Genome research最新文献

{"title":"Estrogen-induced chromatin looping changes identify a subset of functional regulatory elements","authors":"Hosiana Abewe, Alexandra Richey, Jeffery M. Vahrenkamp, Matthew Ginley-Hidinger, Craig M. Rush, Noel Kitchen, Xiaoyang Zhang, Jason Gertz","doi":"10.1101/gr.279699.124","DOIUrl":"https://doi.org/10.1101/gr.279699.124","url":null,"abstract":"Transcriptional enhancers can regulate individual or multiple genes through long-range three-dimensional (3D) genome interactions, and these interactions are commonly altered in cancer. Yet, the functional relationship between changes in 3D genome interactions associated with regulatory regions and differential gene expression appears context-dependent. In this study, we used HiChIP to capture changes in 3D genome interactions between active regulatory regions of endometrial cancer cells in response to estrogen treatment and uncovered significant differential long-range interactions strongly enriched for estrogen receptor alpha (ER, also known as ESR1)–bound sites (ERBSs). The ERBSs anchoring differential chromatin loops with either a gene's promoter or distal regions were correlated with larger transcriptional responses to estrogen compared with ERBSs not involved in differential 3D genome interactions. To functionally test this observation, CRISPR-based Enhancer-i was used to deactivate specific ERBSs, which revealed a wide range of effects on the transcriptional response to estrogen. However, these effects are only subtly and not significantly stronger for ERBSs in differential chromatin loops. In addition, we observed an enrichment of 3D genome interactions between the promoters of estrogen-upregulated genes and found that looped promoters can work together cooperatively. Overall, our work reveals that estrogen treatment causes large changes in 3D genome structure in endometrial cancer cells; however, these changes are not required for a regulatory region to contribute to an estrogen transcriptional response.","PeriodicalId":12678,"journal":{"name":"Genome research","volume":"14 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143538299","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":"Quality assessment of long read data in multisample lrRNA-seq experiments with SQANTI-reads","authors":"Netanya Keil, Carolina Monzó, Lauren McIntyre, Ana Conesa","doi":"10.1101/gr.280021.124","DOIUrl":"https://doi.org/10.1101/gr.280021.124","url":null,"abstract":"SQANTI-reads leverages SQANTI3, a tool for the analysis of the quality of transcript models, to develop a read-level quality control framework for replicated long-read RNA-seq experiments. The number and distribution of reads, as well as the number and distribution of unique junction chains (transcript splicing patterns), in SQANTI3 structural categories are informative of raw data quality. Multisample visualizations of QC metrics are presented by experimental design factors to identify outliers. We introduce new metrics for 1) the identification of potentially under-annotated genes and putative novel transcripts and for 2) quantifying variation in junction donors and acceptors. We applied SQANTI-reads to two different datasets, a <em>Drosophila</em> developmental experiment and a multiplatform dataset from the LRGASP project and demonstrate that the tool effectively reveals the impact of read coverage on data quality, and readily identifies strong and weak splicing sites.","PeriodicalId":12678,"journal":{"name":"Genome research","volume":"18 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143538430","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":"Notable challenges posed by long-read sequencing for the study of transcriptional diversity and genome annotation","authors":"Carolina Monzó, Adam Frankish, Ana Conesa","doi":"10.1101/gr.279865.124","DOIUrl":"https://doi.org/10.1101/gr.279865.124","url":null,"abstract":"Long-read sequencing (LRS) technologies have revolutionized transcriptomic research by enabling the comprehensive sequencing of full-length transcripts. Using these technologies, researchers have reported tens of thousands of novel transcripts, even in well-annotated genomes, while developing new algorithms and experimental approaches to handle the noisy data. The LRGASP community effort benchmarked LRS methods in transcriptomics and validated many novel, lowly-expressed, sample-specific transcripts identified by long reads. These molecules represent deviations of the major transcriptional program, that were easily overlooked by short-read sequencing methods but are now captured by the full-length, single-molecule approach. This Perspective discusses the challenges and opportunities associated with LRS' capacity to unravel this fraction of the transcriptome, both in terms of transcriptome biology and genome annotation. For transcriptome biology, we need to develop novel experimental and computational methods to effectively differentiate technology errors from rare but real molecules. For genome annotation, we must agree on the strategy to capture molecular variability while still defining reference annotations that are useful for genome research.","PeriodicalId":12678,"journal":{"name":"Genome research","volume":"23 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143538298","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 prospective trial comparing programmable targeted long-read sequencing and short-read genome sequencing for genetic diagnosis of cerebellar ataxia","authors":"Haloom Rafehi, Liam G. Fearnley, Justin Read, Penny Snell, Kayli C. Davies, Liam Scott, Greta Gillies, Genevieve C. Thompson, Tess A. Field, Aleena Eldo, Simon Bodek, Ernest Butler, Luke Chen, John Drago, Himanshu Goel, Anna Hackett, G. Michael Halmagyi, Andrew Hannaford, Katya Kotschet, Kishore R. Kumar, Smitha Kumble, Matthew Lee-Archer, Abhishek Malhotra, Mark Paine, Michael Poon, Kate Pope, Katrina Reardon, Steven Ring, Anne Ronan, Matthew Silsby, Renee Smyth, Chloe Stutterd, Mathew Wallis, John Waterston, Thomas Wellings, Kirsty West, Christine Wools, Kathy H.C. Wu, David J. Szmulewicz, Martin B. Delatycki, Melanie Bahlo, Paul J. Lockhart","doi":"10.1101/gr.279634.124","DOIUrl":"https://doi.org/10.1101/gr.279634.124","url":null,"abstract":"The cerebellar ataxias (CAs) are a heterogeneous group of disorders characterized by progressive incoordination. Seventeen repeat expansion (RE) loci have been identified as the primary genetic cause and account for &gt;80% of genetic diagnoses. Despite this, diagnostic testing is limited and inefficient, often utilizing single gene assays. This study evaluates the effectiveness of long- and short-read sequencing as diagnostic tools for CA. We recruited 110 individuals (48 females, 62 males) with a clinical diagnosis of CA. Short-read genome sequencing (SR-GS) was performed to identify pathogenic RE and also non-RE variants in 356 genes associated with CA. Independently, long-read sequencing with adaptive sampling (LR-AS) was performed to identify pathogenic RE. SR-GS provided a genetic diagnosis for 38% of the cohort (40/110) including seven non-RE pathogenic variants. RE causes disease in 33 individuals, with the most common condition being SCA27B (<em>n</em> = 24). In comparison, LR-AS identified pathogenic RE in 29 individuals. RE identification for the two methods was concordant apart from four SCA27B cases not detected by LR-AS due to low read depth. For both technologies manual review of the RE alignment enhances diagnostic outcomes. Orthogonal testing for SCA27B revealed a 15% and 0% false positive rate for SR-GS and LR-AS, respectively. In conclusion, both technologies are powerful screening tools for CA. SR-GS is a mature technology currently used by diagnostic providers, requiring only minor changes in bioinformatic workflows to enable CA diagnostics. LR-AS offers considerable advantages in the context of RE detection and characterization but requires optimization before clinical implementation.","PeriodicalId":12678,"journal":{"name":"Genome research","volume":"55 4 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143518775","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":"Exploring the epigenome profiles of repetitive elements with the WashU Repeat Browser","authors":"Jiawei Shen, Siyuan Cheng, Deepak Purushotham, Xiaoyu Zhuo, Alan Y Du, Wenjin Zhang, Daofeng Li, Ting Wang","doi":"10.1101/gr.279764.124","DOIUrl":"https://doi.org/10.1101/gr.279764.124","url":null,"abstract":"Repetitive elements, mostly derived from transposable elements (TEs), account for half the DNA in human and other mammalian genomes. Although epigenetic mechanisms, including DNA methylation and repressive histone modifications, have evolved to suppress TE activities, TEs have substantially shaped the regulatory landscape of the host genome by contributing regulatory sequences to it. TE-derived sequences are often highly repetitive and thus have low mappability, making it difficult to profile the genomics of TEs using short-read sequencing technology. Many specialized bioinformatics tools have been developed for TE-related analysis, but meaningfully visualizing, navigating, and interpreting such data remains challenging. Here, we describe the WashU Repeat Browser to host genomics profiles of human and mouse TEs using data produced by the ENCODE Project and to support the navigation, interactive visualization, integration, comparison, and analysis in the context of TEs. WashU Repeat Browser is a web-based platform allowing users to browse genomic and statistical signals over repetitive elements derived from ENCODE, Roadmap, and FANTOM datasets. The Browser provides a TE-centric view including TE subfamily enrichments, TE subfamily profiling, as well as overviews of genomic signals on individual TE loci where we extend the WashU Epigenome Browser to display user-selected datasets and TE loci. These features could help to close the gaps in our understanding of the repetitive sequences and their putative regulatory functions and aid investigators in formulating new hypotheses by integrating their data with public data.","PeriodicalId":12678,"journal":{"name":"Genome research","volume":"15 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462864","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 genomic consequences and persistence of sociality in spiders","authors":"Jilong Ma, Jesper Bechsgaard, Anne Aagaard, Palle Villesen, Trine Bilde, Mikkel Schierup","doi":"10.1101/gr.279503.124","DOIUrl":"https://doi.org/10.1101/gr.279503.124","url":null,"abstract":"In cooperatively breeding social animals, a few individuals account for all reproduction. In some taxa, sociality is accompanied by a transition from outcrossing to inbreeding. In concert, these traits reduce effective population size, potentially rendering transitions to sociality ‘evolutionarily dead-ends’. We addressed this hypothesis in a comparative genomic study in spiders, where sociality has evolved independently at least 23 times, but social branches are recent and short. We present genomic evidence for the evolutionary dead-end hypothesis in a spider genus with three independent transitions to sociality. We assembled and annotated high-quality, chromosome-level reference genomes from three pairs of closely related social and subsocial <em>Stegodyphus</em> species. We timed the divergence between the social and subsocial species pairs to be from 1.3 to 1.8 million years. Social evolution in spiders involves a shift from outcrossing to inbreeding and from equal to female-biased sex ratio, causing severe reductions in effective population size and decreased efficacy of selection. We show that transitions to sociality only had full effect on purifying selection at 119, 260 and 279 kya respectively, and follow similar convergent trajectories of progressive loss of diversity and shifts to an increasingly female-biased sex ratio. This almost deterministic genomic response to sociality may explain why social spider species do not persist. What causes species extinction is not clear, but could be either selfish meiotic drive eliminating the production of males, or an inability to retain genome integrity in the face of extremely reduced efficacy of selection.","PeriodicalId":12678,"journal":{"name":"Genome research","volume":"181 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451834","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":"Long-read single-cell RNA sequencing enables the study of cancer subclone-specific genotypes and phenotypes in chronic lymphocytic leukemia","authors":"Gage S. Black, Xiaomeng Huang, Yi Qiao, Philip Moos, Deepa Sampath, Deborah M. Stephens, Jennifer A. Woyach, Gabor T. Marth","doi":"10.1101/gr.279049.124","DOIUrl":"https://doi.org/10.1101/gr.279049.124","url":null,"abstract":"Bruton's tyrosine kinase (BTK) inhibitors are effective for the treatment of chronic lymphocytic leukemia (CLL) due to BTK's role in B cell survival and proliferation. Treatment resistance is most commonly caused by the emergence of the hallmark <em>BTK</em>^C481S mutation that inhibits drug binding. In this study, we aimed to investigate cancer subclones harboring a <em>BTK</em>^C481S mutation and identify cells with co-occurring CLL driver mutations. In addition, we sought to determine whether <em>BTK</em>-mutated subclones exhibit distinct transcriptomic behavior when compared to other cancer subclones. To achieve these goals, we use scBayes, which integrates bulk DNA sequencing and single-cell RNA sequencing (scRNA-seq) data to genotype individual cells for subclone-defining mutations. While the most common approach for scRNA-seq includes short-read sequencing, transcript coverage is limited due to the vast majority of the reads being concentrated at the priming end of the transcript. Here, we utilized MAS-seq, a long-read scRNA-seq technology, to substantially increase transcript coverage and expand the set of informative mutations to link cells to cancer subclones in six CLL patients who acquired <em>BTK</em>^C481S mutations during BTK inhibitor treatment. In two patients who developed two independent <em>BTK</em>-mutated subclones, we found that most <em>BTK</em>-mutated cells have an additional CLL-driver gene mutation. When examining subclone-specific gene expression, we found that in one patient, <em>BTK</em>-mutated subclones are transcriptionally distinct from the rest of the malignant B cell population with an overexpression of CLL-relevant genes.","PeriodicalId":12678,"journal":{"name":"Genome research","volume":"80 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443319","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 unified analysis of atlas single cell data","authors":"Hao Chen, Nam D Nguyen, Matt Ruffalo, Ziv Y Bar-Joseph","doi":"10.1101/gr.279631.124","DOIUrl":"https://doi.org/10.1101/gr.279631.124","url":null,"abstract":"Recent efforts to generate atlas-scale single-cell data provide opportunities for joint analysis across tissues and modalities. Existing methods use cells as the reference unit, hindering downstream gene-based analysis and removing genuine biological variations. Here we present GIANT, an integration method designed for atlas-scale gene analysis across cell types and tissues. GIANT converts datasets into gene graphs and recursively embeds genes without additional alignment. Applying GIANT to two recent atlas datasets yields unified gene embedding spaces across human tissues and data modalities. Further evaluations demonstrate GIANT's usefulness in discovering diverse gene functions and underlying gene regulations in cells from different tissues.","PeriodicalId":12678,"journal":{"name":"Genome research","volume":"64 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443323","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":"Transcriptomic and proteomic effects of gene deletion are not evolutionarily conserved","authors":"Yang Li, Jianzhi George Zhang","doi":"10.1101/gr.280008.124","DOIUrl":"https://doi.org/10.1101/gr.280008.124","url":null,"abstract":"Although the textbook definition of gene function is the effect for which the gene was selected and/or by which it is maintained, gene function is commonly inferred from the phenotypic effects of deleting the gene. Because some of the deletion effects are byproducts of other effects, they may not reflect the gene's selected-effect function. To evaluate the degree to which the phenotypic effects of gene deletion inform gene function, we compare the transcriptomic and proteomic effects of systematic gene deletions in budding yeast (<em>Saccharomyces cerevisiae</em>) with those effects in fission yeast (<em>Schizosaccharomyces pombe</em>). Despite evidence for functional conservation of orthologous genes, their deletions result in no more sharing of transcriptomic or proteomic effects than that from deleting non-orthologous genes. Because the wild-type mRNA and protein levels of orthologous genes are significantly correlated between the two yeasts and because transcriptomic effects of deleting the same gene strongly overlap between studies in the same <em>S. cerevisiae</em> strain by different laboratories, our observation cannot be explained by rapid evolution or large measurement error of gene expression. Analysis of transcriptomic and proteomic effects of gene deletions in multiple <em>S. cerevisiae</em> strains by the same laboratory reveals a high sensitivity of these effects to the genetic background, explaining why these effects are not evolutionarily conserved. Together, our results suggest that most transcriptomic and proteomic effects of gene deletion do not inform selected-effect function. This finding has important implications for assessing and/or understanding gene function, pleiotropy, and biological complexity.","PeriodicalId":12678,"journal":{"name":"Genome research","volume":"12 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443322","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":"Evolutionarily new genes in humans with disease phenotypes reveal functional enrichment patterns shaped by adaptive innovation and sexual selection","authors":"Jian-Hai Chen, Patrick Landback, Deanna Arsala, Alexander Guzzetta, Shengqian Xia, Jared Atlas, Dylan Sosa, Yong Zhang, Jingqiu Cheng, Bairong Shen, Manyuan Long","doi":"10.1101/gr.279498.124","DOIUrl":"https://doi.org/10.1101/gr.279498.124","url":null,"abstract":"New genes (or young genes) are genetic novelties pivotal in mammalian evolution. However, their phenotypic impacts and evolutionary patterns over time remain elusive in humans due to the technical and ethical complexities of functional studies. Integrating gene age dating with Mendelian disease phenotyping, we reveal a gradual rise in disease gene proportion as gene age increases. Logistic regression modeling indicates that this increase in older genes may be related to their longer sequence lengths and higher burdens of deleterious de novo germline variants (DNVs). We also find a steady integration of new genes with biomedical phenotypes into the human genome over macroevolutionary timescales (~0.07% per million years). Despite this stable pace, we observe distinct patterns in phenotypic enrichment, pleiotropy, and selective pressures across gene ages. Young genes show significant enrichment in diseases related to the male reproductive system, indicating strong sexual selection. Young genes also exhibit disease-related functions potentially linked to human phenotypic innovations, such as increased brain size, musculoskeletal phenotypes, and color vision. We further reveal a logistic growth pattern of pleiotropy over evolutionary time, indicating a diminishing marginal growth of new functions for older genes due to intensifying selective constraints over time. We propose a \"pleiotropy-barrier\" model that delineates higher potentials for phenotypic in-novation in young genes compared to older genes, a process under natural selection. Our study demonstrates that evolutionarily new genes are critical in influencing human reproductive evolution and adaptive phenotypic innovations driven by sexual and natural selection, with low pleiotropy as a selective advantage.","PeriodicalId":12678,"journal":{"name":"Genome research","volume":"1 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143417623","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}