High Feed efficiency (FE) in growing heifers has economic importance in dairy,
but remains less understood in buffaloes. Feed conversion efficiency is defined
as dry matter intake (DMI) per unit body weight gain and is determined as
residual feed intake (RFI), i.e., the difference between actual and predicted feed intake
to gain unit body weight during a feed trial run for 78 days under control
feeding. A large variation was identified ranging between -0.42 to 0.35 in
growing buffalo heifers (n=40) of age
between 11 to 15 months. An average daily weight gain (ADG) varied between
382.0 and 807.6 g/day when compared with the control-fed heifers at an organized buffalo farm. The whole blood transcriptome data obtained from the
selected growing heifers from extremes of estimated high and low RFI efficiency
were compared with the reference assembly generated from the transcriptome of
multiparous buffaloes (n = 16) of diverse age of maturity, period of regaining
post partum cyclicity and level of milk production.
Differentially expressed genes (DEGs) were identified using the reference genome of Mediterranean water buffalo. GO:
terms (Padj<0.05, FDR<0.05)
enriched by annotated DEGs and biological pathways in gene network for RFI
efficiency trait were identified. GO:terms
specific to pre-transcriptional
References
[1]
Connor, E.J., Hutchison, H., Norman, K., Olson, C., Van Tassell, J. and Baldwin, R. (2013) Use of Residual Feed Intake in Holsteins during Early Lactation Shows Potential to Improve Feed Efficiency through Genetic Selection. Journal of Animal Science, 91, 3978-3988. https://doi.org/10.2527/jas.2012-5977
[2]
Koch, R.M., Swiger, L.A., Chambers, D. and Gregory, K. (1963) Efficiency of Feed Use in Beef Cattle. Journal of Animal Science, 22, 486-494.
https://doi.org/10.2527/jas1963.222486x
[3]
Bisitha, K., Chandra, B.S., Singh, K.S., et al. (2014) Residual Feed Intake as a Feed Efficiency Selection Tool and Its Relationship with Feed Intake, Performance and Nutrient Utilization in Murrah Buffalo Calves. Tropical Animal Health and Production, 46, 615-621. https://doi.org/10.1007/s11250-014-0536-2
[4]
Serão, N.V.L., González-Peña, D., Beever, J.E., Faulkner, D.B., Southey, B.R. and Rodriguez-Zas, S.L. (2013) Single Nucleotide Polymorphisms and Haplotypes Associated with Feed Efficiency in Beef Cattle. BMC Genetics, 14, Article No. 94.
http://www.biomedcentral.com/1471-2156/14/94
https://doi.org/10.1186/1471-2156-14-94
[5]
Kahi, A.K. and Hirooka, H. (2007) Effect of Direct and Indirect Selection Criteria for Efficiency of Gain on Profitability of Japanese Black Cattle Selection Strategies. Journal of Animal Science, 85, 2401-2412. https://doi.org/10.2527/jas.2006-713
[6]
Brito, L.F., Oliveira, H.R., Houlahan, K., Fonseca, P.S., Lam, S., et al. (2020) Genetic Mechanisms Underlying Feed Utilization and Implementation of Genomic Selection for Improved Feed Efficiency in Dairy Cattle. Canadian Journal of Animal Science, 100, 587-604. https://doi.org/10.1139/cjas-2019-0193
[7]
Poonam, S., Nath, A., Sundar, S., Jerome, P., et al. (2020) Inferring Relationship of Blood Metabolic Changes and Average Daily Gain with Feed Conversion Efficiency in Murrah Heifers: Machine Learning Approach. Frontiers in Veterinary Science, Section Animal Nutrition and Metabolism, 7, 518.
https://doi.org/10.3389/fvets.2020.00518
[8]
Salleh, M.S., Mazzoni, G., Nielsen, M.O., Løvendah, P. and Kadarmideen, H.N. (2018) Identification of Expression QTLs Targeting Candidate Genes for Residual Feed Intake in Dairy Cattle Using Systems Genomics. Journal of Genetics and Genome Research, 5, 35. https://doi.org/10.23937/2378-3648/1410035
[9]
Patel, R.K. and Jain, M. (2012) NGS QC Toolkit: A Toolkit for Quality Control of Next Generation Sequencing Data. PLOS ONE, 7, e30619.
https://doi.org/10.1371/journal.pone.0030619
[10]
Huang, D.W., Sherman, B.T., Tan, Q., Collins, J.R., et al. (2007) The DAVID Gene Functional Classification Tool: A Novel Biological Module-Centric Algorithm to Functionally Analyze Large Gene Lists. Genome Biology, 8, R183.
https://doi.org/10.1186/gb-2007-8-9-r183
[11]
Bray, N.L., Pimentel, H., Melsted, P. and Pachter, L. (2016) Near-Optimal Probabilistic RNA-seq Quantification. Nature Biotechnology, 34, 525-527.
https://doi.org/10.1038/nbt.3519
[12]
Love, M.I., Huber, W. and Anders, S. (2014) Moderated Estimation of Fold Change and Dispersion for RNA-seq Data with DESeq2. Genome Biology, 15, 550.
https://doi.org/10.1186/s13059-014-0550-8
[13]
Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B. and Ideker, T. (2003) Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks. Genome Research, 13, 2498-2504. https://doi.org/10.1101/gr.1239303
[14]
Richardson, E.C., Herd, R.M., Archer, J.A. and Arthur, P.F. (2004) Metabolic Differences in Angus Steers Divergently Selected for Residual Feed Intake. Australian Journal of Experimental Agriculture, 44, 441-452. https://doi.org/10.1071/EA02219
[15]
Herd, R.M. and Arthur, P.F. (2009) Physiological Basis for Residual Feed Intake. Journal of Animal Science, 87, E64-E71. https://doi.org/10.2527/jas.2008-1345
[16]
McKenna, C., Keogh, K., Porter, R.K., Waters, S.M., Cormican, P. and Kenny, D.A. (2021) An Examination of Skeletal Muscle and Hepatic Tissue Transcriptomes from Beef Cattle Divergent for Residual Feed Intake. Scientific Reports, 11, Article No. 8942. https://doi.org/10.1038/s41598-021-87842-3
[17]
Tizioto, P.C., Coutinho, L.L., Priscila, S.N., Aline, O., Cesar, S.M., Diniz, W.J.S., et al. (2016) Gene Expression Differences in Longissimus Muscle of Nelore Steers Genetically Divergent for Residual Feed Intake. Scientific Reports, 6, Article No. 39493. https://doi.org/10.1038/srep39493
[18]
Salleh, M.S., Mazzoni, G., Höglund, J.K., Olijhoek, D.W., Lund, P., Løvendah, H.N. and Kadarmideen, P. (2017) RNA-Seq Transcriptomics and Pathway Analyses Reveal Potential Regulatory Genes and Molecular Mechanisms in High- and Low-Residual Feed Intake in Nordic Dairy Cattle. BMC Genomics, 18, Article No. 258. https://doi.org/10.1186/s12864-017-3622-9
[19]
Kolath, W.H., Kerley, M.S., Golden, J.W. and Keisler, D.H. (2006) The Relationship between Mitochondrial Function and Residual Feed Intake in Angus Steers. Journal of Animal Science, 84, 861-865. https://doi.org/10.2527/2006.844861x
[20]
Hoque, M.A. and Suzuki, K. (2009) Genetics of Residual Feed Intake in Cattle and Pigs: A Review Asian-Aust. Journal of Animal Science, 22, 747-755.
https://doi.org/10.5713/ajas.2009.80467
[21]
Bazile, J., Jaffrezic, F., Dehais, P., et al. (2020) Molecular Signatures of Muscle Growth and Composition Deciphered by the Meta-Analysis of Age-Related Public Transcriptomics Data. Physiological Genomics, 52, 322-332.
https://doi.org/10.1152/physiolgenomics.00020.2020
[22]
McConnell, J.D., Stone, D.K., Johnson, L. and Wilson, J.D. (1987) Partial Purification and Characterization of Dynein Adenosine Triphosphatase from Bovine Sperm. Biology of Reproduction, 37, 385-393.
https://doi.org/10.1095/biolreprod37.2.385
[23]
Lorch, D.P., Lindemann, C.B. and Hunt, A.J. (2008) The Motor Activity of Mammalian Axonemal Dynein Studied in Situ on Doublet Microtubules. Cell Motility and the Cytoskeleton, 65, 487-494. https://doi.org/10.1002/cm.20277
[24]
Oliveira, P.S.N., Coutinho, L.L., Tizioto, P.C., Cesar, A.S.M., de Oliveira, G.B., et al. (2018) An Integrative Transcriptome Analysis Indicates Regulatory mRNA-miRNA Networks for Residual Feed Intake in Nelore Cattle. Scientific Reports, 8, Article No. 17072. https://doi.org/10.1038/s41598-018-35315-5
[25]
Kooistra, M.R.H., Dube, N. and Bos, J.L. (2006) Rap1: A Key Regulator in Cell-Cell Junction Formation. Journal of Cell Science, 120, 17-22.
https://doi.org/10.1242/jcs.03306
[26]
Nkrumah, J.D., Li, C., Basarab, J.B., Guercio, S., Meng, Y., Murdoch, B., Hansen, C. and Moore, S.S. (2004) Association of a Single Nucleotide Polymorphism in the Bovine Leptin Gene with Feed Intake, Feed Efficiency, Growth, Feeding Behavior, Carcass Quality and Body Composition. Canadian Journal of Animal Science, 84, 211-219. https://doi.org/10.4141/A03-033
[27]
Hoehn, K.L., Hudachek, S.F., Summers, S.A. and Florant, G.L. (2004) Seasonal, Tissue-Specific Regulation of Akt/Protein Kinase B and Glycogen Synthase in Hibernators. The American Journal of Physiology-Regulatory, Integrative and Comparative Physiology, 286, R498-R504. https://doi.org/10.1152/ajpregu.00509.2003
[28]
Feitosa, F.L.B., Pereira, A.S.C., Mueller, L.F., de Souza Fonseca, P.A., Braz, C.U., Amorin, S., Espigolan, R., et al. (2021) Genome-Wide Association Study for Beef Fatty Acid Profile Using Haplotypes in Nellore Cattle. Livestock Science, 245, Article ID: 104396. https://doi.org/10.1016/j.livsci.2021.104396
[29]
Khansefid, M., Millen, C.A., Chen, Y., Pryce, J.E., Chamberlain, A.J., Vander Jagt, C.J., Gondro, C. and Goddard, M.E. (2017) Gene Expression Analysis of Blood, Liver, and Muscle in Cattle Divergently Selected for High and Low Residual Feed Intake. Journal of Animal Science, 95, 4764-4775.
https://doi.org/10.2527/jas2016.1320
[30]
Oshurkova, J.L. and Glagoleva, T.I. (2017) Physiological Activity of Platelet Aggregation in Calves of Vegetable Feeding. Biomedical and Pharmacology Journal, 10, 1395-1400. https://doi.org/10.13005/bpj/1244
[31]
Basarab, J.A., et al. (2010) Interactions with Other Traits: Reproduction and Fertility. In: Hill, R.A., Ed., Feed Efficiency in the Beef Industry, John Wiley & Sons, Hoboken, 123-144.
[32]
Xi, Y.M., Wu, F., Zhao, D.Q. and Yang, Z. (2016) Biological Mechanisms Related to Differences in Residual Feed Intake in Dairy Cows. Animal, 10, 1311-1318.
https://doi.org/10.1017/S1751731116000343
[33]
Wood, B.J., Archer, J.A. and van der Werf, J.H.H. (2004) Response to Selection in Beef Cattle Using IGF-1 as a Selection Criterion for Residual Feed Intake under Different Australian Breeding Objectives. Livestock Production Science, 91, 69-81.
https://doi.org/10.1016/j.livprodsci.2004.06.009
[34]
Kelly, A.K., McGee, M., Crews, D.H., Fahey, A.G., Wylie, A.R. and Kenny, D.A. (2010) Effect of Divergence in Residual Feed Intake on Feeding Behavior, Blood Metabolic Variables, and Body Composition Traits in Growing Beef Heifers. Journal of Animal Science, 88, 109-123. https://doi.org/10.2527/jas.2009-2196
[35]
Welch, C.M., Thornton, K.J., Murdoch, G.K., Chapalamadugu, K.C., Schneider, C.S., Ahola, J.K., Hall, J.B., Price, W.J. and Hill, R.A. (2013) An Examination of the Association of Serum IGF-I Concentration, Potential Candidate Genes, and Fiber Type Composition with Variation in Residual Feed Intake in Progeny of Red Angus Sires Divergent for Maintenance Energy EPD. Journal of Animal Science, 91, 5626-5636. https://doi.org/10.2527/jas.2013-6609
[36]
Sharma, V.K., Kundu, S.S., Datt, C., Prusty, S., Kumar, M. and Sontakke, U.B. (2017) Buffalo Heifers Selected for Lower Residual Feed Intake Have Lower Feed Intake, Better Dietary Nitrogen Utilisation and Reduced Enteric Methane Production. Journal of Animal Physiology and Animal Nutrition (Berlin), 102, e607-e614.
https://doi.org/10.1111/jpn.12802
[37]
Alexandre, P.A., Kogelman, J., Santana, M.H., Passarelli, P.D., Fantinato-neto, H., Silva, P.P.L., Leme, P.R., Strefezzi, R.F., Coutinho, L., Ferraz, J.B., Eler, J.P., Kadarmideen, H.N. and Fukumasu, H. (2015) Liver Transcriptomic Networks Reveal Main Biological Processes Associated with Feed Efficiency in Beef Cattle. BMC Genomics, 16, Article No. 1073. https://doi.org/10.1186/s12864-015-2292-8
[38]
Paradis, F., Yue, S., Grant, J., Stothard, P., Basarab, J. and Fitzsimmons, C. (2015) Transcriptomic Analysis by RNA Sequencing Reveals That Hepatic Interferon-Induced Genes May Be Associated with Feed Efficiency in Beef Heifers. Journal of Animal Science, 93, 3331-3341. https://doi.org/10.2527/jas.2015-8975
[39]
Weber, K.L., Welly, B.T., Van Eenennaam, A.L., Young, A.E., Porto-neto, L.R., Reverter, A. and Rincon, G. (2016) Identification of Gene Networks for Residual Feed Intake in Angus Cattle Using Genomic Prediction and RNA-seq. PLOS ONE, 11, e0152274. https://doi.org/10.1371/journal.pone.0152274
[40]
Mishra, D.C., Sikka, P., Yadav, S., Bhati, J., Paul, S.S., Jerome, A., et al. (2020) Identification and Characterization of Trait-Specific SNPs Using ddRAD Sequencing in Water Buffalo. Genomics, 112, 3571-3578.
https://doi.org/10.1016/j.ygeno.2020.04.012