes affecting genetic diversity across regions of the genome and across species. Canonical population genetic models of sexually reproducing species define the rate of meiotic recombination in terms of the frequency of recombination events per site per sexual generation. This paper studies the interplay of several factors with respect to their effects on neutral genetic diversity in a facultatively sexual, diploid, unicellular species such as yeast. The relevant factors are the prevalence of meiosis versus mitosis, the recombination rate, and the selection and dominance coefficients at loci under positive selection. We assume that many generations of mitotic cell divisions are interspersed with episodes of sexual reproduction, in which all individuals in the population undergo meiosis, followed by random matings among the resulting gametes. Our findings reveal that a single hard selective sweep can reduce neutral nucleotide site diversity across the entire genome, provided that the frequency of meiotic events is sufficiently low, and that the effects of a selective sweep on levels of neutral diversity at sites linked to the target of selection can be markedly different from those predicted by standard models of sweeps based on obligate sexuality. Species that reproduce by facultative sex are thus likely to exhibit unusual patterns of genetic diversity.</p>","PeriodicalId":49007,"journal":{"name":"PLoS Genetics","volume":"21 8","pages":"e1011798"},"PeriodicalIF":3.7,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12408092/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144785768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Activation of Pvt1b isoform contributes to local Pvt1 abundance to repress Myc during stress.","authors":"Qiao Li, Christiane E Olivero, Erin Floyd, Jane Ding, Emily Dangelmaier, James Knight, Nadya Dimitrova","doi":"10.1371/journal.pgen.1011790","DOIUrl":"10.1371/journal.pgen.1011790","url":null,"abstract":"<p><p>Many long noncoding RNA (lncRNA) loci harbor multiple alternative isoforms. It is not known whether isoform-specific sequence elements enable distinct functions. Previous work identified two alternative transcription start site (TSS) isoforms in the Pvt1 lncRNA locus - the constitutively expressed Pvt1a and the stress-induced Pvt1b. While the function of Pvt1a is not known, the p53-regulated Pvt1b was shown to act locally to repress the transcription of the neighboring Myc proto-oncogene in response to genotoxic and oncogenic stress. Here, we investigated whether Pvt1b contains isoform-specific repressive sequence elements. Our results revealed that Pvt1b contributes to but is not required for Myc repression. Using in vivo and in vitro models of genotoxic and oncogenic stress, we observed that Pvt1a compensates for Pvt1b loss, resulting in Pvt1b deficiency having a moderate effect on Myc regulation, stress response, and tumor suppression. Long-read sequencing exposed a diversity of stress-induced Pvt1a and Pvt1b isoforms, further arguing against a specialized role for Pvt1b. We propose that p53-induced increase in total Pvt1 abundance, and not isoform-specific activation, represses Myc during stress.</p>","PeriodicalId":49007,"journal":{"name":"PLoS Genetics","volume":"21 7","pages":"e1011790"},"PeriodicalIF":3.7,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12312954/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144761996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced genetic fine mapping accuracy with Bayesian Linear Regression models in diverse genetic architectures.","authors":"Merina Shrestha, Zhonghao Bai, Tahereh Gholipourshahraki, Astrid J Hjelholt, Sile Hu, Mads Kjolby, Palle Duun Rohde, Peter Sørensen","doi":"10.1371/journal.pgen.1011783","DOIUrl":"10.1371/journal.pgen.1011783","url":null,"abstract":"<p><p>We evaluated Bayesian Linear Regression (BLR) models with BayesC and BayesR priors as statistical genetic fine-mapping tools, comparing their performance to established methods such as FINEMAP and SuSiE. Through extensive simulations and analyses of UK Biobank (UKB) phenotypes, we assessed F1 classification scores and predictive accuracy across models. Simulations encompassed diverse genetic architectures varying in polygenicity, heritability, causal SNP proportions, and disease prevalence. In the empirical analyses, we used over 6.6 million imputed SNPs and phenotypic data from more than 335,000 UKB participants. Our results show that BLR models, particularly those using the BayesR prior, consistently achieved higher F1 scores than the external methods, but having comparable predictive accuracy. Applying the BLR model at the region-wide level generally yielded better F1 scores than the genome-wide approach, except for traits with high polygenicity. These findings highlight BLR models as accurate and robust tools for statistical fine mapping in both simulated and empirical genetic datasets.</p>","PeriodicalId":49007,"journal":{"name":"PLoS Genetics","volume":"21 7","pages":"e1011783"},"PeriodicalIF":3.7,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12327644/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144754865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of hub gene associated with colorectal cancer: Integrating Mendelian randomization, transcriptome analysis and experimental verification.","authors":"Yu Zhang, Xu Han, Yichun Yang, Jiayan Ren, Zixi Zhang, Yanmin Zhang, Qi Su, Dake Chu","doi":"10.1371/journal.pgen.1011788","DOIUrl":"10.1371/journal.pgen.1011788","url":null,"abstract":"<p><strong>Background: </strong>Colorectal cancer (CRC) is a prevalent malignancy with significant mortality rates globally. Understanding the genetic and molecular mechanisms underlying CRC development is crucial for improving therapeutic strategies.</p><p><strong>Method: </strong>In this study, we utilized cis-eQTL summary data to identify genes potentially causally associated with CRC. The expression levels of candidate genes in tumor and normal tissues were compared using the GEPIA2 database. The correlations between FUT8 expression and cellular functions, tumor mutation burden, immune checkpoint genes, and immune infiltration were analyzed. Molecular docking was performed to identify potential drugs targeting FUT8, and the effects of the selected drug on cell proliferation were evaluated using the MTT assay. Additionally, the cellular thermal shift assay (CETSA) was employed to assess the interaction between the drug and the target protein.</p><p><strong>Results: </strong>We identified 19 genes with eQTLs potentially associated with CRC, among which six eQTLs were associated with increased CRC risk, including FUT8. FUT8 was significantly overexpressed in CRC tumor tissues and correlated with various cellular functions such as stemness, invasion, EMT, and metastasis. Higher FUT8 expression was associated with higher tumor mutation burden and significant correlations with multiple immune checkpoint genes. Molecular docking identified VE-822 as a promising drug candidate targeting FUT8, which demonstrated inhibitory effects on CRC cell proliferation. The CETSA results indicated that VE ‒ 822 could bind to FUT8 and improve its thermal stability.</p><p><strong>Conclusion: </strong>FUT8 is a crucial gene that causes colon cancer and is linked to tumour immunity. VE-822 is a promising candidate for treating CRC by targeting FUT8.</p>","PeriodicalId":49007,"journal":{"name":"PLoS Genetics","volume":"21 7","pages":"e1011788"},"PeriodicalIF":3.7,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12349882/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144745643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic inference of on-target and off-target side-effects of antipsychotic medications.","authors":"Andrew R Elmore, Aws Sadik, Lavinia Paternoster, Golam M Khandaker, Tom R Gaunt, Gibran Hemani","doi":"10.1371/journal.pgen.1011793","DOIUrl":"10.1371/journal.pgen.1011793","url":null,"abstract":"<p><p>It is often difficult to ascertain whether patient-reported side-effects are caused by a drug, and if so, through which mechanism. Adverse side-effects are the primary cause of antipsychotic drug discontinuation rather than poor efficacy. Using a novel method combining genetic and drug binding affinity data, we investigated evidence of causal mechanisms for 80 reported side-effects of 6 commonly prescribed antipsychotic drugs which together target 68 receptors. We analysed publicly available drug binding affinity data and genetic association data using Mendelian randomization and genetic colocalization to devise a representative 'score' for each combination of drug, side-effect, and receptor. We show that 36 side-effects are likely caused by drug action through 30 receptors, which are mainly attributable to off-target effects (26 off-target receptors underlying 39 side-effects). This method allowed us to distinguish which reported side-effects have evidence of causality. Of individual drugs, clozapine has the largest cumulative side-effect profile (Score = 57.5, SE = 11.2), and the largest number of side-effects (n = 36). We show that two well-known side-effects for clozapine, neutropenia and weight change, are underpinned by the action of GABA and CHRM3 receptors respectively. Our novel genetic approach can map side-effects to drugs and elucidate underlying mechanisms, which could potentially inform clinical practice, drug repurposing, and pharmacological development. Further, this method can be generalized to infer the on-target and off-target effects of drugs at any stage of the drug development pipeline.</p>","PeriodicalId":49007,"journal":{"name":"PLoS Genetics","volume":"21 7","pages":"e1011793"},"PeriodicalIF":3.7,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12321077/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144734498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel insights into post-myocardial infarction cardiac remodeling through algorithmic detection of cell-type composition shifts.","authors":"Brian Gural, Logan Kirkland, Abigail Hockett, Peyton Sandroni, Jiandong Zhang, Manuel Rosa-Garrido, Samantha K Swift, Douglas J Chapski, Michael A Flinn, Caitlin C O'Meara, Thomas M Vondriska, Michaela Patterson, Brian C Jensen, Christoph D Rau","doi":"10.1371/journal.pgen.1011807","DOIUrl":"10.1371/journal.pgen.1011807","url":null,"abstract":"<p><p>Interpreting bulk RNA sequencing from heterogeneous tissues like the post-myocardial infarction (MI) heart is confounded by dynamic changes in cell-type composition. To address this, we developed a computational approach using single-nucleus RNA sequencing (snRNA-seq) references to estimate and correct for cell-type abundance shifts in bulk transcriptomic data. We applied this method to analyze infarct border zone transcriptomes from wild-type (WT) and cardiomyocyte-specific α1A-adrenergic receptor knockout (cmAKO) mice subjected to MI via left coronary artery ligation or sham surgery. Our analysis revealed exaggerated cardiomyocyte loss and fibroblast gain in cmAKO mice post-MI compared to WT, implicating α1A-ARs in maintaining cellular homeostasis. We then demonstrate the confounding effect of composition changes though simulations: a modest 10% change in the major cell type's abundance caused over 20% of transcripts to appear as differentially expressed genes (DEGs) when composition was ignored. Applying our correction method refined the interpretation of MI-induced transcriptomic changes, attributing many apparent DEGs, particularly those related to metabolism and inflammation, to shifts in cell abundance rather than direct transcriptional regulation. Importantly, the correction also unveiled previously masked biological processes associated with the cmAKO-specific response to MI, including pathways related to cell adhesion, cell cycle regulation, and stress response, highlighting potential intrinsic mechanisms of α1A-AR cardioprotection. RNAscope validation supported the composition-aware findings for key genes. This work presents a robust method for dissecting bulk RNA-seq data from complex tissues and provides refined insights into the cellular and molecular roles of cardiomyocyte α1A-ARs during cardiac injury and remodeling.</p>","PeriodicalId":49007,"journal":{"name":"PLoS Genetics","volume":"21 7","pages":"e1011807"},"PeriodicalIF":3.7,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12309993/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144709626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel expectation-maximization approach to infer general diploid selection from time-series genetic data.","authors":"Adam G Fine, Matthias Steinrücken","doi":"10.1371/journal.pgen.1011769","DOIUrl":"10.1371/journal.pgen.1011769","url":null,"abstract":"<p><p>Detecting and quantifying the strength of selection is a major objective in population genetics. Since selection acts over multiple generations, many approaches have been developed to detect and quantify selection using genetic data sampled at multiple points in time. Such time-series genetic data is commonly analyzed using Hidden Markov Models, but in most cases, under the assumption of additive selection. However, many examples of genetic variation exhibiting non-additive mechanisms exist, making it critical to develop methods that can characterize selection in more general scenarios. Here, we extend a previously introduced expectation-maximization algorithm for the inference of additive selection coefficients to the case of general diploid selection, in which the heterozygote and homozygote fitness are parameterized independently. We furthermore introduce a framework to identify bespoke modes of diploid selection from given data, a heuristic to account for variable population size, and a procedure for aggregating data across linked loci to increase power and robustness. Using extensive simulation studies, we find that our method accurately and efficiently estimates selection coefficients for different modes of diploid selection across a wide range of scenarios; however, power to classify the mode of selection is low unless selection is very strong. We apply our method to ancient DNA samples from Great Britain in the last 4,450 years and detect evidence for selection in six genomic regions, including the well-characterized LCT locus. Our work is the first genome-wide scan characterizing signals of general diploid selection.</p>","PeriodicalId":49007,"journal":{"name":"PLoS Genetics","volume":"21 7","pages":"e1011769"},"PeriodicalIF":3.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12310050/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144692185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}