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At least 307 records · Page 17Linked to original sources
PubMed1999

Genotypic expression at different ages: I. Prolificacy traits of sheep.

Genetic parameters for prolificacy traits for Columbia (COLU), Polypay (POLY), Rambouillet (RAMB), and Targhee (TARG) breeds of sheep were estimated with REML using animal models. Traits were number of live births (LAB), litter size at birth (LSB) and weaning (LSW), and litter weight weaned (LWW). Numbers of observations ranged from 5,140 to 7,095 for prolificacy traits and from 5,101 to 8,973 for litter weight weaned for the four breeds. For single-trait analyses, ewes were classified as young (1 yr old), middle-aged (2 and 3 yr old), or older (> 3 yr old). After single-trait analyses, three-trait analyses were done for each characteristic with traits defined by age class. Generally, heritability estimates from single-trait analyses were low and ranged from .01 to .17 for LAB and LSB and from .00 to .10 for LSW. Heritability estimates obtained for LWW ranged from low to moderate (.00 to .25) and were less for older ewes. Heritability estimates from the three-trait analyses were generally similar to estimates from single-trait analyses. Heritabilities for LAB and LSB were similar, and, for three-trait analyses, they ranged across age groups from .07 to .13 for COLU, .13 to .16 for POLY, .10 to .16 for RAMB, and .01 to .16 for TARG. Estimates for LSW from three-trait analyses ranged from .07 to .12 for COLU, .04 to .09 for POLY, .01 to .11 for RAMB, and .03 to .11 for TARG. For LWW, heritabilities ranged from .00 to .21 for COLU, .05 to .08 for POLY, .12 to .15 for RAMB, and .18 to .29 for TARG. Genetic correlations for LAB, LSB and LSW among age-defined traits ranged from .25 to 1.00. Genetic correlations for LAB and LSB between young and middle and between young and older age classes were less than .80 in COLU, POLY, and RAMB breeds. Only genetic correlations between middle and older age classes for these breeds were greater than .80. For TARG, genetic correlations among all age classes were greater than .80 (.88 to 1.00) for those traits. All genetic correlations among ages for LSW were greater than .80 for POLY and TARG. For RAMB, only the correlation between young and older age classes for LSW was less than .80 (.45). None was greater than .80 for COLU. For LWW, genetic correlations among all age classes in POLY and RAMB were greater than .80 (.82 to 1.00). For COLU, genetic correlation between young and middle was low (.07), between young and older was high (.88), and between middle and older classes was moderately high (.54). For TARG, genetic correlations were .49, .65, and .98 for young-middle, young-older, and middle-older age classes, respectively. Results indicate that more progress could be made in selection programs for prolificacy traits in some sheep breeds by considering age of ewe as a part of the trait rather than by simply adjusting for ages of ewes.

Aging↗
PubMed2004

Whole genome scan to detect chromosomal regions affecting multiple traits in dairy cattle.

Chromosomal regions affecting multiple traits (multiple trait quantitative trait regions or MQR) in dairy cattle were detected using a method based on results from single trait analyses to detect quantitative trait loci (QTL). The covariance between contrasts for different traits in single trait regression analysis was computed. A chromosomal region was considered an MQR when the observed covariance between contrasts deviated from the expected covariance under the null hypothesis of no pleiotropy or close linkage. The expected covariance and the confidence interval for the expected covariance were determined by permutation of the data. Four categories of traits were analyzed: production (5 traits), udder conformation (6 traits), udder health (2 traits), and fertility (2 traits). The analysis of a granddaughter design involving 833 sons of 20 grandsires resulted in 59 MQR (alpha = 0.01, chromosomewise). Fifteen MQR were found on Bos taurus autosome (BTA) 14. Four or more MQR were found on BTA 6, 13, 19, 22, 23, and 25. Eight MQR involving udder conformation and udder health and 4 MQR involving production traits and udder health were found. Five MQR were identified for combinations of fertility and udder conformation traits, and another 5 MQR were identified for combinations of fertility and production traits. For 22 MQR, the difference between the correlation attributable to the MQR and the overall genetic correlation was >0.60. Although the false discovery rate was relatively high (0.52), it was considered important to present these results to assess potential consequences of using these MQR for marker-assisted selection.

Animals↗
PubMed2005

Epistatic pleiotropy and the genetic architecture of covariation within early and late-developing skull trait complexes in mice.

The role of epistasis as a source of trait variation is well established, but its role as a source of covariation among traits (i.e., as a source of "epistatic pleiotropy") is rarely considered. In this study we examine the relative importance of epistatic pleiotropy in producing covariation within early and late-developing skull trait complexes in a population of mice derived from an intercross of the Large and Small inbred strains. Significant epistasis was found for several pairwise combinations of the 21 quantitative trait loci (QTL) affecting early developing traits and among the 20 QTL affecting late-developing traits. The majority of the epistatic effects were restricted to single traits but epistatic pleiotropy still contributed significantly to covariances. Because of their proportionally larger effects on variances than on covariances, epistatic effects tended to reduce within-group correlations of traits and reduce their overall degree of integration. The expected contributions of single-locus and two-locus epistatic pleiotropic QTL effects to the genetic covariance between traits were analyzed using a two-locus population genetic model. The model demonstrates that, for single-locus or epistatic pleiotropy to contribute to trait covariances in the study population, both traits must show the same pattern of single-locus or epistatic effects. As a result, a large number of the cases where loci show pleiotropic effects do not contribute to the covariance between traits in this population because the loci show a different pattern of effect on the different traits. In general, covariance patterns produced by single-locus and epistatic pleiotropy predicted by the model agreed well with actual values calculated from the QTL analysis. Nearly all single-locus and epistatic pleiotropic effects contributed positive components to covariances between traits, suggesting that genetic integration in the skull is achieved by a complex combination of pleiotropic effects.

Age Factors↗
PubMed2005

Estimates of genetic parameters for Canadian Holstein female reproduction traits.

Age at first insemination, days from calving to first insemination, number of services, first-service nonreturn rate to 56 d, days from first service to conception, calving ease, stillbirth, gestation length, and calf size of Canadian Holstein cows were jointly analyzed in a linear multiple-trait model. Traits covered a wide spectrum of aspects related to reproductive performance of dairy cows. Other frequently used fertility characteristics, like days open or calving intervals, could easily be derived from the analyzed traits. Data included 94,250 records in parities 1 to 6 on 53,158 cows from Ontario and Quebec, born in the years 1997 to 2002. Reproductive characteristics of heifers and cows were treated as different but genetically correlated traits that gave 16 total traits in the analysis. Repeated records for later parities were modeled with permanent environmental effects. Direct and maternal genetic effects were included in linear models for traits related to calving performance. Bayesian methods with Gibbs sampling were used to estimate covariance components of the model and respective genetic parameters. Estimates of heritabilities for fertility traits were low, from 3% for nonreturn rate in heifers to 13% for age at first service. Interval traits had higher heritabilities than binary or categorical traits. Service sire, sire of calf, and artificial insemination technician were important (relative to additive genetic) sources of variation for nonreturn rate and traits related to calving performance. Fertility traits in heifers and older cows were not the same genetically (genetic correlations in general were smaller than 0.9). Genetic correlations (both direct and maternal) among traits indicated that different traits measured different aspects of reproductive performance of a dairy cow. These traits could be used jointly in a fertility index to allow for selection for better fertility of dairy cattle.

Animals↗
PubMed1979

Relationships between non-metric skeletal traits and cranial size and shape.

A long-standing controversy exists about the comparative utility of metric and non-metric traits as biological indicators in population studies. We hypothesize that the underlying scale which determines the presence or absence of a cranial non-metric trait is an expression of general and/or local size variation in the cranium. Therefore metric and non-metric traits will share a common developmental determination. The hypothesis implies that the underlying scale of a non-metric trait will be correlated with measures of cranial size and shape. Forty-eight cranial metric and twenty-five cranial non-metric traits were scored on the left side of adult male crania from four North American Indian populations. New threshold traits were generated for each non-metric trait by dichotomizing discriminant scores produced by discriminant function analysis. The discriminant analysis was performed using metric traits to discriminate between groups formed by non-metric trait presence or absence. Every non-metric trait tested was significantly correlated with its threshold trait in at least one population. The correlations were of moderate to high levels depending on the trait and population sample studied. This implies that metric and non-metric traits share a moderate to high degree of developmental determination. The cause of these correlations may lie in the common effects that growth and development of the soft tissue and functional spaces of the cranium exert on both metric and non-metric traits.

Cephalometry↗
PubMed2006

Phenotypic study on total and partial lifetime traits for dairy ewes.

A data file on 36,396 lactations was used to determine the strength of the phenotypic relationship between productive, reproductive and lifespan traits for 7935 Spanish Churra ewes. These ewes first lambed between 1989 and 1997 and belonged to 23 flocks. The study took into account four lifespan traits (lifetime, productive life, useful life and lifetime score), three productive traits (total milk yield produced during lifetime, lambs weaned during ewe lifetime and total revenues from sold milk and weaned lambs during lifetime) and two reproductive traits (age at first lambing and mean interval between successive lambings). Moreover, milk yield and revenues from sold milk and weaned lambs were calculated per day of lifetime, productive life and useful life. Partial lifespan traits were considered for the first three parities. The model included flock, birth year within flock and season of birth of the ewe as fixed effects. The first two effects contributed significantly to variation in all traits, while season significantly affected lifespan traits, productive traits and age at first lambing. Milk production level was added to the model for lifespan traits only. It significantly contributed to explaining the variation in all lifespan traits with high percentage of variance explained averaging 14.91%. Lifetime averaged 2324 d. Productive life accounted for 57% of lifetime while useful life represented 50% of productive life. Age at first lambing averaged 622 d and average days dry during lifetime was 560. During lifetime, ewes gave an average of 4.6 parities, 6.5 weaned lambs and 636 l of milk. Average revenue from milk and lambs during lifetime was 673 euros. Milk/day of lifetime, productive life and useful life averaged 0.26, 0.51 and 0.93 l, respectively. The corresponding per-day revenues from sold milk and weaned lambs were, 0.27 euros, 0.55 euros and 1.01 euros, respectively. Lifespan and productive traits had strong relationships (rp among these traits ranged between 0.75 and 0.95). Two-parity and three-parity per-day milk yield had moderately high correlation (0.70-0.83) with total lifetime per-day milk yield traits. Therefore, good use of these traits would be helpful in determining best individuals early in life.

Analysis of Variance↗
PubMed1999

"Quasi-REML" correlation estimates between production and health traits in the presence of selection and confounding: a simulation study.

Performance of the "quasi-REML" method for estimating correlations between a continuous trait and a categorical trait, and between two categorical traits, was studied with Monte Carlo simulations. Three continuous, correlated traits were simulated for identical populations and three scenarios with either no selection, selection for one moderately heritable trait (Trait 1, h2 = .25), and selection for the same trait plus confounding between sires and management groups. The "true" environmental correlations between Traits 2 (h2 = .10) and 3 (h2 = .05) were always of the same absolute size (.20), but further data scenarios were generated by setting the sign of environmental correlation to either positive or negative. Observations for Traits 2 and 3 were then reassigned to binomial categories to simulate health or reproductive traits with incidences of 15 and 5%, respectively. Genetic correlations (r(g12), r(g13), and r(g23) and environmental correlations (r(e12), r(e13), and r(e23)) were estimated for the underlying continuous scale (REML) and the visible categorical scales ("quasi-REML") with linear multiple-trait sire and animal models. Contrary to theory, practically all "quasi-REML" genetic correlations were underestimated to some extent with the sire and animal models. Selection inflated this negative bias for sire model estimates, and the sign of r(e23) noticeably affected r(g23) estimates for the animal model, with greater bias and SD for estimates when the "true" r(e23) was positive. Transformed "quasi-REML" environmental correlations between a continuous and a categorical trait were estimated with good efficiency and little bias, and corresponding correlations between two categorical traits were systematically overestimated. Confounding between sires and contemporary groups negatively affected all correlation estimates on the underlying and the visible scales, especially for sire model "quasi-REML" estimates of genetic correlation. Selection, data structure, and the (co)variance structure influences how well correlations involving categorical traits are estimated with "quasi-REML" methods.

Animal Husbandry↗
PubMed2000

Genetic parameters among weight, prolificacy, and wool traits of Columbia, Polypay, Rambouillet, and Targhee sheep.

Genetic parameters for Columbia, Polypay, Rambouillet, and Targhee sheep were estimated using REML with animal models for prolificacy, weight, and wool traits. All bivariate analyses included a covariance between additive genetic effects for the two traits plus appropriate additional covariances. Number of observations by breed ranged from 5,140 to 7,095 for prolificacy traits, from 7,750 to 9,530 for weight traits, and from 4,603 to 34,746 for wool traits. Heritability estimates ranged from .03 to .11 for prolificacy traits (litter size at birth and litter size at weaning), from .09 to .26 for weight traits (birth weight and average daily gain), and from .25 to .53 for wool traits (fleece weight, fleece grade and staple length). Estimates of direct genetic correlations among prolificacy and among weight traits were positive and ranged from .58 to 1.00 and .18 to 1.00, respectively. Estimates of direct genetic correlation between fleece weight and staple length were positive (.50 to .70) but were negative between fleece weight and fleece grade (-.60 to -.34) and between staple length and fleece grade (-.72 and -.40). Prolificacy and wool traits were essentially uncorrelated. Weight and prolificacy traits were slightly positively correlated. Weight traits had a moderate positive direct genetic correlation with fleece weight and staple length, but were uncorrelated with fleece grade. These estimates of genetic parameters between prolificacy, weight, and wool traits can be used to construct multiple-trait selection indexes for dual-purpose sheep.

Age Factors↗
PubMed1991

Genetics of health traits in Holstein cattle.

Incidences of 22 health related traits were analyzed for 11,008 lactation records provided by 21st Century Genetics. Traits were analyzed both individually and grouped into one of five health categories. Significant sources of variation included herd-year, lactation, cow, and sire effects. Genetic parameters were estimated with multiple-trait REML. Repeatability and heritability estimates were low to moderate. Estimates ranged from .09 to .57 for repeatability and from .02 to .21 for heritability when individual traits were pooled by health category. Reproductive and respiratory traits were the least heritable (less than .10); mammary and locomotive traits were slightly higher (less than .20); and digestive category was most heritable (.21). Genetic correlations of mature equivalent milk with number of inseminations and other reproductive problems were positive (antagonistic), but those with incidences of other health problems were negative. Phenotypic correlations among mature equivalent milk and fat with individual health traits and categories of health traits were small and mostly near zero. Genetic correlations among health traits were positive except for reproduction with mammary and respiratory traits. Phenotypic correlations among health traits were near zero. Results suggest that selection for reduction of health problems is possible. If selection is practiced for improved health, these health traits should be properly weighted relative to production and other traits by the appropriate economic value. Evaluation of animals for health problems should be done on a multiple-trait basis.

Animals↗
PubMed1992

Genetic parameters of conformation traits, milk yield, and herd life in Holsteins.

Genetic parameters were estimated simultaneously for 5 herd-life traits, 15 conformation (type) traits, and milk yield measured in first lactation for 128,601 Holstein cows. Heritabilities of all traits were higher in registered than in grade cows. Genetic correlations of linear type traits with first lactation yield ranged from -.48 for udder depth to .54 for dairy form. Genetic correlations among milk yield and herd-life traits were all positive except for milk-corrected herd life in grade cows. Udder traits had largest absolute genetic correlations with herd-life traits, followed by body traits and feet and leg traits. Some traits associated with body size and foot angle differed between registered and grade cows. Estimates of genetic trends from obtained parameters revealed greatest progress for milk yield from single-trait selection but also the largest changes for some type traits and milk-corrected herd life in an undesirable direction. Relative milk to type ratios of between 2:1 and 3:1 yielded 90% of the gain in milk yield with no change or slight improvement in type traits and functional herd life. Selection for type traits associated with herd life appears to be warranted to improve days of functional herd life or to decrease involuntary culling of dairy cows.

Animals↗
PubMed1996

Bilateral asymmetry in dental discrete traits in human isolates: south Sinai Bedouin tribes.

Data are presented on dental morphology as adjudged from dental casts of children (boys and girls) 6-13 years of age from four Bedouin tribes of Southern Sinai (Gebeliya, Muzeina, Hamada and Aliquat) and a mixed group designated as "other tribes", (Awlad Said, Gararsha, Sawalcha, Haweitat and Beni-Wassal). Alginate was the impression material used and the casts were made of artificial stone poured into the irreversible hydrocolloid impression. A total of 352 casts were available for study. In the maxilla, 29 dental discrete traits of permanent teeth and 2 traits of deciduous teeth were observed, and in the mandible, 24 traits of permanent teeth and 2 traits of deciduous teeth; in all, 57 traits were observed. Only clear traits were considered. From the studied 57 traits only 30 morphological traits were used for the estimation of the asymmetry. Total symmetry was observed in 2 mandibular teeth and traits: a) Lateral incisor-LI-slight inclination; b) Canine-Cn-no lingual cingulum and in 3 maxillary teeth and traits a) Central incisor-CI-slight convexity of labial profile curvature; b) First premolar-PM1-intercuspal distance more than 3 mm; and c) Second molar,-M2-pit groove pattern similar to the first molar. Low values of asymmetry (1-5.1%) were observed in traits describing outline form and shape, surface outline, and number of cusps in three maxillary and two mandibular teeth (nine discrete traits). High values of asymmetry (12.7-37.0%) were observed regarding traits describing styles on slopes, ridges, pits, grooves and lingual tubercles in three maxillary and one mandibular teeth (15 discrete traits). The high rate in molars was higher than that in the incisors. A higher rate of asymmetry occurred in the maxilla than in the mandible.

Adolescent↗
PubMed2006

A simple method to localise pleiotropic susceptibility loci using univariate linkage analyses of correlated traits.

Univariate linkage analysis is used routinely to localise genes for human complex traits. Often, many traits are analysed but the significance of linkage for each trait is not corrected for multiple trait testing, which increases the experiment-wise type-I error rate. In addition, univariate analyses do not realise the full power provided by multivariate data sets. Multivariate linkage is the ideal solution but it is computationally intensive, so genome-wide analysis and evaluation of empirical significance are often prohibitive. We describe two simple methods that efficiently alleviate these caveats by combining P-values from multiple univariate linkage analyses. The first method estimates empirical pointwise and genome-wide significance between one trait and one marker when multiple traits have been tested. It is as robust as an appropriate Bonferroni adjustment, with the advantage that no assumptions are required about the number of independent tests performed. The second method estimates the significance of linkage between multiple traits and one marker and, therefore, it can be used to localise regions that harbour pleiotropic quantitative trait loci (QTL). We show that this method has greater power than individual univariate analyses to detect a pleiotropic QTL across different situations. In addition, when traits are moderately correlated and the QTL influences all traits, it can outperform formal multivariate VC analysis. This approach is computationally feasible for any number of traits and was not affected by the residual correlation between traits. We illustrate the utility of our approach with a genome scan of three asthma traits measured in families with a twin proband.

Asthma↗
PubMed2006

Heritability of cardiovascular and personality traits in 6,148 Sardinians.

In family studies, phenotypic similarities between relatives yield information on the overall contribution of genes to trait variation. Large samples are important for these family studies, especially when comparing heritability between subgroups such as young and old, or males and females. We recruited a cohort of 6,148 participants, aged 14-102 y, from four clustered towns in Sardinia. The cohort includes 34,469 relative pairs. To extract genetic information, we implemented software for variance components heritability analysis, designed to handle large pedigrees, analyze multiple traits simultaneously, and model heterogeneity. Here, we report heritability analyses for 98 quantitative traits, focusing on facets of personality and cardiovascular function. We also summarize results of bivariate analyses for all pairs of traits and of heterogeneity analyses for each trait. We found a significant genetic component for every trait. On average, genetic effects explained 40% of the variance for 38 blood tests, 51% for five anthropometric measures, 25% for 20 measures of cardiovascular function, and 19% for 35 personality traits. Four traits showed significant evidence for an X-linked component. Bivariate analyses suggested overlapping genetic determinants for many traits, including multiple personality facets and several traits related to the metabolic syndrome; but we found no evidence for shared genetic determinants that might underlie the reported association of some personality traits and cardiovascular risk factors. Models allowing for heterogeneity suggested that, in this cohort, the genetic variance was typically larger in females and in younger individuals, but interesting exceptions were observed. For example, narrow heritability of blood pressure was approximately 26% in individuals more than 42 y old, but only approximately 8% in younger individuals. Despite the heterogeneity in effect sizes, the same loci appear to contribute to variance in young and old, and in males and females. In summary, we find significant evidence for heritability of many medically important traits, including cardiovascular function and personality. Evidence for heterogeneity by age and sex suggests that models allowing for these differences will be important in mapping quantitative traits.

Adolescent↗
PubMed2003

[QTLs mapping of leaf traits and root vitality in a recombinant inbred line population of rice].

By employing a recombinant inbred line (RIL) population of 247 lines derived from an inidca-indica cross Zhenshan 97B x Milyang 46, a linkage map consisting of 158 DNA markers was constructed and used for the determination of QTLs conditioning five leaf traits and root exudates. The leaf traits analyzed were leaf area, leaf length, leaf width, leaf perimeter and leaf length/width ratio measured on top first leaf, top second and top third leaves. The RIL population showed transgressive segregation on each trait, and highly significant or significant positive correlations were observed between all traits except between leaf length and width, and between leaf perimeter and length/width ratio. A total of 24 QTLs located in 9 intervals were detected to have significant additive effects for leaf traits analyzed, with LOD scores ranging 2.9-11.8 and 4.0%-32.5% phenotypic variation explained for a single QTL. Clustering of QTLs for leaf traits was evident. In interval RM197-RZ516 on chromosome 6, 2 QTLs for leaf length, 2 QTLs for leaf width and 3 QTLs for leaf length/width ratio of different leaves were detected, among which the alleles for increasing trait values were from Zhenshan 97B for leaf length and leaf length/width ratio, and from Milyang 46 for leaf width. In interval RM1-RG532 on chromosome 1,2 QTLs for leaf length and 2 QTLs for leaf perimeter were detected on top first leaf and top second leaf, respectively, and all the alleles for increasing trait values were from Milyang 46. In this interval, larger additive effects were observed for QTLs detected on top first leaf than at top second leaf. In interval RZ667-B10B on chromosome 6, a QTL for leaf perimeter of top second leaf was detected, accounting for 8.0% phenotypic variation. In intervals RZ66-RM264 and RG81-RM313 on chromosome 8 and 12, each QTL was detected for leaf length of top third leaf and explained for 9.0% and 15.3% phenotypic variation, respectively. Epistasis analysis detected 56 and 4 significant additive-by-additive interactions for leaf traits and root vitality, explaining 2.7% to 13.7% and 6.8% to 14.9% of the total phenotypic variation, respectively. On comparison with QTLs for yield traits detected in the same population previously, it was found that the majority of QTLs for leaf traits and root vitality and those for yield traits were located in similar intervals. Fine mapping of QTLs for both leaf and yield traits in these chromosomal regions would facilitate investigations of the source-sink relationship in rice.

Chromosome Mapping↗
PubMed2026

The Multiple Roles of Genetics on Freshwater Macrophyte Functional Traits in the Interplay With the Environment: A Review.

The study of functional trait variation is increasingly used to understand macrophyte adaptation, as traits reflect organismal performance under different ecosystem conditions. Phenotypic expression results from the interplay of genetic and environmental factors: genetics provides the molecular basis for heritable traits and constrains potential phenotypes, while the environment acts as a selective and modulatory force. However, the genetic insight into traits has rarely been addressed in freshwater macrophyte studies. This review examines the different ways in which the DNA of macrophytes interplays with the environment and contributes to the variation in their functional traits, outlining main approaches, gaps, and future challenges. Only 21 studies explicitly combined genetics with functional traits and environment in the last fifteen years. The most common approach was the use of common garden experiments to explore acclimation and adaptation in a few model species. Current studies mainly focus on morphological and growth traits that best describe macrophytes' economic strategies, with limited attention to other trait categories, while the genetic and DNA traits studied are more variable. Across studies, environmental factors generally explained a larger proportion of functional trait variation, highlighting the dominant role of phenotypic plasticity for macrophyte acclimatation, whereas genetic contribution increased under experimentally manipulated conditions. Genome size and epigenetic variation influenced phenotypic plasticity; however, the effect was different and inconsistent on traits and depended on phylogenetic relationships and geographical environment variation. In field studies of natural populations, life history traits and hydrology had a strong effect on the geographic distribution of genetic diversity and the response to selection, as well as on our ability to distinguish selection from genetic drift. Future research should enhance molecular analyses, adopt multifactorial and long-term experimental designs, develop conceptual frameworks to address the relationships between genomics, environment and functional traits and integrate emerging tools to capture macrophyte adaptation better.

adaptation↗
PubMed2006

Heritability and genetic correlation estimates for performance and carcass and body composition traits in a male broiler line.

The current research was conducted to estimate the heritability coefficients and the genetic correlations for performance and carcass and body composition traits in a single sire broiler line. The performance traits analyzed were BW at 38 d, ultrasound records of pectoral muscle depth, feed intake, feed conversion ratio, and BW at 42 d. The carcass traits analyzed were eviscerated BW, breast weight, and leg weight, and the body composition traits analyzed were abdominal fat content, heart weight, gizzard weight, liver weight, and intestine weight. The number of observations varied between 4,120 and 29,040 for each trait. The (co)variance components, heritability, and genetic correlation estimates were obtained by restricted maximum likelihood. The numerator relationship matrix had 42,912 animals. Based on the heritability estimates obtained, the analyzed traits seemed to be able to respond to selection, at variable intensities. The genetic correlation estimates between a great number of performance traits, as well as between a great number of carcass traits, were suggestive of a close genetic relationship between these traits. The genetic correlation estimates between body composition traits were variable. A large genetic association between a great number of performance and carcass traits seemed to exist. The genetic correlation estimates between performance and body composition traits were variable, and important associations between carcass and body composition traits did not seem to exist.

Abdominal Fat↗
PubMed2000

Detection of putative loci affecting milk, health, and conformation traits in a US Holstein population using 105 microsatellite markers.

Quantitative trait loci affecting milk yield, health, and conformation traits were studied for eight large US Holstein grandsire families by using the granddaughter design. A total of 105 microsatellite markers, located throughout the bovine genome, were selected for the scan. The data analyzed include genotypes for 35 markers in eight families not previously reported and genotypes for 70 markers reported previously in seven of those families. Analyses of markers previously reported were updated. Effects of marker alleles were analyzed for 38 traits, including traits for milk production, somatic cell score, productive life, conformation, calving ease, and 16 canonical traits derived from conformation and production traits. Permutation tests were used to calculate empirical trait-wise error rates. A trait-wise critical value of P = 0.1 was used to determine significance. Eight putative quantitative trait loci associated with 7 of the 35 new markers were identified within specific families. Two of these markers were associated with differences in strength and rump angle on chromosomes 4 and 9, respectively. Different markers were associated with protein percentage, milk yield, and somatic cell score on chromosomes 6, 7, and 10 in different families. Differences in the canonically transformed traits were associated with markers on chromosomes 5, 6, and 9. Additional marker-trait combinations were identified in the across-family tests, including effects on chromosomes 3, 4, and 9 for protein percentage, body depth, and canonical conformation traits, respectively. Additional markers are being added to allow interval analysis for putative quantitative trait loci that have been identified and to increase marker density.

Alleles↗
PubMed2003

Nonmetric subadult skeletal sexing traits: I. A blind test of the accuracy of eight previously proposed methods using prehistoric known-sex mummies from northern Chile.

While a number of nonmetric sex-related traits have been proposed, the accurate assignment of sex to subadult skeletal materials is generally considered problematic. Eight previously proposed nonmetric traits of the ilia and mandible have been demonstrated by other researchers to be related to the known-sex of subadults, yet there has been relatively little research attempting to evaluate the utility of these traits using independent collections of known-sex subadult skeletal remains. These eight traits include: elevation of the auricular surface, angle of the greater sciatic notch, depth of the greater sciatic notch, the "arch criteria," curvature of the iliac crest, gonial eversion, mandibular protrusion, and mandibular arcade shape. The present study blindly tested these eight nonmetric traits using 85 autopsied prehistoric known-sex mummified subadult remains from northern Chile that range in age between newborn and 15 skeletal years of age. The two primary questions examined for each trait are: (1) are the different character states for each of the eight traits related to known-sex, and (2) which of the eight traits are accurate enough for use in forensic cases? These questions are examined for each trait by both sex and age class so as to uncover potential sex- and age-related strengths and weaknesses for each of the characteristics. The results indicate that all eight of the previously proposed subadult sex-related traits are indeed related to known-sex, but that there is a great deal of variation by both sex and age in terms of the strength of congruent sex-related associations. With the exception of gonial eversion, all of the traits produced statistically significant chi2 values for their associations with known-sex when all subadult remains were considered. However, when all subadults are considered, only four traits demonstrated acceptable levels of accuracy for forensic applications. These traits include the arch criteria (82.3%), angle of the sciatic notch (80.7%), depth of the sciatic notch (79.0%), and mandibular arcade shape (77.6%). For subadults ranging in age from newborn to five skeletal years of age, only depth of the sciatic notch (81.5%) and the arch criteria (81.5%) approach acceptable levels of accuracy for use in forensic cases. The implications of these results are discussed and recommendations for bioarchaeological and forensic applications are made.

Adolescent↗