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 wh en compar ed 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 regulation of nucleus and Chromatin organization under Nucleoplasm, Energy balancing, Immunity, Cell signaling, ROS optimization, ATP generation through the Electron Transport chain and cell proliferation were determined. The study reveals the indicators targeting the actual metabolic changes and molecular functions underlying the feed utilization capacity of buffaloes. Estimated RFI efficiency revealed a large variation over heifers which may lower the DMI even up to 13.6% thus, enabling an increase in ADG up to 16% by involving efficient heifers in breeding plan. The study revealed a scope of high gain by selective breeding for FE in heifers. FE variants catalogued in the study are useful breed - specific RFI markers for future reference. The study contributes to the understanding of feed efficiency in buffaloes and its association with key interactive traits such as reproduction and growth. This knowledge can be utilized to develop more effective breeding programs.
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
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
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
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
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
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
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
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
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
Blood Transcriptome
Differentially Expressed Genes
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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