Ferdowsi University of Mashhad

Document Type : Research Articles


1 Ferdowsi University of Mashhad

2 University of Tehran

3 Ramin Agriculture and Natural Resources University


The poultry industry occupies an important position in the provision of animal protein. 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. The main use of RNA-Seq in agriculture species are focusing on finding the immune related genes or pathways by comparison of the whole transcriptome following pathogen challenge. Alternative splicing (AS) is the major fundamental mechanism generating the protein diversity and regulating the gene expression in eukaryotic organism. Identifying genes that are differentially spliced between two groups of RNA-sequencing samples is interesting subject in transcriptome with next-generation sequencing technology in this study used RNA sequencing to comparison isoforms of two breeds. A total of 64,819 transcripts were identified by aligning sequence reads to genome among the evaluated isoforms for expression analysis, 310 were significantly differentially expressed between two breeds, including 251 up-regulated and 59 down-regulated. The KEGG results of up regulated isoforms showed that that no pathway was found significantly different (FDR ≤ 0.05). However, enrichment analysis suggested that seven were over-represented (P-value ≤ 0.05) within the up regulated isoforms. Only one of them functionally related to immune system, natural killer cell mediated cytotoxicity. The results showed genes which are breed-specific expression and the comparative transcriptome analysis help to understand the difference of genetic mechanism.


1.Black D. L. (2003) Mechanisms of alternative pre-messenger RNA splicing. Annual Review of Biochemistry 72:291-336.
2.Bolger A. M., Lohse M. and Usadel B. (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics:btu170.
3.Caceres J. F. and Kornblihtt A. R. (2002) Alternative splicing: multiple control mechanisms and involvement in human disease. TRENDS in Genetics 18:186-193.
4.Cheng H. H., Kaiser P. and Lamont S. J. (2013) Integrated genomic approaches to enhance genetic resistance in chickens. Annu. Rev. Anim. Biosci. 1:239-260.
5.Dennis G., Sherman B. T., Hosack D. A., Yang J., Gao W., Lane H. C. and Lempicki R. A. (2003) DAVID: database for annotation, visualization, and integrated discovery. Genome biology 4:1.
6.Jeong H.-S., Kim D.-W., Chun S.-Y., Sung S., Kim H.-J., Cho S., Kim H. and Oh S.-J. (2014) Native Pig and Chicken Breed Database: NPCDB. Asian-Australasian journal of animal sciences 27:1394.
7.Kim D., Langmead B. and Salzberg S. L. (2015) HISAT: a fast spliced aligner with low memory requirements. Nature methods 12:357-360.
8.Li E. and Li C. (2014) Use of RNA-seq in aquaculture research. Poultry Fish Wildlife Sci 2:e108.
9.Li H. and Homer N. (2010) A survey of sequence alignment algorithms for next-generation sequencing. Briefings in bioinformatics 11:473-483.
10.Mohammed B. R. and Sunday O. S. (2015) An Overview of the Prevalence of Avian Coccidiosis in Poultry Production and Its Economic Importance in Nigeria. Veterinary Research 3:35-45.
11.Muir W. M. and Aggrey S. E. 2003. Poultry Genetics, Breeding, and Biotechnology. CABI.
12.Perumbakkam S., Muir W. M., Black-Pyrkosz A., Okimoto R. and Cheng H. H. (2013) Comparison and contrast of genes and biological pathways responding to Marek’s disease virus infection using allele-specific expression and differential expression in broiler and layer chickens. BMC genomics 14:1.
13.Sandford E. E. (2011) Whole transcriptome response of chicken spleen and peripheral blood leukocytes to avian pathogenic Escherichia coli.
14.Swaggerty C. L., Pevzner I. Y., He H., Genovese K. J., Nisbet D. J., Kaiser P. and Kogut M. H. (2009) Selection of broilers with improved innate immune responsiveness to reduce on-farm infection by foodborne pathogens. Foodborne Pathogens and Disease 6:777-783.
15.Tazi J., Bakkour N. and Stamm S. (2009) Alternative splicing and disease. Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease 1792:14-26.
16.Trapnell C., Roberts A., Goff L., Pertea G., Kim D., Kelley D. R., Pimentel H., Salzberg S. L., Rinn J. L. and Pachter L. (2012) Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nature protocols 7:562-578.
17.Trapnell C., Williams B. A., Pertea G., Mortazavi A., Kwan G., Van Baren M. J., Salzberg S. L., Wold B. J. and Pachter L. (2010) Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nature biotechnology 28:511-515.
18.Truong A. D., Hong Y. H. and Lillehoj H. S. (2015) RNA-seq profiles of immune related genes in the spleen of Necrotic enteritis-afflicted chicken lines. Asian-Australasian journal of animal sciences 28:1496.
19.Wang W., Qin Z., Feng Z., Wang X. and Zhang X. (2013) Identifying differentially spliced genes from two groups of RNA-seq samples. Gene 518:164-170.
20.Wang Y., Lupiani B., Reddy S., Lamont S. and Zhou H. (2014) RNA-seq analysis revealed novel genes and signaling pathway associated with disease resistance to avian influenza virus infection in chickens. Poultry science 93:485-493.