Juan Pablo Gutiérrez

Summary: Ketosis is one of the most prevalent metabolic disorders in dairy herds and typically occurs during early lactation due to a negative energy balance, the subsequent mobilization of adipose tissue reserves, and the accumulation of ketone bodies. Milk β-hydroxybutyrate (mBHB) concentration is used as an indicator of subclinical ketosis, as it can be routinely recorded in the milk recording system. This study estimated the genetic parameters of mBHB across 5 lactations, compared sire rankings, and evaluated the minimum test-day records for implementing efficient routine genetic evaluations. The 5 mBHB traits showed low heritability but high genetic correlations. The estimated breeding value reliabilities and rank correlations among sires suggest that using 2 test-day records within the first 68 days in milk from the first 3 lactations is preferable for incorporating mBHB as an indicator trait of subclinical ketosis resistance in the Spanish Holstein breeding program. Cow image by OpenClipart-Vectors from Pixabay; close-up image by Wolfgang Ehrecke from Pixabay.

Uniformity of production traits is desired for different traits in livestock species, including the uniformity of within-litter birth weights in piglets. Birth weight (BW) in pigs is associated with increased vitality and survival until weaning. However, as uniformity of BW increases, the importance of initial weight decreases as competition between piglets decreases. The aim of this study was to estimate the direct and maternal genetic components of BW, jointly with the maternal genetic component of the residual variance for within-litter BW, and their genetic correlations. We used two distinct datasets of Swiss Large White pigs: 1) the experimental farm dataset and 2) the commercial farms dataset, comprising 43,135 and 23,313 records of individual piglet birth weight, respectively. For statistical analysis, the heteroscedastic (or canalising selection) model was used. This model assumes that both the mean BW and the residual variance are affected by systematic and random effects, with the residual variance being heterogeneous and partially under genetic control. Despite the best fitting model was the most complex one including both genetic effects for the mean trait, the results indicated that direct genetic effects, or correlations with such effects, are negligible. The genetic environmental variance for BW ranged between 0.071 and 0.131 for experimental farm and 0.037 to 0.094. The genetic correlation between the mean BW and its variability was always positive and ranged between 0.149 and 0.307 for the experimental farm and between 0.220 and 0.589 for the commercial farms. It is thus sufficient to model BW and its variability by including only the maternal genetic effect for both traits. In addition, even though moderate genetic correlations exist between the mean and the variance of BW, focusing selection on BW uniformity within litters would be preferable to creating a selection index for both traits simultaneously. Implications: Monitoring within-litter birth weight variability is important for efficient piglet production and welfare. Our findings suggest that maternal genetic effects are sufficient to model birth weight and its variability as genetic components of environmental variance. For both traits, direct genetic variance and its correlations with other components are negligible. However, since there are moderate genetic correlations between the mean and variance of birth weight, it is preferable to focus solely on selecting for within-litter birth weight uniformity rather than combining both traits in the selection index. This approach simplifies breeding strategies while maintaining the goal of improving piglets’ welfare. Highlights: Data on individual piglet birth weight were collected on Swiss farms over 18 years Heteroscedastic animal models integrated three dimensions of genetic components The direct genetic effect and its correlations are minimal and irrelevant for selection Maternal genetic effects are crucial for birth weight and its variability Selection for uniformity is preferable to selection for both traits simultaneously

The aims of this study were to estimate the genetic parameters of clinical mastitis (CM) and somatic cell score (SCS) traits, and to compare the performance of genetic evaluations of CM traits using univariate and bivariate analyses (CM-SCS). Data was edited according to the Udder Health Golden Standard harmonization and then, 6 CM traits and 6 SCS traits were considered, as the result of combining 3 lactation classification (1, 2, ≥ 3) and 2 milking periods (early, late). The linear mixed animal models included the ratio of period at risk as a covariate, herd-year of calving, month of calving, and lactation-age as fixed effects, and the permanent environmental effect for traits of ≥ 3 lactations. Prevalence of CM in early lactation was similar regardless the lactation number (5-6%) and the estimated heritabilities were 0.01. Prevalences in late lactation ranged from 10% to 24% and heritabilities ranged from 0.03 to 0.05. Estimated heritabilities of SCS ranged from 0.06 to 0.16 with univariate analyses. Somatic cell count (therefore its log-transformation SCS) showed higher probability of identify correctly healthy cows than infected cows but there was still up to 36% of healthy cows for CM not detected by SCS. Genetic correlations between CM-SCS traits ranged from 0.36 to 0.95, and SCS in lactation 3 and later did not add extra information to SCS in second lactation for predicting CM. Regarding reliabilities of estimated breeding value (EBV) for CM traits, bivariate CM-SCS analyses led to substantial increases with respect to the single-trait model for sires (7-12% more in first lactation and 16-28% more for second lactation). Sire's rank correlations for CM between univariate and bivariate analyses (0.47-0.92) suggest that discarding sires could be more accurate than selecting candidates for sires of dams. We can conclude that SCS in first lactation could be useful to supplement CM data in first and second lactations to improve udder health genetic evaluation.

When prevention of species extinction is the priority, captive breeding is a key component in conservation programmes, allowing the recording of pedigree information in studbooks. The genealogical information registered in Cuvier’s gazelle studbook between 1975 and 2023 was analysed to (a) assess if the implemented mating policy was successful in preserving the genetic background of the founders (1 male:3 females) in the present population, and b) improve future management and breeding decisions. Although the maternal contribution of one founder female was lost and the mean inbreeding of the total live population was high (0.305 ± 0.095), the breeding policy applied produced better results than expected from a population starting from four founders. It was successful in keeping the individual increase in inbreeding low (0.047 ± 0.021), and, notably, the inbreeding tended to decrease during the last three decades of the breeding programme, ensuring the viability of this highly inbred population. Historical dissemination of individuals among the zoos of Europe and North America caused population structuring and genetic differentiation of the live North American population. However, it did not risk the viability of the captive population. The average relatedness coefficients allowed the identification of individuals with underrepresented genotypes, which is relevant to plan future mating guidelines to keep the founders’ representation balanced in the next generations. This study highlights the importance of keeping long-term pedigree information to monitor changes in the genetic diversity of captive populations, which is crucial to implement optimal mating decisions and assuring their long-term viability within an ex situ conservation programme.

Background: The identification of low-frequency haplotypes, never observed in homozygous state in a population, is considered informative on the presence of potentially harmful alleles (candidate alleles), putatively involved in inbreeding depression. Although identification of candidate alleles is challenging, studies analyzing the dynamics of potentially harmful alleles are lacking. A pedigree of the highly endangered Gochu Asturcelta pig breed, including 471 individuals belonging to 51 different families with at least 5 offspring each, was genotyped using the Axiom PigHDv1 Array (658,692 SNPs). Analyses were carried out on four different cohorts defined according to pedigree depth and at the whole population (WP) level. Results: The 4,470 Linkage Blocks (LB) identified in the Base Population (10 individuals), gathered a total of 16,981 alleles in the WP. Up to 5,466 (32%) haplotypes were statistically considered candidate alleles, 3,995 of them (73%) having one copy only. The number of alleles and candidate alleles varied across cohorts according to sample size. Up to 4,610 of the alleles identified in the WP (27% of the total) were present in one cohort only. Parentage analysis identified a total of 67,742 parent-offspring incompatibilities. The number of mismatches varied according to family size. Parent-offspring inconsistencies were identified in 98.2% of the candidate alleles and 100% of the LB in which they were located. Segregation analyses informed that most potential candidate alleles appeared de novo in the pedigree. Only 17 candidate alleles were identified in the boar, sow, and paternal and maternal grandparents and were considered segregants. Conclusions: Our results suggest that neither mutation nor recombination are the major forces causing the apparition of candidate alleles. Their occurrence is more likely caused by Allele-Drop-In events due to SNP calling errors. New alleles appear when wrongly called SNPs are used to construct haplotypes. The presence of candidate alleles in either parents or grandparents of the carrier individuals does not ensure that they are true alleles. Minimum Allele Frequency thresholds may remove informative alleles. Only fully segregant candidate alleles should be considered potentially harmful alleles. A set of 16 candidate genes, potentially involved in inbreeding depression, is described.

The quality of alpaca textile fibre has great potential, especially if objectionable fibres (coarse and medullated fibres) that cause itching are reduced, considering that objectionable fibres can be identified by diameter and medullation types. The objective of this study was to estimate genetic parameters for medullar types and their respective diameters to evaluate the possibility of incorporating them as selection criteria in alpaca breeding programmes. The research used 3149 alpaca fibre samples collected from 2020 to 2022, from a population of 1626 Huacaya type alpacas. The heritability and correlations of the percentages of non‐medullated (NM), fragmented medulle (FM), uncontinuous medullated (UM), continuous medullated (CM), and strongly medullated (SM) fibres were analysed, also the fibre diameter (FD) for each of the medullation types. The heritability estimated for medullation types were 0.25 ± 0.01, 0.18 ± 0.01, 0.10 ± 0.01, 0.20 ± 0.01 and 0.11 ± 0.01 for NM, FM, UM, CM and SM, respectively. The genetic correlations for medullation categories ranged from 0.15 ± 0.03 to 0.66 ± 0.02 (in absolute values). The heritabilility estimated for fibre diameter (FD) of each of the medullation types were 0.29 ± 0.03, 0.27 ± 0.02, 0.35 ± 0.02, 0.30 ± 0.02, 0.25 ± 0.02 and 0.10 ± 0.02 for FD, FD_NM, FD_FM, FD_UM, FD_CM and FD_SM, respectively. The genetic correlations for fibre diameter of the medullation types ranged from 0.04 ± 0.04 to 0.97 ± 0.01. FD, NM and FM are the main traits to be used as selection criteria under a genetic index, since they would reduce fibre diameter, and also increase NM and FM, and, in addition reducing indirectly CM, SM, and SM_FD. Therefore, the quality of alpaca fibre could be improved.

Runs of homozygosity (ROH) are defined as long continuous homozygous stretches in the genome which are assumed to originate from a common ancestor. It has been demonstrated that divergent selection for variability in mice is possible and that low variability in birth weight is associated with robustness. To analyse ROH patterns and ROH‐based genomic inbreeding, two mouse lines that were divergently selected for birth weight variability for 26 generations were used, with: 752 individuals for the high variability line (H‐Line), 766 individuals for the low variability line (L‐Line) and 74 individuals as a reference population. Individuals were genotyped using the high density Affymetrix Mouse Diversity Genotyping Array. ROH were identified using both the sliding windows (SW) and the consecutive runs (CR) methods. Inbreeding coefficients were calculated based on pedigree (F_PED) information, on ROH identified using the SW method (F_ROHSW) and on ROH identified using the CR method (F_ROHCR). Differences in genomic inbreeding were not consistent across generations and these parameters did not show clear differences between lines. Correlations between F_PED and F_ROH were high, particularly for F_ROHSW. Moreover, correlations between F_ROHSW and F_PED were even higher when ROH were identified with no restrictions in the number of heterozygotes per ROH. The comparison of F_ROH estimates between either of the selected lines were based on significant differences at the chromosome level, mainly in chromosomes 3, 4, 6, 8, 11, 15 and 19. ROH‐based inbreeding estimates that were computed using longer homozygous segments had a higher relationship with F_PED. Differences in robustness between lines were not attributable to a higher homozygosis in the L‐Line, but maybe to the different distribution of ROH at the chromosome level between lines. The analysis identified a set of genomic regions for future research to establish the genomic basis of robustness.