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RATIONALE: Genetic studies of Idiopathic Pulmonary Fibrosis (IPF) have improved our understanding of this disease, but not all causal loci have been identified. OBJECTIVE: To identify genes enriched with rare deleterious variants in IPF and familial pulmonary fibrosis. METHODS: We performed gene burden analysis of whole exome data, tested single variants for disease association, conducted KIF15 functional studies, and examined human lung single cell RNA sequencing data. MEASUREMENT AND MAIN RESULTS: Gene burden analysis of 1,725 cases and 23,509 controls identified heterozygous rare deleterious variants in KIF15, a kinesin involved in spindle separation during mitosis, and three telomere-related genes (TERT, RTEL1, PARN). KIF15 was implicated in autosomal dominant models of rare deleterious variants (OR 4.9 [95%CI 2.7, 8.8] P=2.55x10-7) and rare protein-truncating variants (OR 7.6 [3.3, 17.1], P=8.12x10-7). Meta-analysis of the discovery and replication cohorts, including 2,966 cases and 29,817 controls, confirm the involvement of KIF15, plus the three telomere-related genes. A common variant within a KIF15 intron (rs74341405, OR 1.6 [1.4, 1.9], P=5.63x10-10) is associated with IPF risk, confirming a prior report. Lymphoblastoid cells from individuals heterozygous for the common variant have decreased KIF15 and reduced rates of cell growth. Cell proliferation is dependent on KIF15 in the presence of an inhibitor of Eg5/KIF11, which has partially redundant function. KIF15 is expressed specifically in replicating human lung cells, and shows diminished expression in replicating epithelial cells of IPF patients. CONCLUSIONS: Both rare deleterious variants and common variants in KIF15 link a non-telomerase pathway of cell proliferation with IPF susceptibility.

Genome-wide rare variant studies of IPF patients of non-European ancestry have been understudied. Here, we evaluate the enrichment of rare genetic variants of 241 unrelated non-European cases, representing individuals of Latino, African, South Asian, East Asian, and Other Admixed ancestry. Gene burden analysis of deleterious rare (protein-truncating and missense) variants demonstrate an excess of TERT rare damaging variants (OR 67.1, 95% CI [23.1, 195.0], P = 9.4 x 10-14) in non-European subjects. Analysis by ancestry demonstrated an excess of rare, damaging TERT variants in the Latino subgroup (OR 80.9, 95% CI [17.3, 383.8], P = 2.6 x 10-8). Although the non-European group did not show enrichment of PARN, RTEL1, and KIF15 rare deleterious variants, these groups all showed a trend in the same direction as the European ancestry group. For TERT and KIF15, the inclusion of IPF patients of non-European ancestry led to a higher odds ratios and increased evidence in favor of rare deleterious variant contributions, thus demonstrating the increased power of multi-ethnic studies over single-ethnicity studies. To our knowledge, this is the first study that confirms the involvement of rare deleterious TERT variants for IPF patients of Latino and non-European ancestry. To better understand the genetic underpinnings of IPF patients of all ancestries, additional work will be needed to broaden patient recruitment to normalize imbalances.

Schizophrenia has a multifactorial etiology, involving a polygenic architecture. The potential benefit of whole genome sequencing (WGS) in schizophrenia and other psychotic disorders is not well studied. We investigated the yield of clinical WGS analysis in 251 families with a proband diagnosed with schizophrenia (N = 190), schizoaffective disorder (N = 49), or other conditions involving psychosis (N = 48). Participants were recruited in Israel and USA, mainly of Jewish, Arab, and other European ancestries. Trio (parents and proband) WGS was performed for 228 families (90.8%); in the other families, WGS included parents and at least two affected siblings. In the secondary analyses, we evaluated the contribution of rare variant enrichment in particular gene sets, and calculated polygenic risk score (PRS) for schizophrenia. For the primary outcome, diagnostic rate was 6.4%; we found clinically significant, single nucleotide variants (SNVs) or small insertions or deletions (indels) in 14 probands (5.6%), and copy number variants (CNVs) in 2 (0.8%). Significant enrichment of rare loss-of-function variants was observed in a gene set of top schizophrenia candidate genes in affected individuals, compared with population controls (N = 6,840). The PRS for schizophrenia was significantly increased in the affected individuals group, compared to their unaffected relatives. Last, we were also able to provide pharmacogenomics information based on CYP2D6 genotype data for most participants, and determine their antipsychotic metabolizer status. In conclusion, our findings suggest that WGS may have a role in the setting of both research and genetic counseling for individuals with schizophrenia and other psychotic disorders and their families.

Background In the majority of cases, the cause of stillbirth remains unknown despite detailed clinical and laboratory evaluation. Approximately 10 to 20% of stillbirths are attributed to c...

Although often considered a single-entity, chronic kidney disease (CKD) comprises many pathophysiologically distinct disorders that result in persistently abnormal kidney structure and/or function, and encompass both monogenic and polygenic aetiologies. Rare inherited forms of CKD frequently span diverse phenotypes, reflecting genetic phenomena including pleiotropy, incomplete penetrance and variable expressivity. Use of chromosomal microarray and massively parallel sequencing technologies has revealed that genomic disorders and monogenic aetiologies contribute meaningfully to seemingly complex forms of CKD across different clinically defined subgroups and are characterized by high genetic and phenotypic heterogeneity. Investigations of prevalent genomic disorders in CKD have integrated genetic, bioinformatic and functional studies to pinpoint the genetic drivers underlying their renal and extra-renal manifestations, revealing both monogenic and polygenic mechanisms. Similarly, massively parallel sequencing-based analyses have identified gene- and allele-level variation that contribute to the clinically diverse phenotypes observed for many monogenic forms of nephropathy. Genome-wide sequencing studies suggest that dual genetic diagnoses are found in at least 5% of patients in whom a genetic cause of disease is identified, highlighting the fact that complex phenotypes can also arise from multilocus variation. A multifaceted approach that incorporates genetic and phenotypic data from large, diverse cohorts will help to elucidate the complex relationships between genotype and phenotype for different forms of CKD, supporting personalized medicine for individuals with kidney disease.

BackgroundWhole genome sequencing (WGS) can detect variants and estimate telomere length. The clinical utility of WGS in estimating risk, progression and survival of pulmonary fibrosis patients is unknown.MethodsIn this observational cohort study, we performed WGS on 949 patients with idiopathic pulmonary fibrosis or familial pulmonary fibrosis to determine rare and common variant genotypes, estimate telomere length and assess the association of genomic factors with clinical outcomes.ResultsWGS estimates of telomere length correlated with quantitative PCR (R=0.65) and Southern blot (R=0.71) measurements. Rare deleterious qualifying variants were found in 14% of the total cohort, with a five-fold increase in those with a family history of diseaseversusthose without (25%versus5%). Most rare qualifying variants (85%) were found in telomere-related genes and were associated with shorter telomere lengths. Rare qualifying variants had a greater effect on telomere length than a polygenic risk score calculated using 20 common variants previously associated with telomere length. The common variant polygenic risk score predicted telomere length only in sporadic disease. Reduced transplant-free survival was associated with rare qualifying variants, shorter quantitative PCR-measured telomere lengths and absence of theMUC5Bpromoter (rs35705950) single nucleotide polymorphism, but not with WGS-estimated telomere length or the common variant polygenic risk score. Disease progression was associated with both measures of telomere length (quantitative PCR measured and WGS estimated), rare qualifying variants and the common variant polygenic risk score.ConclusionAs a single test, WGS can inform pulmonary fibrosis genetic-mediated risk, evaluate the functional effect of telomere-related variants by estimating telomere length, and prognosticate clinically relevant disease outcomes.

ACTB encodes β‐cytoplasmic actin, an essential component of the cytoskeleton. Based on chromosome 7p22.1 deletions that include the ACTB locus and on rare truncating ACTB variants, a phenotype resulting from ACTB haploinsufficiency was recently proposed. We report putative ACTB loss‐of‐function variants in four patients. To the best of our knowledge, we report the first 7p22.1 microdeletion confined to ACTB and the second ACTB frameshifting mutation that predicts mRNA decay. A de‐novo ACTB p.(Gly302Ala) mutation affects β‐cytoplasmic actin distribution. All four patients share a facial gestalt that is distinct from that of individuals with dominant‐negative ACTB variants in Baraitser‐Winter cerebrofrontofacial syndrome. Two of our patients had strikingly thin and sparse scalp hair. One patient had sagittal craniosynostosis and hypospadias. All three affected male children have attention deficits and mild global developmental delay. Mild intellectual disability was present in only one patient. Heterozygous ACTB deletion can allow for normal psychomotor function., ACTB encodes β‐cytoplasmic actin, an essential component of the cytoskeleton. Based on rare chromosome 7p22.1 deletions that include the ACTB locus and on rare truncating ACTB variants, a phenotype resulting from ACTB haploinsufficiency was recently proposed. We report the first 7p22.1 microdeletion confined to ACTB, and the second ACTB frameshifting mutation that predicts mRNA decay. Mild intellectual disability was present in one patient. Attention deficits and mild global developmental delay were present in three patients. Normal psychomotor function was seen in one patient with a heterozygous ACTB deletion. Heterozygous ACTB deletion can allow for normal psychomotor function.

The first phase of genome-wide association studies (GWAS) assessed the role of common variation in human disease. Advances optimizing and economizing high-throughput sequencing have enabled a second phase of association studies that assess the contribution of rare variation to complex disease in all protein-coding genes. Unlike the early microarray-based studies, sequencing-based studies catalogue the full range of genetic variation, including the evolutionarily youngest forms. Although the experience with common variants helped establish relevant standards for genome-wide studies, the analysis of rare variation introduces several challenges that require novel analysis approaches.

The authors reply: We appreciate the interest of Dr. Zhang and colleagues in our manuscript. The main difference between our publication and that of Zhang et al. (1), was that we assessed all rare predicted loss-of-function variants (pLOFs) meeting the same criteria in cases and controls, which is a well-established paradigm in the field (2). On the other hand, Zhang et al. included specific variants which were experimentally confirmed only in cases, but not controls, precluding a valid case-control comparison.We matched patients as closely as possible to the previous study, and the inclusion of more severe cases (WHO grades 7-10) should only strengthen the signal against population controls. The use of population controls is standard in such settings and has minimal impact on power, because only a small proportion of individuals exposed to SARS-Cov-2 develop severe disease (3). Additionally, for the pLOF model we report adequate power even for an odds ratio of 5.5, which is considerably lower than the one reported by Zhang et al. We tested the same dominant model as Zhang et al., even though LOF variants in these genes have only been reported to cause disease under recessive inheritance (4).We have serious concerns about confounding by ancestry in the analysis by Zhang et al. in which the pLOF carriers were mostly European, but functionally validated missense variants were found in various nationalities from Asia, Europe, Latin America, and the Middle East. Because the rates of pLOFs vary considerably across populations, adjusting for only 3 principal components of ancestry in rare-variant association tests of multi-ethnic cohorts does not provide adequate control for population structure.While we noted that age differences may contribute to the discrepancies between the two studies, Zhang et al. do not discuss the role of age in the interpretation of their results stating: "Inborn errors of TLR3- and IRF7-dependent type I IFN immunity at eight loci were found in as many as 23 patients (3.5%) of various ages (17 to 77 years) and ancestries (various nationalities from Asia, Europe, Latin America, and the Middle East) and in patients of both sexes." We also note that the patients with autoantibodies were not excluded from the primary analysis by Zhang et al., but this was done only in the post-hoc analysis.Most importantly, our negative findings are in full agreement with the recently published independent study of 586,157 individuals, including 20,952 cases of COVID-19 (4,928 hospitalized and 1,304 requiring ventilation or resulting in death) (5). There were no significant associations with any of the 13 candidate genes examined either individually or in aggregate, or when comparisons included all hospitalized cases or only the most severe cases. Indeed, none of the associations displayed even marginal significance. Therefore, consistent with our study, these findings do not support substantial contributions of inborn errors in type I IFN immunity to COVID-19 severity.These negative results underscore the importance of proper study design, selection of appropriate genetic models, adequate control for genetic ancestry, and adherence to unbiased methods for genetic discovery rather than focusing only on a candidate biological pathway.

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,864 COVID-19 cases (713 with severe and 1,151 with mild disease) and 15,033 ancestry-matched population controls across 4 independent COVID-19 biobanks. We tested whether rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only 1 rare pLOF mutation across these genes among 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We found no evidence of association of rare LOF variants in the 13 candidate genes with severe COVID-19 outcomes.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.

Background A common approach for sequencing studies is to do joint-calling and store variants of all samples in a single file. If new samples are continually added or controls are re-used for several studies, the cost and time required to perform joint-calling for each analysis can become prohibitive. Results We present ATAV, an analysis platform for large-scale whole-exome and whole-genome sequencing projects. ATAV stores variant and per site coverage data for all samples in a centralized database, which is efficiently queried by ATAV to support diagnostic analyses for trios and singletons, as well as rare-variant collapsing analyses for finding disease associations in complex diseases. Runtime logs ensure full reproducibility and the modularized ATAV framework makes it extensible to continuous development. Besides helping with the identification of disease-causing variants for a range of diseases, ATAV has also enabled the discovery of disease-genes by rare-variant collapsing on datasets containing more than 20,000 samples. Analyses to date have been performed on data of more than 110,000 individuals demonstrating the scalability of the framework. To allow users to easily access variant-level data directly from the database, we provide a web-based interface, the ATAV data browser (http://atavdb.org/). Through this browser, summary-level data for more than 40,000 samples can be queried by the general public representing a mix of cases and controls of diverse ancestries. Users have access to phenotype categories of variant carriers, as well as predicted ancestry, gender, and quality metrics. In contrast to many other platforms, the data browser is able to show data of newly-added samples in real-time and therefore evolves rapidly as more and more samples are sequenced. Conclusions Through ATAV, users have public access to one of the largest variant databases for patients sequenced at a tertiary care center and can look up any genes or variants of interest. Additionally, since the entire code is freely available on GitHub, ATAV can easily be deployed by other groups that wish to build their own platform, database, and user interface.

Duplex sequencing is currently the most reliable method to identify ultra-low frequency DNA variants by grouping sequence reads derived from the same DNA molecule into families with information on the forward and reverse strand. However, only a small proportion of reads are assembled into duplex consensus sequences, and reads with potentially valuable information are discarded at different steps of the bioinformatics pipeline, especially reads without a family. We developed a bioinformatics tool-set that analyses the tag and family composition with the purpose to understand data loss and implement modifications to maximize the data output for the variant calling. Specifically, our tools show that tags contain PCR and sequencing errors that contribute to data loss and lower DCS yields. Our tools also identified chimeras, which result in unpaired families that do not form DCS. Finally, we also developed a tool called Variant Analyzer that re-examines variant calls from raw reads and provides different summary data that categorizes the confidence level of a variant call by a tier-based system. We demonstrate that this tool identified false positive variants tagged by the tier-based classification. Furthermore, with this tool we can include reads without a family and check the reliability of the call, which increases substantially the sequencing depth for variant calling, a particular important advantage for low-input samples or low-coverage regions.

Summary Both mild and severe epilepsies are influenced by variants in the same genes, yet an explanation for the resulting phenotypic variation is unknown. As part of the ongoing Epi25 Collaboration, we performed a whole-exome sequencing analysis of 13,487 epilepsy-affected individuals and 15,678 control individuals. While prior Epi25 studies focused on gene-based collapsing analyses, we asked how the pattern of variation within genes differs by epilepsy type. Specifically, we compared the genetic architectures of severe developmental and epileptic encephalopathies (DEEs) and two generally less severe epilepsies, genetic generalized epilepsy and non-acquired focal epilepsy (NAFE). Our gene-based rare variant collapsing analysis used geographic ancestry-based clustering that included broader ancestries than previously possible and revealed novel associations. Using the missense intolerance ratio (MTR), we found that variants in DEE-affected individuals are in significantly more intolerant genic sub-regions than those in NAFE-affected individuals. Only previously reported pathogenic variants absent in available genomic datasets showed a significant burden in epilepsy-affected individuals compared with control individuals, and the ultra-rare pathogenic variants associated with DEE were located in more intolerant genic sub-regions than variants associated with non-DEE epilepsies. MTR filtering improved the yield of ultra-rare pathogenic variants in affected individuals compared with control individuals. Finally, analysis of variants in genes without a disease association revealed a significant burden of loss-of-function variants in the genes most intolerant to such variation, indicating additional epilepsy-risk genes yet to be discovered. Taken together, our study suggests that genic and sub-genic intolerance are critical characteristics for interpreting the effects of variation in genes that influence epilepsy.

IntroductionAsthma risk is a complex interplay between genetic susceptibility and environment. Despite many significantly-associated common variants, the contribution of rarer variants with potentially greater effect sizes has not been as extensively studied. We present an exome-based study adopting 24,576 cases and 120,530 controls to assess the contribution of rare protein-coding variants to the risk of early-onset or all-comer asthma.MethodsWe performed case-control analyses on three genetic units: variant-, gene- and pathway-level, using sequence data from the Scandinavian Asthma Genetic Study and UK Biobank participants with asthma. Cases were defined as all-comer asthma (n=24,576) and early-onset asthma (n=5,962). Controls were 120,530 UK Biobank participants without reported history of respiratory illness.ResultsVariant-level analyses identified statistically significant variants at moderate-to-common allele frequency, including protein-truncating variants in FLG and IL33. Asthma risk was significantly increased not only by individual, common FLG protein-truncating variants, but also among the collection of rare-to-private FLG protein-truncating variants (p=6.8×10−7). This signal was driven by early-onset asthma and did not correlate with circulating eosinophil levels. In contrast, a single splice variant in IL33 was significantly protective (p=8.0×10−10), while the collection of remaining IL33 protein-truncating variants showed no class effect (p=0.54). A pathway-based analysis identified that protein-truncating variants in loss-of-function intolerant genes were significantly enriched among individuals with asthma.ConclusionsAccess to the full allele frequency spectrum of protein-coding variants provides additional clarity about the potential mechanisms of action for FLG and IL33. Beyond these two significant drivers, we detected a significant enrichment of protein-truncating variants in loss-of-function intolerant genes.

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,934 COVID-19 cases (713 with severe and 1,221 with mild disease) and 15,251 ancestry-matched population controls across four independent COVID-19 biobanks. We then tested if rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only one rare pLOF mutation across these genes amongst 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We find no evidence of association of rare loss-of-function variants in the proposed 13 candidate genes with severe COVID-19 outcomes.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable athttps://rgc-covid19.regeneron.com.

BackgroundA common approach for sequencing studies is to do joint-calling and store variants of all samples in a single file. If new samples keep being added or controls are re-used for several studies, the cost and time required to perform joint-calling for each analysis can become prohibitive.ResultsWe present ATAV, an analysis platform for large-scale whole-exome and whole-genome sequencing projects. ATAV stores variant and per site coverage data for all samples in a centralized database, which is efficiently queried by ATAV to support diagnostic analyses for trios and singletons, as well as rare-variant collapsing analyses for finding disease associations in complex diseases. Runtime logs ensure full reproducibility and the modularized ATAV framework makes it extensible to continuous development. Besides helping with the identification of disease-causing variants for a range of diseases, ATAV has also enabled the discovery of disease-genes by rare-variant collapsing on datasets containing more than 20,000 samples. Analyses to date have been performed on data of more than 110,000 individuals demonstrating the scalability of the framework.The ATAV data browser (http://atavdb.org/) is a web-based interface that allows users to easily access variant-level data directly from the database. Summary-level data for more than 40,000 samples can be queried by the general public representing a mix of cases and controls of diverse ancestries. Users have access to phenotype categories of variant carriers, as well as predicted ancestry, gender, and quality metrics. In contrast to many other platforms, the data browser is able to show data of newly-added samples in real-time and is therefore evolving rapidly as more and more samples are sequenced.ConclusionsSince all code is freely available on GitHub, ATAV can easily be used by other groups to build up their own platform, database, and user interface. In addition to that users can query one of the largest variant databases for patients sequenced at a tertiary care center and look up their own genes or variants of interest.

There is an urgent need to identify effective therapies for COVID-19. The SARS-CoV-2 host factor protease TMPRSS2 is required for viral entry and thus an attractive target for therapeutic intervention. In mouse, knockout of tmprss2 led to protection against SARS-CoV-1 with no deleterious phenotypes, and in human populations genetic loss of TMPRSS2 does not appear to be selected against. Here, we mined publicly available gene expression data to identify several compounds that down-regulate TMPRSS2. Recognizing the need for immediately available treatment options, we focused on FDA-approved drugs. We found 20 independent studies that implicate estrogenic and androgenic compounds as transcriptional modulators of TMPRSS2, suggesting these classes of drugs may be promising therapeutic candidates for clinical testing and observational studies of COVID-19. We also note that expression of TMPRSS2 is highly variable and skewed in humans, with a minority of individuals having extremely high expression. Combined with literature showing that inhibition of TMPRSS2 protease activity reduces SARS-CoV-2 viral entry in human cells, our results raise the hypothesis that modulation of TMPRSS2 expression is a promising therapeutic avenue for COVID-19.

There is an urgent need to identify effective therapies for COVID-19 given that a broadly available and effective vaccine is likely at least one year away. Here, we identify compounds that transcriptionally inhibit host proteins required for SARS-CoV-2 entry and should be evaluated for efficacy in SARS-CoV-2 viral infection assays. Recognizing the need for immediately available treatment options, we focused particular attention on FDA-approved drugs that could be immediately repurposed to treat COVID-19 patients. By mining publicly available gene expression data, we identify several compounds that down-regulate TMPRSS2, a protein required for SARS-CoV-2 entry that has emerged as a promising therapeutic target. Among these, we find twenty independent studies that implicate estrogen-related and androgen-related compounds as transcriptional modulators of TMPRSS2 expression, suggesting that these drugs and others acting on the pathway may be promising therapeutic candidates for COVID-19 for further testing. It is also noteworthy that TMPRSS2 has highly variable and skewed expression in humans, spanning two orders of magnitude with a small minority of individuals having extremely high expression. Combined with literature showing that TMPRSS2 loss-of-function in mouse is protective against SARS while anti-estrogen treatment predicted to increase TMPRSS2 expression exacerbates SARS, this observation raises the hypothesis that TMPRSS2 expression may positively correlate with severity in COVID-19.

Congenital disorders of glycosylation (CDGs) comprise a large number of inherited metabolic defects that affect the biosynthesis and attachment of glycans. CDGs manifest as a broad spectrum of disease, most often including neurodevelopmental and skeletal abnormalities and skin laxity. Two patients with biallelic CSGALNACT1 variants and a mild skeletal dysplasia have been described previously. We investigated two unrelated patients presenting with short stature with advanced bone age, facial dysmorphism, and mild language delay, in whom trio‐exome sequencing identified novel biallelic CSGALNACT1 variants: compound heterozygosity for c.1294G>T (p.Asp432Tyr) and the deletion of exon 4 that includes the start codon in one patient, and homozygosity for c.791A>G (p.Asn264Ser) in the other patient. CSGALNACT1 encodes CSGalNAcT‐1, a key enzyme in the biosynthesis of sulfated glycosaminoglycans chondroitin and dermatan sulfate. Biochemical studies demonstrated significantly reduced CSGalNAcT‐1 activity of the novel missense variants, as reported previously for the p.Pro384Arg variant. Altered levels of chondroitin, dermatan, and heparan sulfate moieties were observed in patients’ fibroblasts compared to controls. Our data indicate that biallelic loss‐of‐function mutations in CSGALNACT1 disturb glycosaminoglycan synthesis and cause a mild skeletal dysplasia with advanced bone age, CSGALNACT1‐CDG., Congenital disorders of glycosylation (CDGs) comprise a large number of inherited metabolic defects that affect the biosynthesis and attachment of glycans. Four patients with biallelic CSGALNACT1 variants and a mild skeletal dysplasia are now known. Biallelic loss‐of‐function mutations in CSGALNACT1 disturb glycosaminoglycan synthesis and cause a mild skeletal dysplasia with advanced bone age, CSGALNACT1‐CDG

The first phase of genome-wide association studies (GWAS) assessed the role of common variation in human disease. Advances optimizing and economizing high-throughput sequencing have enabled a second phase of association studies that assess the contribution of rare variation to complex disease in all protein-coding genes. Unlike the early microarray-based studies, sequencing-based studies catalogue the full range of genetic variation, including the evolutionarily youngest forms. Although the experience with common variants helped establish relevant standards for genome-wide studies, the analysis of rare variation introduces several challenges that require novel analysis approaches.

Meiosis strongly influences the transmission and evolution of heterozygous poly-A repeats as measured experimentally in a large collection of single recombination products in a human hotspot., Meiotic recombination has strong, but poorly understood effects on short tandem repeat (STR) instability. Here, we screened thousands of single recombinant products with sperm typing to characterize the role of polymorphic poly-A repeats at a human recombination hotspot in terms of hotspot activity and STR evolution. We show that the length asymmetry between heterozygous poly-A’s strongly influences the recombination outcome: a heterology of 10 A’s (9A/19A) reduces the number of crossovers and elevates the frequency of non-crossovers, complex recombination products, and long conversion tracts. Moreover, the length of the heterology also influences the STR transmission during meiotic repair with a strong and significant insertion bias for the short heterology (6A/7A) and a deletion bias for the long heterology (9A/19A). In spite of this opposing insertion-/deletion-biased gene conversion, we find that poly-A’s are enriched at human recombination hotspots that could have important consequences in hotspot activation.

Importance Sequencing studies have identified causal genetic variants for distinct subtypes of heart failure (HF) such as hypertrophic or dilated cardiomyopathy. However, the role of rare, high-impact variants in HF, for which ischemic heart disease is the leading cause, has not been systematically investigated. Objective To assess the contribution of rare variants to all-cause HF with and without reduced left ventricular ejection fraction. Design, setting, and participants This was a retrospective analysis of clinical trials and a prospective epidemiological resource (UK Biobank). Whole-exome sequencing of patients with HF was conducted from the Candesartan in Heart Failure-Assessment of Reduction in Mortality and Morbidity (CHARM) and Controlled Rosuvastatin Multinational Trial in Heart Failure (CORONA) clinical trials. Data were collected from March 1999 to May 2003 for the CHARM studies and September 2003 to July 2007 for the CORONA study. Using a gene-based collapsing approach, the proportion of patients with HF and controls carrying rare and presumed deleterious variants was compared. The burden of pathogenic variants in known cardiomyopathy genes was also investigated to assess the diagnostic yield. Exome sequencing data were generated between January 2018 and October 2018, and analysis began October 2018 and ended April 2020. Main outcomes and measures Odds ratios and P values for genes enriched for rare and presumed deleterious variants in either patients with HF or controls and diagnostic yield of pathogenic variants in known cardiomyopathy genes. Results This study included 5942 patients with HF and 13 156 controls. The mean (SD) age was 68.9 (9.9) years and 4213 (70.9%) were male. A significant enrichment of protein-truncating variants in the TTN gene (P = 3.35 × 10-13; odds ratio, 2.54; 95% CI, 1.96-3.31) that was further increased after restriction to variants in exons constitutively expressed in the heart (odds ratio, 4.52; 95% CI, 3.10-6.68). Validation using UK Biobank data showed a similar enrichment (odds ratio, 4.97; 95% CI, 3.94-6.19 after restriction). In the clinical trials, 201 of 5916 patients with HF (3.4%) had a pathogenic or likely pathogenic cardiomyopathy variant implicating 21 different genes. Notably, 121 of 201 individuals (60.2%) had ischemic heart disease as the clinically identified etiology for the HF. Individuals with HF and preserved ejection fraction had only a slightly lower yield than individuals with midrange or reduced ejection fraction (20 of 767 [2.6%] vs 15 of 392 [3.8%] vs 166 of 4757 [3.5%]). Conclusions and relevance An increased burden of diagnostic mendelian cardiomyopathy variants in a broad group of patients with HF of mostly ischemic etiology compared with controls was observed. This work provides further evidence that mendelian genetic conditions may represent an important subset of complex late-onset diseases such as HF, irrespective of the clinical presentation.

Interbreeding between ancestors of humans and other hominins outside of Africa has been studied intensively, while their common history within Africa still lacks proper attention. However, shedding light on human evolution in this time period about which little is known, is essential for understanding subsequent events outside of Africa. We investigate the genetic relationships of humans, Neandertals, and Denisovans by identifying very short DNA segments in the 1000 Genomes Phase 3 data that these hominins share identical by descent (IBD). By focusing on low frequency and rare variants, we identify very short IBD segments with high confidence. These segments reveal events from a very distant past because shorter IBD segments are presumably older than longer ones. We extracted two types of very old IBD segments that are not only shared among humans, but also with Neandertals and/or Denisovans. The first type contains longer segments that are found primarily in Asians and Europeans where more segments are found in South Asians than in East Asians for both Neandertal and Denisovan. These longer segments indicate complex admixture events outside of Africa. The second type consists of shorter segments that are shared mainly by Africans and therefore may indicate events involving ancestors of humans and other ancient hominins within Africa. Our results from the autosomes are further supported by an analysis of chromosome X, on which segments that are shared by Africans and match the Neandertal and/or Denisovan genome were even more prominent. Our results indicate that interbreeding with other hominins was a common feature of human evolution starting already long before ancestors of modern humans left Africa.

Background Duplex sequencing is the most accurate approach for identification of sequence variants present at very low frequencies. Its power comes from pooling together multiple descendants of both strands of original DNA molecules, which allows distinguishing true nucleotide substitutions from PCR amplification and sequencing artifacts. This strategy comes at a cost—sequencing the same molecule multiple times increases dynamic range but significantly diminishes coverage, making whole genome duplex sequencing prohibitively expensive. Furthermore, every duplex experiment produces a substantial proportion of singleton reads that cannot be used in the analysis and are thrown away. Results In this paper we demonstrate that a significant fraction of these reads contains PCR or sequencing errors within duplex tags. Correction of such errors allows “reuniting” these reads with their respective families increasing the output of the method and making it more cost effective. Conclusions We combine an error correction strategy with a number of algorithmic improvements in a new version of the duplex analysis software, Du Novo 2.0. It is written in Python, C, AWK, and Bash. It is open source and readily available through Galaxy, Bioconda, and Github: https://github.com/galaxyproject/dunovo.

Meiotic recombination has strong, but poorly understood, effects on short tandem repeat (STR) instability. Here, we screened thousands of single recombinant products to characterize the transmission and evolution of polymorphic poly-A repeats at a human recombination hotspot. We show that length asymmetry between heterozygous poly-As plays a key role in the recombination outcome and their transmission. A difference of 10 As (9A/19A) elevates the frequency of non-crossovers, complex recombination products, and long conversion tracts. Moreover, asymmetry also influences STR transmission: the shorter allele is transmitted more frequently (deletion bias) at the asymmetric STR (9A/19A), while the longer allele is favored (insertion bias) at the site with a small STR length difference (6A/7A). Finally, potentially due to this opposing insertion/deletion driven evolution, we find that poly-As are enriched at human recombination hotspots predominantly with short poly-As, possibly influencing open chromatin regions that in turn can activate hotspots.

Background Studies have identified many common genetic associations that influence renal function and all-cause CKD, but these explain only a small fraction of variance in these traits. The contribution of rare variants has not been systematically examined. Methods We performed exome sequencing of 3150 individuals, who collectively encompassed diverse CKD subtypes, and 9563 controls. To detect causal genes and evaluate the contribution of rare variants we used collapsing analysis, in which we compared the proportion of cases and controls carrying rare variants per gene. Results The analyses captured five established monogenic causes of CKD: variants in PKD1 , PKD2 , and COL4A5 achieved study-wide significance, and we observed suggestive case enrichment for COL4A4 and COL4A3 . Beyond known disease-associated genes, collapsing analyses incorporating regional variant intolerance identified suggestive dominant signals in CPT2 and several other candidate genes. Biallelic mutations in CPT2 cause carnitine palmitoyltransferase II deficiency, sometimes associated with rhabdomyolysis and acute renal injury. Genetic modifier analysis among cases with APOL1 risk genotypes identified a suggestive signal in AHDC1 , implicated in Xia–Gibbs syndrome, which involves intellectual disability and other features. On the basis of the observed distribution of rare variants, we estimate that a two- to three-fold larger cohort would provide 80% power to implicate new genes for all-cause CKD. Conclusions This study demonstrates that rare-variant collapsing analyses can validate known genes and identify candidate genes and modifiers for kidney disease. In so doing, these findings provide a motivation for larger-scale investigation of rare-variant risk contributions across major clinical CKD categories.

Motivation Biclustering has become a major tool for analyzing large datasets given as matrix of samples times features and has been successfully applied in life sciences and e-commerce for drug design and recommender systems, respectively. Factor Analysis for Bicluster Acquisition (FABIA), one of the most successful biclustering methods, is a generative model that represents each bicluster by two sparse membership vectors: one for the samples and one for the features. However, FABIA is restricted to about 20 code units because of the high computational complexity of computing the posterior. Furthermore, code units are sometimes insufficiently decorrelated and sample membership is difficult to determine. We propose to use the recently introduced unsupervised Deep Learning approach Rectified Factor Networks (RFNs) to overcome the drawbacks of existing biclustering methods. RFNs efficiently construct very sparse, non-linear, high-dimensional representations of the input via their posterior means. RFN learning is a generalized alternating minimization algorithm based on the posterior regularization method which enforces non-negative and normalized posterior means. Each code unit represents a bicluster, where samples for which the code unit is active belong to the bicluster and features that have activating weights to the code unit belong to the bicluster. Results On 400 benchmark datasets and on three gene expression datasets with known clusters, RFN outperformed 13 other biclustering methods including FABIA. On data of the 1000 Genomes Project, RFN could identify DNA segments which indicate, that interbreeding with other hominins starting already before ancestors of modern humans left Africa. Availability and implementation https://github.com/bioinf-jku/librfn

Targeted next‐generation‐sequencing (NGS) panels have largely replaced Sanger sequencing in clinical diagnostics. They allow for the detection of copy‐number variations (CNVs) in addition to single‐nucleotide variants and small insertions/deletions. However, existing computational CNV detection methods have shortcomings regarding accuracy, quality control (QC), incidental findings, and user‐friendliness. We developed panelcn.MOPS, a novel pipeline for detecting CNVs in targeted NGS panel data. Using data from 180 samples, we compared panelcn.MOPS with five state‐of‐the‐art methods. With panelcn.MOPS leading the field, most methods achieved comparably high accuracy. panelcn.MOPS reliably detected CNVs ranging in size from part of a region of interest (ROI), to whole genes, which may comprise all ROIs investigated in a given sample. The latter is enabled by analyzing reads from all ROIs of the panel, but presenting results exclusively for user‐selected genes, thus avoiding incidental findings. Additionally, panelcn.MOPS offers QC criteria not only for samples, but also for individual ROIs within a sample, which increases the confidence in called CNVs. panelcn.MOPS is freely available both as R package and standalone software with graphical user interface that is easy to use for clinical geneticists without any programming experience. panelcn.MOPS combines high sensitivity and specificity with user‐friendliness rendering it highly suitable for routine clinical diagnostics.