Skip to main content
Premium Trial:

Request an Annual Quote

Nucleic Acids Research Papers on Repaired Chromatin Analysis, Single-Molecule Dynamics, More

A team from Greece describes a strategy for following chromatin associated with newly formed DNA fragments under different conditions. The "accelerated native isolation of factors on unscheduled nascent DNA" (aniFOUND) method relies on nucleotide excision repair features and click chemistry-based chromatin isolation strategies, the researchers say. By bringing in additional "unscheduled DNA synthesis" (UDS) labeling, sequencing, and mass spec-based proteomic approaches for a related aniFOUND-seq method, for example, they looked at contributors to DNA damage repair in response to lesions formed by ultraviolet light. "By coupling nascent UDS labeling to proteomic and next generation sequencing technologies," the authors explain, "this method provides an in-depth view of the repaired chromatin-associated proteome composition and its genome-wide distribution."

Researchers from the University of Northern Iowa and elsewhere share a "kinetic event resolving algorithm" (KERA) aimed at analyzing single-molecule dynamics based on fluorescent reporter microscopy data or other colocalization single-molecule spectroscopy collections — an approach they used to track replication protein A and xeroderma pigmentosum complementation group D helicase enzyme dynamics. "KERA organizes the data in groups by transition patterns, and displays exhaustive dwell time data for each interaction sequence," the team writes. "Enumerating and quantifying sequences of molecular interactions provides important information regarding the underlying mechanism of the assembly, dynamics, and architecture of the macromolecular complexes."

Finally, a team from China's Sichuan University and Northeast Normal University describes an approach for genotyping single cells with the help of insights from nearby genome regions. The "single cell genotyper utilizing information from local genome territory" (SCOUT) approach "classifies all candidate [single-nucleotide variants (SNVs)] into homozygous, heterozygous, intermediate, and low major allele SNVs according to the highest likelihood score" by bringing in base count clues for heterozygous variants in adjacent parts of the genome, the investigators note. Their results in simulated and real single-cell sequence datasets suggest SCOUT can bump up the identification of authentic SNVs in individual cells with relatively speedy computational times compared to available single-cell genotyping strategies.