Resumen Los objetivos fueron analizar la estructura y variabilidad genética del bisonte americano con marcadores genéticos de tipo SNP. Se muestrearon 174 bisontes y se analizaron 42,366 SNP distribuidos en los 29 cromosomas. Se estimó la heterocigosis esperada (He) y observada (Ho), contenido de información polimórfica (CIP), índice de fijación (FIS), índice de Shannon (IS), desequilibrio de ligamiento y relación de parentesco (Rij; %), así como el tamaño efectivo de población (Ne). Se realizó un análisis de estructura genética para inferir cuántas líneas o genomas (k) definen la población. Se identificó y seleccionó un panel con 2,135 SNP polimórficos, con un promedio de 74 SNP por cromosoma. En el proceso de exclusión, 84.5 % fueron monomórficos, 8.5 % con porcentaje de usables menor a 90 %, 6.3 % con frecuencia del alelo menor inferior a 0.01 y 0.70 % por desequilibrio Hardy-Weinberg (P<0.05). Las estimaciones de IS, Ho, He, FIS y CIP fueron de 0.30, 0.187, 0.182, -0.029 y 0.152, respectivamente. Se generaron 15,051 estimaciones de Rij, el valor promedio de éstas fue 7.6 %, y el 45.1 % de ellas fue igual a cero. El Ne fue de 12.5, señalando un posible incremento de consanguinidad por generación de 4 %. Se identificaron tres líneas genéticas, con proporciones de 0.730, 0.157 y 0.113; dado el origen de la población, se asocian a selección natural o deriva genética. La variabilidad genética, así como los niveles de la Rij, se deben de considerar en esquemas de conservación.

Abstract Controlling for genetic variables to managing conservation populations. Single nucleotide polymorphism (SNP) genetic markers were used to analyze genetic structure and variability in an American bison population in the state of Chihuahua, Mexico. A total of 174 individuals were sampled and analysis done of 42,366 SNP distributed in 29 chromosomes. Estimates were done of expected (He) and observed (Ho) heterozygosity, polymorphic information content (PIC), the fixation index (FST), the Shannon index (SI), linkage disequilibrium (LD), kinship relationships (Rij; %), and effective population size (Ne). A genetic structure analysis was run to infer how many lines or genomes (k) define the studied population. A panel with 2,135 polymorphic SNPs was identified and selected, with an average of 74 SNP per chromosome. In the exclusion process, 84.5 % were monomorphic, 8.5 % had a usable percentage less than 90 %, 6.3 % had a minor allele frequency less than 0.01 and 0.70 % exhibited Hardy-Weinberg disequilibrium (P<0.05). Estimated values were 0.30 for the SI, 0.187 for Ho, 0.182 for He, -0.029 for the FST, and 0.152 for PIC. Of the 15,051 Rij estimates generated, the average value was 7.6 %, and 45.1 % were equal to zero. The Ne was 12.5, indicating a possible increase of 4 % in consanguinity per generation. Three genetic lines were identified (proportions = 0.730, 0.157 and 0.113), and, given the study population’s origin, are probably associated with natural selection or genetic drift. Genetic variability, as well as Rij levels, must be considered in conservation schemes.

Resumen El objetivo fue el ajuste de un modelo no lineal (MNL) para evaluar la curva de crecimiento en bovinos Limousin, en pureza de raza (PRZ) y cinco grados de cruzamiento (GPZ; 1/2, 3/4, 7/8, 15/16, 31/32 de Limousin). Se analizó el peso vivo, el intervalo de peso al nacer a 500 días de edad. Se evaluaron cuatro MNL: Brody, Bertalanffy, Gompertz y logístico. Se estimaron parámetros de crecimiento: peso adulto (PAD); tasa de crecimiento (TAC); edad (EPI; meses) y peso (PPI; kg) al punto de inflexión; edad (meses; E50M) para alcanzar 50% de madurez y madurez a 15 meses (GM15). Con el MNL seleccionado en PRZ se caracterizó la curva de crecimiento en GPZ. El modelo de mejor ajuste fue Bertalanffy. El PAD para machos PRZ fue 566.1, para GPZ estuvo en el intervalo de 446.9 a 527.4; para hembras, en GPZ estuvo en el intervalo de 374.5 a 419.9, en PRZ fue 443.0. Los MNL presentaron correlaciones por debajo de -0.75 entre PAD y TAC. En vaquillas de PRZ, EPI se estimó a 3.7 con 131.2 para PPI; en GPZ, EPI y PPI estuvieron en los intervalos de 2.9 a 3.7 y 110.9 a 124.4, respectivamente. E50M para hembras, en PRZ fue a 10.6 y para GPZ en el intervalo de 8.9 a 10.5. GM15 para hembras, en GPZ el promedio fue 90.5 % en PRZ fue de 87.9 %. Los machos en PRZ alcanzan E50M a partir de 13 meses.

Abstract The objective was to fit a non-linear model (NLM) to evaluate the growth curve in purebred (PB) Limousin cattle and in five degrees of crossbreeding (DCBs: 1/2, 3/4, 7/8, 15/16, 31/32 Limousin). Live weight, the birth weight interval at 500 d of age, was analyzed. Four NLMs were evaluated: Brody, Bertalanffy, Gompertz, and logistic. Growth parameters were estimated: adult weight (ADW); growth rate (GR); age (AIP; months) and weight (WIP; kg) at inflection point; age (months; A50M) to reach 50 % maturity and degree of maturity at 15 mo (DM15). The growth curve in DCB was characterized using the NLM selected for BP. The best-fitting model was Bertalanffy. The ADW for purebred (PB) males was 566.1, for crossbred (CB) males it was in the range of 446.9 to 527.4; for CB females it was in the range of 374.5 to 419.9, and for PB females, it was 443.0. The NLMs exhibited correlations below -0.75 between ADW and GR. In PB heifers, AIP was estimated at 3.7, and WIP, at 131.2; in CB heifers, AIP and WIP were in the ranges of 2.9 to 3.7 and 110.9 to 124.4, respectively. A50M for PB females was 10.6, and for CB females, within the range of 8.9 to 10.5. DM15 for CB females, the average was 90.5 %, and 87.9 % for PB females. PB males reach A50M at the age of 13 mo.

Abstract Sperm motility and kinematics analysis are important to predict bull fertility. However, there are other molecules in the sperm with the ability to improve the pregnancy rate. For example, PLCZ1 is a sperm protein that plays a unique role in the activation of the zygote and is important for the survival of the embryo. The objective of this work was to compare the expression of PLCZ1 mRNA in sperm cells of Chihuahuan Criollo and European bulls in the winter and summer seasons, under a low-input system. Six (3.33 ± 0.43 years old) bulls (three Criollo, three European) were used. Gross and individual motility were measured in semen obtained by electrostimulation. The cell pack was pelletized by centrifugation and stored in liquid nitrogen. The sperm cells were purified and total RNA was extracted. cDNA was synthesized to perform qPCR and measure the relative level of PLCZ1 transcripts in each bull. There were no differences in individual motility, however, gross motility was lower (P < 0.05) in Criollo bulls, both in the winter (71.1 ± 2.8 vs. 76.6 ± 2.8%) and in the summer season (58.9 ± 2.8 vs. 77.7 ± 2.8%). PLCZ1 expression was 5.3 times higher (P < 0.05) in winter than in summer (5.09 ± 1.09 vs 0.959 ± 1.09). No difference (P>0.05) was found in the expression levels of PLCZ1 between both breeds (4.36 ± 1.09 vs 1.69 ± 1.09), for Criollo and European, respectively. Although the animals presented seminal motility within the recommended limits for insemination, the expression levels of PLCZ1 vary depending on the time of the year and this might impact the rate of successful pregnancies. Therefore, it is important to complement conventional analysis of seminal quality with molecular characteristics.

ABSTRACT: The objectives were to analyze the genealogical information of Gyr (GY) and Nelore (NL) cattle from Costa Rica. Analyzed: pedigree integrity (GY, 13272; NL, 18153); number of complete, maximum traced and equivalent complete generations; inbreeding (FI); generation interval (GI) through four selection routes; average additive genetic ratio (AGR); effective number of founders (fe); effective number of ancestors (fa); effective population size (Ne). The analysis was performed with the ENDOG software. The maximum proportion of unknown parents, grandparents, and great-grandparents was 18.6%, 39.9%, and 59.3%, respectively. The average FI for NL was 8.87% and 2.85% in GY. The average consanguineous population (%) and FI was 53.9 and 16.5% in NL, 28.9 and 9.9% in GY. The average and maximum values of AGR for NL were 3.5 and 12.8, 1.4 and 5.6 in GY. The fe and fa for NL were 65.0 and 38.0, in GY 145.7 and 59.0. The Ne indicated increases in FI in the range of 1 to 2% in GY, for NL greater than 2%, with a status of care to monitor the evolution of F and AGR and their possible implications in genetic improvement. The GI ranged from 6.3 to 7.9 years with a general average of 6.9 years. These results show a summary of the genetic and reproductive management those breeders have carried out.

RESUMO: Os objetivos foram analisar as informações genealógicas de bovinos Gir (GY) e Nelore (NL) da Costa Rica. Foram considerados: integridade do pedigree (GY, 13272; NL, 18153); número de gerações completas, máximas traçadas e equivalentes completas; endogamia (FI); intervalo de geração (GI) por meio de quatro rotas de seleção; razão genética aditiva média (AGR); número efetivo de fundadores (fe); número efetivo de ancestrais (fa); tamanho efetivo da população (Ne). A análise foi realizada com o software ENDOG. A proporção máxima de pais, avós e bisavós desconhecidos foi de 18,6%, 39,9% e 59,3%, respectivamente. O FI médio para NL foi de 8,87% e 2,85% no GY. A média da população consanguínea (%) e FI foi de 53,9 e 16,5% em NL, 28,9 e 9,9% em GY. Os valores médios e máximos de AGR para NL foram 3,5 e 12,8, 1,4 e 5,6 no GY. Os fe e fa para NL foram 65,0 e 38,0, no GY 145,7 e 59,0. O Ne indicou aumentos de FI na faixa de 1 a 2% no GY, para NL superiores a 2%, com status de cuidado para acompanhar a evolução de F e AGR e suas possíveis implicações no melhoramento genético. O IG variou de 6,3 a 7,9 anos com média geral de 6,9 anos. Esses resultados mostram um resumo do manejo genético e reprodutivo realizado por esses criadores.

RESUMO: Os objetivos deste estudo foram analisar o pedigree (41.521 registros de 1958 a 2019) da raça Sardo Negro para avaliar a estrutura, evolução e variabilidade genética (VG) da população. Os parâmetros genéticos populacionais utilizados foram: número efetivo de fundadores (fe) e ancestrais (fa); integridade do pedigree; relação genética aditiva (RGA); número de gerações completas (NGC), máximo plotado (NGT) e equivalentes (NGE); tamanho efetivo (Ne); consanguinidade (F); intervalo geracional (IG). O IG médio foi de 7,45 anos. Foram identificados 7.804 fundadores e 4.856 ancestrais, para fe 185 e 97 na fa. As médias e máximas para NGC, NGE e NGT foram 1,6 e 5,0, 2,5 e 6,5, 4,3 e 12, com estimativas de Ne 15,9, 25,9 e 69,0, respectivamente. O aumento de F, vinculado ao Ne, ficou na faixa de 0,72% a 3,1% por geração. A média para F 3,6% e 1,0% em RGA; a proporção de consanguíneos foi de 32,0%, com F na faixa de 0,01 a 62,2% e média de 11,3%. A taxa da população consanguínea foi de 1,3% ao ano. No RGA, a taxa ao ano era de 0,04%. Para a continuidade e projeção da raça, deve-se considerar a evolução de F em função de Ne e as possíveis implicações dos esquemas de seleção. A variabilidade genética sustentada ao longo do tempo resulta do Ne.

ABSTRACT: This study analyzed the Sardo Negro breed pedigree (41,521 animals registered from 1958 to 2019) to determine its structure, evolution, and genetic variability (GV). The population genetic parameters evaluated were effective number of founders (fe) and ancestors (fa), pedigree integrity, additive genetic relationship (AGR); number of complete generations (NCG), maximum generations traced (NMGT), and equivalent complete generations (NECG); effective population size (Ne), inbreeding coefficient (F), and generation interval (GI). The average GI was 7.45 years. A total of 7,804 founders and 4,856 ancestors were identified for a fe of 185 and a fa of 97. The average and maximum values of NCG, NECG, and NMGT were 1.6 and 5.0, 2.5 and 6.5, 4.3 and 12, with Ne estimates of 15.9, 25.9, and 69.0, respectively. The increase in F, linked to Ne, ranged from 0.72% to 3.1% per generation. The average values for F and AGR were 3.6% and 1.0%, respectively. The proportion of inbred individuals was 32.0%, with F values ranging from 0.01 to 62.2% and an average of 11.3%. The rate of inbred population was 1.3% per year. The annual rate of AGR was 0.04%. For the continuity and projection of the breed, the evolution of F as a function of Ne and the possible implications of the selection schemes must be considered. The genetic variability sustained over time results from the Ne.

ABSTRACT This study aimed to evaluate the lactation curve of female Murrah buffaloes, using mixed nonlinear models (NLM), across three lactation periods (180 d, 210 d, and 240 d). A total of 5334 data on daily milk production (kg) were analyzed. The data were collected every seven days in the interval of one to 250 days of lactation, corresponding to 221 lactations and 145 females, with calvings from 2017 to 2019. The data came from a herd located in the Centro municipality, Tabasco, Mexico. Five NLM were evaluated: Wood (WOD), Wiltmink (WIL), Cobby (COB), Brody (BRO), Sikka (SIK). The best fit model was selected based on the mean prediction error, mean absolute percentage error (MAPE), prediction error variance, coefficient of determination (R2), concordance correlation coefficient (CCC), Akaike (AIC) and Bayesian (BIC) information criteria. A regression analysis was performed between the observed and predicted values. All the NLM had a R2 above 0.91. They tend to underestimate the predictions, without residual autocorrelation. The MAPE showed an average value of 23.5%. The best fit model was WOD, followed by SIK and BRO. For WIL and COB, the mixed model did not improve the fitting. The shortest lactation period showed the best fit, followed by the 210 d and 240 d periods. The relationship between observed:predicted values fluctuated from 0.65 to 1.00, with an average value of 0.94. The use of NLM transcended in the AIC and BIC. The evaluated models showed goodness of fit, with good predictability, but low values in accuracy and precision of prediction.

Abstract In order to define the SNP panel for paternity tests in cattle, genotypes were analyzed in three breeds (number of SNPs evaluated and individuals sampled): Hereford (HER; 202; 1317), Brangus (BRA; 217; 3431) and Limousin (LIM; 151; 8205). Within breed, SNPs with a percentage of genotyped individuals (PGI) less than 90 %, with Hardy-Weinberg disequilibrium (HW; P<0.05), with allele frequency less than 0.10 or less and with linkage disequilibrium, where the correlation between genotypic frequencies was greater than 0.25, were discarded. The levels of expected (He) and observed (Ho) heterozygosity, polymorphic information content (PIC) were estimated; as well as the Shannon index, the fixation index and effective population size (Ne). The combined exclusion probability (CEP) and identity probability (CIP) were calculated. The final panel was 121, 188 and 113 SNPs in HER, BRA and LIM, respectively; the main source of discard was HW followed by PGI. Levels of Ho and He were above 0.40; CIP was greater than 0.32 and Ne presented estimates above 181.3. The results for CEP were higher than 0.999999; for CIP, they were below 1 x 10-20.

Resumen Con el objetivo de definir el panel de polimorfismos de nucleótido simple (SNP) para pruebas de paternidad en bovinos, se analizaron los genotipos en tres razas (número de SNP evaluados e individuos muestreados): Hereford (HER; 202; 1317), Brangus (BRA; 217; 3431) y Limousin (LIM; 151; 8205). Dentro de raza, se descartó los SNP con porcentaje de individuos genotipados (PIG) menor a 90 %, con desequilibrio Hardy Weinberg (HW; P<0.05), con frecuencia de alelo menor de 0.10 o menos y con desequilibrio de ligamiento, donde la correlación entre frecuencias genotípicas fue superior a 0.25. Se estimó los niveles de heterocigosis esperada (He) y observada (Ho), contenido de información polimórfica (CIP); así como, el índice de Shannon, el índice de fijación y tamaño efectivo de población (Ne). Se calculó la probabilidad de exclusión (PEC) y de identidad combinada (PIC). El panel final fue de 121, 188 y 113 SNP en HER, BRA y LIM, respectivamente; la principal fuente de descarte fue HW seguido de PIG. Los niveles de Ho y He fueron superior a 0.40; el PIC fue mayor a 0.32 y Ne presentó estimaciones por arriba de 181.3. Los resultados para la PEC fueron superiores a 0.999999; para la PIC, estuvieron por debajo de 1 x 10-20.

ABSTRACT The objective of this study was to evaluate the population of Brahman cattle from Costa Rica. Pedigree analysis of 98,749 animals was used to estimate the following parameters: pedigree integrity, as a proportion of known ancestors; the number of complete generations, maximum generations traced, and equivalent complete generations; inbreeding coefficient (F); generation interval (GI) across four selection paths; additive genetic relationship (AGR); effective number of founders (fe) and ancestors (fa); and effective population size (Ne). The analysis was carried out using the ENDOG software. The maximum proportions of unknown parents, grandparents, and great-grandparents were 14.1%, 38.9%, and 61.2%, respectively. Average F for the whole population was 0.86, while 27.4% of the population was inbred, with an average F of 3.1%. The inbred population increased through the time, while F decreased. The average AGR was 0.64, with maximum values of 4.1 and positive trends. The fe and fa were 617.8 and 172.0, respectively. The Ne indicated increases of F, with values lower than 1%. The GI fluctuated from 6.4 to 7.4, with an average of 6.85 years. These results summarize previous breeding practices and represent useful information for designing breeding programs by anticipating the relationship between the selection response and increases of inbreeding.

Abstract Metagenomics uses molecular biology techniques to analyze the diversity of microbial genomes (metagenomes). Metagenome diversity has been analyzed using molecular markers to classify bacteria and archaea into taxonomic groups at the genus level. Among the most widely used molecular markers are ribosomal genes, genes encoding subunits of cytochrome C, and certain constitutive genes (gyrB, rpoB, rpoD, recA, atpD, infB, groEL, pmoA, sodA). The most widely used marker for classifying bacteria and metagenomic samples is the 16S rRNA gene, although it does not allow certain sequences to be properly classified. However, all the sequences of the hypervariable regions can be identified with the sequencing of the complete 16S rRNA gene, and, therefore, this molecular marker has made it possible to classify them at the species taxonomic level. Next generation sequencing, also called mass sequencing or high throughput sequencing, has helped to describe complex metagenomes such as those of environmental samples, which have an ecological importance, as well as metagenomes growing in extreme environments. They have also proved helpful in studies related to animal and human health, and in the agro-food field. Specifically, both the 16S rRNA molecular marker and high throughput sequencing combined with bioinformatic tools for metagenomic analysis have been used to describe the ruminal metagenome, a microbial community of great importance because it is involved in animal production of meat and milk. Despite the many studies that have been conducted in this field, some microorganisms still remain to be discovered and characterized.

Resumen La metagenómica utiliza técnicas de biología molecular para analizar la diversidad de los genomas microbianos (metagenomas). La diversidad de los metagenomas se ha analizado mediante marcadores moleculares para clasificar bacterias y arqueas en grupos taxonómicos a nivel de género. Entre los marcadores moleculares más utilizados se encuentran los genes ribosomales, genes que codifican subunidades del citocromo C y algunos genes constitutivos (gyrB, rpoB, rpoD, recA, atpD, infB, groEL, pmoA, sodA). El marcador más utilizado es el gen 16S rRNA para clasificar bacterias y arqueas de muestras metagenómicas, aunque no permite clasificar de forma adecuada algunas secuencias. Sin embargo, con la secuenciación del gen completo 16S rRNA se identifican todas las secuencias de las regiones hipervariables, por lo que se ha logrado clasificar hasta nivel taxonómico de especie con este marcador molecular. La secuenciación de próxima generación, también llamada secuenciación masiva o de alto rendimiento ha ayudado a describir metagenomas complejos como los de muestras ambientales, con importancia ecológica, así como metagenomas que crecen en ambientes extremos. También han ayudado a estudios relacionados con sanidad animal y en humanos, y en el ámbito agroalimentario. Específicamente, tanto el uso del marcador molecular 16S rRNA como la secuenciación de alta eficiencia combinadas con el uso de las herramientas bioinformáticas para el análisis metagenómico se han usado para describir el metagenoma ruminal, una comunidad microbiana de gran importancia debido a que está involucrada en la producción animal de carne y leche. A pesar de los muchos estudios que se han realizado en este campo, aún faltan microorganismos por descubrir y caracterizar.

Abstract Pedigree analysis is vital in designing genetic improvement strategies. Population genetic parameters were analyzed in ten sheep breeds in Mexico: Blackbelly (BBL; n= 19,695); Charollais (CHA; n= 5,033); Dorper (DOR; n= 42,171); White Dorper (DOB; n= 4,213); Dorset (DOS; n= 5,557); Hampshire (HAM; n= 12,210); Katahdin (KAT; n= 77,955); Pelibuey (PEL; n= 42,256); Rambouillet (RAM; n= 11,951); and Suffolk (SUF; n= 14,099). All animals were born between 1992 and 2018. The analyses were run with the ENDOG software. Known parents values ranged from 76.4 % (SUF) to 95.3 % (KAT), with an 86.0 % average; animals with unknown parents corresponded to founders. The consanguineous population (as a percentage of total population) fluctuated from 12.3 % in DOS to 48.7 % in DOB, with a 29.7 % average. Average inbreeding (F) ranged from 3.9% (KAT) to 14.6% (DOB), with an 8.0 % average. The proportion of consanguineous individuals in all populations increased (P<0.05). Genetic relatedness was stable, and F had negative trends (P<0.05). The highest consanguineous population growth rates were present in the KAT, DOB and BBL populations. Inbreeding (F) was highest in DOB and DOS, while genetic relatedness was highest in DOB and CHA. Effective population size (Ne) was greater than 50 in six of the populations but less than 37 in the remaining four. These low Ne values highlight the need to monitor the evolution of F and its possible implications. The generational interval (GI) ranged from 3.0 to 4.15, with a 3.45 years’ average. The highest GI values were for RAM and SUF, and the lowest for BBL and DOR.

Resumen Se analizó el pedigrí en diez razas de ovinos mediante parámetros genéticos poblacionales. Las poblaciones fueron Blackbelly (BBL; 19,695), Charollais (CHA; 5,033), Dorper (DOR; 42,171), Dorper Blanco (DOB; 4,213), Dorset (DOS; 5,557), Hampshire (HAM; 12,210), Katahdin (KAT; 77,955), Pelibuey (PEL; 42,256), Rambouillet (RAM; 11,951) y Suffolk (SUF; 14,099); nacidos de 1992 a 2018. Los análisis se realizaron con el software Endog. En padres conocidos, los valores oscilaron de 76.4 % (SUF) a 95.3 % (KAT), con promedio general de 86.0%, los animales con padres desconocidos correspondieron a los fundadores. La población consanguínea (como porcentaje de la población total) fluctuó del 12.3 % en DOS al 48.7 % en DOB, con promedio general de 29.7 %; la consanguinidad (F) promedio osciló de 3.9 (KAT) a 14.6 (DOB), con promedio general de 8.0. La evolución de F y sus componentes fue: en todas las poblaciones, la proporción de consanguíneos se incrementó (P<0.05); los niveles de relación genética (RG) son estables; y, la F presentó tendencias negativas (P<0.05). KAT, DOB y BBL con altas tasas de crecimiento en población consanguínea; DOB y DOS, DOB y CHA con los niveles más altos de F y RG, respectivamente. Seis poblaciones presentaron tamaño efectivo (Ne) mayor a 50; el resto presentaron Ne menor a 37, lo cual señala el estatus de cuidado para monitorear la evolución de F y sus posibles implicaciones. El intervalo generacional (IG) osciló de 3.0 a 4.15, con promedio general de 3.45 años, los mayores IG fueron para RAM y SUF, BBL y DOR con IG menores.

Abstract Characterizing growth in livestock is important when making management, marketing and genetic improvement decisions. Nonlinear models were tested to identify those with the best fit for growth curves in seven sheep breeds [Blackbelly (n= 19,084); Pelibuey (n= 39,025); Dorper (n= 35,814); Katahdin (n= 74,154); Suffolk (n= 10,267); Hampshire (n= 7,561); and Rambouillet (n= 7,384)]. Using breed registry databases, live weight was assessed from birth to 230 d of age. The SAS program was applied to test six nonlinear models: Brody, Verhulst, von Bertalanffy, Gompertz, Mitscherlich and logistic. The criteria for selecting the best-fit model were the average prediction error; the prediction error variance; the Durbin-Watson statistic; the coefficient of determination; the root-mean-square error; and the Akaike and Bayesian information criteria. For the Hampshire, Pelibuey and Suffolk breeds the best-fit model was the von Bertalanffy, with a sigmoid curve and an inflection point age between 40 and 57 d. For the Katahdin, Blackbelly, Dorper and Rambouillet breeds the best-fit models were the Brody and Mitscherlich models, with a continuous growth curve, no inflection point and constant growth rate. Marked differences were observed in adult weight between breeds, with average values (kg) of 44.6 for Blackbelly, 49.2 for Rambouillet, 52.9 for Pelibuey, 55.6 for Hampshire, 60.2 for Katahdin, 64.7 for Suffolk and 65.2 for Dorper; values tended to be highest in the Brody and Mitscherlich models, and lowest in the logistic and Verhulst models.

Resumen Caracterizar el crecimiento ayuda en la toma de decisiones de manejo, comercialización y mejoramiento genético. El objetivo fue identificar un modelo no lineal (MNL) para describir la curva de crecimiento en borregas de registro a través de siete razas. Se evaluó el peso vivo, desde el nacimiento hasta los 230 d de edad, de las razas Blackbelly (BB; n= 19,084), Pelibuey (PE; n= 39,025), Dorper (DR; n= 35,814), Katahdin (KT; n= 74,154), Suffolk (SF; n= 10,267), Hampshire (HS; n= 7561) y Rambouillet (RB; n= 7,384). Se evaluaron los MNL: Brody (BRO), Verhulst (VER), Von Bertalanffy (VBE), Gompertz (GOM), Mitscherlich (MIT) y Logístico (LOG). Los análisis se realizaron con el software SAS. Los criterios para seleccionar el modelo con mejor ajuste fueron: error de predicción promedio, varianza del error de predicción, estadístico Durbin-Watson, coeficiente de determinación, raíz del cuadrado medio del error, criterios de información Akaike y Bayesiano. Para HS, PE y SF, el mejor modelo fue VBE, con una curva sigmoide y edad al punto de inflexión entre 40 y 57 d. Los modelos BRO y MIT tuvieron el mejor ajuste para KT, BB, DR y RB, con una curva continua, sin punto de inflexión y tasa de crecimiento constante. Para peso adulto se observaron marcadas diferencias, con valores promedio (kg) de 44.6 en BB, 49.2 en RB, 52.9 en PE, 55.6 en HS, 60.2 en KT, 64.7 en SF y 65.2 en DR; con la tendencia de valores mayores para los modelos BRO y MIT, y los menores para LOG y VER.

Abstract: The objectives were to characterize the growth of Siboney cows with nonlinear models (MNL) and the effects of growth parameters on age at first mating (AFM). It was analyzed 10 064 live weight data from 2 021 heifers. The MNL evaluated were Logistic, Gompertz, Brody and Bertalanffy. The selection of best model was with the coefficient of determination, Akaike and Bayesian criteria. With a linear regression of quadratic order, the AFM was analyzed with respect to the weight at 24 months (W24M), growth rate (GRA), weight at the point of inflection (WPI) and maturity at 24 months (M24M). The MNL of best fit was Bertalanffy; with asymptotic weight of 514.3 kg, inflection point was at 5.93 months with 152.4 kg. From the regression analysis: AFM = (0.026102)(W24M) - (0.0000636)(W24M2), AFM = (23.86)(GRA) - (59.17)(GRA2), AFM = (0.0796)(M24M) - (0.000675)(M24M2), AFM = (0.0299)(WPI) - (0.00009506)(WPI2), all different from zero (p < 0.01).

Resumen: El objetivo fue caracterizar el crecimiento de vacas Siboney con modelos no lineales (MNL) y los efectos de los parámetros de crecimiento sobre la edad al primer empadre (EPE). Se analizaron 10 064 datos de peso vivo de 2 021 vaquillas. Los MNL evaluados fueron logístico, Gompertz, Brody y Bertalanffy. La selección del mejor modelo fue con el coeficiente de determinación, criterios Akaike y Bayesiano. Con regresión lineal de orden cuadrático, la EPE se analizó con respecto al peso a 24 meses (P24M), tasa de crecimiento (TAC), peso al punto de inflexión (PPI) y madurez a los 24 meses (GM24). El MNL de mejor ajuste fue Bertalanffy; con peso asintótico de 514.3 kg, punto de inflexión a los 5.93 meses con 152.4 kg. Del análisis de regresión: EPE = (0.026102)(P24M) - (0.0000636)(P24M2), EPE = (23.86)(TAC) - (59.17)(TAC2), EPE = (0.0796)(GM24) - (0.000675)(GM242), EPE = (0.0299)(PPI) - (0.00009506)(PPI2), todos diferente de cero (p < 0.01).

Abstract: The objective of this study was to evaluate genetic diversity of seven Mexican beef cattle populations, using pedigree analyses. The analyses were carried out with the Endog software, using information of the registered animals on national herd-book of each breed. The size of the populations studied were: Angus (AN)= 73,271; Black Brangus (BN)= 68,474; Red Brangus (BR)= 12,925; Hereford (HE)= 13,248; Limousin (LI)= 53,221; Salers (SA)= 14,065; and Braunvieh (SE)= 184,788. In general, the populations showed important improvements in pedigree integrities for the more recent 10 yr, with comparative parameters to other published in cattle populations. The generation interval varied among breeds from 5.1 to 7.2 yr. The average inbreeding and relatedness coefficients were relatively low in the different populations (0.9-4.2 and 0.3-6.5 %, respectively); although increases of these indicators during the 10 more recent years were detected in some breeds (BN, BR and HE). The effective population size of studied populations fluctuated between 24 and 192, with values lower than 50 in BR and SA. The parameters related with probability of gene origin indicated that the unbalanced contribution of founders, the bottlenecks and genetic drift have had an important effect on the current populations with the consequent losses in genetic diversity. It is recommended to continue or adopt mating strategies that minimize inbreeding and the intensive use of few animals to maintain genetic variability in future generations, and to increase the genetic diversity through the strategical use of genes from other countries.

Resumen: El objetivo de este estudio fue evaluar la diversidad genética de siete poblaciones de bovinos para carne en México, mediante análisis de sus pedigríes. Los análisis se realizaron con el programa Endog, utilizando información de los animales inscritos en el libro genealógico nacional de cada raza. Los tamaños de los pedigríes estudiados fueron: Angus (AN)= 73,271; Brangus Negro (BN)= 68,474; Brangus Rojo (BR)= 12,925; Hereford (HE)= 13,248; Limousin (LI)= 53,221; Salers (SA)= 14,065; y Suizo Europeo (SE)= 184,788. En general, las poblaciones mostraron mejoras importantes en la integridad de sus pedigríes en los 10 años más recientes, con parámetros comparables a los publicados en otras poblaciones de bovinos. El intervalo generacional varió de 5.1 a 7.2 años entre razas. Los coeficientes de consanguinidad y de relación genética aditiva promedio fueron relativamente bajos en las diferentes poblaciones (0.9-4.2 y 0.3-6.5 %, respectivamente); aunque en algunas razas (BN, BR y HE) se detectaron incrementos de estos indicadores en los 10 años más recientes. El tamaño efectivo de población fluctuó entre 24 y 192, con valores menores que 50 en BR y SA. Los parámetros relacionados con la probabilidad de origen de los genes indican que las contribuciones desbalanceadas de los animales fundadores, los cuellos de botella y la deriva genética, han tenido un efecto importante en las poblaciones actuales, con la consecuente pérdida de diversidad genética. Se recomienda continuar o adoptar estrategias de apareamiento que minimicen la consanguinidad, y el uso intensivo de pocos animales para mantener la variabilidad genética de futuras generaciones, así como ampliar la diversidad genética mediante el uso estratégico de genes provenientes de otros países.

Abstract: In Lidia cattle breed, the selection is based on the performance of the bull during the fighting. Head position (HP) and hands (PH), course of the bull (CB) and finish of the onslaught (FO), define the performance of the bull, and can be implemented as selection criteria. The objective was to estimate heritability (h2) and genetic correlation (rg) for HP, PH, CB and FO; and building two selection indexes: IS1 with relative values of factorial analysis, IS2 by relative values from the standard deviation of each trait. The response to selection (RS) and accuracy (AC) were calculated. The number of observations (average ± standard deviation) value for HP, PH, CB and FO were 984 (5.46 ± 1.4), 978 (2.93 ± 1.1), 981 (3.15 ± 0.7) and 785 (2.88 ± 1.1), respectively; with scales of one to seven for HP, and one to five for the rest of the variables. For h2 and rg a multivariate analysis was performed with MTDFREML software. The h2 was of 0.20 ± 0.06, 0.15 ± 0.05, 0.13 ± 0.03 y 0.17 ± 0.05 for HP, CB, PH y FO, respectively. All rg were positive, from 0.57 to 0.94, with average value of 0.753. IS1 = 0.068*HP + 0.048*CB - 0.012*PH + 0.088*FO; with AC of 0.46 and RS of 0.325. IS2 = 0.231*HP + 0.249*CB - 0.038*PH + 0.298*FO; with AC of 0.45 and RS of 1.15.

Resumen: En la ganadería de lidia, la selección está en función del desempeño del toro durante la lidia. Posición de la cabeza (PC) y de las manos (PM), recorrido del toro (RE) y modo de finalizar (FI) la embestida define el desempeño del toro, y pueden ser considerados como criterios de selección. El objetivo fue estimar heredabilidades (h2) y correlaciones genéticas (rg) para PC, PM, FI y RE; y construir dos índices de selección: IS1 con valores relativos de un análisis factorial, IS2 con valores relativos a partir de la desviación estándar de cada rasgo. Se calculó la respuesta a la selección (RS) y exactitud (EX) de cada IS. El número de observaciones (valor promedio ± desviación estándar) para PC, PM, RE y FI fue 984 (5.46 ± 1.4), 978 (2.93 ± 1.1), 981 (3.15 ± 0.7) y 785 (2.88 ± 1.1), respectivamente; con escalas de uno a siete para PC, y de uno a cinco para el resto de las variables. Para h2 y rg se realizó un análisis multivariado con el software MTDFREML. La h2 fue de 0.20 ± 0.06, 0.15 ± 0.05, 0.13 ± 0.03 y 0.17 ± 0.05 para PC, RE, PM y FI, respectivamente; todas las rg fueron positivas, de 0.57 a 0.94, con valor promedio de 0.753. IS1 = 0.068*PC + 0.048*RE - 0.012*PM + 0.088*FI; con EX de 0.46 y RS de 0.325. IS2 = 0.231*PC + 0.249*RE - 0.038*PM + 0.298*FI; con EX de 0.45 y RS de 1.15.

ABSTRACT: The objective was to characterize the growth of Cebu cattle in grazing performance tests. We used 15 990 live weight data, taken between 150 and 630 d of age, of 3 198 males with five weights each: 1) weaning weight (WW), 2) initial test weight (IW), 3) first weighing (W1), 4) second weighing (W2) and 5) final test weight (FW). Nonlinear models (NLM) were compared: Brody (BRO), Logistic (LOG), von Bertalanffy (BER) and Gompertz (GOM). Two types of analyses (ANA1, ANA2) were carried out with the SAS NLMIXED procedure: ANA1 with mixed NLM (MNLM), by including the random effect of a regression coefficient; and ANA2 with MNL, with no random effects associated with regression coefficients. The model was selected using the criteria of mean prediction error; variance of the prediction error; Durbin Watson statistic; coefficient of determination; Akaike information criterion and Bayesian criterion. The mean weights (kg) for WW, IW, W1, W2 and FW were 175.9 ± 33.4, 182.5 ± 32.1, 225.8 ± 49.6, 266.8 ± 61.9 and 340.3 ± 68.1, respectively. Analyses with MNLM (ANA1) presented better results, with LOG being the best fit, followed by GOM, BER and BRO. The ANA2 results were overestimated and out of context to be associated with bovine growth; the growth curves generated with MNLM showed good predictive capacity and were based on the data generating process, which refers to the growth of Cebu cattle.

RESUMEN: El objetivo fue caracterizar el crecimiento de bovinos Cebú en pruebas de comportamiento en pastoreo. Se utilizaron 15 990 datos de peso vivo, tomados entre 150 y 630 d de edad, de 3 198 machos con cinco pesadas cada uno: 1) peso al destete (PD), 2) peso inicio de prueba (PI), 3) primera pesada (P1), 4) segunda pesada (P2) y 5) peso final de prueba (PF). Se contrastaron los modelos no lineales (MNL): Brody (BRO), Logístico (LOG), von Bertalanffy (BER) y Gompertz (GOM); en dos tipos de análisis (ANA1, ANA2) con NLMIXED de SAS. ANA1, con MNL mixtos (MNLM), al incluir el efecto aleatorio de un coeficiente de regresión; y ANA2 con MNL, sin efectos aleatorios asociados a coeficientes de regresión. La selección del modelo se realizó con los criterios error de predicción promedio; varianza del error de predicción; estadístico Durbin Watson; coeficiente de determinación; criterio de información Akaike y criterio Bayesiano. Los pesos promedio (kg) ajustados al PD, PI, P1, P2 y PF fueron 175.9 ± 33.4, 182.5 ± 32.1, 225.8 ± 49.6, 266.8 ± 61.9 y 340.3 ± 68.1, respectivamente. Los análisis con MNLM (ANA1) presentaron mejores resultados, siendo el LOG el que presentó mejor ajuste, seguido de GOM, BER y BRO. Los resultados del ANA2 fueron sobre estimados y fuera de contexto para asociarse al crecimiento de bovinos; las curvas de crecimiento generadas con MNLM presentaron buena capacidad predictiva y estuvieron en función del proceso generador de los datos, que se refiere al crecimiento del ganado Cebú.