Literature DB >> 30968112

Investigating causal biological relationships between reproductive performance traits in high-performing gilts and sows1.

Kessinee Chitakasempornkul1, Mariana B Meneget2, Guilherme J M Rosa3, Fernando B Lopes3, Abigail Jager1, Márcio A D Gonçalves4, Steve S Dritz2, Mike D Tokach5, Robert D Goodband5, Nora M Bello1.   

Abstract

Efficient management of swine production systems requires understanding of complex reproductive physiological mechanisms. Our objective in this study was to investigate potential causal biological relationships between reproductive performance traits in high-producing gilts and sows. Data originated from a nutrition experiment and consisted of 200 sows and 440 gilts arranged in body weight blocks and randomly assigned to dietary treatments during late gestation at a commercial swine farm. Reproductive performance traits consisted of weight gain during late gestation, total number born and number born alive in a litter, born alive average birth weight, wean-to-estrous interval, and total litter size born in the subsequent farrowing. Structural equation models combined with the inductive causation algorithm, both adapted to a hierarchical Bayesian framework, were employed to search for, estimate, and infer upon causal links between the traits within each parity group. Results indicated potentially distinct reproductive networks for gilts and for sows. Sows showed sparse connectivity between reproductive traits, whereas the network learned for gilts was densely interconnected, suggesting closely linked physiological mechanisms in younger females, with a potential for ripple effects throughout their productive lifecycle in response to early implementation of tailored managerial interventions. Cross-validation analyses indicated substantial network stability both for the general structure and for individual links, though results about directionality of such links were unstable in this study and will need further investigation. An assessment of relative statistical power in sows and gilts indicated that the observed network discrepancies may be partially explained on a biological basis. In summary, our results suggest distinctly heterogeneous mechanistic networks of reproductive physiology for gilts and sows, consistent with physiological differences between the groups. These findings have potential practical implications for integrated understanding and differential management of gilts and sows to enhance efficiency of swine production systems.
© The Author(s) 2019. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  hierarchical Bayesian models; structural equation model; structure learning; swine reproductive physiology

Mesh:

Year:  2019        PMID: 30968112      PMCID: PMC6541814          DOI: 10.1093/jas/skz115

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


  29 in total

1.  Responses in ovulation rate, embryonal survival, and litter traits in swine to 14 generations of selection to increase litter size.

Authors:  R K Johnson; M K Nielsen; D S Casey
Journal:  J Anim Sci       Date:  1999-03       Impact factor: 3.159

2.  Effect of season and outdoor climate on litter size at birth in purebred landrace and yorkshire sows in Thailand.

Authors:  Padet Tummaruk; Wichai Tantasuparuk; Mongkol Techakumphu; Annop Kunavongkrit
Journal:  J Vet Med Sci       Date:  2004-05       Impact factor: 1.267

3.  Quantitative genetic models for describing simultaneous and recursive relationships between phenotypes.

Authors:  Daniel Gianola; Daniel Sorensen
Journal:  Genetics       Date:  2004-07       Impact factor: 4.562

4.  Number of conceptuses in utero affects porcine fetal muscle development.

Authors:  S C Town; C T Putman; N J Turchinsky; W T Dixon; G R Foxcroft
Journal:  Reproduction       Date:  2004-10       Impact factor: 3.906

5.  An Analysis of Variability in Number of Digits in an Inbred Strain of Guinea Pigs.

Authors:  S Wright
Journal:  Genetics       Date:  1934-11       Impact factor: 4.562

6.  A structural equation model for describing relationships between somatic cell score and milk yield in dairy goats.

Authors:  G de los Campos; D Gianola; P Boettcher; P Moroni
Journal:  J Anim Sci       Date:  2006-11       Impact factor: 3.159

7.  Characterization of summer infertility of sows in large confinement units.

Authors:  J H Britt; V E Szarek; D G Levis
Journal:  Theriogenology       Date:  1983-07       Impact factor: 2.740

8.  Inferring relationships between somatic cell score and milk yield using simultaneous and recursive models.

Authors:  X-L Wu; B Heringstad; Y-M Chang; G de Los Campos; D Gianola
Journal:  J Dairy Sci       Date:  2007-07       Impact factor: 4.034

9.  Exploring biological relationships between calving traits in primiparous cattle with a Bayesian recursive model.

Authors:  Evangelina López de Maturana; Xiao-Lin Wu; Daniel Gianola; Kent A Weigel; Guilherme J M Rosa
Journal:  Genetics       Date:  2008-11-03       Impact factor: 4.562

Review 10.  Prenatal programming of postnatal development in the pig.

Authors:  G R Foxcroft; W T Dixon; M K Dyck; S Novak; J C S Harding; F C R L Almeida
Journal:  Soc Reprod Fertil Suppl       Date:  2009
View more
  3 in total

1.  Inferring phenotypic causal structure among farrowing and weaning traits in pigs.

Authors:  Toshihiro Okamura; Kazuo Ishii; Motohide Nishio; Guilherme J M Rosa; Masahiro Satoh; Osamu Sasaki
Journal:  Anim Sci J       Date:  2020 Jan-Dec       Impact factor: 1.749

2.  Utilization and reproductive performance of gilts in large-scale pig farming system with different production levels in China: a descriptive study.

Authors:  Ran Guan; Wenchao Gao; Peng Li; Xuwei Qiao; Jing Ren; Jian Song; Xiaowen Li
Journal:  Porcine Health Manag       Date:  2021-12-13

3.  Analysis of the causal structure of traits involved in sow lactation feed efficiency.

Authors:  Mónica Mora; Ingrid David; Hélène Gilbert; Guilherme J M Rosa; Juan Pablo Sánchez; Miriam Piles
Journal:  Genet Sel Evol       Date:  2022-07-26       Impact factor: 5.100

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.