Genome Biology最新文献

Background: As the ancestor of CRISPR-Cas12 nucleases, TnpB represents the most compact gene editing tool currently available. Recent studies have identified multiple TnpB systems with gene editing activity in mammalian cells, and the potential of TnpB in treating diseases has been demonstrated in animal models. However, the editing characteristics of various TnpB systems, comparable to CRISPR tools, require more extensive investigation.

Results: Using a standardized evaluation framework, we conduct a thorough analysis of the editing properties of four TnpB variants alongside representative Cas12 and Cas9 tools applications. Overall, TnpBs exhibit intermediate editing activity and safety profiles among all tested systems, with ISYmu1 TnpB demonstrating a good performance in both editing activity and specificity. Considering its compact size, potent editing efficiency and high specificity, ISYmu1 TnpB represents a promising candidate for gene therapy.

Conclusions: By comprehensively analyzing genome editing outcomes, we characterize TnpB systems for genome editing and identify ISYmu1 TnpB as an optimal miniature RNA-guided genome editors with balanced performance, highlighting its potential for therapeutic applications.

Single-cell three-dimensional genome sequencing (sc3DG-seq) reveals genome regulation and heterogeneity in various biological processes, but a universal analysis tool is lacking. Here we present STARK, a versatile toolkit for processing, quality control, and analysis of diverse sc3DG-seq data. Utilizing STARK, we benchmark 15 technologies, quantitatively comparing their strengths and limitations. We also develop EmptyCells to filter empty barcodes and introduce Spatial Structure Capture Efficiency (SSCE) to assess chromatin structure capture quality. Additionally, we establish scNucleome, a uniformly processed repository of sc3DG-seq datasets, to serve as a foundational resource for future 3D genome research.

Background: Deconvolution of bulk RNA-expression data unlocks the cellular complexity of cancer, yet traditional pseudobulk benchmarks may not always be reliable in real-world settings where absolute cell proportions are unknown.

Results: Here, we introduce a novel real-data framework, leveraging 18 real bulk RNA-expression cohorts (5,891 samples) across nine cancer types to evaluate five deconvolution methods based on differentially proportioned (DP) and prognosis-related (PR) cell types. Across three innovative benchmark scenarios-consistency with scRNA-seq, reproducibility across cohorts, and reproducibility of prognostic relevance-ReCIDE and BayesPrism stand out as two robust deconvolution methods. Application of a pan-cancer analysis based on the deconvolution of TCGA cohorts identifies matrix cancer-associated fibroblasts (mCAF) as a prognostic marker with consistent effects across multiple cancers. Building on this finding, we find a prognostic indicator combining classical monocytes and mCAF cell proportions to be significant in five TCGA cohorts, which we further validate in five independent GEO cohorts.

Conclusions: This study broadens deconvolution benchmarking, offering actionable tools for precision oncology and guiding method selection for translational research.

Background: While height is a highly heritable trait with strong polygenic prediction, previous studies have postulated that minimal variation of its individual differences can be captured by DNA methylation (DNAm). We investigated the role of blood-based genome-wide DNAm in capturing the variance in adult height in a large population-based cohort of 7,654 unrelated individuals from Generation Scotland using DNAm profiled on the Illumina EPIC array. The posterior DNAm probe effects were used to construct a DNAm profile score (Methylation Profile Score-MPS) which was evaluated in three independent cohorts.

Results: Genome-wide DNAm captures 25.0% (95% credible interval (CrI) 17.2-31.9) of the phenotypic variation in height when applying Bayesian penalised regression using BayesR + conditional on genetic effects. The total variation captured jointly by DNAm and genetic effects (80.3%, 95% CrI 70.1-87.2) is larger than the marginal estimate based on genetic effects only (56.3%, 95% CrI 45.8-66.8). Out-of-sample prediction shows that the MPS is weakly correlated with measured height (Pearson correlation ranging from 0.14-0.26), as well as being associated with several health and lifestyle factors in the LBC1936 that are established correlates of height.

Conclusion: With the advent of larger sample sizes in epigenomics anticipated to improve the power to detect associations between DNAm and complex traits, we urge caution when making assumptions around "null traits" based solely on methylome-wide association study results and encourage the use of whole-genome methods to assess the proportion of variation in a trait that may be captured by DNAm.

Background: Transposable elements (TEs) occupy nearly half of the human genome and play diverse biological roles. Despite their abundance, the extent to which TEs contribute to three-dimensional (3D) genome structure remains unclear.

Results: To investigate this, we generate a modified Hi-C analysis pipeline to probe TE-associated chromatin interactions. Our analysis reveals that TE sequences are responsible for 3D genome structure in interphase nuclei. This phenomenon is mediated by the recruitment of specific epigenetic/transcription factors to TEs, which both promote and impair chromatin contacts. We computationally identified known factors positively associated with chromatin contacts (CTCF, RAD21, SMC3) and chromatin contact impairing proteins (RNF2). Additionally, we identiy potential novel factors (SMARCA4, MAFK), which, when knocked down, lead to decreased chromatin contacts and loops at and between TEs. Notably, SMARCA4 knockdown selectively reduce short-range contacts, highlighting its role in maintaining 3D genome structure through TE binding.

Conclusions: Overall, our findings demonstrate that TEs are crucial determinants of 3D genome organization in mammalian cells.

Background: Drought is a major abiotic stress that affects the growth and yield of maize. Alternative transcripts are crucial in abiotic stress responses in plants. However, the genetic basis of alternative transcripts mediated drought response in maize remains largely unknown.

Results: We characterize thousands of drought-responsive genes based on the transcriptomic dataset of 197 maize association population under well-watered and drought-stressed conditions. We perform mRNA profiling of the seedlings at six-leaf stage under drought stress. Through co-expression analysis and experimental validation, we identify a splicing associated factor ZmMBF1, which positively regulates drought response in maize. We also detect thousands of alternative transcript QTLs (atQTLs) and expression QTLs (eQTLs), some of them are linked with stress responsive genes under well-watered and drought-stressed conditions, respectively. Co-localization analysis demonstrates that most of the natural variations in alternative transcripts and gene expression levels are regulated independently by different sequence variations. Variations in transposons, inverted repeats, and UA-rich sequences are significantly associated with atQTLs, suggesting important roles of these variations in regulating alternative transcripts and drought response. As proof of concept, we demonstrate that variations in UA-rich sequence of ZmPYL8 intron regulate drought resistance by affecting ZmPYL8 alternative transcripts, generating two transcripts that function antagonistically in regulating ABA signaling and drought response.

Conclusions: This study reveals the response of maize alternative transcripts to drought at the population level, illustrating the pivotal roles of intron variations in regulating maize alternative transcripts and drought response. It also provides genetic resources and theoretical basis for breeding maize with drought-resistance.

Emerging DNA language models provide powerful tools to address the challenge of accurately predicting chromatin loops, fundamental structures governing 3D genome organization and gene regulation. Here we present CLAMP, which utilizes a deep language model pre-trained on broad cross-species chromatin accessibility data. CLAMP achieves superior performance compared to existing methods in predicting specific protein-mediated loops across 10 species, 18 proteins, and 24 cell types. CLAMP incorporates a novel CoVE explainer that reveals context-dependent genomic feature contributions, providing insights into the features driving predictions. CLAMP predictions effectively identify functionally significant chromatin loops and associated biological pathways.

RNA editing by adenosine deaminases acting on RNA (ADARs) is an essential cellular process performed by three enzymes in mammals: ADAR1-p150, ADAR1-p110, and ADAR2, demonstrating different target specificity and selectivity. Here we describe TSniffer, a novel tool to analyze RNA editing in RNA-sequencing datasets. TSniffer uses a rolling window approach to identify editing sites and operates in two modes allowing identification and quantification in single samples, and quantification in predefined regions across multiple datasets. Using wild type and ADAR-deficient datasets, we provide strategies for identification of ADAR editing sites and verify the accuracy and biological relevance of our findings.

Background: The human gut microbiota exhibits significant diversity across populations, influenced by factors such as geography, diet, and lifestyle, particularly between the Han Chinese and non-Chinese populations. While previous studies have predominantly focused on the taxonomic abundance of the gut microbiome, the impact of single nucleotide polymorphisms (SNPs) in driving population-specific differences remains largely underexplored.

Results: In this study, we systematically investigated gut microbial differences between the Han Chinese and non-Chinese populations using the Human Gut Microbiome Reference Genome Catalog (HGMRGC). We observed geography was the primary driver of microbial variation of abundance and SNPs. We identified 689 population-specific genome clusters from the Collinsella genus with functional differences in carbohydrate utilization and 108 species exhibiting distinct prevalence related to vitamin biosynthesis, antibiotic resistance, and carbohydrate metabolism. Beta diversity analysis highlighted significant inter-population differences in both microbial abundance and SNPs, while alpha diversity analysis revealed that non-Chinese populations exhibited higher diversity in microbial abundance, and Han Chinese populations displayed greater diversity in SNPs.

Conclusions: This study offers a comprehensive analysis of gut microbial differences between Han Chinese and non-Chinese populations, highlighting the profound influence of population-specific traits on microbial diversity and function. We also provide a comprehensive human gut microbial reference genome catalog, with a particular focus on the Han Chinese population, laying a foundation for future research on gut microbiota genomic variations.

Background: Northwestern Xinjiang is situated at the confluence of the central Eurasian Steppe, the Inner Asian Mountain Corridor and the Tianshan mountains, and is home to rich archaeological, cultural and genetic diversity. However, the local population dynamics remain poorly understood due to the lack of time-series ancient DNA data.

Results: We analyze DNA from ten individuals from the Narensu site in northwestern Xinjiang spanning the Chalcolithic to the Iron Age. Our findings reveal that the earliest inhabitants of northwestern Xinjiang were formed by a genetic admixture of Ancient North Eurasians and Altai hunter-gatherers around 6000 years ago. The simultaneous arrival of ancestry related to the Bactria Margiana Archaeological Complex from Central Asia and Afanasievo-related populations from the Steppe in the early Bronze Age was detected, thereby highlighting the important role of the Inner Asian Mountain Corridor as a migration route between southern Central Asia and Xinjiang. This may also have involved the formation of the Chemurchek population in Altai, northern Xinjiang bordering Russia. Eurasian steppe ancestry identified in Narensu has changed to the late Bronze Age Sintashta populations, and eastern Eurasian ancestry from Baikal turns prominent since the Iron Age.

Conclusions: Here, by reconstructing the population dynamics from the Chalcolithic to the Iron Age, our study reveals that the Narensu inhabitants have continuously accumulated with multiple waves of gene influx from surrounding regions. Altogether, these findings provide a comprehensive picture into the population fusion history of northwestern Xinjiang as well as across the Eurasian continent.