Heritability Estimates For Traits Research Articles

INTERRELATION OF YIELD AND ITS COMPONENTS IN COTTON (Gossypium hirsutum L.) GENOTYPES

Cotton is regarded as a profitable crop that gives people fiber and shelter. Research focuses on how yield, its components, and related attributes work together to enhance cotton. During the Kharif season of 2022, the present study was completed, implementing a randomized complete block design with ten genotypes and three replications. The study took place at the Nuclear Institute of Agriculture (NIA), located in Tandojam. This work aimed to examine the correlation and regression between upland cotton genotypes and heritability estimates for traits associated with yield. The outcomes showed that all of the parameters in the mean square of the ANOVA were significant. In contrast to the remaining genotypes, genotype FH-142 displayed the most favorable performance; it had the tallest plants, more sympodial branches, more bolls per plant, an improved seed index, and the longest staple length. The genotype CRIS-342 came in second, exhibiting good plant height, sympodial branches, a good number of bolls per plant, a ginning outturn, and the highest boll weight among the other genotypes. The findings of the correlation and regression indicated that the number of bolls per plant-1 had a highly significant and positive relationship with monopodial branches plant-1 (r = 0.73*) and (b = 2.45) and that the number of bolls per plant had a strong relationship with seed cotton yield plant-1 (r = 0.83**) and (b = 3.29). Staple length and seed cotton yield plant-1 had a negative correlation (-0.77*) with regression (b = -4.58). The highest heritability estimates in the broad sense are for monopodial branch plants (84.61), ginning outturn% (97.03), bolls plant-1 (93.96), plant height (90.70), staple length (79.31), and seed index (71.42). However, the boll's weight showed a low heritability (23.71). Further breeding programs can utilize genotype FH-142 to increase the number of sympodial branches, increase the number of boll plants, and improve the staple length. Genotype CRIS-342 can be utilized for medium-stature plant height, boll weight, and better ginning outturn. However, genotype NIA-BT-40 can be utilized for short-strategy plants with the highest ginning output.

PSX-9 Comparison of single- and multiple-trait genomic predictions of cattle carcass quality traits in multibreed and purebred populations

Abstract Estimation of genetic parameters for carcass traits and their use in the evaluation of carcass quality is of considerable importance in the genetic improvement of beef cattle. The objective of this study was to compare the predictive ability of single- and multi-trait genomic prediction models for the following carcass quality traits: hot carcass weight (HCW); fat thickness (FAT); rib eye area (REA); marbling score (MARB); and peak force (PEAKF) from multibreed and purebred populations. The purebred population included 1,068 purebred Angus animals from Iowa State University whereas the multibreed population consisted of 887 animals sired by 1 of 8 purebreds (209 Angus-, 10 Brahman-, 182 Charolais-, 76 Hereford-, 44 Limousin-, 136 Maine-Anjou-, 96 Shorthorn-, and 134 South Devon- sired offspring) from the Carcass Merit Project funded by the US beef cattle industry to evaluate the genetic prediction of tenderness. After quality control of SNP markers generated with Illumina v1 50K BeadChips, 33,718 SNP markers from were used to obtain heritability and genetic correlation estimates between traits separately in either the multibreed or purebred populations. Genotyped individuals were randomly clustered into 10 groups for cross-fold validation to quantify the correlations between and predicted performance (without the individual’s data) and the realized phenotype of the individual from single- or multi-trait genomic prediction in the multibreed and purebred populations. Heritability estimates of traits from multi-trait analyses ranged from 0.42 to 0.61 in multibreed population and from 0.24 to 0.44 in the purebred population, whereas the single trait values were 0.30 to 0.53 in multibreed, and 0.23 to 0.42 in the purebred population. Estimates were greater in the multibreed population compared with the purebred population (Table 1). Compared with the single-trait analyses, multi-trait analyses resulted in higher heritability estimates for FAT, REA and PEAKF traits in the purebred population and for HCW, REA, MARB and PEAKF traits in multibreed population. Genetic correlations from multi-trait analyses indicated the genetic association between traits. In testing data sets, correlations between observed and predicted phenotypes from single-trait analyses were 4- to 7-fold greater in purebred than in the multibreed population (Table 2). These results may be due to the greater genomic relationship expected in purebred than in the multibreed population. However, the multi-trait analyses resulted in a considerable increase in correlations between observed and predicted values in multibreed population due to genetic correlations between traits.

Genetic and environmental effects on morphological traits of social phenotypes in wasps.

Many species exhibit distinct phenotypic classes, such as sexes in dioecious species or castes in social species. The evolution of these classes is affected by the genetic architecture governing traits shared between phenotypes. However, estimates of the genetic and environmental factors contributing to phenotypic variation in distinct classes have rarely been examined. We studied the genetic architecture underlying morphological traits in phenotypic classes in the social wasp Vespula maculifrons. Our data revealed patriline effects on a few traits, indicating weak genetic influences on caste phenotypic variation. Interestingly, traits exhibited higher heritability in queens than workers. This result suggests that genetic variation has a stronger influence on trait variation in the queen caste than the worker caste, which is unexpected because queens typically experience direct selection. Moreover, estimates of heritability for traits were correlated between the castes, indicating that variability in trait size was governed by similar genetic architecture in the two castes. However, we failed to find evidence for a significant relationship between caste dimorphism and caste correlation, as would be expected if trait evolution was constrained by intralocus genetic conflict. Our analyses also uncovered variation in the allometric relationships for traits. These analyses suggested that worker traits were proportionally smaller than queen traits for most traits examined. Overall, our data provide evidence for a strong environmental and moderate genetic basis of trait variation among castes. Moreover, our results suggest that selection previously operated on caste phenotype in this species, and phenotypic variation is now governed primarily by environmental differences.

The phenotypic and genetic effects of drought-induced stress on wood specific conductivity and anatomical properties in white spruce seedlings, and relationships with growth and wood density.

Drought frequency and intensity are projected to increase with climate change, thus amplifying stress on forest trees. Resilience to drought implicates physiological traits such as xylem conductivity and wood anatomical traits, which are related to growth and wood density. Integrating drought-stress response traits at the juvenile stage into breeding criteria could help promote the survival of planted seedlings under current and future climate and thus, improve plantation success. We assessed in greenhouse the influence of drought-induced stress on 600 two-year-old white spruce (Picea glauca) seedlings from 25 clonal lines after two consecutive growing seasons. Three levels of drought-induced stress were applied: control, moderate and severe. Seedlings were also planted at a 45° angle to clearly separate compression from normal wood. We looked at the phenotypic and genetic effects of drought stress on xylem specific hydraulic conductivity, lumen diameter, tracheid diameter and length, and the number of pits per tracheid in the normal wood. We detected no significant effects of drought stress except for tracheid length, which decreased with increasing drought stress. We found low to high estimates of trait heritability, which generally decreased with increasing drought stress. Genetic correlations were higher than phenotypic correlations for all treatments. Specific conductivity was genetically highly correlated positively with lumen diameter and tracheid length under all treatments. Tracheid length and diameter were always negatively correlated genetically, indicating a trade-off in resource allocation. Moderate to high genetic correlations sometimes in opposite direction were observed between physico-anatomical and productivity traits, also indicating trade-offs. A large variation was observed among clones for all physico-anatomical traits, but clonal ranks were generally stable between control and drought-induced treatments. Our results indicate the possibility of early screening of genetic material for desirable wood anatomical attributes under normal growing conditions, thus allowing to improve the drought resilience of young trees.

Planting Density Does Not Affect Root Shape Traits Associated with Market Class in Carrot

Carrot (Daucus carota var. sativus) cultivars with common root shape, appearance, and end-use are grouped and commercialized in market classes. The shape of the carrot storage root is the result of growth and development, which is highly influenced by genotype; however, the extent to which planting density affects root shape traits and its interaction with genotype remains unexplored. To observe the effects of market class and density on carrot root shape characteristics, five cultivars classified in five different market classes, including Imperator, Nantes, Danvers, Chantenay, and Ball, were each grown at five planting densities ranging from 0.5 million to 4.5 million plants/ha. A generalized complete block design with a two-way factorial treatment arrangement of the two factors, density and genotype, was used in three environments. Roots were phenotyped using a digital imaging pipeline and scored for root size (length, maximum width) and compound root shape traits including traits derived from the principal component analysis of root contour profiles like root fill and tip and shoulder curvature. The results suggest that planting density had minimal impact on the shape of carrot roots, and the expected shape for each market class was maintained regardless of planting density; however, the analysis was constrained by the presence of interactions among genotype, density, and environment, which influence the contribution of main effects to shape. For the Nantes, Danvers, Chantenay, and Imperator market classes, planting density influenced the size of the carrot root, with size decreasing by up to 50% in length and width at high planting densities. We found high estimates of broad-sense heritability for traits that determine the shape of the carrot root, such as root fill and length-to-width ratio, which capture size-independent variation of the storage root. Although environmental signals play a role, our results suggested that the shape of the carrot root is primarily determined by genotype, and that planting density generally does not have a significant effect on its shape.

Genetic architecture and genomic selection of fatty acid composition predicted by Raman spectroscopy in rainbow trout

BackgroundIn response to major challenges regarding the supply and sustainability of marine ingredients in aquafeeds, the aquaculture industry has made a large-scale shift toward plant-based substitutions for fish oil and fish meal. But, this also led to lower levels of healthful n−3 long-chain polyunsaturated fatty acids (PUFAs)—especially eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids—in flesh. One potential solution is to select fish with better abilities to retain or synthesise PUFAs, to increase the efficiency of aquaculture and promote the production of healthier fish products. To this end, we aimed i) to estimate the genetic variability in fatty acid (FA) composition in visceral fat quantified by Raman spectroscopy, with respect to both individual FAs and groups under a feeding regime with limited n-3 PUFAs; ii) to study the genetic and phenotypic correlations between FAs and processing yields- and fat-related traits; iii) to detect QTLs associated with FA composition and identify candidate genes; and iv) to assess the efficiency of genomic selection compared to pedigree-based BLUP selection.ResultsProportions of the various FAs in fish were indirectly estimated using Raman scattering spectroscopy. Fish were genotyped using the 57 K SNP Axiom™ Trout Genotyping Array. Following quality control, the final analysis contained 29,652 SNPs from 1382 fish. Heritability estimates for traits ranged from 0.03 ± 0.03 (n-3 PUFAs) to 0.24 ± 0.05 (n-6 PUFAs), confirming the potential for genomic selection. n-3 PUFAs are positively correlated to a decrease in fat deposition in the fillet and in the viscera but negatively correlated to body weight. This highlights the potential interest to combine selection on FA and against fat deposition to improve nutritional merit of aquaculture products. Several QTLs were identified for FA composition, containing multiple candidate genes with indirect links to FA metabolism. In particular, one region on Omy1 was associated with n-6 PUFAs, monounsaturated FAs, linoleic acid, and EPA, while a region on Omy7 had effects on n-6 PUFAs, EPA, and linoleic acid. When we compared the effectiveness of breeding programmes based on genomic selection (using a reference population of 1000 individuals related to selection candidates) or on pedigree-based selection, we found that the former yielded increases in selection accuracy of 12 to 120% depending on the FA trait.ConclusionThis study reveals the polygenic genetic architecture for FA composition in rainbow trout and confirms that genomic selection has potential to improve EPA and DHA proportions in aquaculture species.

Genetic evaluation of growth performance of kashmir merino sheep

A study was conducted to evaluate the growth performance of Kashmir Merino sheep at two Government Sheep Breeding Farms (Kralapathri and Goabal) in Kashmir using 6299 birth records spread over 21 years (1997 to 2017). Mixed linear model with sire as a random effect and year, sex, birth type, parity and farm as fixed effects were used for analysis. The overall least squares means for birth weight (BW), six months body weight (W6), average daily gain from birth to six months (ADG1), metabolic weight at six months (W6 0.75), Kleiber ratio from birth to six months (KR1), yearling bodyweight (W12), metabolic weight at yearling age (W12 0.75), average daily gain from six month toyearling age (ADG2) and Kleiber ratio from six months to yearling age (KR2) were 3.26±0.06 kg, 18.74±0.47 kg, 84.60±2.63 g, 8.96±0.17kg, 9.27±0.12, 21.75±0.66 kg, 10.03±0.23kg, 22.21±3.01 g and 2.11±0.25, respectively. The effects of year and sex of animal were significant (P<0.01) whereas, effect of birth type (except BW) and farm was non-significant for all the traits. The effect of parity was significant on the BW, W6, W6 0.75, KR1 and W12. The estimates of heritability for BW, W6, ADG1, W60.75, KR1, W12, W120.75, ADG2 and KR2 were 0.64±0.07, 0.54±0.07, 0.54±0.06, 0.55±0.06, 0.54±0.07, 0.60±0.09, 0.69±0.09, 0.50±0.08 and 0.59±0.08, respectively. The genetic, phenotypic and environmental correlations ranged from low to high. The high heritability estimates of traits under study indicated existence of genetic variance which can be utilised to improve growth performance and feed efficiency conversion of Kashmir Merino sheep. To reduce the generation interval, 6 month body weight (high heritability and high genetic correlations with other traits including 12 month weight) canbechosenas aselection criterion.

Bayesian, Likelihood-Free Modelling of Phenotypic Plasticity and Variability in Individuals and Populations.

There is a paradigm shift from the traditional focus on the “average” individual towards the definition and analysis of trait variation within individual life-history and among individuals in populations. This is a result of increasing availability of individual phenotypic data. The shift allows the use of genetic and environment-driven variations to assess robustness to challenge, gain greater understanding of organismal biological processes, or deliver individual-targeted treatments or genetic selection. These consequences apply, in particular, to variation in ontogenetic growth. We propose an approach to parameterise mathematical models of individual traits (e.g., reaction norms, growth curves) that address two challenges: 1) Estimation of individual traits while making minimal assumptions about data distribution and correlation, addressed via Approximate Bayesian Computation (a form of nonparametric inference). We are motivated by the fact that available information on distribution of biological data is often less precise than assumed by conventional likelihood functions. 2) Scaling-up to population phenotype distributions while facilitating unbiased use of individual data; this is addressed via a probabilistic framework where population distributions build on separately-inferred individual distributions and individual-trait interpretability is preserved. The approach is tested against Bayesian likelihood-based inference, by fitting weight and energy intake growth models to animal data and normal- and skewed-distributed simulated data. i) Individual inferences were accurate and robust to changes in data distribution and sample size; in particular, median-based predictions were more robust than maximum- likelihood-based curves. These results suggest that the approach gives reliable inferences using few observations and monitoring resources. ii) At the population level, each individual contributed via a specific data distribution, and population phenotype estimates were not disproportionally influenced by outlier individuals. Indices measuring population phenotype variation can be derived for study comparisons. The approach offers an alternative for estimating trait variability in biological systems that may be reliable for various applications, for example, in genetics, health, and individualised nutrition, while using fewer assumptions and fewer empirical observations. In livestock breeding, the potentially greater accuracy of trait estimation (without specification of multitrait variance-covariance parameters) could lead to improved selection and to more decisive estimates of trait heritability.

How does selfing affect the genetic variance of quantitative traits? An updated meta-analysis on empirical results in angiosperm species.

Most theoretical works predict that selfing should reduce the level of additive genetic variance available for quantitative traits within natural populations. Despite a growing number of quantitative genetic studies undertaken during the last two decades, this prediction is still not well supported empirically. To resolve this issue and confirm or reject theoretical predictions, we reviewed quantitative trait heritability estimates from natural plant populations with different rates of self-fertilization and carried out a meta-analysis. In accordance with models of polygenic traits under stabilizing selection, we found that the fraction of additive genetic variance is negatively correlated with the selfing rate. Although the mating system explains a moderate fraction of the variance, the mean reduction of narrow-sense heritability values between strictly allogamous and predominantly selfing populations is strong, around 60%. Because some nonadditive components of genetic variance become selectable under inbreeding, we determine whether self-fertilization affects the relative contribution of these components to genetic variance by comparing narrow-sense heritability estimates from outcrossing populations with broad-sense heritability estimated in autogamous populations. Results suggest that these nonadditive components of variance may restore some genetic variance in predominantly selfing populations; it remains, however, uncertain how these nonadditive components will contribute to adaptation.

Genetic analysis of reproductive performance in sows during porcine reproductive and respiratory syndrome (PRRS) and porcine epidemic diarrhea (PED) outbreaks

BackgroundPorcine reproductive and respiratory syndrome (PRRS) is one of the most infectious swine diseases in the world, resulting in over 600 million dollars of economic loss in the USA alone. More recently, the USA swine industry has been having additional major economic losses due to the spread of porcine epidemic diarrhea (PED). However, information regarding the amount of genetic variation for response to diseases in reproductive sows is still very limited. The objectives of this study were to identify periods of infection with of PRRS virus (PRRSV) and/or PED virus (PEDV), and to estimate the impact their impact on the phenotypic and genetic reproductive performance of commercial sows.ResultsDisease (PRRS or PED) was significant (P < 0.05) for all traits analyzed except for total piglets born. Heritability estimates for traits during Clean (without any disease), PRRS, and PED ranged from 0.01 (number of mummies; Clean and PED) to 0.41 (abortion; PED). Genetic correlations between traits within disease statuses ranged from −0.99 (proportion born dead with number weaned; PRRS) to 0.99 (number born dead with born alive; Clean). Within trait, between disease statuses, estimates ranged from − 0.17 (number weaned between PRRS and PED) to 0.99 (abortion between Clean and PRRS).ConclusionResults indicate that selection for improved performance during PRRS and PED in commercial sows is possible and would not negatively impact performance in Clean environments.

Genetic Variation among Fennel (Foeniculum vulgare Mill.) Varieties on the Basis of Essential Oil Composition and Molecular Markers (ISSR, SCoT, CDDP and CBDP)

Fennel (Foeniculum vulgare Mill.) benefits from a lot of useful medicinal properties. Genetic variance and heritability estimates of traits in a plant's primary germplasms are needed before planning of a new breeding programme. In the present study, the genetic diversity for 14 fennel ecotypes was assessed by using molecular markers (ISSR, SCoT, CDDP and CBDP). Across the cultivars, a total of 102 fragments got amplified, of which 692 were polymorphic. Average polymorphic band per primer was 6.7. The highest amounts of polymorphism were observed in variety RF-145 and RF-205. As per diversity analysis, the polymorphic varieties were screened further for essential oil content. Essential oil content was determined by gas-chromatography–mass-spectrometry. Both varieties were evaluated for their essential oil content and its composition. Essential oil content ranged from 20.05 to 25.21%. Twenty-three major compounds including limonene, p-ocimene, p-ocimene, dihydrotagetone, tagetone, cis-tagetone, trans-tagetone. β-Terpinene, camphene, sabinine, myrcene, β-phellandrene, γ-terpinene, linalool, fenchone, methyl chavicol, trans-anethole, cis-anethole, camphor, estragole, β-elemene, α-himachalene and β-himachalene were detected. In variety RF-145 and 17 major compounds including α-pinene, camphene, β-pinene, myrcene, carvacrol, fenchone, α-terpinene, β-elemene, γ-terpinene, thymol, limonene, trans-anethole, camphor, estragole, camphene, sabinine, myrcene were detected in variety RF-205. Anethole was most abundant compound in both fennel germplasm lines which ranged from a minimum of 69.35% to a maximum of 73.44%.

Genetic evaluation of egg quality traits in Uttara fowl using MMLSML

External and internal egg quality traits of Uttara fowl reared at instructional poultry farm were measured in 125 eggs selected from 25 sires. The heritability estimates of traits were estimated from sire component of variances and covariances using mixed model least- squares and maximum likelihood (MMLSML). Heritability estimates for external egg quality traits ranged from 0.34 to 0.83 and for internal egg quality traits from 0.19 to 0.81. Genetic correlation between egg weight and eggshell thickness (EST) was positive (0.43) and EST showed high genetic correlations with eggshell weight (0.79) also. Internal egg quality traits like albumen height showed high positive genetic correlations with albumen weight (0.63), albumen index (0.84), yolk height (0.71) and yolk index (0.65). In conclusion, higher albumen height tends to have better internal egg quality and it is feasible to improve egg quality through selection.

New mastitis phenotypes suitable for genomic selection in meat sheep and their genetic relationships with udder conformation and lamb live weights

Mastitis can prove expensive in sheep reared for meat production due to costs associated with treatment methods, poor lamb growth and premature culling of ewes. The most commonly used method to detect mastitis, in dairy systems, is somatic cell counts. However, in many meat-producing sheep flocks ewes are not routinely handled, thus regular milk sampling is not always possible. It is, therefore, worthwhile to investigate alternative phenotypes, such as those associated with udder conformation and methods of evaluating somatic cell counts in the milk, such as the California Mastitis Test. The main objectives of this study were therefore: (a) to estimate genetic parameters of traits relating to mastitis and udder conformation in a meat sheep breed; (b) estimate the level of association between somatic cell counts and the California Mastitis Test and (c) assess the relationships between mastitis and both udder conformation and lamb live weights. Data were collected from Texel ewes based on 29 flocks, throughout the UK, during 2015 and 2016. The ewes were scored twice each year, at mid- and late-lactation. Eight different conformation traits, relating to udder and teat characteristics, and milk samples were recorded. The data set comprised of data available for 2957 ewes. The pedigree file used contained sire and dam information for 31 775 individuals. The animal models used fitted relevant fixed and random effects. Heritability estimates for traits relating to mastitis (somatic cell score and the California Mastitis Test), ranged from 0.08 to 0.11 and 0.07 to 0.11, respectively. High genetic correlations were observed between somatic cell score and the California Mastitis Test (0.76 to 0.98), indicating the California Mastitis Test to be worthwhile for assessing infection levels, particularly at mid-lactation. The strongest correlations observed between the mastitis traits and the udder conformation traits were associated with udder depth (0.61 to 0.75) also at mid-lactation. Negative phenotypic correlations were estimated between mastitis and the weight of lamb reared by the ewe (−0.15 to −0.23), suggesting that lamb weights fell as infection levels rose. Genetic correlations were not significantly different from zero. Reducing mastitis will lead to improvements in flock productivity and the health and welfare of the animals. It will also improve the efficiency of production and the resilience to disease challenge. The economic benefits, therefore, of these results combined could be substantial not only in this breed but also in the overall meat sheep industry.

Genetic analysis of a red tilapia (Oreochromis spp.) population undergoing three generations of selection for increased body weight at harvest

Quantitative genetic analysis was performed on 10,919 data records collected over three generations from the selection programme for increased body weight at harvest in red tilapia (Oreochromis spp.). They were offspring of 224 sires and 226 dams (50 sires and 60 dams per generation, on average). Linear mixed models were used to analyse body traits (weight, length, width and depth), whereas threshold generalised models assuming probit distribution were employed to examine genetic inheritance of survival rate, sexual maturity and body colour. The estimates of heritability for traits studied (body weight, standard length, body width, body depth, body colour, early sexual maturation and survival) across statistical models were moderate to high (0.13-0.45). Genetic correlations among body traits and survival were high and positive (0.68-0.96). Body length and width exhibited negative genetic correlations with body colour (-0.47 to -0.25). Sexual maturity was genetically correlated positively with measurements of body traits (weight and length). Direct and correlated genetic responses to selection were measured as estimated breeding values in each generation and expressed in genetic standard deviation units (σG). The cumulative improvement achieved for harvest body weight was 1.72 σG after three generations or 12.5% per generation when the gain was expressed as a percentage of the base population. Selection for improved body weight also resulted in correlated increase in other body traits (length, width and depth) and survival rate (ranging from 0.25 to 0.81 genetic standard deviation units). Avoidance of black spot parent matings also improved the overall red colour of the selected population. It is concluded that the selective breeding programme for red tilapia has succeeded in achieving significant genetic improvement for a range of commercially important traits in this species, and the large genetic variation in body colour and survival also shows that there are prospects for future improvement of these traits in this population of red tilapia.

Categorical Visual Score Traits of a Nellore Beef Cattle Population

Variance components and genetic parameters of economically relevant traits in livestock, whether continuous or categorical, can be estimated by methods computationally available providing support for the selection and mating of animals in breeding programs. The objectives of this paper were to obtain and compare the variance components estimates for visual traits under continuous or categorical distribution in single-trait analysis and their correlations with continuous productive traits in two-trait analysis. Data of conformation (CONF), precocity of fat deposition (PREC) and muscling (MUSC) visual scores evaluated at 18 months of age as well as the weight at 18 months of age (YW) were collected from animals born from 2000 to 2012, in Nellore cattle herds raised in Southeastern and Central Western tropical regions of Brazil. Methods III of Henderson, Restricted Maximum Likelihood (REML), Bayesian Inference and generalized linear mixed model (GLMM) were tested. Variance components obtained from single-trait analysis were similar to those obtained from two-trait analysis. The estimates of heritability (h2) for the visual scores ranged from 0.1081 to 0.2190. Heritability estimates for traits evaluated by visual scores have moderate to high magnitude justifying the inclusion of visual scores as selection criteria in animal breeding and the selection of animals with higher scores for mating. High genetic correlations between yearling weight and morphological traits were verified. For visual scores of conformation, precocity and muscling, the most suitable model based on one-trait or two-trait analyses considered an animal model, a linear distribution of the data and the estimation method of the components of (co)variance based on Bayesian methodology.

Estimates of genetic parameters for lifetime reproductive performance traits in Makuie ewes

The objective of this study was to estimate genetic parameters for lifetime (over 2–5 years of age) reproductive performance traits in Makuie ewes. The data were extracted from Makuie Sheep Breeding and Raising Station dataset between 1989 and 2015. The studied traits were average of lifetime fertility, fecundity, survival, stay-ability, and total of lifetime female lambs born per ewe joined, female lambs weaned per ewe joined, weight of lambs born, weight of lambs weaned, and pregnancy days. Each trait was fitted by four different animal models, which were differentiated by including or excluding maternal effects. The Akaike information criterion was used to select the most appropriate model for each trait. In addition, series of bivariate animal models were implemented to estimate genetic and phenotypic correlations between traits. Estimates of direct heritability for traits were ranged from 0.00 to 0.15, which indicated that some traits (average fertility, average fecundity, and total weight of lambs born) had low additive genetic basis but others had no or very lower genetic basis. Maternal effects (both genetic and permanent environment) had very little or no effect on the studied traits. Genetic and phenotypic correlations between traits ranged from −0.92 to 0.99 and −0.01 to 0.97, respectively. The results indicated that fertility, fecundity, and total weight of lambs born could be improved by inclusion in the selection index due to their heritability estimation of greater than 0.12. For other traits genetic gain through conventional genetic selection method may be useless in Makuie sheep due to their low heritability estimates. However, these traits could be improved by providing better environment and management techniques.

Effect of inclusion or non-inclusion of short lactations and cow and/or dam genetic group on genetic evaluation of Girolando dairy cattle.

The objective of this study was to evaluate the effects of inclusion or non-inclusion of short lactations and cow (CGG) and/or dam (DGG) genetic group on the genetic evaluation of 305-day milk yield (MY305), age at first calving (AFC), and first calving interval (FCI) of Girolando cows. Covariance components were estimated by the restricted maximum likelihood method in an animal model of single trait analyses. The heritability estimates for MY305, AFC, and FCI ranged from 0.23 to 0.29, 0.40 to 0.44, and 0.13 to 0.14, respectively, when short lactations were not included, and from 0.23 to 0.28, 0.39 to 0.43, and 0.13 to 0.14, respectively, when short lactations were included. The inclusion of short lactations caused little variation in the variance components and heritability estimates of traits, but their non-inclusion resulted in the re-ranking of animals. Models with CGG or DGG fixed effects had higher heritability estimates for all traits compared with models that consider these two effects simultaneously. We recommend using the model with fixed effects of CGG and inclusion of short lactations for the genetic evaluation of Girolando cattle.

Pregnancy scanning can be used as a source of data for genetic evaluation of reproductive traits of ewes

Reproductive traits generated from mothering up lambs to ewes (n = 59 603 records) were compared with data resulting from pregnancy scanning (n = 46 663 records), to examine the consistency between the two data sources for deriving specific reproductive traits and to estimate genetic parameters. The reproductive traits considered were fertility (FERT: 0/1) of ewes joined, total litter size (LSIZE: lambs born), the number of lambs surviving at weaning (LSIZEW: lambs weaned) and the percentage of lambs surviving (LSURV = LSIZEW/LSIZE) for ewes that lambed, along with the composite traits number of lambs born (NLB) and number weaned (NLW) for ewes joined. Corresponding trait values were derived from pregnancy scan data (FERT_S, LSIZE_S and NLB_S) for comparison, and were classified as inconsistent if the trait values did not match from scanning and lambing records. Data were obtained from four flocks, representing different time frames, locations, management and breeds or bloodlines. Each flock recorded scan data separately from lambing outcomes. Genetic parameters were estimated separately within each flock. Average levels of inconsistency between scan- and lambing-data values varied between 4.6% and 14.8% across flocks, tending to be highest (9.1–18.5%) for litter size of ewes scanned with multiple fetuses, and lowest (0.29–7.3%) for assignment of fertility. Inconsistencies did not have a significant impact on estimates of trait heritabilities, suggesting recording errors were independent of genetic merit. In three flocks, the genetic correlations (ra) between comparable traits derived from the different data sources were not different from unity (ra ≥ 0.99) even when phenotypic correlations (rp) were lower (rp ≥ 0.84). In the flock with the highest inconsistency rate between data sources, the range in ra varied between 0.60 (fertility) and 1.0 (litter size). Therefore, pregnancy scan data can be directly substituted for reproductive traits traditionally based on lambing data, but attention should be paid to ensuring accuracy of the data sources used. Scan data also provide no information on lamb-survival outcomes after birth, so does not constitute complete data on reproductive outcomes. Genetic evaluation systems might also benefit from fine tuning for scale-induced effects (due to litter size) on parameters to improve the accuracy of across flock prediction of breeding values for reproductive traits.

Genetic and environmental components of phenotypic and behavioral trait variation during lake sturgeon (Acipenser fulvescens) early ontogeny

Quantifying the relative contributions of genetic and environmental effects and their interaction on phenotypic variation is vital to understand how populations respond to their environment. Adults can plastically respond to environmental conditions by selecting breeding and egg incubation locations that affect offspring traits during embryonic and larval development. Environmental conditions during incubation can also affect traits during later ontogenetic stages (i.e., ontogenetic contingency). Using a well-studied population of lake sturgeon (Acipenser fulvescens) from Black Lake, Michigan, eggs were reared from full and half-sibling families at two spawning locations and in a common garden experiment consisting of three water velocity treatments: high, low, and variable. Larvae reared within the stream varied significantly between spawning sites for traits quantified at hatch including body length, body area, and yolk-sac area. Estimates of trait heritabilities ranged from 0.42–0.48. Growth from hatch to 2–3 weeks post hatch when larvae emerged from the substrate to begin exogenously feeding varied among families reared at the spawning locations due to a genotype-by-environment (G-by-E) interaction. In the common garden experiment, phenotypic variation among families was greatest for larvae reared under high velocity and a significant G-by-E was detected for body length, body area, and head area. Growth also varied among velocity treatments, but did not vary between families. Overall, results indicate that adult-selected spawning and rearing locations as well as genetic effects influence offspring phenotypic trait variation. Importantly, egg incubation conditions can also affect trait variation during sequential ontogenetic stages potentially affecting larval survival and population levels of recruitment.

Abstract P070: Comparison of Heritability Estimation Using the Principal Components Calculated by Maximizing Variance and Heritability for OSA Traits

RATIONALE: Obstructive sleep apnea (OSA) is a common disorder characterized by repetitive pauses in breathing during sleep associated with significant cardiovascular morbidity. Accumulating study results suggest that there are strong genetic contributions for this disease as defined by the apnea hypopnea index (AHI), the number of breathing pauses per hour of sleep. Using this metric, it has been shown that OSA significantly aggregates within families (1-2); heritability for the AHI is estimated to vary from about 20 to 40% (2-3). However, the AHI is only one index from several that describe OSA severity, and may not be the most relevant phenotype for genetic studies. It has not, however, been clear how to systematically assess heritability of multiple correlated and uncorrelated OSA traits. METHODS: To identify OSA related phenotypes that are most heritable to inform discovery of genetic risk variants for the disease, heritability analysis of multiple OSA related phenotypes were conducted using family data from Cleveland Family Study which comprises 700 African Americans from 147 families and 669 European Americans from 139 families. Principal-components analysis was performed using two approaches for combining data for six OSA traits that describe several dimensions of physiological and clinical impairment: the AHI and three other sleep study metrics (average hypopnea duration, average oxygen saturation, and percent time at oxygen saturation of &lt; 90%) and two OSA symptoms (habitual snoring and excessive sleepiness). One method uses the traditional principal-components (PC) approach assuming all subjects are independent. The other developed by Rabinowitz and Ott (4) calculates principal components by maximizing the heritability. RESULTS: In European Americans, the maximum heritability for the traditional multi-trait PC was 0.513 (SE=0.1010) while it was 0.512 (SE=0.100) for the PC calculated maximizing heritability. The maximum individual trait heritability was for average oxygen saturation, which is 0.388 (SE=0.107). In African Americans, the maximum heritability of traditional multi-trait 0.50 (SE=0.094) while it was 0.616 (SE=0.091) for the PC calculated maximizing heritability. The maximum individual trait heritability was for average hypopnea duration, which is 0.570 (SE=0.096). CONCLUSIONS: In general, both principal components approaches (maximizing variance and heritability) of six OSA related traits result higher heritability estimates than individual trait heritability estimates. The principal components approach based on maximizing heritability has the potential to improve trait heritability and therefore can be useful in future association analysis for searching genes underlying obstructive sleep apnea.