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 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 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 five-year 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 father-offspring pathways was nearly 1 yr. longer than that of the mother-offspring 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 , a commune in the Saône-et- 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 ’s adaptation ability to different Mexican environments, coupled with good production performance (growth, doing ability), contributed greatly to a growing Charolais popularity, making it one of the most predominant beef 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, great-grandparents, 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 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 father-son, father-daughter, mother-son 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 individual from 1984 increase to 2018. in inbreeding Inbreeding coefficients coefficients ( were), average calculated complete using the algorithm 117 population size ( 117), estimated thepopulation aim from of this individualsize study ( ),was increase estimated to characterize in inbreedingfrom individual the coefficients genetic increase diversity ( in inbreeding), average coefficientscomplete coefficients ( ( ), averageaverage complete complete generation equivalent, � � 118 �generation��� 𝑁𝑁𝑁𝑁��� �equivalent, 𝑁𝑁𝑁𝑁���� and effective numbers� of founders ( ), ancestors� ( ∆𝐹𝐹) and founder∆𝐹𝐹 genomes ( ) generation equivalent,𝑁𝑁𝑁𝑁���� 118 and �effective�generation��118 numbersgeneration equivalent,𝑁𝑁𝑁𝑁 of equivalent, founders and effective ( and), ancestors effectivenumbers (numbersof )founders and founder∆𝐹𝐹of founders( ), genomesancestors (�� ), ancestors (( ) and founder∆𝐹𝐹( ) and genomesfounder genomes( ) ( ) evolution of the registered118 118Mexican generation Charolais equivalent, cattle𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁��� �popu and­ effectiveand numbers effective of foundersnumbers� ( of), founders ancestors f( (e), )ancestors and founder∆𝐹𝐹∆𝐹𝐹 (fa), genomes and ( ) ���� 𝑁𝑁𝑁𝑁���� 118 generation116 equivalent, described �and byeffective Sargolzaei numbers et al of∆𝐹𝐹[9], founders which is( based), ancestors on an indirect( ) and methodfounder proposed genomes earlier( ) [10]. Effective generation equivalent,𝑁𝑁𝑁𝑁118 and generationeffective numbers equivalent, of foundersand effective ( ), ancestorsnumbers of( founders) and founder∆𝐹𝐹 ( ), ancestorsgenomes (( ) )and founder genomes ( ) � � � � � � 118 lation by pedigree analysis applying the approaches referred founder genomes� (Ng) were calculated� per� time period.𝑓𝑓 The�𝑓𝑓 𝑓𝑓 𝑓𝑓 � 𝑁𝑁 𝑁𝑁 119 were calculated𝑓𝑓 per time period.�� 𝑓𝑓 The was��𝑓𝑓 estimated as:𝑁𝑁 𝑓𝑓 �,� where is the𝑁𝑁 average inbreeding 119 were calculated per time119 period.were119 The calculated� were was calculated per estimated time� period.per as: time The period. was The,𝑓𝑓 𝑓𝑓where estimated was� is estimated as:the𝑓𝑓 𝑓𝑓 average as: inbreeding , where , where is the𝑁𝑁𝑁𝑁 average is the inbreeding average inbreeding above. 119 � were calculated117� perpopulation time𝑓𝑓 period. size The ( ),𝑓𝑓 estimated was� estimated from as:individual increase𝑁𝑁 , where in inbreeding is the average coefficients inbreeding ( � ), average complete 119 𝑓𝑓 were calculated𝑓𝑓 per time period. The was𝑁𝑁 was estimated estimated as: as:� , ,where where isis the�the average average� inbreeding 119 were calculated per 119time period.were Thecalculated was per estimated time period. as: The was , where estimated is as: the average inbreeding , where is the average inbreeding� ���� 𝑁𝑁𝑁𝑁���� � 𝑁𝑁𝑁𝑁���� ���𝑁𝑁𝑁𝑁���� � �∆��𝑁𝑁𝑁𝑁���� � �∆� ∆𝐹𝐹���� ∆𝐹𝐹���� 𝑁𝑁𝑁𝑁�120��� � inbreedingrate of the nrate individuals𝑁𝑁𝑁𝑁���� of� the 𝑁𝑁𝑁𝑁��∆����� �n individualsevaluated�∆𝐹𝐹���� [11]. evaluated Average𝑁𝑁𝑁𝑁���� � �∆�[11]. complete Average generation∆𝐹𝐹���� � equivalent was calculated for each � 120 rate120 of therate n individualsof 𝑁𝑁𝑁𝑁�the���𝑁𝑁𝑁𝑁� ��n� �individuals evaluated evaluated [11]. 𝑁𝑁𝑁𝑁�Average���� �[11]. �∆��∆�� � �completeAverage�� completegeneration∆𝐹𝐹����� generation equivalent equivalent was∆𝐹𝐹 calculated was calculated for each for each 120 rate120 of therate n�� �individuals� of the118 n individuals evaluatedgeneration��� �evaluated[11]. equivalent, Average���� [11].𝑁𝑁𝑁𝑁 complete andAverage���� effective generationcomplete numbers 𝑁𝑁𝑁𝑁generation equivalent �of founders equivalent was (calculated∆𝐹𝐹), ancestorswas calculatedfor each( ) and for foundereach genomes ( ) 120 MATERIALSrate of the𝑁𝑁𝑁𝑁�� �n� individuals AND evaluated METHODS120𝑁𝑁𝑁𝑁�� �� �[11].rate𝑁𝑁𝑁𝑁 �∆���� �Averageof the n individualscomplete∆𝐹𝐹���� 𝑁𝑁𝑁𝑁 generation evaluated� �∆� complete equivalent [11]. Average∆𝐹𝐹 generation was completecalculated equivalent generation for each was equivalentcalculated wasfor each calculated indi­ for each 120 rate of the n individuals evaluated [11]. Average complete generation equivalent was calculated for each n n 121n individual121 individual as the sum as nthe of (1/2)sum of coefficients (1/2)n coefficients of all known �of all ancestors,known ancestors,� where n where is the nnumber is the numberof �generations of generations 121 individual as the sum121 of (1/2)individual coefficients asn nthe ofvidual sum all knownof as (1/2)the ancestors,sum coefficients of (1/2) where coefficientsof alln is known the number ancestors,of𝑓𝑓 all ofknown generations where ancestors, 𝑓𝑓n is the number of generations𝑁𝑁 121121n individualindividual119 asas thethe were sumsum ofcalculatedof (1/2)(1/2) coefficientscoefficients per time period. ofof allall The knownknown ancestors,wasancestors, estimated wherewhere as: n n isis thethe numbernumber , where ofof generationsgenerations is the average inbreeding 121 Pedigreeindividualn data as the sum of (1/2) coefficients of all known ancestors, where n is the number of generations 121 individual as the sum of (1/2) coefficients of all known ancestors, where n is the number of generationswhere n is the number of generations separating� the indi­ Genealogical records of cattle born from 1934122 to 2018separating122 were separating122 the individualseparating the individual to eachthe individual known to each ancestor knownto each [12]. ancestorknown ancestor [12]. [12]. 122 separating122 separatingthe individual the individualto each known to each ancestor known [12]. ancestor [12]. � ��� ���� �∆����� ���� 122 separating120 the individualrate of the to eachn individuals knownvidual ancestorto evaluated each known[12]. [11].𝑁𝑁𝑁𝑁 ancestorAverage complete[12]. 𝑁𝑁𝑁𝑁 generation� equivalent∆𝐹𝐹 was calculated for each 122 separating the individual122 toprovided separatingeach known by the the ancestor individual Charolais [12]. to Charbray each known Herd ancestor Book [12]. de México. 123 123The 123 wasThe calculated The wasThe fcalculated e wasas: was calculated calculated 1/as: as:as: 1/, where 1/ , where is the ,probability where is the qprobabilityk is isof the thegene probability origin of gene of oforiginthe gene k ancestor, of origin the k of ancestor, the k ancestor, The data file contained123 identification123The was The numberscalculated was of calculatedas: the calf, 1/ as: ,1/ where , iswhere nthe probability is the probability of gene origin of gene of the origin k ancestor, of the k ancestor, 123 The 121 was calculatedindividual as: as the sum1/ of (1/2), where coefficients � is the of probability all� known� � ofancestors, gene� origin where of then is k the ancestor, number of generations 123 The was calculated as: 1/ , where is the probability� �probability of gene� oforigin gene of origin the k ancestor,�of the� k ancestor, while the� f was 123 The was calculated sire,as: dam 1/ and breeder,, where and genotype,is the probability sex and of birth gene yearorigin of of � the k ancestor,� �� � � � � ��� �∑���� � � a � � � 𝑓𝑓124��� � while𝑓𝑓 the𝑓𝑓� � 𝑓𝑓was� estimated∑���𝑓𝑓 �𝑞𝑞 as:∑𝑓𝑓 � =𝑞𝑞 1/𝑞𝑞 𝑞𝑞 𝑞𝑞, where 𝑞𝑞 is the marginal contribution of an ancestor j that is � 𝑓𝑓 ���124 while124𝑓𝑓 � the∑ while was��𝑞𝑞 the estimated ∑��� ���was𝑞𝑞 �estimated �as: = 1/ as:�� = 1/, where , whereis the marginal is the marginalcontribution contribution of an ancestor of an jancestor that is j that is � �124 while124� the while was��� the estimated�𝑓𝑓𝑓𝑓 was as:estimated� = 1/ as:𝑓𝑓 𝑓𝑓 � �=estimated ,1/ where∑ 𝑞𝑞𝑞𝑞 as: ,is where the marginal 𝑞𝑞𝑞𝑞 is the contribution marginal, where qcontributionj isof the an ancestormarginal of an j thatancestorcontri is ­ j that is � the calf.� 𝑓𝑓 ��� � � 124𝑓𝑓 � while∑ 𝑞𝑞the122 was 𝑞𝑞separatingestimated as:the individual = 1/ to each, where known is ancestor the marginal �[12].� contribution� � of an ancestor j that is 𝑓𝑓 124 while𝑓𝑓 � the ∑ was𝑞𝑞 estimated𝑞𝑞 as: = 1/ , where is the marginal� � contribution� of an ancestor� � j that� is ��� � � 124 while the was estimated as: = 1/ , where is the marginal� contribution �of an ancestor� bution j that� �� ofis an�𝑓𝑓� ancestor� j��� that� �is not𝑓𝑓��� explained� ∑� 𝑞𝑞 by �other ancestors𝑞𝑞 � 𝑓𝑓���� � 𝑓𝑓 ��� � 𝑓𝑓 �∑ 𝑓𝑓 𝑞𝑞 ∑ 𝑞𝑞𝑞𝑞 𝑞𝑞 � � 𝑓𝑓 � � 𝑓𝑓 � 125𝑓𝑓 not125∑ 𝑓𝑓 explained�𝑞𝑞 not∑ explained��� by𝑞𝑞 �other by ancestors 𝑞𝑞other� ancestors chosen chosenbefore. Thebefore. Thewas calculated was calculated as = as 1/ g =, where 1/ g , where g is the g is the � 125 not explained� ��� by other� 125𝑓𝑓 ancestorsnot� explained chosen𝑓𝑓 before.bychosen other∑ The before.ancestors𝑞𝑞 was The chosencalculated𝑞𝑞 N was before. calculated as The = 1/ as was Ng, where =calculated 1/2 g ,is where asthe = 1/ g, where g is the � Data �editing𝑓𝑓 ��� � �125125𝑓𝑓 notnot∑ explainedexplained𝑞𝑞 123 byby 𝑞𝑞 otherotherThe ancestors ancestors was calculated chosenchosen before. before.as: TheThe 1/ g was was, calculatedwherecalculated is as asthe gprobability = = 1/ 1/ g g, , where whereof gene g g origin isis thethe of the k ancestor, 𝑓𝑓 125 not 𝑓𝑓explained∑ by𝑞𝑞 other ancestors𝑞𝑞 chosen before. The was calculated as = 1/ g, where g is the 125 not explained by other ancestors chosen before. The was calculated as = 1/ g, where g is the � � � � � � Initially, progeny with any fraction of Charolais, including average is the coancestry average� coancestry in the reference in� the population. reference� 𝑁𝑁Genetic population.𝑁𝑁 bottlenecks� and𝑁𝑁 random2𝑁𝑁𝑓𝑓 genetic2𝑓𝑓 drift𝑓𝑓 were𝑓𝑓 defined 126 average126 coancestry�average126 coancestry in the reference𝑁𝑁 in� the reference population.∑����� � population. Genetic𝑁𝑁 �𝑁𝑁 bottlenecks Genetic2𝑓𝑓 �� bottlenecks and𝑓𝑓 random and𝑁𝑁 genetic random2𝑓𝑓 drift genetic were 𝑓𝑓drift defined were defined 126 average126 coancestryaverage coancestry in124 the referencewhile in� the the population.𝑓𝑓reference was Geneticestimated population. Genetic bottlenecks� as: bottlenecks 𝑓𝑓 Genetic� = 1/ 𝑁𝑁 and𝑁𝑁bottlenecks and 𝑞𝑞random random, where and genetic𝑞𝑞 random is the 𝑁𝑁drift𝑁𝑁 marginal genetic were 2were2𝑓𝑓𝑓𝑓 drift definedcontribution defined were 𝑓𝑓𝑓𝑓 defined of an ancestor j that is 126 Charbrayaverage coancestry calves, and in those the reference with126� an population.unknownaverage coancestry Charolais Genetic� 𝑁𝑁 bottlenecksin pro the­ reference and randompopulation.𝑁𝑁 genetic Genetic2𝑓𝑓 drift bottlenecks were𝑓𝑓 defined and random genetic drift were defined 126 average coancestry in the reference population. Genetic𝑁𝑁 bottlenecks and random𝑁𝑁 genetic2𝑓𝑓 drift were𝑓𝑓 defined � � portion were deleted from the data file. Then, the 127pedigree, as127 � the asas: the the and f a: fe: and: and �Nratios, g:fa :ratios, respectively.��� ratios, �respectively. respectively. Finally,� Finally, Finally,marginal marginal marginal and cumulated and and cumulated gene contributions gene contributions of the first of the first 127 as 127the : as and the : 127 andratios, as :respectively. the ratios, :𝑓𝑓 respectively.and Finally, : ratios,marginal Finally, respectively.𝑓𝑓 andmarginal cumulated∑ 𝑞𝑞Finally,and cumulated gene marginal 𝑞𝑞contributions gene and contributions cumulated of the first gene of the contributions first of the first 127 consistingas the : of andonly : ratios, Charolais 127respectively. as animals, the Finally,:125 was and marginal revised not: explained ratios, toand cumulated respectively. bycumulated other gene ancestors Finally, contributionsgene marginalcontributionschosen ofbefore. and the cumulatedfirst ofThe the first wasgene calculatedfifteen contributions ancestorsas of = the 1/ first g, where g is the 127 as the : and : ratios, respectively. Finally, marginal and cumulated gene contributions� � of� �the�� first𝑓𝑓� 𝑓𝑓�� � 𝑁𝑁� 𝑓𝑓� 𝑓𝑓� 𝑓𝑓� 𝑁𝑁� 𝑓𝑓� � 128� 𝑓𝑓 fifteen128𝑓𝑓 𝑓𝑓𝑁𝑁ancestorsfifteen𝑓𝑓𝑓𝑓 ancestors𝑁𝑁 with𝑓𝑓 the with maximum the maximum genetic geneticimpact weimpactre obtained were obtained for the latterfor the period latter (2014-2018).period (2014-2018). The The verify that i) sires only128 appearedfifteen as ancestors fathers, 𝑓𝑓butwith𝑓𝑓�𝑓𝑓128 𝑓𝑓not� the as maximum𝑁𝑁 𝑁𝑁mothers;fifteen�𝑓𝑓𝑓𝑓� ancestors geneticwith impactwith thethe we maximumre obtained genetic genetic for the impact impactlatter weperiod werere� obtained (2014-2018). obtained for thefor The latterthe � period (2014-2018). The � � � � 𝑓𝑓� 𝑓𝑓� 𝑁𝑁� 𝑓𝑓� 128128 fifteenfifteen ancestorsancestors126 withaveragewith thethe coancestry maximummaximum in geneticgenetic the reference impactimpact wepopulation.werere obtainedobtained Genetic forfor thethe𝑁𝑁 bottlenecks latterlatter periodperiod and (2014-2018). (2014-2018).random𝑁𝑁 genetic The2The𝑓𝑓 drift were𝑓𝑓 defined 128 fifteen 𝑓𝑓ancestors𝑓𝑓 𝑁𝑁 with128𝑓𝑓 the ii)maximumfifteen dams ancestors only genetic appeared withimpact the as wemaximum mothers,re obtained genetic but for not the impact as latter fathers; we periodre obtainediii) (2014-2018). forlatter the The latterperiod period (2014 (2014-2018). through 2018). The The expected marginal 129 expected marginal contribution129 expected129 of an individual expected129marginal expected marginal contributionquantifi marginales contribution its of contribution an contribution individual of an to individual thequantifi of referencean individuales quantifi its contributionpopulation, esquantifi its contribution eswhich to its the contribution reference to the reference population, to the reference population, which population, which which calves only appeared as progeny,129129 but expected notexpected as parent marginal 127marginal in theas contribution contribution the same : and of of ancontribution an :individual individual ratios, respectively.quantifi quantifiof an individualeses its its contributionFinally, contribution quantifies marginal to to the the and itsreference reference contributioncumulated population, population, gene to contributions which which of the first 129 expected marginal contribution129 expected of an marginalindividual contribution quantifies its of contribution an individual to quantifi the referencees its contribution population,the towhich reference the reference population, population, which which has not previously been record; iv) no calves were born before neither of theirhas130 nottwo previously has130 not previouslyhas been not explainedpreviously been explained by been greater explained by contributing greater by contributinggreater individuals. contributing individuals. A comprehensive individuals. A comprehensive A explanation comprehensive explanation of the explanation of the of the 130 has130 not previouslyhas not previously been130 explained been explainedby� greater� bycontributing� greater� contributing individuals. individuals. A comprehensive A comprehensive explanation explanation of the of the 130 has not previously128 fifteen been 𝑓𝑓 ancestorsexplained𝑓𝑓 𝑁𝑁explained withby𝑓𝑓 greater the maximum bycontributing greater genetic contributing individuals. impact we A individuals. comprehensivere obtained forA compre explanationthe latter­ period of the (2014-2018). The 130 has not previously been130 explainedparents;has not byandpreviously greater v) there contributing been were explained not individuals.repeated by greater records. A contributingcomprehensive After pediindividuals. explanation­ A comprehensive of the explanation of the 131 meaning131 hensivemeaning and computation explanation and computation of parameters of the of parametersmeaning based on andbased probabilities computation on probabilities of gene of origin of gene to origin evaluate to evaluate populations populations based based gree verification, the131 final meaning data131 file and meaningconsisted computation and of131 computation331,390 ofmeaning parameters records. of and parameters based computation on probabilities based of onparameters probabilities of gene based origin of on gene to probabilities evaluate origin to populations evaluate of gene originpopulations based to evaluate based populations based 131 meaning 129and computationexpected marginalof parameters contribution based on of probabilities an individual of quantifi gene origines its contributionto evaluate populations to the reference based population, which 131 meaning and computation131 ofmeaning parameters and basedcomputation on probabilities of parameters of gene based origin on probabilitiesto evaluate populations of geneparameters origin based to evaluate based populationson probabilities based of gene origin to evaluate Finally, pedigree data were divided into seven periods132 (or on132 pedigree on pedigree information information may be foundmay be elsewhere found elsewhere [2,3,13]. 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138 of founders and founder genomes. Gene contribution of ancestors was estimated with the PEDIG program

Ríos-Utrera et al (2021) Anim Biosci 34:1116-1122 effective numbers of founders and founder genomes. Gene is similar to that reported for three subpopulations of the contribution of ancestors was estimated with the PEDIG pro­ Brown Cattle of Switzerland (, US-Brown Swiss, gram [16]. and Braunvieh×US-Brown Swiss) [17]. On the contrary, in a more recent study that included American , only RESULTS AND DISCUSSION about 91% of the ancestors were known up to the third gen­ eration [18]. Evolution of the pedigree The number of animals in the reference population, in the Average complete generation equivalent pedigree and with two parents known increased from the Average complete generation equivalent consistently increased first (1984 through 1988) to the fifth period (2004 through across periods, from 4.76, for the first reference population 2008), but decreased from the fifth to the last period (2014 (1984 through 1988), to 7.86, for the last reference popula­ through 2018). The number of animals with one known par­ tion (2014 through 2018). This estimate of pedigree depth, ent rose from the 1984-1988 to the 1994-1998 period, but similar to the estimate of pedigree completeness (proportion the opposite was true from the 1994 through 1998 to the 2014 of known ancestors), indicates that the quality of the pedi­ through 2018 period (Table 1). gree has significantly progressed along the years (Table 2), reaching a high level in the last quinquennium. In a study Proportion of known ancestors conducted in France [19], a similar number of complete gen­ In general, proportion of known ancestors increased over eration equivalent was observed in the Aubrac (7.8), Charolais time periods in generations 1 to 5. In the paternal genera­ (7.9), Limousin (6.7), and Salers (8.0) breed, whereas the tion, proportion of known ancestors was very high, oscillating (5.8), Blonde d’Aquitaine (5.8), Flamande (5.8), from 0.9919, for the 1984 through 1988 subpopulation, to (6.2), (3.7), Gasconne (3.4), and Rouge 0.9999, for the 2014 through 2018 subpopulation. Proportion des prés bred (4.8) reached a smaller number of complete of known ancestors was also relatively high in the grandpa­ generation equivalent. rental and great-grandparental generations, ranging from 0.9148 to 0.9965, and from 0.8702 to 0.9898, respectively. In Inbreeding generations 4 and 5, proportion of known ancestors was not During the first seventeen years (1984 through 2000), the as high as in the three most recent generations, as expected, inbreeding coefficient showed some fluctuation across the oscillating from 0.7445 to 0.9686, and from 0.5660 to 0.9240, years. For example, inbreeding decreased rapidly from 1984 respectively; nevertheless, values across time periods revealed to 1985, increased moderately from 1985 to 1987, fell once that proportion of known ancestors has substantially im­ again from 1987 to 1989, rose sharply from 1989 to 1990, proved over time (Table 2). Proportion of known ancestors and decreased suddenly once again from 1990 to 1992; from in generations 1 to 5 of the 2014 through 2018 subpopulation 2000 to 2018, however, evolution of the inbreeding coefficient

Table 1. Pedigree evolution in the Mexican Charolais cattle population Item 1984-1988 1989-1993 1994-1998 1999-2003 2004-2008 2009-2013 2014-2018 NAR 7,008 18,706 35,336 49,771 61,990 51,815 48,783 NAP 25,363 52,260 82,929 110,595 132,765 128,122 127,430 NTP 19,221 42,187 70,387 97,013 119,797 115,897 115,756 NOP 281 393 553 408 369 342 326 NAR, number of animals in the reference population; NAP, number of animals in the pedigree; NTP, number of animals with two known parents; NOP, num- ber of animals with one known parent.

Table 2. Evolution of proportion of known ancestors and average complete generation equivalent (GE) in the Mexican Charolais cattle population Generation Period GE 1 2 3 4 5 1984-1988 0.9919 0.9148 0.8702 0.7445 0.5660 4.76 1989-1993 0.9973 0.9486 0.9083 0.8159 0.6524 5.30 1994-1998 0.9968 0.9404 0.9078 0.8565 0.7144 5.70 1999-2003 0.9997 0.9666 0.9403 0.9066 0.8139 6.31 2004-2008 0.9999 0.9820 0.9618 0.9381 0.8795 6.91 2009-2013 0.9999 0.9925 0.9796 0.9583 0.9162 7.44 2014-2018 0.9999 0.9965 0.9898 0.9686 0.9240 7.86

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indicates a relative steadiness across time. The slight decrease 1988) to the second period (1989 through 1993) for the four in inbreeding in the 2000 through 2018 period is attributed parent-offspring pathways, but increased from the third (1994 to the registration of a higher number of founder animals through 1998) to the seventh period (2014 through 2018). In and outcrossing with imported sires. The variation of the in­ general, the generation intervals of the two father-offspring breeding coefficient over the first seventeen years could be pathways were greater than those of the two mother-offspring caused by the relatively small number of the available animals. pathways. In cattle born during the last time period, the aver­ The average number of animals by year from 1984 to 2000 age generation interval of the father-offspring pathways was was 2.3 times smaller than that from 2001 to 2018. However, nearly 1 yr. longer than that of the mother-offspring pathways the coefficient of inbreeding ranged from 0.0110 (2003) to (Table 3). The same pattern has been observed in several dairy 0.0245 (1990) over the entire interval, showing inbreeding (Ayrshire, Guernsey, Holstein, Jersey) [25] and beef cattle has not been an issue in the registered Mexican Charolais populations (Simmental, Charolais, Limousin, Hereford, cattle population (Figure 1). Angus, Japanese Black) [5,23,26], whose generation inter­ The average inbreeding coefficient of 0.0135 in the latter vals of the two pathways from sires were longer than those quinquennium (2014 through 2018) is similar to those re­ two from dams, being largely attributed to the use of artificial ported for the Mexican Simmental population [5], Asturiana insemination whereby semen from certain sires were used de la Montaña [20], the American Limousin population [21], extensively over time and therefore resulting in sires used and the Italian Chianina, Marchigiana and Romagnola pop­ beyond their lifespan [25]. ulations [22]; though, for Japanese Black [23], American Hereford [24] and American Red Angus [18] the average Effective population size inbreeding coefficient was calculated as 0.05, 0.098 and ­al The Mexican Charolais cattle population had a steadily rise most 0.04, respectively. in effective size since 1984 and until 2013; but underwent a minor decline from 2013 to 2018. In general, the effective 24 Generation interval population size was moderately high, fluctuating from 105.0 The generation interval decreased from the first (1984 through to 237.1. The effective size of the population in the most 395

7.00

6.00

5.00

4.00

F (%) 3.00

2.00

1.00

0.00 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Year of birth 396 Figure 1. Evolution of inbreeding (F) in the Mexican Charolais cattle population from 1984 to 2018.

Table 3. Evolution of generation interval (years) by parent-offspring pathway in the Mexican Charolais cattle population Pathway 1984-1988 1989-1993 1994-1998 1999-2003 2004-2008 2009-2013 2014-2018 Father-son 7.4±0.39 7.0±0.22 6.8±0.15 8.1±0.17 8.2±0.13 8.8±0.16 8.5±0.28 Father-daughter 7.0±0.32 6.0±0.17 6.0±0.13 6.5±0.14 6.6±0.11 6.7±0.13 6.3±0.21 Mother-son 6.5±0.24 5.8±0.11 6.2±0.10 6.3±0.08 6.4±0.08 6.5±0.09 6.6±0.15 Mother-daughter 6.3±0.24 5.5±0.11 5.7±0.09 6.1±0.08 6.2±0.08 6.3±0.09 6.4±0.15 Average 6.7±0.05 5.8±0.03 5.9±0.02 6.4±0.02 6.5±0.02 6.6±0.02 6.5±0.05

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Ríos-Utrera et al (2021) Anim Biosci 34:1116-1122 recent period was 2.22 times greater than that in the initial from the fourth (1999 through 2003) to the seventh sub­ period (Table 4). The quality of the pedigree suggests the population (2014 through 2018). The effective number of effective population size was not biased upward (overesti­ founders decreased across the first three time periods, from mated), mainly that of cattle born in the last period, which 563.7 to 546.2, but exhibited a substantial increment across had the better pedigree quality (Table 2). Depending on the the last four quinquennia, from 645.2 to 886.8. The relatively animal breeding plan, several authors recommend keeping great difference between the total and the effective number an effective population size between 30 and 250 [27-29]. The of founders indicates that some founders were used widely, effective size of the most recent subpopulation is within this whereas others contributed little to the population (Table recommended range. 4). The effective number of founders maintained by the pop­ The effective population size maintained by the Mexican ulation along the years has been quite big, suggesting that a Charolais population in the latter period (2014 through 2018) large proportion of matings among unrelated animals has is 2.77 times smaller than that reported for the French Cha­ been possible; therefore, it may explain the milder inbreed­ rolais population [19], but is considerably greater than those ing coefficient observed in the present study. The effective of many other beef cattle populations, such as the American number of founders obtained in the current study is greater Hereford [24], the Irish Hereford and Simmental [26], the than that reported by other researchers [5,22,26,30], indi­ French Salers and Blonde d’Aquitaine [19], the Japanese Black cating that the Mexican Charolais cattle population was [23], the Spanish Asturiana de los Valles [13], the Mexican created from a higher number of individuals in comparison Simmental [5], the Italian Chianina, Marchigiana and Rom­ with other beef cattle populations. agnola [22], and the Austrian Braunvieh [30]. Effective numbers of ancestors and founder genomes Total and effective number of founders The population displayed a steadily increase in the effective The population had an increase in the total number of founders number of ancestors from the first (207) to the fifth period from the first (1984 through 1988) to the fourth subpopu­ (247); however, exhibited a decrease from the fifth to the lation (1999 through 2003), nevertheless, had a decline sixth period (239); from the sixth to the seventh period the

Table 4. Evolution of genetic variability estimates in the Mexican Charolais cattle population Estimate 1984-1988 1989-1993 1994-1998 1999-2003 2004-2008 2009-2013 2014-2018

Ne 105.0±28 157.1±36 164.3±38 226.4±48 232.8±47 237.1±47 233.2±42 f 5,861 9,680 11,989 13,174 12,599 11,883 11,348

fe 563.7 562.5 546.2 645.2 712.9 794.0 886.8

fa 207.0 216.0 232.0 246.0 247.0 239.0 244.0

Ng 130.1 133.8 138.3 143.7 136.4 128.0 127.7

Ne, effective population size based on increase of inbreeding coefficients; f, total number of founders;e f , effective number of founders; fa, effective number of ancestors; Ng, effective number of founder genomes.

Table 5. The fifteen Mexican Charolais ancestors with the maximum genetic contribution to the calves born from 2014 to 2018 Genetic contribution (%) Ancestor Gender Year of birth Number of calves Marginal Cumulated Ijoufflu Male 1993 1,034 1.8 1.8 Fandango Male 1990 146 1.7 3.4 Till Male 2000 34 1.5 5.0 Tattenhall impeccable Male 2000 17 1.4 6.4 Flambeau Male 2000 21 1.3 7.7 Amour de Paris Male 1965 356 1.3 9.0 Necessaire Male 1997 1,050 1.1 10.1 Vaillant Male 1964 343 1.0 11.1 Jumper Male 1994 833 1.0 12.1 Balmyle Vendetta Male 2004 559 1.0 13.1 Van Gohg Male 1984 240 1.0 14.1 Blason Male 1986 31 0.9 15.0 Quidquid Male 2000 28 0.9 15.8 Abraham Male 1975 695 0.8 16.7 Jourdan Male 1994 767 0.8 17.5

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population showed an increase once again, reaching 244 ef­ relationships among fe, fa, and Ng showed that loss of genetic fective ancestors (Table 4). The effective number of founder variability was due to genetic bottlenecks in the pedigree genomes increased from the 1984 through 1988 (130.1) to and random genetic drift; however, the magnitude of these the 1999 through 2003 period (143.7), but decreased from genetic variability estimates, along with that of the effective the fifth to the seventh period (127.7), revealing some loss of population size, indicate that the Mexican Charolais cattle alleles during the last fifteen years (2004 through 2018) (Table population has a relatively broad genetic base, larger than

4). The af :fe ratio suggests that the genetic diversity depletion that of a significant number of dairy and beef cattle popu­ in the last twenty years (1999 through 2018) was partially lations; therefore, it is not currently in danger of genetic caused by the formation of genetic bottlenecks in the pedi­ erosion. Expected progeny differences for several traits (e.g., gree. This ratio was 0.381, 0.346, 0.301, and 0.275 for cattle weaning weight, frame score, scrotal circumference, heifer born in the 1999 through 2003, 2004 through 2008, 2009 fertility, stayability) have been recently available (last eighteen through 2013, and 2014 through 2018 time periods, respec­ years) for breeders of the Charolais Charbary Herd Book tively. In addition, the Ng:fa ratio indicates that genetic drift de México and a widespread use of them is in process. This also caused loss of genetic variability in the Mexican Charolais fact is expected to enhance the use of a few sires with high cattle population; this latter ratio was 0.584, 0.552, 0.536, genetic merit; therefore, future monitoring of the genetic and 0.523, respectively. Even though the Mexican Charolais variability of the population and quantification of the effect cattle population lost some genetic diversity, its effective of inbreeding on economically important traits may be needed. numbers of ancestors and founder genomes are still high compared with the values reported by other authors for CONFLICT OF INTEREST Limousin, Abondance and [3]; Swiss brown cattle [17]; Irish Charolais, Limousin, Angus, Hereford, and We certify that there is no conflict of interest with any financial Simmental [26]; Austrian Simmental, Braunvieh, Pinzgauer, organization regarding the material discussed in the manu­ and Grauvieh [30]; and Italian Chianina, Romagnola, and script. Marchigiana [22]. ACKNOWLEDGMENTS Marginal genetic contribution of ancestors All fifteen Mexican Charolais ancestors with the largest ­ge The provision of the pedigree information by the Charolais netic contribution to the genome of the progeny born from Charbray Herd Book de México is greatly appreciated. 2014 to 2018 were males, with no females having a substantial genetic influence on the population. Among these ancestors, REFERENCES the most influential bull explained 1.8% of the total genetic variability, whereas the two least influential bulls explained 1. MacCluer JW, VandeBerg JL, Read B, Ryder OA. Pedigree 0.8%. The marginal genetic contribution of the first fifteen analysis by computer simulation. Zoo Biol 1986;5:147-60. ancestors was 17.5% of the total genetic variability (Table https://doi.org/10.1002/zoo.1430050209 5). Contrary to the marginal genetic contribution obtained 2. Lacy RC. Analysis of founder representation in pedigrees: in this study, McParland et al [26] reported that the most founder equivalents and founder genome equivalents. Zoo influential ancestor to the Charolais females born in 2004, Biol 1989;8:111-23. https://doi.org/10.1002/zoo.1430080 contributed about 8% of their genes. Similarly, in the Aus­ 203 trian Braunvieh, Pinzgauer, and Grauvieh cattle populations 3. Boichard D, Maignel L, Verrier É. The value of using proba­ almost 10% of the genes were accounted for by the genetic bilities of gene origin to measure genetic variability in a popu­ contribution of only one bull [30]. Overall, the relatively lation. Genet Sel Evol 1997;29:5-23. https://doi.org/10.1186/ high genetic variability of the Mexican Charolais population 1297-9686-29-1-5 may be partially explained by the facts that i) the popula­ 4. Román PSI, Ríos UA, Montaño BM, et al. Genetic improve­ tion derived from a relatively high number of founders, ii) ment of cattle in the tropics. In: González PE, Dávalos FJL, breeders have been importing semen and embryos, and iii) Rodríguez RO, editors. State of the art of the research and the use of a few bulls has not generally been a practice among technological innovation in tropical cattle farming. Mexico breeders. City, México: Redgatro; 2015. pp. 99-152. In conclusion, proportions of known ancestors and aver­ 5. Ríos Utrera Á, Vega Murillo VE, Montaño Bermúdez M, age complete generation equivalent revealed a highly acceptable Martínez Velázquez G, Román Ponce SI. Genetic diversity quality status (completeness and depth) of the current pedi­ assessment of the Mexican Simmental population through gree. Evolution of the inbreeding coefficient suggests that pedigree analysis. Rev Bras Zootec 2018;47:e20160088. https:// inbreeding has never been an issue in the population. Inter­ doi.org/10.1590/rbz4720160088

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