Changes In Genetic Parameters Research Articles

Genetic assessment and monitoring of wild, captive, and reintroduced northern leopard frog populations

The northern leopard frog (Lithobates pipiens) has undergone dramatic declines in population size and range over recent decades in western Canada and the United States. In British Columbia, only a single population remains at the Creston Valley Wildlife Management Area. Yet, the continuing viability of this population is uncertain. In this paper, the current genetic structure of northern leopard frog populations in western Canada was assessed using microsatellite markers. Historical samples from the extinct population of Fort Steele in British Columbia were compared with the Creston Valley population to understand changes in population genetic parameters over time. Genotypic data from four populations (Creston Valley, Drain K, Prince Spring, and Cypress Hill) sampled in 2004 and 2019 were compared. To evaluate changes in the genetic diversity of the Creston Valley population over time, allelic richness and expected heterozygosity of the population were compared at three time points using genotypes from 2000, 2004, and 2019. Northern leopard frog populations in western Canada showed high genetic differentiation, with genetic diversity decreasing from east to west. Although there weren’t notable changes in genetic parameters between 2004 and 2019, there was evidence of a decline in diversity between 2000 and 2019. The extinct population of Fort Steele had private alleles, while the current Creston Valley population did not, suggesting a genetic bottleneck in the Creston Valley population. Therefore, genetic rescue, specifically for the endangered Creston Valley population, can be considered as an action to support recovery. Additionally, continued genetic monitoring will help in the effective management of the species by providing information on the success of conservation actions.

Estimation of genetic parameters for feed efficiency traits using random regression models in dairy cattle

Feed efficiency has become an increasingly important research topic in recent years. As feed costs rise and the environmental impacts of agriculture become more apparent, improving the efficiency with which dairy cows convert feed to milk is increasingly important. However, feed intake is expensive to measure accurately on large populations, making the inclusion of this trait in breeding programs difficult. Understanding how the genetic parameters of feed efficiency and traits related to feed efficiency vary throughout the lactation period is valuable to gain understanding into the genetic nature of feed efficiency. This study used 121,226 dry matter intake (DMI) records, 120,500 energy-corrected milk (ECM) records, and 98,975 metabolic body weight (MBW) records, collected on 7,440 first-lactation Holstein cows from 6 countries (Canada, Denmark, Germany, Spain, Switzerland, and the United States), from January 2003 to February 2022. Genetic parameters were estimated using a multiple-trait random regression model with a fourth-order Legendre polynomial for all traits. Weekly phenotypes for DMI were re-parameterized using linear regressions of DMI on ECM and MBW, creating a measure of feed efficiency that was genetically corrected for ECM and MBW, referred to as genomic residual feed intake (gRFI). Heritability (SE) estimates varied from 0.15 (0.03) to 0.29 (0.02) for DMI, 0.24 (0.01) to 0.29 (0.03) for ECM, 0.55 (0.03) to 0.83 (0.05) for MBW, and 0.12 (0.03) to 0.22 (0.06) for gRFI. In general, heritability estimates were lower in the first stage of lactation compared with the later stages of lactation. Additive genetic correlations between weeks of lactation varied, with stronger correlations between weeks of lactation that were close together. The results of this study contribute to a better understanding of the change in genetic parameters across the first lactation, providing insight into potential selection strategies to include feed efficiency in breeding programs.

Recent Changes in Genetic Diversity, Structure, and Gene Flow in a Passerine Experiencing a Rapid Population Decline, the Dupont’s Lark (Chersophilus duponti)

Monitoring temporal dynamics in genetic diversity is of great importance for conservation, especially for threatened species that are suffering a rapid population decline and increased fragmentation. Here, we investigate temporal variation in genetic diversity, structure, and gene flow in the Dupont’s lark (Chersophilus duponti) across most of its range. This species shows increasing levels of population fragmentation, substantial population declines, and severe range contraction, so temporal losses of genetic diversity, increasing differentiation, and decreasing gene flow are expected when comparing present day data with previous situations. To address this, we resampled sites (nine regions in two countries) after 12–15 years (five-to-seven generations) and assessed changes in genetic parameters using 11 microsatellite markers. We found no substantial loss in genetic diversity over time at the species level, but we detected considerable variation among regions in the amount of allelic diversity and heterozygosity lost over time. Temporal variation in allele frequencies (common, rare, and private alleles), and changes in genetic differentiation and gene flow over time suggest a major role of connectivity for the stability of the overall metapopulation. Our results agree with the hypothesis that connectivity rescues genetic diversity via immigration and gene flow. However, evidence of recent genetic bottleneck and the substantial changes detected in some regions are clear signs of genetic erosion and may be signalling a rapid decline of the populations. Urgent actions must be carried out to stop and reverse human impacts on this threatened lark and its habitat.

Changes in genetic parameters for milk yield and heat tolerance in the Thai Holstein crossbred dairy population under different heat stress levels and over time

The objectives of this study were to investigate changes in genetic parameters for milk yield (MY) and heat tolerance of the crossbred Thai Holstein Friesian population under different heat stress levels over time, and to investigate the threshold point of heat stress manifestation on milk production. Genetic parameters were estimated using single-step genomic REML (ssGREML) and traditional REML models. Data included 58,965 test-day MY records from 1999 to 2008 (old data) and 105,485 test-day MY records from 2009 to 2018 (recent data) from the first parity of 24,520 cows. The pedigree included 55,168 animals, of which 882 animals had genotypes. Variance components were estimated with the REMLF90 program using a repeatability model with random regressions on a function of temperature-humidity index (THI) for additive genetic and permanent environmental effects. Fixed effects included farm-calving season combination, breed group-months in milk combination, and age at first calving. Random effects included additive genetic (intercept and slope) effects, permanent environmental (intercept and slope) effects, and herd-month-year of test. The phenotypic mean for MY was 13.33 ± 4.39 kg/d in the old data, and 14.48 ± 4.40 kg/d in the recent data. Estimates over different THI levels for the intercept additive genetic variance using old data ranged from 2.61 to 2.77 and from 5.02 to 5.38 using recent data with the REML method. In ssGREML analyses (performed with recent data only) the estimates for the intercept additive genetic variance ranged from 4.71 to 5.05. Estimates for the slope additive genetic variance were close to zero in all cases, with the largest values (0.024-0.030) at the most extreme THI value (80). Using REML, the covariance between the intercept and the slope additive genetic effects (THI from 72 to 80) ranged from -0.001 to 0.019 with old data and from 0.027 to 0.060 with recent data. The same covariance ranged from 0.026 to 0.057 in ssGREML analyses. The covariance between the intercept and the slope permanent environmental effects ranged from -0.42 to -0.67 for all data and THI levels. Across THI levels, the genetic correlation between MY and heat tolerance varied from -0.06 to 0.13 with old data, from 0.16 to 0.30 with recent data in REML analyses, and from 0.15 to 0.30 in ssGREML analyses, suggesting that in the current population the top animals for MY are more resistant to heat stress. This was expected, because of the introduction of Bos indicus genes in the last years. Heritability estimates for MY ranged from 0.19 to 0.21 (old data) and from 0.33 to 0.40 (recent data) for REML analyses. Heritability estimates for MY using ssGREML ranged from 0.31 to 0.38. A decline in MY was found when the animals' breed composition had more than 97.3% of Holstein genetics, and it was greatest at THI 80. The heritability and genetic correlations observed in this study show that selection for MY is possible without a negative correlated response for heat tolerance. Although the inclusion of genomic information is expected to increase the accuracy of selection, more genotypes must be collected for successful application. Future research should address other production and fitness traits within the Thai Holstein population.

Beef trait genetic parameters based on old and recent data and its implications for genomic predictions in Italian Simmental cattle.

This study aimed to evaluate the changes in variance components over time to identify a subset of data from the Italian Simmental (IS) population that would yield the most appropriate estimates of genetic parameters and breeding values for beef traits to select young bulls. Data from bulls raised between 1986 and 2017 were used to estimate genetic parameters and breeding values for four beef traits (average daily gain [ADG], body size [BS], muscularity [MUS], and feet and legs [FL]). The phenotypic mean increased during the years of the study for ADG, but it decreased for BS, MUS, and FL. The complete dataset (ALL) was divided into four generational subsets (Gen1, Gen2, Gen3, and Gen4). Additionally, ALL was divided into two larger subsets: the first one (OLD) combined data from Gen1 and Gen2 to represent the starting population, and the second one (CUR) combined data from Gen3 and Gen4 to represent a subpopulation with stronger ties to the current population. Genetic parameters were estimated with a four-trait genomic animal model using a single-step genomic average information restricted maximum likelihood algorithm. Heritability estimates from ALL were 0.26 ± 0.03 for ADG, 0.33 ± 0.04 for BS, 0.55 ± 0.03 for MUS, and 0.23 ± 0.03 for FL. Higher heritability estimates were obtained with OLD and ALL than with CUR. Considerable changes in heritability existed between Gen1 and Gen4 due to fluctuations in both additive genetic and residual variances. Genetic correlations also changed over time, with some values moving from positive to negative or even to zero. Genetic correlations from OLD were stronger than those from CUR. Changes in genetic parameters over time indicated that they should be updated regularly to avoid biases in genomic estimated breeding values (GEBV) and low selection accuracies. GEBV estimated using CUR variance components were less biased and more consistent than those estimated with OLD and ALL variance components. Validation results indicated that data from recent generations produced genetic parameters that more appropriately represent the structure of the current population, yielding accurate GEBV to select young animals and increasing the likelihood of higher genetic gains.

Changes in genetic parameters for fitness and growth traits in pigs under genomic selection.

Genomic selection increases accuracy and decreases generation interval, speeding up genetic changes in the populations. However, intensive changes caused by selection can reduce the genetic variation and can strengthen undesirable genetic correlations. The purpose of this study was to investigate changes in genetic parameters for fitness traits related with prolificacy (FT1) and litter survival (FT2 and FT3), and for growth (GT1 and GT2) traits in pigs over time. The data set contained 21,269 (FT1), 23,246 (FT2), 23,246 (FT3), 150,492 (GT1), and 150,493 (GT2) phenotypic records obtained from 2009 to 2018. The pedigree file included 369,776 animals born between 2001 and 2018, of which 39,103 were genotyped. Genetic parameters were estimated with bivariate models (FT1-GT1, FT1-GT2, FT2-GT1, FT2-GT2, FT3-GT1, and FT3-GT2) using 3-yr sliding subsets. With a Bayesian implementation using the GIBBS3F90 program computations were performed as genomic analysis (GEN) or pedigree-based analysis (PED), that is, with or without genotypes, respectively. For GEN (PED), the changes in heritability from the first to the last year interval, that is, from 2009–2011 to 2015–2018 were 8.6 to 5.6 (7.9 to 8.8) for FT1, 7.8 to 7.2 (7.7 to 10.8) for FT2, 11.4 to 7.6 (10.1 to 7.5) for FT3, 35.1 to 16.5 (32.5 to 23.7) for GT1, and 35.9 to 16.5 (32.6 to 24.1) for GT2. Differences were also observed for genetic correlations as they changed from −0.31 to −0.58 (−0.28 to −0.73) for FT1-GT1, −0.32 to −0.50 (−0.29 to −0.74) for FT1-GT2, −0.27 to −0.45 (−0.30 to −0.65) for FT2-GT1, −0.28 to −0.45 (−0.32 to −0.66) for FT2-GT2, 0.14 to 0.17 (0.11 to 0.04) for FT3-GT1, and 0.14 to 0.18 (0.11 to 0.05) for FT3-GT2. Strong selection in pigs reduced heritabilities and emphasized the antagonistic genetic relationships between fitness and growth traits. With genotypes considered, heritability estimates were smaller and genetic correlations were greater than estimates with only pedigree and phenotypes. When selection is based on genomic information, genetic parameters estimated without this information can be biased because preselection is not accounted for by the model.

211 Changes in genetic parameters of fitness and growth traits under genomic selection in pigs

Abstract Genomic selection increases intensity of selection and decreases generation interval. However, intensive selection reduces genetic variation and can strengthen undesirable genetic correlations. The purpose of this study was to investigate changes in genetic parameters of litter size (LS), number born alive (NBA), number born dead (NBD) and average daily gain (ADG) and weight at off-test (WT) in pigs over time. The data set contained 20,086 (LS), 21,230 (NBA), 21,230 (NBD), 144,717 (ADG) and 144,718 (WT) phenotypic records. Pedigree file included 369,776 animals born between 2001 and 2018, of which 39,038 were genotyped. Two trait models were evaluated (LS-ADG, LS-WT, NBA-ADG, NBA-WT, NBD-ADG and NBD-WT) using 3-year sliding subsets starting from 2010. Variance components and genetic parameters were estimated using GIBBS2F90 program. Computations were performed with (BLUP) or without (ssGBLUP) genotypes. For BLUP (ssGBLUP), the changes in heritability from 2010–2012 to 2015–2018 were 0.08 to 0.09 (0.08 to 0.06) for LS, 0.33 to 0.24 (0.37 to 0.16) for ADG, 0.11 to 0.07 (0.10 to 0.07) for NBD, and 0.32 to 0.24 (0.38 to 0.17) for WT. Differences were also observed for genetic correlations as they were -0.23 to -0.73 (-0.31 to -0.58) for LS-ADG, -0.24 to -0.74 (-0.31 to -0.50) for LS-WT, -0.33 to -0.65 (-0.41 to -0.53) for NBA-ADG, -0.35 to -0.66 (-0.42 to -0.45) for NBA-WT, 0.12 to 0.04 (0.12 to 0.16) for NBD-ADG, and 0.11 to 0.05 (0.11 to 0.22) for NBD-WT. Genomic selection in pigs reduced heritabilities and emphasized the antagonistic relationship that are under strong selection. Heritabilities estimated from ssGBLUP declined more than those by BLUP while changes in the genetic correlations were smaller and more gradual by ssGBLUP. Differences between ssGBLUP and BLUP could be caused by genomic pre-selection unaccounted for by BLUP.

Longitudinal analysis of body weight and average daily feed intake during the feedlot test period in Angus cattle.

The objectives of this study were to compare different models for analysing body weight (BW) and average daily feed intake (ADFI) data collected during a 70-day feedlot test period and to explore whether genetic parameters change over time to evaluate the implications of selection response. (Co)variance components were estimated using repeatability and random regression models in 2,071 Angus steers. Models included fixed effects of contemporary group, defined as herd-year-observation_date-age, with additive genetic and permanent environmental components as random effects. Models were assessed based on the log likelihood, Akaike's information criterion and the Bayesian information criterion. For both traits, random regression models (RRMs) presented a better fit, indicating that genetic parameters change over the test period. Using a two-trait RRM, the heritability from day 1 up to day 70 for BW increased from 0.40 to 0.50, while for ADFI, it decreased from 0.44 to 0.33. The genetic correlation increased from 0.53 at day 1 up to 0.79 at day 70. Selection based on an index assuming no change in genetic parameters would yield a 2.78%-3.13% lower selection response compared to an index using parameters estimated with RRMs and assuming these genetic parameters are correct. Results imply that it may be beneficial to implement RRMs to account for the change of parameters across the feedlot period in feed efficiency traits.

Pedigree reconstruction using molecular data reveals an early warning sign of gene diversity loss in an island population of Tasmanian devils (Sarcophilus harrisii)

Tasmanian devils have experienced an 85% population decline since the emergence of an infectious cancer. In response, a captive insurance population was established in 2006 with a subpopulation later introduced onto Maria Island, Tasmania. We aimed to (1) examine the genetic parameters of the Maria Island population as a stand-alone site and within its broader metapopulation context, (2) assess the efficacy of assisted colonisations, and (3) inform future translocations. This study reconstructs the pedigree of 86 island-born devils using 31 polymorphic microsatellite loci. Combined molecular and pedigree analysis was used to monitor change in population genetic parameters in 4 years since colonisation. Molecular analysis alone revealed no significant change in genetic diversity, while DNA-reconstructed pedigree analysis revealed a statistically significant increase in inbreeding due to skewed founder representation. Pedigree modelling predicted that gene diversity would only be maintained above the threshold of 95% for a further 2 years, dropping to 77.1% after 40 years. Modelling alternative supplementation strategies revealed introducing eight new founders every 3 years will enable the population to retain 95% gene diversity until 2056, provided the translocated animals breed; to ensure this we recommend introducing ten new females every 3 years. We highlight the value of combining pedigree analyses with molecular data, from both a single-site and metapopulation viewpoint, for analysing changes in genetic parameters within populations of conservation concern. The importance of post-release genetic monitoring in an established population is emphasised, given how quickly inbreeding can accumulate and gene diversity be lost.

Genetic diversity and structure of Megabalanus azoricus in the Azores: Implications for aquaculture management

Megabalanus azoricus giant barnacles are the most traditional seafood of the Azores archipelago (NE Atlantic). This valuable commercial species has been highly exploited in the past and it is considered one of the key species for the development of aquaculture in the region. Despite the importance for conservation and aquaculture there is still a lack of basic information about M. azoricus genetic diversity and population structure. Here we used seven microsatellites markers to analyse 300 samples collected at six out of nine islands of the Azores archipelago, including also different locations from a single island, to provide information on the scale of genetic diversity and population structure of this species. Parameters like heterozygosity, allelic richness and effective number of alleles indicated a high genetic diversity and variability among islands. Pairwise comparisons and PCoA analysis on FST and Jost's DEST showed significant and evident differentiation among sampling locations. Additionally, AMOVA allocates a small (6.02%) but statistically significant portion of the variance to the among Island level revealing also a weak resolution (1.87%) at finer scale. Additionally Monte Carlo resampling methods indicated the most likely sources of the recruits were the local or adjacent populations. Genetic risks associated with the giant barnacle potential production scheme should be taken into account in a future management plan delimiting, as precautionary measure, this culture at a single island or at groups of islands here identified. Moreover a monitoring strategy should be implemented with the aim to evaluate possible changes in genetic parameters of native populations.

Economic evaluation of breeding strategies for improvement of dairy cattle in Kenya

Cost-benefit analysis using net present value (NPV) as the economic evaluation criterion was used to investigate the economic merits of four breeding strategies used for genetic improvement of dairy cattle in Kenya. The breeding strategies were evaluated over a 25-year period. The costs involved in setting up and running each strategy were obtained from large-scale dairy cattle farms, and government and private institutions involved in genetic improvement of dairy cattle. Only benefits from genetic improvement were considered. The impact on NPV due to changes in genetic and economic parameters was investigated. The ranking of the breeding strategies greatly differed with genetic ranking. Among the local selection programs, a strategy utilizing young bulls, sons of local bulls, was more profitable than one utilizing old progeny tested bulls. Continuous semen importation was not an economically viable alternative. The strategy utilizing young bulls progeny of imported bulls (PIB) was only viable if imports were from countries which are >2.00 SD in genetic merit above the local dairy cattle population. The ranking of strategies was not sensitive to changes in genetic parameters but to economic parameters. The use of local semen from young bulls progeny of local proven bulls is recommended. Alternatively, PIB can be utilized but the semen will have to be imported from countries which are >2.00 SD above the local dairy cattle population or the cost of imported semen should be < or = US$40 per straw.

Genetics of Growth and Reproduction in the Turkey. 17. Changes in Genetic Parameters Over Forty Generations of Selection for Increased Sixteen-Week Body Weight

A line (F) of turkeys was selected over 40 generations for increased 16-wk BW. The base population for the F line was a randombred control population that was maintained without conscious selection and used to remove yearly environmental variation in the F line. Selection was effective in increasing 16-wk BW in the F line. Selection differentials based on the mean of the selected parents minus the mean of the entire population (intended) and intended selection differentials weighted for number of offspring produced (actual) did not differ consistently, indicating that natural selection was not opposing artificial selection during the reproduction of the F line. The realized heritability of 16-wk BW in the F line, based on the linear regression of the selection response on accumulated actual selection differential, declined with selection. For both sexes combined, the realized heritability was 0.309 ± 0.022 (SE), 0.268 ± 0.033, 0.268 ± 0.026, 0.166 ± 0.016, and 0.242 ± 0.004, respectively, for generations 1 to 10, 11 to 20, 21 to 30, 31 to 40, and 1 to 40. Genetic increases in 16-wk BW in the F line over 40 generations of selection were positively associated with BW at other ages (8 and 20 wk of age and at 50% production), shank length and width at 16 wk of age, days from stimulatory lighting to production of the first egg, and egg weight but were negatively associated with egg production, intensity of lay (maximum and average clutch length and rate of lay), and walking ability. Over the 40 generations of selection, genetic increases in BW in the F line were not associated with changes in broodiness or mortality to 8 wk of age. During generations 31 to 40, BW at 8 and 20 wk of age continued to increase in the F line, but there was no significant change in adult BW, and the only significant change in reproduction traits was for average clutch length (−0.030). Because the genetic changes in some correlated traits were not consistent in all generation intervals studied, the genetic correlation between the selected trait (16-wk BW) and the correlated trait apparently changed with selection.

Heritability and correlations for body condition score and dairy form within and across lactation and age.

The objectives of the current study were to investigate the relationship between body condition score (BCS) and dairy form and changes in genetic parameters for BCS and dairy form within and across lactations and age. Body condition score and dairy form were obtained from the Holstein Association USA, Inc. Records were edited to include those cows classified between 24 and 60 mo of age and between 0 and 335 d in milk (DIM). A minimum of 20 daughters per sire and 15 cows per herd-classification visit were required. The dataset consisted of 135,178 records from 119,215 cows. Repeatability, multiple trait, and random regression models were used to analyze the data. All models included fixed effects for herd-classification visit, age within lactations 1, 2, and 3 or higher, and 5th-order polynomials for DIM. Random effects included sire and permanent environment for all models. Random regression models included age at classification nested within sire or DIM and lactation number nested within sire. Genetic variance for both BCS and dairy form was lowest in early lactation and highest in midlactation. Genetic correlations within and across lactations were high. The genetic correlation between DIM 0 in lactation 1 and DIM 305 in lactation 3 was estimated to be 0.77 for BCS and 0.60 for dairy form. The genetic correlation estimate between 30 mo of age at classification and 50 mo of age at classification was 0.94 for both dairy form and BCS. The repeatability models appeared to generate accurate evaluations for BCS or dairy form at all ages and stages of lactation.

Behaviour plasticity without learning: phenotypic and genetic variation of naı̈ve Daphnia in an ecological trade-off

The swimming behaviour of adult Daphnia largely governs their depth, which has a direct effect on both individual foraging success and predation avoidance. We treated individual swimming behaviour as a threshold character and used directional changes in average clonal depth within experimental tubes as a test for character plasticity. We compared the swimming behaviours of two cohabiting, phenotypically similar Daphnia (Daphnia galeata and Daphnia galeata–Daphnia rosea hybrid) to determine (1) whether there is inherited variation (H2) for different traits (responses to hunger and predator cues); (2) whether changes in genetic parameters (norm of reaction and character state) across four environments could be simulated by combinations of the presence or absence of a predator cue and high or low hunger levels; and (3) whether these Daphnia would respond to directional selection, particularly in a trade-off environment (high hunger and predator cue treatments). Responses of both D.galeata and theD.galeata –rosea hybrid to hunger and a predator cue and the trade-off environment were plastic.Daphnia galeata expressed significant genetic variation within (H2) and between environments (heritability of plasticity). Both the character state and norm of reaction estimates of heritable variation in the hybrid were close to zero. Genetic correlations were positive and stable across six environmental pairs in Daphnia galeata. Most hybrid genetic correlations were not significant. The phenotypic distributions of both D.galeata and the hybrid were bimodal in the trade-off environment. The D.galeata distribution was partly due to between-clone variation and the hybrid distribution was almost entirely due to within-clone variation. Genetic variation expressed byD.galeata in the trade-off environment appears to depend on both clone by environment interactions and stable inherited differences. These results indicate that while plastic phenotypic responses cause a similar opportunity for selection inD.galeata and the hybrid, their responses to selection would be different in the trade-off and in related environments.

Genetics of growth and reproduction in the turkey. 14. Changes in genetic parameters over thirty generations of selection for increased body weight

A line (F) of turkeys was selected over 30 generations for increased 16-wk BW. The base population for the F line was a randombred control population (RBC2) that was maintained without conscious selection and used to remove yearly environmental variation in the F line. Selection was effective in increasing 16-wk BW in the F line. Selection differentials based on the mean of selected parents minus mean of entire population (intended) and intended selection differentials weighted for number of offspring produced (actual) did not consistently differ, indicating that natural selection was not significantly opposing artificial selection. The realized heritability (h2) of 16-wk BW in the F line, based on the linear regression of the selection response on accumulated actual selection differentials, declined with selection; the decline appeared to be slightly different for males than females. For both sexes combined, the realized h2 was 0.309+/-0.022 (SE), 0.268+/-0.033, 0.242+/-0.026, and 0.254+/-0.007, respectively, for Generations 1 to 10, 11 to 20, 21 to 30, and 1 to 30. Genetic increases in 16-wk BW in the F line were positively associated with BW at other ages (8, 20, and 24 wk of age and at 50% production), days from stimulatory lighting to production of the first egg, and egg weight. Genetic increases were negatively associated with egg production, intensity of lay (maximum and average clutch length and rate of lay), and hatch of fertile eggs. There was no significant relationship between 16-wk BW and total days lost from broodiness or fertility. The genetic changes in some correlated traits were not consistent in all generation intervals studied, indicating that the genetic correlation between the selected trait (16 wk BW) and the correlated trait changed with selection.

Selection for litter size components: a critical review

The measurement of component variables such as the number of ova shed (OR) and its inclusion in a linear index with litter size (LS) or prenatal survival has been suggested in order to accelerate genetic progress for LS. Despite optimistic theoretical predictions, however, in no selection experiment has the advantage of including OR in an index as compared to direct selection for LS been convincingly demonstrated. A literature survey shows no clear evidence of changes in genetic parameters with selection. By contrast, genetic drift may suffice to explain the less than expected usefulness of measuring OR, although it is not necessarily the sole cause. It is shown that an approximate figure of how much can be gained by measuring OR relative to direct selection for LS is given by (1+(J!Ls/(J!oR)1/2 with mass selection, where y is the phenotypic variance. Nonetheless, the size of the experiment needed to test this prediction is likely to be very large.

Optimum designs for breeding programmes under mass selection with an application in fish breeding

AbstractA procedure for maximizing genetic gain (after a number of generations of selection) for a given rate of inbreeding or for a given coefficient of variation of response is presented. An infinitesimal genetic model is assumed. Mass selection is practised for a number of discrete generations. With constraints on inbreeding, expected rates of genetic progress (ΔG) are combined with expeced rates of inbreeding (ΔF) in a linear objective function (Ω = ΔG - μΔF). In addition, an expression to approximate the rate of gain at any generation accounting for changes in genetic parameters due to linkage disequilibrium and due to inbreeding is derived. Predicted gain is in general within 5% of that obtained from simulation. Thus, both ΔG and ΔF are obtained from simple analytical formulae. An equivalent function is used when the coefficient of variation of response (CV) is the parameter restricted (Ω = ΔG -μCV). Maximization of the objective function Ω for appropriate values of μ gives the optimum number of sires and dams selected when specific constraints on the level of inbreeding or the coefficient of variation of response are imposed. The method is applied to a practical situation in fish breeding. Optimum mating ratios and optimum numbers of sires selected are obtained for different scored population sizes and heritabilities. Results obtained with this procedure agree very well with results from simulation studies. The optimum number of sires increases with the size of the scheme and with more severe restrictions on risk. In the schemes considered, the optimum mating ratio is equal to 2 unless the constraint on the rate of inbreeding is severe, the size of the scheme is small and the heritability is low. In these situations the optimum mating ratio is equal to 1. The procedure is general in terms of generations of selection considered and in terms of parameters to be constrained. A large amount of computer processor unit time is saved with this method in comparison with simulation procedures.

Long-term restricted index selection in mice designed to change fat content without changing body size

The objective of this study was to determine if low secondary selection differentials, caused by selecting within full-sib families, may have accounted for the failure of an intended restricted selection index to reduce epididymal fat pad weight (EF) without changing body weight (BW) in mice. Replicate lines that had been selected within full-sib families for high (HE) or low (LE) EF, while holding BW constant, were crossed. After two generations of random mating, two replicates were sampled and selection initiated for the same restricted index criteria except that mass selection was used to increase the selection differentials. In both phases of selection the HE restricted index selection, designed to increase EF without altering BW, was in agreement with expectation. In contrast, the LE index, designed to decrease EF without changing BW, did not agree with theory since BW increased while EF decreased only slightly. Therefore, reduced selection differentials could not explain the deviation from theory. A possible explanation may reside in the restricted selection index being more sensitive to changes in genetic parameters due to shifts in gene frequency as a consequence of the selection applied. However, linkage disequilibrium and genetic drift can not be ruled out as contributing factors to the asymmetry of response.

Change of Expected Response to Multitrait Selection in a Synthetic Population of Perennial Ryegrass Through Recurrent Selection

AbstractThe changes in genetic parameters, variances, covariances and heritabilities, caused by the Bulmer effect have been predicted for an artificial breeding population of perennial ryegrass using recursion formulae. This enabled anticipation of the decrease in the expected response to multitrait index selection, using two different sets of economic weights. This theoretical decrease in selection efficiency was found to be quite substantial; it is approximately halved after 4 cycles of individual recurrent selection with a fairly high selection intensity of 5 %.However the synthetic population is improved for 4 out of 5 agronomic traits and could theoretically reach quite a high level of performance after 5 cyles. The choice of economic weights has relatively little influence on the expected genetic progress of each trait.

Prediction of asymptotic rates of response from selection on multiple traits using univariate and multivariate best linear unbiased predictors

AbstractPredicted rate of genetic response for multiple trait breeding objectives from multivariate analyses is compared with that from univariate analyses for a range of breeding schemes, A selection index that approximates a multipl trait best linear unbiased prediction (BLUP) animal model is utilized. Changes in genetic parameters due to linkage disequilibrium generated by selection are accounted for. This study shows that asymptotic response in the aggregate breeding value, and its component traits, to selection on multivariate predictions, can easily be calculated from first generation responses, which use ancestral information. For two-path breeding schemes with equal accuracy for males and females, proportional reductions in responses depend only on selection intensity. In general, benefit from multivariate over univariate analyses is slightly smaller at the asymptote than in the first generation. Multivariate analyses give substantially more response than univariate analyses on untransformed data, when correlations between traits are high and when genetic and phenotypic correlations have opposite signs. The advantage of multivariate analyses decreases with increasing family size. When three random factors (additive genetic, common and individual environmental effects) are included in the model, the benefit of multivariate analysis is negligible if univariate analyses are performed on canonical traits. In this case, the advantage of multivariate analyses is never higher than 1% for all cases studied. These results are of particular relevance to the design of genetic evaluation programmes.