Open Access

A genome-wide scan of selective sweeps in two broiler chicken lines divergently selected for abdominal fat content

  • Hui Zhang1, 2,
  • Shou-Zhi Wang1, 2,
  • Zhi-Peng Wang1, 2,
  • Yang Da3,
  • Ning Wang1, 2,
  • Xiao-Xiang Hu4,
  • Yuan-Dan Zhang5,
  • Yu-Xiang Wang1, 2,
  • Li Leng1, 2,
  • Zhi-Quan Tang1, 2 and
  • Hui Li1, 2Email author
BMC Genomics201213:704

DOI: 10.1186/1471-2164-13-704

Received: 3 September 2012

Accepted: 10 December 2012

Published: 15 December 2012

Abstract

Background

Genomic regions controlling abdominal fatness (AF) were studied in the Northeast Agricultural University broiler line divergently selected for AF. In this study, the chicken 60KSNP chip and extended haplotype homozygosity (EHH) test were used to detect genome-wide signatures of AF.

Results

A total of 5357 and 5593 core regions were detected in the lean and fat lines, and 51 and 57 reached a significant level (P<0.01), respectively. A number of genes in the significant core regions, including RB1, BBS7, MAOA, MAOB, EHBP1, LRP2BP, LRP1B, MYO7A, MYO9A and PRPSAP1, were detected. These genes may be important for AF deposition in chickens.

Conclusions

We provide a genome-wide map of selection signatures in the chicken genome, and make a contribution to the better understanding the mechanisms of selection for AF content in chickens. The selection for low AF in commercial breeding using this information will accelerate the breeding progress.

Keywords

Abdominal fat Selection signature Extended haplotype homozygosity (EHH)

Background

The linkage disequilibrium (LD) is important in livestock genetics for its key role in genomic selection [1] and detecting the causal mutations of economically important traits [26]. Based on the LD information, there are two main methods to detect genes underlying phenotypic variation, including one from phenotype to genome and another one from genome to phenotype. The first method is performed by targeting particular candidate genes or by quantitative trait loci (QTL) mapping and positional cloning of QTL. In the second method, patterns of LD in populations that are incompatible with the hypothesis of genetic neutrality are identified, and these patterns are selection signatures [7]. The aim of the second method is to identify artificial selections by statistically evaluating the genomic data [7].

Allele frequencies underlying selection are expected to change. A neutral mutation will take many generations until the mutated allele reaches a high or low population frequency. In this case, the LD between the mutation and its neighboring loci will be degraded because of the recombination in every generation [8]. The frequency of a novel mutation will increase or decrease more rapidly than the neutral mutation because it is underlying artificial selection, so that the surrounding conserved haplotype was long [9, 10]. This is the background of the extended haplotype homozygosity (EHH) statistic method used to detect selection signatures [11]. There are also many other methods to detect selective sweeps from DNA sequence data, including the Tajima’s D[12] and Fay and Wu’s H-test [13] for selected mutations, measuring large allele-frequency differences among populations by FST[14], and the integrated Haplotype Score (iHS) [15], which is an extension of the EHH statistic [11]. Among these methods, the EHH test is particularly useful [7, 11]. The EHH test is used to detect artificial selections according to the characteristics of haplotypes within a single population, and do not require the genotype of the ancestor [7]. Furthermore, the EHH test is less sensitive to ascertainment bias than other approaches, so it was designed to work with SNP rather than sequencing data [7, 16].

The broilers used in this study were selected for eleven generations and genomic regions controlling AF deposition are expected to exhibit signatures of selective sweep. The aim of this study was to identify the selection signatures underlying the artificial selection for AF in chicken and to investigate the genes important for AF deposition.

Methods

Ethics statement

All animal work was conducted according to the guidelines for the care and use of experimental animals established by the Ministry of Science and Technology of the People’s Republic of China (Approval number: 2006–398) and approved by the Laboratory Animal Management Committee of Northeast Agricultural University.

DNA samples and data preparation

Broilers used in this study were from two Northeast Agricultural University broiler lines divergently selected for AF content (NEAUHLF). The two lines have been selected since 1996 using AF percentage (%AFW or AFP) and plasma very low-density lipoprotein (VLDL) concentration as selection criteria [17]. The two lines were selected for 11 generations and the AFP changes over the 11 generations are shown in Figure 1. A total of 475 individuals from generation 11 of NEAUHLF were used in this study.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-13-704/MediaObjects/12864_2012_Article_4655_Fig1_HTML.jpg
Figure 1

The separation of AFP over 11 generations between lean and fat lines.

Genotyping was carried out using the Illumina chicken 60K SNP chip containing a total of 57636 SNPs. Markers were filtered to exclude loci with unknown positions, monomorphic loci and loci with a minor allele frequency <0.05.

The haplotype and LD analysis

The fastPHASE [18] (http://​depts.​washington.​edu/​fphase/​download/​) was used to reconstruct the haplotypes for every chromosome using the default parameters. The reconstructed haplotypes were inserted into HAPLOVIEW v4.1 [19] to estimate LD statistics based on pairwise r2 and to construct the blocking pattern in the candidate regions of interest to enable selection signature analysis.

The EHH test

The “core region” was defined as the region in the genome characterized by the strong LD among SNPs involving a set of “core haplotypes” [7]. The Sweep v.1.1 (http://​www.​soft82.​com/​get/​download/​windows/​sweep/​) was used to identify the core regions [11]. The algorithm defined a pair of SNPs to be in strong LD if the upper 95% confidence bound of D’ is between 0.70 and 0.98 [20]. The program was set to select core regions with at least two SNPs. EHH was defined as the probability that two randomly chosen haplotypes carrying the candidate core haplotype were homozygous for the entire interval spanning the core region to a given locus [11]. The EHH test [11] was based on one of the core haplotype vs. other haplotypes in the same position. The “Relative Extended Haplotype Homozygosity” (REHH) statistic corrects EHH for the variability in recombination rates [7]. It was computed by EHHt / EHH ¯ https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-13-704/MediaObjects/12864_2012_Article_4655_IEq1_HTML.gif; with EHH ¯ https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-13-704/MediaObjects/12864_2012_Article_4655_IEq2_HTML.gif defined as the decay of EHH on all other core haplotypes combined. The REHH value was used in the current study to determine the selection signatures. To determine the significance of REHH values, the haplotypes were ordered into 20 bins according to their frequencies [7]. The REHH values of each haplotype in a candidate region were compared with all equally frequent haplotypes and the P-values were obtained [11]. The significant selection signatures were defined as P<0.01.

Results

Markers and core haplotypes

A total of 43034 SNPs on 28 autosomes in chickens were included in the selection signature analysis (Table 1). These markers covered 950.68 Mb of the genome, with an average of 22.09 kb between adjacent markers.
Table 1

Summary of genome-wide marker and core region (CR) distribution in the lean and fat lines

Chr

SNP (n)1

Chr length (Mbp)

Mean distance (kb)

No. CR (n)

Mean CR length (kb)

Coverage CR length2 (kb)

Max CR length (kb)

CR length/Chr length3

CR SNPs4 (n)

Max CR SNPs (n)

CR SNPs/SNP5

Lean line

Fat line

Lean line

Fat line

Lean line

Fat line

Lean line

Fat line

Lean line

Fat line

Lean line

Fat line

Lean line

Fat line

Lean line

Fat line

1

7135

200.95

28.16

881

920

125.59

114.92

110644.43

105728.03

2288.64

2191.34

0.55

0.53

3906

3716

19

19

0.55

0.52

2

5290

154.46

29.20

639

695

149.62

108.91

95606.56

75690.16

2048.43

2042.96

0.62

0.49

3260

2628

19

19

0.62

0.50

3

4081

113.65

27.85

517

533

121.58

108.97

62855.68

58081.43

863.98

735.27

0.55

0.51

2301

2107

19

19

0.56

0.52

4

3313

94.16

28.42

411

428

137.96

108.07

56701.29

46255.07

2087.33

611.37

0.60

0.49

1992

1676

19

19

0.60

0.51

5

2170

62.23

28.68

260

266

138.85

105.39

36101.29

28034.75

823.62

816.35

0.58

0.45

1282

1032

19

19

0.59

0.48

6

1714

35.84

20.91

217

225

94.92

72.79

20598.01

16377.61

535.90

523.04

0.57

0.46

983

826

19

19

0.57

0.48

7

1769

38.17

21.58

197

232

111.15

86.03

21897.27

19958.16

621.29

2163.72

0.57

0.52

1048

899

19

19

0.59

0.51

8

1394

30.62

21.97

159

175

111.56

96.82

17738.07

16944.10

1914.74

1949.21

0.58

0.55

791

763

19

19

0.57

0.55

9

1168

24.02

20.57

159

153

78.35

75.92

12457.00

11615.65

413.33

403.29

0.52

0.48

613

557

19

17

0.52

0.48

10

1297

22.42

17.29

172

176

70.99

63.35

12210.13

11148.99

387.48

347.35

0.54

0.50

735

699

19

19

0.57

0.54

11

1196

21.87

18.29

128

156

124.72

83.15

15964.06

12971.74

886.96

1093.97

0.73

0.59

871

706

19

19

0.73

0.59

12

1324

20.45

15.44

169

184

71.34

51.16

12057.10

9412.86

352.96

369.92

0.59

0.46

809

633

19

19

0.61

0.48

13

1128

18.32

16.24

144

141

75.86

75.09

10924.53

10584.67

373.56

373.56

0.60

0.58

695

656

19

19

0.62

0.58

14

984

15.76

16.02

127

123

75.17

68.77

9546.48

8459.25

402.70

402.70

0.61

0.54

598

544

19

19

0.61

0.55

15

1010

12.93

12.80

123

133

58.20

50.28

7158.60

6687.12

407.05

407.05

0.55

0.52

567

541

19

19

0.56

0.54

16

12

0.17

13.87

3

1

41.85

67.25

125.54

67.25

64.36

67.25

0.74

0.40

9

3

4

3

0.75

0.25

17

844

10.61

12.57

112

108

59.07

43.89

6616.05

4740.59

242.32

236.98

0.62

0.45

523

394

19

19

0.62

0.47

18

845

10.89

12.88

112

121

48.74

45.96

5459.42

5561.31

317.30

317.30

0.50

0.51

431

431

12

19

0.51

0.51

19

804

9.89

12.31

117

110

36.01

48.41

4212.67

5325.00

406.27

371.08

0.43

0.54

353

421

14

19

0.44

0.52

20

1460

13.92

9.53

184

181

45.89

46.33

8442.96

8386.18

273.60

270.67

0.61

0.60

904

888

19

19

0.62

0.61

21

726

6.88

9.47

81

90

47.74

35.17

3867.13

3165.72

211.67

196.05

0.56

0.46

432

354

19

18

0.60

0.49

22

295

3.89

13.19

36

30

71.16

79.29

2561.59

2378.83

267.88

289.01

0.66

0.61

193

182

19

19

0.65

0.62

23

577

6.02

10.44

81

80

37.13

31.74

3007.73

2539.51

239.20

239.20

0.50

0.42

307

272

19

19

0.53

0.47

24

676

6.23

9.22

87

91

40.77

32.96

3546.91

2999.26

133.00

212.48

0.57

0.48

387

339

13

19

0.57

0.50

25

170

2.02

11.86

23

18

34.97

32.38

804.26

582.82

82.74

72.39

0.40

0.29

99

68

12

10

0.58

0.40

26

617

5.03

8.16

81

85

34.55

59.60

2798.60

2515.94

246.20

278.91

0.56

0.50

345

312

19

19

0.56

0.51

27

472

4.84

10.25

60

59

46.66

40.46

2799.62

2387.38

384.65

482.24

0.58

0.49

299

215

19

19

0.63

0.46

28

563

4.46

7.92

77

79

36.64

27.66

2820.93

2185.41

520.13

172.85

0.63

0.49

336

318

19

19

0.60

0.56

Total

43034

950.68

22.09

5357

5593

102.58

85.96

549523.91

480784.79

2288.64

2191.34

0.58

0.51

25069

22180

19

19

0.58

0.52

1The number of SNPs.

2Total length covered by core regions.

3The proportion of total core region lengths on chromosome length.

4Number of SNPs in core regions.

5The proportion of total number of SNPs in core regions on number of SNPs used.

For the SNPs analyzed in this study, the average minor allele frequency was 0.29 ± 0.13. A summary of genome-wide markers and core haplotype distribution in the data set is shown in Table 1. A total of 5357 and 5593 core regions spanning 549523.91 kb and 480784.79 kb of the genome, respectively, in the lean and fat lines were detected (Table 1). Mean core region length was estimated as 102.58±37.24 kb and 85.96±26.65 kb, with a maximum of 2288.64 kb and 2191.34 kb in the lean and fat lines, respectively (Table 1). Chromosome 1 was the largest chromosome in chickens, and it had the largest haplotypic structures in the genome, which covered 110644.43 kb and 105728.03 kb in the lean and fat lines, respectively. For each chromosome, the proportion of length covered by core regions vs. total length, as well as the number of SNPs forming core regions vs. the total number of SNPs, are shown in Table 1. The distribution of the size of core regions is shown in Figure 2. Overall, 25069 and 22180 SNPs in the lean and fat lines, respectively, participated in forming core regions, with a range of 2 to 19 SNPs per core.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-13-704/MediaObjects/12864_2012_Article_4655_Fig2_HTML.jpg
Figure 2

Distribution of SNP numbers in the core regions (A) and the length of core regions (B) in lean and fat lines.

Whole genome selection signatures

For all 5357 and 5593 core regions in the lean and fat lines, respectively, a total of 44822 and 46775 EHH tests, with an average of 8.37 and 8.36 tests per core region, were calculated. To find outlying core haplotypes, we calculated REHH at 1 Mb distances both on the upstream and downstream sides. Figure 3 shows the distribution of REHH values vs. haplotype frequencies in the lean and fat lines, respectively. Corresponding P-values are indicated by different colored symbols. The –log10 of the P-values associated with REHH against the chromosomal position was plotted to visualize the chromosomal distribution of outlying core haplotypes with frequency <25% (Figure 4). The results indicated that these selection signals were not uniformly distributed across all chromosomes, with a substantial overrepresentation on chromosomes 1, 2, 3 and 4.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-13-704/MediaObjects/12864_2012_Article_4655_Fig3_HTML.jpg
Figure 3

Distribution of REHH vs. core haplotype frequencies in the lean and fat lines. Core haplotypes with P-values lower than 0.05 and 0.01 are presented in blue and red, respectively.

https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-13-704/MediaObjects/12864_2012_Article_4655_Fig4_HTML.jpg
Figure 4

Genome-wide map of P -values for core haplotypes with frequency >0.25 in lean and fat lines, respectively. Dashed lines display the threshold level of 0.01.

The genome-wide statistics of the selection signature test, including the number of tests and outlying core haplotypes for each chromosome, are presented in Table 2. Of 16677 and 18346 tests on core haplotypes with frequency ≥0.25, there were 51 and 57 tests with P<0.01 in the lean and fat lines, respectively. There were 153 and 251 tests with P<0.05 in the lean and fat lines, respectively.
Table 2

The number of tests on core haplotypes (CH) (both sides) with frequency≥0.25 and P -values of REHH test

Chr

Lean line

Fat line

Test on CH

P-value <0.05

P-value <0.01

Test on CH

P-value <0.05

P-value <0.01

1

2806

113

4

3063

138

12

2

2009

105

8

2271

104

3

3

1654

79

10

1705

74

8

4

1273

58

6

1371

66

5

5

844

34

3

883

36

4

6

699

25

2

757

31

2

7

638

29

2

770

31

5

8

464

16

1

574

33

2

9

516

20

1

564

19

1

10

540

23

2

582

27

1

11

397

15

1

534

20

2

12

503

14

0

619

20

1

13

447

19

3

474

22

1

14

379

14

0

418

16

1

15

329

12

1

420

18

2

17

350

16

0

348

14

2

18

354

12

2

432

13

2

19

334

12

1

338

13

0

20

561

28

3

566

19

0

21

255

6

0

304

11

0

22

105

5

1

85

2

0

23

258

11

0

245

12

1

24

287

9

0

308

12

2

25

46

1

0

36

1

0

26

231

11

0

253

4

0

27

181

8

0

184

7

0

28

217

5

0

242

14

0

Total

16,677

700

51

18,346

777

57

The conformity of the distribution of Tukey’s outliers was examined, with outlying core haplotypes defined at the threshold level of 0.01. Figure 5 displays box plots of the distribution of –log10 (P-values) within each bin of core haplotype frequency. The results indicated that the extreme outliers appear in the small haplotype frequencies bins.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-13-704/MediaObjects/12864_2012_Article_4655_Fig5_HTML.jpg
Figure 5

Box plot of the distribution of P -values in core haplotype frequency bins in the lean (left) and fat (right) lines. The dashed and continuous lines indicated the threshold P-values of 0.01 and 0.001, respectively.

Mapping selection signatures to genes

A summary of statistics for 51 and 57 positively selected core regions with P<0.01 of the REHH tests in the lean and fat lines, respectively, is presented in Table 3. Corresponding genes were identified by aligning the core positions with the chicken genome sequence (Table 3). The full genes names were from Ensembl online (http://​www.​ensembl.​org/​index.​html). A total of 66 and 46 genes in the core regions were detected in the lean and fat lines, respectively, including RB1 (retinoblastoma 1), BBS7 (Bardet-Biedl syndrome 7), MAOA (monoamine oxidase A), MAOB (monoamine oxidase B), EHBP1 (EH domain binding protein 1), LRP2BP (LRP2 binding protein), LRP1B (low-density lipoprotein receptor-related protein 1B), MYO7A (myosin VIIA), MYO9A (myosin IXA) and PRPSAP1 (phosphoribosyl pyrophosphate synthetase-associated protein 1). The haplotype analysis of these genes revealed that the haplotype frequencies were significantly different (P<0.01) between the two lines (Table 4).
Table 3

Statistics summary for core haplotypes with P <0.01 after the relative extended haplotype homozygosity (REHH) test

Lean line

Chr

Core position

Hap Freq

EHH

REHH1

REHH P-value1

Genes

1

39360501-39455853

0.46

0.98

3.99

0.0027

/

1

49926970-49964278

0.30

0.97

4.18

0.0021

C12orf69, WBP11, H2A4, H2B1, H4, H32, H2B8

1

173098805-173190831

0.37

0.99

4.25

0.0027

RB1, LPAR6, O57531, RCBTB2

1

198071099-198113519

0.55

0.80

3.03

0.0031

GDPD4, MYO7A

2

3631683-3739002

0.32

0.70

4.88

0.0004

Q5ZK34

2

19934135-20028093

0.30

0.97

3.88

0.0035

RSU1

2

26912546-26974875

0.28

1.00

3.65

0.0050

/

2

99818321-100051643

0.41

1.00

3.00

0.0047

GNAL, NRGN

2

131104507-131150076

0.48

0.98

3.24

0.0029

Q6V0P0, INTS8, F1P3N8

2

143016981-143059231

0.36

0.97

3.46

0.0034

/

2

145836411-145908271

0.30

1.00

3.72

0.0045

/

2

150489129-150540434

0.34

1.00

3.51

0.0044

/

3

3794973-3861882

0.30

0.79

4.72

0.0005

C20orf26, CRNKL1

3

3794973-3861882

0.30

0.82

3.85

0.0020

C20orf26, CRNKL1

3

10257926-10454969

0.55

0.49

2.49

0.0019

F1NRN6

3

14895290-14957057

0.44

0.72

3.16

0.0048

PLCB4

3

26957549-26996618

0.46

0.80

3.69

0.0009

/

3

26957549-26996618

0.46

0.83

3.47

0.0013

/

3

27303800-27335510

0.52

0.92

3.78

0.0009

SRBD1

3

27382993-27430067

0.54

0.84

3.77

0.0009

SRBD1

3

35555718-35610466

0.47

0.66

3.02

0.0031

E1C4G2

3

68936320-69076223

0.27

0.98

3.79

0.0041

RPF2, GTF3C6, Q5F484, CDK19

4

3522359-3551494

0.59

0.54

3.10

0.0023

MBNL3

4

9568761-9604871

0.55

1.00

2.95

0.0040

/

4

17765695-17819334

0.41

1.00

3.56

0.0037

F1NEF4, HMGB3

4

46149116-46190279

0.36

0.99

3.35

0.0044

EREG, Q645M5

4

55424480-55472209

0.66

0.9

2.60

0.0005

TRPC3, BBS7

4

83051637-83117974

0.39

0.87

3.72

0.0022

/

5

9740941-9828144

0.49

1.00

3.42

0.0014

IF4G2, CTR9, MRVI1

5

23825115-23872187

0.41

0.78

3.19

0.0030

O93582

5

42592517-42679460

0.30

1.00

3.70

0.0044

/

6

6546601-6626145

0.39

1.00

4.42

0.0011

/

6

35354459-35390346

0.38

0.99

3.72

0.0030

PTPRE

7

28869664-28906344

0.31

1.00

4.88

0.0015

MYLK

7

35674098-35715122

0.67

0.48

2.09

0.0027

 

8

6107407-6172105

0.36

0.63

3.72

0.0020

IER5, KIAA1614, XPR1

9

16264832-16366749

0.45

0.97

4.04

0.0024

PSMD1, ARMC9, B3GNT7

10

5831963-5856349

0.59

0.97

1.83

0.0034

/

10

19717086-19745274

0.48

1.00

2.90

0.0011

CHSY1

11

17094961-17160195

0.30

0.63

3.35

0.0001

BCDO1, GAN

13

2628777-2664596

0.35

1.00

3.94

0.0048

Q5ZHQ9

13

2726706-2746894

0.39

0.79

4.06

0.0041

/

13

16758621-16783127

0.26

0.69

3.26

0.0050

FSTL4

15

7345639-7377799

0.26

0.54

2.38

0.0004

SEZ6L, ASPHD2, HPS4

18

9949736-10015444

0.39

1.00

2.34

0.0031

SPAG9

18

10117401-10135964

0.39

1.00

2.64

0.0013

F1NM51

19

8727596-8786448

0.60

0.55

1.77

0.0038

MSI1

20

9090808-9113453

0.29

0.95

6.18

0.0036

MYT1

20

9246245-9278998

0.32

0.80

5.39

0.0040

E1C8M0

20

9879361-9899719

0.27

0.96

6.40

0.0030

CSK21

22

2952274-3002268

0.29

0.29

3.93

0.0039

/

Fat line

1

51248496-51279543

0.33

0.81

4.45

0.0018

TCF20

1

58120009-58215364

0.55

0.99

3.15

0.0016

Q8UVD4

1

60171076-60254771

0.46

1.00

4.12

0.0049

/

1

67763862-67830818

0.26

0.96

4.06

0.0026

/

1

68213617-68257241

0.61

0.94

4.21

0.0016

SOX5

1

69634186-69686357

0.66

0.99

2.89

0.0003

/

1

101535615-101635667

0.29

1.00

5.24

0.0005

SAMSN1

1

114789487-114875623

0.29

0.99

3.66

0.0048

MAOB, MAOA

1

125909995-126011984

0.35

1.00

3.77

0.0036

E1BTB5

1

154665510-154752965

0.72

0.89

2.09

0.0034

/

1

181800227-181883545

0.33

0.99

4.00

0.0033

A1XGV6

1

181800227-181883545

0.33

1.00

3.81

0.0043

A1XGV6

2

76768841-76854523

0.31

1.00

4.30

0.0041

/

2

151203953-151251059

0.62

0.82

2.32

0.0033

TRAPPC9

2

153117092-153143883

0.71

0.77

1.68

0.0038

/

3

9177907-9222825

0.38

0.95

4.00

0.0024

EHBP1

3

9177907-9222825

0.38

0.90

3.66

0.0039

EHBP1

3

16143474-16194865

0.30

0.98

4.98

0.0016

/

3

24945839-24986772

0.61

0.70

2.15

0.0014

/

3

44265116-44311493

0.40

0.99

3.50

0.0050

UNC93A

3

69863850-69906698

0.34

1.00

4.29

0.0038

/

3

85874137-85931473

0.41

1.00

3.97

0.0031

LMBRD1

3

97227680-97337906

0.28

0.99

3.81

0.0042

/

4

11582141-11642538

0.27

0.96

4.53

0.0029

/

4

40653593-40713404

0.32

0.93

4.40

0.0010

C4orf20, LRP2BP, SNX25

4

55950677-55991394

0.28

0.99

4.55

0.0028

/

4

55950677-55991394

0.28

1.00

4.36

0.0036

/

4

86719441-86754976

0.57

0.75

2.88

0.0048

/

5

556571-628531

0.25

0.67

4.37

0.0026

F1NYX6, PLCB2, BUB1B, PAK6

5

40239840-40261525

0.29

0.97

4.48

0.0038

VSX2, F1N9P5

5

47240577-47282933

0.40

0.95

2.91

0.0029

RIN3, LGMN

5

59811459-59880511

0.39

0.66

3.36

0.0041

/

6

26756202-26793956

0.34

0.98

3.94

0.0049

/

6

29341938-29401207

0.32

0.97

5.50

0.0007

ABLIM1

7

30090927-30155133

0.30

0.88

3.77

0.0033

F1NF72

7

31374271-31418061

0.42

1.00

2.88

0.0049

LYPD1, NCKAP5

7

33795201-33904515

0.47

1.00

2.20

0.0025

LRP1B

7

36818722-36875768

0.26

0.99

3.95

0.0024

Q9DEH4

7

37031922-37124566

0.56

1.00

2.92

0.0047

STAM2, FMNL2

8

5597-492518

0.56

0.99

1.94

0.0036

F1NF53

8

2178258-2252969

0.47

0.92

4.20

0.0004

NEK7

9

2952291-3007034

0.41

0.71

3.85

0.0044

/

10

763998-831991

0.50

0.78

5.04

0.0004

MYO9A, F1P0M4

11

9804894-9826761

0.47

0.52

3.11

0.0014

/

11

16253047-16303345

0.58

0.35

1.80

0.0040

/

12

1157199-1170169

0.37

0.63

4.57

0.0030

/

13

1533552-1640154

0.40

1.00

3.41

0.0049

SRA1, APBB3, F1NH59

14

8048059-8173629

0.42

0.86

3.09

0.0015

/

15

8495796-8543001

0.29

1.00

4.86

0.0003

TBX6, CRKL, KLHL22

15

8495796-8543001

0.29

0.99

4.43

0.0006

TBX6, CRKL, KLHL22

17

3250605-3271593

0.27

0.97

3.91

0.0033

/

17

4062173-4087131

0.26

0.94

3.77

0.0040

C4PCF3

18

4433126-4445816

0.26

0.79

5.99

0.0037

PRPSAP1

18

8365846-8400245

0.47

0.80

3.53

0.0038

/

23

935267-970086

0.31

0.91

5.40

0.0040

EDN2

24

5613517-5633477

0.28

0.86

4.38

0.0024

ZW10, F1NC10

24

6145308-6158962

0.31

0.80

5.30

0.0047

/

1REHH and P-values are presented for upstream and downstream sides from each core haplotype, respectively.

Table 4

Haplotype frequencies in the lean and fat lines of the core regions including 10 important genes

Gene and core regions

Haplotype Number

Haploptypes

Haplotype frequency

P-value1

Lean line

Fat line

MAOB, MAOA

1

CAAGG

0.645

0.615

<0.001

Chr1: 114789487-114875623

2

AAAGA

0.197

0

3

CGGAG

0.158

0.269

4

CGAGA

0

0.077

5

AAAGG

0

0.038

RB1

1

GGAA

0.421

0.410

<0.001

Chr1: 173098805-173190831

2

GAGG

0.368

0.103

3

GAAA

0.211

0.192

4

AAGG

0

0.244

5

AGGA

0

0.038

6

GAGA

0

0.013

MYO7A

1

AGG

0.618

0.090

<0.001

Chr1: 198071099-198113519

2

GAA

0.316

0.207

3

GGA

0.066

0.652

4

GAG

0

0.037

5

GGG

0

0.014

EHBP1

1

GGG

0.855

0.090

<0.001

Chr3: 9177907-9222825

2

GAG

0.132

0.359

3

AGG

0.013

0.128

4

GGA

0

0.423

LRP2BP

1

GGGG

0.443

0.487

<0.001

Chr4: 40653593-40713404

2

AAAA

0.338

0.211

3

GGAA

0.176

0

4

AAGG

0.044

0.303

BBS7

1

AGGC

0.605

0.282

<0.001

Chr4: 55424480-55472209

2

GAAA

0.368

0.301

3

AAAA

0.026

0

4

AGAC

0

0.198

5

AGAA

0

0.161

6

GAAC

0

0.058

LRP1B

1

AGAGAC

0.361

0.013

<0.001

Chr7: 33795201-33904515

2

GGAGGA

0.197

 

3

AGAAGA

0.105

0.154

4

GGGGGA

0.066

0.449

5

AGAAGC

0.057

0.346

6

GAGGGA

0.055

0.038

7

GAGAGA

0.050

0

8

GGAAGA

0.049

0

9

GAGGAA

0.026

0

10

GGAGAA

0.018

0

11

AGAAAC

0.016

0

MYO9A

1

GGGAA

0.355

0.051

<0.001

Chr10: 763998-831991

2

AAGAA

0.276

0.358

3

AAGAG

0.237

0

4

GGGGA

0.118

0.013

5

AGGAA

0.013

0.065

6

AGAAA

0

0.500

7

AAAAA

0

0.013

PRPSAP1

1

AGA

0.816

0.615

<0.001

Chr18: 4433126-4445816

    

2

GGG

0.118

0.026

3

AAG

0.066

0.090

4

AGG

0

0.269

1P-values of Fisher’s Exact Test for difference analysis of haplotype frequencies between lean and fat lines.

Mapping selection signatures to QTLs

The chicken QTL database available online (http://​www.​animalgenome.​org/​cgi-bin/​QTLdb/​GG/​index) was explored to identify any overlapping of the core regions with significant REHH P-values (P<0.01) and published QTLs in chickens. The approximate positions of the overlapping QTLs for each core region are listed in Table 5. There were many overlaps between the core regions with significant REHH P-values (P<0.01) and published QTLs for AF content in chickens.
Table 5

Reported QTL near the core regions with P <0.01 in the lean and fat lines

Lean line

Chr

Core region (bp)

Trait

QTL position (bp)

F-ratio

P-value

Reference

1

39360501-39455853

AFP

1937738-52700434

1.474

Suggestive

[21]

1

49926970-49964278

AFP

25998723-65961966

1.732

Suggestive

[21]

AFW

25998723-65961966

1.882

Suggestive

[21]

AFW

48175152- 51977642

8.14

Significant

[22]

1

173098805-173190831

AFW

158352237- 182910620

3.18

Significant

[23]

AFP

171224834- 174526878

20.34

Significant

[23]

2

3631683-3739002

AFW

3097660- 4097660

3.38

Suggestive

[24]

3

3794973-3861882

AFP

800029-110574691

1.364

Suggestive

[21]

3

10257926-10454969

AFP

800029-110574691

1.364

Suggestive

[21]

AFW

6841859-13986734

8.16

Significant

[22]

AFP

6841859- 57396057

7.9

Significant

[25]

AFW

6841859- 44850897

7.4

Significant

[25]

3

14895290-14957057

AFP

800029-110574691

1.364

Suggestive

[21]

AFW

6841859-13986734

8.16

Significant

[22]

AFP

6841859- 57396057

7.9

Significant

[25]

AFW

6841859- 44850897

7.4

Significant

[25]

AFW

13986734-25508863

\

Suggestive

[26]

3

26957549-26996618

AFP

800029-110574691

1.364

Suggestive

[21]

AFP

6841859- 57396057

7.9

Significant

[25]

AFW

6841859- 44850897

7.4

Significant

[25]

AFW

24160710-51592221

\

Suggestive

[27]

AFW

25508863- 35512024

\

Suggestive

[26]

3

27303800-27335510

AFP

800029-110574691

1.364

Suggestive

[21]

AFP

6841859- 57396057

7.9

Significant

[25]

AFW

6841859- 44850897

7.4

Significant

[25]

AFW

24160710-51592221

\

Suggestive

[27]

AFW

25508863- 35512024

\

Suggestive

[26]

3

27382993-27430067

AFP

800029-110574691

1.364

Suggestive

[21]

AFP

6841859- 57396057

7.9

Significant

[25]

AFW

6841859- 44850897

7.4

Significant

[25]

AFW

24160710-51592221

\

Suggestive

[27]

AFW

25508863- 35512024

\

Suggestive

[26]

3

35555718-35610466

AFP

800029-110574691

1.364

Suggestive

[21]

AFW

35512024-40755790

18.5

Significant

[28]

AFP

35512024-40755790

13.1

Significant

[28]

4

17765695-17819334

AFW

17425871-18425871

\

Significant

[29]

4

46149116-46190279

AFW

42005559- 51609571

2.26

Suggestive

[30]

4

55424480-55472209

AFP

51266614- 88408499

16.0

Significant

[25]

4

83051637-83117974

AFP

51266614- 88408499

16.0

Significant

[25]

AFW

80258156-88408499

6.9

Significant

[25]

AFW

81539616- 84618310

2.04

Suggestive

[30]

5

23825115-23872187

AFW

18412554-42717839

21.8

Significant

[25]

AFP

18723157- 43339045

19.4

Significant

[25]

AFW

19782191- 30162990

\

Suggestive

[26]

AFW

19782191- 30162990

7.04

Significant

[31]

5

42592517-42679460

AFW

18412554-42717839

21.8

Significant

[25]

AFP

18723157- 43339045

19.4

Significant

[25]

AFW

37226264-53779276

6.74

Significant

[31]

6

35354459-35390346

AFP

29647151- 37399694

6.9

Significant

[25]

7

28869664-28906344

AFW

25306930- 38010856

\

Suggestive

[27]

AFW

28166221- 29166221

9.78

Significant

[32]

AFW

28166221- 29166221

\

Significant

[33]

7

35674098-35715122

AFW

25306930- 38010856

\

Suggestive

[27]

9

16264832-16366749

AFW

13658592-23770679

5.03

Suggestive

[22]

AFW

15457880-16457880

7.0

Suggestive

[34]

10

19717086-19745274

AFP

16519830- 20778533

9.9

Significant

[28]

13

16758621-16783127

AFW

16327806- 18173123

2.10

Suggestive

[30]

15

7345639-7377799

AFW

1917251- 10769106

10.2

Significant

[25]

AFP

2388961-10769106

12.8

Significant

[25]

AFW

2798507-10769106

8.13

Significant

[22]

AFW

2798507-10769106

5.67

Suggestive

[22]

AFW

3717446-7928397

2.21

Suggestive

[30]

AFP

3717446-7928397

2.22

Suggestive

[30]

Fat line

1

51248496-51279543

AFP

1937738-52700434

1.474

Suggestive

[21]

AFW

48175152- 51977642

8.14

Significant

[22]

AFP

25998723- 65961966

1.732

Suggestive

[21]

AFW

25998723- 65961966

1.882

Suggestive

[21]

1

58120009-58215364

AFP

25998723- 65961966

1.732

Suggestive

[21]

AFW

25998723- 65961966

1.882

Suggestive

[21]

AFW

55261695-67128747

12.18

Significant

[35]

1

60171076-60254771

AFP

25998723- 65961966

1.732

Suggestive

[21]

AFW

25998723- 65961966

1.882

Suggestive

[21]

AFW

55261695-67128747

12.18

Significant

[35]

1

67763862-67830818

AFW

67327367-68327367

\

Significant

[33]

1

68213617-68257241

AFW

67327367-68327367

\

Significant

[33]

1

101535615-101635667

AFW

89938943-167462479

9.4

Significant

[36]

AFW

94157976- 102460326

6.11

Suggestive

[35]

1

114789487-114875623

AFW

113344161- 132660888

7.90

Suggestive

[35]

AFW

114143603- 115143603

7.1

Significant

[36]

1

125909995-126011984

AFW

113344161- 132660888

7.90

Suggestive

[35]

1

181800227-181883545

AFW

158352237-182910620

3.18

Significant

[23]

3

9177907-9222825

AFP

800029- 110574691

1.364

Suggestive

[21]

AFW

6841859- 13986734

8.16

Significant

[22]

AFW

6841859- 13986734

5.8

Suggestive

[22]

AFP

6841859-57396057

7.9

Significant

[25]

AFW

6841859-44850897

7.4

Significant

[25]

3

16143474-16194865

AFP

800029- 110574691

1.364

Suggestive

[21]

AFP

6841859-57396057

7.9

Significant

[25]

AFW

6841859-44850897

7.4

Significant

[25]

AFW

13986734-25508863

\

Suggestive

[26]

3

24945839-24986772

AFP

800029- 110574691

1.364

Suggestive

[21]

AFP

6841859-57396057

7.9

Significant

[25]

AFW

6841859-44850897

7.4

Significant

[25]

AFW

13986734-25508863

\

Suggestive

[26]

AFW

24160710-51592221

\

Suggestive

[27]

3

44265116-44311493

AFP

800029- 110574691

1.364

Suggestive

[21]

AFP

6841859-57396057

7.9

Significant

[25]

AFW

6841859-44850897

7.4

Significant

[25]

AFW

24160710-51592221

\

Suggestive

[27]

AFW

40755790-45203763

7.5

Significant

[28]

AFP

40755790-45203763

10.8

Significant

[28]

3

69863850-69906698

AFP

800029- 110574691

1.364

Suggestive

[21]

3

85874137-85931473

AFP

800029- 110574691

1.364

Suggestive

[21]

3

97227680-97337906

AFP

800029- 110574691

1.364

Suggestive

[21]

4

40653593-40713404

AFP

40473174-41473174

\

Significant

[32]

4

55950677-55991394

AFP

51266614- 88408499

16.0

Significant

[25]

4

86719441-86754976

AFP

51266614- 88408499

16.0

Significant

[25]

AFW

80258156-88408499

6.9

Significant

[25]

5

40239840-40261525

AFW

18412554- 42717839

21.8

Significant

[25]

AFP

18723157- 43339045

19.4

Significant

[25]

AFW

37226264- 53779276

6.74

Significant

[31]

AFW

40158255- 41158255

\

Significant

[37]

AFW

40158255- 41158255

\

Significant

[38]

AFP

40158255- 41158255

\

Significant

[38]

5

47240577-47282933

AFW

37226264- 53779276

6.74

Significant

[31]

5

59811459-59880511

AFW

51748760-60234891

\

Significant

[26]

AFW

53867807-62098509

11.87

Significant

[31]

AFW

53867807-62098509

6.82

Significant

[31]

7

30090927-30155133

AFW

25306930- 38010856

\

Suggestive

[27]

7

31374271-31418061

AFW

25306930- 38010856

\

Suggestive

[27]

7

33795201-33904515

AFW

25306930- 38010856

\

Suggestive

[27]

AFW

32440861-34526547

2.08

Suggestive

[30]

7

36818722-36875768

AFW

25306930- 38010856

\

Suggestive

[27]

7

37031922-37124566

AFW

25306930- 38010856

\

Suggestive

[27]

9

2952291-3007034

AFW

2798942-3798942

\

Significant

[32]

AFP

2972071-3972071

\

Significant

[32]

11

9804894-9826761

AFW

6272742- 12810705

2.15

Suggestive

[30]

12

1157199-1170169

AFP

734209- 12275026

5.22

Significant

[28]

AFP

734209- 12275026

4.51

Significant

[28]

AFP

813709-1813709

\

Significant

[32]

15

8495796-8543001

AFW

1917251- 10769106

10.2

Significant

[25]

AFP

2388961- 10769106

12.8

Significant

[25]

AFW

2798507- 10769106

8.13

Significant

[22]

AFW

2798507- 10769106

5.67

Suggestive

[22]

23

935267-970086

AFW

74802-1074802

\

Significant

[39]

Discussion

Selective sweep is used to detect genomic regions with reduced variation in allele frequency in any population experiencing divergent selection for specific traits. Here, we determined the feasibility of the selective sweep approach for finding genes important for AF deposition in chickens. The long-range haplotype test was employed, which detects selection signature by measuring the characteristics of haplotypes within the lean and fat lines divergently selected for AF content. There were 5357 and 5593 core regions in the lean and fat lines, respectively. When comparing the average marker spacing with mean core length and number of SNPs forming cores, we revealed that core regions are more likely to appear in regions with higher marker density.

The selection signatures on the whole genome were calculated, and a subset of putative core regions with significant REHH P-values (P<0.01) was identified. The genes in these core regions were detected and 10 genes, including RB1, BBS7, MAOA, MAOB, EHBP1, LRP2BP, LRP1B, MYO7A, MYO9A and PRPSAP1, were important for fatness. Among these 10 important genes, seven genes, including RB1, BBS7, MAOA, MAOB, EHBP1, LRP2BP and LRP1B, were all in the QTL regions reported previously for AF in chickens (Table 5). Although the other three genes, including MYO7A, MYO9A and PRPSAP1, were not in the QTL regions, these genes were also important for the AF deposition.

The known functions of these 10 genes were analyzed and the results indicated that they were likely to be linked with fatness. The RB1 gene regulates the C/EBP-DNA-binding activity during 3T3-L1 adipogenesis and plays a key role in adipocyte differentiation [40, 41].

The BBS7 gene is a member of the Bardet-Biedl syndrome (BBS) family. BBS is a pleiotropic genetic disorder characterized by obesity, photoreceptor degeneration, polydactyly, hypogenitalism, renal abnormalities, and developmental delay [42]. BBS is recognized to be a genetically heterogeneous autosomal recessive disorder mapped to eight loci [42]. Positional cloning and candidate genes identified six BBS genes, including BBS1, BBS2, BBS4, BBS6, BBS7, and BBS8[42]. These BBS genes may be important for obesity.

The MAOA and MAOB are two enzymes important for dopamine production. The dopamine levels influence the risk of obesity and MAOA and MOAB may be implicated in human obesity [43].

The EHBP1 gene is required for insulin-stimulated GLUT4 movements [44]. Insulin stimulates glucose transport in adipose tissues by recruiting intracellular membrane vesicles containing the glucose transporter GLUT4 to the plasma membrane [44]. The mechanisms involved in the biogenesis of these vesicles and their translocation to the cell surface were studied and the results indicated that EHD1 and EHBP1 are required for perinuclear localization of GLUT4, and the loss of EHBP1 disrupts insulin-regulated GLUT4 recycling in cultured adipocytes [44]. This indicates that the EHBP1 gene may be important in adipocyte differentiation.

The LRP2BP and LRP1B genes are two members of the low-density lipoprotein receptor family that participates in a wide range of physiological processes, including the regulation of lipid metabolism, protection against atherosclerosis, neurodevelopment, and transport of nutrients and vitamins [45].

The MYO7A and MYO9A are two myosin genes. A spontaneous mutant mouse line, Myo7ash1-6J, was used to study the function of the MYO7A gene, and the result indicated that the mutant male homozygous mice displayed decreased body weight and body fat [46]. The MYO9A gene was in the BBS4 region of chromosome 15q22-q23 [47], which might be important for obesity.

The PRPSAP1 gene is named as phosphoribosyl pyrophosphate synthetase-associated protein 1. The results of differentially expressed genes associated with insulin resistance indicate that PRPSAP1 gene is associated with percentage of body fat [48].

The associations of these 10 genes with obesity or lipid metabolism were mainly in humans and mice. Because of the high conservation of these genes between humans, mice and chickens, the 10 genes might also be important for AF deposition in chickens.

Conclusions

Our results provide a genome-wide map of selection signatures in two chicken lines divergently selected for AF content. There were 51 and 57 core regions showing significant P-values (P<0.01) of selection signatures in the lean and fat lines, respectively. In these core regions there were a number of important genes, including RB1, BBS7, MAOA, MAOB, EHBP1, LRP2BP, LRP1B, MYO7A, MYO9A and PRPSAP1. These genes are important for AF deposition in chickens.

Abbreviations

AF: 

Abdominal fat

AFP: 

Abdominal fat percentage

AFW: 

Abdominal fat weight

BBS: 

Bardet-Biedl syndrome

CH: 

Core haplotypes

CR: 

Core region

EHH: 

Extended haplotype homozygosity

IHS: 

Integrated Haplotype Score

LD: 

Linkage disequilibrium

NEAU: 

Northeast Agricultural University

NEAUHLF: 

Northeast Agricultural University broiler lines divergently selected for abdominal fat content

NRC: 

National Research Council

QTL: 

Quantitative trait loci

REHH: 

Relative Extended Haplotype Homozygosity

SNP: 

Single nucleotide polymorphism

VLDL: 

Very low-density lipoprotein.

Declarations

Acknowledgements

The authors would like to acknowledge the members of the Poultry Breeding Group of the College of Animal Science and Technology in Northeast Agricultural University for managing the birds and collecting data. This research was supported by the China Agriculture Research System (No. CARS-42), National 863 Project of China (No. 2011AA100301), National 973 Project of China (No. 2009CB941604) and Program for Innovation Research Team in University of Heilongjiang Province (No. 2010td02).

Authors’ Affiliations

(1)
Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture
(2)
College of Animal Science and Technology, Northeast Agricultural University
(3)
Department of Animal Science, University of Minnesota
(4)
College of Biological Science, China Agricultural University
(5)
Animal Genetics and Breeding Unit, University of New England

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