The incorporation of fertility indices in genetic improvement programmes

2001 ◽  
Vol 26 (1) ◽  
pp. 237-249 ◽  
Author(s):  
J.E. Pryce ◽  
R.F. Veerkamp
Keyword(s):  
Genetic Variance ◽  
Selection Index ◽  
Genetic Correlations ◽  
Live Weight ◽  
Parameter Estimates ◽  
Phenotypic Variance ◽  
Production Traits ◽  
Genetic Progress ◽  
Detection Rates ◽  
Days Open

AbstractIn recent years there has been considerable genetic progress in milk production. Yet, increases in yield have been accompanied by an apparent lengthening of calving intervals, days open, days to first heat and a decline in conception rates, which appears to be both at the genetic and phenotypic level. Fertility has a high relative economic value compared to production traits such as protein, making it attractive to include in a breeding programme. To do this there needs to be genetic variance in fertility. Measures of fertility calculated from service dates have a small genetic compared to phenotypic variance, hence heritability estimates are small, typically less than 5%, although coefficients of genetic variance are comparable to those of production traits. Heritabilities of commencement of luteal activity determined using progesterone profiles are generally higher, and have been reported as being from 0.16 to 0.28, which could be because of a more precise quantification of genetic variance, as management influences such as delaying insemination and heat detection rates are excluded. However, it might not be the use of progesterone profiles alone, as days to first heat observed by farm staff has a heritability of 0.15. The most efficient way to breed for improved fertility is to construct a selection index using the genetic and phenotypic parameter estimates of all traits of interest in addition to their respective economic values. Index traits for fertility could include measures such as calving interval, days open, days to first service, or days to first heat but there may also be alternative measures. Examples include traits related to energy balance, such as live weight and condition score (change), both of which have higher heritabilities than fertility measures and have genetic correlations of sufficient magnitude to make genetic progress by using them feasible. To redress the balance between fertility and production, some countries already publish genetic evaluations of fertility including: Denmark, Finland, France, Germany, Israel, The Netherlands, Norway and Sweden.

scholarly journals Estimation of Genetic Parameters for Pork Quality, Novel Carcass, Primal-Cut and Growth Traits in Duroc Pigs

Animals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 779 ◽  
Author(s):  
Hannah E. Willson ◽  
Hinayah Rojas de Oliveira ◽  
Allan P. Schinckel ◽  
Daniela Grossi ◽  
Luiz F. Brito
Keyword(s):  
Genetic Parameters ◽  
Growth Traits ◽  
Low Cost ◽  
Selection Index ◽  
Carcass Traits ◽  
Genetic Correlations ◽  
Pork Quality ◽  
Production Traits ◽  
Genetic Progress ◽  
Selection Indexes

More recently, swine breeding programs have aimed to include pork quality and novel carcass (e.g., specific primal cuts such as the Boston butt or belly that are not commonly used in selection indexes) and belly traits together with growth, feed efficiency and carcass leanness in the selection indexes of terminal-sire lines, in order to efficiently produce pork with improved quality at a low cost to consumers. In this context, the success of genetic selection for such traits relies on accurate estimates of heritabilities and genetic correlations between traits. The objective of this study was to estimate genetic parameters for 39 traits in Duroc pigs (three growth, eight conventional carcass (commonly measured production traits; e.g., backfat depth), 10 pork quality and 18 novel carcass traits). Phenotypic measurements were collected on 2583 purebred Duroc gilts, and the variance components were estimated using both univariate and bivariate models and REML procedures. Moderate to high heritability estimates were found for most traits, while genetic correlations tended to be low to moderate overall. Moderate to high genetic correlations were found between growth, primal-cuts and novel carcass traits, while low to moderate correlations were found between pork quality and growth and carcass traits. Some genetic antagonisms were observed, but they are of low to moderate magnitude. This indicates that genetic progress can be achieved for all traits when using an adequate selection index.

Quantitative genetic studies on wool yellowing in Corriedale sheep. 1. Wool yellowing susceptibility and wool production traits—genetic parameter estimates

1998 ◽  
Vol 49 (8) ◽  
pp. 1195 ◽  
Author(s):  
M. V. Benavides ◽  
A. P. Maher ◽  
M. J. Young ◽  
P. R. Beatson ◽  
T. C. Reid
Keyword(s):  
Selection Index ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Fibre Diameter ◽  
Parameter Estimates ◽  
Production Traits ◽  
Correlated Responses ◽  
Percentage Yield ◽  
Fleece Weight ◽  
Average Information

The potential for the reduction of wool yellowing susceptibility (YPC) in Corriedale sheep via selection was examined. The heritabilities of YPC and greasy fleece weight (GFW) and clean fleece weight (CFW), yield percentage (Yield), mean fibre diameter (MFD), and subjective greasy wool colour assessment (Visual), and phenotypic and genetic correlations among these traits were estimated from records on 1492 progeny of 53 sires of a Corriedale flock by using restricted maximum likelihood procedures using an average information algorithm. The heritability of YPC was 0·27 ± 0·06. Genetic correlations between YPC and GFW, CFW, Yield, MFD, and Visual were 0·20 ± 0·14, 0·11 ± 0·14, –0·15 ± 0·13, 0·24 ± 0·14, and 0·95 ± 0·06, respectively. Phenotypic correlations were low between these traits and YPC. Visual had a heritability of 0·30 ± 0·06 and medium-high genetic correlations with all traits, except CFW. Heritability estimates of GFW, CFW, Yield, and MFD were 0·55 ± 0·07, 0·52 ± 0·07, 0·51 ± 0·07, and 0·52 ± 0·07, respectively. The expected correlated responses to selection against YPC are likely to cause reductions in CFW and MFD. Correlated responses from the reduction of Visual are predicted to be greater for all production traits than those from the reduction of YPC. Responses in YPC are predicted to be slightly higher when selection is on Visual (–0·21 score/year) than when selection is on YPC itself (–0·19 score/year). A selection index, including CFW, MFD, and YPC as aggregate breeding and breeding objective traits, calculated at I = +3·26CFW – 0·14MFD + 0·03YPC, predicted a YPC increase, worsening the problem.

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.

Genetic parameters for daily live-weight gain, live fleshiness and bone thinness in station-tested Piemontese young bulls

2001 ◽  
Vol 72 (3) ◽  
pp. 449-456 ◽  
Author(s):  
A. Albera ◽  
R. Mantovani ◽  
G. Bittante ◽  
A. F. Groen ◽  
P. Carnier
Keyword(s):  
Weight Gain ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Live Weight ◽  
Adaptation Period ◽  
Production Traits ◽  
Multiple Trait ◽  
Live Weight Gain ◽  
Total Gain

AbstractEstimates of genetic parameters for beef production traits were obtained for Piemontese cattle. Data were from 988 young bulls station-tested from 1989 till 1998. Bulls entered the station at 6 to 8 weeks of age and, after an adaptation period of 3 months, were tested for growth, live fleshiness and bone thinness. Length of test was 196 days. Growth traits considered were gain at farm, gain during the adaptation period, gain on test and total gain at the station. Six different fleshiness traits and bone thinness were scored on live animals at the end of the test using a linear system. Live evaluations of fleshiness were adjusted for the weight at scoring in order to provide an assessment of conformation independent of body size. Genetic parameters were estimated using animal models. Heritability of live-weight gain ranged from 0·20 in the adaptation period to 0·60 for total gain at the station. Genetic correlations between gains at station in different periods were high (from 0·63 to 0·97). Residual correlation between gain during the adaptation period and gain during test was negative, probably due to the occurrence of compensatory growth of the animals.Live fleshiness traits and bone thinness were of moderate to high heritability (from 0·34 to 0·55) and highly correlated indicating that heavy muscled bulls also have thin bones. Accuracy of breeding values and therefore response to selection were improved by multiple trait analysis of the live fleshiness traits and bone thinness. Overall weight gain at the station had a moderate negative genetic correlation with all live fleshiness traits and bone thinness (from –0·11 to –0·39).

scholarly journals Polygenic Architecture of Human Neuroanatomical Diversity

2020 ◽  
Vol 30 (4) ◽  
pp. 2307-2320
Author(s):  
Anne Biton ◽  
Nicolas Traut ◽  
Jean-Baptiste Poline ◽  
Benjamin S Aribisala ◽  
Mark E Bastin ◽  
...  
Keyword(s):  
Genetic Variance ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Global Scale ◽  
Phenotypic Variance ◽  
Environmental Correlations ◽  
Genomic Architecture ◽  
Snp Data ◽  
Environmental Causes ◽  
The Uk

Abstract We analyzed the genomic architecture of neuroanatomical diversity using magnetic resonance imaging and single nucleotide polymorphism (SNP) data from >26 000 individuals from the UK Biobank project and 5 other projects that had previously participated in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our results confirm the polygenic architecture of neuroanatomical diversity, with SNPs capturing from 40% to 54% of regional brain volume variance. Chromosomal length correlated with the amount of phenotypic variance captured, r ~ 0.64 on average, suggesting that at a global scale causal variants are homogeneously distributed across the genome. At a local scale, SNPs within genes (~51%) captured ~1.5 times more genetic variance than the rest, and SNPs with low minor allele frequency (MAF) captured less variance than the rest: the 40% of SNPs with MAF <5% captured <one fourth of the genetic variance. We also observed extensive pleiotropy across regions, with an average genetic correlation of rG ~ 0.45. Genetic correlations were similar to phenotypic and environmental correlations; however, genetic correlations were often larger than phenotypic correlations for the left/right volumes of the same region. The heritability of differences in left/right volumes was generally not statistically significant, suggesting an important influence of environmental causes in the variability of brain asymmetry. Our code is available athttps://github.com/neuroanatomy/genomic-architecture.

Genetic and phenotypic trends and parameters in reproduction, greasy fleece weight and liveweight in Merino lines divergently selected for multiple rearing ability

2004 ◽  
Vol 44 (8) ◽  
pp. 745 ◽  
Author(s):  
S. W. P. Cloete ◽  
A. R. Gilmour ◽  
J. J. Olivier ◽  
J. B. van Wyk
Keyword(s):  
Genetic Correlations ◽  
Annual Production ◽  
Production Traits ◽  
Genetic Progress ◽  
Additive Variance ◽  
Genetic Changes ◽  
Environmental Correlations ◽  
Breeding Values ◽  
Reproduction Traits ◽  
Fleece Weight

Genetic and phenotypic trends and parameters were estimated for reproduction, fleece weight and liveweight in a South African Merino population, divergently selected from 1986, either for (H line) or against (L line) maternal multiple rearing ability. Annual reproduction, ewe greasy fleece weight and pre-joining liveweight data were recorded on 809 Merino ewes, from 1986 to 2002. Phenotypic trends indicated divergence in reproduction traits between the H and L lines. The direct additive variance ratio (h2 ± s.e.) for day of lambing was 0.08 ± 0.02. Estimates of h2 for reproduction traits were: 0.10 ± 0.02 for number of lambs born per ewe; 0.04 ± 0.02 for number of lambs weaned per ewe; and 0.04 ± 0.02 for weight of lamb weaned per ewe, corrected for the gender of the lamb. Corresponding h2 estimates for annual production were 0.57 ± 0.06 for greasy fleece weight and 0.48 ± 0.06 for ewe liveweight at joining. Service sire only exerted a significant (P<0.05) effect on day of lambing, but it accounted for merely 2% of the overall phenotypic variation. Ewe permanent environment variance ratios (c2ewe) for the reproduction traits were: 0.07 ± 0.03 for number of lambs born per ewe; 0.11 ± 0.03 for number of lambs weaned per ewe; and 0.11 ± 0.03 for total weight of lamb weaned per ewe. Corresponding c2ewe estimates for annual production traits were 0.14 ± 0.05 for greasy fleece weight and 0.27 ± 0.06 for ewe joining weight. Genetic and ewe permanent environmental correlations between measures of reproduction exceeded 0.7. Genetic correlations of reproduction traits with greasy fleece weight were low and variable in sign. Genetic correlations of reproduction traits with ewe joining weight were positive and particularly high for weight of lamb weaned. Permanent environmental correlations of reproduction traits with greasy fleece weight and joining weight were generally low to moderate. Genetic trends for the H and L lines (derived from averaged direct breeding values within birth years) were divergent (P<0.01) for all reproduction traits. Expressed as percentage of the overall least squares means of the respective traits, breeding values in the H line increased annually, with 1.3% for lambs born per ewe, 1.5% for lambs weaned per ewe and by 1.8% for weight of lamb weaned per ewe. Corresponding trends in the L line were, respectively, –0.6%, –1.0% and –1.2% per year. Substantial genetic progress in annual lamb output was attainable, despite relatively small h2 estimates. This response was achieved without unfavourable genetic changes in wool and liveweight.

Multitrait and repeatability estimates of random effects on litter size in sheep

2002 ◽  
Vol 74 (2) ◽  
pp. 209-216 ◽  
Author(s):  
C. Hagger
Keyword(s):  
Litter Size ◽  
Random Effects ◽  
Genetic Gain ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Parameter Estimates ◽  
Data Sets ◽  
Phenotypic Variance ◽  
The Third ◽  
Meat Sheep

AbstractFive data sets with records of first, second and third lambings of the White Alpine sheep (WAS1, WAS2), the Brown-Headed Meat sheep (BFS), the Black-Brown Mountain sheep (SBS) and the Valais Black-Nose sheep (SNS) of Switzerland were used to estimate phenotypic and genetic parameters for litter size using a multitrait and a repeatability model by the REML method. The sets contained litter information from 26 274, 25 165, 18 913, 14 953 and 21 726 ewes, respectively. Average numbers of litters per ewe were between 2·09 and 2·31. Average litter sizes at birth were between 1·36 and 1·57 lambs in first, between 1·52 and 1·75 in second and, between 1·56 and 1·86 in third parities. Multitrait estimates of heritability for size of first litters were 0·164, 0·157, 0·117, 0·223 and 0·116 for the WAS1, WAS2, BFS, SBS and SNS data, respectively. The corresponding estimates were 0·176, 0·165, 0·140, 0·208 and 0·134 for second and, 0·141, 0·155, 0·121, 0·145 and 0·107 for third litters. The systematic increase in phenotypic variances from first to third litter within data sets favoured the multivariate over the repeatability approach. Genetic correlations between size of the first three litters were, with one exception, above 0·927. Random flock ✕ year and sire of litter effects contributed between 2·2% and 13·2% and between 0·7% and 4·7% to the phenotypic variance of the traits, respectively. Residuals contributed between 70·6% and 84·2% to this parameter, estimates for the third litter were always highest. Heritability estimates from the repeatability model were smaller than the smallest multivariate estimates. Expected genetic gain in litter size from selection on the multitrait model was equal to the achieved response from the repeatability approach.

scholarly journals Estimation of Genetic Parameters of Biomass Production and Composition Traits in Miscanthus Sinensis Using a Staggered-start Design

2021 ◽  
Author(s):  
Raphael Raverdy ◽  
Emilie Mignot ◽  
Stéphanie Arnoult ◽  
Laura Fingar ◽  
Guillaume Bodineau ◽  
...  
Keyword(s):  
Biomass Production ◽  
Genetic Parameters ◽  
Genetic Variance ◽  
Biomass Composition ◽  
Miscanthus Sinensis ◽  
Individual Plant ◽  
Production Traits ◽  
Genetic Progress ◽  
Year Effect ◽  
Large Interaction

Abstract Traits for biomass production and composition make Miscanthus a promising bioenergy crop for different bioconversion routes. They need to be considered in miscanthus breeding programs as they are subjected to genetic and genetic x environment factors. The objective was to estimate the genetic parameters of an M. sinensis population grown during four years in two French locations. In each location, the experiment was established according to a staggered-start design in order to decompose the year effect into age and climate effects. Linear Mixed Models were used to estimate genetic variance, genotype x age, genotype x climate interaction variances and residual variances. Individual plant broad-sense heritability means ranged from 0.42 to 0.62 for biomass production traits, and were more heritable than biomass composition traits with means ranging from 0.26 to 0.47. Heritability increased through time for most of the biomass production and composition traits. Low genetic variance along with large genotype x age and genotype x climate interaction variances tended to decrease the heritability of biomass production traits for young plant ages. Most of the production traits showed large interaction variances for age and climate in both locations, while biomass composition traits highlighted large interaction variances due to climate in Orléans. The genetic and phenotypic correlations between biomass production and composition traits were moderate and positive, while hemicelluloses were negatively correlated with all traits. Efficient genetic progress is achievable for miscanthus breeding when plants get older. The joint improvement of biomass production and composition traits would help provide a better response of miscanthus to selection.

Optimum selection indexes for production traits of holstein/friesian cattle in britain

1989 ◽  
Vol 1989 ◽  
pp. 17-17
Author(s):  
J.P. Gibson
Keyword(s):  
Genetic Improvement ◽  
Selection Index ◽  
Linear Functions ◽  
Production Traits ◽  
Economic Optimization ◽  
Genetic Progress ◽  
Index Approach ◽  
Production Environments ◽  
Non Linear ◽  
Production Economic

The goal of livestock genetic improvement is maximun increase in the economic efficiency of production (economic merit). When several traits contribute to economic merit, optimum genetic improvement can often be achieved by use of a discriminant function of available information (known as a selection index) which maximises expected genetic progress in the aggregate genotype, economic merit. This approach assumes that economic merit is a linear function of genetically controlled outputs. Although this may not always be true, since genetic responses are usually relatively small (0.005 to 0.020 of the mean per year) any non-linear effects are second-order and can generally be ignored. Economic optimization procedures which match production environments to genotypes would generate effectively non-linear functions, such non-linearity will generally be small. Thus the selection index approach can be applied, provided that functions describing economic merit are based on previously optimized production environments.

Quantitative genetic studies on wool yellowing in Corriedale sheep. II. Clean wool colour and wool production traits: genetic parameter estimates and economic returns

2000 ◽  
Vol 51 (2) ◽  
pp. 191
Author(s):  
M. V. Benavides ◽  
A. P. Maher
Keyword(s):  
Selection Criteria ◽  
Selection Index ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Fibre Diameter ◽  
Economic Losses ◽  
Direct Selection ◽  
Parameter Estimates ◽  
Selection Indices ◽  
Visual Colour

The potential for improvement of clean wool colour (CWC) in Corriedale sheep via selection was examined. The heritability, and phenotypic and genetic correlations, of CWC, brightness (Y), greasy (GFW) and clean (CFW) fleece weights , yield percentage (Yield), mean fibre diameter (MFD), and visual colour score were estimated from 440 progeny of 19 sires of a Corriedale flock using restricted maximum likelihood (REML) procedures with average information algorithm (AIREML). The heritability of CWC was estimated at 0.27±0.13. Clean wool colour showed strong positive genetic correlations with CFW and MFD. Visual colour score and CWC were also positively genetically correlated. As expected, direct selection criteria against MFD, CWC, or visual colour score would reduce CWC; however, direct selection against MFD would improve clean wool colour with negligible reductions on CFW, thus resulting in small economic gains. Several selection indices were calculated having either CFW, MFD, and CWC or CFW and MFD as selection criteria. The b-values of an unrestricted index were estimated at I1 = + 1.15 CFW + 0.13 MFD + 0.43 CWC, with positive correlated responses for all 3 breeding objective traits (CFW, MFD, and CWC). A second index, where CFW was restricted to nil genetic change, was estimated at: I2 = + 0.14 CFW − 0.02 MFD + 0.01 CWC. This index was expected to cause a negligible genetic gain for CWC (−0.04 Y–Z units/head.year). To avoid economic losses with the reduction on CFW, a third selection index was calculated where CWC was restricted to nil change. The index was estimated at I3 = +0.61 CFW − 0.07 MFD + 0.02 CWC with expected increases in CFW and decreases in MFD. Selection indices with (a) CFW and MFD (I4) and (b) CFW, MFD, and visual colour score (I5) as selection criteria would increase CFW, MFD, and CWC at the same rates observed in I1.

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