Human Genetics最新文献

{"title":"Characterization of a novel HDAC2 pathogenetic variant: a missing puzzle piece for chromatinopathies.","authors":"Elisabetta Di Fede, Antonella Lettieri, Esi Taci, Silvia Castiglioni, Stefano Rebellato, Chiara Parodi, Elisa Adele Colombo, Paolo Grazioli, Federica Natacci, Paola Marchisio, Lidia Pezzani, Grazia Fazio, Donatella Milani, Valentina Massa, Cristina Gervasini","doi":"10.1007/s00439-024-02675-0","DOIUrl":"10.1007/s00439-024-02675-0","url":null,"abstract":"<p><p>Histone deacetylases (HDACs) are enzymes pivotal for histone modification (i.e. acetylation marks removal), chromatin accessibility and gene expression regulation. Class I HDACs (including HDAC1, 2, 3, 8) are ubiquitously expressed and they often participate in multi-molecular protein complexes. To date, three neurodevelopmental disorders caused by mutations in genes encoding for HDACs (HDAC4, HDAC6 and HDAC8) and thus belonging to the group of chromatinopathies, have been described. We performed whole exome sequencing (WES) for a patient (#249) clinically diagnosed with the chromatinopathy Rubinstein-Taybi syndrome (RSTS) but negative for mutations in RSTS genes, identifying a de novo frameshift variant in HDAC2 gene. We then investigated its molecular effects in lymphoblastoid cell lines (LCLs) derived from the patient compared to LCLs from healthy donors (HD). As the variant was predicted to be likely pathogenetic and to affect the sequence of nuclear localization signal, we performed immunocytochemistry and lysates fractionation, observing a nuclear mis-localization of HDAC2 compared to HD LCLs. In addition, HDAC2 total protein abundance resulted altered in patient, and we found that newly identified variant in HDAC2 affects also acetylation levels, with significant difference in acetylation pattern among patient #249, HD and RSTS cells and in expression of a known molecular target. Remarkably, RNA-seq performed on #249, HD and RSTS cells shows differentially expressed genes (DEGs) common to #249 and RSTS. Interestingly, our reported patient was clinically diagnosed with RSTS, a chromatinopathy which known causative genes encode for enzymes antagonizing HDACs. These results support the role of HDAC2 as causative gene for chromatinopathies, strengthening the genotype-phenotype correlations in this relevant group of disorders.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11186948/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140944837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"STRAS:a snakemake pipeline for genome-wide short tandem repeats annotation and score.","authors":"Mengna Zhang","doi":"10.1007/s00439-024-02662-5","DOIUrl":"10.1007/s00439-024-02662-5","url":null,"abstract":"<p><p>High-throughput whole genome sequencing (WGS) is clinically used in finding single nucleotide variants and small indels. Several bioinformatics tools are developed to call short tandem repeats (STRs) copy numbers from WGS data, such as ExpansionHunter denovo, GangSTR and HipSTR. However, expansion disorders are rare and it is hard to find candidate expansions in single patient sequencing data with ~ 800,000 STRs calls. In this paper I describe a snakemake pipeline for genome-wide STRs Annotation and Score (STRAS) using a Random Forest (RF) model to predict pathogenicity. The predictor was validated by benchmark data from Clinvar and PUBMED. True positive rate was 93.8%. True negative rate was 98.0%.Precision was 98.6% and recall rate was 93.8%. F1-score was 0.961. Sensitivity was 93.8% and specificity was 99.6%. These results showed STRAS could be a useful tool for clinical researchers to find STR loci of interest and filter out neutral STRs. STRAS is freely available at https://github.com/fancheyu5/STRAS .</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140174494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in long-read single-cell transcriptomics.","authors":"Pallawi Kumari, Manmeet Kaur, Kiran Dindhoria, Bruce Ashford, Shanika L Amarasinghe, Amarinder Singh Thind","doi":"10.1007/s00439-024-02678-x","DOIUrl":"https://doi.org/10.1007/s00439-024-02678-x","url":null,"abstract":"<p><p>Long-read single-cell transcriptomics (scRNA-Seq) is revolutionizing the way we profile heterogeneity in disease. Traditional short-read scRNA-Seq methods are limited in their ability to provide complete transcript coverage, resolve isoforms, and identify novel transcripts. The scRNA-Seq protocols developed for long-read sequencing platforms overcome these limitations by enabling the characterization of full-length transcripts. Long-read scRNA-Seq techniques initially suffered from comparatively poor accuracy compared to short read scRNA-Seq. However, with improvements in accuracy, accessibility, and cost efficiency, long-reads are gaining popularity in the field of scRNA-Seq. This review details the advances in long-read scRNA-Seq, with an emphasis on library preparation protocols and downstream bioinformatics analysis tools.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141086302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cross-ancestry genetic architecture and prediction for cholesterol traits.","authors":"Md Moksedul Momin, Xuan Zhou, Elina Hyppönen, Beben Benyamin, S Hong Lee","doi":"10.1007/s00439-024-02660-7","DOIUrl":"10.1007/s00439-024-02660-7","url":null,"abstract":"<p><p>While cholesterol is essential, a high level of cholesterol is associated with the risk of cardiovascular diseases. Genome-wide association studies (GWASs) have proven successful in identifying genetic variants that are linked to cholesterol levels, predominantly in white European populations. However, the extent to which genetic effects on cholesterol vary across different ancestries remains largely unexplored. Here, we estimate cross-ancestry genetic correlation to address questions on how genetic effects are shared across ancestries. We find significant genetic heterogeneity between ancestries for cholesterol traits. Furthermore, we demonstrate that single nucleotide polymorphisms (SNPs) with concordant effects across ancestries for cholesterol are more frequently found in regulatory regions compared to other genomic regions. Indeed, the positive genetic covariance between ancestries is mostly driven by the effects of the concordant SNPs, whereas the genetic heterogeneity is attributed to the discordant SNPs. We also show that the predictive ability of the concordant SNPs is significantly higher than the discordant SNPs in the cross-ancestry polygenic prediction. The list of concordant SNPs for cholesterol is available in GWAS Catalog. These findings have relevance for the understanding of shared genetic architecture across ancestries, contributing to the development of clinical strategies for polygenic prediction of cholesterol in cross-ancestral settings.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140305485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semiautomated approach focused on new genomic information results in time and effort-efficient reannotation of negative exome data.","authors":"Alejandro Ferrer, Patrick Duffy, Rory J Olson, Michael A Meiners, Laura Schultz-Rogers, Erica L Macke, Stephanie Safgren, Joel A Morales-Rosado, Margot A Cousin, Gavin R Oliver, David Rider, Megan Williams, Pavel N Pichurin, David R Deyle, Eva Morava, Ralitza H Gavrilova, Radhika Dhamija, Klass J Wierenga, Brendan C Lanpher, Dusica Babovic-Vuksanovic, Charu Kaiwar, Carolyn R Vitek, Tammy M McAllister, Myra J Wick, Lisa A Schimmenti, Konstantinos N Lazaridis, Filippo Pinto E Vairo, Eric W Klee","doi":"10.1007/s00439-024-02664-3","DOIUrl":"10.1007/s00439-024-02664-3","url":null,"abstract":"<p><p>Most rare disease patients (75-50%) undergoing genomic sequencing remain unsolved, often due to lack of information about variants identified. Data review over time can leverage novel information regarding disease-causing variants and genes, increasing this diagnostic yield. However, time and resource constraints have limited reanalysis of genetic data in clinical laboratories setting. We developed RENEW, (REannotation of NEgative WES/WGS) an automated reannotation procedure that uses relevant new information in on-line genomic databases to enable rapid review of genomic findings. We tested RENEW in an unselected cohort of 1066 undiagnosed cases with a broad spectrum of phenotypes from the Mayo Clinic Center for Individualized Medicine using new information in ClinVar, HGMD and OMIM between the date of previous analysis/testing and April of 2022. 5741 variants prioritized by RENEW were rapidly reviewed by variant interpretation specialists. Mean analysis time was approximately 20 s per variant (32 h total time). Reviewed cases were classified as: 879 (93.0%) undiagnosed, 63 (6.6%) putatively diagnosed, and 4 (0.4%) definitively diagnosed. New strategies are needed to enable efficient review of genomic findings in unsolved cases. We report on a fast and practical approach to address this need and improve overall diagnostic success in patient testing through a recurrent reannotation process.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140305486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The natural history and genotype–phenotype correlations of TMPRSS3 hearing loss: an international, multi-center, cohort analysis","authors":"Brett M. Colbert, Cris Lanting, Molly Smeal, Susan Blanton, Derek M. Dykxhoorn, Pei-Ciao Tang, Richard L. Getchell, Hedwig Velde, Mirthe Fehrmann, Ryan Thorpe, Prem Chapagain, Heidy Elkhaligy, Hannie Kremer, Helger Yntema, Lonneke Haer-Wigman, Shelby Redfield, Tieqi Sun, Saskia Bruijn, Astrid Plomp, Thadé Goderie, Jiddeke van de Kamp, Rolien H. Free, Jolien Klein Wassink-Ruiter, Josine Widdershoven, Els Vanhoutte, Liselotte Rotteveel, Marjolein Kriek, Marieke van Dooren, Lies Hoefsloot, Heriette H. W. de Gier, Amanda Schaefer, Diana Kolbe, Hela Azaiez, Grace Rabie, Armal Aburayyan, Mariana Kawas, Moien Kanaan, Jourdan Holder, Shin-ichi Usami, Zhengyi Chen, Pu Dai, Jeffrey Holt, Rick Nelson, Byung Yoon Choi, Eliot Shearer, Richard J. H. Smith, Ronald Pennings, Xue Zhong Liu","doi":"10.1007/s00439-024-02648-3","DOIUrl":"https://doi.org/10.1007/s00439-024-02648-3","url":null,"abstract":"<p><i>TMPRSS3</i>-related hearing loss presents challenges in correlating genotypic variants with clinical phenotypes due to the small sample sizes of previous studies. We conducted a cross-sectional genomics study coupled with retrospective clinical phenotype analysis on 127 individuals. These individuals were from 16 academic medical centers across 6 countries. Key findings revealed 47 unique <i>TMPRSS3</i> variants with significant differences in hearing thresholds between those with missense variants versus those with loss-of-function genotypes. The hearing loss progression rate for the DFNB8 subtype was 0.3 dB/year. Post-cochlear implantation, an average word recognition score of 76% was observed. Of the 51 individuals with two missense variants, 10 had DFNB10 with profound hearing loss. These 10 all had at least one of 4 TMPRSS3 variants predicted by computational modeling to be damaging to TMPRSS3 structure and function. To our knowledge, this is the largest study of TMPRSS3 genotype–phenotype correlations. We find significant differences in hearing thresholds, hearing loss progression, and age of presentation, by TMPRSS3 genotype and protein domain affected. Most individuals with TMPRSS3 variants perform well on speech recognition tests after cochlear implant, however increased age at implant is associated with worse outcomes. These findings provide insight for genetic counseling and the on-going design of novel therapeutic approaches.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140834410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel network-based method identifies a cuproplasia-related pan-cancer gene signature to predict patient outcome","authors":"Vu Viet Hoang Pham, Toni Rose Jue, Jessica Lilian Bell, Fabio Luciani, Filip Michniewicz, Giuseppe Cirillo, Linda Vahdat, Chelsea Mayoh, Orazio Vittorio","doi":"10.1007/s00439-024-02673-2","DOIUrl":"https://doi.org/10.1007/s00439-024-02673-2","url":null,"abstract":"<p>Copper is a vital micronutrient involved in many biological processes and is an essential component of tumour cell growth and migration. Copper influences tumour growth through a process called cuproplasia, defined as abnormal copper-dependent cell-growth and proliferation. Copper-chelation therapy targeting this process has demonstrated efficacy in several clinical trials against cancer. While the molecular pathways associated with cuproplasia are partially known, genetic heterogeneity across different cancer types has limited the understanding of how cuproplasia impacts patient survival. Utilising RNA-sequencing data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets, we generated gene regulatory networks to identify the critical cuproplasia-related genes across 23 different cancer types. From this, we identified a novel 8-gene cuproplasia-related gene signature associated with pan-cancer survival, and a 6-gene prognostic risk score model in low grade glioma. These findings highlight the use of gene regulatory networks to identify cuproplasia-related gene signatures that could be used to generate risk score models. This can potentially identify patients who could benefit from copper-chelation therapy and identifies novel targeted therapeutic strategies.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140629680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Examination of the shared genetic architecture between multiple sclerosis and systemic lupus erythematosus facilitates discovery of novel lupus risk loci","authors":"Sophia Kerns, Katherine A. Owen, Dana Schwalbe, Amrie C. Grammer, Peter E. Lipsky","doi":"10.1007/s00439-024-02672-3","DOIUrl":"https://doi.org/10.1007/s00439-024-02672-3","url":null,"abstract":"<p>Systemic Lupus Erythematosus (SLE) is an autoimmune disease with heterogeneous manifestations, including neurological and psychiatric symptoms. Genetic association studies in SLE have been hampered by insufficient sample size and limited power compared to many other diseases. Multiple Sclerosis (MS) is a chronic relapsing autoimmune disease of the central nervous system (CNS) that also manifests neurological and immunological features. Here, we identify a method of leveraging large-scale genome wide association studies (GWAS) in MS to identify novel genetic risk loci in SLE. Statistical genetic comparison methods including linkage disequilibrium score regression (LDSC) and cross-phenotype association analysis (CPASSOC) to identify genetic overlap in disease pathophysiology, traditional 2-sample and novel PPI-based mendelian randomization to identify causal associations and Bayesian colocalization were applied to association studies conducted in MS to facilitate discovery in the smaller, more limited datasets available for SLE. Pathway analysis using SNP-to-gene mapping identified biological networks composed of molecular pathways with causal implications for CNS disease in SLE specifically, as well as pathways likely causal of both pathologies, providing key insights for therapeutic selection.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140600004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"VARista: a free web platform for streamlined whole-genome variant analysis across T2T, hg38, and hg19","authors":"Noam Hadar, Vadim Dolgin, Katya Oustinov, Yuval Yogev, Tomer Poleg, Amit Safran, Ofek Freund, Nadav Agam, Matan M. Jean, Regina Proskorovski-Ohayon, Ohad Wormser, Max Drabkin, Daniel Halperin, Marina Eskin-Schwartz, Ginat Narkis, Sufa Sued-Hendrickson, Ilana Aminov, Maya Gombosh, Sarit Aharoni, Ohad S. Birk","doi":"10.1007/s00439-024-02671-4","DOIUrl":"https://doi.org/10.1007/s00439-024-02671-4","url":null,"abstract":"<p>With the increasing importance of genomic data in understanding genetic diseases, there is an essential need for efficient and user-friendly tools that simplify variant analysis. Although multiple tools exist, many present barriers such as steep learning curves, limited reference genome compatibility, or costs. We developed VARista, a free web-based tool, to address these challenges and provide a streamlined solution for researchers, particularly those focusing on rare monogenic diseases. VARista offers a user-centric interface that eliminates much of the technical complexity typically associated with variant analysis. The tool directly supports VCF files generated using reference genomes hg19, hg38, and the emerging T2T, with seamless remapping capabilities between them. Features such as gene summaries and links, tissue and cell-specific gene expression data for both adults and fetuses, as well as automated PCR design and integration with tools such as SpliceAI and AlphaMissense, enable users to focus on the biology and the case itself. As we demonstrate, VARista proved effective in narrowing down potential disease-causing variants, prioritizing them effectively, and providing meaningful biological context, facilitating rapid decision-making. VARista stands out as a freely available and comprehensive tool that consolidates various aspects of variant analysis into a single platform that embraces the forefront of genomic advancements. Its design inherently supports a shift in focus from technicalities to critical thinking, thereby promoting better-informed decisions in genetic disease research. Given its unique capabilities and user-centric design, VARista has the potential to become an essential asset for the genomic research community. https://VARista.link</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140600192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Loss-of-function variants affecting the STAGA complex component SUPT7L cause a developmental disorder with generalized lipodystrophy","authors":"Johannes Kopp, Leonard A. Koch, Hristiana Lyubenova, Oliver Küchler, Manuel Holtgrewe, Andranik Ivanov, Christele Dubourg, Erika Launay, Sebastian Brachs, Stefan Mundlos, Nadja Ehmke, Dominik Seelow, Mélanie Fradin, Uwe Kornak, Björn Fischer-Zirnsak","doi":"10.1007/s00439-024-02669-y","DOIUrl":"https://doi.org/10.1007/s00439-024-02669-y","url":null,"abstract":"<p>Generalized lipodystrophy is a feature of various hereditary disorders, often leading to a progeroid appearance. In the present study we identified a missense and a frameshift variant in a compound heterozygous state in <i>SUPT7L</i> in a boy with intrauterine growth retardation, generalized lipodystrophy, and additional progeroid features. <i>SUPT7L</i> encodes a component of the transcriptional coactivator complex STAGA. By transcriptome sequencing, we showed the predicted missense variant to cause aberrant splicing, leading to exon truncation and thereby to a complete absence of SUPT7L in dermal fibroblasts. In addition, we found altered expression of genes encoding DNA repair pathway components. This pathway was further investigated and an increased rate of DNA damage was detected in proband-derived fibroblasts and genome-edited HeLa cells. Finally, we performed transient overexpression of wildtype SUPT7L in both cellular systems, which normalizes the number of DNA damage events. Our findings suggest <i>SUPT7L</i> as a novel disease gene and underline the link between genome instability and progeroid phenotypes.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140600126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}