Does genetic correlation change across environments for harvest whole weight and its uniformity in the Portuguese oyster (Crassostrea angulata)

Aquaculture ◽  
2021 ◽  
Vol 536 ◽  
pp. 736444
Author(s):  
Sang V. Vu ◽  
Arthur R. Gilmour ◽  
Ngoc T.H. Nguyen ◽  
Michael Dove ◽  
In Van Vu ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Crassostrea Angulata

Genetic and Environmental Influences on Executive Functions and Intelligence in the ABCD Study

2020 ◽  
Author(s):  
Samantha M Freis ◽  
Claire Morrison ◽  
Jeffrey M. Lessem ◽  
John K. Hewitt ◽  
Naomi P. Friedman
Keyword(s):  
Cognitive Development ◽  
Executive Functions ◽  
Genetic Correlation ◽  
Middle Childhood ◽  
Middle Age ◽  
Environmental Influences ◽  
Genetic Correlations ◽  
Twin Studies

Executive functions (EFs) and intelligence (IQ) are phenotypically correlated and heritable; however, they show variable genetic correlations in twin studies spanning childhood to middle age. We analyzed data from over 11,000 children (9-10-year-olds, including 749 twin pairs) in the Adolescent Brain Cognitive Development (ABCD) Study to examine the phenotypic and genetic relations between EFs and IQ in childhood. We identified two EF factors – Common EF and Updating-Specific, which were both related to IQ (rs = .64-.81). Common EF and IQ were heritable (53-67%), and their genetic correlation (rG = .86) was not significantly different than 1. These results suggest that EFs and IQ are phenotypically but not genetically separable in middle childhood.

scholarly journals GENETIC CORRELATION BETWEEN GROWTH RATE AND LITTER SIZE IN MICE

Genetics ◽  
1966 ◽  
Vol 54 (6) ◽  
pp. 1423-1429 ◽  
Author(s):  
G W Rahnefeld ◽  
R E Comstock ◽  
Madho Singh ◽  
S R NaPuket
Keyword(s):  
Growth Rate ◽  
Genetic Correlation ◽  
Litter Size

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

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

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

scholarly journals Prediction Accuracies of Genomic Selection for Nine Commercially Important Traits in the Portuguese Oyster (Crassostrea angulata) Using DArT-Seq Technology

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 210
Author(s):  
Sang V. Vu ◽  
Cedric Gondro ◽  
Ngoc T. H. Nguyen ◽  
Arthur R. Gilmour ◽  
Rick Tearle ◽  
...  
Keyword(s):  
Moisture Content ◽  
Genomic Selection ◽  
Shell Length ◽  
Prediction Accuracy ◽  
Genomic Information ◽  
Morphometric Traits ◽  
Shell Weight ◽  
Shell Width ◽  
Crassostrea Angulata ◽  
Selection For

Genomic selection has been widely used in terrestrial animals but has had limited application in aquaculture due to relatively high genotyping costs. Genomic information has an important role in improving the prediction accuracy of breeding values, especially for traits that are difficult or expensive to measure. The purposes of this study were to (i) further evaluate the use of genomic information to improve prediction accuracies of breeding values from, (ii) compare different prediction methods (BayesA, BayesCπ and GBLUP) on prediction accuracies in our field data, and (iii) investigate the effects of different SNP marker densities on prediction accuracies of traits in the Portuguese oyster (Crassostrea angulata). The traits studied are all of economic importance and included morphometric traits (shell length, shell width, shell depth, shell weight), edibility traits (tenderness, taste, moisture content), and disease traits (Polydora sp. and Marteilioides chungmuensis). A total of 18,849 single nucleotide polymorphisms were obtained from genotyping by sequencing and used to estimate genetic parameters (heritability and genetic correlation) and the prediction accuracy of genomic selection for these traits. Multi-locus mixed model analysis indicated high estimates of heritability for edibility traits; 0.44 for moisture content, 0.59 for taste, and 0.72 for tenderness. The morphometric traits, shell length, shell width, shell depth and shell weight had estimated genomic heritabilities ranging from 0.28 to 0.55. The genomic heritabilities were relatively low for the disease related traits: Polydora sp. prevalence (0.11) and M. chungmuensis (0.10). Genomic correlations between whole weight and other morphometric traits were from moderate to high and positive (0.58–0.90). However, unfavourably positive genomic correlations were observed between whole weight and the disease traits (0.35–0.37). The genomic best linear unbiased prediction method (GBLUP) showed slightly higher accuracy for the traits studied (0.240–0.794) compared with both BayesA and BayesCπ methods but these differences were not significant. In addition, there is a large potential for using low-density SNP markers for genomic selection in this population at a number of 3000 SNPs. Therefore, there is the prospect to improve morphometric, edibility and disease related traits using genomic information in this species.

Blood catalase and haematocrit values in a breeding colony of Dutch-belted rabbits

2001 ◽  
Vol 35 (2) ◽  
pp. 140-146 ◽  
Author(s):  
R. H. Foote ◽  
E. Hare
Keyword(s):  
Genetic Correlation ◽  
Seminal Plasma ◽  
Catalase Activity ◽  
Preliminary Evidence ◽  
Age Effect ◽  
Breeding Colony ◽  
First Report ◽  
Rabbit Blood ◽  
Different Ages ◽  
Males And Females

Rabbit seminal plasma catalase is much higher than in the semen of other mammals, and differences appear to be inherited. Because of the scarcity of information on rabbit blood catalase and haematocrit in Dutch-belted rabbits, an investigation of possible effects of gender, age and genetics on these variables was undertaken. There were 191 rabbits sampled at 2-3 months, 130 at 12 months and 61 at 18-24 months of age. There was no age effect on the haematocrit values and on blood catalase activity. At 12 months of age males had an average haematocrit value of 44% compared with 40% for females ( P < 0.05). Corresponding average catalase values were 431 and 356 units/ml of blood ( P < 0.05). Also catalase was measured in the semen and blood of 34 males, and males differed in both their blood and semen catalase activity ( P < 0.05). The correlation between the two traits was r = 0.44. Heritability ( h2) estimates, based on 231 rabbits were 0.40 for blood catalase activity, and 0.26 for haematocrit. The genetic correlation between the two variables was 0.83 ( P < 0.05). These studies are consistent with the literature in that female rabbits have a slightly lower haematocrit value than males, and this is associated with a lower catalase activity. This appears to be the first report of a study that compares rabbit blood catalase in males and females of different ages. Preliminary evidence that differences may have a heritable basis is consistent with previous studies on rabbit semen catalase.

scholarly journals Selection Response Due to Different Combination of Antagonistic Milk, Beef, and Morphological Traits in the Alpine Grey Cattle Breed

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1340
Author(s):  
Enrico Mancin ◽  
Cristina Sartori ◽  
Nadia Guzzo ◽  
Beniamino Tuliozi ◽  
Roberto Mantovani
Keyword(s):  
Genetic Correlation ◽  
Functional Traits ◽  
Performance Test ◽  
Genetic Relationships ◽  
Selection Index ◽  
Milk Traits ◽  
Linear Type ◽  
Dual Purpose ◽  
Type Traits ◽  
Selection Indexes

Selection in local dual-purpose breeds requires great carefulness because of the need to preserve peculiar traits and also guarantee the positive genetic progress for milk and beef production to maintain economic competitiveness. A specific breeding plan accounting for milk, beef, and functional traits is required by breeders of the Alpine Grey cattle (AG), a local dual-purpose breed of the Italian Alps. Hereditability and genetic correlations among all traits have been analyzed for this purpose. After that, different selection indexes were proposed to identify the most suitable for this breed. Firstly, a genetic parameters analysis was carried out with different datasets. The milk dataset contained 406,918 test day records of milk, protein, and fat yields and somatic cells (expressed as SCS). The beef dataset included performance test data conducted on 749 young bulls. Average daily gain, in vivo estimated carcass yields, and carcass conformation (SEUROP) were the phenotypes obtained from the performance tests. The morphological dataset included 21 linear type evaluations of 11,320 first party cows. Linear type traits were aggregated through factor analysis and three factors were retained, while head typicality (HT) and rear muscularity (RM) were analyzed as single traits. Heritability estimates (h2) for milk traits ranged from 0.125 to 0.219. Analysis of beef traits showed h2 greater than milk traits, ranging from 0.282 to 0.501. Type traits showed a medium value of h2 ranging from 0.238 to 0.374. Regarding genetic correlation, SCS and milk traits were strongly positively correlated. Milk traits had a negative genetic correlation with the factor accounting for udder conformations (−0.40) and with all performance test traits and RM. These latter traits showed also a negative genetic correlation with udder volume (−0.28). The HT and the factor accounting for rear legs traits were not correlated with milk traits, but negatively correlated with beef traits (−0.32 with RM). We argue that the consequence of these results is that the use of the current selection index, which is mainly focused on milk attitude, will lead to a deterioration of all other traits. In this study, we propose more appropriate selection indexes that account for genetic relationships among traits, including functional traits.

scholarly journals Investigating regions of shared genetic variation in attention deficit/hyperactivity disorder and major depressive disorder: a GWAS meta-analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Victoria Powell ◽  
Joanna Martin ◽  
Anita Thapar ◽  
Frances Rice ◽  
Richard J. L. Anney
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Genetic Correlation ◽  
Attention Deficit ◽  
Meta Analysis ◽  
Major Depressive ◽  
Hyperactivity Disorder ◽  
High Level ◽  
Genomic Regions

AbstractAttention deficit/hyperactivity disorder (ADHD) demonstrates a high level of comorbidity with major depressive disorder (MDD). One possible contributor to this is that the two disorders show high genetic correlation. However, the specific regions of the genome that may be responsible for this overlap are unclear. To identify variants associated with both ADHD and MDD, we performed a meta-analysis of GWAS of ADHD and MDD. All genome wide significant (p < 5 × 10–8) SNPs in the meta-analysis that were also strongly associated (p < 5 × 10–4) independently with each disorder were followed up. These putatively pleiotropic SNPs were tested for additional associations across a broad range of phenotypes. Fourteen linkage disequilibrium-independent SNPs were associated with each disorder separately (p < 5 × 10–4) and in the cross-disorder meta-analysis (p < 5 × 10–8). Nine of these SNPs had not been highlighted previously in either individual GWAS. Evidence supported nine of the fourteen SNPs acting as eQTL and two as brain eQTL. Index SNPs and their genomic regions demonstrated associations with other mental health phenotypes. Through conducting meta-analysis on ADHD and MDD only, our results build upon the previously observed genetic correlation between ADHD and MDD and reveal novel genomic regions that may be implicated in this overlap.

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