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PubMed2021

Genetic Relationship Between Endometriosis and Melanoma.

Epidemiological studies have observed that risk of endometriosis is associated with history of cutaneous melanoma and vice versa. Evidence for shared biological mechanisms between the two traits is limited. The aim of this study was to investigate the genetic correlation and causal relationship between endometriosis and melanoma. Summary statistics from genome-wide association meta-analyses (GWAS) for endometriosis and melanoma were used to estimate the genetic correlation between the traits and Mendelian randomization was used to test for a causal association. When using summary statistics from separate female and male melanoma cohorts we identified a significant positive genetic correlation between melanoma in females and endometriosis (r g = 0.144, se = 0.065, p = 0.025). However, we find no evidence of a correlation between endometriosis and melanoma in males or a combined melanoma dataset. Endometriosis was not genetically correlated with skin color, red hair, childhood sunburn occasions, ease of skin tanning, or nevus count suggesting that the correlation between endometriosis and melanoma in females is unlikely to be influenced by pigmentary traits. Mendelian Randomization analyses also provided evidence for a relationship between the genetic risk of melanoma in females and endometriosis. Colocalization analysis identified 27 genomic loci jointly associated with the two diseases regions that contain different causal variants influencing each trait independently. This study provides evidence of a small genetic correlation and relationship between the genetic risk of melanoma in females and endometriosis. Genetic risk does not equate to disease occurrence and differences in the pathogenesis and age of onset of both diseases means it is unlikely that occurrence of melanoma causes endometriosis. This study instead provides evidence that having an increased genetic risk for melanoma in females is related to increased risk of endometriosis. Larger GWAS studies with increased power will be required to further investigate these associations.

endometriosis↗

PubMed1990

Genetic analysis of absolute growth measurements, relative growth rate and restricted selection indices in red Angus cattle.

Performance records on 41,184 Red Angus cattle were analyzed and estimates of parameters calculated for absolute growth rate, relative growth rate and restricted selection indices. Heritability estimates for birth weight, 205-d weight, 365-d weight and postweaning gain were .46 +/- .02, .39 +/- .02, .40 +/- .02 and .36 +/- .02, respectively. Heritability estimates for preweaning, postweaning and postnatal relative growth rates were identical (.33 +/- .02). Heritability estimates for restricted selection indices were .31 +/- .02, .33 +/- .02 and .31 +/- .02 for weaning index, yearling index and postweaning index, respectively. The genetic correlation between preweaning and postweaning absolute growth rate was .15. The genetic correlation between consecutive measurements of relative growth rate (RGR) was -.33. Genetic correlations of birth weight with preweaning RGR and postnatal RGR were -.68 and -.71, respectively. Correlations among measures of relative growth rate using simulated data were similar to correlations of actual data, indicating that these relationships are the result of numerator/denominator relationships and not biological causes. The genetic correlation between weaning and postweaning indices was near zero. Small genetic coefficients of variation for preweaning and postnatal relative growth rates indicate further problems with the expression of growth in this manner. Restricted selection indices exhibited much larger genetic coefficients of variation than measurements of RGR. Genetic standard deviations were 7.8%, 7.2% and 13.7% of the means for weaning, yearling and postweaning indices, respectively.

Animals↗

PubMed2005

Genetic analysis of age at first service, return rate, litter size, and weaning-to-first service interval of gilts and sows.

The aim of this study was to estimate genetic parameters of seven traits related to sow reproductive performance. Data on all Norwegian Landrace pigs (NL) born in nucleus herds and raised in nucleus or multiplying herds from 1990 to 2000 were extracted from the Norwegian national recording scheme. Reproductive traits investigated were age at first service (AFS), return rate in gilts (RRg), age at first farrowing (AFF), live-born piglets in the first litter (NBA1), interval from weaning to first service after first litter (WTS1), return rate after first litter (RR1), live-born piglets in the second litter (NBA2), and interval from weaning to first service after second litter (WTS2). After editing, the data set comprised 12,583 to 56,042 records, depending on the trait. A mixed linear and a joint linear threshold animal model were used to estimate (co)variance components. A full Bayesian approach via Gibbs sampling was adopted. The statistical model used for analysis included contemporary groups of herd-year (-season), purebred or crossbred litter, single or double insemination, mating type, parity in which the animal was born, a regression on lactation length, and an additive genetic effect. Neither the estimated heritabilities nor the genetic correlations differed much between the two approaches, but there was a tendency for higher genetic correlations using the joint linear threshold model approach. Average heritabilities were as follows: AFS = 0.31; RRg = 0.03; RR1 = 0.02; NBA1 = 0.12; NBA2 = 0.14; WTS1 = 0.08; and WTS2 = 0.03. The highest genetic correlations were estimated between NBA1 and NBA2 (r(g) = 0.95), RR1 and WTS1 (r(g) = 0.93), and between WTS1 and WTS2 (r(g) = 0.78). The estimated genetic correlation between NBA and WTS were close to zero. Selection for increased NBA will slightly increase AFS and reduce the probability of a return. Selection for decreased AFS will have a favorable effect on WTS intervals; however, selection for decreased AFS seems to have an unfavorable effect on return rate both on gilts and sows. Conversely, selection for decreased WTS intervals will reduce the probability of a return. Potential selection candidates to include in a multivariate fertility index are AFS, NBA, and WTS1. Due to the low heritability and low, but favorable, genetic correlations to NBA and WTS, RR is not recommended as a selection candidate.

Age Factors↗

PubMed2000

Breaking through artificial selection limits of an adaptive behavior in mice and the consequences for correlated responses.

Previous divergent selection for nest-building behavior at 22 +/- 1 degrees C resulted in a 40-fold difference between the high and the low lines in amount of cotton used to build a nest. Correlated responses to selection indicated positive genetic correlations with body weight, nest-building at 4 +/- 1 degrees C, and litter size and negative genetic correlations with food consumption. At generation 46, the replicate high-selected (High 1 x High 2), randomly bred control (Control 1 x Control 2), and low-selected (Low 1 x Low 2) lines were crossed and the F1 showed significant heterosis for nest-building behavior. Regression of the F3 on the F2 generation gave heritability estimates of 0.16 +/- 0.10 for the high and 0.07 +/- 0.10 for the low cross, revealing a potential to break the selection limit (at least in the high direction), which had been reached at about 20 generations of selection. Indeed, renewed selection resulted in responses in both the high and the low directions of nesting, yielding realized heritabilities of 0.29 +/- 0.02 and 0.30 +/- 0.004, respectively. Replicated renewed selection, using the F3 generation as the base population, in the high direction of nesting resulted in correlated increases in nest-building at 4 +/- 1 degrees C, litter size, and food consumption. Body weight did not change. The positive correlation with food consumption is opposite in sign compared to the original selection experiment. This indicates that the evolutionary potential of a population to adapt to a changing environment not only depends on its current genetic variability in one adaptive trait, but may be constrained by genetic correlations changing over the course of selection.

Animals↗

PubMed2006

Genetic analysis of calf market weight and carcass traits in Japanese Black cattle.

Heritabilities of and genetic correlations between additive direct and maternal genetic effects for calf market weight, and additive direct genetic effects for carcass traits, were estimated for Japanese Black cattle by REML procedures under 2-trait animal models. Data were collected from calf and carcass markets in Hyogo and Tottori prefectures and analyzed separately by prefecture. Calf market weight was measured on 42,745 and 23,566 calves in Hyogo and Tottori, respectively. Only the fattening animals with calf market weight were extracted from the carcass database and used for estimation. The carcass traits analyzed were carcass weight, ribeye area, rib thickness, subcutaneous fat thickness, yield estimate, beef marbling score, and 4 meat characters (color, brightness, firmness, and texture). Direct and maternal heritabilities for calf market weight were estimated to be 0.22 and 0.07 in Hyogo, and 0.37 and 0.15 in Tottori, respectively. The estimates of heritabilities for carcass traits were moderate to high in both prefectures. The estimates of direct-maternal genetic correlations for calf market weight were positive (0.17) in Hyogo and negative (-0.63) in Tottori. The direct effect for calf market weight was positively correlated with the direct effect for carcass weight (0.87 and 0.56 in Hyogo and Tottori, respectively) but negatively correlated with the direct effect for beef marbling score (-0.10 in both prefectures). The estimates of genetic correlations between the maternal effect for calf market weight and the direct effects for carcass traits varied from -0.13 to 0.34 in Hyogo and from -0.14 to 0.15 in Tottori. Because direct and maternal genetic effects for early growth traits can be evaluated from calf market weight data in the production system of Japanese Black cattle, this information should be incorporated into selection and mating schemes of the breed.

Animals↗

PubMed2002

Genetic parameters of dairy character, protein yield, clinical mastitis, and other diseases in the Danish Holstein cattle.

The primary aim of this study was to estimate genetic correlations between dairy character, protein yield, clinical mastitis, and other diseases. Data consisted of first lactation records of Danish Holstein cows calving from 1990 to 1999. After editing, the data included records on 934,639 cows, of which 101,853 were assessed for dairy character, 472,421 for diseases, and 834,993 for protein yield. The disease traits were defined as binary traits in the period from 10 d before to 50 d after calving for clinical mastitis, and from 10 d before to 100 d after calving for diseases other than mastitis. Data were analyzed with a linear sire model using the method of AI-REML. Heritabilities were estimated to be 0.265 for protein yield, 0.261 for dairy character, 0.035 for clinical mastitis, and 0.020 for diseases other than mastitis. Estimates of genetic correlations between protein yield and dairy character, protein yield and clinical mastitis, and protein yield and diseases other than mastitis were 0.38, 0.33, and 0.14. Between the two disease traits, the genetic correlation was 0.24. The genetic correlation between dairy character and clinical mastitis was 0.24. Between dairy character and diseases other than mastitis the genetic correlation was 0.41. Thus, cows with high score for dairy character were more prone to diseases. The genetic correlation between dairy character and the disease traits, when both traits were adjusted for protein yield, was 0.13 for clinical mastitis and 0.39 for diseases other than mastitis. These findings suggest that, dairy character should be given a negative rather than a positive weight in the breeding goal.

Animals↗

PubMed2003

Genetic relations of yolk proportion and chick weight with production traits in a White Leghorn line.

1. The main purpose of this study was to estimate genetic correlations between yolk proportion, chick weight and production traits using an animal model. 2. Direct-direct genetic correlations were estimated between yolk proportion and age at first egg (-0.34), body weight at 20 (0.10), 40 (0.58) and 60 (0.52) weeks of age, egg number (0.56), egg mass (0.59), feed intake (0.64) and feed conversion (-0.25). 3. Maternal-direct genetic correlations were estimated between chick weight and age at first egg (0.40), body weight at 20 (0.57), 40 (0.66) and 60 (0.56) weeks of age, egg number (-0.50), egg mass (0.21), feed intake (0.45) and feed conversion (0.17), respectively. 4. In conclusion, the results suggest that selection on a higher yolk proportion would not have any unfavourable effects on egg production. Maternal-direct genetic correlations between chick weight and production traits resembled direct-direct genetic correlations between egg weight and production traits found in other studies.

Age Factors↗

PubMed1999

Evolution of the genetic covariance between male and female components of mate recognition: an experimental test.

The evolution of a positive genetic correlation between male and female components of mate recognition systems will result as a consequence of assortative mating and, in particular, is central to a number of theories of sexual selection. Although the existence of such genetic correlations has been investigated in a number of taxa, it has yet to be shown that such correlations evolve and whether they may evolve as rapidly as suggested by sexual selection models. In this study, I used a hybridization experiment to disrupt natural mate recognition systems and then observed the subsequent evolutionary dynamics of the genetic correlation between male and female components for 56 generations in hybrids between Drosophila serrata and Drosophila birchii. The genetic correlation between male and female components evolved from 0.388 at generation 5 to 1.017 at generation 37 and then declined to -0.040 after a further 19 generations. These results indicated that the genetic basis of the mate recognition system in the hybrid populations evolved rapidly. The initial rapid increase in the genetic correlation was consistent with the classic assumption that male and female components will coevolve under sexual selection. The subsequent decline in genetic correlation may be attributable to the fixation of major genes, or, alternatively, may be a result of a cyclic evolutionary change in mate recognition.

Animals↗

PubMed1989

Growth of Mashona cattle on range in Zimbabwe. II. Estimates of genetic parameters and predicted response to selection.

For 1,456 Mashona calves sired by 88 bulls heritability estimates from paternal half-sibs were 0.44 +/- 0.11 for birth weight, 0.38 +/- 0.10 for 205-day weaning weight, 0.39 +/- 0.10 for 18-month weight, 0.37 +/- 0.10 for pre-weaning daily liveweight gain and 0.41 +/- 0.11 for daily gain from weaning to 18 months of age. Genetic correlations were relatively low for birth weight with weaning weight (0.42 +/- 0.18), 18-month weight (0.56 +/- 0.16), pre-weaning gain (0.33 +/- 0.19) and post-weaning gain (0.36 +/- 0.19). Higher genetic correlations were observed for pre-weaning gain with weaning weight (0.98 +/- 0.01) and 18-month weight (0.59 +/- 0.14) and for 18-month weight with weaning weight (0.67 +/- 0.12) and post-weaning gain (0.73 +/- 0.10). Post-weaning daily gain was not significantly correlated genetically with both pre-weaning gain (-0.11 +/- 0.22) and weaning weight (-0.03 +/- 0.22). With 10% retention of males and 60% of females expected genetic improvements per generation from direct selection for weaning weight or 18-month weight were 8.11 kg and 12.12 kg respectively. These improvements would be reduced by 18% and 35% if selection indices were used to produce no correlated change in birth weight.

Animals↗

PubMed2004

Evaluation of body condition score measured throughout lactation as an indicator of fertility in dairy cattle.

Body condition score (BCS) records of primiparous Holstein cows were analyzed both as a single measure per animal and as repeated measures per sire of cow. The former resulted in a single, average, genetic evaluation for each sire, and the latter resulted in separate genetic evaluations per day of lactation. Repeated measure analysis yielded genetic correlations of less than unity between days of lactation, suggesting that BCS may not be the same trait across lactation. Differences between daily genetic evaluations on d 10 or 30 and subsequent daily evaluations were used to assess BCS change at different stages of lactation. Genetic evaluations for BCS level or change were used to estimate genetic correlations between BCS measures and fertility traits in order to assess the capacity of BCS to predict fertility. Genetic correlation estimates with calving interval and non-return rate were consistently higher for daily BCS than single measure BCS evaluations, but results were not always statistically different. Genetic correlations between BCS change and fertility traits were not significantly different from zero. The product of the accuracy of BCS evaluations with their genetic correlation with the UK fertility index, comprising calving interval and non-return rate, was consistently higher for daily than for single BCS evaluations, by 28 to 53%. This product is associated with the conceptual correlated response in fertility from BCS selection and was highest for early (d 10 to 75) evaluations.

Analysis of Variance↗

PubMed1996

Correlation of genetic and physical maps at the A mating-type locus of Coprinus cinereus.

The A mating type locus of Coprinus cinereus is remarkable for its extreme diversity, with over 100 different alleles in natural populations. Classical genetic studies have demonstrated that this hypervariability arises in part from recombination between two subloci of A, alpha and beta, although more recent population genetic data have indicated a third segregating sublocus. In this study, we characterized the molecular basis by which recombination generates nonparental A mating types. We mapped the frequency and location of all recombination events in two crosses and correlated the genetic and physical maps of A. We found that all recombination events were located in 6 kb of noncoding DNA between the alpha and beta subloci and that the rate of recombination in this noncoding region matched that generally observed for this genome. No recombination within gene clusters or within coding regions was observed, and the two alpha and beta subloci described in genetic analyses correlated with the previously characterized alpha and beta gene clusters. We propose that pairs of genes constitute both the sex determining and the hereditary unit of A.

Chromosome Mapping↗

PubMed2001

Heritabilities and correlations among body condition scores, production traits, and reproductive performance.

The objectives of this study were to estimate the heritability of body condition scores (BCS) from producer and consultant-recorded data and to describe the genetic and phenotypic relationships among BCS, production traits, and reproductive performance. Body condition scores were available at calving, postpartum, first service, pregnancy check, before dry off, and at dry off from the Dairy Records Management Systems in Raleigh, NC, through the PCDART program. Heritabilities, genetic correlations, and phenotypic correlations were estimated assuming an animal model using average information REML. Herd-year-season effects and age at calving were included in all models. Prior calving interval was included in models for second and third lactations. Analyses that included reproductive traits were conducted with and without mature equivalent milk as a covariable. Heritability estimates for BCS ranged from 0.09 at dry-off to 0.15 at postpartum in first lactation. Heritability estimates ranged from 0.07 before dry-off to 0.20 at pregnancy check in second lactation and from 0.08 before dry-off to 0.19 at first service in third lactation. Genetic correlations between adjacent BCS within first lactation were greater than 0.96 with the exception of calving and postpartum (0.74). In second lactation, adjacent genetic correlations were 1.0 with the exception of calving and postpartum (0.84). Genetic correlations across lactations were greater than 0.77. Phenotypic correlations between scoring periods were highest for adjacent scoring periods and when BCS was lowest. Phenotypic correlations were lower than genetic correlations, i.e., less than 0.70. Higher BCS during the lactation were negatively related to production, both genetically and phenotypically, but the relationship was moderate. Higher BCS were favorably related genetically to reproductive performance during the lactation.

Animals↗

PubMed1985

Genetic and phenotypic relationships between lactation cell counts and milk yield and composition of Holstein cows.

Monthly somatic cell count data were collected between February 1977 and February 1982 for Holstein cows in 928 herds enrolled on the Quebec Dairy Herd Analysis Service. The geometric mean of the log monthly cell counts was calculated for each lactation. Official lactation records for 305-day milk, fat, and protein yields, and fat and protein percents were obtained for same cows. There were 18,189 cows in first lactation representing 257 sires, 13,225 in second lactation representing 206 sires, and 8,683 in third lactation representing 151 sires. Heritabilities of yield traits and protein percent increased across three lactations. Heritability of fat percent was similar in first and third lactations but decreased slightly in second lactations. Heritability of lactation cell count was small, being least in second lactations. Genetic correlations between lactation cell count and yield traits were positive in first lactations, small and negative in second lactations, and small and positive in third lactations. Genetic correlations between lactation cell count and fat and protein contents were small in the three lactations. Phenotypic correlations between lactation cell count and production traits were small in each of the three lactations. Genetic correlations between yield traits in early lactation and lactation cell count in a subsequent lactation were positive. The genetic correlation between protein percent in an early lactation and cell count in a later lactation was large between first and second lactations, decreased between second and third lactation, and small between first and third lactations. Genetic correlations were small and negative for fat percent.

Animals↗

PubMed2003

Genetic architecture for normal and novel host-plant use in two local populations of the herbivorous ladybird beetle, Epilachna pustulosa.

Trade-offs in host-plant use are thought to promote the evolution of host specificity. However, usually either positive or no genetic correlations have been found. Whereas factors enhancing variation in overall viability have been claimed to mask negative genetic correlations, alternative hypotheses emphasize the sequential changes in genetic correlation in the course of host-range evolution. In this study, the genetic architectures of performances on different hosts were compared in two populations of the herbivorous ladybird beetle, Epilachna pustulosa, using three host plants, one being normal for both, one novel for only one population, and the other novel for both populations. The genetic correlations between larval periods on normal hosts were significantly positive whereas those between normal and novel hosts were not different from zero. There was no evidence for reduced genetic variation on the normal host-plants. These results suggest that the host-range is not restricted by the antagonistic genetic associations among exploitation abilities on different plant species, but rather that selection of different host-plants may improve the coordination between genes responsible for the use of different plants.

Adaptation, Physiological↗

PubMed1995

Genetic parameters for milk yield, survival, workability, and type traits for Australian dairy cattle.

Genetic parameters, such as heritabilities and genetic correlations were estimated for milk yield, survival, workability, and type traits for Australian Holstein-Friesian and Jersey cattle. All analyses were performed using multivariate REML with a sire model. Heritabilities for lactation yield traits were moderate, ranging from .20 to .28, and heritabilities for mean test day deviations were approximately .40 higher. Heritabilities for survival (probability of surviving to the next lactation) were low, ranging from .02 to .08. Genetic correlations between survival scores were high, ranging from .37 to .98, in particular between adjacent survival scores (on average .91 and .97 for Holstein-Friesians and Jerseys). Heritabilities for stayabilities were larger, ranging from .03 to .22. On average, genetic correlations between stayabilities were very high, ranging from .66 to .99. For milking speed, temperament, and likeability, heritability estimates ranged from .18 (for likeability in Holstein-Friesians) to .29 (for milking speed in Jerseys). Undesirable scores for milking speed and temperament had negative genetic correlations with stayabilities (correlations approximately -.20). Heritabilities for type traits were all moderate (.11 to .42), and genetic correlations among type traits and between type traits and production traits were large. Phenotypic correlations between type traits and stayabilities were low. Generally, genetic correlations between type traits and stayabilities were low although the standard errors of those estimates were large.

Animals↗

PubMed2003

Heritability of body length and measures of body density and their relationship to backfat thickness and loin muscle area in swine.

The objective of this study was to estimate heritability for body length (LEN) at the end of performance testing and to estimate genetic correlations with backfat (BF) thickness and loin muscle area (LMA) in Landrace, Yorkshire, Duroc, and Hampshire breeds of swine. Also examined were two measures of body density involving body length and weight and their relationships to backfat and loin muscle area. Data consisted of performance test records collected in a commercial swine operation from 1992 to 1999. Boars from 60% of the litters were culled at weaning based on a maternal breeding value of the dam. Remaining boars and all females were grown to 100 d of age (15,594, 55,497, 12,267, and 9,782 Landrace, Yorkshire, Duroc, and Hampshire pigs, respectively). At this time, all pigs were weighed (WT100) and selected for performance testing based on a combination of maternal and performance indexes, which differed by breed. All pigs were weighed at the end of the 77 d performance test (WT177) when BF, LMA, and LEN were measured. Two measures of body density involving length were calculated: Body mass index (BMI) = WT177/LEN2 and body density (DENSITY) = WT177/LEN. For each breed, genetic parameters were estimated using an animal model with random litter effects and multiple-trait REML procedures. A series of three-trait models including WT100 and combinations of two other traits in each analysis was conducted. Fixed effects included contemporary group and age as a covariate. Average estimates of heritability were 0.16 to 0.32 for LEN (unadjusted for WT177), 0.12 to 0.26 for LEN (adjusted for WT177), 0.23 to 0.33 for DENSITY, and 0.16 to 0.25 for BMI. Genetic correlations between LEN and LMA were low. Genetic correlations between LEN (unadjusted for WT177) and BF were 0.10 to 0.41. Adjusting LEN for WT177 gave correlations of 0.11 for Landrace and Hampshire and negative correlations (-0.06 and -0.19, respectively) for Yorkshire and Duroc. Genetic correlations between LMA and DENSITY and between LMA and BMI were comparable and ranged from 0.44 to 0.54. Genetic correlations between BF and DENSITY were slightly higher (0.53 to 0.68) than those between BF and BMI (0.37 to 0.67). In these data, not much relationship between BF and body length at a constant weight and age was found. There was a negative relationship between LMA and LEN at a constant weight and age, implying that longer pigs had smaller LMA.

Adipose Tissue↗

PubMed2002

Evaluation of classifiers that score linear type traits and body condition score using common sires.

Subjective visual assessment of animals by classifiers is undertaken for several different traits in farm livestock, e.g., linear type traits, body condition score, or carcass conformation. One of the difficulties in assessment is the effect of an individual classifier. To ensure that classifiers rank animals consistently, i.e., the repeatability between classifiers and within classifier, genetic links across routinely scored observations may be used to validate scoring of individual classifiers. Eighteen classifiers of NRS scored 18 traits, and body condition for 91,589 first-lactation heifers, daughters of 601 sires. Genetic parameters were estimated in a series of bivariate analyses. In turn, observations of each individual classifier were trait 1 and all observations of all other classifiers were grouped as trait 2. Likelihoods were used to test whether additive genetic or residual variances for each classifier (trait 1) differed significantly from the grouped records (trait 2), and to test whether the genetic correlation between trait 1 and trait 2 was significantly smaller than unity. Arbitrary criteria were set to mark traits for individual classifiers when a significant deviation was found: genetic correlations of < or = 0.40, and more than 15% deviation for the standard deviation. One classifier had relatively low heritabilities, but high genetic correlations with the others. This might indicate that the repeatability within classifier should be improved. Another classifier had high genetic correlations with the others, but his sire variances were significantly higher than average for most traits. For the genetic correlations, each classifier averaged 3.3 traits marked, ranging from 0 to 9. Overall feet and legs, rump width, central ligament, and foot angle received most marks (12 to 6 classifiers), but no disagreement existed on the definition (i.e., no mark) for body condition score, stature, rump angle, teat length, overall udder, and teat placement. These simple and cheap marks can be used in training sessions to improve the quality of the scoring system.

Animals↗

PubMed1985

Genetic, phenotypic and environmental relationships between sow body weight and sow productivity traits.

Yorkshire and Duroc litter records were used to estimate genetic, phenotypic and environmental relationships between sow body weight and sow productivity traits. Two data sets with two subsets each were used to complete this study; 663 and 460 records included litter traits only, while 522 and 359 records also contained sow body weight for Yorkshires and Durocs, respectively. Heritability estimates for number born (NB), number born alive (NBA), total birth weight of live pigs (BWLIT), litter weight at 3 wk (WT3WK), sow weight at parturition (WTDAMPAR) and sow weight at weaning (WTDAMWN) were .24 +/- .14, .21 +/- .14, .42 +/- .16, .19 +/- .14, .72 +/- .21 and .42 +/- .18, respectively, for Yorkshires and .05 +/- .10, .04 +/- .10, .21 +/- .14, .25 +/- .15, .85 +/- .25 and .87 +/- .26, respectively, for the Durocs. Repeatability estimates for NB, NBA, BWLIT, WT3WK, WTDAMPAR and WTDAMWN were .13 +/- .06, .17 +/- .06, .27 +/- .06, .13 +/- .06, .64 +/- .05 and .54 +/- .05, respectively, for Yorkshires and .17 +/- .06, .21 +/- .06, .14 +/- .06, .17 +/- .06, .28 +/- .07 and .39 +/- .07, respectively, for Durocs. Genetic correlations among litter traits were high and positive in the Yorkshire data. Genetic correlations between NBA and WTDAMPAR, NBA and WTDAMWN, WT3WK and WTDAMPAR, and WT3WK and WTDAMWN were .37 +/- .25, .18 +/- .34, .60 +/- .29 and .29 +/- .45, respectively, in the Yorkshire data. Genetic correlations among litter traits in the Duroc analysis had large standard errors but were generally similar to the estimates obtained from the Yorkshire data. The genetic correlation between WTDAMPAR and WTDAMWN was .93 +/- .09 for Yorkshire sows. The primary conclusion from this study is that as selection increases sow productivity traits, there will be a positive correlated response in sow body weight.

Analysis of Variance↗