Rapid Targeted Assembly of the Proteome Reveals Evolutionary Variation of GC Content in Avian Lice.

Nucleotide base composition plays an influential role in the molecular mechanisms involved in gene function, phenotype, and amino acid composition. GC content (proportion of guanine and cytosine in DNA sequences) shows a high level of variation within and among species. Many studies measure GC content in a small number of genes, which may not be representative of genome-wide GC variation. One challenge when assembling extensive genomic data sets for these studies is the significant amount of resources (monetary and computational) associated with data processing, and many bioinformatic tools have not been optimized for resource efficiency. Using a high-performance computing (HPC) cluster, we manipulated resources provided to the targeted gene assembly program, automated target restricted assembly method (aTRAM), to determine an optimum way to run the program to maximize resource use. Using our optimum assembly approach, we assembled and measured GC content of all of the protein-coding genes of a diverse group of parasitic feather lice. Of the 499 426 genes assembled across 57 species, feather lice were GC-poor (mean GC = 42.96%) with a significant amount of variation within and between species (GC range = 19.57%-73.33%). We found a significant correlation between GC content and standard deviation per taxon for overall GC and GC3, which could indicate selection for G and C nucleotides in some species. Phylogenetic signal of GC content was detected in both GC and GC3. This research provides a large-scale investigation of GC content in parasitic lice laying the foundation for understanding the basis of variation in base composition across species.

Decoding chromosome organization using CheC-PLS: chromosome conformation by proximity labeling and long-read sequencing.

Genomic approaches have provided detailed insight into chromosome architecture. However, commonly deployed techniques do not preserve connectivity-based information, leaving large-scale genome organization poorly characterized. Here, we developed CheC-PLS: a proximity-labeling technique that indelibly marks, and then decodes, protein-associated sites. CheC-PLS tethers dam methyltransferase to a protein of interest, followed by Nanopore sequencing to identify methylated bases - indicative of in vivo proximity - along reads >100kb. As proof-of-concept we analyzed, in budding yeast, a cohesin-based meiotic backbone that organizes chromatin into an array of loops. Our data recapitulates previously obtained association patterns, and, importantly, exposes variability between cells. Single read data reveals cohesin translocation on DNA and, by anchoring reads onto unique regions, we define the internal organization of the ribosomal DNA locus. Our versatile technique, which we also deployed on isolated nuclei with nanobodies, promises to illuminate diverse chromosomal processes by describing the in vivo conformations of single chromosomes.