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Animal Breeding &
Genomics Centre
Whole Genome Scan:
QTL for Milk Fat Composition in
Summer
Nazir A Ganai
Tuesday 24th
March 2009
Animal Breeding &
Genomics Centre
Milk Genomics Initiative
Aim: Identify opportunities to use genetic variation to
improve milk quality characteristics
 Milk quality:
 Milk-Protein composition
 Milk-fat composition
 Improve:
 Technological efficiency (production of cheese, butter)
 Innovative dairy products (e.g. promoting human health)
Animal Breeding &
Genomics Centre
Milk Fat composition
 Importance
Major energy component - 2.25 times caloric value of CHOs
Farmers: for economics
Industry: for quality dairy products
Designer Milk: for good health
An (indirect) aim of the Milk Genomics Initiative
MGI aims to find the QTL / genes underlying the variation of milk fat
composition
Ultimately propose genetic interventions to alter the milk fat composition for
good health and/or better processing qualities
Animal Breeding &
Genomics Centre
Human versus Cow milk composition
Constituent Human
milk
Cow milk
Protein % protein 1.3 % 3.5%
Casein : Whey protein 40:60 80:20
Fat % fat 3.9% 4.0%
Saturated 1.8 g/100g 2.5
Mono-Unsaturated 1.6 1.0
Poly-unsaturated 0.5 0.18
Animal Breeding &
Genomics Centre
Milk Fat Composition
Normal Milk
 Fat % 3 to 5%
 SFA ~68%
 MUFA ~27%
 PUFA ~5%
Ideal milk
 Fat % ~2%
 SFA < 8%
 MUFA 82%
 PUFA 10%
Animal Breeding &
Genomics Centre
Milk Fatty acids and human health
Type of Fat Role Effect
Sat. Fatty Acids Lauric acid (12:0)
Palmitic acid 16:0
Myristic acid
Raise LDL Cholestrol
•Atheroseclerosis
•High BP
•CHD
Trans fatty acids Trans 18:1
Unsat. Fatty
acids
Oleic acid cis 18:1
Linoleic acid 18:2
Linolenic acid 18:3
Lower LDL Cholestrol Good for health
Animal Breeding &
Genomics Centre
Milk Fat Profile
• 400 different FA in milk
• Different ways to classify
•Origin in Milk
•Short / Medium Chain: synthesized de novo
•Long Chain : preformed-
•Melting point:
•Saturated
•Un saturated
•Biological properties
•Good for health
•Bad
Animal Breeding &
Genomics Centre
 SFA ~68%
 MUFA~27%
 PUFA ~5%
C4:0 to C20:0
C14:0 = ~12%
C16:0 = ~30% Palmitic acid
C18:0 = ~10%
C10:1 to C18:1
C18:1cis9 = ~21%
C18:1trans = ~2.15%
C16:1 = ~1.4%
C14:1 = ~1.16%
C18:2 cis9,12 (Linoleic acid) 1.12
CLA cis9, trans11(C18:2) Rumenic acid 0.56
C18:3 cis9,12,15 α-Linolenic acid 0.50
Fatty Acid Profile
Animal Breeding &
Genomics Centre
Variability in milk fat composition
 Environmental:
 FA profile highly sensitive to the kind of feed
 Summer milk fat – low in saturated, high in unsaturated
Trait Summer Winter
UFA 29.24 25.5
C18trans 2.14 1.50
CLAcis 9, tr 11 0.56 0.39
C18:3 cis9,12,15 0.50 0.41
C16:0 29.0 32.6
Animal Breeding &
Genomics Centre
Heritability
 Short and medium chain 0.23 to 0.57
 Long chain FA 0.12 to 0.33
 Genes involved in biosynthesis of milk : > 40
 To find genes causing genetic variation :
difficult
 Therefore, the first approach to is find QTL
underlying the genetic variation
Animal Breeding &
Genomics Centre
Aim
 To find QTL for milk fat composition in summer
 Compare the results with winter milk fat analysis
Animal Breeding &
Genomics Centre
Material & Methods
• Resource population
• 1905 Cows
• 398 herds
• 7-sire families
• Milk sampling
• Summer
• Marker Map: 1341 SNPs over 29 autosomes
• Analysis: Multi-marker regression analysis
Animal Breeding &
Genomics Centre
Genome Scan Results
 Total fat Traits: 46
 Significant QTL (PGenome <0.05) : 4
 BTA14, BTA15, BTA26, BTA27
 Variation explained in: 33 traits
 Suggestive QTL: 20
 Variation explained in: 44 traits
Animal Breeding &
Genomics Centre
Resource population
873 cows
50 bulls
5 bulls
848 cows
Animal Breeding &
Genomics Centre
Material & Methods
 Milk sample
 Capillary zone
electrophoresis
 Blood sample
 DNA analyses
• 1912
• 398
• Pedigree
• 1
• Winter
• 1
Minutes
-6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22
AU
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
AU
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
BSA56141
BSA114802
34243
a-lac943014
b-Lg-B2130515b-Lg-A1505886
1800076577877559
1163910
1373411
2897212
4386713
a-Cas-S2143209146167315
12240316
17162117
22288018
a-Cas-S1129719819
3363020
3980421
a-Cas-S053015322
34383233821324
k-Cas25819125
5743226
b-Cas-B5112327
10199528
b-Cas-A1109282729
865930
b-Cas-A2107159931
13083832
747633
1154334
1176735
2395336
3382437
3112738
1297539
212440
3170341
950742
2134343
2924844
2757745
PDA- 214nm
11891
Name
Area
Pk #
Animal Breeding &
Genomics Centre
Detection of DNA regions
 Using 1341 Single Nucleotide Polymorphisms
(SNPs) as genetic markers
Ind 1 CACCGCGCCT GGTCCC G TTT TGGCTATTCT
CACCGCGCCT GGTCCC G TTT TGGCTATTCT
Ind 2 CACCGCGCCT GGTCCC A TTT TGGCTATTCT
CACCGCGCCT GGTCCC A TTT TGGCTATTCT
 Genetic markers can be used to reconstruct the
inheritance from parents to offspring
Animal Breeding &
Genomics Centre
Animal Breeding &
Genomics Centre
BTA-14: Long Chain Fatty Acids
0
5
10
15
20
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101
cM
Fvalue
0
0.25
0.5
0.75
1
InformationContent
C18:1
C18:1cis9
C18:2
C18:2 cis9,12
c183
fat%
ratio SFA/UFA
SFA
Total index
UFA
IC
BTA-14: Medium & Shrot Chain FA
0
2
4
6
8
10
12
14
16
18
1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101
cM
Fvalue
0
0.25
0.5
0.75
1
InformationContent
C7:0
C9:0
C11:0
C13:0
C16:0
C16:1
IC
Animal Breeding &
Genomics Centre
BTA 26: QTL at 28 cM for Mono-unsaturated Fatty Acids
0
5
10
15
1 11 21 31 41 51 61
Fvalue
0
0.25
0.5
0.75
1
InformationContent
C10:1
C14:1
C16:1
C10index
C12index
C14index
C16index
IC
Animal Breeding &
Genomics Centre
Variance explained by DNA regions
Chromosome Trait VQTL
(%)
14 Fat% 12
SFA 9.2
UFA 8.7
FA 3 - 10%
26
27
MUFA
C5:0, C11:0
1 – 4%
1.3 – 1.8%
Animal Breeding &
Genomics Centre
Comparison between results on summer & winter
samples
#BTA Position Summer Fat Winter Fat
6 - - C6:0, C8:0
14 0 cM 24 traits 21 traits : same
Exceptions: C6:0, C8:0, C10:0
15 38 cM
9 cM
C4:0
C17:0
C18:1 trans
16 - - C18index
CLAindex
19 - - C14:0
26 28 cM MUFA MUFA
27 6 cM Odd Chain FA
C5 : C13
-
Animal Breeding &
Genomics Centre
Comparison for individual FA
Trait rA
Chromosomes with QTL
Winter Summer
fat% 0.97 6,8,11,13,14,27 5,7,8,13,14
C4:0 0.95 2,7,19,25,27 15,18
C6:0 0.94 2,6,13,23 13,14,15
C8:0 0.94 6,14,17,29 13,14
C14:0 0.93 14,19,22,26 15,21,29
C16:0 0.78 1,4,6,9,11,14 5,14,19,24
C18:0 0.84 1,11,16,19 8,11,21,23
C18:1 cis 9 14,21 14,24,28
C16:1 1,6,13,14,19,26, 14,15,18,26,
C14:1 26,13,19 8,11,15,26
C18:2 cis 9,12 0.96 7,11,12,14 14
CLA cis9, trans 11 0.82 11,14,17 14,29
C18:3 cis9,12,15 0.83 3,14,22 9,11,14,21
Animal Breeding &
Genomics Centre
Conclusion (for summer milk fat)
 Detected 4 QTL on BTA14, 15, 26 and 27 for summer milk fat
composition.
 QTL on BTA14 significantly influenced most of the traits, both saturated
and unsaturated.
 QTL on BTA15 influenced the saturated FA only (C4:0 and C17:0).
 QTL on BTA26 specifically influenced MUFA. The source of such FA
in milk is the desaturation activity of enzyme SCD, for which the gene
has been already mapped to BTA26.
 QTL on BTA27 specifically influenced odd-chain Saturated FA.
The origin of such FA is different from even-chain FA.
Animal Breeding &
Genomics Centre
Summer vs Winter milk fat composition
 Similarities:
 Only two QTL on BTA14 and BTA26 influence the same traits in both
seasons.
 Differences:
 3 QTL on BTA6, 16, 29 influenced fat composition in winter milk only.
 QTL on BTA27 is influenced fat composition in Summer milk only.
 All the suggestive QTL on 23 other autosomes influenced different traits
in two seasons.
 This lack of consistency :
 background effects like : epistasis and environmental
interactions,
 less powerful experimental design (half-sib structure) for QTL analysis.
Animal Breeding &
Genomics Centre
Opportunities for genetic selection
Health Promoting
(low fat %)I beleive there is a
long way before we
can modulate the
milk fat composition
for a Designer Milk
through marker
assisted selection !!
Animal Breeding &
Genomics Centre
Thank You for your attention!

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Nlm presentation qtl for fat

  • 1. Animal Breeding & Genomics Centre Whole Genome Scan: QTL for Milk Fat Composition in Summer Nazir A Ganai Tuesday 24th March 2009
  • 2. Animal Breeding & Genomics Centre Milk Genomics Initiative Aim: Identify opportunities to use genetic variation to improve milk quality characteristics  Milk quality:  Milk-Protein composition  Milk-fat composition  Improve:  Technological efficiency (production of cheese, butter)  Innovative dairy products (e.g. promoting human health)
  • 3. Animal Breeding & Genomics Centre Milk Fat composition  Importance Major energy component - 2.25 times caloric value of CHOs Farmers: for economics Industry: for quality dairy products Designer Milk: for good health An (indirect) aim of the Milk Genomics Initiative MGI aims to find the QTL / genes underlying the variation of milk fat composition Ultimately propose genetic interventions to alter the milk fat composition for good health and/or better processing qualities
  • 4. Animal Breeding & Genomics Centre Human versus Cow milk composition Constituent Human milk Cow milk Protein % protein 1.3 % 3.5% Casein : Whey protein 40:60 80:20 Fat % fat 3.9% 4.0% Saturated 1.8 g/100g 2.5 Mono-Unsaturated 1.6 1.0 Poly-unsaturated 0.5 0.18
  • 5. Animal Breeding & Genomics Centre Milk Fat Composition Normal Milk  Fat % 3 to 5%  SFA ~68%  MUFA ~27%  PUFA ~5% Ideal milk  Fat % ~2%  SFA < 8%  MUFA 82%  PUFA 10%
  • 6. Animal Breeding & Genomics Centre Milk Fatty acids and human health Type of Fat Role Effect Sat. Fatty Acids Lauric acid (12:0) Palmitic acid 16:0 Myristic acid Raise LDL Cholestrol •Atheroseclerosis •High BP •CHD Trans fatty acids Trans 18:1 Unsat. Fatty acids Oleic acid cis 18:1 Linoleic acid 18:2 Linolenic acid 18:3 Lower LDL Cholestrol Good for health
  • 7. Animal Breeding & Genomics Centre Milk Fat Profile • 400 different FA in milk • Different ways to classify •Origin in Milk •Short / Medium Chain: synthesized de novo •Long Chain : preformed- •Melting point: •Saturated •Un saturated •Biological properties •Good for health •Bad
  • 8. Animal Breeding & Genomics Centre  SFA ~68%  MUFA~27%  PUFA ~5% C4:0 to C20:0 C14:0 = ~12% C16:0 = ~30% Palmitic acid C18:0 = ~10% C10:1 to C18:1 C18:1cis9 = ~21% C18:1trans = ~2.15% C16:1 = ~1.4% C14:1 = ~1.16% C18:2 cis9,12 (Linoleic acid) 1.12 CLA cis9, trans11(C18:2) Rumenic acid 0.56 C18:3 cis9,12,15 α-Linolenic acid 0.50 Fatty Acid Profile
  • 9. Animal Breeding & Genomics Centre Variability in milk fat composition  Environmental:  FA profile highly sensitive to the kind of feed  Summer milk fat – low in saturated, high in unsaturated Trait Summer Winter UFA 29.24 25.5 C18trans 2.14 1.50 CLAcis 9, tr 11 0.56 0.39 C18:3 cis9,12,15 0.50 0.41 C16:0 29.0 32.6
  • 10. Animal Breeding & Genomics Centre Heritability  Short and medium chain 0.23 to 0.57  Long chain FA 0.12 to 0.33  Genes involved in biosynthesis of milk : > 40  To find genes causing genetic variation : difficult  Therefore, the first approach to is find QTL underlying the genetic variation
  • 11. Animal Breeding & Genomics Centre Aim  To find QTL for milk fat composition in summer  Compare the results with winter milk fat analysis
  • 12. Animal Breeding & Genomics Centre Material & Methods • Resource population • 1905 Cows • 398 herds • 7-sire families • Milk sampling • Summer • Marker Map: 1341 SNPs over 29 autosomes • Analysis: Multi-marker regression analysis
  • 13. Animal Breeding & Genomics Centre Genome Scan Results  Total fat Traits: 46  Significant QTL (PGenome <0.05) : 4  BTA14, BTA15, BTA26, BTA27  Variation explained in: 33 traits  Suggestive QTL: 20  Variation explained in: 44 traits
  • 14. Animal Breeding & Genomics Centre Resource population 873 cows 50 bulls 5 bulls 848 cows
  • 15. Animal Breeding & Genomics Centre Material & Methods  Milk sample  Capillary zone electrophoresis  Blood sample  DNA analyses • 1912 • 398 • Pedigree • 1 • Winter • 1 Minutes -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 AU 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 AU 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 BSA56141 BSA114802 34243 a-lac943014 b-Lg-B2130515b-Lg-A1505886 1800076577877559 1163910 1373411 2897212 4386713 a-Cas-S2143209146167315 12240316 17162117 22288018 a-Cas-S1129719819 3363020 3980421 a-Cas-S053015322 34383233821324 k-Cas25819125 5743226 b-Cas-B5112327 10199528 b-Cas-A1109282729 865930 b-Cas-A2107159931 13083832 747633 1154334 1176735 2395336 3382437 3112738 1297539 212440 3170341 950742 2134343 2924844 2757745 PDA- 214nm 11891 Name Area Pk #
  • 16. Animal Breeding & Genomics Centre Detection of DNA regions  Using 1341 Single Nucleotide Polymorphisms (SNPs) as genetic markers Ind 1 CACCGCGCCT GGTCCC G TTT TGGCTATTCT CACCGCGCCT GGTCCC G TTT TGGCTATTCT Ind 2 CACCGCGCCT GGTCCC A TTT TGGCTATTCT CACCGCGCCT GGTCCC A TTT TGGCTATTCT  Genetic markers can be used to reconstruct the inheritance from parents to offspring
  • 18. Animal Breeding & Genomics Centre BTA-14: Long Chain Fatty Acids 0 5 10 15 20 1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 cM Fvalue 0 0.25 0.5 0.75 1 InformationContent C18:1 C18:1cis9 C18:2 C18:2 cis9,12 c183 fat% ratio SFA/UFA SFA Total index UFA IC BTA-14: Medium & Shrot Chain FA 0 2 4 6 8 10 12 14 16 18 1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 cM Fvalue 0 0.25 0.5 0.75 1 InformationContent C7:0 C9:0 C11:0 C13:0 C16:0 C16:1 IC
  • 19. Animal Breeding & Genomics Centre BTA 26: QTL at 28 cM for Mono-unsaturated Fatty Acids 0 5 10 15 1 11 21 31 41 51 61 Fvalue 0 0.25 0.5 0.75 1 InformationContent C10:1 C14:1 C16:1 C10index C12index C14index C16index IC
  • 20. Animal Breeding & Genomics Centre Variance explained by DNA regions Chromosome Trait VQTL (%) 14 Fat% 12 SFA 9.2 UFA 8.7 FA 3 - 10% 26 27 MUFA C5:0, C11:0 1 – 4% 1.3 – 1.8%
  • 21. Animal Breeding & Genomics Centre Comparison between results on summer & winter samples #BTA Position Summer Fat Winter Fat 6 - - C6:0, C8:0 14 0 cM 24 traits 21 traits : same Exceptions: C6:0, C8:0, C10:0 15 38 cM 9 cM C4:0 C17:0 C18:1 trans 16 - - C18index CLAindex 19 - - C14:0 26 28 cM MUFA MUFA 27 6 cM Odd Chain FA C5 : C13 -
  • 22. Animal Breeding & Genomics Centre Comparison for individual FA Trait rA Chromosomes with QTL Winter Summer fat% 0.97 6,8,11,13,14,27 5,7,8,13,14 C4:0 0.95 2,7,19,25,27 15,18 C6:0 0.94 2,6,13,23 13,14,15 C8:0 0.94 6,14,17,29 13,14 C14:0 0.93 14,19,22,26 15,21,29 C16:0 0.78 1,4,6,9,11,14 5,14,19,24 C18:0 0.84 1,11,16,19 8,11,21,23 C18:1 cis 9 14,21 14,24,28 C16:1 1,6,13,14,19,26, 14,15,18,26, C14:1 26,13,19 8,11,15,26 C18:2 cis 9,12 0.96 7,11,12,14 14 CLA cis9, trans 11 0.82 11,14,17 14,29 C18:3 cis9,12,15 0.83 3,14,22 9,11,14,21
  • 23. Animal Breeding & Genomics Centre Conclusion (for summer milk fat)  Detected 4 QTL on BTA14, 15, 26 and 27 for summer milk fat composition.  QTL on BTA14 significantly influenced most of the traits, both saturated and unsaturated.  QTL on BTA15 influenced the saturated FA only (C4:0 and C17:0).  QTL on BTA26 specifically influenced MUFA. The source of such FA in milk is the desaturation activity of enzyme SCD, for which the gene has been already mapped to BTA26.  QTL on BTA27 specifically influenced odd-chain Saturated FA. The origin of such FA is different from even-chain FA.
  • 24. Animal Breeding & Genomics Centre Summer vs Winter milk fat composition  Similarities:  Only two QTL on BTA14 and BTA26 influence the same traits in both seasons.  Differences:  3 QTL on BTA6, 16, 29 influenced fat composition in winter milk only.  QTL on BTA27 is influenced fat composition in Summer milk only.  All the suggestive QTL on 23 other autosomes influenced different traits in two seasons.  This lack of consistency :  background effects like : epistasis and environmental interactions,  less powerful experimental design (half-sib structure) for QTL analysis.
  • 25. Animal Breeding & Genomics Centre Opportunities for genetic selection Health Promoting (low fat %)I beleive there is a long way before we can modulate the milk fat composition for a Designer Milk through marker assisted selection !!
  • 26. Animal Breeding & Genomics Centre Thank You for your attention!

Editor's Notes

  1. Quality characteristics are mainly related to milk-fat and milk-protein composition. Improvements may imply technological efficiency, such as production of cheese or butter, where you can think of yield or colour. Improvements may also imply innovative products, such as products promoting human health. Some examples of products with beneficial effects on human health are given on the next slide.