CRISPR mutagenesis screens conducted with SpCas9 and other nucleases have identified certain cis-regulatory elements and genetic variants but at a limited resolution due to the absence of protospacer adjacent motif (PAM) sequences. Here, leveraging the broad targeting scope of the near-PAMless SpRY variant, we have demonstrated that saturated SpRY mutagenesis and base editing screens can faithfully identify functional regulatory elements and essential genetic variants for target gene expression at single-base resolution. We further extended this methodology to investigate a genome-wide association study (GWAS) locus at 10q22.1 associated with a red blood cell trait, where we identified potential enhancers regulating HK1 gene expression, despite not all of these enhancers exhibiting typical chromatin signatures. More importantly, our saturated base editing screens pinpoint multiple causal variants within this locus that would otherwise be missed by Bayesian statistical fine-mapping. Our approach is generally applicable to functional interrogation of all non-coding genomic elements while complementing other high-coverage CRISPR screens.
{"title":"SpRY-mediated screens facilitate functional dissection of non-coding sequences at single-base resolution.","authors":"Yao Yao, Zhiwei Zhou, Xiaoling Wang, Zhirui Liu, Yixin Zhai, Xiaolin Chi, Jingyi Du, Liheng Luo, Zhigang Zhao, Xiaoyue Wang, Chaoyou Xue, Shuquan Rao","doi":"10.1016/j.xgen.2024.100583","DOIUrl":"10.1016/j.xgen.2024.100583","url":null,"abstract":"<p><p>CRISPR mutagenesis screens conducted with SpCas9 and other nucleases have identified certain cis-regulatory elements and genetic variants but at a limited resolution due to the absence of protospacer adjacent motif (PAM) sequences. Here, leveraging the broad targeting scope of the near-PAMless SpRY variant, we have demonstrated that saturated SpRY mutagenesis and base editing screens can faithfully identify functional regulatory elements and essential genetic variants for target gene expression at single-base resolution. We further extended this methodology to investigate a genome-wide association study (GWAS) locus at 10q22.1 associated with a red blood cell trait, where we identified potential enhancers regulating HK1 gene expression, despite not all of these enhancers exhibiting typical chromatin signatures. More importantly, our saturated base editing screens pinpoint multiple causal variants within this locus that would otherwise be missed by Bayesian statistical fine-mapping. Our approach is generally applicable to functional interrogation of all non-coding genomic elements while complementing other high-coverage CRISPR screens.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11293580/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141422072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-10Epub Date: 2024-06-18DOI: 10.1016/j.xgen.2024.100587
Katie L Burnham, Nikhil Milind, Wanseon Lee, Andrew J Kwok, Kiki Cano-Gamez, Yuxin Mi, Cyndi G Geoghegan, Ping Zhang, Stuart McKechnie, Nicole Soranzo, Charles J Hinds, Julian C Knight, Emma E Davenport
Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.
{"title":"eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis.","authors":"Katie L Burnham, Nikhil Milind, Wanseon Lee, Andrew J Kwok, Kiki Cano-Gamez, Yuxin Mi, Cyndi G Geoghegan, Ping Zhang, Stuart McKechnie, Nicole Soranzo, Charles J Hinds, Julian C Knight, Emma E Davenport","doi":"10.1016/j.xgen.2024.100587","DOIUrl":"10.1016/j.xgen.2024.100587","url":null,"abstract":"<p><p>Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11293594/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141428438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12Epub Date: 2024-05-20DOI: 10.1016/j.xgen.2024.100563
Yocelyn Recinos, Suying Bao, Xiaojian Wang, Brittany L Phillips, Yow-Tyng Yeh, Sebastien M Weyn-Vanhentenryck, Maurice S Swanson, Chaolin Zhang
Divergence of precursor messenger RNA (pre-mRNA) alternative splicing (AS) is widespread in mammals, including primates, but the underlying mechanisms and functional impact are poorly understood. Here, we modeled cassette exon inclusion in primate brains as a quantitative trait and identified 1,170 (∼3%) exons with lineage-specific splicing shifts under stabilizing selection. Among them, microtubule-associated protein tau (MAPT) exons 2 and 10 underwent anticorrelated, two-step evolutionary shifts in the catarrhine and hominoid lineages, leading to their present inclusion levels in humans. The developmental-stage-specific divergence of exon 10 splicing, whose dysregulation can cause frontotemporal lobar degeneration (FTLD), is mediated by divergent distal intronic MBNL-binding sites. Competitive binding of these sites by CRISPR-dCas13d/gRNAs effectively reduces exon 10 inclusion, potentially providing a therapeutically compatible approach to modulate tau isoform expression. Our data suggest adaptation of MAPT function and, more generally, a role for AS in the evolutionary expansion of the primate brain.
{"title":"Lineage-specific splicing regulation of MAPT gene in the primate brain.","authors":"Yocelyn Recinos, Suying Bao, Xiaojian Wang, Brittany L Phillips, Yow-Tyng Yeh, Sebastien M Weyn-Vanhentenryck, Maurice S Swanson, Chaolin Zhang","doi":"10.1016/j.xgen.2024.100563","DOIUrl":"10.1016/j.xgen.2024.100563","url":null,"abstract":"<p><p>Divergence of precursor messenger RNA (pre-mRNA) alternative splicing (AS) is widespread in mammals, including primates, but the underlying mechanisms and functional impact are poorly understood. Here, we modeled cassette exon inclusion in primate brains as a quantitative trait and identified 1,170 (∼3%) exons with lineage-specific splicing shifts under stabilizing selection. Among them, microtubule-associated protein tau (MAPT) exons 2 and 10 underwent anticorrelated, two-step evolutionary shifts in the catarrhine and hominoid lineages, leading to their present inclusion levels in humans. The developmental-stage-specific divergence of exon 10 splicing, whose dysregulation can cause frontotemporal lobar degeneration (FTLD), is mediated by divergent distal intronic MBNL-binding sites. Competitive binding of these sites by CRISPR-dCas13d/gRNAs effectively reduces exon 10 inclusion, potentially providing a therapeutically compatible approach to modulate tau isoform expression. Our data suggest adaptation of MAPT function and, more generally, a role for AS in the evolutionary expansion of the primate brain.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11228892/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141077375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The gut microbiome displays genetic differences among populations, and characterization of the genomic landscape of the gut microbiome in China remains limited. Here, we present the Chinese Gut Microbial Reference (CGMR) set, comprising 101,060 high-quality metagenomic assembled genomes (MAGs) of 3,707 nonredundant species from 3,234 fecal samples across primarily rural Chinese locations, 1,376 live isolates mainly from lactic acid bacteria, and 987 novel species relative to worldwide databases. We observed region-specific coexisting MAGs and MAGs with probiotic and cardiometabolic functionalities. Preliminary mouse experiments suggest a probiotic effect of two Faecalibacillus intestinalis isolates in alleviating constipation, cardiometabolic influences of three Bacteroides fragilis_A isolates in obesity, and isolates from the genera Parabacteroides and Lactobacillus in host lipid metabolism. Our study expands the current microbial genomes with paired isolates and demonstrates potential host effects, contributing to the mechanistic understanding of host-microbe interactions.
{"title":"Gut microbial genomes with paired isolates from China illustrate probiotic and cardiometabolic effects.","authors":"Pan Huang, Quanbin Dong, Yifeng Wang, Yunfan Tian, Shunhe Wang, Chengcheng Zhang, Leilei Yu, Fengwei Tian, Xiaoxiang Gao, Hang Guo, Shanrong Yi, Mingyang Li, Yang Liu, Qingsong Zhang, Wenwei Lu, Gang Wang, Bo Yang, Shumao Cui, Dongxu Hua, Xiuchao Wang, Yuwen Jiao, Lu Liu, Qiufeng Deng, Beining Ma, Tingting Wu, Huayiyang Zou, Jing Shi, Haifeng Zhang, Daming Fan, Yanhui Sheng, Jianxin Zhao, Liming Tang, Hao Zhang, Wei Sun, Wei Chen, Xiangqing Kong, Lianmin Chen, Qixiao Zhai","doi":"10.1016/j.xgen.2024.100559","DOIUrl":"10.1016/j.xgen.2024.100559","url":null,"abstract":"<p><p>The gut microbiome displays genetic differences among populations, and characterization of the genomic landscape of the gut microbiome in China remains limited. Here, we present the Chinese Gut Microbial Reference (CGMR) set, comprising 101,060 high-quality metagenomic assembled genomes (MAGs) of 3,707 nonredundant species from 3,234 fecal samples across primarily rural Chinese locations, 1,376 live isolates mainly from lactic acid bacteria, and 987 novel species relative to worldwide databases. We observed region-specific coexisting MAGs and MAGs with probiotic and cardiometabolic functionalities. Preliminary mouse experiments suggest a probiotic effect of two Faecalibacillus intestinalis isolates in alleviating constipation, cardiometabolic influences of three Bacteroides fragilis_A isolates in obesity, and isolates from the genera Parabacteroides and Lactobacillus in host lipid metabolism. Our study expands the current microbial genomes with paired isolates and demonstrates potential host effects, contributing to the mechanistic understanding of host-microbe interactions.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11228888/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140917584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12Epub Date: 2024-05-22DOI: 10.1016/j.xgen.2024.100565
Senlin Lin, Yan Cui, Fangyuan Zhao, Zhidong Yang, Jiangning Song, Jianhua Yao, Yu Zhao, Bin-Zhi Qian, Yi Zhao, Zhiyuan Yuan
Spatially resolved transcriptomics (SRT) technologies have revolutionized the study of tissue organization. We introduce a graph convolutional network with an attention and positive emphasis mechanism, termed BINARY, relying exclusively on binarized SRT data to accurately delineate spatial domains. BINARY outperforms existing methods across various SRT data types while using significantly less input information. Our study suggests that precise gene expression quantification may not always be essential, inspiring further exploration of the broader applications of spatially resolved binarized gene expression data.
{"title":"Complete spatially resolved gene expression is not necessary for identifying spatial domains.","authors":"Senlin Lin, Yan Cui, Fangyuan Zhao, Zhidong Yang, Jiangning Song, Jianhua Yao, Yu Zhao, Bin-Zhi Qian, Yi Zhao, Zhiyuan Yuan","doi":"10.1016/j.xgen.2024.100565","DOIUrl":"10.1016/j.xgen.2024.100565","url":null,"abstract":"<p><p>Spatially resolved transcriptomics (SRT) technologies have revolutionized the study of tissue organization. We introduce a graph convolutional network with an attention and positive emphasis mechanism, termed BINARY, relying exclusively on binarized SRT data to accurately delineate spatial domains. BINARY outperforms existing methods across various SRT data types while using significantly less input information. Our study suggests that precise gene expression quantification may not always be essential, inspiring further exploration of the broader applications of spatially resolved binarized gene expression data.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11228956/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141089387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12Epub Date: 2024-05-29DOI: 10.1016/j.xgen.2024.100580
Unnati Sonawala, Helen Beasley, Peter Thorpe, Kyriakos Varypatakis, Beatrice Senatori, John T Jones, Lida Derevnina, Sebastian Eves-van den Akker
Pathogens are engaged in a fierce evolutionary arms race with their host. The genes at the forefront of the engagement between kingdoms are often part of diverse and highly mutable gene families. Even in this context, we discovered unprecedented variation in the hyper-variable (HYP) effectors of plant-parasitic nematodes. HYP effectors are single-gene loci that potentially harbor thousands of alleles. Alleles vary in the organization, as well as the number, of motifs within a central hyper-variable domain (HVD). We dramatically expand the HYP repertoire of two plant-parasitic nematodes and define distinct species-specific "rules" underlying the apparently flawless genetic rearrangements. Finally, by analyzing the HYPs in 68 individual nematodes, we unexpectedly found that despite the huge number of alleles, most individuals are germline homozygous. These data support a mechanism of programmed genetic variation, termed HVD editing, where alterations are locus specific, strictly governed by rules, and theoretically produce thousands of variants without errors.
{"title":"A gene with a thousand alleles: The hyper-variable effectors of plant-parasitic nematodes.","authors":"Unnati Sonawala, Helen Beasley, Peter Thorpe, Kyriakos Varypatakis, Beatrice Senatori, John T Jones, Lida Derevnina, Sebastian Eves-van den Akker","doi":"10.1016/j.xgen.2024.100580","DOIUrl":"10.1016/j.xgen.2024.100580","url":null,"abstract":"<p><p>Pathogens are engaged in a fierce evolutionary arms race with their host. The genes at the forefront of the engagement between kingdoms are often part of diverse and highly mutable gene families. Even in this context, we discovered unprecedented variation in the hyper-variable (HYP) effectors of plant-parasitic nematodes. HYP effectors are single-gene loci that potentially harbor thousands of alleles. Alleles vary in the organization, as well as the number, of motifs within a central hyper-variable domain (HVD). We dramatically expand the HYP repertoire of two plant-parasitic nematodes and define distinct species-specific \"rules\" underlying the apparently flawless genetic rearrangements. Finally, by analyzing the HYPs in 68 individual nematodes, we unexpectedly found that despite the huge number of alleles, most individuals are germline homozygous. These data support a mechanism of programmed genetic variation, termed HVD editing, where alterations are locus specific, strictly governed by rules, and theoretically produce thousands of variants without errors.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11228951/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141181730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12Epub Date: 2024-05-31DOI: 10.1016/j.xgen.2024.100581
Jesus Gonzalez-Ferrer, Julian Lehrer, Ash O'Farrell, Benedict Paten, Mircea Teodorescu, David Haussler, Vanessa D Jonsson, Mohammed A Mostajo-Radji
Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-efficient pipeline for single-cell RNA classification. We benchmark SIMS against datasets from different tissues and species. We demonstrate SIMS's efficacy in classifying cells in the brain, achieving high accuracy even with small training sets (<3,500 cells) and across different samples. SIMS accurately predicts neuronal subtypes in the developing brain, shedding light on genetic changes during neuronal differentiation and postmitotic fate refinement. Finally, we apply SIMS to single-cell RNA datasets of cortical organoids to predict cell identities and uncover genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.
{"title":"SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis.","authors":"Jesus Gonzalez-Ferrer, Julian Lehrer, Ash O'Farrell, Benedict Paten, Mircea Teodorescu, David Haussler, Vanessa D Jonsson, Mohammed A Mostajo-Radji","doi":"10.1016/j.xgen.2024.100581","DOIUrl":"10.1016/j.xgen.2024.100581","url":null,"abstract":"<p><p>Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-efficient pipeline for single-cell RNA classification. We benchmark SIMS against datasets from different tissues and species. We demonstrate SIMS's efficacy in classifying cells in the brain, achieving high accuracy even with small training sets (<3,500 cells) and across different samples. SIMS accurately predicts neuronal subtypes in the developing brain, shedding light on genetic changes during neuronal differentiation and postmitotic fate refinement. Finally, we apply SIMS to single-cell RNA datasets of cortical organoids to predict cell identities and uncover genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11228957/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141186955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pancreatic cancer (PC) is the deadliest malignancy due to late diagnosis. Aberrant alterations in the blood proteome might serve as biomarkers to facilitate early detection of PC. We designed a nested case-control study of incident PC based on a prospective cohort of 38,295 elderly Chinese participants with ∼5.7 years' follow-up. Forty matched case-control pairs passed the quality controls for the proximity extension assay of 1,463 serum proteins. With a lenient threshold of p < 0.005, we discovered regenerating family member 1A (REG1A), REG1B, tumor necrosis factor (TNF), and phospholipase A2 group IB (PLA2G1B) in association with incident PC, among which the two REG1 proteins were replicated using the UK Biobank Pharma Proteomics Project, with effect sizes increasing steadily as diagnosis time approaches the baseline. Mendelian randomization analysis further supported the potential causal effects of REG1 proteins on PC. Taken together, circulating REG1A and REG1B are promising biomarkers and potential therapeutic targets for the early detection and prevention of PC.
胰腺癌(PC)因诊断较晚而成为最致命的恶性肿瘤。血液蛋白质组的异常改变可作为生物标志物,有助于早期发现胰腺癌。我们设计了一项巢式病例对照研究,研究对象是38 295名随访时间在5.7年以上的中国老年人。40对匹配的病例对照通过了1463种血清蛋白的近似延伸检测质量控制。以 p
{"title":"Identification of biomarkers and potential therapeutic targets for pancreatic cancer by proteomic analysis in two prospective cohorts.","authors":"Jingjing Lyu, Minghui Jiang, Ziwei Zhu, Hongji Wu, Haonan Kang, Xingjie Hao, Shanshan Cheng, Huan Guo, Xia Shen, Tangchun Wu, Jiang Chang, Chaolong Wang","doi":"10.1016/j.xgen.2024.100561","DOIUrl":"10.1016/j.xgen.2024.100561","url":null,"abstract":"<p><p>Pancreatic cancer (PC) is the deadliest malignancy due to late diagnosis. Aberrant alterations in the blood proteome might serve as biomarkers to facilitate early detection of PC. We designed a nested case-control study of incident PC based on a prospective cohort of 38,295 elderly Chinese participants with ∼5.7 years' follow-up. Forty matched case-control pairs passed the quality controls for the proximity extension assay of 1,463 serum proteins. With a lenient threshold of p < 0.005, we discovered regenerating family member 1A (REG1A), REG1B, tumor necrosis factor (TNF), and phospholipase A2 group IB (PLA2G1B) in association with incident PC, among which the two REG1 proteins were replicated using the UK Biobank Pharma Proteomics Project, with effect sizes increasing steadily as diagnosis time approaches the baseline. Mendelian randomization analysis further supported the potential causal effects of REG1 proteins on PC. Taken together, circulating REG1A and REG1B are promising biomarkers and potential therapeutic targets for the early detection and prevention of PC.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140961339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12DOI: 10.1016/j.xgen.2024.100582
Joel Gelernter, Daniel F Levey, Marco Galimberti, Kelly Harrington, Hang Zhou, Keyrun Adhikari, Priya Gupta, J Michael Gaziano, Dean Eliott, Murray B Stein
Epiretinal membrane (ERM) is a common retinal condition characterized by the presence of fibrocellular tissue on the retinal surface, often with visual distortion and loss of visual acuity. We studied European American (EUR), African American (AFR), and Latino (admixed American, AMR) ERM participants in the Million Veteran Program (MVP) for genome-wide association analysis-a total of 38,232 case individuals and 557,988 control individuals. We completed a genome-wide association study (GWAS) in each population separately, and then results were meta-analyzed. Genome-wide significant (GWS) associations were observed in all three populations studied: 31 risk loci in EUR subjects, 3 in AFR, and 2 in AMR, with 48 in trans-ancestry meta-analysis. Many results replicated in the FinnGen sample. Several GWS variants associate to alterations in gene expression in the macula. ERM showed significant genetic correlation to multiple traits. Pathway enrichment analyses implicated collagen and collagen-adjacent mechanisms, among others. This well-powered ERM GWAS identified novel genetic associations that point to biological mechanisms for ERM.
{"title":"Genome-wide association study of the common retinal disorder epiretinal membrane: Significant risk loci in each of three American populations.","authors":"Joel Gelernter, Daniel F Levey, Marco Galimberti, Kelly Harrington, Hang Zhou, Keyrun Adhikari, Priya Gupta, J Michael Gaziano, Dean Eliott, Murray B Stein","doi":"10.1016/j.xgen.2024.100582","DOIUrl":"10.1016/j.xgen.2024.100582","url":null,"abstract":"<p><p>Epiretinal membrane (ERM) is a common retinal condition characterized by the presence of fibrocellular tissue on the retinal surface, often with visual distortion and loss of visual acuity. We studied European American (EUR), African American (AFR), and Latino (admixed American, AMR) ERM participants in the Million Veteran Program (MVP) for genome-wide association analysis-a total of 38,232 case individuals and 557,988 control individuals. We completed a genome-wide association study (GWAS) in each population separately, and then results were meta-analyzed. Genome-wide significant (GWS) associations were observed in all three populations studied: 31 risk loci in EUR subjects, 3 in AFR, and 2 in AMR, with 48 in trans-ancestry meta-analysis. Many results replicated in the FinnGen sample. Several GWS variants associate to alterations in gene expression in the macula. ERM showed significant genetic correlation to multiple traits. Pathway enrichment analyses implicated collagen and collagen-adjacent mechanisms, among others. This well-powered ERM GWAS identified novel genetic associations that point to biological mechanisms for ERM.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11228954/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141319153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12Epub Date: 2024-05-14DOI: 10.1016/j.xgen.2024.100562
Francisco Rodriguez-Algarra, David M Evans, Vardhman K Rakyan
The phenotypic impact of genetic variation of repetitive features in the human genome is currently understudied. One such feature is the multi-copy 47S ribosomal DNA (rDNA) that codes for rRNA components of the ribosome. Here, we present an analysis of rDNA copy number (CN) variation in the UK Biobank (UKB). From the first release of UKB whole-genome sequencing (WGS) data, a discovery analysis in White British individuals reveals that rDNA CN associates with altered counts of specific blood cell subtypes, such as neutrophils, and with the estimated glomerular filtration rate, a marker of kidney function. Similar trends are observed in other ancestries. A range of analyses argue against reverse causality or common confounder effects, and all core results replicate in the second UKB WGS release. Our work demonstrates that rDNA CN is a genetic influence on trait variance in humans.
{"title":"Ribosomal DNA copy number variation associates with hematological profiles and renal function in the UK Biobank.","authors":"Francisco Rodriguez-Algarra, David M Evans, Vardhman K Rakyan","doi":"10.1016/j.xgen.2024.100562","DOIUrl":"10.1016/j.xgen.2024.100562","url":null,"abstract":"<p><p>The phenotypic impact of genetic variation of repetitive features in the human genome is currently understudied. One such feature is the multi-copy 47S ribosomal DNA (rDNA) that codes for rRNA components of the ribosome. Here, we present an analysis of rDNA copy number (CN) variation in the UK Biobank (UKB). From the first release of UKB whole-genome sequencing (WGS) data, a discovery analysis in White British individuals reveals that rDNA CN associates with altered counts of specific blood cell subtypes, such as neutrophils, and with the estimated glomerular filtration rate, a marker of kidney function. Similar trends are observed in other ancestries. A range of analyses argue against reverse causality or common confounder effects, and all core results replicate in the second UKB WGS release. Our work demonstrates that rDNA CN is a genetic influence on trait variance in humans.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11228893/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140946449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}