Gene Expression Analysis on Apoptosis network and design it in Esfahani and Ross Breeds

Economic pressure on the modern poultry industry has directed the selection process towards fast-growing broilers that have a reduced feed conversion ratio. Selection based heavily on growth characteristics could adversely affect immune competence leaving chickens more susceptible to disease. Native breeds of chickens are playing an important role in rural economies in most of the developing and underdeveloped countries. The immune system is an adaptive defensed at evolved in phylogenesis to control an organism’s integrity and apoptosis system is involved in many immune system mechanisms and diseases therefore this study has emphasized on apoptosis system. Recently, next generation sequencing technology (RNA-Seq) has become available as a powerful tool to investigate transcriptional profiles for gene expression analysis of many organisms. So, we performed comparative gene expression analysis of native and commercial chickens by RNAsequencing technology, in order to, detect differentially expressed genes involved in apoptosis in native and commercial breed poultry.
The chicken in this study was female from Esfahani and Ross breeds (47 days of age). The blood samples were collected from Brachial/ulnar wing vein; 5 ml was taken. The total RNA was extracted by using Trizol (Invitrogen, USA) according to the manufacture's protocol. The RNA pool was prepared by mixing together equal quantities of three RNA samples per group/ Total RNA was sent to BGI Company (China) for paired-end sequencing by an Illumina Hiseq 2000 platform and the raw reads were generated. Approximately 18 million fragments were sequenced with length of 150 bp. The quality of the row data was checked with Fast QC vol 0.11.2 and Trimmomatic (v 0.35) were used to remove Illumina adaptors, trimming of reads as well as quality or filtering reads by removing low-quality reads. The reads passed the quality control were mapped to the reference genome using Tophat2 (v2.1.1). For aligning and DE analyzing were used cufflinks, cuffmerge and cuffdiff. Then significant DEGs imported to String for creating gene expression network and use DAVID 6.8 for investigation gene annotation and pathway analysis and finally Cytoscape v. 3.5.1 was used for network and cluster analysis.
Among 1328 significant differentially expressed genes in immune system, 11 genes were identified in a pathway in KEGG database, which named apoptosis genes. Gene ontology has been shown that the most significant biological process term containing 4 genes in term of GO: 1900182 positive regulation of protein localization to nucleus. The apoptosis genes Network analysis showed that number of nods was 11, number of edges was 20, average of degree was 3.64, average local clustering coefficient was0.621. Furthermore, analysis of apoptosis gene networks by Cytoscape showed that PIK3R1 had the highest value by degree. Beside of this result, AKT1 and CSF2RB had the highest value by Beetwinness Centrality. The highest out degree and the lowest in degree were related to AKT1.
Overall, 3 apoptic genes including PIK3R1, AKT1 and CSF2RB were recognized as very important in breeding poultry. According to involving apoptic genes in disease and Innate immune system, we mayuse these genes in breeding plans. We can regulate them with appropriate cell and molecular methods or using epigenetic procedures.