Structure and genetic variability of the Mexican Sardo Negro breed

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.

Population genetic analysis of 12 X-chromosomal STRs in a Swiss sample

X-chromosomal STRs are a powerful tool to assess a broad variety of complex kinship scenarios. We introduce herewith the first Swiss X-STR dataset based on 1198 individuals (592 female, 606 male), characterized with the Qiagen Investigator® Argus X-12 QS multiplex kit. Anomalous allele patterns, allele and haplotype frequencies, and forensic and population genetic parameters are presented. We detected linkage disequilibrium within three out of the four designated linkage groups and no apparent intra-national population substructure. We compared the dataset to a global panel of X-STR datasets and it fits well in the European context, as expected.

Relationship between direct and maternal genetic effects on weaning weight of Limousin and crossbred beef calves

Population genetic parameters, direct and maternal breeding value, the genetic trend in the weaning weight of Limousin beef cattle calves were estimated in the period 1992–2019. Data of 19 764 calves (15 437 purebred Limousin and 4 327 crossbred) were computed. Crossbred calves were sired by Limousin breeding bulls from Simmental dams. Calves in question came from 37 herds and from 240 sires in Hungary. DFREML and MTDFREML software was used for the estimation of population genetic parameters, BLUP animal model for breeding value estimation. Weighted linear regression model was used for describing genetic trends. The maternal heritability (h²_m ± SE = 0.29 ± 0.03; 0.32 ± 0.10) was approximately half of the direct heritability (h²_d ± SE = 0.63 ± 0.05; 0.68 ± 0.12). The direct maternal covariance is negative, the direct maternal genetic correlation coefficients (r_dm ± SE = –0.80 ± 0.03 and –0.96 ± 0.07) are strong negative. The Spearman rank correlation between direct and maternal breeding value in purebred population is moderate and negative (r_rank = –0.33; P < 0.01), in crossbred population it is strong and negative (r_rank = –0.99; P < 0.01). According to direct and maternal breeding values of sires, the genetic trend of the weaning weight of purebred and crossbred Limousin calves appeared stagnant during the examined period (b = +0.01 kg/year to +0.19 kg/year). Keywords: d

Distributional characterizations and testing for differences of relatedness and inbreeding of a subpopulation of American Hereford bulls

Beta distributions are characterized by two determining parameters and a parameter space from 0 to 1, and may be useful for examining population genetic parameters such as the relationship or inbreeding coefficients. Often subpopulations exist within breeds that are congregated around particular lineages of cattle or ancestors that breeders value. These subpopulations are more related to each other than to the majority of other animals; they may have higher inbreeding as well. Value may be added to these subpopulations because of their relatedness with important or renowned ancestors. The objectives of this work were to compare the relatedness and inbreeding of a group of 26 modern bulls from a subpopulation of the American Hereford breed relative to 1) 30 males with the most descendants present in the pedigree, 2) 15 renowned American Hereford bulls considered important individuals in the breed’s history, and 3) 19 prominent subpopulation male ancestors. Conformance of the mean relationship coefficients of the bulls with the three groups and the mean inbreeding coefficient with all pedigree animals to beta distributions was assessed by 1) visually determining the parameters of the beta distributions based on the entire pedigree, 2) testing the mean relationship coefficient or inbreeding coefficient of the group of subpopulation bulls for its positional inclusion in those distributions, and 3) bootstrap sampling methodology. The mean relationship coefficients of the 26 Trask bulls with the 30 bulls with the most descendants, the 15 renowned ancestors, and the 19 Trask male ancestors were 0.15, 0.132, and 0.208, respectively. Testing of these means in beta distributions indicated that the group of 26 Trask bulls were no more related to the three groups of bulls than all of the animals in the pedigree (0.06 < P < 0.25). Bootstrap sampling indicated that the 26 bulls were more related to the three groups of male ancestors than the remainder of the animals in the pedigree (P < 0.0001). The mean inbreeding coefficient of the 26 bulls (0.13) did not differ from the overall inbreeding coefficient (0.056) when tested using a beta distribution; however, bootstrap sampling indicated otherwise (P < 0.0001). Results may indicate the inadequacy of visually parameterizing a beta distribution. Quantification of pedigree relatedness of a group of animals to key ancestors, especially with no DNA available, may add value to that group and individuals.

Temporal migration rates affect the genetic structure of populations in the biennial Erysimum mediohispanicum with reproductive asynchrony

Migration is a process with important implications for the genetic structure of populations. However, there is an aspect of migration seldom investigated in plants: migration between temporally isolated groups of individuals within the same geographic population. The genetic implications of temporal migration can be particularly relevant for semelparous organisms, which are those that reproduce only once in a lifetime after a certain period of growth. In this case, reproductive asynchrony in individuals of the same population generates demes of individuals differing in their developmental stage (non-reproductive and reproductive). These demes are connected by temporal migrants, that is, individuals that become annually asynchronous with respect to the rest of individuals of their same deme. Here, we investigated the extent of temporal migration and its effects on temporal genetic structure in the biennial plant Erysimum mediohispanicum. To this end, we conducted two independent complementary approaches. First, we empirically estimated temporal migration rates and temporal genetic structure in four populations of E. mediohispanicum during three consecutive years using nuclear microsatellites markers. Second, we developed a demographic genetic simulation model to assess genetic structure for different migration scenarios differing in temporal migration rates and their occurrence probabilities. We hypothesized that genetic structure decreased with increasing temporal migration rates due to the homogenizing effect of migration. Empirical and modelling results were consistent and indicated a U-shape relationship between genetic structure and temporal migration rates. Overall, they indicated the existence of temporal genetic structure and that such genetic structure indeed decreased with increasing temporal migration rates. However, genetic structure increased again at high temporal migration rates. The results shed light into the effects of reproductive asynchrony on important population genetic parameters. Our study contributes to unravel the complexity of some processes that may account for genetic diversity and genetic structure of natural populations.

The Limits to Estimating Population-Genetic Parameters with Temporal Data

The ability to obtain genome-wide sequences of very large numbers of individuals from natural populations raises questions about optimal sampling designs and the limits to extracting information on key population-genetic parameters from temporal-survey data. Methods are introduced for evaluating whether observed temporal fluctuations in allele frequencies are consistent with the hypothesis of random genetic drift, and expressions for the expected sampling variances for the relevant statistics are given in terms of sample sizes and numbers. Estimation methods and aspects of statistical reliability are also presented for the mean and temporal variance of selection coefficients. For nucleotide sites that pass the test of neutrality, the current effective population size can be estimated by a method of moments, and expressions for its sampling variance provide insight into the degree to which such methodology can yield meaningful results under alternative sampling schemes. Finally, some caveats are raised regarding the use of the temporal covariance of allele-frequency change to infer selection. Taken together, these results provide a statistical view of the limits to population-genetic inference in even the simplest case of a closed population.

Estimation of population genetic parameters using an EM algorithm and sequence data from experimental evolution populations

Motivation Evolve and resequence (E&R) experiments show promise in capturing real-time evolution at genome-wide scales, enabling the assessment of allele frequency changes SNPs in evolving populations and thus the estimation of population genetic parameters in the Wright–Fisher model (WF) that quantify the selection on SNPs. Currently, these analyses face two key difficulties: the numerous SNPs in E&R data and the frequent unreliability of estimates. Hence, a methodology for efficiently estimating WF parameters is needed to understand the evolutionary processes that shape genomes. Results We developed a novel method for estimating WF parameters (EMWER), by applying an expectation maximization algorithm to the Kolmogorov forward equation associated with the WF model diffusion approximation. EMWER was used to infer the effective population size, selection coefficients and dominance parameters from E&R data. Of the methods examined, EMWER was the most efficient method for selection strength estimation in multi-core computing environments, estimating both selection and dominance with accurate confidence intervals. We applied EMWER to E&R data from experimental Drosophila populations adapting to thermally fluctuating environments and found a common selection affecting allele frequency of many SNPs within the cosmopolitan In(3R)P inversion. Furthermore, this application indicated that many of beneficial alleles in this experiment are dominant. Availability and implementation Our C++ implementation of ‘EMWER’ is available at https://github.com/kojikoji/EMWER. Supplementary information Supplementary data are available at Bioinformatics online.