The southern river terrapin, Batagur affinis is one of the world's 25 most endangered freshwater turtle species. The major portion of the global population is currently found in peninsular Malaysia, with the only remnant Indochinese population in southern Cambodia. For more than a decade, wild nests in this remnant Cambodian population have been fenced and hatchlings reared in captivity. Here we amplified 10 microsatellite markers from all 136 captive individuals, obtained 2,658 presumably unlinked and neutral single nucleotide polymorphisms from 72 samples with ddRAD-seq, and amplified 784 bp of mtDNA from 50 samples. Our results reveal that the last Indochinese population comprised only four kinship groups as of 2012, with all offspring sired from <10 individuals in the wild. We demonstrate an obvious decrease in genetic contributions of breeders in the wild from 2006-2012 and identify high-value breeders instrumental for ex-situ management of the contemporary genetic stock of the species.
The movement of patients in magnetic resonance imaging (MRI) scanners results in motion artefacts which impair image quality. Non-completion of scans leads to delay in diagnosis and increased costs. This study aimed to develop and evaluate an intervention to enable patients to stay still in MRI scanners (reducing motion artefacts) and to enhance scan completion. Successful scan outcome was deemed to be completing the scan with no motion artefacts.
Condensin is a central regulator of mitotic genome structure with mutants showing poorly condensed chromosomes and profound segregation defects. Here, we identify NCT, a complex comprising the Nrc1 BET-family tandem bromodomain protein (SPAC631.02), casein kinase II (CKII), and several TAFs, as a regulator of condensin function. We show that NCT and condensin bind similar genomic regions but only briefly colocalize during the periods of chromosome condensation and decondensation. This pattern of NCT binding at the core centromere, the region of maximal condensin enrichment, tracks the abundance of acetylated histone H4, as regulated by the Hat1-Mis16 acetyltransferase complex and recognized by the first Nrc1 bromodomain. Strikingly, mutants in NCT or Hat1-Mis16 restore the formation of segregation-competent chromosomes in cells containing defective condensin. These results are consistent with a model where NCT targets CKII to chromatin in a cell-cycle-directed manner in order to modulate the activity of condensin during chromosome condensation and decondensation.
The social system of animals involves a complex interplay between physiology, natural history, and the environment. Long relied upon discrete categorizations of "social" and "solitary" inhibit our capacity to understand species and their interactions with the world around them. Here, we use a globally distributed camera trapping dataset to test the drivers of aggregating into groups in a species complex (martens and relatives, family Mustelidae, Order Carnivora) assumed to be obligately solitary. We use a simple quantification, the probability of being detected in a group, that was applied across our globally derived camera trap dataset. Using a series of binomial generalized mixed-effects models applied to a dataset of 16,483 independent detections across 17 countries on four continents we test explicit hypotheses about potential drivers of group formation. We observe a wide range of probabilities of being detected in groups within the solitary model system, with the probability of aggregating in groups varying by more than an order of magnitude. We demonstrate that a species' context-dependent proclivity toward aggregating in groups is underpinned by a range of resource-related factors, primarily the distribution of resources, with increasing patchiness of resources facilitating group formation, as well as interactions between environmental conditions (resource constancy/winter severity) and physiology (energy storage capabilities). The wide variation in propensities to aggregate with conspecifics observed here highlights how continued failure to recognize complexities in the social behaviors of apparently solitary species limits our understanding not only of the individual species but also the causes and consequences of group formation.
Dystonia is one of the most prevalent movement disorders, characterized by significant clinical and etiological heterogeneity. Despite considerable heritability (∼25%) and the identification of several disease-linked genes, the etiology in most patients remains elusive. Moreover, understanding the correlations between clinical manifestation and genetic variants has become increasingly complex. To comprehensively unravel dystonia's genetic spectrum, we performed exome sequencing on 1,924 dystonia patients [40.3% male, 92.9% White, 93.2% isolated dystonia, median age at onset (AAO) 33 years], including 1,895 index patients, who were previously genetically unsolved. The sample was mainly based on two dystonia registries (DysTract and the Dystonia Coalition). Further, 72 additional patients of Asian ethnicity, mainly from Malaysia, were also included. We prioritized patients with negative genetic prescreening, early AAO, positive family history, and multisite involvement of dystonia. Rare variants in genes previously linked to dystonia ( n =405) were examined. Variants were confirmed via Sanger sequencing, and segregation analysis was performed when possible. We identified 137 distinct likely pathogenic or pathogenic variants (according to ACMG criteria) across 51 genes in 163/1,924 patients [42.9% male, 85.9% White, 68.7% isolated dystonia, median AAO 19 years]. This included 153/1,895 index patients, resulting in a diagnostic yield of 8.1%. Notably, 77/137 (56.2%) of these variants were novel, with recurrent variants in EIF2AK2 , VPS16 , KCNMA1 , and SLC2A1 , and novel variant types such as two splice site variants in KMT2B , supported by functional evidence. Additionally, 321 index patients (16.9%) harbored variants of uncertain significance in 102 genes. The most frequently implicated genes included VPS16 , THAP1 , GCH1 , SGCE , GNAL , and KMT2B. Presumably pathogenic variants in less well-established dystonia genes were also found, including KCNMA1 , KIF1A , and ZMYND11. At least six variants (in ADCY5 , GNB1 , IR2BPL, KCNN2 , KMT2B , and VPS16 ) occurred de novo, supporting pathogenicity. ROC curve analysis indicated that AAO and the presence of generalized dystonia were the strongest predictors of a genetic diagnosis, with diagnostic yields of 28.6% in patients with generalized dystonia and 20.4% in those with AAO < 30 years. This study provides a comprehensive examination of the genetic landscape of dystonia, revealing valuable insights into the frequency of dystonia-linked genes and their associated phenotypes. It underscores the utility of exome sequencing in establishing diagnoses within this heterogeneous condition. Despite prescreening, presumably pathogenic variants were identified in almost 10% of patients. Our findings reaffirm several dystonia candidate genes and expand the phenotypic spectrum of some of these genes to include prominent, sometimes isolated dystonia.
To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.
Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.
In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.
Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.
Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10-8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.
Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P