Genome Biology最新文献

IAMSAM: image-based analysis of molecular signatures using the Segment Anything Model IAMSAM：基于图像的分子特征分析，使用分段 Anything 模型

IF 12.3 1区生物学

Genome Biology Pub Date : 2024-11-11 DOI: 10.1186/s13059-024-03380-x

Dongjoo Lee, Jeongbin Park, Seungho Cook, Seongjin Yoo, Daeseung Lee, Hongyoon Choi

引用次数: 0

Adenine base editors induce off-target structure variations in mouse embryos and primary human T cells 腺嘌呤碱基编辑器在小鼠胚胎和原代人类 T 细胞中诱发脱靶结构变异

IF 12.3 1区生物学

Genome Biology Pub Date : 2024-11-11 DOI: 10.1186/s13059-024-03434-0

Leilei Wu, Shutan Jiang, Meisong Shi, Tanglong Yuan, Yaqin Li, Pinzheng Huang, Yingqi Li, Erwei Zuo, Changyang Zhou, Yidi Sun

{"title":"Adenine base editors induce off-target structure variations in mouse embryos and primary human T cells","authors":"Leilei Wu, Shutan Jiang, Meisong Shi, Tanglong Yuan, Yaqin Li, Pinzheng Huang, Yingqi Li, Erwei Zuo, Changyang Zhou, Yidi Sun","doi":"10.1186/s13059-024-03434-0","DOIUrl":"https://doi.org/10.1186/s13059-024-03434-0","url":null,"abstract":"The safety of CRISPR-based gene editing methods is of the utmost priority in clinical applications. Previous studies have reported that Cas9 cleavage induced frequent aneuploidy in primary human T cells, but whether cleavage-mediated editing of base editors would generate off-target structure variations remains unknown. Here, we investigate the potential off-target structural variations associated with CRISPR/Cas9, ABE, and CBE editing in mouse embryos and primary human T cells by whole-genome sequencing and single-cell RNA-seq analyses. The results show that both Cas9 and ABE generate off-target structural variations (SVs) in mouse embryos, while CBE induces rare SVs. In addition, off-target large deletions are detected in 32.74% of primary human T cells transfected with Cas9 and 9.17% of cells transfected with ABE. Moreover, Cas9-induced aneuploid cells activate the P53 and apoptosis pathways, whereas ABE-associated aneuploid cells significantly upregulate cell cycle-related genes and are arrested in the G0 phase. A percentage of 16.59% and 4.29% aneuploid cells are still observable at 3 weeks post transfection of Cas9 or ABE. These off-target phenomena in ABE are universal as observed in other cell types such as B cells and Huh7. Furthermore, the off-target SVs are significantly reduced in cells treated with high-fidelity ABE (ABE-V106W). This study shows both CRISPR/Cas9 and ABE induce off-target SVs in mouse embryos and primary human T cells, raising an urgent need for the development of high-fidelity gene editing tools.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142598474","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}

引用次数: 0

SpottedPy quantifies relationships between spatial transcriptomic hotspots and uncovers environmental cues of epithelial-mesenchymal plasticity in breast cancer SpottedPy 量化空间转录组热点之间的关系，揭示乳腺癌上皮-间质可塑性的环境线索

IF 12.3 1区生物学

Genome Biology Pub Date : 2024-11-11 DOI: 10.1186/s13059-024-03428-y

Eloise Withnell, Maria Secrier

引用次数: 0

scDOT: optimal transport for mapping senescent cells in spatial transcriptomics scDOT：空间转录组学中绘制衰老细胞图谱的最佳传输方式

IF 12.3 1区生物学

Genome Biology Pub Date : 2024-11-08 DOI: 10.1186/s13059-024-03426-0

Nam D. Nguyen, Lorena Rosas, Timur Khaliullin, Peiran Jiang, Euxhen Hasanaj, Jose A. Ovando-Ricardez, Marta Bueno, Irfan Rahman, Gloria S. Pryhuber, Dongmei Li, Qin Ma, Toren Finkel, Melanie Königshoff, Oliver Eickelberg, Mauricio Rojas, Ana L. Mora, Jose Lugo-Martinez, Ziv Bar-Joseph

引用次数: 0

GraphPCA: a fast and interpretable dimension reduction algorithm for spatial transcriptomics data GraphPCA：用于空间转录组学数据的快速、可解释的降维算法

IF 12.3 1区生物学

Genome Biology Pub Date : 2024-11-07 DOI: 10.1186/s13059-024-03429-x

Jiyuan Yang, Lu Wang, Lin Liu, Xiaoqi Zheng

引用次数: 0

CaClust: linking genotype to transcriptional heterogeneity of follicular lymphoma using BCR and exomic variants CaClust：利用 BCR 和外显子变异将滤泡淋巴瘤的基因型与转录异质性联系起来

IF 12.3 1区生物学

Genome Biology Pub Date : 2024-11-05 DOI: 10.1186/s13059-024-03417-1

Kazimierz Oksza-Orzechowski, Edwin Quinten, Shadi Shafighi, Szymon M. Kiełbasa, Hugo W. van Kessel, Ruben A. L. de Groen, Joost S. P. Vermaat, Julieta H. Sepúlveda Yáñez, Marcelo A. Navarrete, Hendrik Veelken, Cornelis A. M. van Bergen, Ewa Szczurek

引用次数: 0

TDFPS-Designer: an efficient toolkit for barcode design and selection in nanopore sequencing TDFPS-Designer：纳米孔测序中条形码设计和选择的高效工具包

IF 12.3 1区生物学

Genome Biology Pub Date : 2024-11-04 DOI: 10.1186/s13059-024-03423-3

Junhai Qi, Zhengyi Li, Yao-zhong Zhang, Guojun Li, Xin Gao, Renmin Han

引用次数: 0

Benchmarking and building DNA binding affinity models using allele-specific and allele-agnostic transcription factor binding data 利用等位基因特异性和等位基因不确定性转录因子结合数据制定基准并构建 DNA 结合亲和力模型

IF 12.3 1区生物学

Genome Biology Pub Date : 2024-10-31 DOI: 10.1186/s13059-024-03424-2

Xiaoting Li, Lucas A. N. Melo, Harmen J. Bussemaker

{"title":"Benchmarking and building DNA binding affinity models using allele-specific and allele-agnostic transcription factor binding data","authors":"Xiaoting Li, Lucas A. N. Melo, Harmen J. Bussemaker","doi":"10.1186/s13059-024-03424-2","DOIUrl":"https://doi.org/10.1186/s13059-024-03424-2","url":null,"abstract":"Transcription factors (TFs) bind to DNA in a highly sequence-specific manner. This specificity manifests itself in vivo as differences in TF occupancy between the two alleles at heterozygous loci. Genome-scale assays such as ChIP-seq currently are limited in their power to detect allele-specific binding (ASB) both in terms of read coverage and representation of individual variants in the cell lines used. This makes prediction of allelic differences in TF binding from sequence alone desirable, provided that the reliability of such predictions can be quantitatively assessed. We here propose methods for benchmarking sequence-to-affinity models for TF binding in terms of their ability to predict allelic imbalances in ChIP-seq counts. We use a likelihood function based on an over-dispersed binomial distribution to aggregate evidence for allelic preference across the genome without requiring statistical significance for individual variants. This allows us to systematically compare predictive performance when multiple binding models for the same TF are available. To facilitate the de novo inference of high-quality models from paired-end in vivo binding data such as ChIP-seq, ChIP-exo, and CUT&Tag without read mapping or peak calling, we introduce an extensible reimplementation of our biophysically interpretable machine learning framework named PyProBound. Explicitly accounting for assay-specific bias in DNA fragmentation rate when training on ChIP-seq yields improved TF binding models. Moreover, we show how PyProBound can leverage our threshold-free ASB likelihood function to perform de novo motif discovery using allele-specific ChIP-seq counts. Our work provides new strategies for predicting the functional impact of non-coding variants.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555785","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}

引用次数: 0

Response to "Neglecting normalization impact in semi-synthetic RNA-seq data simulation generates artificial false positives" and "Winsorization greatly reduces false positives by popular differential expression methods when analyzing human population samples" 对 "在半合成 RNA-seq 数据模拟中忽略归一化的影响会产生人为的假阳性 "和 "在分析人类群体样本时，采用流行的差异表达方法进行反向归一化可大大降低假阳性 "的回应

IF 12.3 1区生物学

Genome Biology Pub Date : 2024-10-30 DOI: 10.1186/s13059-024-03232-8

Xinzhou Ge, Yumei Li, Wei Li, Jingyi Jessica Li

引用次数: 0

Neglecting the impact of normalization in semi-synthetic RNA-seq data simulations generates artificial false positives 在半合成 RNA-seq 数据模拟中忽略归一化的影响会产生人为假阳性结果

IF 12.3 1区生物学

Genome Biology Pub Date : 2024-10-30 DOI: 10.1186/s13059-024-03231-9

Boris P. Hejblum, Kalidou Ba, Rodolphe Thiébaut, Denis Agniel

引用次数: 0