Low-frequency Variants Research Articles

Gene Association Analysis of Quantitative Trait Based on Functional Linear Regression Model with Local Sparse Estimator.

Functional linear regression models have been widely used in the gene association analysis of complex traits. These models retain all the genetic information in the data and take full advantage of spatial information in genetic variation data, which leads to brilliant detection power. However, the significant association signals identified by the high-power methods are not all the real causal SNPs, because it is easy to regard noise information as significant association signals, leading to a false association. In this paper, a method based on the sparse functional data association test (SFDAT) of gene region association analysis is developed based on a functional linear regression model with local sparse estimation. The evaluation indicators CSR and DL are defined to evaluate the feasibility and performance of the proposed method with other indicators. Simulation studies show that: (1) SFDAT performs well under both linkage equilibrium and linkage disequilibrium simulation; (2) SFDAT performs successfully for gene regions (including common variants, low-frequency variants, rare variants and mix variants); (3) With power and type I error rates comparable to OLS and Smooth, SFDAT has a better ability to handle the zero regions. The Oryza sativa data set is analyzed by SFDAT. It is shown that SFDAT can better perform gene association analysis and eliminate the false positive of gene localization. This study showed that SFDAT can lower the interference caused by noise while maintaining high power. SFDAT provides a new method for the association analysis between gene regions and phenotypic quantitative traits.

Word-order variation and coherence in German infinitival complementation

This study provides a synthesis of corpus-based and experimental investigations of word-order preferences in German infinitival complementation. We carried out a systematic analysis of present-day German corpora to establish frequency distributions of different word-order options: extraposition, intraposition, and ‘third construction’. We then examined, firstly, whether and to what extent corpus frequencies and processing economy constraints can predict the acceptability of these three word-order variants, and whether subject raising and subject control verbs form clearly distinguishable subclasses of infinitive-embedding verbs in terms of their word-order behaviour. Secondly, our study looks into the issue of coherence by comparing acceptability ratings for monoclausal coherent and biclausal incoherent construals of intraposed infinitives, and by examining whether a biclausal incoherent analysis gives rise to local and/or global processing difficulty. Taken together, our results revealed that (i) whilst the extraposition pattern consistently wins out over all other word-order variants for control verbs, neither frequency nor processing-based approaches to word-order variation can account for the acceptability of low-frequency variants, (ii) there is considerable verb-specific variation regarding word-order preferences both between and within the two sets of raising and control verbs under investigation, and (iii) although monoclausal coherent intraposition is rated above biclausal incoherent intraposition, the latter is not any more difficult to process than the former. Our findings indicate that frequency of occurrence and processing-related constraints interact with idiosyncratic lexical properties of individual verbs in determining German speakers’ structural preferences.

Interpreting the pervasive observation of U-shaped Site Frequency Spectra.

The standard neutral model of molecular evolution has traditionally been used as the null model for population genomics. We gathered a collection of 45 genome-wide site frequency spectra from a diverse set of species, most of which display an excess of low and high frequency variants compared to the expectation of the standard neutral model, resulting in U-shaped spectra. We show that multiple merger coalescent models often provide a better fit to these observations than the standard Kingman coalescent. Hence, in many circumstances these under-utilized models may serve as the more appropriate reference for genomic analyses. We further discuss the underlying evolutionary processes that may result in the widespread U-shape of frequency spectra.

Identification of Novel Risk Variants of Non-Syndromic Cleft Palate by Targeted Gene Panel Sequencing.

Non-syndromic cleft palate (ns-CP) has a genetically heterogeneous aetiology. Numerous studies have suggested a crucial role of rare coding variants in characterizing the unrevealed component of genetic variation in ns-CP called the "missing heritability". Therefore, this study aimed to detect low-frequency variants that are implicated in ns-CP aetiology in the Polish population. For this purpose, coding regions of 423 genes associated with orofacial cleft anomalies and/or involved with facial development were screened in 38 ns-CP patients using the next-generation sequencing technology. After multistage selection and prioritisation, eight novel and four known rare variants that may influence an individual's risk of ns-CP were identified. Among detected alternations, seven were located in novel candidate genes for ns-CP, including COL17A1 (c.2435-1G>A), DLG1 (c.1586G>C, p.Glu562Asp), NHS (c.568G>C, p.Val190Leu-de novo variant), NOTCH2 (c.1997A>G, p.Tyr666Cys), TBX18 (c.647A>T, p.His225Leu), VAX1 (c.400G>A, p.Ala134Thr) and WNT5B (c.716G>T, p.Arg239Leu). The remaining risk variants were identified within genes previously linked to ns-CP, confirming their contribution to this anomaly. This list included ARHGAP29 (c.1706G>A, p.Arg569Gln), FLNB (c.3605A>G, Tyr1202Cys), IRF6 (224A>G, p.Asp75Gly-de novo variant), LRP6 (c.481C>A, p.Pro161Thr) and TP63 (c.353A>T, p.Asn118Ile). In summary, this study provides further insights into the genetic components contributing to ns-CP aetiology and identifies novel susceptibility genes for this craniofacial anomaly.

Effects of protein-coding variants on blood metabolite measurements and clinical biomarkers in the UK Biobank

Genome-wide association studies (GWASs) have established the contribution of common and low-frequency variants to metabolic blood measurements in the UK Biobank (UKB). To complement existing GWAS findings, we assessed the contribution of rare protein-coding variants in relation to 355 metabolic blood measurements-including 325 predominantly lipid-related nuclear magnetic resonance (NMR)-derived blood metabolite measurements (Nightingale Health Plc) and 30 clinical blood biomarkers-using 412,393 exome sequences from four genetically diverse ancestries in the UKB. Gene-level collapsing analyses were conducted to evaluate a diverse range of rare-variant architectures for the metabolic blood measurements. Altogether, we identified significant associations (p<1×10-8) for 205 distinct genes that involved 1,968 significant relationships for the Nightingale blood metabolite measurements and 331 for the clinical blood biomarkers. These include associations for rare non-synonymous variants in PLIN1 andCREB3L3 with lipid metabolite measurements and SYT7 with creatinine, among others, which may not only provideinsightsinto novel biology but also deepen our understanding of established disease mechanisms. Of the study-wide significant clinical biomarker associations, 40% were not previously detected on analyzing coding variants in a GWAS in the same cohort, reinforcing the importance of studying rare variation to fully understand the genetic architecture of metabolic blood measurements.

Unexpected Findings in Hereditary Breast and Ovarian Cancer Syndrome: Low-Level Constitutional Mosaicism in BRCA2.

Hereditary breast and ovarian cancer syndrome (HBOC) is a clinical entity characterized by an increased risk of developing breast and ovarian cancer. The genetic diagnosis is based on the identification of heterozygous germinal variants in HBOC susceptibility genes. However, it has recently been described that constitutional mosaic variants can contribute to the aetiology of HBOC. In constitutional mosaicism, individuals have at least two genotypically distinct populations of cells that arise from an early post-zygote event. The mutational event occurs early enough in development to affect several tissues. It is detected in germinal genetic studies as low variant allele frequency (VAF) variants (<30%) that are generally overlooked during the prioritization process. Constitutional mosaic variants can affect both somatic and germinal cells, and thus can be passed to the offspring and have important consequences for genetic counselling. In this work, we report the c.9648+1G>A mosaic variant in the BRCA2 gene and propose a diagnostic algorithm to deal with potential mosaic findings identified by Next Generation Sequencing (NGS).

A viewpoint on the genetic determinants of generalised pustular psoriasis.

Generalised pustular psoriasis (GPP) is a rare and severe neutrophilic skin disorder, manifesting with acute episodes of pustulation and systemic upset. The discovery of recessive IL36RN mutations associated with GPP has transformed our understanding of disease drivers, paving the way for the development of targeted anti-IL36 therapeutics. In the light of these remarkable successes, this viewpoint reviews the significance of IL36RN mutations in GPP, their functional impact and their correlation with clinical phenotypes. It then covers the discovery of further genetic determinants (recessive MPO mutations) and risk factors (AP1S3 and CARD14 low-frequency variants) for the disease. It discusses the growing evidence for genetic complexity in GPP and concludes by outlining collaborative strategies that may be adopted to overcome the challenges ahead.

VLF: An R package for the analysis of very low frequency variants in DNA sequences.

Here, we introduce VLF, an R package to determine the distribution of very low frequency variants (VLFs) in nucleotide and amino acid sequences for the analysis of errors in DNA sequence records. The package allows users to assess VLFs in aligned and trimmed protein-coding sequences by automatically calculating the frequency of nucleotides or amino acids in each sequence position and outputting those that occur under a user-specified frequency (default of p = 0.001). These results can then be used to explore fundamental population genetic and phylogeographic patterns, mechanisms and processes at the microevolutionary level, such as nucleotide and amino acid sequence conservation. Our package extends earlier work pertaining to an implementation of VLF analysis in Microsoft Excel, which was found to be both computationally slow and error prone. We compare those results to our own herein. Results between the two implementations are found to be highly consistent for a large DNA barcode dataset of bird species. Differences in results are readily explained by both manual human error and inadequate Linnean taxonomy (specifically, species synonymy). Here, VLF is also applied to a subset of avian barcodes to assess the extent of biological artifacts at the species level for Canada goose (Branta canadensis), as well as within a large dataset of DNA barcodes for fishes of forensic and regulatory importance. The novelty of VLF and its benefit over the previous implementation include its high level of automation, speed, scalability and ease-of-use, each desirable characteristics which will be extremely valuable as more sequence data are rapidly accumulated in popular reference databases, such as BOLD and GenBank.

Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry

BackgroundLow-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes.MethodsWe evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes’ coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.ResultsIn European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 × 10−6) and AC058822.1 (P = 1.47 × 10−4), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C.ConclusionsUsing extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 × 10−5), demonstrating the importance of diversifying study cohorts.

FinnGen provides genetic insights from a well-phenotyped isolated population

Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10–11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.

Genome-wide association study of varicose veins identifies a protective missense variant in GJD3 enriched in the Finnish population

Varicose veins is the most common manifestation of chronic venous disease that displays female-biased incidence. To identify protein-inactivating variants that could guide identification of drug target genes for varicose veins and genetic evidence for the disease prevalence difference between the sexes, we conducted a genome-wide association study of varicose veins in Finns using the FinnGen dataset with 17,027 cases and 190,028 controls. We identified 50 associated genetic loci (P < 5.0 × 10−8) of which 29 were novel including one near ERG with female-specificity (rs2836405-G, OR[95% CI] = 1.09[1.05–1.13], P = 3.1 × 10−8). These also include two X-chromosomal (ARHGAP6 and SRPX) and two autosomal novel loci (TGFB2 and GJD3) with protein-coding lead variants enriched above 56-fold in Finns over non-Finnish non-Estonian Europeans. A low-frequency missense variant in GJD3 (p.Pro59Thr) is exclusively associated with a lower risk for varicose veins (OR = 0.62 [0.55–0.70], P = 1.0 × 10−14) in a phenome-wide scan of the FinnGen data. The absence of observed pleiotropy and its membership of the connexin gene family underlines GJD3 as a potential connexin-modulating therapeutic strategy for varicose veins. Our results provide insights into varicose veins etiopathology and highlight the power of isolated populations, including Finns, to discover genetic variants that inform therapeutic development.

Challenges in Harnessing Shared Within-Host Severe Acute Respiratory Syndrome Coronavirus 2 Variation for Transmission Inference.

The limited variation observed among severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) consensus sequences makes it difficult to reconstruct transmission linkages in outbreak settings. Previous studies have recovered variation within individual SARS-CoV-2 infections but have not yet measured the informativeness of within-host variation for transmission inference. We performed tiled amplicon sequencing on 307 SARS-CoV-2 samples, including 130 samples from 32 individuals in 14 households and 47 longitudinally sampled individuals, from 4 prospective studies with household membership data, a proxy for transmission linkage. Consensus sequences from households had limited diversity (mean pairwise distance, 3.06 single-nucleotide polymorphisms [SNPs]; range, 0-40). Most (83.1%, 255 of 307) samples harbored at least 1 intrahost single-nucleotide variant ([iSNV] median, 117; interquartile range [IQR], 17-208), above a minor allele frequency threshold of 0.2%. Pairs in the same household shared significantly more iSNVs (mean, 1.20 iSNVs; 95% confidence interval [CI], 1.02-1.39) than did pairs in different households infected with the same viral clade (mean, 0.31 iSNVs; 95% CI, .28-.34), a signal that decreases with increasingly stringent minor allele frequency thresholds. The number of shared iSNVs was significantly associated with an increased odds of household membership (adjusted odds ratio, 1.35; 95% CI, 1.23-1.49). However, the poor concordance of iSNVs detected across sequencing replicates (24.8% and 35.0% above a 0.2% and 1% threshold) confirms technical concerns that current sequencing and bioinformatic workflows do not consistently recover low-frequency within-host variants. Shared within-host variation may augment the information in consensus sequences for predicting transmission linkages. Improving sensitivity and specificity of within-host variant identification will improve the informativeness of within-host variation.

Abstract C041: FAN1 splice variant as a possible risk variant for African American hereditary breast cancer and understanding its role in tumorigenesis

Abstract Recognizing African American health and research disparities, there is a need to better understand African American breast cancer risk. Our group has established the Alabama Hereditary Cancer Cohort to aid in identifying risk variants associated with African American hereditary breast cancer. We have identified several suspected risk variants using next-generation sequencing technologies, including a low-frequency African American-specific splicing variant in FANCD2/FANCI-associated nuclease 1 (FAN1). FAN1 is an exo/endonuclease involved in DNA inter-strand crosslinking repair. There has been speculation that FAN1 could be a breast cancer susceptibility gene because FAN1 is in the Fanconi Anemia pathway with known breast cancer susceptibility genes, BRCA1 and BRCA2. This splicing variant, FAN1 c.3057+1G&amp;gt;A, does not interfere with the coded protein, but alters the donor splice site of exon 14, adding 34 bases to the beginning of the 3’ untranslated region. Interestingly, it has an allele frequency of 3.6% in the general African American population but was found in 5.1% of African American breast cancer cases in the Alabama Hereditary Cancer Cohort. Extremely rare in European Americans overall; it was not detected in any European American breast cancer cases. Functionalizing FAN1 c.3057+1G&amp;gt;A and other identified mutations is important to demonstrate pathogenicity. Our group uses prime editing to introduce variants of interest into selected cell lines. Prime editing is an innovative gene-editing technique that can introduce base substitutions, insertions, and deletions into the genome without the need for double-stranded DNA breaks or donor DNA. Upon gene-editing, cell proliferation, invasion, migration, and other cellular characteristics that contribute to tumorigenesis are investigated. Overall, it is imperative to identify African-American breast cancer risk variants and understand how they play a role in disease pathogenesis, leading to better risk assessment and novel therapeutics. Citation Format: Sheniqua R. Glover, Cierla McGuire Sams, Madison Bishop, Troy LoBue, Issac Mcneely, Nancy D. Merner. FAN1 splice variant as a possible risk variant for African American hereditary breast cancer and understanding its role in tumorigenesis [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C041.

Nuclease Enrichment and qPCR Detection of Rare Nucleotide Variants.

The emergence of circulating DNA analysis in blood during the past decade has responded to the need for noninvasive alternatives to classical tissue biopsies. This has coincided with the development of techniques that allow the detection of low-frequency allele variants in clinical samples that typically carry very low amounts of fragmented DNA, such as plasma or FFPE samples. Enrichment of rare variants by nuclease-assisted mutant allele enrichment with overlapping probes (NaME-PrO) enables a more sensitive detection of mutations in tissue biopsy samples alongside standard qPCR detection assays. Such sensitivity is normally achieved by other more complex PCR methods, such as TaqMan qPCR and digital droplet PCR (ddPCR). Here we describe a workflow of mutation-specific nuclease-based enrichment combined with a SYBR Green real-time quantitative PCR detection method that provides comparable results to ddPCR. Using a PIK3CA mutation as an example, this combined workflow enables detection and accurate prediction of initial variant allele fraction in samples with a low mutant allele frequency (<1%) and could be applied flexibly to detect other mutations of interest.

A comparison between similarity matrices for principal component analysis to assess population stratification in sequenced genetic data sets.

Genetic similarity matrices are commonly used to assess population substructure (PS) in genetic studies. Through simulation studies and by the application to whole-genome sequencing (WGS) data, we evaluate the performance of three genetic similarity matrices: the unweighted and weighted Jaccard similarity matrices and the genetic relationship matrix. We describe different scenarios that can create numerical pitfalls and lead to incorrect conclusions in some instances. We consider scenarios in which PS is assessed based on loci that are located across the genome ('globally') and based on loci from a specific genomic region ('locally'). We also compare scenarios in which PS is evaluated based on loci from different minor allele frequency bins: common (>5%), low-frequency (5-0.5%) and rare (<0.5%) single-nucleotide variations (SNVs). Overall, we observe that all approaches provide the best clustering performance when computed based on rare SNVs. The performance of the similarity matrices is very similar for common and low-frequency variants, but for rare variants, the unweighted Jaccard matrix provides preferable clustering features. Based on visual inspection and in terms of standard clustering metrics, its clusters are the densest and the best separated in the principal component analysis of variants with rare SNVs compared with the other methods and different allele frequency cutoffs. In an application, we assessed the role of rare variants on local and global PS, using WGS data from multiethnic Alzheimer's disease data sets and European or East Asian populations from the 1000 Genome Project.

Highly sensitive liquid biopsy Duplex sequencing complements tissue biopsy to enhance detection of clinically relevant genetic variants.

Liquid biopsy (LB) is a promising complement to tissue biopsy for detection of clinically relevant genetic variants in cancer and mosaic diseases. A combined workflow to enable parallel tissue and LB analysis is required to maximize diagnostic yield for patients. We developed and validated a cost-efficient combined next-generation sequencing (NGS) workflow for both tissue and LB samples, and applied Duplex sequencing technology for highly accurate detection of low frequency variants in plasma. Clinically relevant cutoffs for variant reporting and quantification were established. We investigated assay performance characteristics for very low amounts of clinically relevant variants. In plasma, the assay achieved 100% sensitivity and 92.3% positive predictive value (PPV) for single nucleotide variants (SNVs) and 91.7% sensitivity and 100% PPV for insertions and deletions (InDel) in clinically relevant hotspots with 0.5-5% variant allele frequencies (VAFs). We further established a cutoff for reporting variants (i.e. Limit of Blank, LOB) at 0.25% VAF and a cutoff for quantification (i.e. Limit of Quantification, LOQ) at 5% VAF in plasma for accurate clinical interpretation of analysis results. With our LB approach, we were able to identify the molecular cause of a clinically confirmed asymmetric overgrowth syndrome in a 10-year old child that would have remained undetected with tissue analysis as well as other molecular diagnostic approaches. Our flexible and cost-efficient workflow allows analysis of both tissue and LB samples and provides clinically relevant cutoffs for variant reporting and precise quantification. Complementing tissue analysis by LB is likely to increase diagnostic yield for patients with molecular diseases.

Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials

In the treatment of type 2 diabetes, GLP-1 receptor agonists lower blood glucose concentrations, body weight, and have cardiovascular benefits. The efficacy and side effects of GLP-1 receptor agonists vary between people. Human pharmacogenomic studies of this inter-individual variation can provide both biological insight into drug action and provide biomarkers to inform clinical decision making. We therefore aimed to identify genetic variants associated with glycaemic response to GLP-1 receptor agonist treatment. In this genome-wide analysis we included adults (aged ≥18 years) with type 2 diabetes treated with GLP-1 receptor agonists with baseline HbA1c of 7% or more (53 mmol/mol) from four prospective observational cohorts (DIRECT, PRIBA, PROMASTER, and GoDARTS) and two randomised clinical trials (HARMONY phase 3 and AWARD). The primary endpoint was HbA1c reduction at 6 months after starting GLP-1 receptor agonists. We evaluated variants in GLP1R, then did a genome-wide association study and gene-based burden tests. 4571 adults were included in our analysis, of these, 3339 (73%) were White European, 449 (10%) Hispanic, 312 (7%) American Indian or Alaskan Native, and 471 (10%) were other, and around 2140 (47%) of the participants were women. Variation in HbA1c reduction with GLP-1 receptor agonists treatment was associated with rs6923761G→A (Gly168Ser) in the GLP1R (0·08% [95% CI 0·04-0·12] or 0·9 mmol/mol lower reduction in HbA1c per serine, p=6·0 × 10-5) and low frequency variants in ARRB1 (optimal sequence kernel association test p=6·7 × 10-8), largely driven by rs140226575G→A (Thr370Met; 0·25% [SE 0·06] or 2·7 mmol/mol [SE 0·7] greater HbA1c reduction per methionine, p=5·2 × 10-6). A similar effect size for the ARRB1 Thr370Met was seen in Hispanic and American Indian or Alaska Native populations who have a higher frequency of this variant (6-11%) than in White European populations. Combining these two genes identified 4% of the population who had a 30% greater reduction in HbA1c than the 9% of the population with the worse response. This genome-wide pharmacogenomic study of GLP-1 receptor agonists provides novel biological and clinical insights. Clinically, when genotype is routinely available at the point of prescribing, individuals with ARRB1 variants might benefit from earlier initiation of GLP-1 receptor agonists. Innovative Medicines Initiative and the Wellcome Trust.

Multiple Mutations Associated with Emergent Variants Can Be Detected as Low-Frequency Mutations in Early SARS-CoV-2 Pandemic Clinical Samples.

Genetic analysis of intra-host viral populations provides unique insight into pre-emergent mutations that may contribute to the genotype of future variants. Clinical samples positive for SARS-CoV-2 collected in California during the first months of the pandemic were sequenced to define the dynamics of mutation emergence as the virus became established in the state. Deep sequencing of 90 nasopharyngeal samples showed that many mutations associated with the establishment of SARS-CoV-2 globally were present at varying frequencies in a majority of the samples, even those collected as the virus was first detected in the US. A subset of mutations that emerged months later in consensus sequences were detected as subconsensus members of intra-host populations. Spike mutations P681H, H655Y, and V1104L were detected prior to emergence in variant genotypes, mutations were detected at multiple positions within the furin cleavage site, and pre-emergent mutations were identified in the nucleocapsid and the envelope genes. Because many of the samples had a very high depth of coverage, a bioinformatics pipeline, "Mappgene", was established that uses both iVar and LoFreq variant calling to enable identification of very low-frequency variants. This enabled detection of a spike protein deletion present in many samples at low frequency and associated with a variant of concern.

Integrated genomic analysis identifies novel low-frequency cis-regulatory variant rs2279658 associated with VSD risk in Chinese children.

VSD combined with other cardiac or extracardiac malformations (defined as "complex VSD" by us) is one of the major causes of perinatal morbidity and mortality. Functional non-coding SNPs (cis-regulatory SNPs) have not been systematically studied in CHDs, including complex VSD. Here we report an exome-wide association analysis using WES data of 60 PA/VSD cases, 20 TOF cases and 100 controls in Chinese children. We identify 93 low-frequency non-coding SNPs associated with complex VSD risk. A functional genomics pipeline integrating ATAC-seq, ChIP-seq and promoter CHi-C recognizes the rs2279658 variant as a candidate cis-regulatory SNP. Specifically, rs2279658 resides in a cardiac-specific enhancer bound by FOXH1 and PITX2, and would abrogate binding of these two transcription factors to the identified enhancer during cardiac morphogenesis. COQ2 and FAM175A are predicted to be target genes for "rs2279658-FOXH1 or PITX2" pairs in the heart. These findings highlight the importance of cis-regulatory SNPs in the pathogenesis of complex VSD and broaden our understanding of this disease.

Whole genome sequence association analysis of Brain MRI measures

AbstractBackgroundGenome‐wide association studies (GWAS) of brain volumes have identified common genetic variants with modest effect sizes that lie mainly in non‐coding regions. We sought to identify low frequency and rare variants influencing brain volumes by performing association analyses using whole‐genome sequence data from the Trans‐Omics for Precision Medicine (TOPMed) Program.MethodWe analyzed up to 7,607 participants (57% women; 62% European ancestry, 21% African‐Americans, 15% Hispanic/Latino, 2% Chinese‐American), mean age of 60.5 (16.2), from eight TOPMed population‐ or family‐based studies (FHS, GENESTAR, CHS, GENOA, ARIC, CARDIA, MESA, and SAFS). We excluded participants with dementia, stroke, presence of large brain infarcts, tumor or low‐quality scans. We tested the association of hippocampal (HV), total brain (TBV), lateral ventricular (LVV) and intracranial (ICV) volumes to individual genetic variants with minor allele counts ≥ 15 using mixed‐effect linear regression models adjusted for age, age2, sex, study and the first 10 principal components. Models for HV, TBV and log(LVV) were adjusted for ICV. We accounted for relatedness using an empirical kinship matrix and trait variance variability by using a random effect for study.ResultWe detected one novel region with low frequency variants associated with HV (13q14, P = 5.8×10−9). The top 13q14 variant for HV (rs115674829) minor allele frequency (MAF) was 2% in our pooled sample but was more common in the pan‐African 1000 Genomes population (MAF = 14%). This variant lies in LINC00598 at 237kb from FOXO1, a member of the forkhead family of transcription factors that has been linked to Alzheimer’s Disease. Additionally, we detected new suggestive associations (P≤10−7) for TBV (16p11) and LVV (1q25, 2q22, 3q13, 5q14, and 10q23), including common variants. Finally, we confirmed the association of common variants in GWAS loci for all traits.ConclusionOur whole genome sequence analyses revealed intriguing new loci of low‐frequency and common variants, and replicated loci previously associated with brain volumes. Future work will include ancestry‐specific and conditional analyses, as well as gene‐based and scan tests.Supported by: AG058589, AG052409, AG054076, NO1‐HC‐25195, HHSN268201500001I and 75N92019D00031, R01HL131136, P30 AG066546, and K99AG066849.