Literature DB >> 15827242

Selection for placental efficiency in swine: genetic parameters and trends.

H Mesa1, T J Safranski, K A Fischer, K M Cammack, W R Lamberson.   

Abstract

The objectives of this study were to estimate response to divergent selection for an index of placental efficiency in swine, and to evaluate the effect of placental efficiency on litter size. The selection index (SI) included total born (TB), birth weight (BRWT), and placental weight (PW), and was designed to increase in the high line (H) or decrease in the low line (L) the efficiency of the placental function (PE), defined as the ratio BRWT:PW. (Co)variance components were estimated for direct and maternal additive effects by using an animal model with MTDFREML procedures. Estimated breeding values were calculated by using records on individual BRWT (n = 2,111), PW (n = 2,006), PE (n = 1,677), and SI (n = 1,677). Litter traits were evaluated using records on 193 litters. The model included the fixed effects of contemporary group for all traits, with the addition of sex for individual traits and parity for litter traits. Litter was fitted as an uncorrelated random effect for all traits, and TB was used as a linear and quadratic covariate for BRWT, PW, and PE. Direct heritability estimates from single-trait models were 0.03, 0.25, 0.18, 0.11, and 0.08 for BRWT, PW, PE, SI, and TB, respectively. Estimated breeding values were compared between lines by using a model including generation, line within generation, and replicate within line as the error term. Estimates of genetic divergence were 20.7 +/- 2.7 g, 0.24 +/- 0.03, 0.11 +/- 0.02, and 0.07 +/- 0.02 per generation for PW, PE, SI, and TB, respectively (P < 0.01), but divergence was not significant for BRWT. At Generation 4, direct EBV was higher in L than in H for PW (55.9 +/- 8.7 vs. -24.2 +/- 9.5 g, respectively; P < 0.01) and higher in H than in L for PE (0.58 +/- 0.10 vs. -0.35 +/- 0.09 g, respectively; P < 0.01). However, EBV was not different for BRWT, SI, or TB. These results indicate that PW and PE are susceptible to change by genetic selection; however, the correlated response in TB was an unexpected genetic trend toward a higher TB in L of 0.05 +/- 0.01 piglets per generation (P < 0.01).

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Year:  2005        PMID: 15827242     DOI: 10.2527/2005.835983x

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  6 in total

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Journal:  Biol Reprod       Date:  2010-06-23       Impact factor: 4.285

2.  Factors contributing to the variation in placental efficiency on days 70, 90, and 110 of gestation in gilts.

Authors:  Shanice K Krombeen; William C Bridges; Matthew E Wilson; Tiffany A Wilmoth
Journal:  J Anim Sci       Date:  2019-01-01       Impact factor: 3.159

Review 3.  Placental accommodations for transport and metabolism during intra-uterine crowding in pigs.

Authors:  Jeffrey L Vallet; Anthony K McNeel; Jeremy R Miles; Bradley A Freking
Journal:  J Anim Sci Biotechnol       Date:  2014-12-15

4.  Protein expression profiles in Meishan and Duroc sows during mid-gestation reveal differences affecting uterine capacity, endometrial receptivity, and the maternal-fetal Interface.

Authors:  Kejun Wang; Kaijie Yang; Qiao Xu; Yufang Liu; Wenting Li; Ying Bai; Jve Wang; Cui Ding; Ximing Liu; Qiguo Tang; Yabiao Luo; Jie Zheng; Keliang Wu; Meiying Fang
Journal:  BMC Genomics       Date:  2019-12-17       Impact factor: 3.969

5.  Differences in X-chromosome transcriptional activity and cholesterol metabolism between placentae from swine breeds from Asian and Western origins.

Authors:  Steve R Bischoff; Shengdar Q Tsai; Nicholas E Hardison; Alison A Motsinger-Reif; Bradley A Freking; Dan J Nonneman; Gary A Rohrer; Jorge A Piedrahita
Journal:  PLoS One       Date:  2013-01-31       Impact factor: 3.240

6.  DNA methylation patterns and gene expression associated with litter size in Berkshire pig placenta.

Authors:  Jung Hye Hwang; Sang Mi An; Seulgi Kwon; Da Hye Park; Tae Wan Kim; Deok Gyeong Kang; Go Eun Yu; Il-Suk Kim; Hwa Chun Park; Jeongim Ha; Chul Wook Kim
Journal:  PLoS One       Date:  2017-09-07       Impact factor: 3.240

  6 in total

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