Biology subjects

di Palma, F.

Publications and source records attributed to di Palma, F..

3 recordsLinked to original sources

bioRxiv2021

Single Nucleotide Polymorphisms in the Bovine TLR2 Extracellular Domain Contribute to Breed and Species-Specific Innate Immune Functionality

Recent evidence suggests that several cattle breeds may be more resistant to infection with the zoonotic pathogen Mycobacterium bovis than others. Our data presented here suggests that the response to mycobacterial antigens varies in macrophages generated from Brown Swiss (BS) and Holstein Frisian (HF) cattle, two breeds belonging to the Bos taurus family. Whole genome sequencing of the Brown Swiss genome identified several potential candidate genes, in particular Toll-like Receptor-2 (TLR2) a pattern recognition receptor (PRR) that has previously been described to be involved in mycobacterial recognition. Further investigation revealed single nucleotide polymorphisms (SNP) in TLR2 that were identified between DNA isolated from cells of BS and HF cows. Interestingly, one specific SNP, H326Q, showed a different genotype frequency in two cattle subspecies, Bos taurus and Bos indicus. Cloning of the TLR2 gene and subsequent gene-reporter and chemokine assays revealed that this SNP, present in BS and Bos indicus breeds, resulted in a significantly higher response to mycobacterial antigens as well as tri-acylated lipopeptide ligands in general. Comparing wild-type and H326Q containing TLR2 responses, wild-type bovine TLR2 response showed clear, diminished mycobacterial antigen responses compared to human TLR2, however bovine TLR2 responses containing H326Q were found to be partially recovered compared to human TLR2. The creation of human:bovine TLR2 chimeras increased the response to mycobacterial antigens compared to the full-length bovine TLR2, but significantly reduced the response compared to the full-length human TLR2. Thus, our data, not only present evidence that TLR2 is a major PRR in the mammalian species-specific response to mycobacterial antigens, but furthermore, that there are clear differences between the response seen in different cattle breeds, which may contribute to their enhanced or reduced susceptibility to mycobacterial infection.

immunology↗

bioRxiv2021

Whole genome resequencing data enables a targeted SNP panel for conservation and aquaculture of Oreochromis cichlid fishes

Cichlid fish of the genus Oreochromis form the basis of the global tilapia aquaculture and fisheries industry. Non-native farmed tilapia populations are known to be widely distributed across Africa and to hybridize with native Oreochromis species. However, many species are difficult to distinguish morphologically, hampering attempts to maintain good quality farmed strains or to identify pure populations of native species. Here, we describe the development of a single nucleotide polymorphism (SNP) genotyping panel from whole-genome resequencing data that enables targeted species identification in Tanzania. We demonstrate that an optimized panel of 96 genome-wide SNPs based on FST outliers performs comparably to whole genome resequencing in distinguishing species and identifying hybrids. We also show this panel outperforms microsatellite-based and phenotype-based classification methods. Case studies indicate several locations where introduced aquaculture species have become established in the wild, threatening native Oreochromis species. The novel SNP markers identified here represent an important resource for assessing broodstock purity and helping to conserve unique endemic biodiversity, and in addition potentially for assessing broodstock purity in hatcheries.

evolutionary biology↗

bioRxiv2017

A quantitative model for characterizing the evolutionary history of mammalian gene expression

Characterizing the evolutionary history of a genes expression profile is a critical component for understanding the relationship between genotype, expression, and phenotype. However, it is not well-established how best to distinguish the different evolutionary forces acting on gene expression. Here, we use RNA-seq across 7 tissues from 17 mammalian species to show that expression evolution across mammals is accurately modeled by the Ornstein-Uhlenbeck (OU) process. This stochastic process models expression trajectories across time as Gaussian distributions whose variance is parameterized by the rate of genetic drift and strength of stabilizing selection. We use these mathematical properties to identify expression pathways under neutral, stabilizing, and directional selection, and quantify the extent of selective pressure on a genes expression. We further detect deleterious expression levels outside expected evolutionary distributions in expression data from individual patients. Our work provides a statistical framework for interpreting expression data across species and in disease.\n\nOne Sentence SummaryWe demonstrate the power of a stochastic model for quantifying selective pressure on expression and estimating evolutionary distributions of optimal gene expression.

genomics↗