RNA-Seq Profiling between Commercial and Indigenous Iranian Chickens Highlights Differences in Innate Immune Gene Expression.

The purpose of the current study was to examine transcriptomic-based profiling of differentially expressed innate immune genes between indigenous and commercial chickens. In order to compare the transcriptome profiles of the different chicken breeds, we extracted RNA from blood samples of the Isfahan indigenous chicken (as indigenous) and Ross broiler chicken (as commercial) breeds. RNA-Seq yielded totals of 36,763,939 and 31,545,002 reads for the indigenous and commercial breeds, respectively, with clean reads then aligned to the chicken reference genome (Galgal5).

investigation of uncoupling protein function in avian genomes.

Introduction: The uncoupling proteins () are involved in lipid metabolism and belong to a family of mitochondrial anionic transporters. In poultry, only one homologue has been identified and experimentally shown to be associated with growth, feed conversion ratio, and abdominal fat according to its predominant expression in bird muscles. In endotherm birds, cell metabolic efficiency can be tuned by the rate of mitochondrial coupling.

Estimation of genetic parameters for production, reproduction, and growth curve of Fars indigenous chicken.

Iranian native chicken, including Fars indigenous chicken, is an important genetic resource due to its adaptation to stressful environmental conditions, good endurance and resistance to disease. The aim of this research was to determine the genetic infrastructure of Fars indigenous chicken using several nonlinear functions. The dataset included body weight at hatch (BW1), body weight at the 8th week (BW8), body weight at the 12th week (BW12), weight at sexual maturity (WSM), age at sexual maturity (ASM), number of eggs in the first 12 weeks of laying period (EN), egg weight at the first day of laying (EW1), average egg weight at the 28thday of laying (EW28), and average egg weight at weeks 28, 30, and 32 of the laying period (AEW).

An Integrated Bioinformatics Approach to Identify Network-Derived Hub Genes in Starving Zebrafish.

The present study was aimed at identifying causative hub genes within modules formed by co-expression and protein-protein interaction (PPI) networks, followed by Bayesian network (BN) construction in the liver transcriptome of starved zebrafish. To this end, the GSE11107 and GSE112272 datasets from the GEO databases were downloaded and meta-analyzed using the MetaDE package, an add-on R package. Differentially expressed genes (DEGs) were identified based upon expression intensity N(µ = 0.