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V. M.-R. Arnould 1 , N. Gengler 1,2 , and H. Soyeurt 1,2

V. M.-R. Arnould 1 , N. Gengler 1,2 , and H. Soyeurt 1,2 1 Gembloux Agricultural University, Animal Science Unit, Belgium 2 National Fund for Scientific Research, Belgium.

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V. M.-R. Arnould 1 , N. Gengler 1,2 , and H. Soyeurt 1,2

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  1. V. M.-R. Arnould1, N. Gengler1,2, and H. Soyeurt 1,2 1 Gembloux Agricultural University, Animal Science Unit, Belgium 2 National Fund for Scientific Research, Belgium Lactation Number Effects on the Genetic Variability of the Stearoyl Coenzyme-A Desaturase 9 Activity Estimated by Test-Day Model

  2. Context • Interest for human health • Many factors affecting milk fat composition have been reviewed (e.g., Palmquist et al., 1993; Soyeurt et al. 2006): • Feeding, season • Breed • Lactation stage • Number of lactation, age • ...

  3. Δ9 desaturase • Also named stearoyl Coenzyme-A desaturase or SCD • Able to introduce a cis-bond between carbons 9 and 10 of SFA • Involved in the production of the majority of MONO and CLA in milk

  4. General objective Study thegenetic variation of Δ9-desaturase activity in bovine milk within and between lactations using multitrait random regression test-day models

  5. Lactation stage effect • Milk fat composition significantly change with lactation stage (Stoop et al., 2008) • Principally due to changes in energy status

  6. Lactation number effect • Few information are available on lactation number effect on Δ9 activity • Lactation number effect = age effect ? • Contradictions / fat content: • Milk fat not affected by lactation number • Fat content decreases with increasing number of lactation (or age of cow)

  7. Lactation number effects • Contradictions / fat composition • No difference • The amount of UNSAT increases with increasing age • While palmitic acid decreases

  8. Materials & Methods • Data set • Spectra collected between January 2007 and October 2008 • Holstein cows (> 84%) • Milk history • 4 < DIM < 365 • Milk yield, %Fat, %Protein • Multi-trait random regression test-day models

  9. Materials & Methods • Lactations were grouped as following: • First lactation (39%) • Second lactation (29%) • Third and fourth lactations (32%) • Random herd-based data sub set

  10. Materials & Methods • Models: • Fixed effects: • Herd x date of test • Class of 15 days in milk (20) • Class of age (16) • Random effects: • Herd x year of calving • Permanent environment • Additive genetic effect • Residuals Second order Legendre Polynomials

  11. Studied traits • Milk yield • Fat content • Protein content • 3 Δ9 indices (product / substrate): • C14:1 cis-9/C14:0 • C16:1 cis-9/C16:0 • C18:1 cis-9/C18:0

  12. Studied traits

  13. Studied traits Similar statistical characteristics between population and sample data set

  14. Studied traits Slight increasing of milk yield with increasing number of lactation

  15. Studied traits No modification of fat content with increasing number of lactation

  16. Studied traits

  17. Studied traits Similar observations

  18. Results • Lactation stage effect

  19. HeritabilityLactation 1

  20. HeritabilityLactation 1 Variability of heritability C14:1 cis-9/C14:0 0.23 C16:1 cis-9/C16:0 0.11 C18:1 cis-9/C18:0 0.15

  21. HeritabilityLactation 1 Increasing of heritability values throughout the lactation

  22. Variance component Lactation 1 - C14:1 cis-9/C14:0

  23. Variance component Lactation 1 - C14:1 cis-9/C14:0 Increasing of genetic variance component throughout the lactation

  24. Results • Lactation number effect

  25. HeritabilityC14:1 cis-9/C14:0

  26. HeritabilityC14:1 cis-9/C14:0 C14:1 cis-9/C14:0 Lactation 1: 0.23 Lactation 2: 0.22 Lactations 3 et 4: 0.20

  27. HeritabilityC14:1 cis-9/C14:0 Similar trends of heritability estimates for lactations 1, 2, and 3 and 4

  28. HeritabilityC16:1 cis-9/C16:0 C18:1 cis-9/C18:0 Similar observations for C16:1 cis-9 /C16:0 and C18:1 cis-9/C18:0

  29. Heritability Few or none difference between lactations

  30. Genetic variance componentC14:1 cis-9/C14:0

  31. Genetic variance componentC14:1 cis-9/C14:0 Similar trends of genetic variance estimates for lactations 1, 2, and 3 and 4

  32. Genetic varianceC16:1 cis-9/C16:0 C18:1 cis-9/C18:0 Similar observations for C16:1 cis-9 /C16:0 and C18:1 cis-9/C18:0

  33. Results • Correlations

  34. Relationships C14:1 cis-9/C14:0 Genetic correlation Phenotypic correlation

  35. Relationships C14:1 cis-9/C14:0 Genetic correlation Phenotypic correlation

  36. Relationships C16:1 cis-9/C16:0 Genetic correlation Phenotypic correlation

  37. Relationships C18:1 cis-9/C18:0 Genetic correlation Phenotypic correlation

  38. RelationshipsC14:1 cis-9/C14:0

  39. Relationships C16:1 cis-9/C16:0 C18:1 cis-9/C18:0 Similar observations for C16:1 cis-9 /C16:0 and C18:1 cis-9/C18:0

  40. Spearman correlation • Application: • Sort sires according to their breeding values for C14:1 cis-9/C14:0 • Comparison among the lists of sires obtained for the 3 lactation groups

  41. Spearman correlation

  42. Spearman correlation • Conclusions: • The top 20 is similar for the 3 lactation groups • So, dairy cow in first lactation is as good in second or third lactation.

  43. Conclusions • Lactation stage effects • Genetic variability of Δ9 activity throughout lactation • Lactation number effects • None or few useful effects of lactation number on Δ9 activity

  44. Conclusions • The desaturation of milk fatty acids presents a substantial genetic component → possibility to modulate milk fat profile by selective breeding • Negative correlations between Δ9 activity (ratios) and fat and protein content: increasing activity of Δ9 → could inhibit the synthesis of fat and protein in bovine milk

  45. In the future • Study the difference between Δ9 activity estimator • Enlarge the studied number of lactation: per example: 1-3 vs 4-6

  46. Thank you for your attention Acknowledgments SPW – DGA-RNE project: D31-5593 (section 1) AWE Milk committee (Battice) FNRS: 2.4507.02F (2) F.4552.05 FRFC 2.4623.08 Email: arnould.v@fsagx.ac.be

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