Genome-Wide association study of Rumen Volatile fatty acid ratios in Holstein cattle

Esmaeili Lima, Fatemeh; Moradi Shahr Babak, Mohammad; Moradi Shahrbabak, Hossain; Jalil Sarghale, Ali

doi:10.22059/jap.2025.392025.623839

Document Type : Research Paper

Authors

¹ Department of Animal Science, Faculty of Agriculture, University of Tehran, Karaj, Iran. E-mail: fatemeh.lima@ut.ac.ir

² Corresponding Author, Department of Animal Science, Faculty of Agriculture, University of Tehran, Karaj, Iran. E-mail: moradim@ut.ac.ir

³ Department of Animal Science, Faculty of Agriculture, University of Tehran, Karaj, Iran. E-mail: hmoradis@ut.ac.ir

⁴ Department of Animal Science, Faculty of Agriculture, University of Tehran, City Karaj, Country Iran. E-mail: ali_jalil17@ut.ac.ir

10.22059/jap.2025.392025.623839

Abstract

Objective: Methane is a greenhouse gas that has a global warming potential of 27.2 times than of carbon dioxide. The ruminant gut produces methane a through a strong fermentation process, making methane a potent greenhouse gas. This research sought to identify genomic regions associated with methane emission in Holstein dairy cattle using a genome-wide association method and volatile fatty acid (VFA) ratios of acetate to propionate and propionate to butyrate.
Methods: Samples of Hair and rumen fluid (via an esophageal tube) were collected from 150 animals that were selected from an industrial Holstein dairy cattle herd based on the breeding values (EBV) of the bidirectional milk yield trait, using related standards for sampling. After measuring the concentration of volatile fatty acids (VFAs) in rumen fluid, we measured the concentration of these acids to determine methane emission for each animal. Hair cards samples were sent to the Gene Seek company (country of America), and the DNA samples were genotyped using SNP panel of GGP-LD v4' (30,108 SNPs). Genotyping results were quality controlled using Plink2.0 software. A total of 29888 SNPs were estimated and after quality control 5723 of them were culled due to quality control criteria. GWAS Analysis: Genomic regions associated with methane emission were identified by GWAS, and least squared analysis of variance with proc GLM (Generalized linear model) in SAS (2002-v 9.1) software was used to identify significant fixed effect factors related to methane emission. The relationship between genotypes and methane emission traits was analyzed by a mixed linear model in Plink (19) software.
Results: The least square analysis variance (P<0.05) for predicted methane emission trait was significant for effect of age and barnyard. Five and two SNPs were found to be significant for acetate to propionate and propionate to butyrate traits, respectively, which were located on chromosomes 3, 28 and 10, 11, respectively. Some of these SNPs were located close to the QTLs identified using annotation for methane emission, body weight, milk production traits, and remaining lactation period.
Conclusion: Results of this research demonstrate that genetic selection may be an effective way to reduce methane emissions per animal, because the improvement achieved through genetic selection is both heritable, accumulative, and permanent.

Keywords

References

جلیل سرقلعه، علی؛ مرادی شهربابک، حسین؛ مرادی شهربابک، محمد؛ نجاتی جوارمی، اردشیر؛ ساعتچی، مهدی و میار، یونس (1397). پویش کل ژنومی برای شناسایی نواحی ژنومی مرتبط با انتشارمتان درگاو بااستفاده ازتراشه 30K. مجله پژوهش‌های سلولی و مولکولی، مجله زیست‌شناسی ایران، 34 (1)، 65-76.

References

Allen, M., Bradford, B., & Oba, M. (2009). Board-invited review: The hepatic oxidation theory of the control of feed intake and its application to ruminants. Journal of animal science, 87(10), 3317-3334. doi:10.2527/jas.2009-1779

Aschenbach, J. R., Kristensen, N. B., Donkin, S. S., Hammon, H. M., & Penner, G. B. (2010). Gluconeogenesis in dairy cows: the secret of making sweet milk from sour dough. IUBMB life, 62(12), 869-877. DOI:10.1002/iub.400.

Bannink, A., Kogut, J., Dijkstra, J., France, J., Kebreab, E., Van Vuuren, A., & Tamminga, S. (2006). Estimation of the stoichiometry of volatile fatty acid production in the rumen of lactating cows. Journal of theoretical biology, 238(1), 36-51. https://doi.org/10.1016/j.jtbi.2005.05.026

Calderón-Chagoya, R., Vega-Murillo, V. E., García-Ruiz, A., Ríos-Utrera, Á., Martínez-Velázquez, G., & Montaño-Bermúdez, M. (2022). Genome and chromosome wide association studies for growth traits in Simmental and Simbrah cattle. Animal bioscience, 36(1), 19. https://doi.org/10.5713/ab.21.0517

Czerkawski, J. W. (2013). An introduction to rumen studies. Elsevier.

Dekkers, J. C. (2004). Commercial application of marker-and gene-assisted selection in livestock: strategies and lessons. Journal of animal science, 82(suppl_13), E313-E328. DOI:10.2527/2004.8213_supplE313x

Di, D. (1975). Methanogenesis, an integrated part of carbohydrate fermentation and its control. Digestion and Metabolism in the Ruminant.

Dijkstra, J., Van Zijderveld, S., Apajalahti, J., Bannink, A., Gerrits, W., Newbold, J., Perdok, H., & Berends, H. (2011). Relationships between methane production and milk fatty acid profiles in dairy cattle. Animal Feed Science and Technology, 166, 590-595. https://doi.org/10.1016/j.anifeedsci.2011.04.042

Halachmi, I., Børsting, C. F., Maltz, E., Edan, Y., & Weisbjerg, M. R. (2011). Feed intake of Holstein, Danish Red, and Jersey cows in automatic milking systems. Livestock Science, 138(1-3), 56-61..https://doi.org/10.1016/j.livsci.2010.12.001

Jalil Sarghale, A., Moradi Shahrbabak, H., Moradi Shahrbabak,M.,NejatiJavaremi,A., Saatchi, M., & Mayar, Y. (2003). Genome wide association study to identify genome region associated with methane emission in cattle using 30K panel. Journal of Cellular and Molecular Research, 34(1), 65-76. DOI: 20.1001.1.23832738.1400.34.1.8.5. (In Persian)

Janssen, P. H. (2010). Influence of hydrogen on rumen methane formation and fermentation balances through microbial growth kinetics and fermentation thermodynamics. Animal Feed Science and Technology, 160(1-2), 1-22. https://doi.org/10.1016/j.anifeedsci.2010.07.002

Jiménez-Montero, J. A., Gonzalez-Recio, O., & Alenda, R. (2012). Genotyping strategies for genomic selection in small dairy cattle populations. Animal, 6(8), 1216-1224. https://doi.org/10.1017/S1751731112000341

Jonker, A., Hickey, S. M., McEwan, J. C., Rowe, S. J., Janssen, P. H., MacLean, S., Sandoval, E., Lewis, S., Kjestrup, H., & Molano, G. (2019). Genetic parameters of plasma and ruminal volatile fatty acids in sheep fed alfalfa pellets and genetic correlations with enteric methane emissions. Journal of animal science, 97(7), 2711-2724. https://doi.org/10.1093/jas/skz162

Kristensen, N. B. (2001). Rumen microbial sequestration of [2-13C] acetate in cattle. Journal of animal science, 79(9), 2491-2498. https://doi.org/10.2527/2001.7992491x

Malhi, M., Gui, H., Yao, L., Aschenbach, J. R., Gäbel, G., & Shen, Z. (2013). Increased papillae growth and enhanced short-chain fatty acid absorption in the rumen of goats are associated with transient increases in cyclin D1 expression after ruminal butyrate infusion. Journal of dairy science, 96(12), 7603-7616. https://doi.org/10.3168/jds.2013-6700

Meuwissen, T. H., Hayes, B. J., & Goddard, M. (2001). Prediction of total genetic value using genome-wide dense marker maps. genetics, 157(4), 1819-1829. https://doi.org/10.1093/genetics/157.4.1819

Nejati-Javaremi, A., Smith, C., & Gibson, J. (1997). Effect of total allelic relationship on accuracy of evaluation and response to selection. Journal of animal science, 75(7), 1738-1745. https://doi.org/10.2527/1997.7571738x

Ottenstein, D., & Bartley, D. (1971). Improved gas chromatography separation of free acids C2-C5 in dilute solution. Analytical Chemistry, 43(7), 952-955. https://doi.org/10.1021/ac60302a043

Pearson, T. A., & Manolio, T. A. (2008). How to interpret a genome-wide association study. Jama, 299(11), 1335-1344. doi:10.1001/jama.299.11.1335

Penner, G., Taniguchi, M., Guan, L., Beauchemin, K., & Oba, M. (2009). Effect of dietary forage to concentrate ratio on volatile fatty acid absorption and the expression of genes related to volatile fatty acid absorption and metabolism in ruminal tissue. Journal of dairy science, 92(6), 2767-2781. https://doi.org/10.3168/jds.2008-1716

Saleem, F., Ametaj, B., Bouatra, S., Mandal, R., Zebeli, Q., Dunn, S., & Wishart, D. (2012). A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. Journal of dairy science, 95(11), 6606-6623. https://doi.org/10.3168/jds.2012-5403

SAS, S. (2002). 9.1 for Windows SAS Institute. Inc., Cary, North Carolina, 2004.

Sehested, J., Diernæs, L., Møller, P. D., & Skadhauge, E. (1999). Ruminal transport and metabolism of short-chain fatty acids (SCFA) in vitro: effect of SCFA chain length and pH. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology, 123(4), 359-368. https://doi.org/10.1016/S1095-6433(99)00074-4

Świerk, S., Przybyło, M., Flaga, J., Szczepanik, K., Białek, W., Flieger, P., & Górka, P. (2024). Effect of butyrate sources in a high-concentrate diet on rumen structure and function in growing rams. Animal, 18(9), 101285. https://doi.org/10.1016/j.animal.2024.101285

Urrutia, N. L., & Harvatine, K. J. (2017). Acetate dose-dependently stimulates milk fat synthesis in lactating dairy cows. The Journal of nutrition, 147(5), 763-769. https://doi.org/10.3945/jn.116.245001

Van Gastelen, S., Antunes-Fernandes, E., Hettinga, K., Klop, G., Alferink, S., Hendriks, W., & Dijkstra, J. (2015). Enteric methane production, rumen volatile fatty acid concentrations, and milk fatty acid composition in lactating Holstein-Friesian cows fed grass silage-or corn silage-based diets. Journal of dairy science, 98(3), 1915-1927. https://doi.org/10.3168/jds.2014-8552

Van Nevel, C., & Demeyer, D. (1996). Control of rumen methanogenesis. Environmental Monitoring and assessment, 42, 73-97. DOI: 10.1007/BF00394043

Van Valenberg, H., Hettinga, K., Dijkstra, J., Bovenhuis, H., & Feskens, E. (2013). Concentrations of n-3 and n-6 fatty acids in Dutch bovine milk fat and their contribution to human dietary intake. Journal of dairy science, 96(7), 4173-4181. https://doi.org/10.3168/jds.2012-6300

Wolin, M. J. (1960). A theoretical rumen fermentation balance. Journal of dairy science, 43(10), 1452-1459. https://doi.org/10.3168/jds.S0022-0302(60)90348-9

Journal of Animal Production, Print ISSN: 2008-6776., Online ISSN: 2382-994X

Genome-Wide association study of Rumen Volatile fatty acid ratios in Holstein cattle

References

References

References

Volume 27, Issue 4
January 2026
Pages 365-375

Genome-Wide association study of Rumen Volatile fatty acid ratios in Holstein cattle

References

References

References

Volume 27, Issue 4January 2026Pages 365-375

Volume 27, Issue 4
January 2026
Pages 365-375