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The power to detect linkage disequilibrium with quantitative traits in selected samples.

Results from power studies for linkage detection have led to many ongoing and planned collections of phenotypically extreme nuclear families. Given the great expense of collecting these families and the imminent availability of a dense diallelic marker map, the families are likely to be used in allelic-association as well as linkage studies. However, optimal selection strategies for linkage may not be equally powerful for association. We examine the power to detect linkage disequilibrium for quantitative traits after phenotypic selection. The results encompass six selection strategies that are in widespread use, including single selection (two designs), affected sib pairs, concordant and discordant pairs, and the extreme-concordant and -discordant design. Selection of sibships on the basis of one extreme proband with high or low trait scores provides as much power as discordant sib pairs but requires the screening and phenotyping of substantially fewer initial families from which to select. Analysis of the role of allele frequencies within each selection design indicates that common trait alleles generally offer the most power, but similarities between the marker- and trait-allele frequencies are much more important than the trait-locus frequency alone. Some of the most widespread selection designs, such as single selection, yield power gains only when both the marker and quantitative trait loci (QTL) are relatively rare in the population. In contrast, discordant pairs and the extreme-proband design provide power for the broadest range of QTL-marker-allele frequency differences. Overall, proband selection from either tail provides the best balance of power, robustness, and simplicity of ascertainment for family-based association analysis.

Alleles

Genetic linkage disequilibrium of deleterious mutations in threatened mammals.

The impact of negative selection against deleterious mutations in endangered species remains underexplored. Recent studies have measured mutation load by comparing the accumulation of deleterious mutations, however, this method is most effective when comparing within and between populations of phylogenetically closely related species. Here, we introduced new statistics, LDcor, and its standardized form nLDcor, which allows us to detect and compare global linkage disequilibrium of deleterious mutations across species using unphased genotypes. These statistics measure averaged pairwise standardized covariance and standardize mutation differences based on the standard deviation of alleles to reflect selection intensity. We then examined selection strength in the genomes of seven mammals. Tigers exhibited an over-dispersion of deleterious mutations, while gorillas, giant pandas, and golden snub-nosed monkeys displayed negative linkage disequilibrium. Furthermore, the distribution of deleterious mutations in threatened mammals did not reveal consistent trends. Our results indicate that these newly developed statistics could help us understand the genetic burden of threatened species.

Animals

A gene-based model of fitness and its implications for genetic variation: Linkage disequilibrium.

A widely used model of the effects of mutations on fitness (the "sites" model) assumes that heterozygous recessive or partially recessive deleterious mutations at different sites in a gene complement each other, similarly to mutations in different genes. However, the general lack of complementation between major effect allelic mutations suggests an alternative possibility, which we term the "gene" model. This assumes that a pair of heterozygous deleterious mutations in trans behave effectively as homozygotes, so that the fitnesses of trans heterozygotes are lower than those of cis heterozygotes. We examine the properties of the two different models, using both analytical and simulation methods. We show that the gene model predicts positive linkage disequilibrium (LD) between deleterious variants within the coding sequence, under conditions when the sites model predicts zero or slightly negative LD. We also show that focussing on rare variants when examining patterns of LD, especially with Lewontin's´ measure, is likely to produce misleading results with respect to inferences concerning the causes of the sign of LD. Synergistic epistasis between pairs of mutations was also modeled; it is less likely to produce negative LD under the gene model than the sites model. The theoretical results are discussed in relation to patterns of LD in natural populations of several species.

complementation

FLT4 gene polymorphisms influence isolated ventricular septal defect predisposition in a Southwest China population.

BACKGROUND: Ventricular septal defect (VSD) is the most common congenital heart disease. Although a small number of genes associated with VSD have been found, the genetic factors of VSD remain unclear. In this study, we evaluated the association of 10 candidate single nucleotide polymorphisms (SNPs) with isolated VSD in a population from Southwest China. METHODS: Based on the results of 34 congenital heart disease whole-exome sequencing and 1000 Genomes databases, 10 candidate SNPs were selected. A total of 618 samples were collected from the population of Southwest China, including 285 VSD samples and 333 normal samples. Ten SNPs in the case group and the control group were identified by SNaPshot genotyping. The chi-square (&#x3c7;2) test was used to evaluate the relationship between VSD and each candidate SNP. The SNPs that had significant P value in the initial stage were further analysed using linkage disequilibrium, and haplotypes were assessed in 34 congenital heart disease whole-exome sequencing samples using Haploview software. The bins of SNPs that were in very strong linkage disequilibrium were further used to predict haplotypes by Arlequin software. ViennaRNA v2.5.1 predicted the haplotype mRNA secondary structure. We evaluated the correlation between mRNA secondary structure changes and ventricular septal defects. RESULTS: The &#x3c7;2 results showed that the allele frequency of FLT4 rs383985 (P&#x2009;=&#x2009;0.040) was different between the control group and the case group (P&#x2009;<&#x2009;0.05). FLT4 rs3736061 (r2&#x2009;=&#x2009;1), rs3736062 (r2&#x2009;=&#x2009;0.84), rs3736063 (r2&#x2009;=&#x2009;0.84) and FLT4 rs383985 were in high linkage disequilibrium (r2&#x2009;>&#x2009;0.8). Among them, rs3736061 and rs3736062 SNPs in the FLT4 gene led to synonymous variations of amino acids, but predicting the secondary structure of mRNA might change the secondary structure of mRNA and reduce the free energy. CONCLUSIONS: These findings suggest a possible molecular pathogenesis associated with isolated VSD, which warrants investigation in future studies.

Child

Correlations between causal effect sizes of proximal SNPs vary with functional annotations and implicate stabilizing selection.

Causal disease effect sizes of proximal single-nucleotide polymorphisms (SNPs) are widely assumed to be independent but could be correlated. Here we introduce a new method, linkage disequilibrium SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs; LDSPEC produced robust estimates in simulations. Analyzing 70 UK Biobank diseases and traits (average N&#x2009;=&#x2009;305,646), we detected significantly non-zero SNP-pair effect correlations (for example, -0.37 &#xb1; 0.09 for low-frequency positive linkage disequilibrium 0-100-bp SNP pairs) that decayed with distance and varied with allele frequency and linkage disequilibrium between SNPs. SNP pairs with shared functions had stronger effect correlations that spanned longer genomic distances. Consequently, SNP heritability estimates were smaller than estimates of the sum of causal effect size variances across SNPs, particularly for certain functional annotations. We recapitulated our findings via forward simulations involving stabilizing selection, implicating the action of linkage masking, whereby haplotypes containing linked SNPs with opposite effects on disease have reduced effects on fitness and escape negative selection.

Polymorphism, Single Nucleotide

Association of CYP19 gene SNPs (rs7176005 and rs6493497) with polycystic ovary syndrome susceptibility in Northern Chinese women.

PURPOSE: The objective of this study was to elucidate the relationship between two single nucleotide polymorphisms (SNPs) rs7176005 and rs6493497 in CYP19 gene and the risk of polycystic ovary syndrome (PCOS) in Northern Chinese women. METHODS: In this case-control study, a total of 340 women with PCOS and 340 matched healthy controls were recruited. Polymerase chain reaction ligase detection reaction (PCR-LDR) method was used to investigate two SNPs (rs7176005 and rs6493497) in the 5'-flanking region of CYP19 gene exon 1. RESULTS: We observed a significant association of rs7176005 and rs6493497 with reduced risk of PCOS. Compared with CC genotype, a significant association of CT genotype (p&#x2009;=&#x2009;0.019), TT genotype (p&#x2009;<&#x2009;0.001) and combined CT&#x2009;+&#x2009;TT genotype (p&#x2009;<&#x2009;0.001) with reduced risk of PCOS was observed. The result of linkage disequilibrium analysis showed that these two SNPs are in complete linkage disequilibrium (r2 = 1). For rs7176005 SNP, compared with CC genotype, CT, TT and CT&#x2009;+&#x2009;TT genotypes reduced the risk of PCOS. The age, BMI-adjusted OR were 0.650 (95% CI&#x2009;=&#x2009;0.460-0.917), 0.158 (95% CI&#x2009;=&#x2009;0.066-0.376) and 0.545(95% CI&#x2009;=&#x2009;0.391-0.759), respectively. CONCLUSIONS: These findings highlight a significant association between CYP19 gene polymorphisms and PCOS susceptibility, implying potential protective effects of T and A alleles. Of course, the major limitation of this study is the sample size of the case-control study. Larger cohort studies are needed to confirm these findings and investigate the underlying causes.

Adult

Virulence-associated variants in Cryptococcus neoformans sequence type 93 are less likely to be associated with population structure compared to independent rare mutations.

Cryptococcus neoformans is a pathogenic yeast that is the causative agent of cryptococcal meningitis. While it is well known that the genotype of C. neoformans impacts patient outcomes, the reason for this association has not been well elucidated. In this study, we examined the relationship between two subpopulations in the sequence type 93 clade of C. neoformans: ST93A and ST93B. We found extensive linkage disequilibrium (LD) among the single nucleotide polymorphisms (SNPs) that differentiate ST93A from ST93B. We also found differences in the extent of linkage among SNPs within each subpopulation; LD was more extensive within ST93B than ST93A. SNPs associated with virulence were in long-range linkage disequilibrium with less frequency than recurrent SNPs not associated with virulence. We investigated the karyotype of ST93A and ST93B using contour-clamped gel electrophoresis and long-read sequencing and found that the extensive long-range linkage was not due to chromosomal rearrangements. Overall, we found that the two subpopulations in ST93 are driven by SNPs in LD. We additionally found that recurrent SNPs associated with virulence were less frequently evolutionarily linked and were two times more likely to be independent, congruent mutations rather than tied to phylogeny.IMPORTANCECryptococcus neoformans is an important pathogen that is widely distributed and ubiquitous in the environment. The majority of the human population has a latent, controlled infection suggesting that C. neoformans is uniquely adapted to cause infection. In spite of this, the reason C. neoformans is a pathogen remains unknown; interestingly, most environmental isolates are avirulent but are genetically very similar to disease-causing virulent isolates. Recent evidence from genome-wide association studies shows that small mutations in key virulence-associated genes are associated with the virulence of specific isolates. The data presented here provide an evolutionary framework for those small mutations. The mutations that impact disease are not being collected over long-term evolution. The mutations may instead occur independently during infection. Identifying these genes that are more likely to be mutated during infection will be fundamental for understanding C. neoformans virulence.

Cryptococcus neoformans

Sparse multitask group Lasso for genome-wide association studies.

A critical hurdle in Genome-Wide Association Studies (GWAS) involves population stratification, wherein differences in allele frequencies among subpopulations within samples are influenced by distinct ancestry. This stratification implies that risk variants may be distinct across populations with different allele frequencies. This study introduces Sparse Multitask Group Lasso (SMuGLasso) to tackle this challenge. SMuGLasso is based on MuGLasso, which formulates this problem using a multitask group lasso framework in which tasks are subpopulations, and groups are population-specific Linkage-Disequilibrium (LD)-groups of strongly correlated Single Nucleotide Polymorphisms (SNPs). The novelty in SMuGLasso is the incorporation of an additional [Formula: see text]-norm regularization for the selection of population-specific genetic variants. As MuGLasso, SMuGLasso uses a stability selection procedure to improve robustness and gap-safe screening rules for computational efficiency. We evaluate MuGLasso and SMuGLasso on simulated data sets as well as on a case-control breast cancer data set and a quantitative GWAS in Arabidopsis thaliana. We show that SMuGLasso is well suited to addressing linkage disequilibrium and population stratification in GWAS data, and show the superiority of SMuGLasso over MuGLasso in identifying population-specific SNPs. On real data, we confirm the relevance of the identified loci through pathway and network analysis, and observe that the findings of SMuGLasso are more consistent with the literature than those of MuGLasso. All in all, SMuGLasso is a promising tool for analyzing GWAS data and furthering our understanding of population-specific biological mechanisms.

Genome-Wide Association Study

Population-scale disease-associated tandem repeat analysis reveals locus and ancestry-specific insights.

Tandem repeat (TR) expansions, including short TRs (motifs &#x2264;6&#x2009;bp) and variable number TRs (motifs >6&#x2009;bp), underlie many monogenic disorders, with variable length and sequence influencing pathogenicity, penetrance, severity, and onset. Accurate genotype-phenotype correlation and disease prevalence estimation require characterization beyond repeat length. Here we present a population-scale analysis of 66 disease-associated TR loci using long-read assemblies from 2530 diverse haplotypes from 1265 unaffected donors. Integrating repeat length, motif composition, local ancestry, linkage disequilibrium, and phylogenetic analyses, we reveal extensive locus-, population-, and allele-specific variation shaping disease risk. Up to 8.5% of individuals carry expansions above established pathogenic thresholds, many containing interrupting motifs or sequence structures that attenuate pathogenicity. After excluding alleles from loci with uncertain disease association, non-pathogenic interrupted expansions, and carrier states inconsistent with inheritance patterns, ~4% carried expansions predicted to confer disease risk, largely at adult-onset loci with reduced penetrance. Ancestry-resolved analyses uncover population-specific TR architectures contributing to epidemiological disparities in repeat expansion disorders. Phylogenetic analyses identify conserved ancestral alleles and loci with recent instability. We describe variable linkage disequilibrium patterns and recombination signatures around specific disease-associated TR loci. Our findings emphasize integrating sequence, ancestry, and evolutionary context to understand the complex landscape of disease-associated TRs.

Humans

Shared genetic architecture of obesity and gastroesophageal reflux disease.

Obesity is identified as a risk factor of gastroesophageal reflux disease (GERD). This study aims to elucidate the shared genetic architecture of obesity-related phenotypes and GERD. Based on the publicly available genome-wide association studies' datasets, this genome-wide pleiotropic association study was conducted with various genetic approaches (including linkage disequilibrium score regression, high-definition likelihood inference for genetic correlations, pleiotropic analysis under composite null hypothesis, Functional Mapping and Annotation, Bayesian colocalization, summary-based Mendelian randomization, and multi-marker analysis of genomic annotation analysis) sequentially to unravel the genetic associations from single-nucleotide polymorphism to gene levels, and to reveal the underlying shared genetic architecture between obesity-related phenotypes and GERD. This study discovered shared genetic mechanisms between GERD and several obesity-related phenotypes, including arm fat percentage (left), arm fat percentage (right), leg fat percentage (left), leg fat percentage (right), trunk fat percentage, waist-to-hip ratio, and body mass index. Significant genetic correlations were observed by linkage disequilibrium score regression and high-definition likelihood inference for genetic correlations, with multiple associated pleiotropic loci and their mapped genes identified by pleiotropic analysis under composite null hypothesis, Functional Mapping and Annotation, Bayesian colocalization, summary-based Mendelian randomization, and multi-marker analysis of genomic annotation analysis. Additionally, several brain tissues were identified to be linked to both obesity and GERD by multi-marker analysis of genomic annotation. This research provided strong evidence of genetic correlations and brought novel insights into the underlying genetic connections and shared genetic architectures of obesity and GERD.

Humans

Investigating the causal role of smoking in gout: A triangulation approach combining NHANES data, genetic correlation, and Mendelian randomization.

The relationship between smoking and the development of gout is not well understood. To address this, we adopted a triangulation framework that integrates observational analysis, genetic correlation estimation, and two-sample Mendelian randomization (MR) to examine whether smoking confers a causal risk for gout. We first performed a cross-sectional analysis using information for 13,626 participants from the National Health and Nutrition Examination Survey between 2013 and 2018. The association of smoking with gout was subsequently assessed through logistic regression models. We next investigated the extent of shared genetic factors between smoking phenotypes and gout. We were able to demonstrate this using the linkage disequilibrium score regression applied to genome-wide association study data of European ancestry. Finally, to verify the causality of our relationship, we carried out a two-sample MR analysis. We selected the inverse-variance weighted (IVW) method and confirmed the consistency of using the IVW method with other statistical methods, including weighted median, weighted mode, and simple mode, as well as MR-Egger regression. We performed sensitivity analyses to investigate the heterogeneity of the hypothesis and stability of the data. Our findings based on National Health and Nutrition Examination Survey data reveal that there is a strong positive association between smoking and the risk of gout (odds ratio [OR]&#x2005;=&#x2005;1.94, 95% confidence interval [CI]&#x2005;=&#x2005;1.48-2.55, P&#x2005;<&#x2005;.001). This association persisted after confounding adjustments (OR&#x2005;=&#x2005;1.41, 95% CI&#x2005;=&#x2005;1.04-1.91, P&#x2005;=&#x2005;.027). In the subgroup analyses, former smokers and current smokers of 10 to 20 cigarettes per day had a substantially increased risk. Post-linkage disequilibrium score regression analysis revealed that the significantly positive genetic correlations of smoking initiation and lifetime smoking index with gout risk were both significantly positive. Additional evidence for causality is presented by MR. Genetic prediction of smoking initiation statistically increases gout risk (IVW OR&#x2005;=&#x2005;1.55, 95% CI&#x2005;=&#x2005;1.26-1.90, P&#x2005;=&#x2005;3.17&#x2005;&#xd7;&#x2005;10-5). A much stronger association is evident for lifetime smoking index (IVW OR&#x2005;=&#x2005;1.99, 95% CI&#x2005;=&#x2005;1.44-2.76, P&#x2005;=&#x2005;3.24&#x2005;&#xd7;&#x2005;10-5). These findings are the same with or without heterogeneity by sensitivity analysis. In light of our integrated analysis, smoking is a causative factor for gout. This suggests that public health interventions like anti-smoking campaigns might reduce gout incidence.

Humans

Genetic Determinants of Leisure-Time Physical Activity in the Taiwanese Population: A Genome-Wide Association Study.

BACKGROUND: Physical inactivity contributes to systemic disease burden and premature mortality worldwide. Leisure-time physical activity (LTPA) improves health outcomes; however, its genetic determinants, particularly in Asian populations, remain unclear. This study aimed to identify genetic loci associated with LTPA in the Taiwanese population. METHODS: We conducted genome-wide association studies in 122,258 Taiwan Biobank participants. LTPA was assessed both as a binary trait (regular exerciser vs non-exerciser) and an ordinal trait (categorized by MET-hours per week into low, moderate, and high physical activity levels). Logistic and ordinal logistic regression models were used under an additive genetic model, adjusting for age, age 2 , sex, body mass index, smoking, and the first 10 genetic principal components. Candidate nonsynonymous mutations were further examined in 1494 whole-genome sequenced participants. RESULTS: Binary trait genome-wide association studies identified genome-wide significant (GWS) loci at ATXN2 (12q24.12), FTO (16q12.2), and NOTCH4 (6p21.32), with associations for FTO and NOTCH4 only observed in body mass index (BMI)-adjusted models. Ordinal trait analysis (<10, 10-<20, &#x2265;20 MET&#xb7;h&#xb7;wk -1 ) identified a single GWS locus at BRAP (12q24.12). Fine-mapping of 12q24.12 revealed multiple GWS single-nucleotide polymorphisms (SNPs) in strong linkage disequilibrium with lead variants; these signals largely disappeared after conditional analysis, consistent with a single underlying association. Whole-genome sequencing and linkage disequilibrium analysis identified three GWS nonsynonymous mutations, with ALDH2 rs671 emerging as the most likely causal variant. CONCLUSIONS: ATXN2-ALDH2 region on chromosome 12q24.12 was identified as a key locus for LTPA in Taiwanese individuals. These findings enhance our understanding of the genetic basis of physical activity and may inform future precision medicine and public health strategies.

Adult

Genetic interconnections between personality-related phenotypes and psychiatric disorders.

BACKGROUND: Personality-related phenotypes are genetically correlated with psychiatric disorders, but whether these relationships reflect shared genetic loci and differ across individual phenotypes remains unclear. We investigated their shared genetic architecture at the level of specific phenotype-disorder pairs. METHODS: We analyzed genome-wide association study summary statistics for 13 personality-related phenotypes and eight psychiatric disorders in populations of European ancestry. Genetic correlations were evaluated separately for 104 phenotype-disorder pairs using linkage disequilibrium score regression and high-definition likelihood. For pairs supported by both methods, MTAG and CPASSOC were applied separately to identify pleiotropic signals, followed by linkage disequilibrium clumping, Bayesian colocalization, gene prioritization, functional enrichment and bidirectional two-sample Mendelian randomization analyses. No composite personality or psychiatric-disorder phenotype was constructed. RESULTS: Among the 104 evaluated pairs, 77 showed significant positive genetic correlations in both analyses. Joint screening of MTAG and CPASSOC results identified pleiotropic signals in 61 pairs, comprising 1088 independent lead SNV-pair associations and 776 unique SNVs. Bayesian colocalization supported 351 signals across 42 pairs and 284 unique lead SNVs. MAGMA identified 1293 unique genes, of which 379 were prioritized by PoPS and 151 were further supported by SMR. These genes were enriched in brain tissues and biological processes involving nervous system development, synaptic organization and intercellular connectivity. Inverse-variance weighted Mendelian randomization identified 41 forward and 32 reverse associations after false-discovery-rate correction, including 21 pairs with bidirectional evidence. CONCLUSION: These item-resolved analyses identify widespread but heterogeneous genetic sharing between personality-related phenotypes and psychiatric disorders. The findings provide a pair-specific map of shared loci and prioritized genes, while the Mendelian randomization results should be interpreted cautiously because of residual heterogeneity and potential horizontal pleiotropy. Further validation in diverse populations and functional studies is required.

Colocalization

Effects of domestication on the body morphology and genetic diversity of the yellowfin seabream (Acanthopagrus latus).

The yellowfin seabream (Acanthopagrus latus) is a significant economic fish along the southeast coast of China. Recently, the drastic decline in the wild populations, exacerbated by overfishing and climate change, has heightened our reliance on aquaculture. However, the current lack of research on its domestication hinders effective conservation of wild populations and balanced management alongside the aquaculture industry. Studies on body characteristics have shown that wild yellowfin seabream possess a higher body, while cultured ones exhibit a wider body. Whole-genome SNP analysis revealed moderate genetic differentiation between cultured and wild populations. Further analyses of linkage disequilibrium, heterozygosity, and genetic diversity revealed that the degree of SNP linkage was lower in the wild population compared to the cultured population. In contrast, heterozygosity and nucleotide polymorphisms were significantly higher in the wild population (P&#xa0;<&#xa0;0.001 and P&#xa0;<&#xa0;0.05, respectively). Additionally, over 300 candidate genes were identified in each cultured population through genomic selection signature analysis, with 67 key genes shared among all three, which were linked to growth and development (ghrb, ghsra, and cfl1), immune response (aire, cd36, and igbp1), and salinity adaptation (abcc3, clic4, and kcnk15). Enrichment analysis indicated that the key candidate genes were significantly enriched in pathways related to protein kinase activity, ion binding and growth hormone synthesis, secretion and action (FDR&#xa0;<&#xa0;0.05). The findings provide valuable insights into the variation in body size of yellowfin seabream under domestication selection and offer an important theoretical basis for the genetic improvement of yellowfin seabream.

Animals

Genomic heterozygosity and hybrid breakdown in cotton (Gossypium): different traits, different effects.

BACKGROUND: Hybrid breakdown has been well documented in various species. Relationships between genomic heterozygosity and traits-fitness have been extensively explored especially in the natural populations. But correlations between genomic heterozygosity and vegetative and reproductive traits in cotton interspecific populations have not been studied. In the current study, two reciprocal F2 populations were developed using Gossypium hirsutum cv. Emian 22 and G. barbadense acc. 3-79 as parents to study hybrid breakdown in cotton. A total of 125 simple sequence repeat (SSR) markers were used to genotype the two F2 interspecific populations. RESULTS: To guarantee mutual independence among the genotyped markers, the 125 SSR markers were checked by the linkage disequilibrium analysis. To our knowledge, this is a novel approach to evaluate the individual genomic heterozygosity. After marker checking, 83 common loci were used to assess the extent of genomic heterozygosity. Hybrid breakdown was found extensively in the two interspecific F2 populations particularly on the reproductive traits because of the infertility and the bare seeds. And then, the relationships between the genomic heterozygosity and the vegetative reproductive traits were investigated. The only relationships between hybrid breakdown and heterozygosity were observed in the (Emian22 &#xd7; 3-79) F2 population for seed index (SI) and boll number per plant (BN). The maternal cytoplasmic environment may have a significant effect on genomic heterozygosity and on correlations between heterozygosity and reproductive traits. CONCLUSIONS: A novel approach was used to evaluate genomic heterozygosity in cotton; and hybrid breakdown was observed in reproductive traits in cotton. These findings may offer new insight into hybrid breakdown in allotetraploid cotton interspecific hybrids, and may be useful for the development of interspecific hybrids for cotton genetic improvement.

Chromosomes, Plant

Refining the link between REM sleep behavior disorder and neurodegeneration: Genetic correlation, Mendelian randomization, and colocalization evidence.

Observational studies have proposed a link between isolated rapid eye movement sleep behavior disorder (iRBD) and several neurodegenerative diseases. We employed genome-wide linkage disequilibrium score regression (LDSC), standard two-sample Mendelian randomization (MR), and colocalization analysis to assess the causal links between iRBD and these neurodegenerative conditions. iRBD demonstrated a positive causal association with Alzheimer disease (odds ratio [OR]&#x2005;=&#x2005;1.02, 95% confidence interval [CI]: 1.00-1.03, P&#x2005;=&#x2005;1.10E-02), Parkinson disease (OR&#x2005;=&#x2005;1.10, 95% CI: 1.03-1.16, P&#x2005;=&#x2005;2.96E-03), and multiple sclerosis (OR&#x2005;=&#x2005;1.09, 95% CI: 1.02-1.17, P&#x2005;=&#x2005;1.61E-02). A strong positive genetic correlation with dementia with Lewy bodies was observed (rg&#x2005;=&#x2005;1.6313, P&#x2005;=&#x2005;.0002), along with a causal association (OR&#x2005;=&#x2005;1.45, 95% CI: 1.03-2.06, P&#x2005;=&#x2005;3.53E-02), further supported by colocalization analysis. No significant causal relationship was identified between iRBD and amyotrophic lateral sclerosis (all P&#x2005;>&#x2005;.05). Additionally, reverse Mendelian randomization analyses did not reveal any causal relationships between the neurodegenerative diseases studied and iRBD. Our findings provide robust genetic evidence supporting a causal relationship between iRBD and the risk of multiple neurodegenerative diseases, highlighting the potential for shared pathophysiological mechanisms.

Humans

Endogenous fine-mapping and prioritization of functional regulatory elements in complex genetic loci.

Most genetic loci linked to polygenic traits are in non-coding regions, with complex regulation and linkage disequilibrium (LD), complicating causal variant and gene prioritization. We used multiplexed single-cell CRISPR interference and activation perturbations to investigate cis-regulatory element (CRE) and gene expression relationships within tight LD in the endogenous chromatin context. We demonstrated the prevalence of multiple causality in perfect LD (pLD) for independent expression quantitative trait loci (eQTLs) and uncovered fine-grained genetic effects on gene expression within pLD, which are difficult to decipher using traditional eQTL fine-mapping or existing computational methods. We found that over one-third of the causal CREs lack classical epigenetic markers prior to perturbation, and we functionally validated one of these hidden regulatory mechanisms. Leveraging Multiome single-cell epigenetic and sequence perturbations, we highlighted the regulatory plasticity of the human genome. Our study will guide the exploration of missing causal mechanisms underlying molecular trait regulation and disease development.

Humans

Genomic diversity, inbreeding, and selection signatures in duroc, landrace, and yorkshire pigs from a long-term closed breeding system.

Duroc (DD), Landrace (LL), and Yorkshire (YY) are among the most widely used commercial pig breeds, having undergone intense long-term selection within closed breeding systems. This study presents a comprehensive genomic analysis of genetic diversity, inbreeding patterns, and selection signatures in DD, LL, and YY populations that have been subject to close breeding for over 15 years. Genomic and pedigree data were available for 1,088 animals (DD&#x2009;=&#x2009;348, LL&#x2009;=&#x2009;276, YY&#x2009;=&#x2009;464), genotyped using the GenoBaits&#xae; Porcine 100&#xa0;K SNP panel. Principal component analysis and genetic diversity metrics revealed distinct population structures among the three breeds. Pairwise genetic differentiation supported this pattern, with DD showing the greatest divergence from LL (0.34&#x2009;&#xb1;&#x2009;0.24) and YY (0.33&#x2009;&#xb1;&#x2009;0.24), while LL and YY were more closely related (FST&#x2009;=&#x2009;0.22&#x2009;&#xb1;&#x2009;0.19). Linkage disequilibrium (LD) analysis further confirmed these differences, as DD exhibited the highest average r&#xb2; (0.34), followed by LL (0.28) and YY (0.25). Within-breed genetic diversity metrics, including observed heterozygosity (HO: 0.37 in DD, 0.39 in LL, 0.38 in YY), expected heterozygosity (HE: 0.36 in DD, 0.37 in LL, 0.38 in YY), and minor allele frequency (MAF: 0.27 in DD, 0.28 in LL, 0.29 in YY), indicated greater genetic variability in LL and YY compared to DD. Runs of homozygosity (ROH) analyses revealed different patterns of autozygosity, with DD exhibiting more long ROH indicative of recent inbreeding, while YY harbored a higher number of short ROH, suggestive of more ancient demographic events. ROH-based inbreeding coefficients (FROH) consistently exceeded pedigree-based estimates (FPED) across all breeds, highlighting the presence of recent or unrecorded inbreeding that pedigree data may not fully capture. According to Generation Proxy Selection Mapping (GPSM), 17, 1, and 12 significant SNPs were detected in DD, LL, and YY, respectively. Functional annotation of ROH islands and GPSM-significant loci revealed both breed-specific and overlapping QTLs related to traits such as growth, reproduction, and carcass. In general, the findings of this study contribute to a deeper understanding of the genomic consequences of long-term closed breeding and provide reference information to support consideration of breeding strategies that balance continued selection for productivity with the maintenance of genetic diversity in modern commercial pig populations.

Animals