976 resultados para Genetic correlations
Resumo:
The objective of this study was to evaluate the association of visual scores of body structure, precocity and muscularity with production (body weight at 18 months and average daily gain) and reproductive (scrotal circumference) traits in Brahman cattle in order to determine the possible use of these scores as selection criteria to improve carcass quality. Covariance components were estimated by the restricted maximum likelihood method using an animal model that included contemporary group as fixed effect. A total of 1,116 observations of body structure, precocity and muscularity were used. Heritability was 0.39, 043 and 0.40 for body structure, precocity and muscularity, respectively. The genetic correlations were 0.79 between body structure and precocity, 0.87 between body structure and muscularity, and 0.91 between precocity and muscularity. The genetic correlations between visual scores and body weight at 18 months were positive (0.77, 0.57 and 0.59 for body structure, precocity and muscularity, respectively). Similar genetic correlations were observed between average daily gain and visual scores (0.60, 0.57 and 0.48, respectively), whereas the genetic correlations between scrotal circumference and these scores were low (0.13, 0.02, and 0.13). The results indicate that visual scores can be used as selection criteria in Brahman breeding programs. Favorable correlated responses should be seen in average daily gain and body weight at 18 months. However, no correlated response is expected for scrotal circumference.
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Forage peanut improvement for use in grass?legume mixtures is expected to have a great impact on the sustainability of Brazilian livestock production. Eighteen cloned Arachis spp. ecotypes were evaluated under clipping in a Brazilian Cerrado region and results analysed using a mixed model methodology. The objective was to estimate genetic and phenotypic parameters and to select the best ecotypes based on selection index applied on their predicted genotypic value. The traits of total dry-matter (DM) and leaf DM yield presented moderate (0_30 < h2g < 0_50) to high (>0_50) broad-sense heritability, in contrast to the low genetic variability in nutritional quality-associated traits. Ecotypes of Arachis spp. contained average crude protein concentrations of 224 g kg _1 DM in leaves and 138 g kg _1 DM in stems, supporting the potential role of these species to overcome the low protein content in Cerrado pastures. The correlations between yield traits and traits associated with low nutritional value in leaves were consistently significant and positive. Genetic correlations among all the yield traits evaluated during the rainy or dry seasons were significant and positive. The ecotypes were ranked based on selection index. The next step is to validate long-term selection of grass?Arachis in combination with pastures under competition and adjusted grazing in the Cerrado region.
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Correlation between genetic parameters and factors such as backfat thickness (BFT), rib eye area (REA), and body weight (BW) were estimated for Canchim beef cattle raised in natural pastures of Brazil. Data from 1648 animals were analyzed using multi-trait (BFT, REA, and BW) animal models by the Bayesian approach. This model included the effects of contemporary group, age, and individual heterozygosity as covariates. In addition, direct additive genetic and random residual effects were also analyzed. Heritability estimated for BFT (0.16), REA (0.50), and BW (0.44) indicated their potential for genetic improvements and response to selection processes. Furthermore, genetic correlations between BW and the remaining traits were high (P > 0.50), suggesting that selection for BW could improve REA and BFT. On the other hand, genetic correlation between BFT and REA was low (P = 0.39 ± 0.17), and included considerable variations, suggesting that these traits can be jointly included as selection criteria without influencing each other. We found that REA and BFT responded to the selection processes, as measured by ultrasound. Therefore, selection for yearling weight results in changes in REA and BFT.
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A major challenge in neuroscience is finding which genes affect brain integrity, connectivity, and intellectual function. Discovering influential genes holds vast promise for neuroscience, but typical genome-wide searches assess approximately one million genetic variants one-by-one, leading to intractable false positive rates, even with vast samples of subjects. Even more intractable is the question of which genes interact and how they work together to affect brain connectivity. Here, we report a novel approach that discovers which genes contribute to brain wiring and fiber integrity at all pairs of points in a brain scan. We studied genetic correlations between thousands of points in human brain images from 472 twins and their nontwin siblings (mean age: 23.7 2.1 SD years; 193 male/279 female).Wecombined clustering with genome-wide scanning to find brain systems withcommongenetic determination.Wethen filtered the image in a new way to boost power to find causal genes. Using network analysis, we found a network of genes that affect brain wiring in healthy young adults. Our new strategy makes it computationally more tractable to discover genes that affect brain integrity. The gene network showed small-world and scale-free topologies, suggesting efficiency in genetic interactions and resilience to network disruption. Genetic variants at hubs of the network influence intellectual performance by modulating associations between performance intelligence quotient and the integrity of major white matter tracts, such as the callosal genu and splenium, cingulum, optic radiations, and the superior longitudinal fasciculus.
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Head motion (HM) is a critical confounding factor in functional MRI. Here we investigate whether HM during resting state functional MRI (RS-fMRI) is influenced by genetic factors in a sample of 462 twins (65% fema≤ 101 MZ (monozygotic) and 130 DZ (dizygotic) twin pairs; mean age: 21 (SD=3.16), range 16-29). Heritability estimates for three HM components-mean translation (MT), maximum translation (MAXT) and mean rotation (MR)-ranged from 37 to 51%. We detected a significant common genetic influence on HM variability, with about two-thirds (genetic correlations range 0.76-1.00) of the variance shared between MR, MT and MAXT. A composite metric (HM-PC1), which aggregated these three, was also moderately heritable (h2=42%). Using a sub-sample (N=35) of the twins we confirmed that mean and maximum translational and rotational motions were consistent "traits" over repeated scans (r=0.53-0.59); reliability was even higher for the composite metric (r=0.66). In addition, phenotypic and cross-trait cross-twin correlations between HM and resting state functional connectivities (RS-FCs) with Brodmann areas (BA) 44 and 45, in which RS-FCs were found to be moderately heritable (BA44: h2-=0.23 (sd=0.041), BA45: h2-=0.26 (sd=0.061)), indicated that HM might not represent a major bias in genetic studies using FCs. Even so, the HM effect on FC was not completely eliminated after regression. HM may be a valuable endophenotype whose relationship with brain disorders remains to be elucidated.
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Large multisite efforts (e.g., the ENIGMA Consortium), have shown that neuroimaging traits including tract integrity (from DTI fractional anisotropy, FA) and subcortical volumes (from T1-weighted scans) are highly heritable and promising phenotypes for discovering genetic variants associated with brain structure. However, genetic correlations (rg) among measures from these different modalities for mapping the human genome to the brain remain unknown. Discovering these correlations can help map genetic and neuroanatomical pathways implicated in development and inherited risk for disease. We use structural equation models and a twin design to find rg between pairs of phenotypes extracted from DTI and MRI scans. When controlling for intracranial volume, the caudate as well as related measures from the limbic system - hippocampal volume - showed high rg with the cingulum FA. Using an unrelated sample and a Seemingly Unrelated Regression model for bivariate analysis of this connection, we show that a multivariate GWAS approach may be more promising for genetic discovery than a univariate approach applied to each trait separately.
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We used diffusion tensor magnetic resonance imaging (DTI) to reveal the extent of genetic effects on brain fiber microstructure, based on tensor-derived measures, in 22 pairs of monozygotic (MZ) twins and 23 pairs of dizygotic (DZ) twins (90 scans). After Log-Euclidean denoising to remove rank-deficient tensors, DTI volumes were fluidly registered by high-dimensional mapping of co-registered MP-RAGE scans to a geometrically-centered mean neuroanatomical template. After tensor reorientation using the strain of the 3D fluid transformation, we computed two widely used scalar measures of fiber integrity: fractional anisotropy (FA), and geodesic anisotropy (GA), which measures the geodesic distance between tensors in the symmetric positive-definite tensor manifold. Spatial maps of intraclass correlations (r) between MZ and DZ twins were compared to compute maps of Falconer's heritability statistics, i.e. the proportion of population variance explainable by genetic differences among individuals. Cumulative distribution plots (CDF) of effect sizes showed that the manifold measure, GA, comparably the Euclidean measure, FA, in detecting genetic correlations. While maps were relatively noisy, the CDFs showed promise for detecting genetic influences on brain fiber integrity as the current sample expands.
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Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment This fraction is the result of undesirable genotype-by-environment interactions (G x E) and measured by the genetic correlation (r(g)) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of G x E over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels
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Quantitative trait loci (QTL) detection was carried out for adventitious rooting and associated propagation traits in a second-generation outbred Corymbia torelliana x Corymbia citriodora subspecies variegata hybrid family (n=186). The parental species of this cross are divergent in their capacity to develop roots adventitiously on stem cuttings and their propensity to form lignotubers. For the ten traits studied, there was one or two QTL detected, with some QTL explaining large amounts of phenotypic variation (e.g. 66% for one QTL for percentage rooting), suggesting that major effects influence rooting in this cross. Collocation of QTL for many strongly genetically correlated rooting traits to a single region on linkage group 12 suggested pleiotropy. A three locus model was most parsimonious for linkage group 12, however, as differences in QTL position and lower genetic correlations suggested separate loci for each of the traits of shoot production and root initiation. Species differences were thought to be the major source of phenotypic variation for some rooting rate and root quality traits because of the major QTL effects and up to 59-fold larger homospecific deviations (attributed to species differences) relative to heterospecific deviations (attributed to standing variation within species) evident at some QTL for these traits. A large homospecific/heterospecific ratio at major QTL suggested that the gene action evident in one cross may be indicative of gene action more broadly in hybrids between these species for some traits.
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A restricted maximum likelihood analysis applied to an animal model showed no significant differences (P > 0.05) in pH value of the longissimus dorsi measured at 24 h post-mortem (pH24) between high and low lines of Large White pigs selected over 4 years for post-weaning growth rate on restricted feeding. Genetic and phenotypic correlations between pH24 and production and carcass traits were estimated using all performance testing records combined with the pH24 measurements (5.05-7.02) on slaughtered animals. The estimate of heritability for pH24 was moderate (0.29 ± 0.18). Genetic correlations between pH24 and production or carcass composition traits, except for ultrasonic backfat (UBF), were not significantly different from zero. UBF had a moderate, positive genetic correlation with pH24 (0.24 ± 0.33). These estimates of genetic correlations affirmed that selection for increased growth rate on restricted feeding is likely to result in limited changes in pH24 and pork quality since the selection does not put a high emphasis on reduced fatness.
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The tropical abalone Haliotis asinina is a wild-caught and cultured species throughout the Indo-Pacific as well as being an emerging model species for the study of haliotids. H. asinina has the fastest recorded natural growth rate of any abalone and reaches sexual maturity within one year. As such, it is a suitable abalone species for selective breeding for commercially important traits such as rapid growth. Estimating the amount of variation in size that is attributable to heritable genetic differences can assist the development of such a selective breeding program. Here we estimated heritability for growth-related traits at 12 months of age by creating a single cohort of 84 families in a full-factorial mating design consisting of 14 sires and 6 dams. Of 500 progeny sampled, 465 were successfully assigned to their parents based on shared alleles at 5 polymorphic microsatellite loci. Using an animal model, heritability estimates were 0.48 ± 0.15 for shell length, 0.38 ± 0.13 for shell width and 0.36 ± 0.13 for weight. Genetic correlations were > 0.98 between shell parameters and weight, indicating that breeding for weight gains could be successfully achieved by selecting for shell length.
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Fibre diameter can vary dramatically along a wool staple, especially in the Mediterranean environment of southern Australia with its dry summers and abundance of green feed in spring. Other research results have shown a very low phenotypic correlation between fibre diameter grown between seasons. Many breeders use short staples to measure fibre diameter for breeding purposes and also to promote animals for sale. The effectiveness of this practice is determined by the relative response to selection by measuring fibre traits on a full 12 months wool staple as compared to measuring them only on part of a staple. If a high genetic correlation exists between the part record and the full record, then using part records may be acceptable to identify genetically superior animals. No information is available on the effectiveness of part records. This paper investigated whether wool growth and fibre diameter traits of Merino wool grown at different times of the year in a Mediterranean environment, are genetically the same trait, respectively. The work was carried out on about 7 dyebanded wool sections/animal.year, on ewes from weaning to hogget age, in the Katanning Merino resource flocks over 6 years. Relative clean wool growth of the different sections had very low heritability estimates of less than 0.10, and they were phenotypically and genetically poorly correlated with 6 or 12 months wool growth. This indicates that part record measurement of clean wool growth of these sections will be ineffective as indirect selection criteria to improve wool growth genetically. Staple length growth as measured by the length between dyebands, would be more effective with heritability estimates of between 0.20 and 0.30. However, these measurements were shown to have a low genetic correlation with wool grown for 12 months which implies that these staple length measurements would only be half as efficient as the wool weight for 6 or 12 months to improve total clean wool weight. Heritability estimates of fibre diameter, coefficient of variation of fibre diameter and fibre curvature were relatively high and were genetically and phenotypically highly correlated across sections. High positive phenotypic and genetic correlations were also found between fibre diameter, coefficient of variation of fibre diameter and fibre curvature of the different sections and similar measurements for wool grown over 6 or 12 months. Coefficient of variation of fibre diameter of the sections also had a moderate negative phenotypic and genetic correlation with staple strength of wool staples grown over 6 months indicating that coefficient of variation of fibre diameter of any section would be as good an indirect selection criterion to improve stable strength as coefficient of variation of fibre diameter for wool grown over 6 or 12 months. The results indicate that fibre diameter, coefficient of variation of fibre diameter and fibre curvature of wool grown over short periods of time have virtually the same heritability as that of wool grown over 12 months, and that the genetic correlation between fibre diameter, coefficient of variation of fibre diameter and fibre curvature on part and on full records is very high (rg > 0.85). This indicates that fibre diameter, coefficient of variation of fibre diameter and fibre curvature on part records can be used as selection criteria to improve these traits. However, part records of greasy and clean wool growth would be much less efficient than fleece weight for wool grown over 6 or 12 months because of the low heritability of part records and the low genetic correlation between these traits on part records and on wool grown for 12 months.
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The genetics of heifer performance in tropical 'wet' and 'dry' seasons, and relationships with steer performance, were studied in Brahman (BRAH) and Tropical Composite (TCOMP) (50% Bos indicus, African Sanga or other tropically adapted Bos taurus; 50% non-tropically adapted Bos taurus) cattle of northern Australia. Data were from 2159 heifers (1027 BRAH, 1132 TCOMP), representing 54 BRAH and 51 TCOMP sires. Heifers were assessed after post-weaning 'wet' (ENDWET) and 'dry' (ENDDRY) seasons. Steers were assessed post-weaning, at feedlot entry, over a 70-day feed test, and after similar to 120-day finishing. Measures studied in both heifers and steers were liveweight (LWT), scanned rump fat, rib fat and M. longissimus area (SEMA), body condition score (CS), hip height (HH), serum insulin-like growth factor-I concentration (IGF-I), and average daily gains (ADG). Additional steer measures were scanned intra-muscular fat%, flight time, and daily (DFI) and residual feed intake (RFI). Uni- and bivariate analyses were conducted for combined genotypes and for individual genotypes. Genotype means were predicted for a subset of data involving 34 BRAH and 26 TCOMP sires. A meta-analysis of genetic correlation estimates examined how these were related to the difference between measurement environments for specific traits. There were genotype differences at the level of means, variances and genetic correlations. BRAH heifers were significantly (P < 0.05) faster-growing in the 'wet' season, slower-growing in the 'dry' season, lighter at ENDDRY, and taller and fatter with greater CS and IGF-I at both ENDWET and ENDDRY. Heritabilities were generally in the 20 to 60% range for both genotypes. Phenotypic and genetic variances, and genetic correlations, were commonly lower for BRAH. Differences were often explained by the long period of tropical adaptation of B. indicus. Genetic correlations were high between corresponding measures at ENDWET and ENDDRY, positive between fat and muscle measures in TCOMP but negative in BRAH (mean of 13 estimates 0.50 and -0.19, respectively), and approximately zero between steer feedlot ADG and heifer ADG in BRAH. Numerous genetic correlations between heifers and steers differed substantially from unity, especially in BRAH, suggesting there may be scope to select differently in the sexes where that would aid the differing roles of heifers and steers in production. Genetic correlations declined as measurement environments became more different, the rates of decline (environment sensitivity) sometimes differing with genotype. Similar measures (LWT, HH and ADG; IGF-I at ENDWET in TCOMP) were genetically correlated with steer DFI in heifers as in steers. Heifer SEMA was genetically correlated with steer feedlot RFI in BRAH (0.75 +/- 0.27 at ENDWET, 0.66 +/- 0.24 at ENDDRY). Selection to reduce steer RFI would reduce SEMA in BRAH heifers but otherwise have only small effects on heifers before their first joining.
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A total of 2115 heifers from two tropical genotypes (1007 Brahman and 1108 Tropical Composite) raised in four locations in northern Australia were ovarian-scanned every 4-6 weeks to determine the age at the first-observed corpus luteum (CL) and this was used to de. ne the age at puberty for each heifer. Other traits recorded at each time of ovarian scanning were liveweight, fat depths and body condition score. Reproductive tract size was measured close to the start of the first joining period. Results showed significant effects of location and birth month on the age at first CL and associated puberty traits. Genotypes did not differ significantly for the age or weight at first CL; however, Brahman were fatter at first CL and had a small reproductive tract size compared with that of Tropical Composite. Genetic analyses estimated the age at first CL to be moderately to highly heritable for Brahman (0.57) and Tropical Composite (0.52). The associated traits were also moderately heritable, except for reproductive tract size in Brahmans (0.03) and for Tropical Composite, the presence of an observed CL on the scanning day closest to the start of joining (0.07). Genetic correlations among puberty traits were mostly moderate to high and generally larger in magnitude for Brahman than for Tropical Composite. Genetic correlations between the age at CL and heifer- and steer-production traits showed important genotype differences. For Tropical Composite, the age at CL was negatively correlated with the heifer growth rate in their first postweaning wet season (-0.40) and carcass marbling score (-0.49), but was positively correlated with carcass P8 fat depth (0.43). For Brahman, the age at CL was moderately negatively genetically correlated with heifer measures of bodyweight, fatness, body condition score and IGF-I, in both their first postweaning wet and second dry seasons, but was positively correlated with the dry-season growth rate. For Brahman, genetic correlations between the age at CL and steer traits showed possible antagonisms with feedlot residual feed intake (-0.60) and meat colour (0.73). Selection can be used to change the heifer age at puberty in both genotypes, with few major antagonisms with steer- and heifer- production traits.
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The Juvenile Wood Initiative (JWI) project has been running successfully since July 2003 under a Research Agreement with FWPA and Letters of Association with the consortium partners STBA (Southern Tree Breeding Association), ArborGen and FPQ (Forestry Plantations Queensland). Over the last five and half years, JWI scientists in CSIRO, FPQ, and STBA have completed all 12 major milestones and 28 component milestones according to the project schedule. We have made benchmark progress in understanding the genetic control of wood formation and interrelationships among wood traits. The project has made 15 primary scientific findings and several results have been adopted by industry as summarized below. This progress was detailed in 10 technical reports to funding organizations and industry clients. Team scientists produced 16 scientific manuscripts (8 published, 1 in press, 2 submitted, and several others in the process of submission) and 15 conference papers or presentations. Primary Scientific Findings. The 15 major scientific findings related to wood science, inheritance and the genetic basis of juvenile wood traits are: 1. An optimal method to predict stiffness of standing trees in slash/Caribbean pine is to combine gravimetric basic density from 12 mm increment cores with a standing tree prediction of MoE using a time of flight acoustic tool. This was the most accurate and cheapest way to rank trees for breeding selection for slash/Caribbean hybrid pine. This method was also recommended for radiata pine. 2. Wood density breeding values were predicted for the first time in the STBA breeding population using a large sample of 7,078 trees (increment cores) and it was estimated that selection of the best 250 trees for deployment will produce wood density gains of 12.4%. 3. Large genetic variation for a suite of wood quality traits including density, MFA, spiral grain, shrinkage, acoustic and non-acoustic stiffness (MoE) for clear wood and standing trees were observed. Genetic gains of between 8 and 49% were predicted for these wood quality traits with selection intensity between 1 to 10% for radiata pine. 4. Site had a major effect on juvenile-mature wood transition age and the effect of selective breeding for a shorter juvenile wood formation phase was only moderate (about 10% genetic gain with 10% selection intensity, equivalent to about 2 years reduction of juvenile wood). 5. The study found no usable site by genotype interactions for the wood quality traits of density, MFA and MoE for both radiata and slash/Caribbean pines, suggesting that assessment of wood properties on one or two sites will provide reliable estimates of the genetic worth of individuals for use in future breeding. 6. There were significant and sizable genotype by environment interactions between the mainland and Tasmanian regions and within Tasmania for DBH and branch size. 7. Strong genetic correlations between rings for density, MFA and MoE for both radiata and slash/Caribbean pines were observed. This suggests that selection for improved wood properties in the innermost rings would also result in improvement of wood properties in the subsequent rings, as well as improved average performance of the entire core. 8. Strong genetic correlations between pure species and hybrid performance for each of the wood quality traits were observed in the hybrid pines. Parental performance can be used to identify the hybrid families which are most likely to have superior juvenile wood properties of the slash/Caribbean F1 hybrid in southeast Queensland. 9. Large unfavourable genetic correlations between growth and wood quality traits were a prominent feature in radiata pine, indicating that overcoming this unfavourable genetic correlation will be a major technical issue in progressing radiata pine breeding. 10. The project created the first radiata pine 18 k cDNA microarray and generated 5,952 radiata pine xylogenesis expressed sequence tags (ESTs) which assembled into 3,304 unigenes. 11. A total of 348 genes were identified as preferentially expressed genes in earlywood or latewood while a total of 168 genes were identified as preferentially expressed genes in either juvenile or mature wood. 12. Juvenile earlywood has a distinct transcriptome relative to other stages of wood development. 13. Discovered rapid decay of linkage disequilibrium (LD) in radiata pine with LD decaying to approximately 50% within 1,700 base pairs (within a typical gene). A total of 913 SNPS from sequencing 177,380 base pairs were identified for association genetic studies. 14. 149 SNPs from 44 genes and 255 SNPs from a further 51 genes (total 95 genes) were selected for association analysis with 62 wood traits, and 30 SNPs were shortlisted for their significant association with variation of wood quality traits (density, MFA and MoE) with individual significant SNPs accounting for between 1.9 and 9.7% of the total genetic variation in traits. 15. Index selection using breeding objectives was the most profitable selection method for radiata pine, but in the long term it may not be the most effective in dealing with negative genetic correlations between wood volume and quality traits. A combination of economic and biological approaches may be needed to deal with the strong adverse correlation.