Differential patterns in runs of homozygosity in two mice lines under divergent selection for environmental variability for birth weight.

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 (FPED ) information, on ROH identified using the SW method (FROHSW ) and on ROH identified using the CR method (FROHCR ). Differences in genomic inbreeding were not consistent across generations and these parameters did not show clear differences between lines. Correlations between FPED and FROH were high, particularly for FROHSW . Moreover, correlations between FROHSW and FPED were even higher when ROH were identified with no restrictions in the number of heterozygotes per ROH. The comparison of FROH 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 FPED . 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.

Genomic inbreeding measures applied to a population of mice divergently selected for birth weight environmental variance.

This study aimed to compare different inbreeding measures estimated from pedigree and molecular data from two divergent mouse lines selected for environmental birth weight during 26 generations. Furthermore, the performance of different approaches and both molecular and pedigree data sources for estimating Ne were tested in this population. A total of 1,699 individuals were genotyped using a high-density genotyping array. Genomic relationship matrices were used to calculate molecular inbreeding: Nejati-Javaremi (F NEJ), Li and Horvitz (F L&H), Van Raden method 1 (F VR1) and method 2 (F VR2), and Yang (F YAN). Inbreeding based on runs of homozygosity (F ROH) and pedigree inbreeding (F PED) were also computed. F ROH, F NEJ, and F L&H were also adjusted for their average values in the first generation of selection and named F ROH0, F NEJ0, and F L&H0. ∆F was calculated from pedigrees as the individual inbreeding rate between the individual and his parents (∆F PEDt) and individual increases in inbreeding (∆F PEDi). Moreover, individual ∆F was calculated from the different molecular inbreeding coefficients (∆F NEJ0, ∆F L&H, ∆F L&H0, ∆F VR1, ∆F VR2, ∆F YAN, and ∆F ROH0). The Ne was obtained from different ∆F, such as Ne PEDt, Ne PEDi, Ne NEJ0, Ne L&H, Ne L&H0, Ne VR1, Ne VR2, Ne YAN, and Ne ROH0. Comparing with F PED , F ROH , F NEJ and F VR2 overestimated inbreeding while F NEJ0 , F L&H , F L&H0 , F VR1 and F YAN underestimated inbreeding. Correlations between inbreeding coefficients and ∆F were calculated. F ROH had the highest correlation with F PED (0.89); F YAN had correlations >0.95 with all the other molecular inbreeding coefficients. Ne PEDi was more reliable than Ne PEDt and presented similar behaviour to Ne L&H0 and Ne NEJ0. Stable trends in Ne were not observed until the 10th generation. In the 10th generation Ne PEDi was 42.20, Ne L&H0 was 45.04 and Ne NEJ0 was 45.05 and in the last generation these Ne were 35.65, 35.94 and 35.93, respectively F ROH presented the highest correlation with F PED, which addresses the identity by descent probability (IBD). The evolution of Ne L&H0 and Ne NEJ0 was the most similar to that of Ne PEDi. Data from several generations was necessary to reach a stable trend for Ne, both with pedigree and molecular data. This population was useful to test different approaches to computing inbreeding coefficients and Ne using molecular and pedigree data.

Breeding Strategies to Optimize Effective Population Size in Low Census Captive Populations: The Case of Gazella cuvieri.

Small-sized animal populations can undergo significant loss of genetic variability that can lead to their extinction. Therefore, studies on animal breeding have focused on mating systems for minimizing the disappearance of genetic variability. The main objective of this study was to compare, using computer simulations, the performance of different breeding schemes to limit the loss of genetic diversity in small-sized populations. This objective was achieved by monitoring the evolution of the effective population size obtained by 23 strategies throughout 20 generations in two populations of Gazella cuvieri. The scenarios were designed with different assumptions, in both reference subpopulations, regarding: the use of parents coancestry or offspring coancestry, the use of their increases or the coefficients themselves, and the number of males and females involved. Computations were performed using an experimental module of Endog v4.9 developed for this purpose. The results of the study showed that strategies for minimizing the coancestry of the parents were better in the short term; however, these strategies were worse in the long term. Minimizing the average coancestry of the offspring was a better approach in the long term. Nevertheless, in both populations, the best results were obtained when both the coancestry of the parents and the coancestry of the offspring were weighted at 5% each and neither males nor females were assumed to contribute to the next generation. In any case, not all strategies had the same evolutionary pattern throughout generations in both populations. The current results show that neither traditional nor new strategies have any general use. Therefore, it is important to carefully test these strategies before applying them to different populations with different breeding needs under different conditions, such as different generation intervals, and different natural breeding systems such as monogamy or polygyny.