Genome Biology最新文献

{"title":"LABS: linear amplification-based bisulfite sequencing for ultrasensitive cancer detection from cell-free DNA","authors":"Xiao-Long Cui, Ji Nie, Houxiang Zhu, Krissana Kowitwanich, Alana V. Beadell, Diana C. West-Szymanski, Zhou Zhang, Urszula Dougherty, Akushika Kwesi, Zifeng Deng, Yan Li, Danqing Meng, Kevin Roggin, Teresa Barry, Ryan Owyang, Ben Fefferman, Chang Zeng, Lu Gao, Carolyn W. T. Zhao, Yuri Malina, Jiangbo Wei, Melanie Weigert, Wenjun Kang, Ajay Goel, Brian C.-H. Chiu, Marc Bissonnette, Wei Zhang, Mengjie Chen, Chuan He","doi":"10.1186/s13059-024-03262-2","DOIUrl":"https://doi.org/10.1186/s13059-024-03262-2","url":null,"abstract":"Methylation-based liquid biopsies show promises in detecting cancer using circulating cell-free DNA; however, current limitations impede clinical application. Most assays necessitate substantial DNA inputs, posing challenges. Additionally, underrepresented tumor DNA fragments may go undetected during exponential amplification steps of traditional sequencing methods. Here, we report linear amplification-based bisulfite sequencing (LABS), enabling linear amplification of bisulfite-treated DNA fragments in a genome-wide, unbiased fashion, detecting cancer abnormalities with sub-nanogram inputs. Applying LABS to 100 patient samples revealed cancer-specific patterns, copy number alterations, and enhanced cancer detection accuracy by identifying tissue-of-origin and immune cell composition.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141320022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CpG island turnover events predict evolutionary changes in enhancer activity","authors":"Acadia A. Kocher, Emily V. Dutrow, Severin Uebbing, Kristina M. Yim, María F. Rosales Larios, Marybeth Baumgartner, Timothy Nottoli, James P. Noonan","doi":"10.1186/s13059-024-03300-z","DOIUrl":"https://doi.org/10.1186/s13059-024-03300-z","url":null,"abstract":"Genetic changes that modify the function of transcriptional enhancers have been linked to the evolution of biological diversity across species. Multiple studies have focused on the role of nucleotide substitutions, transposition, and insertions and deletions in altering enhancer function. CpG islands (CGIs) have recently been shown to influence enhancer activity, and here we test how their turnover across species contributes to enhancer evolution. We integrate maps of CGIs and enhancer activity-associated histone modifications obtained from multiple tissues in nine mammalian species and find that CGI content in enhancers is strongly associated with increased histone modification levels. CGIs show widespread turnover across species and species-specific CGIs are strongly enriched for enhancers exhibiting species-specific activity across all tissues and species. Genes associated with enhancers with species-specific CGIs show concordant biases in their expression, supporting that CGI turnover contributes to gene regulatory innovation. Our results also implicate CGI turnover in the evolution of Human Gain Enhancers (HGEs), which show increased activity in human embryonic development and may have contributed to the evolution of uniquely human traits. Using a humanized mouse model, we show that a highly conserved HGE with a large CGI absent from the mouse ortholog shows increased activity at the human CGI in the humanized mouse diencephalon. Collectively, our results point to CGI turnover as a mechanism driving gene regulatory changes potentially underlying trait evolution in mammals.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141315711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leaf: an ultrafast filter for population-scale long-read SV detection","authors":"Chenxu Pan, Knut Reinert","doi":"10.1186/s13059-024-03297-5","DOIUrl":"https://doi.org/10.1186/s13059-024-03297-5","url":null,"abstract":"Advances in sequencing technology have facilitated population-scale long-read structural variant (SV) detection. Arguably, one of the main challenges in population-scale analysis is developing effective computational pipelines. Here, we present a new filter-based pipeline for population-scale long-read SV detection. It better captures SV signals at an early stage than conventional assembly-based or alignment-based pipelines. Assessments in this work suggest that the filter-based pipeline helps better resolve intra-read rearrangements. Moreover, it is also more computationally efficient than conventional pipelines and thus may facilitate population-scale long-read applications.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141315670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Legal aspects of privacy-enhancing technologies in genome-wide association studies and their impact on performance and feasibility","authors":"Alissa Brauneck, Louisa Schmalhorst, Stefan Weiss, Linda Baumbach, Uwe Völker, David Ellinghaus, Jan Baumbach, Gabriele Buchholtz","doi":"10.1186/s13059-024-03296-6","DOIUrl":"https://doi.org/10.1186/s13059-024-03296-6","url":null,"abstract":"Genomic data holds huge potential for medical progress but requires strict safety measures due to its sensitive nature to comply with data protection laws. This conflict is especially pronounced in genome-wide association studies (GWAS) which rely on vast amounts of genomic data to improve medical diagnoses. To ensure both their benefits and sufficient data security, we propose a federated approach in combination with privacy-enhancing technologies utilising the findings from a systematic review on federated learning and legal regulations in general and applying these to GWAS.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141315652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gene count normalization in single-cell imaging-based spatially resolved transcriptomics","authors":"Lyla Atta, Kalen Clifton, Manjari Anant, Gohta Aihara, Jean Fan","doi":"10.1186/s13059-024-03303-w","DOIUrl":"https://doi.org/10.1186/s13059-024-03303-w","url":null,"abstract":"Recent advances in imaging-based spatially resolved transcriptomics (im-SRT) technologies now enable high-throughput profiling of targeted genes and their locations in fixed tissues. Normalization of gene expression data is often needed to account for technical factors that may confound underlying biological signals. Here, we investigate the potential impact of different gene count normalization methods with different targeted gene panels in the analysis and interpretation of im-SRT data. Using different simulated gene panels that overrepresent genes expressed in specific tissue regions or cell types, we demonstrate how normalization methods based on detected gene counts per cell differentially impact normalized gene expression magnitudes in a region- or cell type-specific manner. We show that these normalization-induced effects may reduce the reliability of downstream analyses including differential gene expression, gene fold change, and spatially variable gene analysis, introducing false positive and false negative results when compared to results obtained from gene panels that are more representative of the gene expression of the tissue’s component cell types. These effects are not observed with normalization approaches that do not use detected gene counts for gene expression magnitude adjustment, such as with cell volume or cell area normalization. We recommend using non-gene count-based normalization approaches when feasible and evaluating gene panel representativeness before using gene count-based normalization methods if necessary. Overall, we caution that the choice of normalization method and gene panel may impact the biological interpretation of the im-SRT data.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141309231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FoldPAthreader: predicting protein folding pathway using a novel folding force field model derived from known protein universe","authors":"Kailong Zhao, Pengxin Zhao, Suhui Wang, Yuhao Xia, Guijun Zhang","doi":"10.1186/s13059-024-03291-x","DOIUrl":"https://doi.org/10.1186/s13059-024-03291-x","url":null,"abstract":"Protein folding has become a tractable problem with the significant advances in deep learning-driven protein structure prediction. Here we propose FoldPAthreader, a protein folding pathway prediction method that uses a novel folding force field model by exploring the intrinsic relationship between protein evolution and folding from the known protein universe. Further, the folding force field is used to guide Monte Carlo conformational sampling, driving the protein chain fold into its native state by exploring potential intermediates. On 30 example targets, FoldPAthreader successfully predicts 70% of the proteins whose folding pathway is consistent with biological experimental data.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Author Correction: The senescent methylome and its relationship with cancer, ageing and germline genetic variation in humans","authors":"Robert Lowe, Marita G. Overhoff, Sreeram V. Ramagopalan, James C. Garbe, James Koh, Martha R. Stampfer, David H. Beach, Vardhman K. Rakyan, Cleo L. Bishop","doi":"10.1186/s13059-024-03295-7","DOIUrl":"https://doi.org/10.1186/s13059-024-03295-7","url":null,"abstract":"<p><b>Author Correction: Genome Biol 16, 194 (2015)</b></p><p><b>https://doi.org/10.1186/s13059-015-0748-4</b></p><br/><p>Following publication of the original article [1], the authors reported two errors in Fig. 1B and Fig. 2B.</p><p>1. The two EP + siGLO and DS + siGLO brightfield/β-gal images from Fig. 2A were accidentally duplicated in Fig. 1B. The images in Fig. 2A are correct.</p><p>The images in Fig. 1B are replaced with representative images of untransfected EP and DS cells. The incorrect and the correct figure are given below.</p><p>The incorrect Fig. 1:</p><figure><picture><source srcset=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13059-024-03295-7/MediaObjects/13059_2024_3295_Figa_HTML.png?as=webp\" type=\"image/webp\"/><img alt=\"figure a\" aria-describedby=\"Figa\" height=\"626\" loading=\"lazy\" src=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13059-024-03295-7/MediaObjects/13059_2024_3295_Figa_HTML.png\" width=\"685\"/></picture></figure><p>The correct Fig. 1:</p><figure><picture><source srcset=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13059-024-03295-7/MediaObjects/13059_2024_3295_Figb_HTML.png?as=webp\" type=\"image/webp\"/><img alt=\"figure b\" aria-describedby=\"Figb\" height=\"623\" loading=\"lazy\" src=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13059-024-03295-7/MediaObjects/13059_2024_3295_Figb_HTML.png\" width=\"685\"/></picture></figure><p>The replacement of these images does not change any of the other data in this figure, nor the conclusion of this figure.</p><p>2. The authors also noticed that the panels in Fig. 2B labelled with “DS” were incorrectly labelled. The bar charts and figure legend correctly state that these images are “DS + siGLO” images. These panels are now relabelled as “DS + siGLO”.</p><p>This proposed relabelling does not change any of the other data in this figure, nor the conclusion of Fig. 2B. The incorrect and the correct figure are given below.</p><p>The incorrect Fig. 2:</p><figure><picture><source srcset=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13059-024-03295-7/MediaObjects/13059_2024_3295_Figc_HTML.png?as=webp\" type=\"image/webp\"/><img alt=\"figure c\" aria-describedby=\"Figc\" height=\"914\" loading=\"lazy\" src=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13059-024-03295-7/MediaObjects/13059_2024_3295_Figc_HTML.png\" width=\"685\"/></picture></figure><p>The correct Fig. 2:</p><figure><picture><source srcset=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13059-024-03295-7/MediaObjects/13059_2024_3295_Figd_HTML.png?as=webp\" type=\"image/webp\"/><img alt=\"figure d\" aria-describedby=\"Figd\" height=\"902\" loading=\"lazy\" src=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13059-024-03295-7/MediaObjects/13059_2024_3295_Figd_HTML.png\" width=\"685\"/></picture></figure><p>In both instances, these errors do not change any ","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141298922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CelFiE-ISH: a probabilistic model for multi-cell type deconvolution from single-molecule DNA methylation haplotypes","authors":"Irene Unterman, Dana Avrahami, Efrat Katsman, Triche Tim Jr., Benjamin Glaser, Benjamin P. Berman","doi":"10.1186/s13059-024-03275-x","DOIUrl":"https://doi.org/10.1186/s13059-024-03275-x","url":null,"abstract":"Deconvolution methods infer quantitative cell type estimates from bulk measurement of mixed samples including blood and tissue. DNA methylation sequencing measures multiple CpGs per read, but few existing deconvolution methods leverage this within-read information. We develop CelFiE-ISH, which extends an existing method (CelFiE) to use within-read haplotype information. CelFiE-ISH outperforms CelFiE and other existing methods, achieving 30% better accuracy and more sensitive detection of rare cell types. We also demonstrate the importance of marker selection and of tailoring markers for haplotype-aware methods. While here we use gold-standard short-read sequencing data, haplotype-aware methods will be well-suited for long-read sequencing.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141299070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural variant landscapes reveal convergent signatures of evolution in sheep and goats","authors":"Ji Yang, Dong-Feng Wang, Jia-Hui Huang, Qiang-Hui Zhu, Ling-Yun Luo, Ran Lu, Xing-Long Xie, Hosein Salehian-Dehkordi, Ali Esmailizadeh, George E. Liu, Meng-Hua Li","doi":"10.1186/s13059-024-03288-6","DOIUrl":"https://doi.org/10.1186/s13059-024-03288-6","url":null,"abstract":"Sheep and goats have undergone domestication and improvement to produce similar phenotypes, which have been greatly impacted by structural variants (SVs). Here, we report a high-quality chromosome-level reference genome of Asiatic mouflon, and implement a comprehensive analysis of SVs in 897 genomes of worldwide wild and domestic populations of sheep and goats to reveal genetic signatures underlying convergent evolution. We characterize the SV landscapes in terms of genetic diversity, chromosomal distribution and their links with genes, QTLs and transposable elements, and examine their impacts on regulatory elements. We identify several novel SVs and annotate corresponding genes (e.g., BMPR1B, BMPR2, RALYL, COL21A1, and LRP1B) associated with important production traits such as fertility, meat and milk production, and wool/hair fineness. We detect signatures of selection involving the parallel evolution of orthologous SV-associated genes during domestication, local environmental adaptation, and improvement. In particular, we find that fecundity traits experienced convergent selection targeting the gene BMPR1B, with the DEL00067921 deletion explaining ~10.4% of the phenotypic variation observed in goats. Our results provide new insights into the convergent evolution of SVs and serve as a rich resource for the future improvement of sheep, goats, and related livestock.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141264914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"iIMPACT: integrating image and molecular profiles for spatial transcriptomics analysis","authors":"Xi Jiang, Shidan Wang, Lei Guo, Bencong Zhu, Zhuoyu Wen, Liwei Jia, Lin Xu, Guanghua Xiao, Qiwei Li","doi":"10.1186/s13059-024-03289-5","DOIUrl":"https://doi.org/10.1186/s13059-024-03289-5","url":null,"abstract":"Current clustering analysis of spatial transcriptomics data primarily relies on molecular information and fails to fully exploit the morphological features present in histology images, leading to compromised accuracy and interpretability. To overcome these limitations, we have developed a multi-stage statistical method called iIMPACT. It identifies and defines histology-based spatial domains based on AI-reconstructed histology images and spatial context of gene expression measurements, and detects domain-specific differentially expressed genes. Through multiple case studies, we demonstrate iIMPACT outperforms existing methods in accuracy and interpretability and provides insights into the cellular spatial organization and landscape of functional genes within spatial transcriptomics data.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141264821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}