Splicing Quantitative Trait Loci Research Articles

Joint models reveal genetic architecture of pubertal stage transitions and their association with BMI in admixed Chilean population.

Early or late pubertal onset can lead to disease in adulthood, including cancer, obesity, type 2 diabetes, metabolic disorders, bone fractures, and psychopathologies. Thus, knowing the age at which puberty is attained is crucial as it can serve as a risk factor for future diseases. Pubertal development is divided into five stages of sexual maturation in boys and girls according to the standardized Tanner scale. We performed genome-wide association studies (GWAS) on the "Growth and Obesity Chilean Cohort Study" cohort composed of admixed children with mainly European and Native American ancestry. Using joint models that integrate time-to-event data with longitudinal trajectories of body mass index (BMI), we identified genetic variants associated with phenotypic transitions between pairs of Tanner stages. We identified $42$ novel significant associations, most of them in boys. The GWAS on Tanner $3\rightarrow 4$ transition in boys captured an association peak around the growth-related genes LARS2 and LIMD1 genes, the former of which causes ovarian dysfunction when mutated. The associated variants are expression and splicing Quantitative Trait Loci regulating gene expression and alternative splicing in multiple tissues. Further, higher individual Native American genetic ancestry proportions predicted a significantly earlier puberty onset in boys but not in girls. Finally, the joint models identified a longitudinal BMI parameter significantly associated with several Tanner stages' transitions, confirming the association of BMI with pubertal timing.

Nucleotide excision repair gene polymorphisms and hepatoblastoma susceptibility in Eastern Chinese children: A five-center case-control study.

Nucleotide excision repair (NER) plays a vital role in maintaining genome stability, and the effect of NER gene polymorphisms on hepatoblastoma susceptibility is still under investigation. This study aimed to evaluate the relationship between NER gene polymorphisms and the risk of hepatoblastoma in Eastern Chinese Han children. In this five-center case-control study, we enrolled 966 subjects from East China (193 hepatoblastoma patients and 773 healthy controls). The TaqMan method was used to genotype 19 single nucleotide polymorphisms (SNPs) in NER pathway genes, including ERCC1, XPA, XPC, XPD, XPF, and XPG. Then, multivariate logistic regression analysis was performed, and odds ratios (ORs) and 95% confidence intervals (95% CIs) were utilized to assess the strength of associations. Three SNPs were related to hepatoblastoma risk. XPC rs2229090 and XPD rs3810366 significantly contributed to hepatoblastoma risk according to the dominant model (adjusted OR=1.49, 95% CI=1.07-2.08, P=0.019; adjusted OR=1.66, 95% CI=1.12-2.45, P=0.012, respectively). However, XPD rs238406 conferred a significantly decreased risk of hepatoblastoma under the dominant model (adjusted OR=0.68, 95% CI=0.49-0.95; P=0.024). Stratified analysis demonstrated that these significant associations were more prominent in certain subgroups. Moreover, there was evidence of functional implications of these significant SNPs suggested by online expression quantitative trait loci (eQTLs) and splicing quantitative trait loci (sQTLs) analysis. In summary, NER pathway gene polymorphisms (XPC rs2229090, XPD rs3810366, and XPD rs238406) are significantly associated with hepatoblastoma risk, and further research is required to verify these findings.

Cross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain.

Neuropsychiatric genome-wide association studies (GWASs), including those for autism spectrum disorder and schizophrenia, show strong enrichment for regulatory elements in the developing brain. However, prioritizing risk genes and mechanisms is challenging without a unified regulatory atlas. Across 672 diverse developing human brains, we identified 15,752 genes harboring gene, isoform, and/or splicing quantitative trait loci, mapping 3739 to cellular contexts. Gene expression heritability drops during development, likely reflecting both increasing cellular heterogeneity and the intrinsic properties of neuronal maturation. Isoform-level regulation, particularly in the second trimester, mediated the largest proportion of GWAS heritability. Through colocalization, we prioritized mechanisms for about 60% of GWAS loci across five disorders, exceeding adult brain findings. Finally, we contextualized results within gene and isoform coexpression networks, revealing the comprehensive landscape of transcriptome regulation in development and disease.

A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer

Splicing-based transcriptome-wide association studies (splicing-TWASs) of breast cancer have the potential to identify susceptibility genes. However, existing splicing-TWASs test the association of individual excised introns in breast tissue only and thus have limited power to detect susceptibility genes. In this study, we performed a multi-tissue joint splicing-TWAS that integrated splicing-TWAS signals of multiple excised introns in each gene across 11 tissues that are potentially relevant to breast cancer risk. We utilized summary statistics from a meta-analysis that combined genome-wide association study (GWAS) results of 424,650 women of European ancestry. Splicing-level prediction models were trained in GTEx (v.8) data. We identified 240 genes by the multi-tissue joint splicing-TWAS at the Bonferroni-corrected significance level; in the tissue-specific splicing-TWAS that combined TWAS signals of excised introns in genes in breast tissue only, we identified nine additional significant genes. Of these 249 genes, 88 genes in 62 loci have not been reported by previous TWASs, and 17 genes in seven loci are at least 1 Mb away from published GWAS index variants. By comparing the results of our splicing-TWASs with previous gene-expression-based TWASs that used the same summary statistics and expression prediction models trained in the same reference panel, we found that 110 genes in 70 loci that are identified only by the splicing-TWASs. Our results showed that for many genes, expression quantitative trait loci (eQTL) did not show a significant impact on breast cancer risk, whereas splicing quantitative trait loci (sQTL) showed a strong impact through intron excision events.

Identification and characterization of whole blood gene expression and splicing quantitative trait loci during early to mid-lactation of dairy cattle

BackgroundCharacterization of regulatory variants (e.g., gene expression quantitative trait loci, eQTL; gene splicing QTL, sQTL) is crucial for biologically interpreting molecular mechanisms underlying loci associated with complex traits. However, regulatory variants in dairy cattle, particularly in specific biological contexts (e.g., distinct lactation stages), remain largely unknown. In this study, we explored regulatory variants in whole blood samples collected during early to mid-lactation (22–150 days after calving) of 101 Holstein cows and analyzed them to decipher the regulatory mechanisms underlying complex traits in dairy cattle.ResultsWe identified 14,303 genes and 227,705 intron clusters expressed in the white blood cells of 101 cattle. The average heritability of gene expression and intron excision ratio explained by cis-SNPs is 0.28 ± 0.13 and 0.25 ± 0.13, respectively. We identified 23,485 SNP-gene expression pairs and 18,166 SNP-intron cluster pairs in dairy cattle during early to mid-lactation. Compared with the 2,380,457 cis-eQTLs reported to be present in blood in the Cattle Genotype-Tissue Expression atlas (CattleGTEx), only 6,114 cis-eQTLs (P < 0.05) were detected in the present study. By conducting colocalization analysis between cis-e/sQTL and the results of genome-wide association studies (GWAS) from four traits, we identified a cis-e/sQTL (rs109421300) of the DGAT1 gene that might be a key marker in early to mid-lactation for milk yield, fat yield, protein yield, and somatic cell score (PP4 > 0.6). Finally, transcriptome-wide association studies (TWAS) revealed certain genes (e.g., FAM83H and TBC1D17) whose expression in white blood cells was significantly (P < 0.05) associated with complex traits.ConclusionsThis study investigated the genetic regulation of gene expression and alternative splicing in dairy cows during early to mid-lactation and provided new insights into the regulatory mechanisms underlying complex traits of economic importance.

Pangenome-genotyped structural variation improves molecular phenotype mapping in cattle.

Expression and splicing quantitative trait loci (e/sQTL) are large contributors to phenotypic variability. Achieving sufficient statistical power for e/sQTL mapping requires large cohorts with both genotypes and molecular phenotypes, and so, the genomic variation is often called from short-read alignments, which are unable to comprehensively resolve structural variation. Here we build a pangenome from 16 HiFi haplotype-resolved cattle assemblies to identify small and structural variation and genotype them with PanGenie in 307 short-read samples. We find high (>90%) concordance of PanGenie-genotyped and DeepVariant-called small variation and confidently genotype close to 21 million small and 43,000 structural variants in the larger population. We validate 85% of these structural variants (with MAF > 0.1) directly with a subset of 25 short-read samples that also have medium coverage HiFi reads. We then conduct e/sQTL mapping with this comprehensive variant set in a subset of 117 cattle that have testis transcriptome data, and find 92 structural variants as causal candidates for eQTL and 73 for sQTL. We find that roughly half of the top associated structural variants affecting expression or splicing are transposable elements, such as SV-eQTL for STN1 and MYH7 and SV-sQTL for CEP89 and ASAH2 Extensive linkage disequilibrium between small and structural variation results in only 28 additional eQTL and 17 sQTL discovered when including SVs, although many top associated SVs are compelling candidates.

Integrating genetic regulation and single-cell expression with GWAS prioritizes causal genes and cell types for glaucoma

Primary open-angle glaucoma (POAG), characterized by retinal ganglion cell death, is a leading cause of irreversible blindness worldwide. However, its molecular and cellular causes are not well understood. Elevated intraocular pressure (IOP) is a major risk factor, but many patients have normal IOP. Colocalization and Mendelian randomization analysis of >240 POAG and IOP genome-wide association study (GWAS) loci and overlapping expression and splicing quantitative trait loci (e/sQTLs) in 49 GTEx tissues and retina prioritizes causal genes for 60% of loci. These genes are enriched in pathways implicated in extracellular matrix organization, cell adhesion, and vascular development. Analysis of single-nucleus RNA-seq of glaucoma-relevant eye tissues reveals that the POAG and IOP colocalizing genes and genome-wide associations are enriched in specific cell types in the aqueous outflow pathways, retina, optic nerve head, peripapillary sclera, and choroid. This study nominates IOP-dependent and independent regulatory mechanisms, genes, and cell types that may contribute to POAG pathogenesis.

Integration of Alzheimer’s Disease GWAS with Molecular QTLs Reveals Prioritized Risk Genes and Disease‐associated Molecular Alterations

AbstractBackgroundDespite the success of genome‐wide association studies (GWAS) to identify genetic variants associated with complex diseases, as the majority of these variants reside in non‐coding genome, one important task is to link these variants to disease‐associated molecular alterations in risk genes. To this end, we developed a systematic gene prioritization methodology that integrated our recent Alzheimer’s disease (AD) GWAS meta‐analysis with molecular quantitative trait loci (QTL) in disease‐relevant tissues and identified highly likely candidate risk genes and molecular alterations within the majority of 42 novel loci identified. In this subsequent study, we updated our pipeline with new molecular QTL catalogues and analyzed the complete landscape of AD risk.MethodWe performed GWAS‐QTL integration in AD‐relevant tissues and cells by querying the lead variants in each locus in the molecular QTL catalogues, (ii) investigating genetic colocalization between GWAS and molecular QTL signals using coloc, and (iii) conducting transcriptome, methylome, and proteome‐wide association studies (TWAS/MWAS/PWAS) using the EADB stage I meta‐analysis GWAS on 85,934 cases and 401,577 controls. The updated gene prioritization pipeline included new analyses based on new brain protein expression QTL (pQTL), cell‐type‐specific expression QTL (ct‐eQTL), expression QTL (eQTL), histone acetylation QTL (haQTL), and methylation QTL (mQTL) catalogues. Moreover, we used Nanopore RNA sequencing to further investigate risk‐associated splicing events revealed by splicing QTL (sQTL) integration.ResultOur brain ct‐eQTL coloc results showed that while the most risk‐associated gene expression alterations are specific to microglia, the proportion of astrocyte‐specific eQTL colocalizations were doubled compared to the previous studies. These included EGFR, a previously prioritized gene due to bulk brain eQTL coloc hits, whose downregulation was regulated by the protective signal specifically in astrocytes. Importantly, in a previously unresolved locus we could prioritize HS3ST5 through astrocyte‐specific eQTLs as well. Furthermore, pQTL coloc and PWAS prioritized SNX1, a previously prioritized gene at a lower confidence together with neighboring FAM96A gene, by implicating its genetic downregulation with increased AD risk.ConclusionOur updated pipeline systematically prioritized AD risk genes and disease‐associated molecular alterations in the majority of risk loci, and contributed to better interpretation of AD GWAS and understanding of genetically‐associated molecular mechanisms underlying AD risk.

Alternative splicing and environmental adaptation in wild house mice.

A major goal of evolutionary genetics is to understand the genetic and molecular mechanisms underlying adaptation. Previous work has established that changes in gene regulation may contribute to adaptive evolution, but most studies have focused on mRNA abundance and only a few studies have investigated the role of post-transcriptional processing. Here, we use a combination of exome sequences and short-read RNA-Seq data from wild house mice (Mus musculus domesticus) collected along a latitudinal transect in eastern North America to identify candidate genes for local adaptation through alternative splicing. First, we identified alternatively spliced transcripts that differ in frequency between mice from the northern-most and southern-most populations in this transect. We then identified the subset of these transcripts that exhibit clinal patterns of variation among all populations in the transect. Finally, we conducted association studies to identify cis-acting splicing quantitative trait loci (cis-sQTL), and we identified cis-sQTL that overlapped with previously ascertained targets of selection from genome scans. Together, these analyses identified a small set of alternatively spliced transcripts that may underlie environmental adaptation in house mice. Many of these genes have known phenotypes associated with body size, a trait that varies clinally in these populations. We observed no overlap between these genes and genes previously identified by changes in mRNA abundance, indicating that alternative splicing and changes in mRNA abundance may provide separate molecular mechanisms of adaptation.

Sequence-based GWAS meta-analyses for beef production traits

BackgroundCombining the results of within-population genome-wide association studies (GWAS) based on whole-genome sequences into a single meta-analysis (MA) is an accurate and powerful method for identifying variants associated with complex traits. As part of the H2020 BovReg project, we performed sequence-level MA for beef production traits. Five partners from France, Switzerland, Germany, and Canada contributed summary statistics from sequence-based GWAS conducted with 54,782 animals from 15 purebred or crossbred populations. We combined the summary statistics for four growth, nine morphology, and 15 carcass traits into 16 MA, using both fixed effects and z-score methods.ResultsThe fixed-effects method was generally more informative to provide indication on potentially causal variants, although we combined substantially different traits in each MA. In comparison with within-population GWAS, this approach highlighted (i) a larger number of quantitative trait loci (QTL), (ii) QTL more frequently located in genomic regions known for their effects on growth and meat/carcass traits, (iii) a smaller number of genomic variants within the QTL, and (iv) candidate variants that were more frequently located in genes. MA pinpointed variants in genes, including MSTN, LCORL, and PLAG1 that have been previously associated with morphology and carcass traits. We also identified dozens of other variants located in genes associated with growth and carcass traits, or with a function that may be related to meat production (e.g., HS6ST1, HERC2, WDR75, COL3A1, SLIT2, MED28, and ANKAR). Some of these variants overlapped with expression or splicing QTL reported in the cattle Genotype-Tissue Expression atlas (CattleGTEx) and could therefore regulate gene expression.ConclusionsBy identifying candidate genes and potential causal variants associated with beef production traits in cattle, MA demonstrates great potential for investigating the biological mechanisms underlying these traits. As a complement to within-population GWAS, this approach can provide deeper insights into the genetic architecture of complex traits in beef cattle.

Identification of alternative splicing associated with clinical features: from pan-cancers to genitourinary tumors.

Alternative splicing events (ASEs) are vital causes of tumor heterogeneity in genitourinary tumors and many other cancers. However, the clinicopathological relevance of ASEs in cancers has not yet been comprehensively characterized. By analyzing splicing data from the TCGA SpliceSeq database and phenotype data for all TCGA samples from the UCSC Xena database, we identified differential clinical feature-related ASEs in 33 tumors. CIBERSORT immune cell infiltration data from the TIMER2.0 database were used for differential clinical feature-related immune cell infiltration analysis. Gene function enrichment analysis was used to analyze the gene function of ASEs related to different clinical features in tumors. To reveal the regulatory mechanisms of ASEs, we integrated race-related ASEs and splicing quantitative trait loci (sQTLs) data in kidney renal clear cell carcinoma (KIRC) to comprehensively assess the impact of SNPs on ASEs. In addition, we predicted regulatory RNA binding proteins in bladder urothelial carcinoma (BLCA) based on the enrichment of motifs around alternative exons for ASEs. Alternative splicing differences were systematically analyzed between different groups of 58 clinical features in 33 cancers, and 30 clinical features in 24 cancer types were identified to be associated with more than 50 ASEs individually. The types of immune cell infiltration were found to be significantly different between subgroups of primary diagnosis and disease type. After integrating ASEs with sQTLs data, we found that 63 (58.9%) of the race-related ASEs were significantly SNP-correlated ASEs in KIRC. Gene function enrichment analyses showed that metastasis-related ASEs in KIRC mainly enriched Rho GTPase signaling pathways. Among those ASEs associated with metastasis, alternative splicing of GIT2 and TUBB3 might play key roles in tumor metastasis in KIRC patients. Finally, we identified several RNA binding proteins such as PCBP2, SNRNP70, and HuR, which might contribute to splicing differences between different groups of neoplasm grade in BLCA. We demonstrated the significant clinical relevance of ASEs in multiple cancer types. Furthermore, we identified and validated alternative splicing of TUBB3 and RNA binding proteins such as PCBP2 as critical regulators in the progression of urogenital cancers.

EQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs.

The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases.

MULTI-OMICS MENDELIAN RANDOMISATION USING EXPRESSION, PROTEIN AND SPLICING QUANTITATIVE TRAIT LOCI: IDENTIfiCATION OF NOVEL DRUG TARGETS ASSOCIATED WITH RISK OF GLIOMAGENESIS

Abstract AIMS Genetic variants associated with molecular traits are also associated with liability to glioma. We sought to pro- vide causal evidence for the prioritization of these traits using triangulation of several causal inference approaches. METHOD We performed two-sample Mendelian randomization and genetic colocalization of molecular traits on glioma. Molecular data were taken from studies of expression quantitative trait loci (QTL) [11,803 genes]; protein QTL [7,376 proteins] and splicing QTL [13,285 genes]) derived from 15 brain tissues. Glioma data were taken from a genome-wide association meta-analysis (12,496 cases and 18,190 controls). RESULTS The MR analysis showed evidence for a causal effect of 25 molecular traits on glioma. Of these, 19 (all gene expression) were robust according to colocalization and Steiger filtering. 18/19 (95%) of these genes were previously implicated in genome-wide and transcriptome-wide association studies with glioma risk. We identified one novel locus with causal evidence in cortex tissue: HBEGF (5q31.3). HBEGF expression has been found to be significantly increased in many human cancer types, including glioma. We found genetically predicted in- creased expression of HBEGF associated with an increased risk of all glioma [OR 1.53 (95%CI 1.28 to 1.82); P =2.66 x 10-6] and the glioblastoma subtype [OR 1.68 (95%CI 1.35 to 2.08); P = 2.97 x 10-6]. CONCLUSIONS We provide robust causal evidence as validation for genes previously implicated with glioma risk in genome- wide association studies. Additionally, we show for the first-time evidence for a causal relationship between HBEGF expression and glioma risk.

Integrative splicing-quantitative-trait-locus analysis reveals risk loci for non-small-cell lung cancer

Splicing quantitative trait loci (sQTLs) have been demonstrated to contribute to disease etiology by affecting alternative splicing. However, the role of sQTLs in the development of non-small-cell lung cancer (NSCLC) remains unknown. Thus, we performed a genome-wide sQTL study to identify genetic variants that affect alternative splicing in lung tissues from 116 individuals of Chinese ancestry, which resulted in the identification of 1,385 sQTL-harboring genes (sGenes) containing 378,210 significant variant-intron pairs. A comprehensive characterization of these sQTLs showed that they were enriched in actively transcribed regions, genetic regulatory elements, and splicing-factor-binding sites. Moreover, sQTLs were largely distinct from expression quantitative trait loci (eQTLs) and showed significant enrichment in potential risk loci of NSCLC. We also integrated sQTLs into NSCLC GWAS datasets (13,327 affected individuals and 13,328 control individuals) by using splice-transcriptome-wide association study (spTWAS) and identified alternative splicing events in 19 genes that were significantly associated with NSCLC risk. By using functional annotation and experiments, we confirmed an sQTL variant, rs35861926, that reduced the risk of lung adenocarcinoma (rs35861926-T, OR= 0.88, 95% confidence interval [CI]: 0.82-0.93, p= 1.87×10-5) by promoting FARP1 exon 20 skipping to downregulate the expression level of the long transcript FARP1-011. Transcript FARP1-011 promoted the migration and proliferation of lung adenocarcinoma cells. Overall, our study provided informative lung sQTL resources and insights into the molecular mechanisms linking sQTL variants to NSCLC risk.

Genetic Control of Alternative Splicing and its Distinct Role in Colorectal Cancer Mechanisms

Dysregulation of alternative splicing is implicated in many human diseases and understanding the genetic variation underlying transcript splicing is essential to dissect the molecular mechanisms of cancers. We aimed to provide a comprehensive functional dissection of splicing quantitative trait loci (sQTLs) in cancer and focus on elucidating its distinct role in colorectal cancer (CRC) mechanisms. Firstly, we performed a comprehensive sQTL analysis to identify genetic variants that control mRNA splicing across 33 cancer types from TCGA and independently validated in our 154 CRC tissues. Then, large-scale, multicenter, multiethnic case-control studies (34,585 cases and 76,023 controls) were conducted to examine the association of these sQTLs with CRC risk. A series of biological experiments in vitro and in vivo were performed to investigate the potential mechanisms of the candidate sQTLs and target genes. The molecular characterization of sQTL revealed its distinct role in cancer susceptibility. Tumor-specific sQTL further showed better response to cancer development. Besides, functionally informed polygenetic risk score highlighted the potentiality of sQTLs in the CRC prediction. Complemented by large-scale population studies, we identified that the risk allele (T) of a multi-ancestry-associated sQTL rs61746794 significantly increased the risk of CRC in Chinese populations (OR=1.20, 95% CI=1.12-1.29, P=8.82×10-7) and European populations (OR=1.11, 95% CI=1.07-1.16, P=1.13×10-7). rs61746794-T facilitated PRMT7 exon 16 splicing mediated by the RBP PRPF8, thus increasing the level of canonical PRMT7 isoform (PRMT7-V2). Overexpression of PRMT7-V2 significantly enhanced the growth of CRC cells and xenograft tumors, compared with PRMT7-V1. Mechanistically, PRMT7-V2 functions as an epigenetic writer that catalyzes the arginine methylation of H4R3 and H3R2, subsequently regulating diverse biological processes, including YAP, AKT, and KRAS pathway. A selective PRMT7 inhibitor, SGC3027, exhibited antitumor effects on human CRC cells. Our study provide an informative sQTLs resource and insights into the regulatory mechanisms linking splicing variants to cancer risk, serving as biomarkers and therapeutic targets.

The impact of population pharmacogenomics and risk allele frequencies on cisplatin-induced peripheral sensory neuropathy (PSN).

12092 Background: Taxane-treated breast cancer patients with genetically African ancestry have worse PSN than other groups. However, no study has examined the association between ancestry and PSN after cisplatin-based chemotherapy. Increased risk could be partially explained by differing risk allele frequencies across populations for alleles increasing the general vulnerability to PSN or altering drug metabolism. Methods: The Platinum Study enrolled cisplatin-treated testicular cancer survivors (TCS) who completed clinical exams and surveys. A PSN score was derived from the mean of 8 sensory items (using EORTC-CIPN20), assigning severity on a 0-2 scale. Multidimensional scaling scores for each TCS were calculated, plotted and anchored by data from the 1000 Genomes Reference population to determine genetic ancestry. Multinomial logistic regression assessed the association between genetic ancestry and PSN. To determine risk alleles for PSN and allele frequencies across populations, risk allele panels were created, including ancestry-informative markers (AIMs) determined by the AncestrySNPMiner tool. Allele frequencies were calculated in each group; SNPs with frequency differences &gt; 0.3 in the African (AFRAFR) population vs. others were included. For filtering the AIMs, GTEx data was used to identify expression quantitative trait loci (eQTL) or splicing quantitative trait loci (sQTL) in nerve/brain tissue. Multinomial logistic regression assessed associations between SNP genotype and PSN phenotype for SNPs with differing allele frequencies across populations. Results: Despite small numbers of non-Europeans, TCS with African ancestry had increased incidence and severity of PSN vs. TCS with European ancestry. In a subset analysis of EUR (n = 681) and AFRAFR (n = 13) patients who received 400-450 mg/m2 of cisplatin, the relative risk ratio (RRR) in the AFRAFR vs. EUR TCS of severe neuropathy vs. none was 7.96 (P = 0.074) and the RRR for any neuropathy vs. none was 7.79 (P = 0.049). There were 394 independent AIMs with significant ( &gt; 0.3) allele frequency differences between the AFRAFR and other populations that were eQTLs and/or sQTLs in nerve/brain tissue. Using multinominal logistic regression between genotype and phenotype for all TCS (n = 1513) with covariates for age at survey and 10 genetic principal components: 16 SNPs had P-values &lt; 0.05 for severe PSN vs. none and/or any PSN vs. none. Although not statistically significant with multiple testing corrections, these suggestively significant SNPs could be potentially validated in additional populations. Conclusions: These results are preliminary evidence for the potential importance of differing risk allele frequencies across populations in explaining some disparities in cisplatin-related PSN. If confirmed, genotyping for risk variants could impact treatment decisions and enable monitoring to mitigate PSN.

Evolutionarily recent retrotransposons contribute to schizophrenia

Transposable elements (TEs) are mobile genetic elements that constitute half of the human genome. Recent studies suggest that polymorphic non-reference TEs (nrTEs) may contribute to cognitive diseases, such as schizophrenia, through a cis-regulatory effect. The aim of this work is to identify sets of nrTEs putatively linked to an increased risk of developing schizophrenia. To do so, we inspected the nrTE content of genomes from the dorsolateral prefrontal cortex of schizophrenic and control individuals and identified 38 nrTEs that possibly contribute to the emergence of this psychiatric disorder, two of them further confirmed with haplotype-based methods. We then performed in silico functional inferences and found that 9 of the 38 nrTEs act as expression/alternative splicing quantitative trait loci (eQTLs/sQTLs) in the brain, suggesting a possible role in shaping the human cognitive genome structure. To our knowledge, this is the first attempt at identifying polymorphic nrTEs that can contribute to the functionality of the brain. Finally, we suggest that a neurodevelopmental genetic mechanism, which involves evolutionarily young nrTEs, can be key to understanding the ethio-pathogenesis of this complex disorder.

Large-scale functional screen identifies genetic variants with splicing effects in modern and archaic humans

Humans coexisted and interbred with other hominins which later became extinct. These archaic hominins are known to us only through fossil records and for two cases, genome sequences. Here, we engineer Neanderthal and Denisovan sequences into thousands of artificial genes to reconstruct the pre-mRNA processing patterns of these extinct populations. Of the 5,169 alleles tested in this massively parallel splicing reporter assay (MaPSy), we report 962 exonic splicing mutations that correspond to differences in exon recognition between extant and extinct hominins. Using MaPSy splicing variants, predicted splicing variants, and splicing quantitative trait loci, we show that splice-disrupting variants experienced greater purifying selection in anatomically modern humans than that in Neanderthals. Adaptively introgressed variants were enriched for moderate-effect splicing variants, consistent with positive selection for alternative spliced alleles following introgression. As particularly compelling examples, we characterized a unique tissue-specific alternative splicing variant at the adaptively introgressed innate immunity gene TLR1, as well as a unique Neanderthal introgressed alternative splicing variant in the gene HSPG2 that encodes perlecan. We further identified potentially pathogenic splicing variants found only in Neanderthals and Denisovans in genes related to sperm maturation and immunity. Finally, we found splicing variants that may contribute to variation among modern humans in total bilirubin, balding, hemoglobin levels, and lung capacity. Our findings provide unique insights into natural selection acting on splicing in human evolution and demonstrate how functional assays can be used to identify candidate causal variants underlying differences in gene regulation and phenotype.

A Large-Scale Exome-Wide Association Study Identifies Novel Germline Mutations in Lung Cancer.

Rationale: Genome-wide association studies have identified common variants of lung cancer. However, the contribution of rare exome-wide variants, especially protein-coding variants, to cancers remains largely unexplored. Objectives: To evaluate the role of human exomes in genetic predisposition to lung cancer. Methods: We performed exome-wide association studies to detect the association of exomes with lung cancer in 30,312 patients and 652,902 control subjects. A scalable and accurate implementation of a generalized mixed model was used to detect the association signals for loss-of-function, missense, and synonymous variants and gene-level sets. Furthermore, we performed association and Bayesian colocalization analyses to evaluate their relationships with intermediate exposures. Measurements and Main Results: We systematically analyzed 216,739 single-nucleotide variants in the human exome. The loss-of-function variants exhibited the most notable effects on lung cancer risk. We identified four novel variants, including two missense variants (rs202197044TET3 [Pmeta (P values of meta-analysis) = 3.60 × 10-8] and rs202187871POT1 [Pmeta = 2.21 × 10-8]) and two synonymous variants (rs7447927TMEM173 [Pmeta = 1.32 × 10-9] and rs140624366ATRN [Pmeta = 2.97 × 10-9]). rs202197044TET3 was significantly associated with emphysema (odds ratio, 3.55; Pfdr = 0.015), whereas rs7447927POT1 was strongly associated with telomere length (β = 1.08; Pfdr (FDR corrected P value) = 3.76 × 10-53). Functional evidence of expression of quantitative trait loci, splicing quantitative trait loci, and isoform expression was found for the four novel genes. Gene-level association tests identified several novel genes, including POT1 (protection of telomeres 1), RTEL1, BSG, and ZNF232. Conclusions: Our findings provide insights into the genetic architecture of human exomes and their role in lung cancer predisposition.

Evaluating the Contribution of Cell Type-Specific Alternative Splicing to Variation in Lipid Levels.

Genome-wide association studies have identified hundreds of loci associated with lipid levels. However, the genetic mechanisms underlying most of these loci are not well-understood. Recent work indicates that changes in the abundance of alternatively spliced transcripts contribute to complex trait variation. Consequently, identifying genetic loci that associate with alternative splicing in disease-relevant cell types and determining the degree to which these loci are informative for lipid biology is of broad interest. We analyze gene splicing in 83 sample-matched induced pluripotent stem cell (iPSC) and hepatocyte-like cell lines (n=166), as well as in an independent collection of primary liver tissues (n=96) to perform discovery of splicing quantitative trait loci (sQTLs). We observe that transcript splicing is highly cell type specific, and the genes that are differentially spliced between iPSCs and hepatocyte-like cells are enriched for metabolism pathway annotations. We identify 1384 hepatocyte-like cell sQTLs and 1455 iPSC sQTLs at a false discovery rate of <5% and find that sQTLs are often shared across cell types. To evaluate the contribution of sQTLs to variation in lipid levels, we conduct colocalization analysis using lipid genome-wide association data. We identify 19 lipid-associated loci that colocalize either with an hepatocyte-like cell expression quantitative trait locus or sQTL. Only 2 loci colocalize with both a sQTL and expression quantitative trait locus, indicating that sQTLs contribute information about genome-wide association studies loci that cannot be obtained by analysis of steady-state gene expression alone. These results provide an important foundation for future efforts that use iPSC and iPSC-derived cells to evaluate genetic mechanisms influencing both cardiovascular disease risk and complex traits in general.