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

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 41-41
Author(s):  
Jorge Hidalgo ◽  
Shogo Tsuruta ◽  
Daniela Lourenco ◽  
Yijian Huang ◽  
Kent Gray ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Genomic Selection ◽  
Variance Components ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Genetic Correlations ◽  
Data Set ◽  
Daily Gain ◽  
Over Time

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.

Genetic parameter estimates for early growth traits in Naeini goat

2012 ◽  
Vol 52 (11) ◽  
pp. 1046 ◽  
Author(s):  
Hasan Baneh ◽  
Mojtaba Najafi ◽  
Ghodrat Rahimi
Keyword(s):  
Environmental Effects ◽  
Variance Components ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Parameter ◽  
Average Daily Gain ◽  
Parameter Estimates ◽  
Estimate Variance ◽  
Daily Gain ◽  
Birth Type

The present study was carried out to estimate variance components for growth traits in Naeini goats. Bodyweight records were collected for two flocks under supervision of the Agriculture Organisation of the Esfahan province between 2000 and 2007. Investigated traits were birthweight (BW; n = 2483), weaning weight (WW; n = 1211) and average daily gain from birth to weaning (ADG; n = 1211). Environmental effects were investigated using fixed-effect models, while (co)variance components and genetic parameters were estimated with single- and three-trait analyses using REML methods and WOMBAT software. Six different animal models were fitted to the traits, with the best model for each trait determined by log-likelihood ratio tests (LRT). All traits were significantly influenced by herd, birth year, sex of the kid, birth type and dam age (P < 0.01). On the basis of LRT, maternal permanent environmental effects (c2) were significant for WW and ADG, while BW was affected only by direct genetic effects. Direct heritability estimates for BW, WW and ADG were 0.25 ± 0.05, 0.07 ± 0.06 and 0.21 ± 0.11, respectively. The estimate of c2 was 0.16 ± 0.06 for both WW and ADG. Estimates of genetic correlation for BW–ADG, BW–WW and ADG–WW were 0.49, 0.61 and 0.94, respectively. The estimated phenotypic correlations were positive and were between 0.03 (BW–ADG) and 0.95 (ADG–WW). These results indicate that selection can be used to improve growth traits in this goat breed.

Genetic parameters for growth and carcass traits of Japanese Black (Wagyu) cattle

2000 ◽  
Vol 71 (1) ◽  
pp. 59-64 ◽  
Author(s):  
T. Oikawa ◽  
T. Sanehira ◽  
K. Sato ◽  
Y. Mizoguchi ◽  
H. Yamamoto ◽  
...  
Keyword(s):  
Body Weight ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Carcass Traits ◽  
Genetic Correlations ◽  
Subcutaneous Fat ◽  
Marbling Score ◽  
Data Set ◽  
Pooled Data

AbstractRestricted maximum likelihood analyses fitting an animal model were conducted to estimate genetic parameters with a pooled-data set of performance tests (growth traits and food intake) on 661 bulls and progeny tests (growth traits and carcass traits) on 535 steers. Traits studied included concentrate intake (CONC), roughage intake (ROU), TDN conversion (TCNV), TDN intake (TINT) of bulls; rib eye area (REA), marbling score (MARB), dressing proportion (DRES) and subcutaneous fat depth (SCF) of steers. Body weight at start (BWS), body weight at finish (BWF) and average daily gain (ADG) of all animals were measured. Estimated heritabilities were 0·18 (CONC), 0·71 (ROU), 0·11 (TCNV) and 0·36 (TINT); 0·02 (REA), 0·49 (MARB), 0·15 (DRES), 0·15 (SCF), and from 0·20 to 0·38 for growth traits. Genetic correlations of ROU were different from those of CONC, probably due to inconsistent restrictions on concentrate intake; those of TINT with the weights, ADG and SCF were high. MARB showed positive genetic correlations with growth traits and low correlations with TINT and SCF. High potentiality for improvement of marbling score was suggested.

scholarly journals Genetic parameters for direct and maternal effects on growth traits of sheep

2012 ◽  
Vol 55 (6) ◽  
pp. 603-611 ◽  
Author(s):  
F. Ghafouri-Kesbi ◽  
H. Baneh
Keyword(s):  
Maternal Effects ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Genetic Correlations ◽  
Selection Criterion ◽  
Information Criterion ◽  
Phenotypic Variance ◽  
Environmental Variance ◽  
Daily Gain

Abstract. The aim of the present study was to estimate (co)variance components and corresponding genetic parameters for birth weight (BW), weaning weight (WW), 6-month weight (W6), 9-month weight (W9), average daily gain from birth to weaning (WWDG), average daily gain from weaning to 6 months (W6DG) and average daily gain from 6 months to 9 months (W9DG) for a nucleus flock of Iranian Makooei sheep. Genetic parameters were estimated by REML procedure fitting six animal models including various combinations of maternal effects. The Akaike information criterion (AIC) was used to determine the most appropriate model. Estimates of direct heritability (h2) ranged from 0.13 (W6DG) to 0.32 (BW). Maternal effects were found to be important in the growth performance of the Makooei sheep, indicating the necessity of including maternal effects in the model to obtain accurate estimates of direct heritability. Estimates of maternal heritability (m2) ranged from 0.05 (W6) to 0.16 (WWDG) and the estimates of proportion of maternal permanent environmental variance to phenotypic variance (c2) were in the range between 0.05 (BW) and 0.10 (W6). Direct additive genetic correlations were positive in all cases and ranged from 0.00 (BW/W9DG) to 0.99 (WW/WWDG). Phenotypic correlations showed a broad range from −0.27 (WW/W9DG) to 0.99 (WW/WWDG). Estimates of genetic parameters showed that genetic improvement through selection programs is possible. WW would be a suitable selection criterion since it has acceptable direct heritability and relatively high genetic correlation with other traits.

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

2020 ◽  
Vol 98 (2) ◽  
Author(s):  
Jorge Hidalgo ◽  
Shogo Tsuruta ◽  
Daniela Lourenco ◽  
Yutaka Masuda ◽  
Yijian Huang ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Relationships ◽  
Genetic Correlations ◽  
Genomic Analysis ◽  
Data Set ◽  
Genetic Changes ◽  
Fitness Traits ◽  
Bayesian Implementation

Abstract 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.

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

2020 ◽  
Vol 98 (8) ◽  
Author(s):  
Alberto Cesarani ◽  
Jorge Hidalgo ◽  
Andre Garcia ◽  
Lorenzo Degano ◽  
Daniele Vicario ◽  
...  
Keyword(s):  
Variance Components ◽  
Genetic Parameters ◽  
Average Daily Gain ◽  
Genetic Correlations ◽  
Single Step ◽  
Breeding Values ◽  
Current Population ◽  
Heritability Estimates ◽  
Over Time ◽  
Combined Data

Abstract 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.

Adaptability in tropical beef cattle: genetic parameters of growth, adaptive and temperament traits in a crossbred population

2005 ◽  
Vol 45 (8) ◽  
pp. 971 ◽  
Author(s):  
K. C. Prayaga ◽  
J. M. Henshall
Keyword(s):  
Beef Cattle ◽  
Genetic Parameters ◽  
Genetic Variance ◽  
Growth Traits ◽  
Additive Genetic Variance ◽  
Average Daily Gain ◽  
Genetic Correlations ◽  
Temperament Traits ◽  
Indicator Traits ◽  
Daily Gain

Adaptability in tropical beef cattle can be assessed by measurable traits such as growth under the influence of environmental stressors, by parasite resistance as measured by indicator traits such as tick counts (TICK) and faecal egg counts of worms (EPG), by heat resistance as measured by indicator traits such as rectal temperatures (TEMP) and coat scores (COAT) and, to a certain extent, temperament of the animal as measured by flight time (FT). Data from a crossbreeding experiment involving various genotypes derived from tropically adapted British, Sanga-derived, Zebu cross, Zebu and Continental beef cattle breeds were analysed to estimate variance components and genetic parameters of growth, adaptive and temperament traits. Breed group differences were accounted for by including fractional coefficients of direct and maternal additive and dominance genetic effects as covariates. In the univariate analyses, 6 models were compared ranging from the simplest model with animal as the only random effect to the full model comprising direct and maternal additive genetic variance and their covariance and the permanent environment effect due to dam (growth traits) and animal (adaptive and temperament traits). The heritability estimates were 0.41, 0.21, 0.19, 0.28, 0.41 and 0.15 for birth weight (BWT), weaning weight (WWT), preweaning average daily gain (PREADG), yearling weight (YWT), final weight at about 18 months of age (FWT) and post-weaning average daily gain (POADG), respectively. The maternal component of additive genetic variance as a proportion of phenotypic variance in BWT, WWT and PREADG was 0.15, 0.10 and 0.10, respectively. The heritability estimates for TICK, EPG, TEMP, COAT and FT were 0.13, 0.24, 0.12, 0.26 and 0.20, respectively. High positive genetic and phenotypic correlations were observed among growth traits. Low (insignificant) genetic correlations were observed between TICK, EPG and growth traits. However, genetic correlations between growth traits and heat tolerance traits (TEMP and COAT) were moderately negative implying that as the ability of an animal to handle heat stress increases, growth also increases at the genetic level. Genetic correlations among TICK, EPG and TEMP were moderately positive, suggesting that closely-linked genes affect these adaptive traits. The significant negative genetic relationship between TEMP and FT suggests that cattle with high heat resistance have desirable temperament. With the increasing crossbred populations in the northern Australian beef cattle industry, the best breeding strategy should aim to exploit both crossbreeding and within population selection to make improvements in growth, adaptive and temperament traits to increase overall productivity of the enterprise.

HERITABILITIES AND GENETIC CORRELATIONS FOR ULTRASONIC BACKFAT MEASUREMENTS, GROWTH AND CARCASS TRAITS IN SWINE

1982 ◽  
Vol 62 (3) ◽  
pp. 665-670 ◽  
Author(s):  
D. C. JEFFRIES ◽  
R. G. PETERSON
Keyword(s):  
Key Words ◽  
Genetic Correlation ◽  
Genetic Parameters ◽  
Average Daily Gain ◽  
Genetic Correlations ◽  
Phenotypic Correlation ◽  
Ultrasonic Measurements ◽  
Yorkshire Pigs ◽  
Daily Gain ◽  
Season Interaction

Genetic parameters were estimated for 2403 purebred Yorkshire pigs over a 2-yr period, representing 21 sires. The traits studied included average daily gain, age adjusted to 90 kg, ultrasonic measurements of backfat at the mid-back and loin positions, total and adjusted total ultrasonic backfat and corresponding carcass backfat measurements. Least squares analyses were used to estimate and adjust for the effects of sex, year-season and sex by year-season interaction. Heritabilities and genetic correlations were calculated for all traits using both half- and full-sib estimates. Adjusted age and adjusted total ultrasonic backfat measurements were found to have the highest heritabilities of the live traits in this study. Estimates of heritability for adjusted age and adjusted total ultrasonic backfat were 0.24 ± 0.10 and 0.26 ± 0.10 based on half-sib and 0.56 ± 0.07 and 0.41 ± 0.06 from full-sib analyses. The genetic correlation between these two traits was −0.07 ± 0.28 based on the half-sib method. The total phenotypic correlation was −0.01 ± 0.02. Key words: Swine, ultrasonic backfat, heritabilities, genetic correlations

scholarly journals (Co)variance components and genetic parameters for growth rate and Kleiber ratio in fat-tailed Mehraban sheep

2013 ◽  
Vol 56 (1) ◽  
pp. 564-572 ◽  
Author(s):  
F. Ghafouri-Kesbi
Keyword(s):  
Growth Rate ◽  
Variance Components ◽  
Genetic Parameters ◽  
Average Daily Gain ◽  
Genetic Correlations ◽  
Phenotypic Variance ◽  
Genetic Progress ◽  
Kleiber Ratio ◽  
Derivative Free ◽  
Maternal Heritability

Abstract. The aim of the present study was to estimate (co)variance components and genetic parameters for average daily gain from birth to weaning (ADGa), weaning to 6 months (ADGb), weaning to 9 months (ADGc), 6 months to 9 months (ADGd) and corresponding Kleiber ratios (KRa, KRb, KRc and KRd) in Mehraban sheep. A derivative-free algorithm combined with a series of six univariate linear animal models was used to estimate phenotypic variance and its direct, maternal and residual components. In addition, bivariate analyses were done to estimate (co)variance components between traits. Estimates of direct heritability (h2) were 0.10, 0.11, 0.16, 0.09, 0.13, 0.13, 0.15 and 0.08 for ADGa, ADGb, ADGc, ADGd, KRa, KRb, KRc and KRd, respectively and indicate that in Mehraban sheep genes contribute very little to the variance of the growth rate and Kleiber ratio. Estimates of maternal heritability (m2) were 0.10, 0.08 and 0.05 for ADGa, KRa and KRb, respectively. Direct additive genetic correlations ranged from −0.32 (KRa-KRd) to 0.99 (ADGb-KRb) and phenotypic correlations ranged from −0.53 (ADGa- ADGd) to 0.99 (ADGa-KRa). Estimates of direct heritability and genetic correlations show that genetic improvement in efficiency of feed utilization through selection programmes is possible, though it would generate a relatively slow genetic progress.

scholarly journals Characterizing the oligogenic architecture of plant growth phenotypes informs genomic selection approaches in a common wheat population

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Noah DeWitt ◽  
Mohammed Guedira ◽  
Edwin Lauer ◽  
J. Paul Murphy ◽  
David Marshall ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Plant Growth ◽  
Genomic Selection ◽  
Plant Height ◽  
Prediction Models ◽  
Growth Traits ◽  
Heading Date ◽  
Additive Genetic Variation ◽  
Moderate Effect ◽  
Over Time

Abstract Background Genetic variation in growth over the course of the season is a major source of grain yield variation in wheat, and for this reason variants controlling heading date and plant height are among the best-characterized in wheat genetics. While the major variants for these traits have been cloned, the importance of these variants in contributing to genetic variation for plant growth over time is not fully understood. Here we develop a biparental population segregating for major variants for both plant height and flowering time to characterize the genetic architecture of the traits and identify additional novel QTL. Results We find that additive genetic variation for both traits is almost entirely associated with major and moderate-effect QTL, including four novel heading date QTL and four novel plant height QTL. FT2 and Vrn-A3 are proposed as candidate genes underlying QTL on chromosomes 3A and 7A, while Rht8 is mapped to chromosome 2D. These mapped QTL also underlie genetic variation in a longitudinal analysis of plant growth over time. The oligogenic architecture of these traits is further demonstrated by the superior trait prediction accuracy of QTL-based prediction models compared to polygenic genomic selection models. Conclusions In a population constructed from two modern wheat cultivars adapted to the southeast U.S., almost all additive genetic variation in plant growth traits is associated with known major variants or novel moderate-effect QTL. Major transgressive segregation was observed in this population despite the similar plant height and heading date characters of the parental lines. This segregation is being driven primarily by a small number of mapped QTL, instead of by many small-effect, undetected QTL. As most breeding populations in the southeast U.S. segregate for known QTL for these traits, genetic variation in plant height and heading date in these populations likely emerges from similar combinations of major and moderate effect QTL. We can make more accurate and cost-effective prediction models by targeted genotyping of key SNPs.

scholarly journals 209 Genomic selection for multiple maternal and growth traits in large white pigs using Single-Step GBLUP

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 42-42
Author(s):  
Breno Fragomeni ◽  
Zulma Vitezica ◽  
Justine Liu ◽  
Yijian Huang ◽  
Kent Gray ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Growth Traits ◽  
Computing Time ◽  
Average Daily Gain ◽  
Genetic Correlations ◽  
Single Step ◽  
Genomic Information ◽  
Genomic Evaluation ◽  
Large White ◽  
Daily Gain

Abstract The objective of this study was to implement a multi-trait genomic evaluation for maternal and growth traits in a swine population. Phenotypes for preweaning mortality, litter size, weaning weight, and average daily gain were available for 282K Large White pigs. The pedigree included 314k individuals, of which 35,731 were genotyped for 45K SNPs. Variance components were estimated in a multi-trait animal model without genomic information by AIREMLF90. Genomic breeding values were estimated using the genomic information by single-step GBLUP. The algorithm for proven and young (APY) was used to reduce computing time. Genetic correlation between proportion and the total number of preweaning deaths was 0.95. A strong, positive genetic correlation was also observed between weaning weight and average daily gain (r = 0.94). Conversely, the genetic correlations between mortality and growth traits were negative, with an average of -0.7. To avoid computations by expensive threshold models, preweaning mortality was transformed from a binary trait to two linear dam traits: proportion and a total number of piglets dead before weaning. Because of the high genetic correlations within groups of traits, inclusion of only one growth and one mortality trait in the model decreases computing time and allows for the inclusion of other traits. Reduction in computing time for the evaluation using APY was up to 20x, and no differences in EPD ranking were observed. The algorithm for proven and young improves the efficiency of genomic evaluation in swine without harming the quality of predictions. For this population, a binary trait of mortality can be replaced by a linear trait of the dam, resulting in a similar ranking for the selection candidates.

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