Estimates Of Genetic Correlations Research Articles

Estimation of genetic correlation with summary association statistics

SummaryGenome-wide association studies have identified thousands of genetic variants that are associated with complex traits. Many complex traits are shown to share genetic etiology. Although various genetic correlation measures and their estimators have been developed, rigorous statistical analysis of their properties, including their robustness to model assumptions, is still lacking. We develop a method of moments estimator of genetic correlation between two traits in the framework of high-dimensional linear models. We show that the genetic correlation defined based on the regression coefficients and the linkage disequilibrium matrix can be decomposed into both the pleiotropic effects and correlations due to linkage disequilibrium between the causal loci of the two traits. The proposed estimator can be computed from summary association statistics when the raw genotype data are not available. Theoretical properties of the estimator in terms of consistency and asymptotic normality are provided. The proposed estimator is closely related to the estimator from the linkage disequilibrium score regression. However, our analysis reveals that the linkage disequilibrium score regression method does not make full use of the linkage disequilibrium information, and its jackknife variance estimate can be biased when the model assumptions are violated. Simulations and real data analysis results show that the proposed estimator is more robust and has better interpretability than the linkage disequilibrium score regression method under different genetic architectures.

PSIII-8 Genetic Parameter Estimates for Bull Prolificacy and Its Relationship with Scrotal Circumference in a Commercial Beef Cattle Population

Abstract The commercial beef cattle industry relies heavily on the use of natural service sires. Either due to the size of breeding herds or to safe-guard against injury during the breeding season, multiple-sire breeding pastures are utilized. Although each bull might be given an equal opportunity to produce offspring, evidence suggest that there is substantial variation in the number of calves sired by each bull in a breeding pasture. DNA-based paternity assignment enables correct assignment of calves to their respective sires in multi-sire pastures and presents an opportunity to investigate the degree to which this trait complex is under genetic control. Field data from a large commercial ranch were used to estimate genetic parameters for calf count (CC; n=623) and yearling scrotal circumference (SC; n=1962) using univariate and bivariate animal models. Average CC and SC were 12.1±11.1 calves and 35.4±2.30 cm, respectively. Average number breeding seasons per bull and bulls per contemporary group were 1.40 and 24.9, respectively. The model for CC included fixed effects of age during the breeding season (in years) and contemporary group (concatenation of breeding pasture and year). Random effects included additive genetic and permanent environmental effects, and a residual. The model for SC included fixed effects of age (in days) and contemporary group (concatenation of month and year of measurement). Random effects included an additive genetic effect and a residual. Univariate model heritability estimates for CC and SC were 0.237±0.156 and 0.456±0.072, respectively. Similarly, the bivariate model resulted in heritability estimates for CC and SC of 0.240±0.155 and 0.461±0.072, respectively. Repeatability estimates for CC from univariate and bivariate models were 0.517±0.054 and 0.518±0.053, respectively. The estimate of genetic correlation between CC and SC was 0.270±0.220. Parameter estimates suggest that both CC and SC would respond favorably to selection and that CC is moderately repeatable.

127 Antibody Response as an Indicator Trait for Improved Reproductive Performance During a PRRSV Outbreak: Genetic Correlations of S/P Ratio with Reproductive Traits in Landrace and Duroc Sows

Abstract Previous studies proposed the use of antibody response to Porcine Reproductive and Respiratory Syndrome virus (PRRSV), measured as sample-to-positive (S/P) ratio, as a potential indicator trait to improve the reproductive performance of PRRSV-infected Landrace sows. However, this indicator trait has not yet been validated in Landrace sows or evaluated in a terminal sire line, such as Duroc. The main objective of this work was to perform host-genetic analyses of S/P ratio and reproductive traits during a PRRSV outbreak in maternal and terminal breeds. The data consisted of 690 Duroc and 541 Landrace multiparous sows (1.9±1.2 and 2.3±1.5, respectively) with S/P ratio collected at approximately 54 days after the predicted beginning of the outbreak. Of these, 644 Duroc and 528 Landrace sows also had reproductive data recorded during the PRRSV outbreak comprising number of piglets born alive (NBA), stillborn piglets (NSB), mummified piglets (NBM), number born dead (NBD; sum of NSB and NBM), total number born (TNB; sum of NBA and NBD), and number weaned (NW). All animals had genotype data on ~30K SNPs common across both breeds. Heritability estimates (± standard error) of S/P ratio during the PRRSV outbreak were moderate, with 0.33±0.06 for Duroc and 0.28±0.07 for Landrace. Reproductive traits during the PRRSV outbreak had overall low heritability estimates (≤0.18). Favorable genetic correlations of S/P ratio with NBA (0.65±0.33), in accordance with previous studies, and NBD (-0.33±0.28) were observed for Landrace sows only. Estimates of genetic correlation with other traits were -0.21±0.30 (NBM), -0.12±0.29 (NSB), 0.10±0.38 (NW), and 0.54±1.29 (TNB) for Landrace. For Duroc, these estimates were weaker: -0.33±0.40 (NBA), 0.26±0.27 (NBA), and 0.28±0.30 (NW), with convergence issues for mortality traits. These results further support the use of S/P ratio as an indicator trait for improved reproductive performance during a PRRSV outbreak in Landrace sows.

A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding

The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.

Comparison of genetic parameters and estimated breeding values for worm resistance in meat sheep obtained using traditional and genomic models.

Gastrointestinal nematode infections have caused expressive losses in sheep production worldwide. The improvement of host genetic resistance to worms has been used as a strategy to mitigate this problem. In this sense, the inclusion of genomic information has shown potential to increase the accuracy of prediction of breeding values and speed up selection. In this study, we aimed to compare estimates of genetic parameters and breeding values for traits that indicate the resistance to gastrointestinal nematode infection in Santa Inês sheep using the pedigree-based BLUP or including genomic information. There were 1478 animals in the pedigree, of which 271 were genotyped using the OvineSNP50 BeadChip (Illumina, Inc.). The host resistance was assessed using the following traits: fecal nematode egg counts (FEC); FAMACHA score (FAMACHA); and resistance to gastrointestinal nematode infection (RGNI) as a combination of FEC, FAMACHA, body condition score, and hematocrit. The genetic parameters and breeding values were estimated using single- and multi-trait analyses. For RGNI, the heritability estimates ranged from 0.25 using the single-trait genomic model (S-H) to 0.54 using the traditional multi-trait model (M-A). The heritability estimates for FEC ranged from 0.06 to 0.36, using the single-trait pedigree-based model (S-A) and the multi-trait genomic model (M-H), respectively. For FAMACHA, the heritability estimates ranged from 0.46 (M-H) to 0.54 (M-A). Estimates of genetic correlation ranged from 0.22 to 0.69. The inclusion of genomic information provided gain in accuracy for all traits. All estimates of predictive ability obtained using genomic data in a multi-trait setting were higher than those obtained using single-trait models. The estimates of predictive ability ranged from 0.03 (S-A) to 0.46 (M-H). The heritability estimates obtained using genomic information showed that all traits evaluated are suitable for genomic selection. Despite the low accuracies obtained, the use of the genomic model provided more accurate estimates of breeding values in comparison to the pedigree-based model.

Estimation of heritability and genetic correlations between milk yield and linear type traits in primiparous Holstein-Friesian cows

Estimation of genetic variability and genetic correlations between production traits (milk yield, fat yield, fat content, protein yield, and protein content) and selected type traits (angularity, fore udder height, rear udder height, front teat placement, teat length, and udder depth) was done using data sets of 10,860 first-calving Holstein-Friesian cows raised in the territory of the Republic of Serbia. Genetic variance and covariance were obtained using the Restricted Maximum Likelihood (REML) method, VCE v6 software, and the multi-trait mixed [...]

Estimates of genetic dissimilarity, selection indices and correlations in a melon germplasm

The success of breeding programs depends on genetic variability. Individuals selected based on a few traits may be a limitation. One alternative is the use of nonparametric indices. However, there is no information on the use of selection indices in melon germplasms. The present study aimed to estimate genetic dissimilarity in a melon germplasm and select potential parent plants for future breeding programs. The genetic material consisted of 37 melon accessions and were assessed the fruit diameter and length, diameter and length of the fruit cavity and total soluble solids. Genetic dissimilarity was assessed by multivariate analyses (UPGMA and Tocher). Selection gain estimates were analyzed by comparing the classic Smith-Hazel and sum of ranks indices. Genetic diversity was observed between accessions. The variable that contributed most to genetic dissimilarity was fruit cavity length. Simultaneous selection for the traits assessed based on the sum of ranks index is better suited to melon germplasm assessment. The best accessions for the five variables simultaneously were UFU07, UFU23, UFU09, UFU21, UFU28 and UFU30.

Heat stress during late pregnancy and postpartum influences genetic parameter estimates for birth weight and weight gain in dual-purpose cattle offspring generations.

Impact of direct heat stress (HS) on genetic parameter estimates, i.e., HS close to the trait recording date, was verified in several previous studies conducted in dairy and beef cattle populations. The aim of the present study was to analyze the impact of time-lagged HS at different recording periods during late pregnancy (a.p.) and postpartum (p.p.) on genetic parameter estimates for birth weight (BWT) and weight gain traits (200 d- and 365 d-weight gain (200dg, 365dg)) in offspring of the dual-purpose cattle breed "Rotes Höhenvieh" (RHV). Furthermore, we estimated genetic correlations within traits across time-lagged climatic indicators, in order to proof possible genotype by environment interactions (G×E). Trait recording included 5,434 observations for BWT, 3,679 observations for 200dg and 2,998 observations for 365dg. Time-lagged climatic descriptors were classes for the mean temperature humidity index (mTHI) and number of HS days (nHS) from the following periods: 7 d-period a.p. (BWT), 56 d-period a.p., and 56 d-period p.p. (200dg and 365dg). Genetic parameters were estimated via 2-trait animal models, i.e., defining the same trait in different climatic environments as different traits. Genetic variances and heritabilities for all traits increased with increasing mTHI- and nHS-classes for all recording periods, indicating pronounced genetic differentiation with regard to time-lagged in utero HS and HS directly after birth. Similarly, in low mTHI- and nHS-classes indicating cold stress, genetic variances, and heritabilities were larger than for temperate climates. Genetic correlations substantially smaller than 0.80 indicating G × E were observed when considering same traits from mTHI- and nHS-classes in greater distance. Estimated breeding values (EBV) of the 10 most influential sires with the largest number of offspring records fluctuated across mTHI- and nHS-classes. Correlations between sire EBV for same traits from distant climatic classes confirmed the genetic correlation estimates. Sires displaying stable EBV with climatic alterations were also identified. Selection of those sires might contribute to improved robustness in the RHV outdoor population genetically.

Meta-analysis of genetic parameters for economic traits in sheep

Very diversified studies estimated genetic parameters in sheep, and reliable estimates that account for the variation between articles can be achieved through a meta-analysis. This study proposed to carry out a meta-analysis to obtain estimates of heritability and genetic correlations for 35 traits, including growth, reproductive, resistance to parasites, wool, and carcass related traits. A total of 191 articles, 505 heritability coefficients, and 356 genetic correlations were evaluated using a random model. The meta-analysis estimated heritability ranging from 0.1213 to 0.3912 for growth traits, from 0.0398 to 0.3047 for reproductive traits, 0.1724 to 0.2582 for resistance to nematodes traits, 0.3616 to 0.5808 for wool traits, and from 0.2063 to 0.3299 for carcass traits. The estimates of genetic correlations were mainly positive and ranged from 0.2500 to 0.9665, except for eggs per gram of feces with body weight (-0.18) and with hematocrit (-0.48). The genetic parameters estimated in the present study can be used in breeding programs under the most different environmental conditions, as they were obtained through many studies with different situations. Thus, these results can support the development of sheep breeding programs, especially in developing and underdeveloped countries, where sheep farming is an important agricultural activity.

Heritability and type B genetic correlation estimates for coastal douglas-fir in the US Pacific Northwest: trends and insights from 906 first-generation and second-cycle tests

ABSTRACT Genetic parameters are reported for coastal Douglas-fir, from measurements on 24,000 first-generation open-pollinated families (786 test sites) and 2,400 second-cycle crosses (120 test sites) over a period of 45 years. The following were estimated: across-site narrow-sense individual heritability (h2 A), narrow-sense family mean heritability (h2 F), and type B genetic correlation (rB), and. narrow-sense single-site heritability (h2 w). The main traits were height, diameter at breast height (dbh), volume index (both cycles), and incidence of stem forking and ramicorn branching, upper stem sinuosity, and second flushing in the leader (second cycle). Smaller datasets were available for progression of budburst, straightness, needle retention, wood specific gravity and acoustic velocity. Measurements were between three and 30 years from planting. The dataset contained at least one trait measured for 2.602 million trees . Heritability (h2 A) estimates for height, dbh, volume and sinuosity ranged from 0.15 to 0.30, with a wider range for h2 w estimates. Heritabilities were higher in the second cycle. Forking and ramicorn branching had good h2 F heritabilities. Second flushing had high h2 A and rB values; the same is often true for AV. Budburst was the most strongly inherited trait. h2 w for height, dbh, volume, forking and ramicorns was correlated with means for those traits.

Genetic Analysis of Persistency for Milk Fat Yield in Iranian Buffaloes (Bubalus bubalis).

This study aimed to estimate heritabilities and genetic trends for different persistency measures for milk fat yield and their genetic correlations with 270-day milk yield in Iranian buffaloes. The records of test-day milk fat yield belonging to the first three lactations of buffaloes within 523 herds consisting of 43,818 records were got from the Animal Breeding Center and Promotion of Animal Products of Iran from 1996 to 2012. To fit the lactation curves based on a random regression test-day model, different orders of Legendre polynomial (LP) functions were selected. Three persistency measures were altered according to the specific condition of the lactation curve in buffaloes: (1) The average of estimated breeding values (EBVs) for test day fat yield from day 226 to day 270 as a deviation from the average of EBVs from day 44 to day 62 (PM1), (2) A summation of contribution for each day from day 53 to day 247 as a deviation from day 248 (PM2), and (3) The difference between EBVs for day 257 and day 80 (PM3). The estimates of heritability for PM1, PM2, and PM3 ranged from 0.20 to 0.48, from 0.36 to 0.47, and from 0.19 to 0.35 over the first three lactations, respectively. The estimate of genetic trends for different persistency measures of milk fat yield was not significant over the lactations (P > 0.05). Genetic correlation estimates between various measures of persistency were generally high over the first three lactations. Also, genetic correlations estimates between persistency measures and 270-day milk yield were mostly low and varied from 0.00 to 0.24 (between PM1 and 270-day milk yield), from −0.19 to 0.13 (between PM2 and 270-day milk yield), and from −0.02 to 0.00 (between PM1 and 270-day milk yield) over the first three lactations, respectively. Persistency measures that showed low genetic correlations with milk fat yield were considered the most suitable measures in selection schemes. Besides, medium to high heritability estimates for different persistency measures for milk fat yield indicated that relevant genetic variations detected for these characters could be regarded in outlining later genetic improvement programs of Iranian buffaloes.

Genomic studies of milk-related traits in water buffalo (Bubalus bubalis) based on single-step genomic best linear unbiased prediction and random regression models

Genomic selection has been widely implemented in many livestock breeding programs, but it remains incipient in buffalo. Therefore, this study aimed to (1) estimate variance components incorporating genomic information in Murrah buffalo; (2) evaluate the performance of genomic prediction for milk-related traits using single- and multitrait random regression models (RRM) and the single-step genomic best linear unbiased prediction approach; and (3) estimate longitudinal SNP effects and candidate genes potentially associated with time-dependent variation in milk, fat, and protein yields, as well as somatic cell score (SCS) in multiple parities. The data used to estimate the genetic parameters consisted of a total of 323,140 test-day records. The average daily heritability estimates were moderate (0.35 ± 0.02 for milk yield, 0.22 ± 0.03 for fat yield, 0.42 ± 0.03 for protein yield, and 0.16 ± 0.03 for SCS). The highest heritability estimates, considering all traits studied, were observed between 20 and 280 d in milk (DIM). The genetic correlation estimates at different DIM among the evaluated traits ranged from -0.10 (156 to 185 DIM for SCS) to 0.61 (36 to 65 DIM for fat yield). In general, direct selection for any of the traits evaluated is expected to result in indirect genetic gains for milk yield, fat yield, and protein yield but also increase SCS at certain lactation stages, which is undesirable. The predicted RRM coefficients were used to derive the genomic estimated breeding values (GEBV) for each time point (from 5 to 305 DIM). In general, the tuning parameters evaluated when constructing the hybrid genomic relationship matrices had a small effect on the GEBV accuracy and a greater effect on the bias estimates. The SNP solutions were back-solved from the GEBV predicted from the Legendre random regression coefficients, which were then used to estimate the longitudinal SNP effects (from 5 to 305 DIM). The daily SNP effect for 3 different lactation stages were performed considering 3 different lactation stages for each trait and parity: from 5 to 70, from 71 to 150, and from 151 to 305 DIM. Important genomic regions related to the analyzed traits and parities that explain more than 0.50% of the total additive genetic variance were selected for further analyses of candidate genes. In general, similar potential candidate genes were found between traits, but our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the traits across parities. These results contribute to a better understanding of the genetic architecture of milk production traits in dairy buffalo and reinforce the relevance of incorporating genomic information to genetically evaluate longitudinal traits in dairy buffalo. Furthermore, the candidate genes identified can be used as target genes in future functional genomics studies.

Evaluation of Genetic Diversity and Estimation of Heritability and Genetic Correlation Using REML for Different Traits in Grass Pea (Lathyrus sativus L.) Genotypes

Evaluation of Genetic Diversity and Estimation of Heritability and Genetic Correlation Using REML for Different Traits in Grass Pea (Lathyrus sativus L.) Genotypes

Genetic parameters for Crassostrea virginica and their application to family-based breeding in the mid-Atlantic, USA

A family-based breeding program was established at the Aquaculture Genetics and Breeding Technology Center (ABC) at the Virginia Institute of Marine Science beginning in 2004. Over the course of developing the program, data were acquired to determine the optimal way to structure the breeding population for the Eastern oyster, Crassostrea virginica, in the Chesapeake Bay estuary, and how best to implement our now-operational ‘industrial breeding’ program. Traits studied were survival, total weight, meat yield, and shell shape and decisions were based on estimates of heritability, genetic correlations, and genotype by environment interaction for these traits. Post-hoc, we examined the effect of genetic groups and genetic trends. Genetic variation was abundant and additive, with no evidence of large non-additive effects. Age: age correlations were high, allowing abbreviated field deployment to assess market qualities as early as possible. Survival at high and low salinity were poorly correlated, meaning the gene processes that control survival at each salinity zone are different, and therefore survival at high and low salinities were treated as separate traits. Total weight (indicator of growth rate) was moderately correlated between salinity zones and, while there was some commonality in genetic control across salinities (with 70% of genes in common), total weight was also treated as a separate trait at high and low salinities. Meat yield and shell shape were highly correlated among sites and can therefore be managed as a single trait across all site types. The mass selected lines from our previous work were used as a source of founders, which allowed genetic gains from those lines to be captured in the family program, thus making family-based selection a continuation of previous efforts rather than a restart. The ABC lines have found wide utility not only in the Chesapeake but also in the mid-Atlantic, defined as Rhode Island to South Carolina, USA. Family-based breeding, using the principles encapsulated in this strategy, would be appropriate as a common approach for contiguous breeding efforts for C. virginica along the east coast of the US from the Northeast to the Gulf coasts.

Genetic relationships between feed efficiency and gut microbiome in pig lines selected for residual feed intake.

This study aimed to evaluate the genetic relationship between faecal microbial composition and five feed efficiency (FE) and production traits, residual feed intake (RFI), feed conversion ratio (FCR), daily feed intake (DFI), average daily gain (ADG) and backfat thickness (BFT). A total of 588 samples from two experimental pig lines developed by divergent selection for RFI were sequenced for the 16 rRNA hypervariable V3‐V4 region. The 75 genera with less than 20% zero values (97% of the counts) and two α‐diversity indexes were analysed. Line comparison of the microbiota traits and estimations of heritability (h2) and genetic correlations (r g) were analysed. A non‐metric multidimensional scaling showed line differences between genera. The α‐diversity indexes were higher in the LRFI line than in the HRFI line (p < .01), with h2 estimates of 0.19 ± 0.08 (Shannon) and 0.12 ± 0.06 (Simpson). Forty‐eight genera had a significant h2 (>0.125). The r g of the α‐diversities indexes with production traits were negative. Some r g of genera belonging to the Lachnospiraceae, Ruminococcaceae, Prevotellaceae, Lactobacillaceae, Streptococcaceae, Rikenellaceae and Desulfovibrionaceae families significantly differed from zero (p < .05) with FE traits, RFI (3), DFI (7) and BFT (11). These results suggest that a sizable part of the variability of the gut microbial community is under genetic control and has genetic relationships with FE, including diversity indicators. It offers promising perspectives for selection for feed efficiency using gut microbiome composition in pigs.

Antagonistic maternal and direct effects of the leptin receptor gene on body weight in pigs.

Maternal effects on offspring growth can impact survival and evolution of natural and domesticated populations. Genetic correlation estimates often support a negative relationship between direct and maternal effects. However, the genetic underpinnings whereby this antagonism operates are unclear. In pigs, sow feeding status and body composition condition piglet development and growth. We hypothesized that variants in genes impacting these traits may be causative of maternal influences that could be antagonistic to the direct effects for piglet growth. A recessive missense mutation (C>T) in the porcine leptin receptor (LEPR) gene (rs709596309) has been identified as the possible causal polymorphism for increased feed intake and fatness. Using data from a Duroc line, we show that the TT sows exerted a negative impact on the body weight of their offspring at the end of the growing period of similar extent to the positive direct effect of the TT genotype over each individual. Thus, TT pigs from TT dams were about as heavy as CC and CT (C–) pigs from C–dams, but TT pigs from C–dams were around 5% heavier than C–pigs from TT dams. In contrast, body composition was only influenced by LEPR direct effects. This antagonism is due to a higher propensity of TT pigs for self-maintenance rather than for offspring investment. We show that TT pigs consumed more feed, favored fatty acid uptake over release, and produced lighter piglets at weaning than their C–counterparts. We conclude that LEPR underlies a transgenerational mechanism for energy distribution that allocates resources to the sow or the offspring according to whether selective pressure is exerted before or after weaning.

Bayesian estimation of the genetic relationship of survival traits from birth to yearling age with birth weight in Guilan sheep.

This study aimed to estimate genetic parameters for cumulative survival traits from birth to yearling age and to estimate their genetic relationship with birth weight in Guilan sheep. The dataset used in this study comprised 41,037 survival records of Guilan lambs born from 496 sires and 10,256 dams, collected by the Guilan Province Agricultural Jihad Organization (in Rasht, Iran) during 1990-2013. The data included complete pedigree information; gender; year, month, and day of death; dam age; year, month, and day of birth; birth type; and birth weight. Cumulative survival traits from birth to yearling age were analyzed using threshold animal models via the Bayesian method. Also, linear-threshold animal models were used to study the genetic relationship between survival at different ages and birth weight. Direct heritability estimates of cumulative survival from birth to 60, 90, 180, 270, and 365days of age were low and equal to 0.17, 0.16, 0.08, 0.04, and 0.04, respectively, and the corresponding maternal heritability estimates were 0.21, 0.18, 0.15, 0.08 and 0.08, respectively. Mean estimates of direct genetic correlations between birth weight and survival traits were medium (from 0.22 to 0.28). To improve the survival traits, more emphasis must be put on the amelioration of the non-genetic factors affecting it. Indirect selection based on traits high genetically correlated with survival could increase the survival rate in Guilan lambs.

Genetic Analysis Of Rabbit Litter Traits At Birth And Weaning

Data on 260 litters were used to provide therefore to estimate the heritability and estimates of heritability, repeatability, genetic and phenotypic correlations for litter traits at birth and at weaning. Breed, sire within breed and doe within sire effects were found to be significant, (P&lt;0.05) for litter size at birth and at weaning and for litter weight at birth and at weaning. Heritability estimates of 0.33±0.08, 0.38±0.02, 0.03±0.02 and 0.16±0.05 were obtained for litter birth weight, litter size at birth, litter size at weaning and litter weaning weight, respectively. Repeatability estimates were found to be generally moderate to high. Genetic and phenotypic correlations were positive and significant (P&lt;0.01). Selection for litter size at birth and litter birth weight are likely to result in improved litter size at weaning and litter weaning weight respectively.

GENETIC ASPECTS OF PREWEANING PERFORMANCE OF NDAMA CATTLE

Records on birth weight (BW), preweaning daily gain (PWG) and weaning weight (WW) of Ndama beef cattle were obtained from the Fashola Livestock Farm in Oyo State of Nigeria between 1954 and 1964 and were analyzed to estimate the phenotypic and genetic parameters of preweaning performances of this breed of cattle. For birth weight, preweaning daily gain and weaning weight respectively heritability was estimated as 0.13 ± 0.08, 0.30 ± 0.14 and 0.25 ± 0.12 from paternal half-sib relationship. The estimates of genetic and phenotypic correlations obtained from these data among the three pre-weaning traits were found to be similar to those already in the general literature on beef cattle.

Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes

Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank (n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data.