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Genetic Diversity Evolution in the Mexican Charolais Cattle Population

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Genetic Diversity Evolution in the Mexican Charolais Cattle Population Open Access Anim Biosci Vol. 34, No. 7:1116-1122 July 2021 https://doi.org/10.5713/ajas.20.0401 pISSN 2765-0189 eISSN 2765-0235 Genetic diversity evolution in the Mexican Charolais cattle population Ángel Ríos-Utrera1, Moisés Montaño-Bermúdez2,*, Vicente Eliezer Vega-Murillo3, Guillermo Martínez-Velázquez4,*, Juan José Baeza-Rodríguez5, and Sergio Iván Román-Ponce6 * Corresponding Authors: Objective: The aim was to characterize the genetic diversity evolution of the registered Moisés Montaño-Bermúdez Tel: +52-5538718700 Ext. 80220, Mexican Charolais cattle population by pedigree analysis. E-mail: [email protected] Methods: Data consisted of 331,390 pedigree records of animals born from 1934 to 2018. Guillermo Martínez-Velázquez Average complete generation equivalent, generation interval, effective population size (Ne), Tel: +52-5538718700 Ext. 84411, E-mail: [email protected] and effective numbers of founders (fe), ancestors (fa), and founder genomes (Ng) were cal­ culated for seven five­year periods. The inbreeding coefficient was calculated per year of 1 Campo Experimental La Posta, Centro birth, from 1984 to 2018, whereas the gene contribution of the most influential ancestors de Investigación Regional Golfo-Centro, Instituto Nacional de Investigaciones was calculated for the latter period. Forestales, Agrícolas y Pecuarias, Medellín, Results: Average complete generation equivalent consistently increased across periods, Veracruz 94277, México from 4.76, for the first period (1984 through 1988), to 7.86, for the last period (2014 through 2 CENIDFyMA, Instituto Nacional de Investigaciones Forestales, Agrícolas y 2018). The inbreeding coefficient showed a relative steadiness across the last seventeen years, Pecuarias, Colón, Querétaro 76280, México oscillating from 0.0110 to 0.0145. During the last period, the average generation interval 3 Facultad de Medicina Veterinaria y for the father­offspring pathways was nearly 1 yr. longer than that of the mother­offspring Zootecnia, Universidad Veracruzana, pathways. The effective population size increased steadily since 1984 (105.0) and until 2013 Veracruz, Veracruz 91710, México 4 Campo Experimental Santiago Ixcuintla, (237.1), but showed a minor decline from 2013 to 2018 (233.2). The population displayed Centro de Investigación Regional Pacífico- an increase in the fa since 1984 and until 2008; however, showed a small decrease during Centro, Instituto Nacional de Investigaciones the last decade. The effective number of founder genomes increased from 1984 to 2003, Forestales, Agrícolas y Pecuarias, Santiago Ixcuintla, Nayarit 63570, México but revealed loss of genetic variability during the last fifteen years (from 136.4 to 127.7). 5 Campo Experimental Mocochá, Centro de The fa:fe ratio suggests that the genetic diversity loss was partially caused by formation of Investigación Regional Pacífico-Sur, Instituto genetic bottlenecks in the pedigree; in addition, the Ng:fa ratio indicates loss of founder alleles Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Mocochá, Yucatán due to genetic drift. The most influential ancestor explained 1.8% of the total genetic vari­ 97454, México ability in the progeny born from 2014 to 2018. 6 Campo Experimental La Campana, Centro Conclusion: Inbreeding, Ne, fa, and Ng are rather beyond critical levels; therefore, the current de Investigación Regional Norte-Centro, Instituto Nacional de Investigaciones genetic status of the population is not at risk. Forestales, Agrícolas y Pecuarias, Aldama, Chihuahua 32910, México Keywords: Cattle; Effective Number of Ancestors; Effective Number of Founder Genomes; ORCID Effective Population Size; Average Complete Generation Equivalent; Generation Interval Ángel Ríos-Utrera https://orcid.org/0000-0003-3108-1133 Moisés Montaño-Bermúdez https://orcid.org/0000-0003-3162-6949 Vicente Eliezer Vega-Murillo https://orcid.org/0000-0002-0847-8944 INTRODUCTION Guillermo Martínez-Velázquez https://orcid.org/0000-0001-6101-1297 Juan José Baeza-Rodríguez The development of the Mexican Charolais population began in 1930 in Northern Mexico https://orcid.org/0000-0001-9339-9695 with several importations of bovines from Charolles, a commune in the Saône­et­Loire Sergio Iván Román-Ponce https://orcid.org/0000-0002-6704-6578 department in the region of Bourgogne in Eastern France. The former Charolais breeders association was founded in 1958, whose name later changes to ‘Charolais Charbray Herd Submitted Jun 13, 2020; Revised Jul 22, 2020; Accepted Aug 16, 2020 Book de México’. The breed’s adaptation ability to different Mexican environments, coupled with good production performance (growth, beef doing ability), contributed greatly to a growing Charolais popularity, making it one of the most predominant beef breeds in the country. It is present in the arid and semiarid regions of the North, the temperate region of the Central Plateau, and the tropical and subtropical regions of the South of Mexico. Copyright © 2021 by Animal Bioscience This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, 1116 and reproduction in any medium, provided the original work is properly cited. www.animbiosci.org Ríos-Utrera et al (2021) Anim Biosci 34:1116-1122 The current breeders association has a membership of 468 Proportion of known ancestors was obtained for the first five cattlemen, which are distributed in 26 of the 32 states that generations (parents, grandparents, great­grandparents, and make up the Mexican territory. so on) for calves born in the seven time periods. Thus, the Towards the end of the 1990’s, parameters based on proba­ second generation for a given animal was assigned a 1.0 if bilities of gene origin (founder equivalents and founder all four grandparents were known, 0.75 if only three were genome equivalent) to measure genetic variability of wild known, and so on [8]. Similarly, generation intervals, defined populations [1,2] were successfully adapted and applied to as the average age of parents when their progeny, upon be­ beef cattle populations [3], on the premise that the classical coming parents themselves, are born, were calculated for inbreeding approach to quantify the rate of genetic drift is the father­son, father­daughter, mother­son and mother­ very sensitive to incomplete pedigree information. Later on, daughter pathways for progeny born during the seven time numerous studies were carried out in different countries to periods. The average generation interval was defined as the 6 6 6 6 6 monitor the genetic status of horse, donkey, sheep and cattle average of the four pathways. The average inbreeding coeffi­ 6 6 6 (dairy and beef) populations to initiate breeding actions if cient was estimated per year of birth, for cattle born from 115 birth,115 forbirth, cattle for born cattle from born 1984 from to 1984 2018. to Inbreeding 2018. Inbreeding coefficients coefficients were calculated were calculated using the using algorithm the algorithm there were possible115 unfavorable birth,115 for trends. birth,cattle forbornIn 115Mexico,cattle from born birth,1984 thirty from forto­ 2018. cattle1984 1984Inbreedingtoborn 2018. tofrom 2018. Inbreeding coefficients1984 Inbreeding to 2018.coefficients were coefficientsInbreeding calculated were coefficients calculatedusing were thecalculated usingalgorithmwere thecalculated using algorithm using the algorithm 115 birth, for cattle born from 1984115 to birth,2018. for Inbreeding cattle born coefficients from 1984 were to 2018.calculated Inbreeding using thecoefficients algorithm were calculated using the algorithm 115 birth, for cattle born fromfive 1984 beef to cattle 2018. breeds Inbreeding are officially coefficients recognized were calculated [4], however, using 116 the algorithmthedescribed algorithm by Sargolzaeidescribed byet Sargolzaeial [9], which et alis [9], based which on anis basedindirect method proposed earlier [10]. Effective 116 described by Sargolzaei116 et aldescribed116 [9], whichdescribed by isSargolzaei based by onSargolzaei et an al indirect [9], etwhich al method [9], is whichbased proposed onis basedan earlier indirect on [10]an methodindirect. Effective proposedmethod proposedearlier [10] earlier. Effective [10]6. Effective herdbook studies for only two116116 breeds describeddescribed (Simmental byby Sargolzaei Sargolzaeiand Romo et­et alal [9],[9], on whichwhich an indirect isis basedbased method onon anan indirectproposedindirect methodmethod earlier proposed[10].proposed Effective earlierearlier popula [10][10]. .­ EffectiveEffective 116 described by Sargolzaei116 et describedal [9], which by Sargolzaeiis based on et anal indirect[9], which method is based proposed on an earlierindirect [10] method. Effective proposed earlier [10]. Effective sinuano) have been recently conducted [5,6]. Therefore,117 population117 tionpopulation sizesize ( size),), estimatedestimated ( ), estimated fromfrom individual from individual increase increase in inbreeding in inbreeding coefficients coefficients ( ), average ( ), averagecomplete complete 117 populationpopulation size ( 117), size estimated ( population), fromestimated individual size from ( individualincrease), estimated in increase inbreeding from individual in inbreeding coefficients increase coefficients ( in), inbreeding average ( complete), coefficients average complete ( ), average complete 117117 population115 size ( birth,), estimatedfor cattle fromborn
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