Isoform Expression Profile Analysis of Residual Feed Intake for Isfahan Native and Ross Chickens Using RNA-Seq Data

Document Type : Genetics & breeding

Authors

1 PhD student of animal breeding, Faculty of Agriculture, Ferdowsi University of Mashhad, and a researcher in Animal Science Research Department, Safiabad Agricultural and Natural Resources Research and Education Center, AREEO, Dezful, Iran

2 Department of Animal Sciences, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

3 Department of Animal Science, Aburaihan Campus, University of Tehran, Iran

4 Department of Animal Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

5 National Institute of Animal Sciences

Abstract

Introduction:In the past decade, many performance traits in chickens have greatly improved to meet the growing demand forchicken meat. On the other hand, due to the 70% share of feed costs in the total cost of livestock production, feedefficiency has become one of the most important genetic traits in livestock and poultry. Residual feed intake (RFI) is the difference between the actual absorption of animal feed and the expected of the animal absorption based on body weight and its level of performance. Selection to improve feed efficiency through RFI is suggested due to its phenotypic independence from body weight and body weight gain. There is evidence for the genetic basis ofvariation in productivity in all species. Previous studies have shown that some genes may play an important role incontrolling RFI through effects on the digestive system and metabolic processes. It seems that changes in theamount of residual feed intake is the result of changes in the expression of the genes associated with it, and the study of transcript changes in chickens with high RFI helps to identify the mechanisms that affect it.Materials and Methods:Experiments were conducted on Commercial breeds (high production efficiency) and Isfahan Native Chickens(low production efficiency). From each breed, 60 chicks were harvested and caged from day 24 to 42 days for 19days. The chicks of both groups were raised under the same management conditions. In order to measure theresidual feed intake of each bird in individual cages and daily intake (FI) of the amount of feed consumed in 19 d(from day 24 to 42) divided by number of days, and daily gain (DG) of the weight difference 24. Using thesefigures, the amount of residual feed consumed will be calculated.Ten samples of liver tissue were then collected from each breed and immediately transferred to liquid nitrogenand transferred to the laboratory for total RNA extraction. Two pooled samples of every breed (each consisting ofthree extracted RNA sample) were prepared.Prior to Alignment, the quality of the raw readings sequence was evaluated using the Fastqc software. Thereference genome for the chicken (Galgal4) and the annotated file were obtained from the Ensembl database. After controlling the quality and Trimming the reads, the Hisat2 software was used to mapping obtain reads from the genome of the reference. Analysis of differential gene expression was performed using Cufflinks.. To identifydifferent isoform of the gene and to measure the expression of isoform, it is necessary to examine the position ofmicrowave splicing between the exons. Cuff compare compares the transcripts that are assembled with a reference genome and categorizes each transcript into known, new, and potential new isoform.Results and Discussion:The phenotypic results showed that the difference in the mean RFI values between the native (+13.430±5.393g/day) and commercial (-11.212±4.435g/day) chickens was highly significant (P<0.001). About 83% of thesequenced fragments were matched to the reference genome and Duplex analysis of gene expression wasperformed..Differential expression analysis for more than 45070 isoform Related to 19003 genes using Cuffdiffshowed that 28949 and 16121 isoform were up- and down-regulated (adjusted P≤0.05) in the native breed,
respectively. 206 Isoform was identified as a change in expression between the native and commercial chickens.Moreover 21081 novel isoform were identified which have not been included in the gene annotation so far.Moreover, the functional enrichment analysis showed that the down-regulated isoform in the native chickens weremainly involved in the different response to stress،response to oxygen-containing compound،response tocytokine،response to nutrient،response to lipid،animal organ development ،single-organism biosyntheticprocess،regulation of multi-organism process response to nutrient level and lipid biosynthetic process. TheDifferentially Expressed Genes and their isoform explored between the chickens of the two breeds led to theidentification of some important candidate genes for further breed improvement programs, including RSAD2, IL15,EGR1, and DUSP16. These genes could be related to the higher RFI of the native.Conclusion:Our findings showed that a large number of related genes with metabolism (fat, amino acids, carbohydrates, andvitamins), growth, as well as oxidative stress and immunity, can make a difference in the RFI. Identification of thedifference genes and their isoform between two breeds of chickens led to the identification of important candidategenes for breeding programs, including RSAD2, IL15, EGR1 and DUSP16.

Keywords


Bolger, A. M., M. Lohse, and B. Usadel. 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics, 30:2114-2120.
2. Bottje, W., and G. Carstens. 2009. Association of mitochondrial function and feed efficiency in poultry and livestock species. Journal of Animal Science, 87: E48-E63.
3. Bottje, W., N. Pumford, C. Ojano-Dirain, M. Iqbal, and K. Lassiter. 2006. Feed efficiency and mitochondrial function. Poultry Science, 85:8-14.
4. Chen, M., and J. L. Manley. 2009. Mechanisms of alternative splicing regulation: insights from molecular and genomics approaches. Nature Reviews Molecular Cell Biology, 10:741-754.
5. Darnell, J. E. 1997. STATs and gene regulation. Science, 277:1630-1635.
6. Dennis G., B. T. Sherman, D. A. Hosack, J. Yang, W. Gao, H. C. Lane, and R. A. Lempicki.2003. DAVID: database for annotation, visualization, and integrated discovery. Genome Biology, 4: R60.
7. Gandomani, V. T., A. Mahdavi, H. Rahmani, A. Riasi, and E. Jahanian. 2014. Effects of different levels of clove bud (Syzygium aromaticum) on performance, intestinal microbial colonization, jejunal morphology, and immunocompetence of laying hens fed different n-6 to n-3 ratios. Livestock Science, 167:236-248.
8. Grubbs, J. K. 2012. Protein profile and reactive oxygen species production in mitochondria from pigs divergently selected for residual feed intake.
9. Grubbs, J. K., A. Fritchen, E. Huff-Lonergan, J. C. Dekkers, N. K. Gabler, and S. M. Lonergan. 2013a. Divergent genetic selection for residual feed intake impacts mitochondria reactive oxygen species production in pigs. Journal of Animal Science, 91:2133-2140.
10. Grubbs, J. K., A. N. Fritchen, E. Huff-Lonergan, N. K. Gabler, and S. M. Lonergan. 2013b. Selection for residual feed intake alters the mitochondria protein profile in pigs. Journal of Proteomics, 80:334-345.
11. Hardman, J. G., and L. Limbird. 2001. Goodman & Gilman’s The Pharmacological Basis of Therapeutics, 10th. USA: McGraw-Hill Companies, Inc.
12. Herd, R., and P. Arthur. 2009. Physiological basis for residual feed intake. Journal of Animal Science, 87: E64-E71.
13. Hiller, D., H. Jiang, W. Xu, and W. H. Wong. 2009. Identifiability of isoform deconvolution from junction arrays and RNA-Seq. Bioinformatics, 25:3056-3059.
14. Iqbal, M., N. Pumford, Z. Tang, K. Lassiter, T. Wing, M. Cooper, and W. Bottje. 2004. Low feed efficient broilers within a single genetic line exhibit higher oxidative stress and protein expression in breast muscle with lower mitochondrial complex activity. Poultry Science, 83:474-484.
15. Iqbal, M., N. Pumford, Z. Tang, K. Lassiter, C. Ojano-Dirain, T. Wing, M. Cooper, and W. Bottje. 2005. Compromised liver mitochondrial function and complex activity in low feed efficient broilers are associated with higher oxidative stress and differential protein expression. Poultry Science, 84:933-941.
16. Kim, D., B. Langmead, and S. L. Salzberg. 2015. HISAT: a fast spliced aligner with low memory requirements. Nature methods, 12:357-60.
17. Kutner, M., C. Nachtsheim, J. Neter, and W. Li. 2004. Applied linear statistical models, McGraw Hill.
18. Liu, W., D. Li, J. Liu, S. Chen, L. Qu, J. Zheng, G. Xu and N. Yang. 2011. A genome-wide SNP scan reveals novel loci for egg production and quality traits in white leghorn and brown-egg dwarf layers. PloS one, 6:E28600.
19. Lohse, M., A. Bolger, A. Nagel, A. R. Fernie, J. E. Lunn, M. Stitt, and B. Usadel. 2012. RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics. Nucleic acids research, gks540.
20. Lu, L., C. Ji, X. Luo, B. Liu, and S. Yu. 2006. The effect of supplemental manganese in broiler diets on abdominal fat deposition and meat quality. Animal Feed Science and Technology, 129:49-59.
21. Lu, H., D. Huang, R. M. Ransohoff, and L. Zhou. 2011. Acute skeletal muscle injury: CCL2 expression by both monocytes and injured muscle is required for repair. The FASEB Journal, 25:3344-3355
22. Lu, Z. X., P. Jiang, and Y. Xing. 2012. Genetic variation of pre‐mRNA alternative splicing in human populations. Wiley Interdisciplinary Reviews: RNA, 3:581-592.
23. Luiting, P., J. Schrama, W. Vander-Hel, and E. Urff. 1991. Metabolic differences between White Leghorns selected for high and low residual food consumption. British Poultry Science, 32:763-782.
24. Luiting, P., and E. Urff. 1991. Residual feed consumption in laying hens. 2. Genetic variation and correlations. Poultry Science, 70:1663-1672.
25. Modrek, B., and C. Lee. 2002. A genomic view of alternative splicing. Nature genetics, 30(1): 3-9.
26. Ojano-Dirain, C., M. Iqbal, D. Cawthon, S. Swonger, T. Wing, M. Cooper, and W. Bottje. 2004. Determination of mitochondrial function and site-specific defects in electron transport in duodenal mitochondria in broilers with low and high feed efficiency. Poultry Science, 83:1394-1403.
27. Ozsolak, F., and P. M. Milos. 2011. RNA sequencing: advances, challenges and opportunities. Nature reviews. Genetics, 12:87.
28. Pitchford, W. 2004. Genetic improvement of feed efficiency of beef cattle: what lessons can be learnt from other species? Australian Journal of Experimental Agriculture, 44:371-382.
29. Rekaya, R., R. Sapp, T. Wing, and S. Aggrey. 2013. Genetic evaluation for growth, body composition, feed efficiency, and leg soundness. Poultry Science, 92:923-929.
30. Smith, R., N. Gabler, J. Young, W. Cai, N. Boddicker, M. Anderson, E. Huff-Lonergan, J. Dekkers, and S. Lonergan .2011. Effects of selection for decreased residual feed intake on composition and quality of fresh pork. Journal of Animal Science, 89:192-200.
31. Stewart, W. C., R. F. Morrison, S. L. Young, and J. M. Stephens .1999. Regulation of signal transducers and activators of transcription (STATs) by effectors of adipogenesis: Coordinate regulation of STATs 1, 5A, and 5B with peroxisome proliferator-activated receptor-γ and C/AAAT enhancer binding protein-α. Biochimica et Biophysica Acta (BBA)-Molecular Cell Research, 1452:188-196.
32. Van-Eerden, E., H. Van-Den-Brand, H. Parmentier, and M. De Jong. 2004. Phenotypic selection for residual feed intake and its effect on humoral immune responses, in growing layer hens. Poultry science, 83:1602-1609.
33. Vuong, C. K., D. L. Black, and S. Zheng. 2016. The neurogenetics of alternative splicing. Nature Reviews Neuroscience, 17:265-81.
34. Xu, Y., Y. Wang, J. Luo, W. Zhao, and X. Zhou. 2017. Deep learning of the splicing (epi) genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision. Nucleic acids research.
35. Yi, G. 2015. Interrogation of Differentially Expressed Genes Governing Residual Feed Intake in Chickens Using RNA-Seq. In: Plant and Animal Genome XXIII Conference. Plant and Animal Genome.
36. Young, J., W. Cai, and J. Dekkers. 2011. Effect of selection for residual feed intake on feeding behavior and daily feed intake patterns in Yorkshire swine. Journal of animal science, 89P639-47.
37. Zhuo, Z., S. J. Lamont, W. R. Lee, and B. Abasht. 2015. RNA-Seq analysis of abdominal fat reveals differences between modern commercial broiler chickens with high and low feed efficiencies. PloS one, 10:E0135810.
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