A general approach for haplotype phasing across the full spectrum of relatedness

Interpretation of SNP combination effects on schizophrenia etiology based on stepwise deep learning with multi-precision data

Schizophrenia genome-wide association studies (GWAS) have reported many genomic risk loci, but it is unclear how they affect schizophrenia susceptibility through interactions of multiple SNPs. We propose a stepwise deep learning technique with multi-precision data (SLEM) to explore the SNP combination effects on schizophrenia through intermediate molecular and cellular functions. The SLEM technique utilizes two levels of precision data for learning. It constructs initial backbone networks with more precise but small amount of multilevel assay data. Then, it learns strengths of intermediate interactions with the less precise but massive amount of GWAS data. The learned networks facilitate identifying effective SNP interactions from the intractably large space of all possible SNP combinations. We have shown that the extracted SNP combinations show higher accuracy than any single SNPs and preserve the accuracy in an independent dataset. The learned networks also provide interpretations of molecular and cellular interactions of SNP combinations toward schizophrenia etiology.

Identification of risk loci for postpartum depression in a genome-wide association study

AIM

Genome-wide association studies (GWAS) of postpartum depression (PPD) based on accumulated cohorts with multiple ethnic backgrounds have failed to identify significantly associated loci. Herein, we conducted a GWAS of Japanese perinatal women along with detailed confounding information to uncover PPD-associated loci.

METHODS

The first and second cohorts (n = 9260 and n = 8582 perinatal women enrolled in the Tohoku Medical Megabank Project) and the third cohort (n = 997), recruited at Nagoya University, underwent genotyping. Of them, 1421, 1264, and 225 were classified as PPD based on the Edinburgh Postnatal Depression Scale 1 month after delivery. The most influential confounding factors of genetic liability to PPD were selected, and logistic regression analyses were performed to evaluate genetic associations with PPD after adjusting for confounders.

RESULTS

A meta-analysis of GWAS results from the three cohorts identified significant associations between PPD and the following loci (P < 5 × 10-8) by integrating the number of deliveries and the number of family members living together as the most influential confounders: rs377546683 at DAB1, rs11940752 near UGT8, rs141172317, rs117928019, rs76631412, rs118131805 at DOCK2, rs188907279 near ZNF572, rs504378, rs690150, rs491868, rs689917, rs474978, rs690118, rs690253 near DIRAS2, rs1435984417 at ZNF618, rs57705782 near PTPRM, and rs185293917 near PDGFB. Pathway analyses indicated that SNPs suggestively associated with PPD were mostly over-represented in categories including long-term depression, GnRH signaling, glutamatergic synapse, oxytocin signaling, and Rap1 signaling.

CONCLUSION

The current GWAS study identified eight loci significantly associated with PPD, which may clarify the genetic structure underlying its pathogenesis.

Genomic Exploration of Essential Hypertension in African-Brazilian Quilombo Populations: A Comprehensive Approach with Pedigree Analysis and Family-Based Association Studies

BACKGROUND

Essential Hypertension (EH) is a global health issue, responsible for approximately 9.4 million deaths annually. Its prevalence varies by region, with genetic factors contributing 30-60% to blood pressure variation. Despite extensive research, the genetic complexity of EH remains largely unexplained. This study aimed to investigate the genetic basis of EH in African-derived individuals from partially isolated quilombo remnant populations in Vale do Ribeira (SP-Brazil).

METHODS

Samples from 431 individuals (167 affected, 261 unaffected, 3 with unknown phenotype) were genotyped using a 650k SNP array. Global ancestry proportions were estimated at 47% African, 36% European, and 16% Native American. Additional data from 673 individuals were used to construct six pedigrees. Pedigrees were pruned, and three non-overlapping marker subpanels were created. We phased haplotypes and performed local ancestry analysis to account for admixture. We then conducted genome-wide linkage analysis (GWLA) and performed fine-mapping through family-based association studies (FBAS) on imputed data and through EH-related genes investigation.

RESULTS

Linkage analysis identified 22 ROIs with LOD scores ranging from 1.45 to 3.03, encompassing 2363 genes. Fine-mapping identified 60 EH-related candidate genes and 118 suggestive or significant variants (FBAS). Among these, 14 genes, including PHGDH, S100A10, MFN2, and RYR2, were strongly associated with hypertension and harbors 29 SNPs.

CONCLUSIONS

Through a complementary approach - combining admixture-adjusted genome-wide linkage analysis based on Markov chain Monte Carlo (MCMC) methods, association studies on imputed data, and in silico investigations - genetic regions, variants, and candidate genes were identified, offering insights into the genetic etiology of EH in quilombo remnant populations.

Diversity in Recombination Hotspot Characteristics and Gene Structure Shape Fine-Scale Recombination Patterns in Plant Genomes

During the meiosis of many eukaryote species, crossovers tend to occur within narrow regions called recombination hotspots. In plants, it is generally thought that gene regulatory sequences, especially promoters and 5' to 3' untranslated regions, are enriched in hotspots, but this has been characterized in a handful of species only. We also lack a clear description of fine-scale variation in recombination rates within genic regions and little is known about hotspot position and intensity in plants. To address this question, we constructed fine-scale recombination maps from genetic polymorphism data and inferred recombination hotspots in 11 plant species. We detected gradients of recombination in genic regions in most species, yet gradients varied in intensity and shape depending on specific hotspot locations and gene structure. To further characterize recombination gradients, we decomposed them according to gene structure by rank and number of exons. We generalized the previously observed pattern that recombination hotspots are organized around the boundaries of coding sequences, especially 5' promoters. However, our results also provided new insight into the relative importance of the 3' end of genes in some species and the possible location of hotspots away from genic regions in some species. Variation among species seemed driven more by hotspot location among and within genes than by differences in size or intensity among species. Our results shed light on the variation in recombination rates at a very fine scale, revealing the diversity and complexity of genic recombination gradients emerging from the interaction between hotspot location and gene structure.

A fine-scale genetic map of the Japanese population

Genetic maps are fundamental resources for linkage and association studies. A fine-scale genetic map can be constructed by inferring historical recombination events from the genome-wide structure of linkage disequilibrium-a non-random association of alleles among loci-by using population-scale sequencing data. We constructed a fine-scale genetic map and identified recombination hotspots from 10 092 551 bi-allelic high-quality autosomal markers segregating among 150 unrelated Japanese individuals whose genotypes were determined by high-coverage (30×) whole-genome sequencing, and the genotype quality was carefully controlled by using their parents' and offspring's genotypes. The pedigree information was also utilized for haplotype phasing. The resulting genome-wide recombination rate profiles were concordant with those of the worldwide population on a broad scale, and the resolution was much improved. We identified 9487 recombination hotspots and confirmed the enrichment of previously known motifs in the hotspots. Moreover, we demonstrated that the Japanese genetic map improved the haplotype phasing and genotype imputation accuracy for the Japanese population. The construction of a population-specific genetic map will help make genetics research more accurate.

Fine-mapping the CYP2A6 regional association with nicotine metabolism among African American smokers

The nicotine metabolite ratio (NMR; 3'hydroxycotinine/cotinine) is a stable biomarker for CYP2A6 enzyme activity and nicotine clearance, with demonstrated clinical utility in personalizing smoking cessation treatment. Common genetic variation in the CYP2A6 region is strongly associated with NMR in smokers. Here, we investigated this regional association in more detail. We evaluated the association of CYP2A6 single-nucleotide polymorphisms (SNPs) and * alleles with NMR among African American smokers (N = 953) from two clinical trials of smoking cessation. Stepwise conditional analysis and Bayesian fine-mapping were undertaken. Putative causal variants were incorporated into an existing African ancestry-specific genetic risk score (GRS) for NMR, and the performance of the updated GRS was evaluated in both African American (n = 953) and European ancestry smokers (n = 933) from these clinical trials. Five independent associations with NMR in the CYP2A6 region were identified using stepwise conditional analysis, including the deletion variant CYP2A6*4 (beta = -0.90, p = 1.55 × 10-11). Six putative causal variants were identified using Bayesian fine-mapping (posterior probability, PP = 0.67), with the top causal configuration including CYP2A6*4, rs116670633, CYP2A6*9, rs28399451, rs8192720, and rs10853742 (PP = 0.09). Incorporating these putative causal variants into an existing ancestry-specific GRS resulted in comparable prediction of NMR within African American smokers, and improved trans-ancestry portability of the GRS to European smokers. Our findings suggest that both * alleles and SNPs underlie the association of the CYP2A6 region with NMR among African American smokers, identify a shortlist of variants that may causally influence nicotine clearance, and suggest that portability of GRSs across populations can be improved through inclusion of putative causal variants.

Genome-wide analyses of neonatal jaundice reveal a marked departure from adult bilirubin metabolism

Jaundice affects almost all neonates in their first days of life and is caused by the accumulation of bilirubin. Although the core biochemistry of bilirubin metabolism is well understood, it is not clear why some neonates experience more severe jaundice and require treatment with phototherapy. Here, we present the first genome-wide association study of neonatal jaundice to date in nearly 30,000 parent-offspring trios from Norway (cases ≈ 2000). The alternate allele of a common missense variant affecting the sequence of UGT1A4 reduces the susceptibility to jaundice five-fold, which replicated in separate cohorts of neonates of African American and European ancestries. eQTL colocalization analyses indicate that the association may be driven by regulation of UGT1A1 in the intestines, but not in the liver. Our results reveal marked differences in the genetic variants involved in neonatal jaundice compared to those regulating bilirubin levels in adults, suggesting distinct genetic mechanisms for the same biological pathways.

Genome-wide association study based on clustering by obesity-related variables uncovers a genetic architecture of obesity in the Japanese and the UK populations

Whether all obesity-related variants contribute to the onset of obesity or one or a few variants cause obesity in genetically heterogeneous populations remains obscure. Here, we investigated the genetic architecture of obesity by clustering the Japanese and British populations with obesity using obesity-related factors. In Step-1, we conducted a genome-wide association study (GWAS) with body mass index (BMI) as the outcome for eligible participants. In Step-2, we assigned participants with obesity (BMI ≥25 kg/m2) to five clusters based on obesity-related factors. Subsequently, participants from each cluster and those with a BMI <25 kg/m2 were combined. A GWAS was conducted for each cluster. Several previously identified obesity-related genes were verified in Step-1. Of the genes detected in Step-1, unique obesity-related genes were detected separately for each cluster in Step-2. Our novel findings suggest that a smaller sample size with increased homogeneity may provide insights into the genetic architecture of obesity.

Bayesian Estimation of Allele-Specific Expression in the Presence of Phasing Uncertainty

Motivation

Allele-specific expression (ASE) analyses aim to detect imbalanced expression of maternal versus paternal copies of an autosomal gene. Such allelic imbalance can result from a variety of cis-acting causes, including disruptive mutations within one copy of a gene that impact the stability of transcripts, as well as regulatory variants outside the gene that impact transcription initiation. Current methods for ASE estimation suffer from a number of shortcomings, such as relying on only one variant within a gene, assuming perfect phasing information across multiple variants within a gene, or failing to account for alignment biases and possible genotyping errors.

Results

We developed BEASTIE, a Bayesian hierarchical model designed for precise ASE quantification at the gene level, based on given genotypes and RNA-Seq data. BEASTIE addresses the complexities of allelic mapping bias, genotyping error, and phasing errors by incorporating empirical phasing error rates derived from Genome-in-a-Bottle individual NA12878. BEASTIE surpasses existing methods in accuracy, especially in scenarios with high phasing errors. This improvement is critical for identifying rare genetic variants often obscured by such errors. Through rigorous validation on simulated data and application to real data from the 1000 Genomes Project, we establish the robustness of BEASTIE. These findings underscore the value of BEASTIE in revealing patterns of ASE across gene sets and pathways.

Availability and Implementation

The software is freely available from https://github.com/x811zou/BEASTIE . BEASTIE is available as Python source code and as a Docker image.

Supplementary information

Additional information is available online.

haploMAGIC: accurate phasing and detection of recombination in multiparental populations despite genotyping errors

Recombination is a key mechanism in breeding for promoting genetic variability. Multiparental populations (MPPs) constitute an excellent platform for precise genotype phasing, identification of genome-wide crossovers (COs), estimation of recombination frequencies, and construction of recombination maps. Here, we introduce haploMAGIC, a pipeline to detect COs in MPPs with single-nucleotide polymorphism (SNP) data by exploiting the pedigree relationships for accurate genotype phasing and inference of grandparental haplotypes. haploMAGIC applies filtering to prevent false-positive COs due to genotyping errors (GEs), a common problem in high-throughput SNP analysis of complex plant genomes. Hence, it discards haploblocks not reaching a specified minimum number of informative alleles. A performance analysis using populations simulated with AlphaSimR revealed that haploMAGIC improves upon existing methods of CO detection in terms of recall and precision, most notably when GE rates are high. Furthermore, we constructed recombination maps using haploMAGIC with high-resolution genotype data from 2 large multiparental populations of winter rapeseed (Brassica napus). The results demonstrate the applicability of the pipeline in real-world scenarios and showed good correlations in recombination frequency compared with alternative software. Therefore, we propose haploMAGIC as an accurate tool at CO detection with MPPs that shows robustness against GEs.

Genetic Ancestry and Self-Reported "Skin Color/Race" in the Urban Admixed Population of São Paulo City, Brazil

Epidemiological studies frequently classify groups based on phenotypes like self-reported skin color/race, which inaccurately represent genetic ancestry and may lead to misclassification, particularly among individuals of multiracial backgrounds. This study aimed to characterize both global and local genome-wide genetic ancestries and to assess their relationship with self-reported skin color/race in an admixed population of Sao Paulo city. We analyzed 226,346 single-nucleotide polymorphisms from 841 individuals participating in the population-based ISA-Nutrition study. Our findings confirmed the admixed nature of the population, demonstrating substantial European, significant Sub-Saharan African, and minor Native American ancestries, irrespective of skin color. A correlation was observed between global genetic ancestry and self-reported color-race, which was more evident in the extreme proportions of African and European ancestries. Individuals with higher African ancestry tended to identify as Black, those with higher European ancestry tended to identify as White, and individuals with higher Native American ancestry were more likely to self-identify as Mixed, a group with diverse ancestral compositions. However, at the individual level, this correlation was notably weak, and no deviations were observed for specific regions throughout the individual's genome. Our findings emphasize the significance of accurately defining and thoroughly analyzing race and ancestry, especially within admixed populations.

The great tit HapMap project: A continental-scale analysis of genomic variation in a songbird

A major aim of evolutionary biology is to understand why patterns of genomic diversity vary within taxa and space. Large-scale genomic studies of widespread species are useful for studying how environment and demography shape patterns of genomic divergence. Here, we describe one of the most geographically comprehensive surveys of genomic variation in a wild vertebrate to date; the great tit (Parus major) HapMap project. We screened ca 500,000 SNP markers across 647 individuals from 29 populations, spanning ~30 degrees of latitude and 40 degrees of longitude - almost the entire geographical range of the European subspecies. Genome-wide variation was consistent with a recent colonisation across Europe from a South-East European refugium, with bottlenecks and reduced genetic diversity in island populations. Differentiation across the genome was highly heterogeneous, with clear 'islands of differentiation', even among populations with very low levels of genome-wide differentiation. Low local recombination rates were a strong predictor of high local genomic differentiation (FST), especially in island and peripheral mainland populations, suggesting that the interplay between genetic drift and recombination causes highly heterogeneous differentiation landscapes. We also detected genomic outlier regions that were confined to one or more peripheral great tit populations, probably as a result of recent directional selection at the species' range edges. Haplotype-based measures of selection were related to recombination rate, albeit less strongly, and highlighted population-specific sweeps that likely resulted from positive selection. Our study highlights how comprehensive screens of genomic variation in wild organisms can provide unique insights into spatio-temporal evolutionary dynamics.

Fine-scale contemporary recombination variation and its fitness consequences in adaptively diverging stickleback fish

Despite deep evolutionary conservation, recombination rates vary greatly across the genome and among individuals, sexes and populations. Yet the impact of this variation on adaptively diverging populations is not well understood. Here we characterized fine-scale recombination landscapes in an adaptively divergent pair of marine and freshwater populations of threespine stickleback from River Tyne, Scotland. Through whole-genome sequencing of large nuclear families, we identified the genomic locations of almost 50,000 crossovers and built recombination maps for marine, freshwater and hybrid individuals at a resolution of 3.8 kb. We used these maps to quantify the factors driving variation in recombination rates. We found strong heterochiasmy between sexes but also differences in recombination rates among ecotypes. Hybrids showed evidence of significant recombination suppression in overall map length and in individual loci. Recombination rates were lower not only within individual marine-freshwater-adaptive loci, but also between loci on the same chromosome, suggesting selection on linked gene 'cassettes'. Through temporal sampling along a natural hybrid zone, we found that recombinants showed traits associated with reduced fitness. Our results support predictions that divergence in cis-acting recombination modifiers, whose functions are disrupted in hybrids, may play an important role in maintaining differences among adaptively diverging populations.

Tracing the fine-scale demographic history and recent admixture in Hmong-Mien speakers

The linguistic, historical, and subsistent uniqueness of Hmong-Mien (HM) speakers offers a wonderful opportunity to investigate how these factors impact the genetic structure. The genetic differentiation among HM speakers and their population history are not well characterized. Here, we generate genome-wide data from 65 Yao ethnicity samples and analyze them with published data, particularly by leveraging haplotype-based methods. We determined that the fine-scale genetic substructure of HM speakers corresponds better with linguistic classification than with geography. Particularly, parallels between serial founder events and language differentiations can be observed in West Hmongic speakers. Multiple lines of evidence indicate that ~500-year-old GaoHuaHua individuals are most closely related to West Hmongic-speaking Bunu. The strong genetic bottleneck of some HM-speaking groups, especially Bunu, could potentially be associated with their long-term practice of swidden agriculture to some degree. The inferred admixture dates for most of the HM speakers overlap with the reign of the Ming dynasty (1368-1644 CE). Besides a common genetic origin for HM speakers, their genetic ancestry is shared primarily with neighboring Han Chinese and Tai-Kadai speakers in south China. In conclusion, our analyses reveal that recent isolation and admixture events have contributed to the genetic population history of present-day HM speakers.

Cancer risks among first-degree relatives of women with a genetic predisposition to breast cancer

BACKGROUND

Associations between germline alterations in women and cancer risks among their relatives are largely unknown.

METHODS

We identified women from 2 Swedish cohorts Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) and prevalent KARMA (pKARMA), including 28 362 women with genotyping data and 13 226 with sequencing data. Using Swedish Multi-Generation Register, we linked these women to 133 389 first-degree relatives. Associations between protein-truncating variants in 8 risk genes and breast cancer polygenic risk score in index women and cancer risks among their relatives were modeled via Cox regression.

RESULTS

Female relatives of index women who were protein-truncating variant carriers in any of the 8 risk genes had an increased breast cancer risk compared with those of noncarriers (hazard ratio [HR] = 1.85, 95% confidence interval [CI] = 1.52 to 2.27), with the strongest association found for protein-truncating variants in BRCA1 and 2. These relatives had a statistically higher risk of early onset than late-onset breast cancer (P = .001). Elevated breast cancer risk was also observed in female relatives of index women with higher polygenic risk score (HR per SD = 1.28, 95% CI = 1.23 to 1.32). The estimated lifetime risk was 22.3% for female relatives of protein-truncating variant carriers and 14.4% for those related to women in the top polygenic risk score quartile. Moreover, relatives of index women with protein-truncating variant presence (HR = 1.30, 95% CI = 1.06 to 1.59) or higher polygenic risk score (HR per SD = 1.04, 95% CI = 1.01 to 1.07) were also at higher risk of nonbreast hereditary breast and ovary cancer syndrome-related cancers.

CONCLUSIONS

Protein-truncating variants of risk genes and higher polygenic risk score in index women are associated with an increased risk of breast and other hereditary breast and ovary syndrome-related cancers among relatives.

History of tuberculosis disease is associated with genetic regulatory variation in Peruvians

A quarter of humanity is estimated to have been exposed to Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs). We recruited former household contacts of TB patients who previously progressed to TB (cases, n = 63) or did not progress to TB (controls, n = 63). Transcriptomic profiling of monocyte-derived DCs and macrophages measured the impact of genetic variants on gene expression by identifying expression quantitative trait loci (eQTL). We identified 330 and 257 eQTL genes in DCs and macrophages (False Discovery Rate (FDR) < 0.05), respectively. Four genes in DCs showed interaction between eQTL variants and TB progression status. The top eQTL interaction for a protein-coding gene was with FAH, the gene encoding fumarylacetoacetate hydrolase, which mediates the last step in mammalian tyrosine catabolism. FAH expression was associated with genetic regulatory variation in cases but not controls. Using public transcriptomic and epigenomic data of Mtb-infected monocyte-derived dendritic cells, we found that Mtb infection results in FAH downregulation and DNA methylation changes in the locus. Overall, this study demonstrates effects of genetic variation on gene expression levels that are dependent on history of infectious disease and highlights a candidate pathogenic mechanism through pathogen-response genes. Furthermore, our results point to tyrosine metabolism and related candidate TB progression pathways for further investigation.

Gene - maltreatment interplay in adult ADHD symptoms: main role of a gene-environment correlation effect in a Brazilian population longitudinal study

Childhood maltreatment correlates with attention-deficit/hyperactivity disorder (ADHD) in previous research. The interaction between ADHD genetic predisposition and maltreatment's impact on ADHD symptom risk remains unclear. We aimed to elucidate this relationship by examining the interplay between a polygenic score for ADHD (ADHD-PGS) and childhood maltreatment in predicting ADHD symptoms during young adulthood. Using data from the 2004 Pelotas (Brazil) birth cohort comprising 4231 participants, we analyzed gene-environment interaction (GxE) and correlation (rGE). We further explored rGE mechanisms through mediation models. ADHD symptoms were assessed at age 18 via self-report (Adult Self Report Scale - ASRS) and mother-reports (Strength and Difficulties Questionnaire - SDQ). The ADHD-PGS was derived from published ADHD GWAS meta-analysis. Physical and psychological child maltreatment was gauged using the Parent-Child Conflict Tactics Scale (CTSPC) at ages 6 and 11, with a mean score utilized as a variable. The ADHD-PGS exhibited associations with ADHD symptoms on both ASRS (β = 0.53; 95% CI: 0.03; 1.03, p = 0.036), and SDQ (β = 0.20; 95% CI: 0.08; 0.32, p = 0.001) scales. The total mean maltreatment score was associated with ADHD symptoms using both scales [(βASRS = 0.51; 95% CI: 0.26;0.77) and (βSDQ = 0.24; 95% CI: 0.18;0.29)]. The ADHD-PGS was associated with total mean maltreatment scores (β = 0.09; 95% CI: 0.01; 0.17; p = 0.030). Approximately 47% of the total effect of ADHD-PGS on maltreatment was mediated by ADHD symptoms at age 6. No evidence supported gene-environment interaction in predicting ADHD symptoms. Our findings underscore the significant roles of genetics and childhood maltreatment as predictors for ADHD symptoms in adulthood, while also indicating a potential evocative mechanism through gene-environment correlation.

Understanding the genomic heterogeneity of North African Imazighen: from broad to microgeographical perspectives

The strategic location of North Africa has led to cultural and demographic shifts, shaping its genetic structure. Historical migrations brought different genetic components that are evident in present-day North African genomes, along with autochthonous components. The Imazighen (plural of Amazigh) are believed to be the descendants of autochthonous North Africans and speak various Amazigh languages, which belong to the Afro-Asiatic language family. However, the arrival of different human groups, especially during the Arab conquest, caused cultural and linguistic changes in local populations, increasing their heterogeneity. We aim to characterize the genetic structure of the region, using the largest Amazigh dataset to date and other reference samples. Our findings indicate microgeographical genetic heterogeneity among Amazigh populations, modeled by various admixture waves and different effective population sizes. A first admixture wave is detected group-wide around the twelfth century, whereas a second wave appears in some Amazigh groups around the nineteenth century. These events involved populations with higher genetic ancestry from south of the Sahara compared to the current North Africans. A plausible explanation would be the historical trans-Saharan slave trade, which lasted from the Roman times to the nineteenth century. Furthermore, our investigation shows that assortative mating in North Africa has been rare.

Selection signatures and landscape genomics analysis to reveal climate adaptation of goat breeds

Goats have achieved global prominence as essential livestock since their initial domestication, primarily owing to their remarkable adaptability to diverse environmental and production systems. Differential selection pressures influenced by climate have led to variations in their physical attributes, leaving genetic imprints within the genomes of goat breeds raised in diverse agroecological settings. In light of this, our study pursued a comprehensive analysis, merging environmental data with single nucleotide polymorphism (SNP) variations, to unearth indications of selection shaped by climate-mediated forces in goats. Through the examination of 43,300 SNPs from 51 indigenous goat breeds adapting to different climatic conditions using four analytical methods: latent factor mixed models (LFMM), F-statistics (Fst), Extended haplotype homozygosity across populations (XPEHH), and spatial analysis method (SAM), A total of 74 genes were revealed to display clear signs of selection, which are believed to be influenced by climatic conditions. Among these genes, 32 were consistently identified by at least two of the applied methods, and three genes (DENND1A, PLCB1, and ITPR2) were confirmed by all four approaches. Moreover, our investigation yielded 148 Gene Ontology (GO) terms based on these 74 genes, underlining pivotal biological pathways crucial for environmental adaptation. These pathways encompass functions like vascular smooth muscle contraction, cellular response to heat, GTPase regulator activity, rhythmic processes, and responses to temperature stimuli. Of significance, GO terms about endocrine regulation and energy metabolic responses, key for local adaptation were also uncovered, including biological processes, such as cell differentiation, regulation of peptide hormone secretion, and lipid metabolism. These findings contribute to our knowledge of the genetic structure of climate-triggered adaptation across the goat genome and have practical implications for marker-assisted breeding in goats.

Whole-genome resequencing of Chinese indigenous sheep provides insight into the genetic basis underlying climate adaptation

BACKGROUND

Chinese indigenous sheep are valuable resources with unique features and characteristics. They are distributed across regions with different climates in mainland China; however, few reports have analyzed the environmental adaptability of sheep based on their genome. We examined the variants and signatures of selection involved in adaptation to extreme humidity, altitude, and temperature conditions in 173 sheep genomes from 41 phenotypically and geographically representative Chinese indigenous sheep breeds to characterize the genetic basis underlying environmental adaptation in these populations.

RESULTS

Based on the analysis of population structure, we inferred that Chinese indigenous sheep are divided into four groups: Kazakh (KAZ), Mongolian (MON), Tibetan (TIB), and Yunnan (YUN). We also detected a set of candidate genes that are relevant to adaptation to extreme environmental conditions, such as drought-prone regions (TBXT, TG, and HOXA1), high-altitude regions (DYSF, EPAS1, JAZF1, PDGFD, and NF1) and warm-temperature regions (TSHR, ABCD4, and TEX11). Among all these candidate genes, eight ABCD4, CNTN4, DOCK10, LOC105608545, LOC121816479, SEM3A, SVIL, and TSHR overlap between extreme environmental conditions. The TSHR gene shows a strong signature for positive selection in the warm-temperature group and harbors a single nucleotide polymorphism (SNP) missense mutation located between positions 90,600,001 and 90,650,001 on chromosome 7, which leads to a change in the protein structure of TSHR and influences its stability.

CONCLUSIONS

Analysis of the signatures of selection uncovered genes that are likely related to environmental adaptation and a SNP missense mutation in the TSHR gene that affects the protein structure and stability. It also provides information on the evolution of the phylogeographic structure of Chinese indigenous sheep populations. These results provide important genetic resources for future breeding studies and new perspectives on how animals can adapt to climate change.

Persistent DNA Methylation Changes across the First Year of Life and Prenatal NO2 Exposure in a Canadian Prospective Birth Study

BACKGROUND

Evidence suggests that prenatal air pollution exposure alters DNA methylation (DNAm), which could go on to affect long-term health. It remains unclear whether DNAm alterations present at birth persist through early life. Identifying persistent DNAm changes would provide greater insight into the molecular mechanisms contributing to the association of prenatal air pollution exposure with atopic diseases.

OBJECTIVES

This study investigated DNAm differences associated with prenatal nitrogen dioxide (NO 2 ) exposure (a surrogate measure of traffic-related air pollution) at birth and 1 y of age and examined their role in atopic disease. We focused on regions showing persistent DNAm differences from birth to 1 y of age and regions uniquely associated with postnatal NO 2 exposure.

METHODS

Microarrays measured DNAm at birth and at 1 y of age for an atopy-enriched subset of Canadian Health Infant Longitudinal Development (CHILD) study participants. Individual and regional DNAm differences associated with prenatal NO 2 (n = 128 ) were identified, and their persistence at age 1 y were investigated using linear mixed effects models (n = 124 ). Postnatal-specific DNAm differences (n = 125 ) were isolated, and their association with NO 2 in the first year of life was examined. Causal mediation investigated whether DNAm differences mediated associations between NO 2 and age 1 y atopy or wheeze. Analyses were repeated using biological sex-stratified data.

RESULTS

At birth (n = 128 ), 18 regions of DNAm were associated with NO 2 , with several annotated to HOX genes. Some of these regions were specifically identified in males (n = 73 ), but not females (n = 55 ). The effect of prenatal NO 2 across CpGs within altered regions persisted at 1 y of age. No significant mediation effects were identified. Sex-stratified analyses identified postnatal-specific DNAm alterations.

DISCUSSION

Regional cord blood DNAm differences associated with prenatal NO 2 persisted through at least the first year of life in CHILD participants. Some differences may represent sex-specific alterations, but replication in larger cohorts is needed. The early postnatal period remained a sensitive window to DNAm perturbations. https://doi.org/10.1289/EHP13034.

Genome-wide association study of nausea and vomiting during pregnancy in Japan: the TMM BirThree Cohort Study

BACKGROUND

Nausea and vomiting during pregnancy (NVP) and hyperemesis gravidarum (HG), common conditions affecting most pregnant women, are highly heritable and associated with maternal and fetal morbidity. However, the pathologies underlying NVP and HG and their associated loci are scarce.

METHODS

We performed genome-wide association studies (GWAS) of NVP in pregnant women (n = 23,040) who participated in the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study in Japan from July 2013 to March 2017. Participants were divided into discovery (n = 9,464) and replication (n = 10,051) stages based on the platform used for their genotyping. Loci that achieved the genome-wide significance level (p < 5.0 × 10- 8) in the discovery stage were selected for genotyping in the replication stage. A meta-analysis integrating the discovery and replication stage results (n = 19,515) was conducted. NVP-related variables were identified as categorical or continuous.

RESULTS

GWAS analysis in the discovery phase revealed loci linked to NVP in two gene regions, 11q22.1 (rs77775955) and 19p13.11 (rs749451 and rs28568614). Loci in these two gene regions have also been shown to be associated with HG in a White European population, indicating the generalizability of the GWAS analyses conducted in this study. Of these, only rs749451 and rs28568614 at 19p13.11 reached the genome-wide suggestive level (p < 1.0 × 10- 5) in the replication stage; however, both loci were significant in the meta-analysis.

CONCLUSIONS

NVP-related loci were identified in the Japanese population at 11q22.1 and 19p13.11, as reported in previous GWAS. This study contributes new evidence on the generalizability of previous GWAS on the association between genetic background and NVP.

Genomic Analyses Capture the Human-Induced Demographic Collapse and Recovery in a Wide-Ranging Cervid

The glacial cycles of the Quaternary heavily impacted species through successions of population contractions and expansions. Similarly, populations have been intensely shaped by human pressures such as unregulated hunting and land use changes. White-tailed and mule deer survived in different refugia through the Last Glacial Maximum, and their populations were severely reduced after the European colonization. Here, we analyzed 73 resequenced deer genomes from across their North American range to understand the consequences of climatic and anthropogenic pressures on deer demographic and adaptive history. We found strong signals of climate-induced vicariance and demographic decline; notably, multiple sequentially Markovian coalescent recovers a severe decline in mainland white-tailed deer effective population size (Ne) at the end of the Last Glacial Maximum. We found robust evidence for colonial overharvest in the form of a recent and dramatic drop in Ne in all analyzed populations. Historical census size and restocking data show a clear parallel to historical Ne estimates, and temporal Ne/Nc ratio shows patterns of conservation concern for mule deer. Signatures of selection highlight genes related to temperature, including a cold receptor previously highlighted in woolly mammoth. We also detected immune genes that we surmise reflect the changing land use patterns in North America. Our study provides a detailed picture of anthropogenic and climatic-induced decline in deer diversity and clues to understanding the conservation concerns of mule deer and the successful demographic recovery of white-tailed deer.

Comparing feature selection and machine learning approaches for predicting CYP2D6 methylation from genetic variation

Introduction

Pharmacogenetics currently supports clinical decision-making on the basis of a limited number of variants in a few genes and may benefit paediatric prescribing where there is a need for more precise dosing. Integrating genomic information such as methylation into pharmacogenetic models holds the potential to improve their accuracy and consequently prescribing decisions. Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic gene conventionally associated with the metabolism of commonly used drugs and endogenous substrates. We thus sought to predict epigenetic loci from single nucleotide polymorphisms (SNPs) related to CYP2D6 in children from the GUSTO cohort.

Methods

Buffy coat DNA methylation was quantified using the Illumina Infinium Methylation EPIC beadchip. CpG sites associated with CYP2D6 were used as outcome variables in Linear Regression, Elastic Net and XGBoost models. We compared feature selection of SNPs from GWAS mQTLs, GTEx eQTLs and SNPs within 2 MB of the CYP2D6 gene and the impact of adding demographic data. The samples were split into training (75%) sets and test (25%) sets for validation. In Elastic Net model and XGBoost models, optimal hyperparameter search was done using 10-fold cross validation. Root Mean Square Error and R-squared values were obtained to investigate each models' performance. When GWAS was performed to determine SNPs associated with CpG sites, a total of 15 SNPs were identified where several SNPs appeared to influence multiple CpG sites.

Results

Overall, Elastic Net models of genetic features appeared to perform marginally better than heritability estimates and substantially better than Linear Regression and XGBoost models. The addition of nongenetic features appeared to improve performance for some but not all feature sets and probes. The best feature set and Machine Learning (ML) approach differed substantially between CpG sites and a number of top variables were identified for each model.

Discussion

The development of SNP-based prediction models for CYP2D6 CpG methylation in Singaporean children of varying ethnicities in this study has clinical application. With further validation, they may add to the set of tools available to improve precision medicine and pharmacogenetics-based dosing.

Differences in polygenic score distributions in European ancestry populations: implications for breast cancer risk prediction

The 313-variant polygenic risk score (PRS313) provides a promising tool for breast cancer risk prediction. However, evaluation of the PRS313 across different European populations which could influence risk estimation has not been performed. Here, we explored the distribution of PRS313 across European populations using genotype data from 94,072 females without breast cancer, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 225,105 female participants from the UK Biobank. The mean PRS313 differed markedly across European countries, being highest in south-eastern Europe and lowest in north-western Europe. Using the overall European PRS313 distribution to categorise individuals leads to overestimation and underestimation of risk in some individuals from south-eastern and north-western countries, respectively. Adjustment for principal components explained most of the observed heterogeneity in mean PRS. Country-specific PRS distributions may be used to calibrate risk categories in individuals from different countries.

Star allele search: a pharmacogenetic annotation database and user-friendly search tool of publicly available 1000 Genomes Project biospecimens

Here we describe a new public pharmacogenetic (PGx) annotation database of a large (n = 3,202) and diverse biospecimen collection of 1000 Genomes Project cell lines and DNAs. The database is searchable with a user friendly, web-based tool ( www.coriell.org/StarAllele/Search ). This resource leverages existing whole genome sequencing data and PharmVar annotations to characterize *alleles for each biospecimen in the collection. This new tool is designed to facilitate in vitro functional characterization of *allele haplotypes and diplotypes as well as support clinical PGx assay development, validation, and implementation.

Reconstructing complex admixture history using a hierarchical model

Various methods have been proposed to reconstruct admixture histories by analyzing the length of ancestral chromosomal tracts, such as estimating the admixture time and number of admixture events. However, available methods do not explicitly consider the complex admixture structure, which characterizes the joining and mixing patterns of different ancestral populations during the admixture process, and instead assume a simplified one-by-one sequential admixture model. In this study, we proposed a novel approach that considers the non-sequential admixture structure to reconstruct admixture histories. Specifically, we introduced a hierarchical admixture model that incorporated four ancestral populations and developed a new method, called HierarchyMix, which uses the length of ancestral tracts and the number of ancestry switches along genomes to reconstruct the four-way admixture history. By automatically selecting the optimal admixture model using the Bayesian information criterion principles, HierarchyMix effectively estimates the corresponding admixture parameters. Simulation studies confirmed the effectiveness and robustness of HierarchyMix. We also applied HierarchyMix to Uyghurs and Kazakhs, enabling us to reconstruct the admixture histories of Central Asians. Our results highlight the importance of considering complex admixture structures and demonstrate that HierarchyMix is a useful tool for analyzing complex admixture events.

Immune-response 3'UTR alternative polyadenylation quantitative trait loci contribute to variation in human complex traits and diseases

Genome-wide association studies (GWASs) have identified thousands of non-coding variants that are associated with human complex traits and diseases. The analysis of such GWAS variants in different contexts and physiological states is essential for deciphering the regulatory mechanisms underlying human disease. Alternative polyadenylation (APA) is a key post-transcriptional modification for most human genes that substantially impacts upon cell behavior. Here, we mapped 9,493 3'-untranslated region APA quantitative trait loci in 18 human immune baseline cell types and 8 stimulation conditions (immune 3'aQTLs). Through the comparison between baseline and stimulation data, we observed the high responsiveness of 3'aQTLs to immune stimulation (response 3'aQTLs). Co-localization and mendelian randomization analyses of immune 3'aQTLs identified 678 genes where 3'aQTL are associated with variation in complex traits, 27.3% of which were derived from response 3'aQTLs. Overall, these analyses reveal the role of immune 3'aQTLs in the determination of complex traits, providing new insights into the regulatory mechanisms underlying disease etiologies.

A purebred South American breed showing high effective population size and independent breed ancestry: The Chilean Terrier

The Chilean Terrier is a known breed in Chile that has not been genetically assessed despite its distinctive color patterns, agility, and hardiness across the diversity of climates encountered within the Chilean landscape. The population structure and its relatedness with other breeds, as well as the actual origin of the breed, remain unknown. We estimated several population parameters using samples from individuals representing the distribution of the Chilean Terrier across the country. By utilizing the Illumina HD canine genotyping array, we computed the effective population size (Ne ), individual inbreeding, and relatedness to evaluate the genetic diversity of the breed. The results show that linkage disequilibrium was relatively low and decayed rapidly; in fact, Ne was very high when compared to other breeds, and similar to other American indigenous breeds (such as the Chihuahua with values of Ne near 500). These results are in line with the low estimates of genomic inbreeding and relatedness and the relatively large number of effective chromosome segments (Me  = 2467) obtained using the properties of the genomic relationship matrix. Between population analysis (cross-population extended haplotype homozygosity, di ) with other breeds such as the Jack Russell Terrier, the Peruvian-Inca Orchid, and the Chihuahua suggested that candidate regions harboring FGF5, PAX3, and ASIP, probably explained some morphological traits, such as the distinctive color pattern characteristic of the breed. When considering Admixture estimates and phylogenetic analysis, together with other breeds of American and European origin, the Chilean Terrier does not have a recent European ancestry. Overall, the results suggest that the breed has evolved independently in Chile from other terrier breeds, from an unknown European terrier ancestor.

Identifying genetic variants that influence the abundance of cell states in single-cell data

To understand genetic mechanisms driving disease, it is essential but difficult to map how risk alleles affect the composition of cells present in the body. Single-cell profiling quantifies granular information about tissues, but variant-associated cell states may reflect diverse combinations of the profiled cell features that are challenging to predefine. We introduce GeNA (Genotype-Neighborhood Associations), a statistical tool to identify cell state abundance quantitative trait loci (csaQTLs) in high-dimensional single-cell datasets. Instead of testing associations to predefined cell states, GeNA flexibly identifies the cell states whose abundance is most associated with genetic variants. In a genome-wide survey of scRNA-seq peripheral blood profiling from 969 individuals,1GeNA identifies five independent loci associated with shifts in the relative abundance of immune cell states. For example, rs3003-T (p=1.96×10-11) associates with increased abundance of NK cells expressing TNF-α response programs. This csaQTL colocalizes with increased risk for psoriasis, an autoimmune disease that responds to anti-TNF treatments. Flexibly characterizing csaQTLs for granular cell states may help illuminate how genetic background alters cellular composition to confer disease risk.

Eurasian back-migration into Northeast Africa was a complex and multifaceted process

Recent studies have identified Northeast Africa as an important area for human movements during the Holocene. Eurasian populations have moved back into Northeastern Africa and contributed to the genetic composition of its people. By gathering the largest reference dataset to date of Northeast, North, and East African as well as Middle Eastern populations, we give new depth to our knowledge of Northeast African demographic history. By employing local ancestry methods, we isolated the Non-African parts of modern-day Northeast African genomes and identified the best putative source populations. Egyptians and Sudanese Copts bore most similarities to Levantine populations whilst other populations in the region generally had predominantly genetic contributions from the Arabian peninsula rather than Levantine populations for their Non-African genetic component. We also date admixture events and investigated which factors influenced the date of admixture and find that major linguistic families were associated with the date of Eurasian admixture. Taken as a whole we detect complex patterns of admixture and diverse origins of Eurasian admixture in Northeast African populations of today.

Prediction of breast cancer risk for sisters of women attending screening

BACKGROUND

Risk assessment is important for breast cancer prevention and early detection. We aimed to examine whether common risk factors, mammographic features, and breast cancer risk prediction scores of a woman were associated with breast cancer risk for her sisters.

METHODS

We included 53 051 women from the Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) study. Established risk factors were derived using self-reported questionnaires, mammograms, and single nucleotide polymorphism genotyping. Using the Swedish Multi-Generation Register, we identified 32 198 sisters of the KARMA women (including 5352 KARMA participants and 26 846 nonparticipants). Cox models were used to estimate the hazard ratios of breast cancer for both women and their sisters, respectively.

RESULTS

A higher breast cancer polygenic risk score, a history of benign breast disease, and higher breast density in women were associated with an increased risk of breast cancer for both women and their sisters. No statistically significant association was observed between breast microcalcifications and masses in women and breast cancer risk for their sisters. Furthermore, higher breast cancer risk scores in women were associated with an increased risk of breast cancer for their sisters. Specifically, the hazard ratios for breast cancer per 1 standard deviation increase in age-adjusted KARMA, Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), and Tyrer-Cuzick risk scores were 1.16 (95% confidence interval [CI] = 1.07 to 1.27), 1.23 (95% CI = 1.12 to 1.35), and 1.21 (95% CI = 1.11 to 1.32), respectively.

CONCLUSION

A woman's breast cancer risk factors are associated with her sister's breast cancer risk. However, the clinical utility of these findings requires further investigation.

The parasitic nematode Strongyloides ratti exists predominantly as populations of long-lived asexual lineages

Nematodes are important parasites of people and animals, and in natural ecosystems they are a major ecological force. Strongyloides ratti is a common parasitic nematode of wild rats and we have investigated its population genetics using single-worm, whole-genome sequencing. We find that S. ratti populations in the UK consist of mixtures of mainly asexual lineages that are widely dispersed across a host population. These parasite lineages are likely very old and may have originated in Asia from where rats originated. Genes that underly the parasitic phase of the parasite's life cycle are hyperdiverse compared with the rest of the genome, and this may allow the parasites to maximise their fitness in a diverse host population. These patterns of parasitic nematode population genetics have not been found before and may also apply to Strongyloides spp. that infect people, which will affect how we should approach their control.

Genetic Origins and Adaptive Evolution of the Deng People on the Tibetan Plateau

The Tibetan Plateau is populated by diverse ethnic groups, but most of them are underrepresented in genomics studies compared with the Tibetans (TIB). Here, to gain further insight into the genetic diversity and evolutionary history of the people living in the Tibetan Plateau, we sequenced 54 whole genomes of the Deng people with high coverage (30-60×) and analyzed the data together with that of TIB and Sherpas, as well as 968 ancient Asian genomes and available archaic and modern human data. We identified 17.74 million novel single-nucleotide variants from the newly sequenced genomes, although the Deng people showed reduced genomic diversity and a relatively small effective population size. Compared with the other Tibetan highlander groups which are highly admixed, the Deng people are dominated by a sole ancestry that could be traced to some ancient northern East Asian populations. The divergence between Deng and Tibetan people (∼4,700-7,200 years) was more recent than that between highlanders and the Han Chinese (Deng-HAN, ∼9,000-14,000 years; TIB-HAN, 7,200-10,000 years). Adaptive genetic variants (AGVs) identified in the Deng are only partially shared with those previously reported in the TIB like HLA-DQB1, whereas others like KLHL12 were not reported in TIB. In contrast, the top candidate genes harboring AGVs as previously identified in TIB, like EPAS1 and EGLN1, do not show strong positive selection signals in Deng. Interestingly, Deng also showed a different archaic introgression scenario from that observed in the TIB. Our results suggest that convergent adaptation might be prevalent on the Tibetan Plateau.

Identifying crossovers and shared genetic material in whole genome sequencing data from families

Large, whole-genome sequencing (WGS) data sets containing families provide an important opportunity to identify crossovers and shared genetic material in siblings. However, the high variant calling error rates of WGS in some areas of the genome can result in spurious crossover calls, and the special inheritance status of the X Chromosome presents challenges. We have developed a hidden Markov model that addresses these issues by modeling the inheritance of variants in families in the presence of error-prone regions and inherited deletions. We call our method PhasingFamilies. We validate PhasingFamilies using the platinum genome family NA1281 (precision: 0.81; recall: 0.97), as well as simulated genomes with known crossover positions (precision: 0.93; recall: 0.92). Using 1925 quads from the Simons Simplex Collection, we found that PhasingFamilies resolves crossovers to a median resolution of 3527.5 bp. These crossovers recapitulate existing recombination rate maps, including for the X Chromosome; produce sibling pair IBD that matches expected distributions; and are validated by the haplotype estimation tool SHAPEIT. We provide an efficient, open-source implementation of PhasingFamilies that can be used to identify crossovers from family sequencing data.

Interaction of Mitochondrial Polygenic Score and Lifestyle Factors in LRRK2 p.Gly2019Ser Parkinsonism

BACKGROUND

A mitochondrial polygenic score (MGS) is composed of genes related to mitochondrial function and found to be associated with Parkinson's disease (PD) risk.

OBJECTIVE

To investigate the impact of the MGS and lifestyle/environment on age at onset (AAO) in LRRK2 p.Gly2019Ser parkinsonism (LRRK2-PD) and idiopathic PD (iPD).

METHODS

We included N = 486 patients with LRRK2-PD and N = 9259 with iPD from the Accelerating Medicines Partnership® Parkinson's Disease Knowledge Platform (AMP-PD), Fox Insight, and a Tunisian Arab-Berber founder population. Genotyping data were used to perform the MGS analysis. Additionally, lifestyle/environmental data were obtained from the PD Risk Factor Questionnaire (PD-RFQ). Linear regression models were used to assess the relationship between MGS, lifestyle/environment, and AAO.

RESULTS

Our derived MGS was significantly higher in PD cases compared with controls (P = 1.1 × 10-8 ). We observed that higher MGS was significantly associated with earlier AAO in LRRK2-PD (P = 0.047, β = -1.40) and there was the same trend with a smaller effect size in iPD (P = 0.231, β = 0.22). There was a correlation between MGS and AAO in LRRK2-PD patients of European descent (P = 0.049, r = -0.12) that was visibly less pronounced in Tunisians (P = 0.449, r = -0.05). We found that the MGS interacted with caffeinated soda consumption (P = 0.003, β = -5.65) in LRRK2-PD and with tobacco use (P = 0.010, β = 1.32) in iPD. Thus, patients with a high MGS had an earlier AAO only if they consumed caffeinated soda or were non-smokers.

CONCLUSIONS

The MGS was more strongly associated with earlier AAO in LRRK2-PD compared with iPD. Caffeinated soda consumption or tobacco use interacted with MGS to predict AAO. Our study suggests gene-environment interactions as modifiers of AAO in LRRK2-PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A novel antisense lncRNA, ARBAG harboring an RNA destabilizing GWAS variant for C-peptide dictates the transcript isoforms of GABRA6 in cerebellum

Human disease-associated genetic variations often map to long non-coding RNA (lncRNA) genes; however, elucidation of their functional impact is challenging. We previously identified a new genetic variant rs4454083 (A/G) residing in exon of an uncharacterized lncRNA ARBAG that strongly associates with plasma levels of C-peptide, a hormone that regulates insulin bioavailability. On the opposite strand, rs4454083 also corresponds to an intron of a cerebellum-specific GABA receptor subunit gene GABRA6 that mediates strengthening of inhibitory synapses by insulin. Here, we show that alleles of rs4454083 modulate transcript levels of the antisense gene, ARBAG, which then controls the expression of the sense gene, GABRA6. Predisposing to low C-peptide, GG (a minor allele genotype across ethnicities) stabilizes ARBAG lncRNA causing higher transcript levels in cerebellum. ARBAG lncRNA abundance leads to cleavage of GABRA6 mRNA at the complementary region, resulting in a dysfunctional GABRA6 protein that would not be recruited for synapse strengthening. Together, our findings in human cerebellar cell-line and induced Pluripotent Stem Cells (iPSCs) demonstrate biological role of a novel lncRNA in determining the ratio of mRNA isoforms of a protein-coding gene and the ability of an embedded variant in modulating lncRNA stability leading to inter-individual differences in protein expression.

A Breast Cancer Polygenic Risk Score Is Feasible for Risk Stratification in the Norwegian Population

BACKGROUND

Statistical associations of numerous single nucleotide polymorphisms with breast cancer (BC) have been identified in genome-wide association studies (GWAS). Recent evidence suggests that a Polygenic Risk Score (PRS) can be a useful risk stratification instrument for a BC screening strategy, and a PRS test has been developed for clinical use. The performance of the PRS is yet unknown in the Norwegian population.

AIM

To evaluate the performance of PRS models for BC in a Norwegian dataset.

METHODS

We investigated a sample of 1053 BC cases and 7094 controls from different regions of Norway. PRS values were calculated using four PRS models, and their performance was evaluated by the area under the curve (AUC) and the odds ratio (OR). The effect of the PRS on the age of onset of BC was determined by a Cox regression model, and the lifetime absolute risk of developing BC was calculated using the iCare tool.

RESULTS

The best performing PRS model included 3820 SNPs, which yielded an AUC = 0.625 and an OR = 1.567 per one standard deviation increase. The PRS values of the samples correlate with an increased risk of BC, with a hazard ratio of 1.494 per one standard deviation increase (95% confidence interval of 1.406-1.588). The individuals in the highest decile of the PRS have at least twice the risk of developing BC compared to the individuals with a median PRS. The results in this study with Norwegian samples are coherent with the findings in the study conducted using Estonian and UK Biobank samples.

CONCLUSION

The previously validated PRS models have a similar observed accuracy in the Norwegian data as in the UK and Estonian populations. A PRS provides a meaningful association with the age of onset of BC and lifetime risk. Therefore, as suggested in Estonia, a PRS may also be integrated into the screening strategy for BC in Norway.

Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-sequencing data in GTEx V8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased whole genome sequencing data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

Microevolutionary processes analysis in the Lithuanian genome

Differences in the relative fitness of genomic variants are foundational, without these, neither natural selection nor adaption can exist. This research analyzed two microevolutionary forces, mutations, and positive selection, using whole genome sequencing data from Lithuanians across three generations: newborns (generation I), their parents (generation II), 60 years old Lithuanians, and the root ancestors (generation III). The main objective was to determine the frequency of mutations under selection in modern humans and how allele frequencies change across generations. Our results show that going through all the landscapes of the relative fitness on each chromosome, the general relative fitness background pattern remains the same in analysed generations. However, the tendency of relative fitness to decrease, in general, is noted. We hypothesize that the de novo genome variants or genome variants with a very low frequency that formed in the previous generation did not have time to be as affected by natural selection, thus, in the following generation, the force of natural selection acting on them is greater and their cumulative relative fitness also decreases. The strong natural selection pressure on the genetic regions that encode the NEGR1 and PTPN1/PTNP21 genes were also identified, highlighting the evolution of the Lithuanian population's genome over generations, and possible genomic "deficiencies" for better adaptation.

Time-varying effects are common in genetic control of gestational duration

Preterm birth is a major burden to neonatal health worldwide, determined in part by genetics. Recently, studies discovered several genes associated with this trait or its continuous equivalent-gestational duration. However, their effect timing, and thus clinical importance, is still unclear. Here, we use genotyping data of 31 000 births from the Norwegian Mother, Father and Child cohort (MoBa) to investigate different models of the genetic pregnancy 'clock'. We conduct genome-wide association studies using gestational duration or preterm birth, replicating known maternal associations and finding one new fetal variant. We illustrate how the interpretation of these results is complicated by the loss of power when dichotomizing. Using flexible survival models, we resolve this complexity and find that many of the known loci have time-varying effects, often stronger early in pregnancy. The overall polygenic control of birth timing appears to be shared in the term and preterm, but not very preterm, periods and exploratory results suggest involvement of the major histocompatibility complex genes in the latter. These findings show that the known gestational duration loci are clinically relevant and should help design further experimental studies.

Combined genome-wide association study of 136 quantitative ear morphology traits in multiple populations reveal 8 novel loci

Human ear morphology, a complex anatomical structure represented by a multidimensional set of correlated and heritable phenotypes, has a poorly understood genetic architecture. In this study, we quantitatively assessed 136 ear morphology traits using deep learning analysis of digital face images in 14,921 individuals from five different cohorts in Europe, Asia, and Latin America. Through GWAS meta-analysis and C-GWASs, a recently introduced method to effectively combine GWASs of many traits, we identified 16 genetic loci involved in various ear phenotypes, eight of which have not been previously associated with human ear features. Our findings suggest that ear morphology shares genetic determinants with other surface ectoderm-derived traits such as facial variation, mono eyebrow, and male pattern baldness. Our results enhance the genetic understanding of human ear morphology and shed light on the shared genetic contributors of different surface ectoderm-derived phenotypes. Additionally, gene editing experiments in mice have demonstrated that knocking out the newly ear-associated gene (Intu) and a previously ear-associated gene (Tbx15) causes deviating mouse ear morphology.

History of tuberculosis disease is associated with genetic regulatory variation in Peruvians

A quarter of humanity is estimated to be latently infected with Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs). We recruited former household contacts of TB patients who previously progressed to TB (cases, n=63) or did not progress to TB (controls, n=63). Transcriptomic profiling of monocyte-derived dendritic cells (DCs) and macrophages measured the impact of genetic variants on gene expression by identifying expression quantitative trait loci (eQTL). We identified 330 and 257 eQTL genes in DCs and macrophages (False Discovery Rate (FDR) < 0.05), respectively. Five genes in DCs showed interaction between eQTL variants and TB progression status. The top eQTL interaction for a protein-coding gene was with FAH, the gene encoding fumarylacetoacetate hydrolase, which mediates the last step in mammalian tyrosine catabolism. FAH expression was associated with genetic regulatory variation in cases but not controls. Using public transcriptomic and epigenomic data of Mtb-infected monocyte-derived dendritic cells, we found that Mtb infection results in FAH downregulation and DNA methylation changes in the locus. Overall, this study demonstrates effects of genetic variation on gene expression levels that are dependent on history of infectious disease and highlights a candidate pathogenic mechanism through pathogen-response genes. Furthermore, our results point to tyrosine metabolism and related candidate TB progression pathways for further investigation.

Invited review: Good practices in genome-wide association studies to identify candidate sequence variants in dairy cattle

Genotype data from dairy cattle selection programs have greatly facilitated GWAS to identify variants related to economic traits. Results can enhance the accuracy of genomic prediction, analyze more complex models that go beyond additive effects, elucidate the genetic architecture of a trait, and finally, decipher the underlying biology of traits. The entire process, comprising data generation, quality control, statistical analyses, interpretation of association results, and linking results to biology should be designed and executed to minimize the generation of false-positive and false-negative associations and misleading links to biological processes. This review aims to provide general guidelines for data analysis that address data quality control, association tests, adjustment for population stratification, and significance evaluation to improve the reliability of conclusions. We also provide guidance on post-GWAS strategy and the interpretation of results. These guidelines are tailored to dairy cattle, which are characterized by long-range linkage disequilibrium, large half-sib families, and routinely collected phenotypes, requiring different approaches than those applied in human GWAS. We discuss common limitations and challenges that have been overlooked in the analysis and interpretation of GWAS to identify candidate sequence variants in dairy cattle.

Germline de novo mutations in families with Mendelian cancer syndromes caused by defects in DNA repair

DNA repair defects underlie many cancer syndromes. We tested whether de novo germline mutations (DNMs) are increased in families with germline defects in polymerase proofreading or base excision repair. A parent with a single germline POLE or POLD1 mutation, or biallelic MUTYH mutations, had 3-4 fold increased DNMs over sex-matched controls. POLE had the largest effect. The DNMs carried mutational signatures of the appropriate DNA repair deficiency. No DNM increase occurred in offspring of MUTYH heterozygous parents. Parental DNA repair defects caused about 20-150 DNMs per child, additional to the ~60 found in controls, but almost all extra DNMs occurred in non-coding regions. No increase in post-zygotic mutations was detected, excepting a child with bi-allelic MUTYH mutations who was excluded from the main analysis; she had received chemotherapy and may have undergone oligoclonal haematopoiesis. Inherited DNA repair defects associated with base pair-level mutations increase DNMs, but phenotypic consequences appear unlikely.

Multi-ethnic imputation system (MI-System): a genotype imputation server for high-dimensional data

OBJECTIVE

Genotype imputation is a commonly used technique that infers un-typed variants into a study's genotype data, allowing better identification of causal variants in disease studies. However, due to overrepresentation of Caucasian studies, there's a lack of understanding of genetic basis of health-outcomes in other ethnic populations. Therefore, facilitating imputation of missing key-predictor-variants that can potentially improve a risk health-outcome prediction model, specifically for Asian ancestry, is of utmost relevance.

METHODS

We aimed to construct an imputation and analysis web-platform, that primarily facilitates, but is not limited to, genotype imputation on East-Asians. The goal is to provide a collaborative imputation platform for researchers in the public domain, towards rapidly and efficiently conducting accurate genotype imputation.

RESULTS

We present an online genotype imputation platform, Multi-ethnic Imputation System (MI-System) (https://misystem.cgm.ntu.edu.tw/), that offers users 3 established pipelines, SHAPEIT2-IMPUTE2, SHAPEIT4-IMPUTE5, and Beagle5.1 for conducting imputation analyses. In addition to 1000 Genomes and Hapmap3, a new customized Taiwan Biobank (TWB) reference panel, specifically created for Taiwanese-Chinese ancestry is provided. MI-System further offers functions to create customized reference panels to be used for imputation, conduct quality control, split whole genome data into chromosomes, and convert genome builds.

CONCLUSION

Users can upload their genotype data and perform imputation with minimum effort and resources. The utility functions further can be utilized to preprocess user uploaded data with easy clicks. MI-System potentially contributes to Asian-population genetics research, while eliminating the requirement for high performing computational resources and bioinformatics expertise. It will enable an increased pace of research and provide a knowledge-base for genetic carriers of complex diseases, therefore greatly enhancing patient-driven research.

STATEMENT OF SIGNIFICANCE

Multi-ethnic Imputation System (MI-System), primarily facilitates, but is not limited to, imputation on East-Asians, through 3 established prephasing-imputation pipelines, SHAPEIT2-IMPUTE2, SHAPEIT4-IMPUTE5, and Beagle5.1, where users can upload their genotype data and perform imputation and other utility functions with minimum effort and resources. A new customized Taiwan Biobank (TWB) reference panel, specifically created for Taiwanese-Chinese ancestry is provided. Utility functions include (a) create customized reference panels, (b) conduct quality control, (c) split whole genome data into chromosomes, and (d) convert genome builds. Users can also combine 2 reference panels using the system and use combined panels as reference to conduct imputation using MI-System.

Genome-wide aggregated trans-effects on risk of type 1 diabetes: A test of the "omnigenic" sparse effector hypothesis of complex trait genetics

The "omnigenic" hypothesis postulates that the polygenic effects of common SNPs on a typical complex trait are mediated through trans-effects on expression of a relatively sparse set of effector ("core") genes. We tested this hypothesis in a study of 4,964 cases of type 1 diabetes (T1D) and 7,497 controls by using summary statistics to calculate aggregated (excluding the HLA region) trans-scores for gene expression in blood. From associations of T1D with aggregated trans-scores, nine putative core genes were identified, of which three-STAT1, CTLA4 and FOXP3-are genes in which variants cause monogenic forms of autoimmune diabetes. Seven of these genes affect the activity of regulatory T cells, and two are involved in immune responses to microbial lipids. Four T1D-associated genomic regions could be identified as master regulators via trans-effects on gene expression. These results support the sparse effector hypothesis and reshape our understanding of the genetic architecture of T1D.

The making of the oral microbiome in Agta hunter-gatherers

Ecological and genetic factors have influenced the composition of the human microbiome during our evolutionary history. We analysed the oral microbiota of the Agta, a hunter-gatherer population where some members have adopted an agricultural diet. We show that age is the strongest factor modulating the microbiome, probably through immunosenescence since we identified an increase in the number of species classified as pathogens with age. We also characterised biological and cultural processes generating sexual dimorphism in the oral microbiome. A small subset of oral bacteria is influenced by the host genome, linking host collagen genes to bacterial biofilm formation. Our data also suggest that shifting from a fish/meat diet to a rice-rich diet transforms their microbiome, mirroring the Neolithic transition. All of these factors have implications in the epidemiology of oral diseases. Thus, the human oral microbiome is multifactorial and shaped by various ecological and social factors that modify the oral environment.

Automatic landmarking identifies new loci associated with face morphology and implicates Neanderthal introgression in human nasal shape

We report a genome-wide association study of facial features in >6000 Latin Americans based on automatic landmarking of 2D portraits and testing for association with inter-landmark distances. We detected significant associations (P-value <5 × 10-8) at 42 genome regions, nine of which have been previously reported. In follow-up analyses, 26 of the 33 novel regions replicate in East Asians, Europeans, or Africans, and one mouse homologous region influences craniofacial morphology in mice. The novel region in 1q32.3 shows introgression from Neanderthals and we find that the introgressed tract increases nasal height (consistent with the differentiation between Neanderthals and modern humans). Novel regions include candidate genes and genome regulatory elements previously implicated in craniofacial development, and show preferential transcription in cranial neural crest cells. The automated approach used here should simplify the collection of large study samples from across the world, facilitating a cosmopolitan characterization of the genetics of facial features.

Clinical case study meets population cohort: identification of a BRCA1 pathogenic founder variant in Orcadians

We multiply ascertained the BRCA1 pathogenic missense variant c.5207T > C; p.Val1736Ala (V1736A) in clinical investigation of breast and ovarian cancer families from Orkney in the Northern Isles of Scotland, UK. We sought to investigate the frequency and clinical relevance of this variant in those of Orcadian ancestry as an exemplar of the value of population cohorts in clinical care, especially in isolated populations. Oral history and birth, marriage and death registrations indicated genealogical linkage of the clinical cases to ancestors from the Isle of Westray, Orkney. Further clinical cases were identified through targeted testing for V1736A in women of Orcadian ancestry attending National Health Service (NHS) genetic clinics for breast and ovarian cancer family risk assessments. The variant segregates with female breast and ovarian cancer in clinically ascertained cases. Separately, exome sequence data from 2088 volunteer participants with three or more Orcadian grandparents, in the ORCADES research cohort, was interrogated to estimate the population prevalence of V1736A in Orcadians. The effects of the variant were assessed using Electronic Health Record (EHR) linkage. Twenty out of 2088 ORCADES research volunteers (~1%) carry V1736A, with a common haplotype around the variant. This allele frequency is ~480-fold higher than in UK Biobank participants. Cost-effectiveness of population screening for BRCA1 founder pathogenic variants has been demonstrated at a carrier frequency below the ~1% observed here. Thus we suggest that Orcadian women should be offered testing for the BRCA1 V1736A founder pathogenic variant, starting with those with known Westray ancestry.