scholarly journals 303 ASAS-EAAP Talk: On the estimation of genetic parameters from molecular data

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 33-33
Author(s):  
Miguel Toro Ibáñez
Keyword(s):  
Linkage Disequilibrium ◽  
Genetic Correlation ◽  
Genomic Selection ◽  
Genetic Parameters ◽  
Genetic Variance ◽  
Genetic Correlations ◽  
Molecular Data ◽  
Snp Markers ◽  
Directional Selection ◽  
Recombination Rates

Abstract We deal with several problems that arise when inferring genetic parameters at the level of quantitative trait loci (QTL) from molecular data such as SNP markers. Linkage Disequilibrium (LD) is recognized as a factor creating ambiguity in the partition of genetic variance. Here, using a simple model with three loci (one QTL and two markers), it is shown that the markers generate apparent AxA and DxD epistasis, even if only third order disequilibrium exists and the QTL is dominant. The problem of “phantom epistasis” is not alleviated by larger sample sizes (de los Campos et al., 2019). We also show that markers can give a distorted picture of the genetic correlation between traits: The genomic correlation could be greater, lower or even of opposite sign than the true genetic correlation. Therefore, speculating about genetic correlations and even about their causes (e.g., pleiotropy) using genomic data is often conjectural. Thirdly, we examine the problem of directional selection generating negative linkage disequilibrium (“Bulmer effect”) in the short term from a genomic selection perspective. It seems that the reduction in response due to the Bulmer effect is the same for genomic selection as for selection based on traditional BLUP. However, the reduction in response with genomic selection is greater than when selection is based directly on phenotypes only (Van Grevenhof et al. 2012). It is also expected that directional selection for a polygenic trait should increase recombination rate, provided there is genetic variance for recombination. It is then of relevance to ask whether recombination rates could be manipulated in order to increase selection response (Battagin et al., 2016). Finally, we consider that recombination and epistasis are closely intertwined: Epistasis generate LD and recombination break them up. Then, we should expect genomes to be modular: regions with low recombination containing functionally related genes loosely linked to other regions.

scholarly journals Realized Sampling Variances of Estimates of Genetic Parameters and the Difference Between Genetic and Phenotypic Correlations

Genetics ◽  
1996 ◽  
Vol 143 (3) ◽  
pp. 1409-1416 ◽  
Author(s):  
Kenneth R Koots ◽  
John P Gibson
Keyword(s):  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Phenotypic Correlation ◽  
Parameter Estimates ◽  
Sampling Variance ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Heritability Estimates

Abstract A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.

scholarly journals Linkage disequilibrium and genetic variances under mutation-selection balance.

Genetics ◽  
1989 ◽  
Vol 121 (4) ◽  
pp. 857-860 ◽  
Author(s):  
A Hastings
Keyword(s):  
Linkage Disequilibrium ◽  
Mutation Rate ◽  
Genetic Variance ◽  
Harmonic Mean ◽  
Recombination Rates ◽  
Genetic Variances ◽  
Locus Selection

Abstract I determine the contribution of linkage disequilibrium to genetic variances using results for two loci and for induced or marginal systems. The analysis allows epistasis and dominance, but assumes that mutation is weak relative to selection. The linkage disequilibrium component of genetic variance is shown to be unimportant for unlinked loci if the gametic mutation rate divided by the harmonic mean of the pairwise recombination rates is much less than one. For tightly linked loci, linkage disequilibrium is unimportant if the gametic mutation rate divided by the (induced) per locus selection is much less than one.

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 Genetic parameters of production and reproduetive traits in on a farm tested Danish Large White and Landrace swine in Greece

2000 ◽  
Vol 43 (3) ◽  
pp. 287-298
Author(s):  
J. Bizelis ◽  
A. Kominakis ◽  
E. Rogdakis ◽  
F. Georgadopoulou
Keyword(s):  
Maximum Likelihood ◽  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Production Traits ◽  
Likelihood Methods ◽  
Large White ◽  
Reproduction Traits ◽  
Maximum Likelihood Methods ◽  
Genetic And Phenotypic Correlations

Abstract. Production and reproduetive traits in Danish Landrace (LD) and Large White (LW) swine were analysed by restricted maximum likelihood methods to obtain heritabilities as well as genetic and phenotypic correlations. Production traits were: age, backfat thickness (BT), muscle depth (MD) and the ratio BT/MD, adjusted to Standard bodyweight of 85 kg. Reproduction traits were: number of pigs born (NB) and number of pigs weaned (NW) per sow and parity. Heritabilities for age, BT, MD and BT/MD were 0.60, 0.44, 0.51 and 0.42 for LD and 0.36, 0.44, 0.37 and 0.45 for LW, respectively. Genetic correlations between age and BT were −0.22 in LD and – 0.44 in LW. The genetic correlation between age and MD was close to zero in both breeds. Genetic correlation between BT and MD were −0.36 and −0.25 in LD and LW, respectively. Heritabilities for NB were 0.25 in LD and 0.13 in LW while heritabilities for NW were close to zero in both breeds. Genetic correlation between NB and NW was 0.46 and 0.70 in LD and LW, respectively.

scholarly journals PSVIII-38 Late-Breaking Abstract: Estimating genetic parameters of feed efficiency traits in American mink

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 347-347
Author(s):  
Pourya Davoudi ◽  
Duy Ngoc Do ◽  
Guoyu Hu ◽  
Siavash Salek Ardestani ◽  
Younes Miar
Keyword(s):  
Body Weight ◽  
Genetic Correlation ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
American Mink ◽  
Genetic Correlations ◽  
Final Body Weight ◽  
Selection For

Abstract Feed cost is the major input cost in the mink industry and thus improvement of feed efficiency through selection for high feed efficient mink is necessary for the mink farmers. The objective of this study was to estimate the heritability, phenotypic and genetic correlations for different feed efficiency measures, including final body weight (FBW), daily feed intake (DFI), average daily gain (ADG), feed conversion ratio (FCR) and residual feed intake (RFI). For this purpose, 1,088 American mink from the Canadian Center for Fur Animal Research at Dalhousie Faculty of Agriculture were recorded for daily feed intake and body weight from August 1 to November 14 in 2018 and 2019. The univariate models were used to test the significance of sex, birth year and color as fixed effects, and dam as a random effect. Genetic parameters were estimated via bivariate models using ASReml-R version 4. Estimates of heritabilities (±SE) were 0.41±0.10, 0.37±0.11, 0.33±0.14, 0.24±0.09 and 0.22±0.09 for FBW, DFI, ADG, FCR and RFI, respectively. The genetic correlation (±SE) was moderate to high between FCR and RFI (0.68±0.15) and between FCR and ADG (-0.86±0.06). In addition, RFI had low non-significant (P > 0.05) genetic correlations with ADG (0.04 ± 0.26) and BW (0.16 ± 0.24) but significant (P < 0.05) high genetic correlation with DFI (0.74 ± 0.11) indicating that selection for lower RFI will reduce feed intake without adverse effects on the animal size and growth rate. The results suggested that RFI can be implemented in genetic/genomic selection programs to reduce feed intake in the mink production system.

Genetic parameter estimations and genomic insights for teat and udder structure in young and mature Canadian Angus cows

2021 ◽  
Author(s):  
K Devani ◽  
J J Crowley ◽  
G Plastow ◽  
K Orsel ◽  
T S Valente
Keyword(s):  
Animal Model ◽  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Age Groups ◽  
Morbidity And Mortality ◽  
Parameter Estimations ◽  
Angus Cattle ◽  
Genetic Evaluations

Abstract Poor teat and udder structure, frequently associated with older cows, impact cow production and health, as well as calf morbidity and mortality. However, producer culling, for reasons including age, production, feed availability, and beef markets, creates a bias in teat and udder scores assessed and submitted to the Canadian Angus Association for genetic evaluations towards improved mammary structure. In addition, due to the infancy of the reporting program, repeated scores are rare. Prior to adoption of genetic evaluations for teat and udder scores in Canadian Angus cattle, it is imperative to verify that teat and udder scores from young cows are the same trait as teat and udder scores estimated on mature cows. Genetic parameters for teat and udder scores from all cows (n=4,192), and then from young cows (parity 1 and 2) and from mature cows (parity ≥ 4) were estimated using a single trait animal model. Genetic correlations for the traits between the two cow age groups were estimated using a two-trait animal model. Estimates of heritability (PSD) were 0.32 (0.07) and 0.45 (0.07) for young teat and udder score, and 0.27 (0.07) and 0.31 (0.07) for mature teat and udder score, respectively. Genetic correlation (PSD) between the young and mature traits was 0.87 (0.13) for teat score and 0.40 (0.17) for udder score. GWAS were used to further explore the genetic and biological commonalities and differences between the two groups. Although there were no genes in common for the two udder scores, 12 genes overlapped for teat score in the two cow age groups. Interestingly, there were also 23 genes in common between teat and udder scores in mature cows. Based on these findings, it is recommended that producers collect teat and udder score on their cow herd annually.

Genetic parameters for egg weight v. age curve, and other egg production and egg weight traits, in synthetic lines of chickens

1983 ◽  
Vol 34 (1) ◽  
pp. 85 ◽  
Author(s):  
BH Yoo ◽  
BL Sheldon ◽  
RN Podger
Keyword(s):  
Standard Deviation ◽  
Genetic Correlation ◽  
Egg Production ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Egg Mass ◽  
Control Line ◽  
Egg Weight ◽  
Egg Number ◽  
Selection For

An exponential curve, W = P-Qexp(- Rt), where W is egg weight at age t, was fitted to egg weights of individual pullets, and genetic parameters were estimated for P, Q and R, the residual standard deviation and other egg weight and egg production characters. The data consisted of records collected over six generations on more than 4000 pullets in two selection lines and a control line which originated from a synthetic gene pool of White Leghorn x Australorp crosses. The half-sib and offspring-on-parent regression estimates of heritability pooled over the lines were 0.23 and 0.33 for P, 0.14 and 0.20 for Q, and 0.14 and 0.25 for R. Genetic correlations were estimated to be -0.10 between P and Q, -0.46 between P and R, and 0.90 between Q and R. These estimates suggest that the egg weight v. age curve may be modified to increase the proportion of eggs in desirable weight grades and reduce the incidence of oversized eggs later in the production year. The genetic correlation between mean weight of first 10 eggs and egg weight at 62 weeks of age was estimated to be 0.68, further suggesting that early egg weight may be improved partly independently of late egg weight. The heritability estimates of egg mass output were not higher than those of egg number in spite of the highly heritable average egg weight being an important component of egg mass, probably because of the negative genetic correlation (r = -0.49) between egg number and average egg weight. The standard deviation of individual pullet's egg weights was moderately heritable and genetically correlated positively with egg weight characters and negatively with egg production; these estimates were consistent with the responses to selection for reduced egg weight variability observed elsewhere

scholarly journals Genetic parameters for fatty acids in intramuscular fat from feedlot-finished Nelore carcasses

2018 ◽  
Vol 58 (2) ◽  
pp. 234 ◽  
Author(s):  
Carolyn Aboujaoude ◽  
Angélica Simone Cravo Pereira ◽  
Fabieli Louise Braga Feitosa ◽  
Marcos Vinicius Antunes de Lemos ◽  
Hermenegildo Lucas Justino Chiaia ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Intramuscular Fat ◽  
Zebu Cattle ◽  
Fa Composition ◽  
Heritability Estimates ◽  
The Individual ◽  
Long Chain

The aim of the present study was to estimate covariance components and genetic parameters for beef fatty acid (FA) composition of intramuscular fat in the longissimus thoracis muscle in Nelore bulls finished in feedlot. Twenty-two FAs were selected. The heritability estimates for individual FAs ranged from 0.01 to 0.35. The heritability estimates for myristic (0.25 ± 0.09), palmitic (0.18 ± 0.07), oleic (0.28 ± 0.09), linoleic (0.16 ± 0.06) and α-linolenic (0.35 ± 0.10) FAs were moderate. Stearic, elaidic, palmitoleic, vaccenic, conjugated linoleic acid, docosahexanoic, eicosatrienoic and arachidonic FAs had heritability estimates below 0.15. The genetic-correlation estimates between the individual saturated FAs (SFAs) were low and negative between myristic and stearic FAs (–0.22 ± 0.84), moderate between palmitic and myristic FAs (0.58 ± 0.56) and negative between palmitic and stearic FAs (–0.69 ± 0.45). The genetic correlations between the individual long-chain polyunsaturated FAs (PUFAs) were positive and moderate (>0.30). However, the genetic-correlation estimates between long-chain PUFAs and α-linolenic acid were low (<0.30), except for the correlation between arachidonic and α-linolenic acids. The genetic correlation estimates of the sums of SFAs with monounsaturated fatty acids and omega 6 FAs were low (0.25 ± 0.59 and –0.02 ± 0.51 respectively), high with PUFAs and omega 9 FAs (–0.85 ± 0.15 and 0.86 ± 0.17 respectively) and moderate with omega 3FAs (–0.67 ± 0.26). The present study demonstrated the existence of genetic variation and, hence, the possibility to increase the proportion of healthy and favourable beef FAs through selection. The results obtained in the study have provided knowledge to elucidate the additive genetic influence on FA composition of intramuscular fat. In addition, genetic-relationship estimates of intramuscular FA profile help seek strategies for genetic selection or genetic-based diet management to enhance the FA profile in Zebu cattle.

scholarly journals AN EXPERIMENTAL EVALUATION OF GENETIC CORRELATION

Genetics ◽  
1973 ◽  
Vol 75 (4) ◽  
pp. 709-726
Author(s):  
J J Rutledge ◽  
E J Eisen ◽  
J E Legates
Keyword(s):  
Body Weight ◽  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Tail Length ◽  
Current Theory ◽  
Standard Errors ◽  
Index Selection ◽  
Effective Population ◽  
Selection Intensities

ABSTRACT Heritability and genetic correlations realized from both single-trait and antagonistic index selection were compared with paternal half-sib estimates. Primary attention was focused on the genetic correlation between six-week body weight and six-week tail length. Parameters realized from single-trait selection were in excellent agreement with paternal half-sib estimates. However, the realized genetic correlation between six-week body weight and six-week tail length obtained from index selection was significantly greater than the other estimates. Differential inbreeding levels and realized selection intensities were considered and rejected as being causative factors for these results. Linkage disequilibrium probably was not a factor either, as the base population had been randomly mated and randomly selected with a large effective population size for many generations. It was concluded that with antagonistic index selection, the pleiotropic effects of genes may be more powerful in retarding response in aggregate genotype than current theory would suggest. Replication of all selected and control lines allowed the use of between-line estimators of sampling variances of realized genetic parameters in the above comparisons. Generally, standard errors of realized genetic parameters were much smaller than corresponding paternal half-sib standard errors. Thus, selection was an efficient method of estimation.

Micron blowout: heritability and genetic correlations with fibre diameter and secondary follicle diameter

1999 ◽  
Vol 50 (8) ◽  
pp. 1375 ◽  
Author(s):  
J. A. Hill ◽  
R. W. Ponzoni ◽  
J. W. James
Keyword(s):  
Genetic Correlation ◽  
Scale Effect ◽  
Genetic Variance ◽  
Genetic Correlations ◽  
Fibre Diameter ◽  
The Other ◽  
Follicle Diameter ◽  
The Difference ◽  
Biased Estimates ◽  
Practical Implications

Calculation of micron blowout as the difference between fibre diameter records taken at different ages can produce ‘biased’ estimates of the heritability and genetic correlations due to a scale effect. In some instances, standardisation of the fibre diameter records to a common genetic variance (i.e. removal of the scale effect) changed the heritability and the genetic correlation estimates. The effect of standardisation on the heritability of micron blowout was determined to a large extent by the difference in the genetic variance between the 2 fibre diameter measurements, whereas in the case of the genetic correlation between micron blowout and another trait, it was also dependent on the genetic correlation between the other trait and the two fibre diameters. It is recommended that heritabilities and genetic correlations involving micron blowout be calculated after standardising the fibre diameter measurements to a common genetic variance. The practical implications of the results are briefly discussed.

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