Biology subjects

Ranathunge, C.

Publications and source records attributed to Ranathunge, C..

3 recordsLinked to original sources

bioRxiv2022

promor: a comprehensive R package for label-free proteomics data analysis and predictive modeling

SummaryWe present promor, a comprehensive, user-friendly R package that streamlines label-free (LFQ) proteomics data analysis and building machine learning-based predictive models with top protein candidates. Availability and implementationpromor is freely available as an open source R package on the Comprehensive R Archive Network (CRAN)(https://CRAN.R-project.org/package=promor) and distributed under the Lesser General Public License (version 2.1 or later). Development version of promor is maintained on GitHub (https://github.com/caranathunge/promor) and additional documentation and tutorials are provided on the package website (https://caranathunge.github.io/promor/). Contactcaranathunge86@gmail.com

bioinformatics↗

bioRxiv2021

A comparative study of population genetic structure reveals patterns consistent with selection at functional microsatellites in common sunflower

Microsatellites have long been considered non-functional, neutrally evolving regions of the genome. Recent findings suggest that they can function as drivers of rapid adaptive evolution. Previous work on common sunflower identified 479 transcribed microsatellites where allele length significantly correlates with gene expression (eSTRs) in a stepwise manner. Here, a population genetic approach is used to test whether eSTR allele length variation is under selection. Genotypic variation among and within populations at 13 eSTRs was compared with that at 19 anonymous microsatellites in 672 individuals from 17 natural populations of sunflower from across a cline running from Saskatchewan to Oklahoma. Expected heterozygosity, allelic richness, and allelic diversity were significantly lower at eSTRs, a pattern consistent with higher relative rates of purifying selection. Further, an analysis of variation in microsatellite allele lengths (lnRV), and heterozygosities (lnRH), indicate recent selective sweeps at the eSTRs. Mean microsatellite allele lengths at four eSTRs within populations are significantly correlated with latitude consistent with the predictions of the tuning knob model which predicts stepwise relationships between microsatellite allele length and phenotypes. This finding suggests that shorter or longer alleles at eSTRs may be favored in climatic extremes. Collectively, our results imply that eSTRs are likely under selection and that they may be playing a role in facilitating local adaptation across a well-defined cline in the common sunflower.

evolutionary biology↗

bioRxiv2018

Transcribed microsatellites often influence gene expression in natural sunflower populations

Microsatellites are common in most species. While an adaptive role for these highly mutable regions has been considered, little is known concerning their contribution towards phenotypic variation. We used populations of the common sunflower (Helianthus annuus) at two latitudes to quantify the effect of microsatellite allele length on phenotype at the level of gene expression. We conducted a common garden experiment with seed collected from sunflower populations in Kansas and Oklahoma followed by an RNA-Seq experiment on 95 individuals. The effect of microsatellite allele length on gene expression was assessed across 3325 microsatellites that could be consistently scored. Our study revealed 479 microsatellites at which allele length significantly correlates with gene expression (eSTRs). When irregular allele sizes not conforming to the motif length were removed, the number of eSTRs rose to 2379. The percentage of variation in gene expression explained by eSTRs ranged from 1-86% when controlling for population and allele-by-population interaction effects at the 479 eSTRs. Of these, 70.4% are in untranslated regions (UTRs). A Gene Ontology (GO) analysis revealed that eSTRs are significantly enriched for GO terms associated with cis- and trans-regulatory processes. These findings suggest that a substantial number of transcribed microsatellites can influence gene expression.

evolutionary biology↗