414 papers
Genomics is the study of an organism's complete set of DNA, offering a deep dive into the biological instructions that shape life. This field explores how genetic information influences traits, health, and evolution, moving beyond single genes to understand the complex interplay within entire genomes. From uncovering the roots of disease to mapping biodiversity, genomics provides the foundational data for many modern medical breakthroughs.
At Gist.Science, we process every new preprint in this category as it appears on bioRxiv, ensuring you stay ahead of the curve. Each paper is accompanied by both a clear, plain-language overview and a detailed technical summary, making cutting-edge research accessible to everyone regardless of their background. Below are the latest papers in genomics, freshly summarized and ready for you to explore.
By applying a cosinor-based framework to GTEx data, this study identifies 167 circadian expression QTLs that reveal how genetic variation shapes tissue-specific rhythmic gene expression and links these dynamic regulatory effects to diverse human phenotypes, demonstrating that accounting for sampling time uncovers genetic influences missed by static analyses.
This study reveals that CTCF gradually acquired novel functional modalities, including its role as a major architectural protein for loop extrusion and its association with transcription start sites, through progressive evolutionary changes in its N-terminal region and binding site characteristics during bilaterian evolution.
The authors introduce Micro-C-TALE, a cost-effective, BAC-based targeted method that combines Micro-C and C-TALE to generate high-resolution chromatin interaction maps with significantly lower sequencing depth than genome-wide approaches, enabling the detection of fine-scale structural changes such as those induced by CRISPR-mediated CTCF site insertion.
By tracking de novo copy number alterations in individual cancer cells across multiple types, this study reveals that chromosomal instability acts as a potent, stochastic mutational force generating 1–5 new alterations per cell cycle, which drives acute genome flux, correlates with genomic complexity, and facilitates convergent evolution under chemotherapy pressure.
The paper introduces PETRO, a method that enables robust estimation of on-target perturbation effects in Perturb-seq by leveraging guide agreement to effectively filter out off-target biases that persist even after standard pooling and filtering.
The paper introduces Carbon-A, a unified 1.2-billion-parameter encoder model that achieves state-of-the-art structural genome annotation across diverse eukaryotic lineages using only genomic sequences, and leverages this capability to build the Carbon Annotation Database (CADB), a comprehensive resource containing predicted gene models for over 48,000 assemblies that significantly expands upon existing reference databases.
This study utilizes Oxford Nanopore long-read sequencing and DNAscent to map the first replication timing programme of the malaria parasite *Plasmodium falciparum*, revealing its relationship to DNA breakage and transient replication fork stalling.
By combining range-wide genomic data with intensive cohort sampling, this study demonstrates that maritime pine exhibits rapid evolutionary responses to contemporary climate change within a single generation, evidenced by shifts in climate-associated loci and reduced genetic load, despite the persistence of widespread adaptive lag.
This study utilizes long-read sequencing and a novel computational workflow (ALLR) to reveal that SF3B1 mutations generate thousands of alternative-spliced long non-coding RNAs capable of producing immunogenic peptides and serving as prognostic biomarkers in chronic lymphocytic leukemia.
By systematically perturbing the complete human genome using Nucleotide Transformer v3, researchers mapped a higher-order network of nucleotide dependencies called "relons" that reveals a new layer of genomic organization beyond linear and 3D structures, offering a framework to interpret genetic variation and disease.