Biology subjects

Casola, C.

Publications and source records attributed to Casola, C..

3 recordsLinked to original sources

bioRxiv2018

SimulateCNVs: a novel software application for simulating CNVs in WES and WGS data

SummarySimulateCNVs is a fast and novel software application for simulating CNVs in WES and WGS data. Current NGS simulators cannot simulate rearranged genomes and their alignment files for WES data and are not easy to use. SimulateCNVs is the first software application that can simulate CNVs in both WES and WGS data, is easy to install, has many unique features, and can output rearranged genomes, short reads and bam files in a single command.\n\nAvailabilitySimulateCNVs is freely available from https://yjulyxing.github.io/\n\nContactinumia@tamu.edu, ccasola@tamu.edu

bioinformatics↗

bioRxiv2018

From de novo to \"de nono\": most novel protein coding genes identified with phylostratigraphy represent old genes or recent duplicates

The evolution of novel protein-coding genes from noncoding regions of the genome is one of the most compelling evidence for genetic innovations in nature. One popular approach to identify de novo genes is phylostratigraphy, which consists of determining the approximate time of origin (age) of a gene based on its distribution along a species phylogeny. Several studies have revealed significant flaws in determining the age of genes, including de novo genes, using phylostratigraphy alone. However, the rate of false positives in de novo gene surveys, based on phylostratigraphy, remains unknown. Here, I re-analyze the findings from three studies, two of which identified tens to hundreds of rodent-specific de novo genes adopting a phylostratigraphy-centered approach. Most of the putative de novo genes discovered in these investigations are no longer included in recently updated mouse gene sets. Using a combination of synteny information and sequence similarity searches, I show that about 60% of the remaining 381 putative de novo genes share homology with genes from other vertebrates, originated through gene duplication, and/or share no synteny information with non-rodent mammals. These results led to an estimated rate of [~]12 de novo genes per million year in mouse. Contrary to a previous study (Wilson et al. 2017), I found no evidence supporting the preadaptation hypothesis of de novo gene formation. Nearly half of the de novo genes confirmed in this study are within older genes, indicating that co-option of preexisting regulatory regions and a higher GC content may facilitate the origin of novel genes.

genomics↗

bioRxiv2017

Pinaceae show elevated rates of gene duplication and gene loss that are robust to incomplete gene annotation

Gene duplications and gene losses are major determinants of genome evolution and phenotypic diversity. The frequency of gene turnover (gene gains and gene losses combined) is known to vary between organisms. Comparative genomic analyses of gene families can highlight such variation; however, estimates of gene turnover rates may be biased when using highly fragmented genome assemblies resulting in poor gene annotations. Here, we address potential biases introduced by gene annotation errors in estimates of gene turnover frequencies in a dataset including both well-annotated angiosperm genomes and the incomplete gene sets of four Pinaceae including two pine species, Norway spruce and Douglas-fir. Previous studies have shown low overall substitution rates, but higher levels of adaptive substitutions, in genes from Pinaceae and other gymnosperms compared to angiosperms. Conversely, our analysis suggests that pines experienced higher gene turnover rates than angiosperm lineages lacking recent whole-genome duplications. This finding is robust to both known major issues in Pinaceae gene sets: missing gene models and erroneous annotation of pseudogenes. A separate analysis limited to the four Pinaceae gene sets confirmed an accelerated gene turnover rate in pines compared to Norway spruce and Douglas-fir. Our results indicate that gene turnover significantly contributes to genome variation and possibly to adaptation and speciation in Pinaceae. Moreover, these findings indicate that reliable estimates of gene turnover frequencies can be discerned in incomplete and potentially inaccurate gene sets.

genomics↗