Skip to main content

Table 6 Regions with large variance in local GEBV from BayesR for milk production traits

From: Improved precision of QTL mapping using a nonlinear Bayesian method in a multi-breed population leads to greater accuracy of across-breed genomic predictions

Gp

BTA

Window mid-point

Breed

Trait

Total loci

Best candidate (mammary exp*)

  

Start

Stop

 

FY

MY

PY

F%

P%

FY-

5

93.375

94.075

H/J3

++

--

-

++

++

4

MGST1(+)

FY-

14

1.325

2.225

H/J1,3

++

--

--

++

++

70

DGAT1

FY-

27

36.075

36.375

H/J3

++

-

-

++

 

9

AGPAT6(+)

FY+

15

35.125

35.275

H/J

++

 

+

  

4

TPH1(−)

FY+

23

28.575

28.775

H/J

++

+

+

 

-

18

.

FYn

2

118.975

119.175

J

   

++

+

11

.

FYn

6

28.675

28.875

H

++

    

2

.

FYn

19

51.225

51.425

H/J

++

  

+

 

18

FASN(+)

FYn

26

21.025

21.225

H/J

++

  

+

 

15

SCD(+)

MY-

3

15.375

15.725

H/J3

 

+

-

-

--

33

MUC1(+)

MY-

11

104.125

104.325

H/J

  

-

 

--

25

ENTAG.12525(+)

MY+

1

144.325

144.525

H/J3

+

++

+

-

-

6

SLC37A1(+)

MY+

6

88.775

89.025

H

 

++

+

-

-

3

GC(−)

MY+

20

58.375

58.375

H/J

+

   

--

3

ANKH(+)

MYn

3

34.225

34.425

H/J

    

--

15

KIAA1324(+)

MYn

5

31.225

31.225

H

    

--

11

LALBA(+)

MYn

5

75.575

75.775

H/J2,3

 

++

 

-

--

11

CSF2RB(+)

MYn

5

118.175

118.375

H

   

-

--

2

.

MYn

6

37.475

38.725

H/J

   

-

--

19

ABCG2(+)

MYn

10

46.375

46.675

H/J3

 

+

 

-

--

6

.

MYn

12

70.225

70.275

J

   

-

--

1

ABCC4(−)

MYn

12

72.125

72.325

J

   

--

--

1

ENTAG.45751(+)

MYn

14

67.125

67.125

J

    

--

1

.

MYn

14

69.775

69.975

H

 

++

 

-

--

2

SDC2(+)

MYn

15

28.475

28.625

H

    

--

7

.

MYn

15

53.275

53.275

H

 

+

  

--

2

FCHSD2(+)

MYn

16

1.475

1.725

H/J

 

+

 

--

--

10

.

MYn

16

40.975

40.975

J

    

--

2

SUCO(+)

MYn

19

42.675

42.925

H/J

   

-

--

22

STAT5A(+)

MYn

19

61.075

61.225

H/J

    

--

2

KCNJ16(−)

MYn

20

29.225

32.125

H/J3

 

++

 

--

--

19

CCL28(+)/GHR(+)

MYn

20

34.425

34.625

H/J3

 

++

 

-

--

2

.

MYn

23

50.975

51.375

H/J

 

+

  

--

2

GMDS(+)

MYn

29

41.875

41.975

H

    

--

25

SLC3A2(+)

PY-

11

103.225

103.425

H/J

-

++

++

--

 

12

PAEP(+)

PY+

5

75.075

75.275

H/J2,3

+

++

++

  

11

ENTAG.38652(+)

PY+

5

88.725

89.025

H/J

+

++

++

-

 

8

GYS2(−)

PY+

6

87.025

87.525

H/J1,3

 

+

++

 

++

14

CSN1S1(+)

PY+

10

16.725

16.925

H

+

+

++

  

2

TLE3(+)

PY+

16

31.025

31.025

H

+

+

++

  

3

.

PY+

18

18.325

18.425

J

+

+

++

  

3

.

PY+

23

39.175

39.375

J

+

+

++

  

8

KIF13A(+)

PY+

28

18.575

18.775

H/J

 

++

++

  

3

.

  1. FY = fat yield (kg/lactation), MY = milk yield (L/lactation), PY = protein yield (kg/lactation), F% = fat percentage (%) and P% = protein percentage in milk (%); ++ or -- indicates that the largest effect of a window in a region was greater than 50 times that of an average window and + or – indicates that window effects are greater than 3 times the average; directions of pleiotropic effects were determined by the correlation of GEBV between traits; regions are H or J (only) QTL when trait effects were greater than 50 times the mean in the alternate breed; descriptions of the identified genes with differential expression are in Additional file 3: Table S5 (see Additional file 3: Table S5). *over- (+) or under- (−) expression in mammary tissue (P < 1 × 10−5) relative to 17 other tissue types. 1some ambiguity in the QTL effects and pattern of effects, possibly indicate > 1 QTL or alleles. 2this region had two clear patterns of QTL effects and was split into two regions. 3similar QTL region also identified by GBLUP.