Low-frequency Genetic Variants Research Articles

Identifying Invaders: The Case of Ceratium furcoides (Gonyaulacales, Dinophyceae) in South America.

Ceratium furcoides is an invasive freshwater dinoflagellate that in the last three decades has expanded its geographic distribution in South America, being recently found in Paraná River floodplain (Argentina). Despite growing concern about the presence and impacts of this invader, information regarding genetic diversity in the Southern Hemisphere is missing. This work constitutes the first phylogenetic characterization of Ceratium populations of South America, particularly, from the Paraná system. After taxonomic identification as C.furcoides based on morphological traits, two sequencing-based approaches were applied using the ribosomal 18S gene: Sanger sequencing to isolated individuals and high-throughput amplicon sequencing (HTS) to environmental DNA. The sequence of C.furcoides obtained shared 100% identity to Asian sequences, and formed a highly supported clade in the constructed reference phylogenetic tree. HTS helped to recover low-frequency genetic variants suggesting the presence of different population of C.furcoides, and to alert potential invasion in its early stages.

Polygenic analysis of the effect of common and low-frequency genetic variants on serum uric acid levels in Korean individuals

Increased serum uric acid (SUA) levels cause gout and are associated with multiple diseases, including chronic kidney disease. Previous genome-wide association studies (GWAS) have identified more than 180 loci that contribute to SUA levels. Here, we investigated genetic determinants of SUA level in the Korean population. We conducted a GWAS for SUA in 6,881 Korean individuals, calculated polygenic risk scores (PRSs) for common variants, and validated the association of low-frequency variants and PRS with SUA levels in 3,194 individuals. We identified two low-frequency and six common independent variants associated with SUA. Despite the overall similar effect sizes of variants in Korean and European populations, the proportion of variance for SUA levels explained by the variants was greater in the Korean population. A rare, nonsense variant SLC22A12 p.W258X showed the most significant association with reduced SUA levels, and PRSs of common variants associated with SUA levels were significant in multiple Korean cohorts. Interestingly, an East Asian-specific missense variant (rs671) in ALDH2 displayed a significant association on chromosome 12 with the SUA level. Further genetic epidemiological studies on SUA are needed in ethnically diverse cohorts to investigate rare or low-frequency variants and determine the influence of genetic and environmental factors on SUA.

Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels.

Alcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels. In the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, ≤5%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered. We discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (PCSK9, LPA, LPL, LIPG, ANGPTL4, APOB, APOC3, and CD300LG) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (P=6.65×10-6 for the interaction test) and replicated at nominal significance level (P=0.013) in SMC5. In conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.

Genomic history of the Italian population recapitulates key evolutionary dynamics of both Continental and Southern Europeans

BackgroundThe cline of human genetic diversity observable across Europe is recapitulated at a micro-geographic scale by variation within the Italian population. Besides resulting from extensive gene flow, this might be ascribable also to local adaptations to diverse ecological contexts evolved by people who anciently spread along the Italian Peninsula. Dissecting the evolutionary history of the ancestors of present-day Italians may thus improve the understanding of demographic and biological processes that contributed to shape the gene pool of European populations. However, previous SNP array-based studies failed to investigate the full spectrum of Italian variation, generally neglecting low-frequency genetic variants and examining a limited set of small effect size alleles, which may represent important determinants of population structure and complex adaptive traits. To overcome these issues, we analyzed 38 high-coverage whole-genome sequences representative of population clusters at the opposite ends of the cline of Italian variation, along with a large panel of modern and ancient Euro-Mediterranean genomes.ResultsWe provided evidence for the early divergence of Italian groups dating back to the Late Glacial and for Neolithic and distinct Bronze Age migrations having further differentiated their gene pools. We inferred adaptive evolution at insulin-related loci in people from Italian regions with a temperate climate, while possible adaptations to pathogens and ultraviolet radiation were observed in Mediterranean Italians. Some of these adaptive events may also have secondarily modulated population disease or longevity predisposition.ConclusionsWe disentangled the contribution of multiple migratory and adaptive events in shaping the heterogeneous Italian genomic background, which exemplify population dynamics and gene-environment interactions that played significant roles also in the formation of the Continental and Southern European genomic landscapes.

Exome-chip association analysis of intracranial aneurysms.

To investigate to what extent low-frequency genetic variants (with minor allele frequencies <5%) affect the risk of intracranial aneurysms (IAs). One thousand fifty-six patients with IA and 2,097 population-based controls from the Netherlands were genotyped with the Illumina HumanExome BeadChip. After quality control (QC) of samples and single nucleotide variants (SNVs), we conducted a single variant analysis using the Fisher exact test. We also performed the variable threshold (VT) test and the sequence kernel association test (SKAT) at different minor allele count (MAC) thresholds of >5 and >0 to test the hypothesis that multiple variants within the same gene are associated with IA risk. Significant results were tested in a replication cohort of 425 patients with IA and 311 controls, and results of the 2 cohorts were combined in a meta-analysis. After QC, 995 patients with IA and 2,080 controls remained for further analysis. The single variant analysis comprising 46,534 SNVs did not identify significant loci at the genome-wide level. The gene-based tests showed a statistically significant association for fibulin 2 (FBLN2) (best p = 1 × 10-6 for the VT test, MAC >5). Associations were not statistically significant in the independent but smaller replication cohort (p > 0.57) but became slightly stronger in a meta-analysis of the 2 cohorts (best p = 4.8 × 10-7 for the SKAT, MAC ≥1). Gene-based tests indicated an association for FBLN2, a gene encoding an extracellular matrix protein implicated in vascular wall remodeling, but independent validation in larger cohorts is warranted. We did not identify any significant associations for single low-frequency genetic variants.

Abstract 3538: Analysis of error profiles in deep next-generation sequencing data

Abstract Background Sequencing errors are a key confounding factor for detecting low frequency genetic variants for cancer screening, testing, treatment and surveillance through deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, enrichment PCR, and sequencing. In this study we systematically investigated the above question by using the current NGS technology. Results We discovered that the substitution error rate can be computationally suppressed to 10-5~10-4, which is 10~100-fold lower than current reports. We then quantified substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing using multiple deep sequencing datasets from multiple sequencing centers. We show that 1) error rate differs by nucleotide substitution types, ranging from 10-5 for A&amp;gt;C/T&amp;gt;G, C&amp;gt;A/G&amp;gt;T, and C&amp;gt;G/G&amp;gt;C changes to 10-4 for A&amp;gt;G/T&amp;gt;C changes; 2) C&amp;gt;T/G&amp;gt;A errors exhibit strong sequence context dependency; 3) sample-specific effects dominate elevated C&amp;gt;A/G&amp;gt;T errors; 4) target enrichment PCR lead to ~6-fold increase of overall error rate; 5) more than 70% of hotspot variants, such as BRAF V600E, can be detected at 0.1%~0.01% frequency with the current NGS technology by applying in-silico error suppression. Conclusions We present the first comprehensive analysis of error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS accuracy both experimentally and computationally which will lead to enhanced precision for deep sequencing. Citation Format: Xiaotu Ma, Jinghui Zhang. Analysis of error profiles in deep next-generation sequencing data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3538.

Analysis of error profiles in deep next-generation sequencing data

BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10−5 to 10−4, which is 10- to 100-fold lower than generally considered achievable (10−3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10−5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10−4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target-enrichment PCR led to ~ 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1 ~ 0.01% frequency with the current NGS technology by applying in silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

Low-frequency variation in TP53 has large effects on head circumference and intracranial volume

Cranial growth and development is a complex process which affects the closely related traits of head circumference (HC) and intracranial volume (ICV). The underlying genetic influences shaping these traits during the transition from childhood to adulthood are little understood, but might include both age-specific genetic factors and low-frequency genetic variation. Here, we model the developmental genetic architecture of HC, showing this is genetically stable and correlated with genetic determinants of ICV. Investigating up to 46,000 children and adults of European descent, we identify association with final HC and/or final ICV + HC at 9 novel common and low-frequency loci, illustrating that genetic variation from a wide allele frequency spectrum contributes to cranial growth. The largest effects are reported for low-frequency variants within TP53, with 0.5 cm wider heads in increaser-allele carriers versus non-carriers during mid-childhood, suggesting a previously unrecognized role of TP53 transcripts in human cranial development.

The impact of rare and low-frequency genetic variants in oxidized LDL level

The impact of rare and low-frequency genetic variants in oxidized LDL level

Common, low-frequency, and rare genetic variants associated with lipoprotein subclasses and triglyceride measures in Finnish men from the METSIM study.

Lipid and lipoprotein subclasses are associated with metabolic and cardiovascular diseases, yet the genetic contributions to variability in subclass traits are not fully understood. We conducted single-variant and gene-based association tests between 15.1M variants from genome-wide and exome array and imputed genotypes and 72 lipid and lipoprotein traits in 8,372 Finns. After accounting for 885 variants at 157 previously identified lipid loci, we identified five novel signals near established loci at HIF3A, ADAMTS3, PLTP, LCAT, and LIPG. Four of the signals were identified with a low-frequency (0.005<minor allele frequency [MAF]<0.05) or rare (MAF<0.005) variant, including Arg123His in LCAT. Gene-based associations (P<10−10) support a role for coding variants in LIPC and LIPG with lipoprotein subclass traits. 30 established lipid-associated loci had a stronger association for a subclass trait than any conventional trait. These novel association signals provide further insight into the molecular basis of dyslipidemia and the etiology of metabolic disorders.

Low-Frequency Synonymous Coding Variation in CYP2R1 Has Large Effects on Vitamin D Levels and Risk of Multiple Sclerosis

Vitamin D insufficiency is common, correctable, and influenced by genetic factors, and it has been associated with risk of several diseases. We sought to identify low-frequency genetic variants that strongly increase the risk of vitamin D insufficiency and tested their effect on risk of multiple sclerosis, a disease influenced by low vitamin D concentrations. We used whole-genome sequencing data from 2,619 individuals through the UK10K program and deep-imputation data from 39,655 individuals genotyped genome-wide. Meta-analysis of the summary statistics from 19 cohorts identified in CYP2R1 the low-frequency (minor allele frequency = 2.5%) synonymous coding variant g.14900931G>A (p.Asp120Asp) (rs117913124[A]), which conferred a large effect on 25-hydroxyvitamin D (25OHD) levels (-0.43 SD of standardized natural log-transformed 25OHD per A allele; p value = 1.5× 10-88). The effect on 25OHD was four times larger and independent of the effect of a previously described common variant near CYP2R1. By analyzing 8,711 individuals, we showed that heterozygote carriers of this low-frequency variant have an increased risk of vitamin D insufficiency (odds ratio [OR] = 2.2, 95% confidence interval [CI] = 1.78-2.78, p = 1.26× 10-12). Individuals carrying one copy of this variant also had increased odds of multiple sclerosis (OR = 1.4, 95% CI = 1.19-1.64, p = 2.63× 10-5) in a sample of 5,927 case and 5,599 control subjects. Inconclusion, we describe a low-frequency CYP2R1 coding variant that exerts the largest effect upon 25OHD levels identified to date in the general European population and implicates vitamin D in the etiology of multiple sclerosis.

Brief Report: The Role of Rare Protein-Coding Variants in Anti-Tumor Necrosis Factor Treatment Response in Rheumatoid Arthritis.

In many rheumatoid arthritis (RA) patients, disease is controlled with anti-tumor necrosis factor (anti-TNF) biologic therapies. However, in a significant number of patients, the disease fails to respond to anti-TNF therapy. We undertook the present study to examine the hypothesis that rare and low-frequency genetic variants might influence response to anti-TNF treatment. We sequenced the coding region of 750 genes in 1,094 RA patients of European ancestry who were treated with anti-TNF. After quality control, 690 genes were included in the analysis. We applied single-variant association and gene-based association tests to identify variants associated with anti-TNF treatment response. In addition, given the key mechanistic role of TNF, we performed gene set analyses of 27 TNF pathway genes. We identified 14,420 functional variants, of which 6,934 were predicted as nonsynonymous 2,136 of which were further predicted to be "damaging." Despite the fact that the study was well powered, no single variant or gene showed study-wide significant association with change in the outcome measures disease activity or European League Against Rheumatism response. Intriguingly, we observed 3 genes, of 27 with nominal signals of association (P < 0.05), that were involved in the TNF signaling pathway. However, when we performed a rigorous gene set enrichment analysis based on association P value ranking, we observed no evidence of enrichment of association at genes involved in the TNF pathway (Penrichment = 0.15, based on phenotype permutations). Our findings suggest that rare and low-frequency protein-coding variants in TNF signaling pathway genes or other genes do not contribute substantially to anti-TNF treatment response in patients with RA.

A low-frequency variant in SMAD7 modulates TGF-β signaling and confers risk for colorectal cancer in Chinese population.

The TGF-β pathway plays an essential role in regulating cell proliferation and differentiation. GWASs and candidate approaches have identified a battery of genetic variants in the TGF-β pathway contributing to colorectal cancer (CRC). However, most of the significant variants are common variants and their functions remain ambiguous. To identify causal variants with low-frequency in the TGF-β pathway contributing to CRC susceptibility in Chinese population, we performed targeted sequencing of 12 key genes in TGF-β signaling in CRC patients followed by a two-stage case-control study with a total of 5109 cases and 5169 controls. Bioinformatic annotations and biochemical experiments were applied to reveal the potential functions of significant variants. Seven low-frequency genetic variants were captured through targeted sequencing. The two stage association studies showed that missense variant rs3764482 (c. 83C>T; p. S28F) in the gene SMAD7 was consistently and significantly associated with CRC risk. Compared with the wild type, the ORs for variant allele were 1.37 (95%CI: 1.10-1.70, P = 0.005), 1.55 (95%CI: 1.30-1.86, P = 1.15 × 106 ), and 1.48 (1.29-1.70, P = 2.44 × 10;8 ) in stage 1, stage 2, and the combined analyses, respectively. Functional annotations revealed that the minor allele T of rs3764482 was more effective than the major allele C in blocking the TGF-β signaling and inhibiting the phosphorylation of receptor-regulated SMADs (R-SMADs). In conclusion, low-frequency coding variant rs3764482 in SMAD7 is associated with CRC risk in Chinese population. The rs3764482 variant may block the TGF-β signaling via impeding the activation of downstream genes, leading to cancer cell proliferation, thus contributing to CRC pathogenesis.

Exome Array Analysis Identifies Variants in SPOCD1 and BTN3A2 That Affect Risk for Gastric Cancer

Several genetic variants have been associated with gastric cancer risk, although these account for only a fraction of cases of gastric cancer. We aimed to identify low-frequency and other genetic variants that determine gastric cancer susceptibility. We performed exome array analysis of DNA in blood samples from 1113 patients with gastric cancer, collected at hospitals from 2006 to 2010 in China, and 1848 individuals without cancer (controls) undergoing physical examinations. Among 71,290 variants analyzed (including 25,784 common variants), 24 variants were selected and replicated in an analysis of DNA in blood samples from 4687 additional cases of gastric cancer and 5780 controls. We compared expression of candidate genes in tumor vs normal gastric tissues using data from TCGA and performed functional annotation analyses. An immortalized human gastric epithelial cell line (GES1) and 7 human gastric cancer lines were used to express transgenes, knock down gene expression (with small interfering RNAs), disrupt genes (using the CRISPR/Cas9 system), or assess expression of reporter constructs. We measured cell proliferation, colony formation, invasion, and migration, and assessed growth of xenograft tumors in nude mice. A low-frequency missense variant rs112754928 in the SPOC domain containing 1 gene (SPOCD1; encoding p.Arg71Trp), at 1p35.2, was reproducibly associated with reduced risk of gastric cancer (odds ratio, 0.56; P= 3.48× 10-8). SPOCD1 was overexpressed in gastric tumors, and knockout of SPOCD1 reduced gastric cancer cell proliferation, invasive activity, and migration, as well as growth of xenograft tumors in nude mice. We also associated the variant rs1679709 at 6p22.1 with reduced risk for gastric cancer (odds ratio, 0.80; P=1.17× 10-13). The protective allele rs1679709-A correlated with the surrounding haplotype rs2799077-T-rs2799079-C, which reduced the enhancer activity of this site to decrease expression of the butyrophilin subfamily 3 member A2 gene (BTN3A2). BTN3A2 is overexpressed in gastric tumors, and deletion of BTN3A2 inhibited proliferation, migration, and invasion of gastric cancer cells. We have associated variants at 1p35.2 and 6p22.1 with gastric cancer risk, indicating a role for SPOCD1 and BTN3A2 in gastric carcinogenesis.

DNA damage is a pervasive cause of sequencing errors, directly confounding variant identification.

Mutations in somatic cells generate a heterogeneous genomic population and may result in serious medical conditions. Although cancer is typically associated with somatic variations, advances in DNA sequencing indicate that cell-specific variants affect a number of phenotypes and pathologies. Here, we show that mutagenic damage accounts for the majority of the erroneous identification of variants with low to moderate (1 to 5%) frequency. More important, we found signatures of damage in most sequencing data sets in widely used resources, including the 1000 Genomes Project and The Cancer Genome Atlas, establishing damage as a pervasive cause of sequencing errors. The extent of this damage directly confounds the determination of somatic variants in these data sets.

Common, low-frequency, and rare genetic variants associated with lipoprotein subclasses and triglyceride measures in Finnish men from the METSIM study

Common, low-frequency, and rare genetic variants associated with lipoprotein subclasses and triglyceride measures in Finnish men from the METSIM study

Systematic Cell-Based Phenotyping of Missense Alleles.

Sequencing of the protein-coding genome, the exome, has proven powerful to unravel links between genetic variation and disease for both Mendelian and complex conditions. Importantly, however, the increasing number of sequenced human exomes and mapping of disease-associated alleles is accompanied by a simultaneous, yet exponential increase in the overall number of rare and low frequency alleles identified. For most of these novel alleles, biological consequences remain unknown since reliable experimental approaches to better characterize their impact on protein function are only slowly emerging.Here we review a scalable, cell-based strategy that we have recently established to systematically profile the biological impact of rare and low frequency missense variants in vitro. By applying this approach to missense alleles identified through cohort-level exome sequencing in the low-density lipoprotein receptor (LDLR) we are able to distinguish rare alleles that predispose to familial hypercholesterolemia and myocardial infarction from alleles without obvious impact on LDLR levels or functions. We propose that systematic implementation of such and similar strategies will significantly advance our understanding of the protein-coding human genome and how rare and low frequency genetic variation impacts on health and disease.

Large Scale Discoveries of Genes and Polymorphisms Associated with Variation in Hematologic Traits

Hematopoiesis generates mature blood cells from hematopoietic stem cells (HSC) in distinct lineages to release of trillions of mature cells each day into the peripheral blood stream to perform essential functions such as oxygen transport, hemostasis and host defense. The formation and turnover of blood cells are tightly controlled and so the properties of blood cells, including their volume and count, have large heritabilities and are easily influenced by genetic variation. Here we describe the most statistically powerful genome wide association study (GWAS) of blood cell indices to date. We tested associations of 29.5 million polymorphic DNA sequence variants derived using the the Affymetrix axiom array with interpolation of 20 million variants using the UK 10000 genome data with 36 different hematological indices of red cells, white cells and platelets, some of which, such as the reticulocyte count, have been explored for the first time. We discovered significant associations at thousands of associated genetic variants, including hundreds of associations for low frequency genetic variants, thus identifying associations with larger effects on indices than those reported for common variants by previous discovery studies. We have described detailed follow-up studies of the novel associations. Using cell type-specific epigenome and gene expression data generated by the BLUEPRINT project and results from chromatin conformation capture in major blood cell types, we can identify the likely causal variants and their functional impact at a large number of the novel loci. Finally, we have evaluated the contribution of genetic variants to common and complex diseases. In conclusion, we have interrogated phenotypes across the whole hematopoietic tree and increased the number of traits associated with blood cell phenotypes by an order of magnitude. Overall, our results demonstrate widespread and powerful genetic influences on the formation and regulation of the major human blood cell types, identifying many novel genes involved and show the value of genome-wide functional annotation from relevant primary cell populations for interpreting genetic association results. DisclosuresNo relevant conflicts of interest to declare.

Towards the genetic basis of cerebral venous thrombosis—the BEAST Consortium: a study protocol

IntroductionCerebral venous thrombosis (CVT) is a rare cerebrovascular condition accounting for <1% of all stroke cases and mainly affects young adults. Its genetic aetiology is not clearly elucidated.Methods and analysisTo...

Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension.

High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to ~192,000 individuals, and used ~155,063 samples for independent replication. We identified 31 novel blood pressure or hypertension associated genetic regions in the general population, including three rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5mmHg/allele) than common variants. Multiple rare, nonsense and missense variant associations were found in A2ML1 and a low-frequency nonsense variant in ENPEP was identified. Our data extend the spectrum of allelic variation underlying blood pressure traits and hypertension, provide new insights into the pathophysiology of hypertension and indicate new targets for clinical intervention.