Genetics of Sow Longevity

The objective of this study was to estimate direct and indirect selection potential for length of productive life and lifetime prolificacy. In order to study the direct selection potential, the heritabilities of these traits were estimated. The genetic correlations of length of productive life and lifetime prolificacy with prolificacy traits and overall leg conformation were estimated to evaluate if selection for these traits could indirectly improve measures of sow longevity. In addition, correlations between length of productive life, lifetime prolificacy, daily gain, and backfat thickness were estimated. Records were utilized from Finnish purebred Landrace (n=26,744) and Large White (n=24,007) sows born on operations that perform on-farm production tests on all females. Heritabilities were estimated using both a survival analysis procedure and a linear model. Due to computational limitations, correlations were estimated with the linear model only. Estimated length of productive life heritabilities obtained from linear model analyses were lower (0.05 to 0.10) than those obtained from survival analyses (0.16 to 0.19). This may be indicative of the superiority of survival analysis compared to linear model analysis methods when evaluating longevity or similar types of data. All the prolificacy traits were genetically correlated with length of productive life and lifetime prolificacy and the correlations were greater than 0.13. These results indicate that selection for increased number of piglets weaned in the first litter and for short first farrowing interval is beneficial for sow longevity and also for sow’s lifetime prolificacy. The genetic correlations between length of productive life and leg conformation score were also favorable (0.32 in Landrace and 0.17 in Large White). The heritabilty estimates indicate that survival analysis is likely the most appropriate method of evaluating longevity traits in swine. Because of computational problems, simultaneous analysis of linear traits and longevity is not currently possible. More research is needed to develop methods for multiple linear and survival trait analyses

A Comparison of Six Maternal Genetic Lines for Sow Longevity

Data from the National Pork Producers Council Maternal Line National Genetic Evaluation Program were used to compare the sow longevity of six different genetic lines, and to estimate the associations of gilt backfat thickness, age at first farrowing, litter size at first farrowing, litter weight at first farrowing, average feed intake during lactation, and average backfat loss during lactation with sow longevity. The lines evaluated were American Diamond Genetics, Danbred North America, Dekalb-Monsanto DK44, Dekalb-Monsanto GPK347, Newsham Hybrids, and National Swine Registry. The results suggest that the sows of Dekalb-Monsanto GPK347 had a clearly lower risk of being culled than the sows of other five lines. Moreover, the shape of the survival distribution function of Delkab- Monsanto GPK347 is clearly different than the other five lines. There were high culling rates due to reproductive failure after first weaning in the sows of the five other lines, however this increased culling rate did not exist in the Dekalb-Monsanto GPK347 line. The results further suggest that sows with lower feed intake and greaterer backfat loss during lactation had the shorter productive lifetime. These between line differences indicate that it is possible to select for sow longevity. More research is needed to show the most efficient methods to select for sow longevity

Effect of Piglet Birth Weight and Weaning Weight on Nursery Off-Test Weight

Management of lightweight pigs is a challenge that many swine producers face. The number and actual weight of lightweight market hogs can directly impact production and marketing decisions as well as disrupt pig flow on a time-sensitive management system. Pigs that have lower birth weights frequently have lower weaning weights and remain a problem through the grow/finish phases of production. The objective of this study was to evaluate the effect of piglet birth weight and weaning weight on nursery off-test weight and to evaluate the linearity of these relationships. These data could be used by commercial producers to determine if it is effective to maintain lightweight piglets at birth or whether euthanasia might be a better option for pigs with low birth weights

Genetic relationship between purebred and crossbred sow longevity

Background The overall breeding objective for a nucleus swine selection program is to improve crossbred commercial performance. Most genetic improvement programs are based on an assumed high degree of positive relationship between purebred performance in a nucleus herd and their relatives’ crossbred performance in a commercial herd. The objective of this study was to examine the relationship between purebred and crossbred sow longevity performance. Sow longevity was defined as a binary trait with a success occurring if a sow remained in the herd for a certain number of parities and including the cumulative number born alive as a measure of reproductive success. Heritabilities, genetic correlations, and phenotypic correlations were estimated using THRGIBBS1F90. Results Results indicated little to no genetic correlations between crossbred and purebred reproductive traits. This indicates that selection for longevity or lifetime performance at the nucleus level may not result in improved longevity and lifetime performance at the crossbred level. Early parity performance was highly correlated with lifetime performance indicating that an indicator trait at an early parity could be used to predict lifetime performance. This would allow a sow to have her own record for the selection trait before she has been removed from the herd. Conclusions Results from this study aid in quantifying the relationship between purebred and crossbred performance and provide information for genetic companies to consider when developing a selection program where the objective is to improve crossbred sow performance. Utilizing crossbred records in a selection program would be the best way to improve crossbred sow productivity

Genetic associations for gilt growth, compositional, and structural soundness traits with sow longevity and lifetime reproductive performance

The objective of this study was to estimate genetic associations for gilt growth, compositional, and structural soundness with sow longevity and lifetime reproduction. Performance and pedigree information from 1,447 commercial females from 2 genetic lines were included in the data analyzed. Growth was expressed as days to 113.5 kg BW (DAYS) and compositional traits included loin muscle area (LMA), 10th rib backfat (BF10), and last rib backfat (LRF). Structural soundness traits included body structure traits [length (BL), depth (BD), width (BWD), rib shape (BRS), top line (BTL), and hip structure (BHS)], leg structure traits [front legs: legs turned (FLT), buck knees (FBK), pastern posture (FPP), foot size (FFS), and uneven toes (FUT); rear legs: legs turned (RLT), leg posture (RLP), pastern posture (RPP), foot size (RFS), and uneven toes (RUT)], and overall leg action (OLA). Lifetime (LT) and removal parity (RP) were considered as longevity traits whereas lifetime reproductive traits included lifetime total number born (LNB), lifetime number born alive (LBA), number born alive per lifetime day (LBA/LT), and percentage productive days from total herd days (PD%). Genetic parameters were estimated with linear animal models using the average information REML algorithm. Second, to account for censored longevity and lifetime reproduction records, genetic parameters were estimated using Markov Chain Monte Carlo and Gibbs sampling methods. Similar estimates were obtained across the analysis methods. Heritability estimates for growth and compositional traits ranged from 0.50 to 0.70 and for structural soundness traits from 0.07 to 0.31. Longevity and lifetime reproductive trait heritability estimates ranged from 0.14 to 0.17 when REML was used. Unfavorable genetic correlations were obtained for DAYS with LT, RP, LNB, LBA, and PD% and for LRF with PD%. However, LMA was favorably associated with LT, RP, and LNB. Moderate to high correlations were obtained for BL and BRS with all longevity and lifetime reproductive traits. Correlations of BWD with LT and RP were moderate. Associations for leg soundness traits with longevity and lifetime reproductive traits were mainly low and nonsignificant (P ≥ 0.10). However, RLP was moderately correlated with LBA/LT and PD%. Current results indicate that selection for fewer DAYS has an antagonistic effect on lifetime performance. Furthermore, great BL, flat BRS, narrow BWD, and upright RLP seem detrimental to sow longevity and lifetime reproduction

Whole-genome SNP association analysis of reproduction traits in the Finnish Landrace pig breed

<p>Abstract</p> <p>Background</p> <p>Good genetic progress for pig reproduction traits has been achieved using a quantitative genetics-based multi-trait BLUP evaluation system. At present, whole-genome single nucleotide polymorphisms (SNP) panels provide a new tool for pig selection. The purpose of this study was to identify SNP associated with reproduction traits in the Finnish Landrace pig breed using the Illumina PorcineSNP60 BeadChip.</p> <p>Methods</p> <p>Association of each SNP with different traits was tested with a weighted linear model, using SNP genotype as a covariate and animal as a random variable. Deregressed estimated breeding values of the progeny tested boars were used as the dependent variable and weights were based on their reliabilities. Statistical significance of the associations was based on Bonferroni-corrected <it>P</it>-values.</p> <p>Results</p> <p>Deregressed estimated breeding values were available for 328 genotyped boars. Of the 62 163 SNP in the chip, 57 868 SNP had a call rate > 0.9 and 7 632 SNP were monomorphic. Statistically significant results (<it>P</it>-value < 2.0E-06) were obtained for total number of piglets born in first and later parities and piglet mortality between birth and weaning in later parity, and suggestive associations (<it>P</it>-value < 4.0E-06) for piglet mortality between birth and weaning in first parity, number of stillborn piglets in later parity, first farrowing interval and second farrowing interval. Two of the statistically significant regions for total number of piglets born in first and later parities are located on chromosome 9 around 95 and 79 Mb. The estimated SNP effect in these regions was approximately one piglet between the two homozygote classes. By combining the two most significant SNP in these regions, favourable double homozygote animals are expected to have 1.3 piglets (<it>P</it>-value = 1.69E-08) more than unfavourable double homozygote animals. A region on chromosome 9 (66 Mb) was statistically significant for piglet mortality between birth and weaning in later parity (0.44 piglets between homozygotes, <it>P</it>-value = 6.94E-08).</p> <p>Conclusions</p> <p>Three separate regions on chromosome 9 gave significant results for litter size and pig mortality. The frequencies of favourable alleles of the significant SNP are moderate in the Finnish Landrace population and these SNP are thus valuable candidates for possible marker-assisted selection.</p

Heritability of longevity in Large White and Landrace sows using continuous time and grouped data models

<p>Abstract</p> <p>Background</p> <p>Using conventional measurements of lifetime, it is not possible to differentiate between productive and non-productive days during a sow's lifetime and this can lead to estimated breeding values favoring less productive animals. By rescaling the time axis from continuous to several discrete classes, grouped survival data (discrete survival time) models can be used instead.</p> <p>Methods</p> <p>The productive life length of 12319 Large White and 9833 Landrace sows was analyzed with continuous scale and grouped data models. Random effect of herd*year, fixed effects of interaction between parity and relative number of piglets, age at first farrowing and annual herd size change were included in the analysis. The genetic component was estimated from sire, sire-maternal grandsire, sire-dam, sire-maternal grandsire and animal models, and the heritabilities computed for each model type in both breeds.</p> <p>Results</p> <p>If age at first farrowing was under 43 weeks or above 60 weeks, the risk of culling sows increased. An interaction between parity and relative litter size was observed, expressed by limited culling during first parity and severe risk increase of culling sows having small litters later in life. In the Landrace breed, heritabilities ranged between 0.05 and 0.08 (s.e. 0.014-0.020) for the continuous and between 0.07 and 0.11 (s.e. 0.016-0.023) for the grouped data models, and in the Large White breed, they ranged between 0.08 and 0.14 (s.e. 0.012-0.026) for the continuous and between 0.08 and 0.13 (s.e. 0.012-0.025) for the grouped data models.</p> <p>Conclusions</p> <p>Heritabilities for length of productive life were similar with continuous time and grouped data models in both breeds. Based on these results and because grouped data models better reflect the economical needs in meat animals, we conclude that grouped data models are more appropriate in pig.</p

Regional perinatal mortality differences in the Netherlands; care is the question

Background. Perinatal mortality is an important indicator of health. European comparisons of perinatal mortality show an unfavourable position for the Netherlands. Our objective was to study regional variation in perinatal mortality within the Netherlands and to identify possible explanatory factors for the found differences. Methods. Our study population comprised of all singleton births (904,003) derived from the Netherlands Perinatal Registry for the period 2000-2004. Perinatal mortality including stillbirth from 22+0weeks gestation and early neonatal death (0-6 days) was our main outcome measure. Differences in perinatal mortality were calculated between 4 distinct geographical regions North-East-South-West. We tried to explain regional differences by adjustment for the demographic factors maternal age, parity and ethnicity and by socio-economic status and urbanisation degree using logistic modelling. In addition, regional differences in mode of delivery and risk selection were analysed as health care factors. Finally, perinatal mortality was analysed among five distinct clinical risk groups based on the mediating risk factors gestational age and congenital anomalies. Results. Overall perinatal mortality was 10.1 per 1,000 total births over the period 2000-2004. Perinatal mortality was elevated in the northern region (11.2 per 1,000 total births). Perinatal mortality in the eastern, western and southern region was 10.2, 10.1 and 9.6 per 1,000 total births respectively. Adjustment for demographic factors increased the perinatal mortality risk in the northern region (odds ratio 1.20, 95% CI 1.12-1.28, compared to reference western region), subsequent adjustment for socio-economic status and urbanisation explained a small part of the elevated risk (odds ratio 1.11, 95% CI 1.03-1.20). Risk group analysis showed that regional differences were absent among very preterm births (22+0- 25+6weeks gestation) and most prominent among births from 32+0gestation weeks onwards and among children with severe congenital anomalies. Among term births (37+0weeks) regional mortality differences were largest for births in women transferred from low to high risk during delivery. Conclusion. Regional differences in perinatal mortality exist in the Netherlands. These differences could not be explained by demographic or socio-economic factors, however clinical risk group analysis showed indications for a role of health care factors