367 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.
This paper introduces BALT-seq, a unified, enzyme-free chemoselective strategy that enables efficient, one-step profiling of hydroxymethylcytosine in both DNA and RNA by installing a biotin-thioether handle under mild acidic bisulfite conditions.
The paper introduces Epi-PoreC, a novel Oxford Nanopore-based method that simultaneously profiles chromatin conformation, DNA methylation, and chromatin accessibility on individual DNA molecules within a single assay.
This study demonstrates that high carrier rates of Familial Mediterranean Fever mutations in Armenians resulted from positive selection driven by resistance to *Yersinia pestis* (plague), with allele frequencies rapidly increasing since the first plague pandemic around 541 CE.
This study reveals that RNA structure, in concert with oscillating helicase levels, globally coordinates stage-specific translation dynamics across hundreds of mRNAs during yeast meiosis to ensure proper progression when transcription is constrained.
This study reveals that parasexual reproduction, characterized by meiotic-independent processes like chromosome-wide loss of heterozygosity, aneuploidy, and ploidy reduction, drives the genomic diversity and phenotypic variation of three distinct hybrid groups in the human pathogen *Cryptococcus neoformans*.
This study introduces a multi-task neural network framework that effectively predicts blood metabolite profiles by separating genetic, covariate, and joint contributions, revealing that nonlinear modeling of covariates—particularly age—is the primary driver of improved predictive performance over traditional linear methods.
The PEGASUS framework establishes the first community-developed standard for reporting predicted effector genes in GWAS by defining a unified schema for metadata, evidence matrices, and prioritized gene lists to enhance the interoperability, reproducibility, and reusability of variant-to-function research.
This study demonstrates that multigenerational genomic prediction for dermo disease resistance in Eastern oysters is significantly enhanced by machine learning, specifically gradient boosting models, which leverage rare genetic variants to achieve a peak correlation accuracy of 0.410, substantially outperforming traditional methods.
The paper introduces Apollo 3, a scalable, collaborative manual genome annotation tool built on JBrowse 2 that enables simultaneous multi-genome editing and synteny visualization.
This study reveals that upon UV irradiation, RNA polymerase II and XPC actively remodel the 3D genome by constraining loop extrusion to shorten chromatin loops and reinforce domains, thereby creating a repair-permissive state that facilitates efficient nucleotide excision repair.