Robust relationship inference in genome-wide association studies

Whole genome resequencing-based analysis of plateau adaptation in Meiren yak (Bos grunniens)

The Meiren yak is an important genetic resource in Gansu Province, China. In this study, we aimed to explore the evolutionary history and population structure of the genetic resource of Meiren yak and to mine the characteristic genes of Meiren yak. We analysed a total of 93 yaks of eight yak breeds based on whole genome resequencing combined with population genomics and used θπ ratio and Fst method to screen the selected sites in the genome region. The results proved that Meiren yak can be used as a potential genetic resource in Gansu Province. The genes in Meiren yak with positive selection in selection signal analysis were subjected to the Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses, which indicated that the genes were related to the adaptability to high altitude and hypoxic environment. By analysing the genetic variation of Meiren yak at the genome-wide level, this study provided a theoretical basis for genetic improvement of Meiren yak and for the development of high-quality yak resources.

Gene-gene interaction analysis for age at onset of bipolar disorder in a Korean population

BACKGROUND

Multiple genes might interact to determine the age at onset of bipolar disorder. We investigated gene-gene interactions related to age at onset of bipolar disorder in the Korean population, using genome-wide association study (GWAS) data.

METHODS

The study population consisted of 303 patients with bipolar disorder. First, the top 1000 significant single-nucleotide polymorphisms (SNPs) associated with age at onset of bipolar disorder were selected through single SNP analysis by simple linear regression. Subsequently, the QMDR method was used to find gene-gene interactions.

RESULTS

The best 10 SNPs from simple regression were located in chromosome 1, 2, 3, 10, 11, 14, 19, and 21. Only five SNPs were found in several genes, such as FOXN3, KIAA1217, OPCML, CAMSAP2, and PTPRS. On QMDR analyses, five pairs of SNPs showed significant interactions with a CVC exceeding 1/5 in a two-locus model. The best interaction was found for the pair of rs60830549 and rs12952733 (CVC = 1/5, P < 1E-07). In three-locus models, four combinations of SNPs showed significant associations with age at onset, with a CVC of >1/5. The best three-locus combination was rs60830549, rs12952733, and rs12952733 (CVC = 2/5, P < 1E-6). The SNPs showing significant interactions were located in the KIAA1217, RBFOX3, SDK2, CYP19A1, NTM, SMYD3, and RBFOX1 genes.

CONCLUSIONS

Our analysis confirmed genetic interactions influencing the age of onset for bipolar disorder and identified several potential candidate genes. Further exploration of the functions of these promising genes, which may have multiple roles within the neuronal network, is necessary.

Genetic Associations With an Amyotrophic Lateral Sclerosis Reversal Phenotype

BACKGROUND AND OBJECTIVES

The term "ALS Reversal" describes patients who initially meet diagnostic criteria for amyotrophic lateral sclerosis (ALS) or had clinical features most consistent with progressive muscular atrophy (PMA) but subsequently demonstrated substantial and sustained clinical improvement. The objective of this genome-wide association study (GWAS) was to identify correlates of this unusual clinical phenotype.

METHODS

Participants were recruited from a previously created database of individuals with the ALS Reversal phenotype. Whole-genome sequencing (WGS) data were compared with ethnicity-matched patients with typically progressive ALS enrolled through the CReATe Consortium's Phenotype-Genotype-Biomarker (PGB) study. These results were replicated using an independent ethnically matched WGS data set from Target ALS. Significant results were further explored with available databases of genetic regulatory markers and expression quantitative trait loci (eQTL) analysis.

RESULTS

WGS from 22 participants with documented ALS Reversals was compared with the PGB primary cohort (n = 103) and the Target ALS validation cohort (n = 140). Two genetic loci met predefined criteria for statistical significance (two-sided permutation p ≤ 0.01) and remained plausible after fine-mapping. The lead single nucleotide variant (SNV) from the first locus was rs4242007 (primary cohort GWAS OR = 12.0, 95% CI 4.1 to 34.6), which is in an IGFBP7 intron and is in near-perfect linkage disequilibrium with a SNV in the IGFBP7 promoter region. Both SNVs are associated with decreased frontal cortex IGFBP7 expression in eQTL data sets. Notably, 3 Reversals, but none of the typically progressive individuals (n = 243), were homozygous for rs4242007. The importance of the second locus, located near GRIP1, is uncertain given the absence of an associated effect on nearby gene transcription.

DISCUSSION

We found a significant association between the Reversal phenotype and an IGFBP7 noncoding SNV that is associated with IGFBP7 expression. This is biologically relevant as IGFBP7 is a reported inhibitor of the insulin growth factor-1 (IGF-1) receptor that activates the possibly neuroprotective IGF-1 signaling pathway. This finding is limited by small sample size but suggests that there may be merit in further exploration of IGF-1 pathway signaling as a therapeutic mechanism for ALS.

TRIAL REGISTRATION INFORMATION

This study was registered with ClinicalTrials.gov (NCT03464903) on March 14, 2018. The first participant was enrolled on June 22, 2018.

Genomic analysis of inbreeding and coancestry in Nordic Jersey and Holstein dairy cattle populations

In recent years, genomic selection (GS) has accelerated genetic gain in dairy cattle breeds worldwide. Despite the evident genetic progress, several dairy populations have also encountered challenges such as heightened inbreeding rates and reduced effective population sizes. The challenge has been to find a balance between achieving substantial genetic gain while managing genetic diversity within the population, thereby mitigating the negative effects of inbreeding depression. This study aims to elucidate the impact of GS on pedigree and genomic rates of inbreeding (ΔF) and coancestry (ΔC) in Nordic Jersey (NJ) and Holstein (NH) cattle populations. Furthermore, key genetic metrics, including the generation interval (L), effective population size (Ne), and future effective population size (FNe) were assessed between 2 time periods, before and after GS, and across distinct animal cohorts in both breeds: females, bulls, and approved semen-producing bulls (AI-sires). Analysis of ΔF and ΔC revealed distinct trends across the studied periods and animal groups. Notably, there was a consistent increase in yearly ΔF for most animal groups in both breeds. An exception was observed in NH AI-sires, which demonstrated a slight decrease in yearly ΔF. Moreover, NJ displayed minimal changes in yearly ΔC between the periods, whereas NH exhibited elevated ΔC values across all animal groups. Particularly striking was the substantial increase in yearly ΔC within the NH female population, surging from 0.02% to 0.39% between the periods. Implementation of GS resulted in a reduction of the generation interval across all animal cohorts in both NJ and NH breeds. However, the extent of reduction was more pronounced in males compared with females. This reduction in generation interval influenced generational changes in ΔF and ΔC. Bulls and AI-sires of both breeds exhibited reduced generational ΔF between periods, in contrast to females that demonstrated an opposing pattern. Between the periods, NJ maintained a relatively stable Ne (29.4 before and 30.3 after GS), whereas NH experienced a notable decline from 54.3 to 42.8. Female groups in both breeds displayed a negative Ne trend, whereas males demonstrated either neutral or positive Ne developments. Regarding FNe, NJ exhibited positive FNe development with an increase from 40.7 to 57.2. The opposite was observed in NH, where FNe decreased from 198.8 to 42.7. In summary, it was evident that the genomic methods could detect differences between the populations and changes in ΔF and ΔC more efficiently than pedigree methods. Implementation of GS yielded positive outcomes within the NJ population regarding the rate of coancestry but the opposite was observed with NH. Moreover, analysis of ΔC data hints at the potential to decrease future ΔF through informed mating strategies. Conversely, NH faces more pressing concerns, even though ΔF remains comparatively modest in contrast to what has been observed in other Holstein populations. These findings underscore the necessity of genomic control of inbreeding and coancestry with strategic changes in the Nordic breeding schemes for dairy to ensure long-term sustainability in the forthcoming years.

Genome-wide association study of hospitalized patients and acute kidney injury

Acute kidney injury (AKI) is a common and devastating complication of hospitalization. Here, we identified genetic loci associated with AKI in patients hospitalized between 2002-2019 in the Million Veteran Program and data from Vanderbilt University Medical Center's BioVU. AKI was defined as meeting a modified KDIGO Stage 1 or more for two or more consecutive days or kidney replacement therapy. Control individuals were required to have one or more qualifying hospitalizations without AKI and no evidence of AKI during any other observed hospitalizations. Genome-wide association studies (GWAS), stratified by race, adjusting for sex, age, baseline estimated glomerular filtration rate (eGFR), and the top ten principal components of ancestry were conducted. Results were meta-analyzed using fixed effects models. In total, there were 54,488 patients with AKI and 138,051 non-AKI individuals included in the study. Two novel loci reached genome-wide significance in the meta-analysis: rs11642015 near the FTO locus on chromosome 16 (obesity traits) (odds ratio 1.07 (95% confidence interval, 1.05-1.09)) and rs4859682 near the SHROOM3 locus on chromosome 4 (glomerular filtration barrier integrity) (odds ratio 0.95 (95% confidence interval, 0.93-0.96)). These loci colocalized with previous studies of kidney function, and genetic correlation indicated significant shared genetic architecture between AKI and eGFR. Notably, the association at the FTO locus was attenuated after adjustment for BMI and diabetes, suggesting that this association may be partially driven by obesity. Both FTO and the SHROOM3 loci showed nominal evidence of replication from diagnostic-code-based summary statistics from UK Biobank, FinnGen, and Biobank Japan. Thus, our large GWA meta-analysis found two loci significantly associated with AKI suggesting genetics may explain some risk for AKI.

Repeated plague infections across six generations of Neolithic Farmers

In the period between 5,300 and 4,900 calibrated years before present (cal. BP), populations across large parts of Europe underwent a period of demographic decline1,2. However, the cause of this so-called Neolithic decline is still debated. Some argue for an agricultural crisis resulting in the decline3, others for the spread of an early form of plague4. Here we use population-scale ancient genomics to infer ancestry, social structure and pathogen infection in 108 Scandinavian Neolithic individuals from eight megalithic graves and a stone cist. We find that the Neolithic plague was widespread, detected in at least 17% of the sampled population and across large geographical distances. We demonstrate that the disease spread within the Neolithic community in three distinct infection events within a period of around 120 years. Variant graph-based pan-genomics shows that the Neolithic plague genomes retained ancestral genomic variation present in Yersinia pseudotuberculosis, including virulence factors associated with disease outcomes. In addition, we reconstruct four multigeneration pedigrees, the largest of which consists of 38 individuals spanning six generations, showing a patrilineal social organization. Lastly, we document direct genomic evidence for Neolithic female exogamy in a woman buried in a different megalithic tomb than her brothers. Taken together, our findings provide a detailed reconstruction of plague spread within a large patrilineal kinship group and identify multiple plague infections in a population dated to the beginning of the Neolithic decline.

Diving into broad-scale and high-resolution population genomics to decipher drivers of structure and climatic vulnerability in a marine invertebrate

Species with widespread distributions play a crucial role in our understanding of climate change impacts on population structure. In marine species, population structure is often governed by both high connectivity potential and selection across strong environmental gradients. Despite the complexity of factors influencing marine populations, studying species with broad distribution can provide valuable insights into the relative importance of these factors and the consequences of climate-induced alterations across environmental gradients. We used the northern shrimp Pandalus borealis and its wide latitudinal distribution to identify current drivers of population structure and predict the species' vulnerability to climate change. A total of 1514 individuals sampled across 24° latitude were genotyped at high geographic (54 stations) and genetic (14,331 SNPs) resolutions to assess genetic variation and environmental correlations. Four populations were identified in addition to finer substructure associated with local adaptation. Geographic patterns of neutral population structure reflected predominant oceanographic currents, while a significant proportion of the genetic variation was associated with gradients in salinity and temperature. Adaptive landscapes generated using climate projections suggest a larger genomic offset in the southern extent of the P. borealis range, where shrimp had the largest adaptive standing genetic variation. Our genomic results combined with recent observations point to further deterioration in southern regions and an impending vulnerable status in the regions at higher latitudes for P. borealis. They also provide rare insights into the drivers of population structure and climatic vulnerability of a widespread meroplanktonic species, which is crucial to understanding future challenges associated with invertebrates essential to ecosystem functioning.

The biogeographic and evolutionary processes shaping population divergence in Laupala

Speciation generates biodiversity and the mechanisms involved are thought to vary across the tree of life and across environments. For example, well-studied adaptive radiations are thought to be fuelled by divergent ecological selection, but additionally are influenced heavily by biogeographic, genomic and demographic factors. Mechanisms of non-adaptive radiations, producing ecologically cryptic taxa, have been less well-studied but should likewise be influenced by these latter factors. Comparing among contexts can help pinpoint universal mechanisms and outcomes, especially if we integrate biogeographic, ecological and evolutionary processes. We investigate population divergence in the swordtail cricket Laupala cerasina, a wide-spread endemic on Hawai'i Island and one of 38 ecologically cryptic Laupala species. The nine sampled populations show striking population genetic structure at small spatio-temporal scales. The rapid differentiation among populations and species of Laupala shows that neither a specific geographical context nor ecological opportunity are pre-requisites for rapid divergence. Spatio-temporal patterns in population divergence, population size change, and gene flow are aligned with the chronosequence of the four volcanoes on which L. cerasina occurs and reveal the composite effects of geological dynamics and Quaternary climate change on population dynamics. Spatio-temporal patterns in genetic variation along the genome reveal the interplay of genetic and genomic architecture in shaping population divergence. In early phases of divergence, we find elevated differentiation in genomic regions harbouring mating song loci. In later stages of divergence, we find a signature of linked selection that interacts with recombination rate variation. Comparing our findings with recent work on complementary systems supports the conclusion that mostly universal factors influence the speciation process.

Why we thrive beneath a northern sky - genomic signals of selection in apple for adaptation to northern Sweden

Good understanding of the genomic regions underlying adaptation of apple to boreal climates is needed to facilitate efficient breeding of locally adapted apple cultivars. Proper infrastructure for phenotyping and evaluation is essential for identification of traits responsible for adaptation, and dissection of their genetic composition. However, such infrastructure is costly and currently not available for the boreal zone of northern Sweden. Therefore, we used historical pomological data on climate adaptation of 59 apple cultivars and whole genome sequencing to identify genomic regions that have undergone historical selection among apple cultivars recommended for cultivation in northern Sweden. We found the apple collection to be composed of two ancestral groups that are largely concordant with the grouping into 'hardy' and 'not hardy' cultivars based on the pomological literature. Using a number of genome-wide scans for signals of selection, we obtained strong evidence of positive selection at a genomic region around 29 MbHFTH1 of chromosome 1 among apple cultivars in the 'hardy' group. Using phased genotypic data from the 20 K apple Infinium® SNP array, we identified haplotypes associated with the two cultivar groups and traced transmission of these haplotypes through the pedigrees of some apple cultivars. This demonstrates that historical data from pomological literature can be analyzed by population genomic approaches as a step towards revealing the genomic control of a key property for a horticultural niche market. Such knowledge is needed to facilitate efficient breeding strategies for development of locally adapted apple cultivars in the future. The current study illustrates the response to a very strong selective pressure imposed on tree crops by climatic factors, and the importance of genetic research on this topic and feasibility of breeding efforts in the light of the ongoing climate change.

Exploring the relationship between admixture and genetic susceptibility to attention deficit hyperactivity disorder in two Latin American cohorts

Contemporary research on the genomics of Attention Deficit Hyperactivity Disorder (ADHD) often underrepresents admixed populations of diverse genomic ancestries, such as Latin Americans. This study explores the relationship between admixture and genetic associations for ADHD in Colombian and Mexican cohorts. Some 546 participants in two groups, ADHD and Control, were genotyped with Infinium PsychArray®. Global ancestry levels were estimated using overall admixture proportions and principal component analysis, while local ancestry was determined using a method to estimate ancestral components along the genome. Genome-wide association analysis (GWAS) was conducted to identify significant associations. Differences between Colombia and Mexico were evaluated using appropriate statistical tests. 354 Single-nucleotide polymorphisms (SNPs) and Single-nucleotide variants (SNVs) related to some genes and intergenic regions exhibited suggestive significance (p-value < 5*10e-5) in the GWAS. None of the variants revealed genome-wide significance (p-value < 5*10e-8). The study identified a significant relationship between risk SNPs and the European component of admixture, notably observed in the LOC105379109 gene. Despite differences in risk association loci, such as FOXP2, our findings suggest a possible homogeneity in genetic variation's impact on ADHD between Colombian and Mexican populations. Current reference datasets for ADHD predominantly consist of samples with high European ancestry, underscoring the need for further research to enhance the representation of reference populations and improve the identification of ADHD risk traits in Latin Americans.

Ecological genetics of isolated loach populations indicate compromised adaptive potential

Many endangered species live in fragmented and isolated populations with low genetic variability, signs of inbreeding, and small effective population sizes - all features elevating their extinction risk. The flat-headed loach (Oreonectes platycephalus), a small noemacheilid fish, is widely across southern China, but only in the headwaters of hillstreams; as a result, they are spatially isolated from conspecific populations. We surveyed single nucleotide polymorphisms in 16 Hong Kong populations of O. platycephalus to determine whether loach populations from different streams were genetically isolated from each other, showed low levels of genetic diversity, signs of inbreeding, and had small contemporary effective population sizes. Estimates of average observed heterozygosity (HO = 0.0473), average weighted nucleotide diversity (πw = 0.0546) and contemporary effective population sizes (Ne = 10.2 ~ 129.8) were very low, and several populations showed clear signs of inbreeding as judged from relatedness estimates. The degree of genetic differentiation among populations was very high (average FST = 0.668), even over short geographic distances (<1.5 km), with clear patterns of isolation by distance. These results suggest that Hong Kong populations of O. platycephalus have experienced strong genetic drift and loss of genetic variability because sea-level rise after the last glaciation reduced connectedness among paleodrainages, isolating populations in headwaters. All this, together with the fact that the levels of genetic diversity and contemporary effective population sizes within O. platycephalus populations are lower than most other freshwater fishes, suggests that they face high local extinction risk and have limited capacity for future adaptation.

Genome-wide discovery for biomarkers using quantile regression at biobank scale

Genome-wide association studies (GWAS) for biomarkers important for clinical phenotypes can lead to clinically relevant discoveries. Conventional GWAS for quantitative traits are based on simplified regression models modeling the conditional mean of a phenotype as a linear function of genotype. We draw attention here to an alternative, lesser known approach, namely quantile regression that naturally extends linear regression to the analysis of the entire conditional distribution of a phenotype of interest. Quantile regression can be applied efficiently at biobank scale, while having some unique advantages such as (1) identifying variants with heterogeneous effects across quantiles of the phenotype distribution; (2) accommodating a wide range of phenotype distributions including non-normal distributions, with invariance of results to trait transformations; and (3) providing more detailed information about genotype-phenotype associations even for those associations identified by conventional GWAS. We show in simulations that quantile regression is powerful across both homogeneous and various heterogeneous models. Applications to 39 quantitative traits in the UK Biobank demonstrate that quantile regression can be a helpful complement to linear regression in GWAS and can identify variants with larger effects on high-risk subgroups of individuals but with lower or no contribution overall.

Genomic Analysis Identifies Risk Factors in Restless Legs Syndrome

OBJECTIVE

Restless legs syndrome (RLS) is a neurological condition that causes uncomfortable sensations in the legs and an irresistible urge to move them, typically during periods of rest. The genetic basis and pathophysiology of RLS are incompletely understood. We sought to identify additional novel genetic risk factors associated with RLS susceptibility.

METHODS

We performed a whole-genome sequencing and genome-wide association meta-analysis of RLS cases (n = 9,851) and controls (n = 38,957) in 3 population-based biobanks (All of Us, Canadian Longitudinal Study on Aging, and CARTaGENE).

RESULTS

Genome-wide association analysis identified 9 independent risk loci, of which 8 had been previously reported, and 1 was a novel risk locus (LMX1B, rs35196838, OR 1.14, 95% CI 1.09-1.19, p value = 2.2 × 10-9). Furthermore, a transcriptome-wide association study also identified GLO1 and a previously unreported gene, ELFN1. A genetic correlation analysis revealed significant common variant overlaps between RLS and neuroticism (rg = 0.40, se = 0.08, p value = 5.4 × 10-7), depression (rg = 0.35, se = 0.06, p value = 2.17 × 10-8), and intelligence (rg = -0.20, se = 0.06, p value = 4.0 × 10-4).

INTERPRETATION

Our study expands the understanding of the genetic architecture of RLS, and highlights the contributions of common variants to this prevalent neurological disorder. ANN NEUROL 2024.

Modelling the demographic history of human North African genomes points to a recent soft split divergence between populations

BACKGROUND

North African human populations present a complex demographic scenario due to the presence of an autochthonous genetic component and population substructure, plus extensive gene flow from the Middle East, Europe, and sub-Saharan Africa.

RESULTS

We conducted a comprehensive analysis of 364 genomes to construct detailed demographic models for the North African region, encompassing its two primary ethnic groups, the Arab and Amazigh populations. This was achieved through an Approximate Bayesian Computation with Deep Learning (ABC-DL) framework and a novel algorithm called Genetic Programming for Population Genetics (GP4PG). This innovative approach enabled us to effectively model intricate demographic scenarios, utilizing a subset of 16 whole genomes at > 30X coverage. The demographic model suggested by GP4PG exhibited a closer alignment with the observed data compared to the ABC-DL model. Both point to a back-to-Africa origin of North African individuals and a close relationship with Eurasian populations. Results support different origins for Amazigh and Arab populations, with Amazigh populations originating back in Epipaleolithic times, while GP4PG supports Arabization as the main source of Middle Eastern ancestry. The GP4PG model includes population substructure in surrounding populations (sub-Saharan Africa and Middle East) with continuous decaying gene flow after population split. Contrary to ABC-DL, the best GP4PG model does not require pulses of admixture from surrounding populations into North Africa pointing to soft splits as drivers of divergence in North Africa.

CONCLUSIONS

We have built a demographic model on North Africa that points to a back-to-Africa expansion and a differential origin between Arab and Amazigh populations.

Polygenic risk scores as a marker for epilepsy risk across lifetime and after unspecified seizure events

A diagnosis of epilepsy has significant consequences for an individual but is often challenging in clinical practice. Novel biomarkers are thus greatly needed. Here, we investigated how common genetic factors (epilepsy polygenic risk scores, [PRSs]) influence epilepsy risk in detailed longitudinal electronic health records (EHRs) of > 700k Finns and Estonians. We found that a high genetic generalized epilepsy PRS (PRSGGE) increased risk for genetic generalized epilepsy (GGE) (hazard ratio [HR] 1.73 per PRSGGE standard deviation [SD]) across lifetime and within 10 years after an unspecified seizure event. The effect of PRSGGE was significantly larger on idiopathic generalized epilepsies, in females and for earlier epilepsy onset. Analogously, we found significant but more modest focal epilepsy PRS burden associated with non-acquired focal epilepsy (NAFE). Here, we outline the potential of epilepsy specific PRSs to serve as biomarkers after a first seizure event.

Runs of homozygosity reveal contrasting histories of inbreeding across global lineages of the edible porcini mushroom, Boletus edulis

Inbreeding, the mating of individuals that are related through common ancestry, is of central importance in evolutionary and conservation biology due to its impacts on individual fitness and population dynamics. However, while advanced genomic approaches have revolutionised the study of inbreeding in animals, genomic studies of inbreeding are rare in plants and lacking in fungi. We investigated global patterns of inbreeding in the prized edible porcini mushroom Boletus edulis using 225 whole genomes from seven lineages distributed across the northern hemisphere. Genomic inbreeding was quantified using runs of homozygosity (ROHs). We found appreciable variation both among and within lineages, with some individuals having over 20% of their genomes in ROHs. Much of this variation could be explained by a combination of elevation and latitude, and to a lesser extent by predicted habitat suitability during the last glacial maximum. In line with this, the majority of ROHs were short, reflecting ancient common ancestry dating back approximately 200-1700 generations ago, while longer ROHs indicative of recent common ancestry (less than approximately 50 generations ago) were infrequent. Our study reveals the inbreeding legacy of major climatic events in a widely distributed forest mutualist, aligning with prevailing theories and empirical studies of the impacts of historical glaciation events on the dominant forest tree species of the northern hemisphere.

Genomic Reference Resource for African Cattle: Genome Sequences and High-Density Array Variants

The diversity in genome resources is fundamental to designing genomic strategies for local breed improvement and utilisation. These resources also support gene discovery and enhance our understanding of the mechanisms of resilience with applications beyond local breeds. Here, we report the genome sequences of 555 cattle (208 of which comprise new data) and high-density (HD) array genotyping of 1,082 samples (537 new samples) from indigenous African cattle populations. The new sequences have an average genome coverage of ~30X, three times higher than the average (~10X) of the over 300 sequences already in the public domain. Following variant quality checks, we identified approximately 32.3 million sequence variants and 661,943 HD autosomal variants mapped to the Bos taurus reference genome (ARS-UCD1.2). The new datasets were generated as part of the Centre for Tropical Livestock Genetics and Health (CTLGH) Genomic Reference Resource for African Cattle (GRRFAC) initiative, which aspires to facilitate the generation of this livestock resource and hopes for its utilisation for complete indigenous breed characterisation and sustainable global livestock improvement.

Association study of GBA1 variants with MSA based on comprehensive sequence analysis -Pitfalls in short-read sequence analysis depending on the human reference genome

Multiple system atrophy (MSA) is a neurodegenerative disorder characterized by various combinations of autonomic failure, parkinsonism, and cerebellar ataxia. To elucidate variants associated with MSA, we have been conducting short-read-based whole-genome sequence analysis. In the process of the association studies, we initially focused on GBA1, a previously proposed susceptibility gene for MSA, to evaluate whether GBA1 variants can be efficiently identified despite its extraordinarily high homology with its pseudogene, GBA1LP. To accomplish this, we conducted a short-read whole-genome sequence analysis with alignment to GRCh38 as well as Sanger sequence analysis and compared the results. We identified five variants with inconsistencies between the two pipelines, of which three variants (p.L483P, p.A495P-p.V499V, p.L483_M489delinsW) were the results of misalignment due to minor alleles in GBA1P1 registered in GRCh38. The miscalling events in these variants were resolved by alignment to GRCh37 as the reference genome, where the major alleles are registered. In addition, a structural variant was not properly identified either by short-read or by Sanger sequence analyses. Having accomplished correct variant calling, we identified three variants pathogenic for Gaucher disease (p.S310G, p.L483P, and p.L483_M489delinsW). Of these variants, the allele frequency of p.L483P (0.003) in the MSA cases was higher than that (0.0011) in controls. The meta-analysis incorporating a previous report demonstrated a significant association of p.L483P with MSA with an odds ratio of 2.92 (95% CI; 1.08 - 7.90, p = 0.0353).

Parental education and children's depression, anxiety, and ADHD traits, a within-family study in MoBa

Children born to parents with fewer years of education are more likely to have depression, anxiety, and attention-deficit hyperactivity disorder (ADHD), but it is unclear to what extent these associations are causal. We estimated the effect of parents' educational attainment on children's depressive, anxiety, and ADHD traits at age 8 years, in a sample of 40,879 Norwegian children born in 1998-2009 and their parents. We used within-family Mendelian randomization, which employs genetic variants as instrumental variables, and controlled for direct genetic effects by adjusting for children's polygenic indexes. We found little evidence that mothers' or fathers' educational attainment independently affected children's depressive, anxiety, or ADHD traits. However, children's own polygenic scores for educational attainment were independently and negatively associated with these traits. Results suggest that differences in these traits according to parents' education may reflect direct genetic effects more than genetic nurture. Consequences of social disadvantage for children's mental health may however be more visible in samples with more socioeconomic variation, or contexts with larger socioeconomic disparities than present-day Norway. Further research is required in populations with more educational and economic inequality and in other age groups.

Distinct positions of genetic and oral histories: Perspectives from India

Over the past decade, genomic data have contributed to several insights on global human population histories. These studies have been met both with interest and critically, particularly by populations with oral histories that are records of their past and often reference their origins. While several studies have reported concordance between oral and genetic histories, there is potential for tension that may stem from genetic histories being prioritized or used to confirm community-based knowledge and ethnography, especially if they differ. To investigate the interplay between oral and genetic histories, we focused on the southwestern region of India and analyzed whole-genome sequence data from 156 individuals identifying as Bunt, Kodava, Nair, and Kapla. We supplemented limited anthropological records on these populations with oral history accounts from community members and historical literature, focusing on references to non-local origins such as the ancient Scythians in the case of Bunt, Kodava, and Nair, members of Alexander the Great's army for the Kodava, and an African-related source for Kapla. We found these populations to be genetically most similar to other Indian populations, with the Kapla more similar to South Indian tribal populations that maximize a genetic ancestry related to Ancient Ancestral South Indians. We did not find evidence of additional genetic sources in the study populations than those known to have contributed to many other present-day South Asian populations. Our results demonstrate that oral and genetic histories may not always provide consistent accounts of population origins and motivate further community-engaged, multi-disciplinary investigations of non-local origin stories in these communities.

Common and rare genetic variants predisposing females to unexplained recurrent pregnancy loss

Recurrent pregnancy loss (RPL) is a major reproductive health issue with multifactorial causes, affecting 2.6% of all pregnancies worldwide. Nearly half of the RPL cases lack clinically identifiable causes (e.g., antiphospholipid syndrome, uterine anomalies, and parental chromosomal abnormalities), referred to as unexplained RPL (uRPL). Here, we perform a genome-wide association study focusing on uRPL in 1,728 cases and 24,315 female controls of Japanese ancestry. We detect significant associations in the major histocompatibility complex (MHC) region at 6p21 (lead variant=rs9263738; P = 1.4 × 10-10; odds ratio [OR] = 1.51 [95% CI: 1.33-1.72]; risk allele frequency = 0.871). The MHC associations are fine-mapped to the classical HLA alleles, HLA-C*12:02, HLA-B*52:01, and HLA-DRB1*15:02 (P = 1.1 × 10-10, 1.5 × 10-10, and 1.2 × 10-9, respectively), which constitute a population-specific common long-range haplotype with a protective effect (P = 2.8 × 10-10; OR = 0.65 [95% CI: 0.57-0.75]; haplotype frequency=0.108). Genome-wide copy-number variation (CNV) calling demonstrates rare predicted loss-of-function (pLoF) variants of the cadherin-11 gene (CDH11) conferring the risk of uRPL (P = 1.3 × 10-4; OR = 3.29 [95% CI: 1.78-5.76]). Our study highlights the importance of reproductive immunology and rare variants in the uRPL etiology.

Independent inheritance of cognition and bipolar disorder in a family sample

Cognitive deficits in people with bipolar disorder (BD) may be the result of the illness or its treatment, but they could also reflect genetic risk factors shared between BD and cognition. We investigated this question using empirical genetic relationships within a sample of patients with BD and their unaffected relatives. Participants with bipolar I, II, or schizoaffective disorder ("narrow" BD, n = 69), related mood disorders ("broad" BD, n = 135), and their clinically unaffected relatives (n = 227) completed five cognitive tests. General cognitive function (g) was quantified via principal components analysis (PCA). Heritability and genetic correlations were estimated with SOLAR-Eclipse. Participants with "narrow" or "broad" diagnoses showed deficits in g, although affect recognition was unimpaired. Cognitive performance was significantly heritable (h2 = 0.322 for g, p < 0.005). Coheritability between psychopathology and g was small (0.0184 for narrow and 0.0327 for broad) and healthy relatives of those with BD were cognitively unimpaired. In this family sample, cognitive deficits were present in participants with BD but were not explained by substantial overlaps in genetic determinants of mood and cognition. These findings support the view that cognitive deficits in BD are largely the result of the illness or its treatment.

The Time-Varying Impact of COVID-19 on the Acute Kidney Disorders: A Historical Matched Cohort Study and Mendelian Randomization Analysis

Background: This study aimed to explore the time-varying impact of COVID-19 on acute kidney disorders, including acute kidney injury and other acute kidney diseases. Methods: From the UK Biobank, 10,121 participants with COVID-19 were matched with up to 3 historically unexposed controls by age, sex, Townsend deprivation index, and the status of hospitalization or receiving critical care. We investigated the association between COVID-19 and incidence of acute kidney disorders, within the first 4 weeks after infection, using conditional and time-varying Cox proportional hazard regression. In addition, one-sample Mendelian randomization, utilizing the polygenic risk score for COVID-19 as an instrumental variable, was conducted to explore the potential causality of the association. Results: In the matched cohort study, we observed a significant association between COVID-19 and acute kidney disorders predominantly within the first 3 weeks. The impact of COVID-19 was time dependent, peaking in the second week (hazard ratio, 12.77; 95% confidence interval, 5.93 to 27.70) and decreasing by the fourth week (hazard ratio, 2.28; 95% confidence interval, 0.75 to 6.93). In subgroup analyses, only moderate to severe COVID-19 cases were associated with acute worsening of renal function in a time-dependent pattern. One-sample Mendelian randomization analyses further showed that COVID-19 might exert a "short-term" causal effect on the risk of acute kidney disorders, primarily confined to the first week after infection. Conclusions: The risk of acute kidney disorders following COVID-19 demonstrates a time-varying pattern. Hazard effects were observed only in patients with moderate or severe but not mild COVID-19.

Small-group originating model: Optimized individual-level GWAS simulation featured by SLiM and using open-access data

The development of analytical methods for Genome-wide Association Studies (GWAS) has outpaced the evolution of simulation techniques and pipelines. This disparity underscores the importance of innovative simulation methods that can keep pace with the rapidly increasing scale of GWAS. The median sample size of GWAS over the past ten years has exceeded 50,000 individuals, a trend that emphasizes the need for simulation tools capable of generating data on a similar or larger scale. This paper introduces a novel method, the small-group originating (SGO) model, utilizing the SLiM software for simulating individual-level GWAS data. Our standardized protocol facilitates the generation of tens of thousands of pseudo-individuals with millions of variants from small (30-90) open-access datasets. SGO stands out, especially when compared to the widely-used resampling method in HapGen, showcasing superior simulation efficiency for large sample sizes (> 13,000) of unrelated individuals. This capability is particularly relevant given the current trajectory towards larger GWAS, necessitating tools that can simulate datasets reflective of this growth. Additionally, SGO provides customization options and can model dynamic life cycles and mating across generations, positioning it as a highly promising alternative for GWAS simulations. In a case study, sensitivity analyses of chromosome-level principal component analysis and kinship coefficient estimation were conducted. The results highlighted the poor robustness of chromosome-level quality control (QC) indexes and the uneven distribution of population structure across chromosomes and ancestries, advocating for the caution against relying solely on chromosome-level QC statistics. With its flexible and efficient approach to generating pseudo GWAS data, our standardized SGO protocol emerges as a crucial asset for method development, power analysis, and benchmarking in GWAS research. It is especially vital in the context of accommodating the demands for large-scale simulations, aligning with the current and future scale of GWAS.

Rare de novo damaging DNA variants are enriched in attention-deficit/hyperactivity disorder and implicate risk genes

Research demonstrates the important role of genetic factors in attention-deficit/hyperactivity disorder (ADHD). DNA sequencing of families provides a powerful approach for identifying de novo (spontaneous) variants, leading to the discovery of hundreds of clinically informative risk genes for other childhood neurodevelopmental disorders. This approach has yet to be extensively leveraged in ADHD. We conduct whole-exome DNA sequencing in 152 families, comprising a child with ADHD and both biological parents, and demonstrate a significant enrichment of rare and ultra-rare de novo gene-damaging mutations in ADHD cases compared to unaffected controls. Combining these results with a large independent case-control DNA sequencing cohort (3206 ADHD cases and 5002 controls), we identify lysine demethylase 5B (KDM5B) as a high-confidence risk gene for ADHD and estimate that 1057 genes contribute to ADHD risk. Using our list of genes harboring ultra-rare de novo damaging variants, we show that these genes overlap with previously reported risk genes for other neuropsychiatric conditions and are enriched in several canonical biological pathways, suggesting early neurodevelopmental underpinnings of ADHD. This work provides insight into the biology of ADHD and demonstrates the discovery potential of DNA sequencing in larger parent-child trio cohorts.

Identification and correction for collider bias in a genome-wide association study of diabetes-related heart failure

Type 2 diabetes (T2D) is a major risk factor for heart failure (HF) and has elevated incidence among individuals with HF. Since genetics and HF can independently influence T2D, collider bias may occur when T2D (i.e., collider) is controlled for by design or analysis. Thus, we conducted a genome-wide association study (GWAS) of diabetes-related HF with correction for collider bias. We first performed a GWAS of HF to identify genetic instrumental variables (GIVs) for HF and to enable bidirectional Mendelian randomization (MR) analysis between T2D and HF. We identified 61 genomic loci, significantly associated with all-cause HF in 114,275 individuals with HF and over 1.5 million controls of European ancestry. Using a two-sample bidirectional MR approach with 59 and 82 GIVs for HF and T2D, respectively, we estimated that T2D increased HF risk (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.04-1.10), while HF also increased T2D risk (OR 1.60, 95% CI 1.36-1.88). Then we performed a GWAS of diabetes-related HF corrected for collider bias due to the study design of index cases. After removing the spurious association of TCF7L2 locus due to collider bias, we identified two genome-wide significant loci close to PITX2 (chromosome 4) and CDKN2B-AS1 (chromosome 9) associated with diabetes-related HF in the Million Veteran Program and replicated the associations in the UK Biobank. Our MR findings provide strong evidence that HF increases T2D risk. As a result, collider bias leads to spurious genetic associations of diabetes-related HF, which can be effectively corrected to identify true positive loci.

eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis

Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.

Identification of shared genetic risks underlying metabolic syndrome and its related traits in the Korean population

Introduction: Observational studies have demonstrated strong correlations between metabolic syndrome (MetS) and its related traits. To gain insight into the genetic architecture and molecular mechanism of MetS, we investigated the shared genetic basis of MetS and its related traits and further tested their causal relationships. Methods: Using summary statistics from genome-wide association analyses of about 72,000 subjects from the Korean Genome and Epidemiological Study (KoGES), we conducted genome-wide multi-trait analyses to quantify the overall genetic correlation and Mendelian randomization analyses to infer the causal relationships between traits of interest. Results: Genetic correlation analyses revealed a significant correlation of MetS with its related traits, such as obesity traits (body mass index and waist circumference), lipid traits (triglyceride and high-density lipoprotein cholesterol), glycemic traits (fasting plasma glucose and hemoglobin A1C), and blood pressure (systolic and diastolic). Mendelian randomization analyses further demonstrated that the MetS-related traits showing significant overall genetic correlation with MetS could be genetically determined risk factors for MetS. Discussion: Our study suggests a shared genetic basis of MetS and its related traits and provides novel insights into the biological mechanisms underlying these complex traits. Our findings further inform public health interventions by supporting the important role of the management of metabolic risk factors such as obesity, unhealthy lipid profiles, diabetes, and high blood pressure in the prevention of MetS.

Conservation genomics of the wild pumpkin Cucurbita radicans in Central Mexico: The influence of a changing environment on the genetic diversity and differentiation of a rare species

The genetic diversity found in natural populations is the result of the evolutionary forces in response to historical and contemporary factors. The environmental characteristics and geological history of Mexico promoted the evolution and diversification of plant species, including wild relatives of crops such as the wild pumpkins (Cucurbita). Wild pumpkin species are found in a variety of habitats, evidencing their capability to adapt to different environments. Despite the potential value of wild Cucurbita as a genetic reservoir for crops, there is a lack of studies on their genetic diversity. Cucurbita radicans is an endangered species threatened by habitat destruction leading to low densities in small and isolated populations. Here, we analyze Genotype by Sequencing genomic data of the wild pumpkin C. radicans to evaluate the influence of factors like isolation, demographic history, and the environment shaping the amount and distribution of its genetic variation. We analyzed 91 individuals from 14 localities along its reported distribution. We obtained 5,107 SNPs and found medium-high levels of genetic diversity and genetic structure distributed in four main geographic areas with different environmental conditions. Moreover, we found signals of demographic growth related to historical climatic shifts. Outlier loci analysis showed significant association with the environment, principally with precipitation variables. Also, the outlier loci displayed differential changes in their frequencies in response to future global climate change scenarios. Using the results of genetic structure, outlier loci and multivariate analyses of the environmental conditions, we propose priority localities for conservation that encompass most of the genetic diversity of C. radicans.

GRPa-PRS: A risk stratification method to identify genetically-regulated pathways in polygenic diseases

Background

Polygenic risk scores (PRS) are tools used to evaluate an individual's susceptibility to polygenic diseases based on their genetic profile. A considerable proportion of people carry a high genetic risk but evade the disease. On the other hand, some individuals with a low risk of eventually developing the disease. We hypothesized that unknown counterfactors might be involved in reversing the PRS prediction, which might provide new insights into the pathogenesis, prevention, and early intervention of diseases.

Methods

We built a novel computational framework to identify genetically-regulated pathways (GRPas) using PRS-based stratification for each cohort. We curated two AD cohorts with genotyping data; the discovery (disc) and the replication (rep) datasets include 2722 and 2854 individuals, respectively. First, we calculated the optimized PRS model based on the three recent AD GWAS summary statistics for each cohort. Then, we stratified the individuals by their PRS and clinical diagnosis into six biologically meaningful PRS strata, such as AD cases with low/high risk and cognitively normal (CN) with low/high risk. Lastly, we imputed individual genetically-regulated expression (GReX) and identified differential GReX and GRPas between risk strata using gene-set enrichment and variational analyses in two models, with and without APOE effects. An orthogonality test was further conducted to verify those GRPas are independent of PRS risk. To verify the generalizability of other polygenic diseases, we further applied a default model of GRPa-PRS for schizophrenia (SCZ).

Results

For each stratum, we conducted the same procedures in both the disc and rep datasets for comparison. In AD, we identified several well-known AD-related pathways, including amyloid-beta clearance, tau protein binding, and astrocyte response to oxidative stress. Additionally, we discovered resilience-related GRPs that are orthogonal to AD PRS, such as the calcium signaling pathway and divalent inorganic cation homeostasis. In SCZ, pathways related to mitochondrial function and muscle development were highlighted. Finally, our GRPa-PRS method identified more consistent differential pathways compared to another variant-based pathway PRS method.

Conclusions

We developed a framework, GRPa-PRS, to systematically explore the differential GReX and GRPas among individuals stratified by their estimated PRS. The GReX-level comparison among those strata unveiled new insights into the pathways associated with disease risk and resilience. Our framework is extendable to other polygenic complex diseases.

Genetic Architecture and Clinical Outcomes of Combined Lipid Disturbances

BACKGROUND

Dyslipoproteinemia often involves simultaneous derangements of multiple lipid traits. We aimed to evaluate the phenotypic and genetic characteristics of combined lipid disturbances in a general population-based cohort.

METHODS

Among UK Biobank participants without prevalent coronary artery disease, we used blood lipid and apolipoprotein B concentrations to ascribe individuals into 1 of 6 reproducible and mutually exclusive dyslipoproteinemia subtypes. Incident coronary artery disease risk was estimated for each subtype using Cox proportional hazards models. Phenome-wide analyses and genome-wide association studies were performed for each subtype, followed by in silico causal gene prioritization and heritability analyses. Additionally, the prevalence of disruptive variants in causal genes for Mendelian lipid disorders was assessed using whole-exome sequence data.

RESULTS

Among 450 636 UK Biobank participants: 63 (0.01%) had chylomicronemia; 40 005 (8.9%) had hypercholesterolemia; 94 785 (21.0%) had combined hyperlipidemia; 13 998 (3.1%) had remnant hypercholesterolemia; 110 389 (24.5%) had hypertriglyceridemia; and 49 (0.01%) had mixed hypertriglyceridemia and hypercholesterolemia. Over a median (interquartile range) follow-up of 11.1 (10.4-11.8) years, incident coronary artery disease risk varied across subtypes, with combined hyperlipidemia exhibiting the largest hazard (hazard ratio, 1.92 [95% CI, 1.84-2.01]; P=2×10-16), even when accounting for non-HDL-C (hazard ratio, 1.45 [95% CI, 1.30-1.60]; P=2.6×10-12). Genome-wide association studies revealed 250 loci significantly associated with dyslipoproteinemia subtypes, of which 72 (28.8%) were not detected in prior single lipid trait genome-wide association studies. Mendelian lipid variant carriers were rare (2.0%) among individuals with dyslipoproteinemia, but polygenic heritability was high, ranging from 23% for remnant hypercholesterolemia to 54% for combined hyperlipidemia.

CONCLUSIONS

Simultaneous assessment of multiple lipid derangements revealed nuanced differences in coronary artery disease risk and genetic architectures across dyslipoproteinemia subtypes. These findings highlight the importance of looking beyond single lipid traits to better understand combined lipid and lipoprotein phenotypes and implications for disease risk.

Drivers of genomic diversity and phenotypic development in early phases of domestication in Hermetia illucens

The black soldier fly (BSF), Hermetia illucens, has the ability to efficiently bioremediate organic waste into usable bio-compounds. Understanding the impact of domestication and mass rearing on fitness and production traits is therefore important for sustainable production. This study aimed to assess patterns of genomic diversity and its association to phenotypic development across early generations of mass rearing under two selection strategies: selection for greater larval mass (SEL lines) and no direct artificial selection (NS lines). Genome-wide single nucleotide polymorphism (SNP) data were generated using 2bRAD sequencing, while phenotypic traits relating to production and population fitness were measured. Declining patterns of genomic diversity were observed across three generations of captive breeding, with the lowest diversity recorded for the F3 generation of both selection lines, most likely due to founder effects. The SEL cohort displayed statistically significantly greater larval weight com the NS lines with pronounced genetic and phenotypic directional changes across generations. Furthermore, lower genetic and phenotypic diversity, particularly for fitness traits, were evident for SEL lines, illustrating the trade-off between selecting for mass and the resulting decline in population fitness. SNP-based heritability was significant for growth, but was low or non-significant for fitness traits. Genotype-phenotype correlations were observed for traits, but individual locus effect sizes where small and very few of these loci demonstrated a signature for selection. Pronounced genetic drift, due to small effective population sizes, is likely overshadowing the impacts of selection on genomic diversity and consequently phenotypic development. The results hold particular relevance for genetic management and selective breeding for BSF in future.

SpadaHC: a database to improve the classification of variants in hereditary cancer genes in the Spanish population

Accurate classification of genetic variants is crucial for clinical decision-making in hereditary cancer. In Spain, genetic diagnostic laboratories have traditionally approached this task independently due to the lack of a dedicated resource. Here we present SpadaHC, a web-based database for sharing variants in hereditary cancer genes in the Spanish population. SpadaHC is implemented using a three-tier architecture consisting of a relational database, a web tool and a bioinformatics pipeline. Contributing laboratories can share variant classifications and variants from individuals in Variant Calling Format (VCF) format. The platform supports open and restricted access, flexible dataset submissions, automatic pseudo-anonymization, VCF quality control, variant normalization and liftover between genome builds. Users can flexibly explore and search data, receive automatic discrepancy notifications and access SpadaHC population frequencies based on many criteria. In February 2024, SpadaHC included 18 laboratory members, storing 1.17 million variants from 4306 patients and 16 343 laboratory classifications. In the first analysis of the shared data, we identified 84 genetic variants with clinically relevant discrepancies in their classifications and addressed them through a three-phase resolution strategy. This work highlights the importance of data sharing to promote consistency in variant classifications among laboratories, so patients and family members can benefit from more accurate clinical management. Database URL: https://spadahc.ciberisciii.es/.

Genomic Reconstruction of the Successful Establishment of a Feralized Bovine Population on the Subantarctic Island of Amsterdam

The feral cattle of the subantarctic island of Amsterdam provide an outstanding case study of a large mammalian population that was established by a handful of founders and thrived within a few generations in a seemingly inhospitable environment. Here, we investigated the genetic history and composition of this population using genotyping and sequencing data. Our inference showed an intense but brief founding bottleneck around the late 19th century and revealed contributions from European taurine and Indian Ocean Zebu in the founder ancestry. Comparative analysis of whole-genome sequences further revealed a moderate reduction in genetic diversity despite high levels of inbreeding. The brief and intense bottleneck was associated with high levels of drift, a flattening of the site frequency spectrum and a slight relaxation of purifying selection on mildly deleterious variants. Unlike some populations that have experienced prolonged reductions in effective population size, we did not observe any significant purging of highly deleterious variants. Interestingly, the population's success in the harsh environment can be attributed to preadaptation from their European taurine ancestry, suggesting no strong bioclimatic challenge, and also contradicting evidence for insular dwarfism. Genome scan for footprints of selection uncovered a majority of candidate genes related to nervous system function, likely reflecting rapid feralization driven by behavioral changes and complex social restructuring. The Amsterdam Island cattle offers valuable insights into rapid population establishment, feralization, and genetic adaptation in challenging environments. It also sheds light on the unique genetic legacies of feral populations, raising ethical questions according to conservation efforts.

Genomic Consequences of Isolation and Inbreeding in an Island Dingo Population

Dingoes come from an ancient canid lineage that originated in East Asia around 8,000 to 11,000 years BP. As Australia's largest terrestrial predator, dingoes play an important ecological role. A small, protected population exists on a world heritage listed offshore island, K'gari (formerly Fraser Island). Concern regarding the persistence of dingoes on K'gari has risen due to their low genetic diversity and elevated inbreeding levels. However, whole-genome sequence data is lacking from this population. Here, we include five new whole-genome sequences of K'gari dingoes. We analyze a total of 18 whole-genome sequences of dingoes sampled from mainland Australia and K'gari to assess the genomic consequences of their demographic histories. Long (>1 Mb) runs of homozygosity (ROHs)-indicators of inbreeding-are elevated in all sampled dingoes. However, K'gari dingoes showed significantly higher levels of very long ROH (>5 Mb), providing genomic evidence for small population size, isolation, inbreeding, and a strong founder effect. Our results suggest that, despite current levels of inbreeding, the K'gari population is purging strongly deleterious mutations, which, in the absence of further reductions in population size, may facilitate the persistence of small populations despite low genetic diversity and isolation. However, there may be little to no purging of mildly deleterious alleles, which may have important long-term consequences, and should be considered by conservation and management programs.

Biostatistical Aspects of Whole Genome Sequencing Studies: Preprocessing and Quality Control

Rapid advances in high-throughput DNA sequencing technologies have enabled large-scale whole genome sequencing (WGS) studies. Before performing association analysis between phenotypes and genotypes, preprocessing and quality control (QC) of the raw sequence data need to be performed. Because many biostatisticians have not been working with WGS data so far, we first sketch Illumina's short-read sequencing technology. Second, we explain the general preprocessing pipeline for WGS studies. Third, we provide an overview of important QC metrics, which are applied to WGS data: on the raw data, after mapping and alignment, after variant calling, and after multisample variant calling. Fourth, we illustrate the QC with the data from the GENEtic SequencIng Study Hamburg-Davos (GENESIS-HD), a study involving more than 9000 human whole genomes. All samples were sequenced on an Illumina NovaSeq 6000 with an average coverage of 35× using a PCR-free protocol. For QC, one genome in a bottle (GIAB) trio was sequenced in four replicates, and one GIAB sample was successfully sequenced 70 times in different runs. Fifth, we provide empirical data on the compression of raw data using the DRAGEN original read archive (ORA). The most important quality metrics in the application were genetic similarity, sample cross-contamination, deviations from the expected Het/Hom ratio, relatedness, and coverage. The compression ratio of the raw files using DRAGEN ORA was 5.6:1, and compression time was linear by genome coverage. In summary, the preprocessing, joint calling, and QC of large WGS studies are feasible within a reasonable time, and efficient QC procedures are readily available.

Gene expression response under thermal stress in two Hawaiian corals is dominated by ploidy and genotype

Transcriptome data are frequently used to investigate coral bleaching; however, the factors controlling gene expression in natural populations of these species are poorly understood. We studied two corals, Montipora capitata and Pocillopora acuta, that inhabit the sheltered Kāne'ohe Bay, Hawai'i. M. capitata colonies in the bay are outbreeding diploids, whereas P. acuta is a mixture of clonal diploids and triploids. Populations were sampled from six reefs and subjected to either control (no stress), thermal stress, pH stress, or combined pH and thermal stress treatments. RNA-seq data were generated to test two competing hypotheses: (1) gene expression is largely independent of genotype, reflecting a shared treatment-driven response (TDE) or, (2) genotype dominates gene expression, regardless of treatment (GDE). Our results strongly support the GDE model, even under severe stress. We suggest that post-transcriptional processes (e.g., control of translation, protein turnover) modify the signal from the transcriptome, and may underlie the observed differences in coral bleaching sensitivity via the downstream proteome and metabolome.

Characterization of genetic variants of GIPR reveals a contribution of β-arrestin to metabolic phenotypes

Incretin-based therapies are highly successful in combatting obesity and type 2 diabetes1. Yet both activation and inhibition of the glucose-dependent insulinotropic polypeptide (GIP) receptor (GIPR) in combination with glucagon-like peptide-1 (GLP-1) receptor (GLP-1R) activation have resulted in similar clinical outcomes, as demonstrated by the GIPR-GLP-1R co-agonist tirzepatide2 and AMG-133 (ref. 3) combining GIPR antagonism with GLP-1R agonism. This underlines the importance of a better understanding of the GIP system. Here we show the necessity of β-arrestin recruitment for GIPR function, by combining in vitro pharmacological characterization of 47 GIPR variants with burden testing of clinical phenotypes and in vivo studies. Burden testing of variants with distinct ligand-binding capacity, Gs activation (cyclic adenosine monophosphate production) and β-arrestin 2 recruitment and internalization shows that unlike variants solely impaired in Gs signalling, variants impaired in both Gs and β-arrestin 2 recruitment contribute to lower adiposity-related traits. Endosomal Gs-mediated signalling of the variants shows a β-arrestin dependency and genetic ablation of β-arrestin 2 impairs cyclic adenosine monophosphate production and decreases GIP efficacy on glucose control in male mice. This study highlights a crucial impact of β-arrestins in regulating GIPR signalling and overall preservation of biological activity that may facilitate new developments in therapeutic targeting of the GIPR system.

Systematic rare variant analyses identify RAB32 as a susceptibility gene for familial Parkinson's disease

Despite substantial progress, causal variants are identified only for a minority of familial Parkinson's disease (PD) cases, leaving high-risk pathogenic variants unidentified1,2. To identify such variants, we uniformly processed exome sequencing data of 2,184 index familial PD cases and 69,775 controls. Exome-wide analyses converged on RAB32 as a novel PD gene identifying c.213C > G/p.S71R as a high-risk variant presenting in ~0.7% of familial PD cases while observed in only 0.004% of controls (odds ratio of 65.5). This variant was confirmed in all cases via Sanger sequencing and segregated with PD in three families. RAB32 encodes a small GTPase known to interact with LRRK2 (refs. 3,4). Functional analyses showed that RAB32 S71R increases LRRK2 kinase activity, as indicated by increased autophosphorylation of LRRK2 S1292. Here our results implicate mutant RAB32 in a key pathological mechanism in PD-LRRK2 kinase activity5-7-and thus provide novel insights into the mechanistic connections between RAB family biology, LRRK2 and PD risk.

Deep history of cultural and linguistic evolution among Central African hunter-gatherers

Human evolutionary history in Central Africa reflects a deep history of population connectivity. However, Central African hunter-gatherers (CAHGs) currently speak languages acquired from their neighbouring farmers. Hence it remains unclear which aspects of CAHG cultural diversity results from long-term evolution preceding agriculture and which reflect borrowing from farmers. On the basis of musical instruments, foraging tools, specialized vocabulary and genome-wide data from ten CAHG populations, we reveal evidence of large-scale cultural interconnectivity among CAHGs before and after the Bantu expansion. We also show that the distribution of hunter-gatherer musical instruments correlates with the oldest genomic segments in our sample predating farming. Music-related words are widely shared between western and eastern groups and likely precede the borrowing of Bantu languages. In contrast, subsistence tools are less frequently exchanged and may result from adaptation to local ecologies. We conclude that CAHG material culture and specialized lexicon reflect a long evolutionary history in Central Africa.

Genomic tools for early selection among Thoroughbreds and Polo Argentino horses for practicing polo

The Polo Argentino (PA) horse is a recognized breed, developed originally by mixing crossbred and Thoroughbred (TB) horses to play polo. Early PA selection is difficult due to unreliable performance estimations. This study investigated the usefulness of genomic markers previously linked to morphological and functional traits as a tool for the early selection of PA. To this, we genotyped 520 PA and 30 TB horses using the Equine GGPArray (Illumina, n = 71,778 SNPs). Analyses included a genetic characterization of six genetic markers associated with behavioral (DRD4), muscular development (MSTN), and body size (LCORL, HMGA6, ZFAT, and LASP1) genes. Genetic differences in the DRD4, MSTN, and LCORL SNP were found between the two breeds, in the last two FST index between breeds was 0.13 and 0.6, respectively (p < 0.01). In DRD4, G allele was the more prevalent in PA (0.56 vs 0.45 in TB, p < 0.05), but no differences were observed between the genotypes associated with phenotypes. In MSTN, heterozygous genotypes were the most common in PA (48 %), with a significant decrease in AA (Hardy-Weinberg p < 0.05), suggesting a negative selection against it in polo horses. In body size, HMGA2 was monomorphic in all horses, while ZFAT and LASP1 SNP showed higher variability. Interestingly, 99 % of PA showed a TT genotype in LCORL (only 66 % in TB), demonstrating selection for smaller horses. Our results suggest that empirical selection in PA has generated an incipient genomic differentiation in discrete traits which could be used as a marker-assisted selection tool for early selection of polo horses.

Influence of Polygenic Background on the Clinical Presentation of Familial Hypercholesterolemia

BACKGROUND

Heterozygous familial hypercholesterolemia (FH) is among the most common genetic conditions worldwide that affects ≈ 1 in 300 individuals. FH is characterized by increased levels of low-density lipoprotein cholesterol (LDL-C) and increased risk of coronary artery disease (CAD), but there is a wide spectrum of severity within the FH population. This variability in expression is incompletely explained by known risk factors. We hypothesized that genome-wide genetic influences, as represented by polygenic risk scores (PRSs) for cardiometabolic traits, would influence the phenotypic severity of FH.

METHODS

We studied individuals with clinically diagnosed FH (n=1123) from the FH Canada National Registry, as well as individuals with genetically identified FH from the UK Biobank (n=723). For all individuals, we used genome-wide gene array data to calculate PRSs for CAD, LDL-C, lipoprotein(a), and other cardiometabolic traits. We compared the distribution of PRSs in individuals with clinically diagnosed FH, genetically diagnosed FH, and non-FH controls and examined the association of the PRSs with the risk of atherosclerotic cardiovascular disease.

RESULTS

Individuals with clinically diagnosed FH had higher levels of LDL-C, and the incidence of atherosclerotic cardiovascular disease was higher in individuals with clinically diagnosed compared with genetically identified FH. Individuals with clinically diagnosed FH displayed enrichment for higher PRSs for CAD, LDL-C, and lipoprotein(a) but not for other cardiometabolic risk factors. The CAD PRS was associated with a risk of atherosclerotic cardiovascular disease among individuals with an FH-causing genetic variant.

CONCLUSIONS

Genetic background, as expressed by genome-wide PRSs for CAD, LDL-C, and lipoprotein(a), influences the phenotypic severity of FH, expanding our understanding of the determinants that contribute to the variable expressivity of FH. A PRS for CAD may aid in risk prediction among individuals with FH.

Two more families supporting the existence of monogenic spinocerebellar ataxia 48

The reduced penetrance of TBP intermediate alleles and the recently proposed possible digenic TBP/STUB1 inheritance raised questions on the possible mechanism involved opening a debate on the existence of SCA48 as a monogenic disorder. We here report clinical and genetic results of two apparently unrelated patients carrying the same STUB1 variant(c.244G > T;p.Asp82Tyr) with normal TBP alleles and a clinical picture fully resembling SCA48, including cerebellar ataxia, dysarthria and mild cognitive impairment. This report provides supportive evidence that this specific ataxia can also occur as a monogenic disease, considering classical TBP allelic ranges.

Distinguishing recrudescence from reinfection in lymphatic filariasis

BACKGROUND

The Global Program to Eliminate Lymphatic Filariasis (GPELF) is the largest public health program based on mass drug administration (MDA). Despite decades of MDA, ongoing transmission in some countries remains a challenge. To optimise interventions, it is critical to differentiate between recrudescence and new infections. Since adult filariae are inaccessible in humans, deriving a method that relies on the offspring microfilariae (mf) is necessary.

METHODS

We developed a genome amplification and kinship analysis-based approach using Brugia malayi samples from gerbils, and applied it to analyse Wuchereria bancrofti mf from humans in Côte d'Ivoire. We examined the pre-treatment genetic diversity in 269 mf collected from 18 participants, and further analysed 1-year post-treatment samples of 74 mf from 4 participants. Hemizygosity of the male X-chromosome allowed for direct inference of haplotypes, facilitating robust maternal parentage inference. To enrich parasite DNA from samples contaminated with host DNA, a whole-exome capture panel was created for W. bancrofti.

FINDINGS

By reconstructing and temporally tracking sibling relationships across pre- and post-treatment samples, we differentiated between new and established maternal families, suggesting reinfection in one participant and recrudescence in three participants. The estimated number of reproductively active adult females ranged between 3 and 11 in the studied participants. Population structure analysis revealed genetically distinct parasites in Côte d'Ivoire compared to samples from other countries. Exome capture identified protein-coding variants with ∼95% genotype concordance rate.

INTERPRETATION

We have generated resources to facilitate the development of molecular genetic tools that can estimate adult worm burdens and monitor parasite populations, thus providing essential information for the successful implementation of GPELF.

FUNDING

This work was financially supported by the Bill and Melinda Gates Foundation (https://www.gatesfoundation.org) under grant OPP1201530 (Co-PIs PUF & Gary J. Weil). B. malayi parasite material was generated with support of the Foundation for Barnes Jewish Hospital (PUF). In addition, the development of computational methods was supported by the National Institutes of Health under grants AI144161 (MM) and AI146353 (MM). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Detecting gene-environment interactions from multiple continuous traits

MOTIVATION

Genetic variants present differential effects on humans according to various environmental exposures, the so-called "gene-environment interactions" (GxE). Many diseases can be diagnosed with multiple traits, such as obesity, diabetes, and dyslipidemia. I developed a multivariate scale test (MST) for detecting the GxE of a disease with several continuous traits. Given a significant MST result, I continued to search for which trait and which E enriched the GxE signals. Simulation studies were performed to compare MST with the univariate scale test (UST).

RESULTS

MST can gain more power than UST because of (1) integrating more traits with GxE information and (2) the less harsh penalty on multiple testing. However, if only few traits account for GxE, MST may lose power due to aggregating non-informative traits into the test statistic. As an example, MST was applied to a discovery set of 93 708 Taiwan Biobank (TWB) individuals and a replication set of 25 200 TWB individuals. From among 2 570 487 SNPs with minor allele frequencies ≥5%, MST identified 18 independent variance quantitative trait loci (P < 2.4E-9 in the discovery cohort and P < 2.8E-5 in the replication cohort) and 41 GxE signals (P < .00027) based on eight trait domains (including 29 traits).

AVAILABILITY AND IMPLEMENTATION

https://github.com/WanYuLin/Multivariate-scale-test-MST.

Benchmarking kinship estimation tools for ancient genomes using pedigree simulations

There is growing interest in uncovering genetic kinship patterns in past societies using low-coverage palaeogenomes. Here, we benchmark four tools for kinship estimation with such data: lcMLkin, NgsRelate, KIN, and READ, which differ in their input, IBD estimation methods, and statistical approaches. We used pedigree and ancient genome sequence simulations to evaluate these tools when only a limited number (1 to 50 K, with minor allele frequency ≥0.01) of shared SNPs are available. The performance of all four tools was comparable using ≥20 K SNPs. We found that first-degree related pairs can be accurately classified even with 1 K SNPs, with 85% F1 scores using READ and 96% using NgsRelate or lcMLkin. Distinguishing third-degree relatives from unrelated pairs or second-degree relatives was also possible with high accuracy (F1 > 90%) with 5 K SNPs using NgsRelate and lcMLkin, while READ and KIN showed lower success (69 and 79% respectively). Meanwhile, noise in population allele frequencies and inbreeding (first-cousin mating) led to deviations in kinship coefficients, with different sensitivities across tools. We conclude that using multiple tools in parallel might be an effective approach to achieve robust estimates on ultra-low-coverage genomes.

Improving population scale statistical phasing with whole-genome sequencing data

Haplotype estimation, or phasing, has gained significant traction in large-scale projects due to its valuable contributions to population genetics, variant analysis, and the creation of reference panels for imputation and phasing of new samples. To scale with the growing number of samples, haplotype estimation methods designed for population scale rely on highly optimized statistical models to phase genotype data, and usually ignore read-level information. Statistical methods excel in resolving common variants, however, they still struggle at rare variants due to the lack of statistical information. In this study we introduce SAPPHIRE, a new method that leverages whole-genome sequencing data to enhance the precision of haplotype calls produced by statistical phasing. SAPPHIRE achieves this by refining haplotype estimates through the realignment of sequencing reads, particularly targeting low-confidence phase calls. Our findings demonstrate that SAPPHIRE significantly enhances the accuracy of haplotypes obtained from state of the art methods and also provides the subset of phase calls that are validated by sequencing reads. Finally, we show that our method scales to large data sets by its successful application to the extensive 3.6 Petabytes of sequencing data of the last UK Biobank 200,031 sample release.

Rare variant analyses validate known ALS genes in a multi-ethnic population and identifies ANTXR2 as a candidate in PLS

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting over 300,000 people worldwide. It is characterized by the progressive decline of the nervous system that leads to the weakening of muscles which impacts physical function. Approximately, 15% of individuals diagnosed with ALS have a known genetic variant that contributes to their disease. As therapies that slow or prevent symptoms continue to develop, such as antisense oligonucleotides, it is important to discover novel genes that could be targets for treatment. Additionally, as cohorts continue to grow, performing analyses in ALS subtypes, such as primary lateral sclerosis (PLS), becomes possible due to an increase in power. These analyses could highlight novel pathways in disease manifestation.

METHODS

Building on our previous discoveries using rare variant association analyses, we conducted rare variant burden testing on a substantially larger multi-ethnic cohort of 6,970 ALS patients, 166 PLS patients, and 22,524 controls. We used intolerant domain percentiles based on sub-region Residual Variation Intolerance Score (subRVIS) that have been described previously in conjunction with gene based collapsing approaches to conduct burden testing to identify genes that associate with ALS and PLS.

RESULTS

A gene based collapsing model showed significant associations with SOD1, TARDBP, and TBK1 (OR = 19.18, p = 3.67 × 10-39; OR = 4.73, p = 2 × 10-10; OR = 2.3, p = 7.49 × 10-9, respectively). These genes have been previously associated with ALS. Additionally, a significant novel control enriched gene, ALKBH3 (p = 4.88 × 10-7), was protective for ALS in this model. An intolerant domain-based collapsing model showed a significant improvement in identifying regions in TARDBP that associated with ALS (OR = 10.08, p = 3.62 × 10-16). Our PLS protein truncating variant collapsing analysis demonstrated significant case enrichment in ANTXR2 (p = 8.38 × 10-6).

CONCLUSIONS

In a large multi-ethnic cohort of 6,970 ALS patients, collapsing analyses validated known ALS genes and identified a novel potentially protective gene, ALKBH3. A first-ever analysis in 166 patients with PLS found a candidate association with loss-of-function mutations in ANTXR2.

Continent-wide genomic analysis of the African buffalo (Syncerus caffer)

The African buffalo (Syncerus caffer) is a wild bovid with a historical distribution across much of sub-Saharan Africa. Genomic analysis can provide insights into the evolutionary history of the species, and the key selective pressures shaping populations, including assessment of population level differentiation, population fragmentation, and population genetic structure. In this study we generated the highest quality de novo genome assembly (2.65 Gb, scaffold N50 69.17 Mb) of African buffalo to date, and sequenced a further 195 genomes from across the species distribution. Principal component and admixture analyses provided little support for the currently described four subspecies. Estimating Effective Migration Surfaces analysis suggested that geographical barriers have played a significant role in shaping gene flow and the population structure. Estimated effective population sizes indicated a substantial drop occurring in all populations 5-10,000 years ago, coinciding with the increase in human populations. Finally, signatures of selection were enriched for key genes associated with the immune response, suggesting infectious disease exert a substantial selective pressure upon the African buffalo. These findings have important implications for understanding bovid evolution, buffalo conservation and population management.

Effect of polygenic scores of telomere length alleles on telomere length in newborns and parents

In adults, polygenic scores (PGSs) of telomere length (TL) alleles explain about 4.5% of the variance in TL, as measured by quantitative polymerase chain reaction (qPCR). Yet, these PGSs strongly infer a causal role of telomeres in aging-related diseases. To better understand the determinants of TL through the lifespan, it is essential to examine to what extent these PGSs explain TL in newborns. This study investigates the effect of PGSs on TL in both newborns and their parents, with TL measured by Southern blotting and expressed in base-pairs (bp). Additionally, the study explores the impact of PGSs related to transmitted or non-transmitted alleles on TL in newborns. For parents and newborns, the PGS effects on TL were 172 bp (p =  2.03 × 10-15) and 161 bp (p =  3.06 × 10-8), explaining 6.6% and 5.2% of the TL variance, respectively. The strongest PGS effect was shown for maternally transmitted alleles in newborn girls, amounting to 214 bp (p =  3.77 × 10-6) and explaining 7.8% of the TL variance. The PGS effect of non-transmitted alleles was 56 bp (p = 0.0593) and explained 0.6% of the TL variance. Our findings highlight the importance of TL genetics in understanding early-life determinants of TL. They point to the potential utility of PGSs composed of TL alleles in identifying susceptibility to aging-related diseases from birth and reveal the presence of sexual dimorphism in the effect of TL alleles on TL in newborns. Finally, we attribute the higher TL variance explained by PGSs in our study to TL measurement by Southern blotting.