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Current evidence suggests that cis-regulatory elements controlling gene expression may be the predominant target of natural selection in humans and other species. Detecting selection acting on these elements is c...
The oncogenic protein HOXA9 plays a critical role in leukemia transformation and maintenance, and its aberrant expression is a hallmark of most aggressive acute leukemia. Although inhibiting the upstream regul...
The three-dimensional genome organization influences diverse nuclear processes. Here we present Chromatin Interaction Predictor (ChIPr), a suite of regression models based on deep neural networks, random fores...
Existing methods for analysis of spatial transcriptomic data focus on delineating the global gene expression variations of cell types across the tissue, rather than local gene expression changes driven by cell...
CRISPR interference (CRISPRi) is the leading technique to silence gene expression in bacteria; however, design rules remain poorly defined. We develop a best-in-class prediction algorithm for guide silencing e...
The cost and complexity of generating a complete reference genome means that many organisms lack an annotated reference. An alternative is to use a de novo reference transcriptome. This technology is cost-effe...
Transcription factors bind DNA in specific sequence contexts. In addition to distinguishing one nucleobase from another, some transcription factors can distinguish between unmodified and modified bases. Curren...
The history of yeast Saccharomyces cerevisiae, aka brewer’s or baker’s yeast, is intertwined with our own. Initially domesticated 8,000 years ago to provide sustenance to our ancestors, for the past 150 years, ye...
To analyze the large volume of data generated by single-cell technologies and to identify cellular correlates of particular clinical or experimental outcomes, differential abundance analyses are often applied....
Dramatic improvements in measuring genetic variation across agriculturally relevant populations (genomics) must be matched by improvements in identifying and measuring relevant trait variation in such populati...
The cost-free increase in statistical power of using imputation to infer missing genotypes is undoubtedly appealing, but is it hazard-free? This case study of three type-2 diabetes (T2D) loci demonstrates that...
The original article was published in Genome Biology 2024 25:4
The original article was published in Genome Biology 2021 22:26
Transposable elements (TEs) are important drivers of genome evolution. Nonetheless, TE annotation remains a complex and challenging task. As more genomes from phylogenetically diverse species are published, a ...
The original article was published in Genome Biology 2019 20:275
The Correspondence to this article has been published in Genome Biology 2024 25:6
The majority of disease-associated variants identified through genome-wide association studies are located outside of protein-coding regions. Prioritizing candidate regulatory variants and gene targets to iden...
Formation of tissue-specific transcriptional programs underlies multicellular development, including dorsoventral (DV) patterning of the Drosophila embryo. This involves interactions between transcriptional enhan...
The vast majority of findings from human genome-wide association studies (GWAS) map to non-coding sequences, complicating their mechanistic interpretations and clinical translations. Non-coding sequences that ...
Variants that disrupt mRNA splicing account for a sizable fraction of the pathogenic burden in many genetic disorders, but identifying splice-disruptive variants (SDVs) beyond the essential splice site dinucle...
Imaging-based spatial transcriptomics techniques provide valuable spatial and gene expression information at single-cell resolution. However, their current capability is restricted to profiling a limited numbe...
Capturing the genetic diversity of wild relatives is crucial for improving crops because wild species are valuable sources of agronomic traits that are essential to enhance the sustainability and adaptability ...
Many deep learning-based methods have been proposed to handle complex single-cell data. Deep learning approaches may also prove useful to jointly analyze single-cell RNA sequencing (scRNA-seq) and single-cell ...
Spatial omics technologies can help identify spatially organized biological processes, but existing computational approaches often overlook structural dependencies in the data. Here, we introduce Smoother, a u...
Metabolites play critical roles in regulating nutritional qualities of plants, thereby influencing their consumption and human health. However, the genetic basis underlying the metabolite-based nutrient qualit...
Deconvolution of cell mixtures in “bulk” transcriptomic samples from homogenate human tissue is important for understanding disease pathologies. However, several experimental and computational challenges imped...
The coordinated transcriptional regulation of activated T-cells is based on a complex dynamic behavior of signaling networks. Given an external stimulus, T-cell gene expression is characterized by impulse and ...
Long-read RNA sequencing has emerged as a powerful tool for transcript discovery, even in well-annotated organisms. However, assessing the accuracy of different methods in identifying annotated and novel trans...
Expression quantitative trait locus (eQTL) analysis has emerged as an important tool in elucidating the link between genetic variants and gene expression, thereby bridging the gap between risk SNPs and associa...
Point mutations in histone variant H3.3 (H3.3K27M, H3.3G34R) and the H3.3-specific ATRX/DAXX chaperone complex are frequent events in pediatric gliomas. These H3.3 point mutations affect many chromatin modific...
Strain-level diversity is widespread among bacterial species and can expand the functional potential of natural microbial communities. However, to what extent communities undergo consistent shifts in strain co...
Many elite genes have been identified from the available cotton genomic data, providing various genetic resources for gene-driven breeding. However, backbone cultivar-driven breeding is the most widely applied...
GCLiPP is a global RNA interactome capture method that detects RNA-binding protein (RBP) occupancy transcriptome-wide. GCLiPP maps RBP-occupied sites at a higher resolution than phase separation-based techniqu...
Genotype imputation is an essential step in genetic studies to improve data quality and statistical power. Public imputation servers are widely used by researchers to impute their data using otherwise access-c...
The dikaryotic stage dominates most of the life cycle in basidiomycetes, and each cell carries two different haploid nuclei. Accurate phasing of these two nuclear genomes and their interactions have long been ...
Identifying host factors is key to understanding RNA virus pathogenicity. Besides proteins, RNAs can interact with virus genomes to impact replication.
Epigenetic scores (EpiScores) can provide biomarkers of lifestyle and disease risk. Projecting new datasets onto a reference panel is challenging due to separation of technical and biological variation with ar...
MALDI-TOF MS-based microbial identification relies on reference spectral libraries, which limits the screening of diverse isolates, including uncultured lineages. We present a new strategy for broad-spectrum i...
Recent state-of-the-art sequencing technologies enable the investigation of challenging regions in the human genome and expand the scope of variant benchmarking datasets. Herein, we sequence a Chinese Quartet,...
Small regulatory RNAs pervade prokaryotes, with the best-studied family of these non-coding genes corresponding to trans-acting regulators that bind via base pairing to their message targets. Given the increasing...
Although generally superior, hybrid approaches for correcting errors in third-generation sequencing (TGS) reads, using next-generation sequencing (NGS) reads, mistake haplotype-specific variants for errors in ...
As a single reference genome cannot possibly represent all the variation present across human individuals, pangenome graphs have been introduced to incorporate population diversity within a wide range of genom...
Spatial transcriptomic technologies, such as the Visium platform, measure gene expression in different regions of tissues. Here, we describe new software, STmut, to visualize somatic point mutations, allelic i...
A tumor contains a diverse collection of somatic mutations that reflect its past evolutionary history and that range in scale from single nucleotide variants (SNVs) to large-scale copy-number aberrations (CNAs...
Common diseases manifest differentially between patients, but the genetic origin of this variation remains unclear. To explore possible involvement of gene transcriptional-variation, we produce a DNA methylati...
Genomic DNA reference materials are widely recognized as essential for ensuring data quality in omics research. However, relying solely on reference datasets to evaluate the accuracy of variant calling results...
Systematic characterization of how genetic variation modulates gene regulation in a cell type-specific context is essential for understanding complex traits. To address this question, we profile gene expressi...
Enhancer dysregulation is one of the important features for cancer cells. Enhancers enriched with H3K4me3 have been implicated to play important roles in cancer. However, their detailed features and regulatory...
RNA editing has been described as promoting genetic heterogeneity, leading to the development of multiple disorders, including cancer. The cytosine deaminase APOBEC3B is implicated in tumor evolution through D...
Linking cis-regulatory sequences to target genes has been a long-standing challenge. In this study, we introduce CREaTor, an attention-based deep neural network designed to model cis-regulatory patterns for genom...
“Red tides” are harmful algal blooms caused by dinoflagellate microalgae that accumulate toxins lethal to other organisms, including humans via consumption of contaminated seafood. These algal blooms are drive...
Differential analysis of bulk RNA-seq data often suffers from lack of good controls. Here, we present a generative model that replaces controls, trained solely on healthy tissues. The unsupervised model learns...
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