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Identification of single nucleotide polymorphisms of PIK3R1 and DUSP1 genes and their genetic associations with milk production traits in dairy cows

  • Bo Han
  • Yuwei Yuan
  • Lijun Shi
  • Yanhua Li
  • Lin Liu
  • Dongxiao SunEmail author
Open Access
Research
  • 111 Downloads

Abstract

Background

Previously, phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1) and dual specificity phosphatase 1 (DUSP1) were identified as promising candidate genes for milk production traits due to their being differentially expressed between the dry period and the peak of lactation in livers of dairy cows. Hence, in this study, the single nucleotide polymorphisms (SNPs) of PIK3R1 and DUSP1 genes were identified and their genetic associations with milk yield, fat yield, fat percentage, protein yield, and protein percentage, were investigated using 1067 Chinese Holstein cows from 40 sire families.

Results

By re-sequencing the entire coding region and 2000 bp of the 5′ and 3′ flanking regions of the two genes, one SNP in the 5′ untranslated region (UTR), three in the 3′ UTR, and two in the 3′ flanking region of PIK3R1 were identified, and one in the 5′ flanking region, one in the 3′ UTR, and two in the 3′ flanking region of DUSP1 were found. Subsequent single-locus association analyses showed that five SNPs in PIK3R1, rs42590258, rs210389799, rs208819656, rs41255622, rs133655926, and rs211408208, and four SNPs in DUSP1, rs207593520, rs208460068, rs209154772, and rs210000760, were significantly associated with milk, fat and protein yields in the first or second lactation (P values ≤ 0.0001 and 0.0461). In addition, by the Haploview 4.2 software, the six and four SNPs in PIK3R1 and DUSP1 respectively formed one haplotype block, and the haplotype-based association analyses showed significant associations between their haplotype combinations and the milk traits in both two lactations (P values ≤ 0.0001 and 0.0364). One SNP, rs207593520(T/G), was predicted to alter the transcription factor binding sites (TFBSs) in the 5′ flanking region of DUSP1. Further, the dual-luciferase assay showed that the transcription activity of allele T in rs207593520 was significantly higher than that of allele G, suggesting the activation of transcriptional activity of DUSP1 gene by allele T of rs207593520. Thus, the rs207593520 SNP was highlighted as a potential causal mutation that should be further verified.

Conclusions

We demonstrated novel and significant genetic effects of the PIK3R1 and DUSP1 genes on milk production traits in dairy cows, and our findings provide information for use in dairy cattle breeding.

Keywords

Chinese Holstein DUSP1 Genetic association Milk production PIK3R1 SNP 

Abbreviations

a

additive

AMPK

Adenosine 5′-monophosphate (AMP)-activated protein kinase

d

dominant

DMEM

Dulbecco’s modified Eagle’s medium

DUSP1

Dual specificity phosphatase 1

FBS

Fetal bovine serum

GO

Gene Ontology

GWAS

Genome-wide association studie

Jak-STAT

Janus kinase/signal transducers and activators of transcription

KLF12

Kruppel like factor 12

LD

LINKAGE disequilibrium

MALDI-TOF MS

matrix-assisted laser desorption/ionization time of flight mass spectrometry

MAPK

Mitogen-activated protein kinase

mTOR

mammalian (mechanistic) target of rapamycin

MYBL1

MYB proto-oncogene like 1

PCR

Polymerase chain reaction

PI3K-Akt

Phosphatidylinositol 3′-kinase (PI3K)-Akt

PIK3R1

Phosphoinositide-3-kinase regulatory subunit 1

QTL

Quantitative trait locus

RNA-Seq

RNA sequencing

SNPs

Single nucleotide polymorphisms

TFBSs

Transcription factor binding sites

UTR

Untranslated region

α

substitution

Background

Genomic selection has been widely applied in dairy cattle breeding. The evaluation system with DNA marker technology and genomics has increased the rate of genetic progress for economic traits [1]. Zhang et al. illustrated that the available quantitative trait locus (QTL) lists detected by hundreds of genome-wide association studies (GWASs) and QTL mapping studies improved the performance of genomic prediction in dairy cattle [2]. To date, a large number of QTLs and genetic associations have been reported for milk traits (http://www.animalgenome.org/cgi-bin/QTLdb/index). Nowadays, RNA sequencing (RNA-Seq) has been proved to be an effective tool to identify crucial functional genes for complex traits in humans, domestic animals, and plants [3, 4, 5]. In a previous study, the liver transcriptomes of Chinese Holstein cows in the dry period, early lactation, and peak of lactation, were analyzed and the expression of phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1; P value = 0.0009) and dual specificity phosphatase 1 (DUSP1; P value = 0.00005) were found significantly decreased and increased in the peak of lactation compared to that in the dry period, respectively. Moreover, the PIK3R1 gene was linked with metabolic gene ontology (GO) terms and pathways, including protein phosphatase binding, protein transport, positive regulation of glucose import, and AMPK (adenosine 5′-monophosphate (AMP)-activated protein kinase), insulin, PI3K-Akt [phosphatidylinositol 3′-kinase (PI3K)-Akt], mTOR [mammalian (mechanistic) target of rapamycin], and Jak-STAT (janus kinase/signal transducers and activators of transcription) signaling pathways, and the DUSP1 gene was linked with inactivation of mitogen-activated protein kinase (MAPK) activity, protein binding, protein dephosphorylation, and MAPK signaling pathway [6], implying that the two genes were involved in milk metabolisms.

PIK3R1 is the regulatory subunit 1 of PI3K that plays an important role in the metabolic actions of insulin in the PI3K signaling pathway. DUSP1, which dephosphorylates c-Jun N-terminal kinase and p38 MAPK, is a negative regulator of MAPK involved with lipid, glucose and energy metabolisms, mitochondrial biogenesis, immune, and various diseases [7, 8, 9, 10, 11, 12]. In addition, the PIK3R1 gene is located on chr.20:14.0466 cM within a distance of 1.95 ~ 3.97 cM to the reported QTLs that have large effects on protein yield [13, 14], and it is 0.38 ~ 2.80 Mb away from five SNPs significantly associated with milk production traits, ARS-BFGL-NGS-16696, BTA-51542-no-rs, ARS-BFGL-NGS-45127, ARS-BFGL-NGS-29910, and Hapmap50995-BTA-51556, identified by the previous GWAS [15]. The DUSP1 gene (chr.20: 5.47596 cM) was found to be within the reported QTL regions that were confirmed to have large genetic effects on fat yield [14] and protein yield [13], and within 0.044 ~ 3.50 Mb from the four SNPs, ARS-BFGL-NGS-48030, Hapmap54098-rs29010434, Hapmap49207-BTA-51446, and Hapmap36217-SCAFFOLD290026_21689, significantly associated with milk traits [15]. These data suggest that PIK3R1 and DUSP1 might be potential candidate genes for milk production traits in dairy cows. Hence, in this study, the single nucleotide polymorphisms (SNPs) of the two genes were identified by re-sequencing and then their genetic effects on milk yield, fat yield, fat percentage, protein yield, and protein percentage were investigated using single-locus and haplotype-based association analyses.

Materials and methods

Animal, sample and phenotypic data collection

Chinese Holstein cows were maintained with the same feeding conditions in 22 dairy farms belonging to the Sanyuan Lvhe Dairy Farming Centre (Beijing, China), and 1067 cows from 40 sire families were selected for the study. The semen of 40 sires and blood samples of 1067 cows respectively were collected for SNP discovery and association analysis. DNAs were extracted from the semen and blood samples using a salt-out procedure and TIANamp Blood DNA Kits (Tiangen, Beijing, China), respectively. The quantity and quality of the extracted DNA samples were measured by using a NanoDrop 2000 spectrophotometer (Thermo Scientific, Hudson, NH, USA) and gel electrophoresis respectively. The phenotypic data for 305-day milk yield, fat yield, fat percentage, protein yield, and protein percentage were provided by the Beijing Dairy Cattle Centre (http://www.bdcc.com.cn/; Beijing, China). The descriptive statistics of the phenotypic values for milk production traits in the first and second lactations are presented in Table 1.
Table 1

Descriptive statistics of the phenotypic values for milk production traits

 

Lactation

Milk yield, kg

Fat yield, kg

Fat percentage, %

Protein yield, kg

Protein percentage, %

Mean

1

10,379.81

350.55

3.387

313.78

3.024

2

10,859.85

390.12

3.599

322.20

2.970

Standard deviation

1

1476.18

60.70

0.423

48.20

0.198

2

1876.61

83.85

0.504

57.63

0.192

Maximum

1

14,505.68

537.97

4.742

457.53

3.508

2

16,512.08

658.25

5.431

467.03

3.538

Minimum

1

6057.96

184.80

2.059

157.73

2.257

2

4756.94

145.05

2.212

137.86

2.199

Coefficient of variation

1

14.22

17.31

12.490

15.36

6.548

2

17.28

21.49

14.004

17.89

6.465

SNP identification and genotyping

The Primer3 (http://bioinfo.ut.ee/primer3-0.4.0/) was used with the bovine reference genome sequence (NC_037347.1) template to design primers that would amplify the entire coding region and 2000 bp of the 5′ and 3′ flanking regions of the PIK3R1 and DUSP1 genes (Additional file 1). Primers were synthesized by the Beijing Genomics Institute (BGI, Beijing, China). Forty semen DNAs with equal concentrations (2.5 ng) for each DNA, were randomly mixed into two pools of 20 sires each and used for all the polymerase chain reactions (PCR). PCR was performed with the conditions presented in Additional file 1. After the amplification, the purified PCR products were sequenced using an ABI3730XL DNA analyser (Applied Biosystems, Foster City, CA, USA), and the sequencing data were analyzed by using CHROMAS (version 2.23) to identify the potential SNPs. The identified SNPs were then individually genotyped using Sequenom MassArray for all the 1067 cows by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS, Sequenom MassARRAY, Bioyong Technologies Inc., HK).

Linkage disequilibrium (LD) estimation and association analyses

The extent of LD between the identified SNPs were estimated using Haploview 4.2 (Broad Institute of MIT and Harvard, Cambridge, MA, USA). The single-locus and haplotype-based association analyses in the first and second lactations for milk production traits were performed using the mixed procedure of SAS 9.13 software with the following animal model: y = μ + HYS + b × M + G + a + e, where, y is the phenotypic value of each trait for each cow; μ is the overall mean; HYS is the fixed effect of farm, year and season of calving; b is the regression coefficient of covariant M; M is the fixed effect of calving month; G is the genotype or haplotype combination effect; a is the individual random additive genetic effect, distributed as \( \mathrm{N}\ \left(0,\mathbf{A}{\updelta}_a^2\right) \), with the additive genetic variance \( {\updelta}_a^2 \); and e is the random residual, distributed as \( \mathrm{N}\ \left(0,\mathbf{I}{\updelta}_{\mathrm{e}}^2\right) \), with identity matrix I and residual error variance \( {\updelta}_{\mathrm{e}}^2 \). Each trait was analyzed separately and each SNP/haplotype block was also fitted separately. Bonferroni correction was applied, and the significant level was equal to the raw P value divided by number of genotypes or haplotype combinations. Furthermore, the additive (a), dominant (d), and substitution (α) effects were calculated using the following formulas: \( \mathrm{a}=\frac{\mathrm{AA}-\mathrm{BB}}{2};\mathrm{d}=\mathrm{AB}-\frac{\mathrm{AA}+\mathrm{BB}}{2};\upalpha =\mathrm{a}+\mathrm{d}\ \left(\mathrm{q}-\mathrm{p}\right) \), where, AA, BB, and AB are the least square means of the milk production traits in the corresponding genotypes, p is the frequency of allele A, and q is the frequency of allele B [16].

Transcription factor binding site (TFBS) prediction and dual-luciferase assay

The MatInspector (https://david.ncifcrf.gov/home.jsp) was used to predict the changes of the TFBSs (Matrix similarity threshold, MST > 0.90) caused by the SNPs in the 5′ flanking or UTR region of the two genes. The fragments containing the binding sites of transcription factor in the 5′ flanking region of the DUSP1 gene were synthesized by Genewiz company (Suzhou, China) and cloned into the pGL4.14 Luciferase Assay Vector (Promega, Madison, WI). The plasmid constructs were sequenced to confirm the integrity of each insertion, and purified with an Endo-free Plasmid Maxi Kit (ComWin Biotech, Beijing, China). The human embryonic kidney 293 T (HEK 293 T) cells were grown in Dulbecco’s modified Eagle’s medium (DMEM; Gibco, Life Technologies, Carlsbad, CA) supplemented with 10% fetal bovine serum (FBS; Gibco), and maintained at 37 °C in a humidified incubator with 5% CO2. Cells were seeded in the 24-well plates at approximately 2 × 105 cells per well before transfection. For each well, 500 ng of the constructed plasmid was co-transfected along with 10 ng of pRL-TK Renilla luciferase reporter vector (Promega) using Lipofectamine 3000 (Invitrogen, CA, USA) according to the manufacturer’s protocol. All the experiments were performed in triplicate. The cells were harvested at 48 h after transfection and the activities of firefly and renilla luciferases were measured using a Dual-Luciferase Reporter Assay System (Promega) on a Modulus microplate multimode reader (Turner Biosystems, CA, USA). The normalized luciferase data (firefly/renilla) were used to calculate the average statistics of the replicates.

Results

Identification of polymorphisms

The entire coding region and 2000 bp of 5′ and 3′ flanking regions of the PIK3R1 and DUSP1 genes were re-sequenced. Six SNPs were identified in PIK3R1, including rs42590258 in the 5′ untranslated region (UTR), rs210389799, rs208819656, and rs41255622 in the 3′ UTR, and rs133655926 and rs211408208 in the 3′ flanking region. Four SNPs were found in DUSP1, including rs207593520 in the 5′ flanking region, rs208460068 in the 3′ UTR, and rs209154772 and rs210000760 in the 3′ flanking region (Table 2). The number of cows with different genotypes in the first and second lactations are presented in Table 2, and the allelic and genotypic frequencies are also shown.
Table 2

Detailed information about the identified SNPs

Gene

SNP

GenBank No.

Position (UMD3.1)

Location

Allele

Allelic frequency

Genotype

Genotypic frequency

PIK3R1

c.*208G > A

rs42590258

chr20:11410254

5’UTR

G

0.64

AA

0.13

A

0.36

AG

0.46

  

GG

0.41

c.*2776 T > C

rs210389799

chr20:11329079

3´UTR

T

0.73

CC

0.07

C

0.27

TC

0.41

  

TT

0.52

c.*2962 T > C

rs208819656

chr20:11328893

3´UTR

T

0.72

CC

0.07

C

0.28

CT

0.42

  

TT

0.51

c.*6275 T > A

rs41255622

chr20:11325580

3´UTR

T

0.52

AA

0.23

A

0.48

AT

0.50

  

TT

0.27

g.11323546C > T

rs133655926

chr20:11323546

3´flanking region

C

0.52

CC

0.27

T

0.48

TC

0.51

  

TT

0.22

g.11323118G > A

rs211408208

chr20:11323118

3´flanking region

G

0.72

AA

0.07

A

0.28

AG

0.42

  

GG

0.51

DUSP1

g.4453141 T > G

rs207593520

chr20:4453141

5´flanking region

G

0.35

GG

0.13

T

0.65

GT

0.44

  

TT

0.43

c.*1505G > A

rs208460068

chr20:4449625

3´UTR

A

0.31

AA

0.07

G

0.69

AG

0.47

  

GG

0.46

g.4448024C > T

rs209154772

chr20:4448024

3´flanking region

C

0.68

CC

0.46

T

0.32

TC

0.45

  

TT

0.09

g.4447105C > G

rs210000760

chr20:4447105

3´flanking region

C

0.68

CC

0.46

G

0.32

CG

0.45

  

GG

0.09

Note: UTR untranslated region

Single-locus association analyses with five milk production traits

For PIK3R1 gene, the single-locus association results (Table 3) showed that the rs42590258 was significantly associated with milk yield (P values = 0.0373 and 0.0233) and fat yield (P values = 0.0461 and 0.0065) in the first and second lactations, and protein percentage in the first lactation (P value = 0.0131), respectively. The SNP, rs208819656, was strongly associated with protein yield in the both lactations (P values = 0.0258 and 0.0117), fat yield in the first lactation (P value = 0.0272), and milk yield in the second lactation (P value = 0.0207), respectively. The rs41255622 and rs133655926 were significantly associated with milk, fat and protein yields in the first lactation (P values: 0.0032 ~ 0.0437). The rs211408208 had a strong association with fat yield in the first lactation (P value = 0.0111). While, the rs210389799 had no significant association with the five milk traits (P values > 0.05). Interestingly, there were no association between the six SNPs of PIK3R1 and the fat and protein percentage traits, except rs42590258 was associated with the protein percentage in the first lactation (P value = 0.0131). The allele additive, dominant, and substitution effects of the six SNPs of PIK3R1 gene were also calculated, and their significant associations with milk, fat and protein yields were found (P values < 0.05; Additional file 2).
Table 3

Associations of the SNPs in PIK3R1 and DUSP1 genes with milk production traits in two lactations in Chinese Holstein (LSM ± SE)

Gene

SNP

Lactation

Genotype(n)

Milk yield, kg

Fat yield, kg

Fat percentage, %

Protein yield, kg

Protein percentage, %

PIK3R1

rs42590258

1

AA (135)

10,462 ± 86.13a

349.88 ± 3.66a

3.35 ± 0.04

306.8 ± 2.67

2.93 ± 0.01Aa

AG (473)

10,266 ± 65.34b

343.3 ± 2.9ab

3.36 ± 0.03

303.29 ± 2.11

2.96 ± 0.01ab

GG (428)

10,314 ± 65.48ab

342.19 ± 2.91b

3.33 ± 0.03

305.32 ± 2.12

2.96 ± 0.01Bb

P value

0.0373

0.0461

0.3398

0.1916

0.0131

2

AA (99)

10,959 ± 98.39a

391.1 ± 4.16ab

3.59 ± 0.04

324.99 ± 3.03

2.97 ± 0.01

AG (328)

10,751 ± 68.47ab

391.5 ± 3.02Aa

3.65 ± 0.03

318.46 ± 2.2

2.97 ± 0.01

GG (297)

10,695 ± 69.91b

383.63 ± 3.08Bb

3.6 ± 0.03

318.94 ± 2.24

2.99 ± 0.01

P value

0.0233

0.0065

0.0538

0.0541

0.0979

rs210389799

1

CC (70)

10,283 ± 104.72

338.75 ± 4.38

3.31 ± 0.04

301.96 ± 3.19

2.94 ± 0.01

TC (427)

10,362 ± 67.57

342.2 ± 2.99

3.31 ± 0.03

305.69 ± 2.18

2.95 ± 0.01

TT (548)

10,381 ± 63.46

345.82 ± 2.83

3.34 ± 0.03

306.91 ± 2.06

2.96 ± 0.01

P value

0.5914

0.0705

0.2506

0.1953

0.4421

2

CC (55)

10,619 ± 119.13

380.41 ± 4.96

3.62 ± 0.05

314 ± 3.62

2.96 ± 0.02

TC (287)

10,770 ± 72.29

385.05 ± 3.18

3.59 ± 0.03

320.02 ± 2.32

2.98 ± 0.01

TT (384)

10,685 ± 65.96

384.05 ± 2.94

3.62 ± 0.03

317.03 ± 2.14

2.98 ± 0.01

P value

0.2598

0.6072

0.6018

0.1141

0.5929

rs208819656

1

CC (72)

10,185 ± 102.59

337.79 ± 4.42ab

3.34 ± 0.04

297.83 ± 3.25Aa

2.96 ± 0.01

CT (419)

10,298 ± 66.79

339.69 ± 2.99a

3.32 ± 0.03

303.08 ± 2.19ab

2.95 ± 0.01

TT (516)

10,332 ± 63.92

344.74 ± 2.87b

3.35 ± 0.03

305.28 ± 2.09Bb

2.96 ± 0.01

P value

0.2816

0.0272

0.2915

0.0258

0.3219

2

CC (58)

10,537 ± 117.02a

389.48 ± 3.43

3.62 ± 0.05

312.93 ± 3.57a

2.97 ± 0.02

CT (286)

10,822 ± 72.57b

391.17 ± 3.04

3.61 ± 0.03

321.96 ± 2.32b

2.98 ± 0.01

TT (376)

10,694 ± 67.37ab

387.81 ± 3.35

3.62 ± 0.03

317.97 ± 2.19ab

2.98 ± 0.01

P value

0.0207

0.5115

0.7832

0.0117

0.8131

rs41255622

1

AA (231)

10,265 ± 72.87a

338.83 ± 3.17a

3.32 ± 0.03

302.24 ± 2.31Aa

2.95 ± 0.01

AT (508)

10,309 ± 64.3a

342.69 ± 2.86ab

3.34 ± 0.03

304.52 ± 2.08a

2.96 ± 0.01

TT (270)

10,449 ± 70.93b

346.79 ± 3.11b

3.33 ± 0.03

308.75 ± 2.26Bb

2.96 ± 0.01

P value

0.013

0.0135

0.7073

0.0032

0.7936

2

AA (174)

10,845 ± 76.65

384.11 ± 3.33

3.63 ± 0.03

320.8 ± 2.5

2.98 ± 0.01

AT (354)

10,737 ± 69.06

386.59 ± 3.06

3.64 ± 0.03

319.91 ± 2.21

2.98 ± 0.01

TT (196)

10,670 ± 78.59

381.95 ± 3.4

3.6 ± 0.03

320.73 ± 2.44

2.97 ± 0.01

P value

0.1056

0.2695

0.428

0.8883

0.5442

rs133655926

1

CC (275)

10,451 ± 70.63a

347.43 ± 3.1a

3.34 ± 0.03

307.9 ± 2.25a

2.95 ± 0.01

TC (519)

10,313 ± 64.02b

343.66 ± 2.85ab

3.35 ± 0.03

304.46 ± 2.08ab

2.96 ± 0.01

TT (229)

10,295 ± 73.94ab

340.67 ± 3.22b

3.33 ± 0.03

303.06 ± 2.34b

2.95 ± 0.01

P value

0.0267

0.0437

0.6163

0.0358

0.6543

2

CC (200)

10,845 ± 76.65

384.11 ± 3.33

3.57 ± 0.03

320.18 ± 2.42

2.96 ± 0.01

TC (358)

10,737 ± 69.06

386.59 ± 3.06

3.62 ± 0.03

318.32 ± 2.23

2.97 ± 0.01

TT (173)

10,670 ± 78.59

381.95 ± 3.4

3.6 ± 0.03

316.28 ± 2.48

2.97 ± 0.01

P value

0.1056

0.2695

0.2678

0.2898

0.6173

rs211408208

1

AA (69)

10,135 ± 105.87

339.36 ± 4.59ab

3.37 ± 0.04

297.57 ± 3.24

2.95 ± 0.01

AG (419)

10,252 ± 67.09

342.8 ± 3.04a

3.34 ± 0.03

301.17 ± 2.16

2.95 ± 0.01

GG (508)

10,260 ± 63.18

348.14 ± 2.86b

3.37 ± 0.03

302.97 ± 2.05

2.96 ± 0.01

P value

0.4168

0.0111

0.2459

0.1178

0.1653

2

AA (57)

10,713 ± 117

385.34 ± 4.88

3.61 ± 0.05

317.64 ± 3.56

2.96 ± 0.02

AG (286)

10,859 ± 72.14

389.01 ± 3.16

3.59 ± 0.03

322.05 ± 2.3

2.97 ± 0.01

GG (371)

10,743 ± 66.59

386.73 ± 2.96

3.62 ± 0.03

317.79 ± 2.16

2.97 ± 0.01

P value

0.1481

0.5837

0.6063

0.0645

0.871

DUSP1

rs207593520

1

GG (128)

10,310 ± 87.86

337.1 ± 3.75a

3.27 ± 0.04

304.66 ± 2.73

2.95 ± 0.01ab

GT (444)

10,372 ± 65.07

344.51 ± 2.89b

3.33 ± 0.03

305.05 ± 2.1

2.94 ± 0.01a

TT (431)

10,397 ± 65.53

345.64 ± 2.91b

3.34 ± 0.03

307.76 ± 2.12

2.96 ± 0.01b

P value

0.5322

0.0201

0.1115

0.1487

0.026

2

GG (99)

11,256 ± 98.44A

395.73 ± 4.18Aa

3.65 ± 0.04

323.58 ± 3.05a

2.97 ± 0.01

GT (303)

10,964 ± 69.52Bb

384.24 ± 3.08Bb

3.59 ± 0.03

318.36 ± 2.24ab

2.97 ± 0.01

TT (310)

10,833 ± 71.81Bb

385.59 ± 3.14b

3.61 ± 0.03

316.61 ± 2.29b

2.97 ± 0.01

P value

<.0001

0.0073

0.2932

0.0418

0.7827

rs208460068

1

AA (76)

10,603 ± 105.06a

347.69 ± 4.41

3.29 ± 0.04

313.22 ± 3.21a

2.96 ± 0.01

AG (473)

10,354 ± 65.04b

344.92 ± 2.88

3.35 ± 0.03

305 ± 2.1Bb

2.95 ± 0.01

GG (467)

10,369 ± 64.51b

343.71 ± 2.86

3.33 ± 0.03

306.61 ± 2.08ab

2.96 ± 0.01

P value

0.0338

0.5601

0.2866

0.0132

0.2481

2

AA (59)

11,344 ± 118.56A

399.21 ± 4.95Aa

3.54 ± 0.05

336.32 ± 3.61A

2.97 ± 0.02

AG (332)

10,842 ± 68.11B

392.67 ± 3.01Aa

3.62 ± 0.03

321.62 ± 2.19B

2.97 ± 0.01

GG (339)

10,617 ± 69.61C

382.41 ± 3.08B

3.62 ± 0.03

315.07 ± 2.24C

2.97 ± 0.01

P value

<.0001

<.0001

0.2052

<.0001

0.969

rs209154772

1

CC (466)

10,307 ± 64.33a

341.63 ± 2.86

3.33 ± 0.03

305.42 ± 2.08a

2.96 ± 0.01

TC (458)

10,316 ± 64.98a

344.11 ± 2.88

3.35 ± 0.03

304.36 ± 2.1Aa

2.95 ± 0.01

TT (91)

10,552 ± 98.79b

345.62 ± 4.16

3.29 ± 0.04

312.43 ± 3.03Bb

2.96 ± 0.01

P value

0.0203

0.3403

0.1808

0.0089

0.1257

2

CC (339)

10,639 ± 69.67Aa

384.61 ± 3.08Aa

3.63 ± 0.03

316.76 ± 2.24Aa

2.98 ± 0.01

TC (318)

10,794 ± 68.91Ab

391.15 ± 3.04c

3.63 ± 0.03

320.77 ± 2.22Aa

2.98 ± 0.01

TT (70)

11,295 ± 111.38B

401.97 ± 4.67Bb

3.58 ± 0.05

334.82 ± 3.41B

2.97 ± 0.02

P value

<.0001

0.0001

0.4368

<.0001

0.6954

rs210000760

1

CC (462)

10,343 ± 64.92a

345.15 ± 2.89

3.35 ± 0.03

306.37 ± 2.1a

2.96 ± 0.01

CG (458)

10,319 ± 64.75Aa

346.4 ± 2.87

3.37 ± 0.03

304.42 ± 2.09Aa

2.95 ± 0.01

GG (91)

10,585 ± 98.43Bb

348.72 ± 4.15

3.3 ± 0.04

312.86 ± 3.02Bb

2.95 ± 0.01

P value

0.0118

0.5743

0.1534

0.0052

0.1864

2

CC (340)

10,614 ± 69.01A

385.45 ± 3.05Aa

3.64 ± 0.03

316.05 ± 2.22Aa

2.98 ± 0.01

CG (319)

10,826 ± 68.53B

392.49 ± 3.03b

3.63 ± 0.03

321.5 ± 2.2Ab

2.98 ± 0.01

GG (71)

11,302 ± 109.96C

401.5 ± 4.61Bb

3.57 ± 0.04

335.23 ± 3.36B

2.97 ± 0.02

P value

<.0001

0.0003

0.2737

<.0001

0.8597

Note: The number in the bracket represents the number of cows for the corresponding genotype; P value shows the significance for the genetic effects of SNPs; a, b, c within the same column with different superscripts means P value < 0.05; A, B, C within the same column with different superscripts means P value < 0.01

As for the DUSP1 gene, the genetic associations between the four identified SNPs and five milk production traits were analyzed. The results showed that the four SNPs were mainly significantly associated with milk, fat and protein yields (P values ≤ 0.0001 and 0.0418), and only one SNP, rs207593520, had strongly association with protein percentage in the first lactation (P value = 0.026). In the first lactation, rs208460068, rs209154772, and rs210000760 were significantly associated with milk and protein yields (P values: 0.0052 ~ 0.0338), while, rs207593520 had associations with fat yield (P value = 0.0201) and protein percentage (P value = 0.026). In the second lactation, the four SNPs, rs207593520, rs208460068, rs209154772, and rs210000760, were strongly associated with milk, fat and protein yields (P values ≤ 0.0001 and 0.0418; Table 3). Further, the additive, dominant and substitution effects of the four SNPs were analyzed, and their significant associations with milk, fat and protein yields were found (P values < 0.05; Additional file 2).

Haplotype-based association analyses with five milk traits

The extent of LD between the six identified SNPs in PIK3R1 were estimated using Haploview 4.2, and six SNPs were found highly linked (D′ > 0.89; Fig. 1) in one block. The haplotype block was formed by five haplotypes, H1 (GCTTTA), H2 (GTATTG), H3 (ATACCG), H4 (GCTTTG), and H5 (GTATTA), with the frequency of 34.7%, 18.7%, 26.8%, 17.6%, and 1.3%, respectively. The haplotype-based association analysis showed that the haplotype block was significantly associated with milk yield (P value < 0.0001), fat yield (P value = 0.0002), protein yield (P value < 0.0001), and protein percentage (P value = 0.0002) in the first lactation, and milk yield (P value = 0.0006), fat percentage (P value = 0.0305), protein yield (P value = 0.003), and protein percentage (P value = 0.0142) in the second lactation, respectively (Table 4).
Fig. 1

Linkage disequilibrium estimated among the SNPs in DUSP1 (a; D′ =0.99 ~ 1.00) and PIK3R1 (b; D′ =0.89 ~ 1.00). The blocks indicate haplotype blocks and the text above the horizontal numbers is the SNP names. The values in boxes are pairwise SNP correlations (D′), while bright red boxes without numbers indicate complete LD (D′ = 1)

Table 4

Associations of haplotype blocks with milk production traits in two lactations in Chinese Holstein (LSM ± SE)

Block

Lactation

Haplotype combination (n)

Milk yield, kg

Fat yield, kg

Fat percentage, %

Protein yield, kg

Protein percentage, %

PIK3R1

1

H1H1 (130)

10,360 ± 89.61bc

343.34 ± 3.81ab

3.33 ± 0.04

304.19 ± 2.78abcd

2.94 ± 0.01Aa

H1H2 (144)

10,048 ± 84.93Aa

337.91 ± 3.63a

3.38 ± 0.03

298.02 ± 2.64Aa

2.97 ± 0.01abc

H1H3 (192)

10,187 ± 79.12ac

336.9 ± 3.41Aa

3.33 ± 0.03

300.14 ± 2.49ACa

2.95 ± 0.01Aac

H1H4 (130)

10,474 ± 86.18Bb

350.09 ± 3.68Bb

3.36 ± 0.04

312.38 ± 2.68Bb

2.99 ± 0.01bc

H2H3 (124)

10,238 ± 87.58abc

335.93 ± 3.73Aa

3.3 ± 0.04

301.63 ± 2.72ACDacd

2.95 ± 0.01ac

H2H4 (65)

10,327 ± 109.41abc

346.65 ± 4.57ab

3.37 ± 0.04

310.8 ± 3.33BCbd

3.01 ± 0.02Bb

H3H3 (68)

10,150 ± 107.13abc

335.16 ± 4.49a

3.32 ± 0.04

299.42 ± 3.27ACDad

2.95 ± 0.02abc

H3H4 (111)

10,448 ± 93.43Bbc

347.85 ± 3.97ab

3.35 ± 0.04

310.36 ± 2.89BDbc

2.98 ± 0.01abc

P value

<.0001

0.0002

0.4417

<.0001

0.0002

2

H1H1 (96)

11,118 ± 100.05Aa

390.74 ± 4.23

3.53 ± 0.04a

328.3 ± 3.08Aa

2.96 ± 0.01ab

H1H2 (106)

10,643 ± 95.67Bb

392.23 ± 4.06

3.69 ± 0.04b

315.26 ± 2.96Bb

2.97 ± 0.01ab

H1H3 (126)

11,056 ± 91.29Aa

395.21 ± 3.9

3.58 ± 0.04ab

324.96 ± 2.84ab

2.95 ± 0.01a

H1H4 (86)

10,863 ± 100.55ab

395.32 ± 4.26

3.64 ± 0.04ab

322.5 ± 3.11ab

2.98 ± 0.01ab

H2H3 (89)

10,920 ± 98.93ab

393.52 ± 4.19

3.6 ± 0.04ab

325.88 ± 3.05b

2.99 ± 0.01ab

H2H4 (42)

10,915 ± 133.11ab

385.35 ± 5.5

3.52 ± 0.05ab

328.33 ± 4.01ab

3.01 ± 0.02b

H3H3 (52)

10,841 ± 124.39ab

388.26 ± 5.19

3.6 ± 0.05ab

321.81 ± 3.78ab

2.97 ± 0.02ab

H3H4 (73)

10,726 ± 110.54ab

387.3 ± 4.64

3.6 ± 0.04ab

319.54 ± 3.38ab

2.99 ± 0.02ab

P value

0.0006

0.4862

0.0305

0.003

0.0142

DUSP1

1

H1H1 (136)

10,202 ± 87.64ab

333.67 ± 3.74

3.29 ± 0.04

301.78 ± 2.72ab

2.96 ± 0.01ab

H1H2 (240)

10,309 ± 73.31ab

343.11 ± 3.19

3.35 ± 0.03

303.68 ± 2.32ab

2.95 ± 0.01ab

H1H3 (241)

10,235 ± 74.22ab

339.15 ± 3.22

3.34 ± 0.03

300.48 ± 2.34Aa

2.94 ± 0.01Aa

H2H2 (112)

10,261 ± 90.23ab

338.92 ± 3.83

3.33 ± 0.04

305.83 ± 2.79ab

2.99 ± 0.01Bb

H2H3 (238)

10,203 ± 73.37a

341.72 ± 3.19

3.38 ± 0.03

301.47 ± 2.33a

2.96 ± 0.01ab

H3H3 (79)

10,526 ± 104.21b

344.29 ± 4.37

3.29 ± 0.04

311.35 ± 3.18Bb

2.96 ± 0.01ab

P value

0.0364

0.0678

0.109

0.0054

0.0131

2

H1H1 (101)

11,043 ± 98.24ADa

402.02 ± 4.16Aa

3.66 ± 0.04

329.32 ± 3.03ACa

2.97 ± 0.01

H1H2 (165)

10,632 ± 82.2Bb

384.09 ± 3.55BCb

3.62 ± 0.03

316.74 ± 2.59BDd

2.97 ± 0.01

H1H3 (156)

10,995 ± 82.56Aa

398.32 ± 3.55Aa

3.62 ± 0.03

327.79 ± 2.58Aa

2.98 ± 0.01

H2H2 (77)

10,248 ± 106.51Cc

376.09 ± 4.48Bb

3.65 ± 0.04

306.23 ± 3.26Bb

2.98 ± 0.01

H2H3 (167)

10,798 ± 82.69ab

395.31 ± 3.57ACa

3.66 ± 0.03

321.26 ± 2.6ADad

2.97 ± 0.01

H3H3 (59)

11,485 ± 118.31Dd

408.46 ± 4.93Aa

3.57 ± 0.05

341.32 ± 3.6Cc

2.97 ± 0.02

P value

<.0001

<.0001

0.4432

<.0001

0.9643

Note: H means haplotype; the number in the bracket represents the number of cows for the corresponding haplotype combination; PIK3R1: H1 (GCTTTA), H2 (GTATTG)), H3 (ATACCG), H4 (GCTTTG), and H5 (GTATTA); DUSP1: H1 (CCGG), H2 (CCGT), and H3 (GTAT); P value shows the significance for genetic effects among the haplotype blocks; a, b, c, d within the same column with different superscripts means P value < 0.05; A, B, C, D within the same column with different superscripts means P value < 0.01

As for DUSP1, the four SNPs were found highly linked in one haplotype block with D´ > 0.99 (Fig. 1). The haplotype block was consist of three haplotypes, H1 (CCGG), H2 (CCGT), and H3 (GTAT), with the frequency of 35.5%, 32.9%, and 30.6%, respectively. The haplotype block was significantly associated with milk yield (P value = 0.0364), protein yield (P value = 0.0054) and percentage (P value = 0.0131) in the first lactation, and milk, fat and protein yields (P values < 0.0001) in the second lactation, respectively. While, no genetic association was observed between the haplotype block and fat percentage in the both two lactations (P values > 0.1; Table 4).

Transcriptional activity of DUSP1 increased by allele T of rs207593520

The MatInspector was used to predict the changes of TFBSs due to the SNPs in the 5′ flanking or UTR region of the two genes, and the allele T of rs207593520 in DUSP1 was found to create the binding sites for the transcription factor MYB proto-oncogene like 1 (MYBL1; MST = 0.91), and the allele G invented the binding sites for kruppel like factor 12 (KLF12; MST = 0.96; Fig. 2a). Further, two plasmids containing allele T or G in the rs207593520 were synthesized for dual-luciferase assay to observe the changes of the transcriptional activity of DUSP1. As the results shown in Fig. 2b, the luciferase activities of two constructs were significantly higher than that of the empty vector (PGL4.14) and blank control (P value < 0.0001), confirming the regulatory role of rs207593520. Moreover, the relative luciferase activity of allele T was significantly higher than that of allele G (P value < 0.0001), implying that the allele T of rs207593520 in DUSP1 might have higher transcriptional activity than the allele G (Fig. 2b).
Fig. 2

Dual-luciferase activity assay. a Sketches of recombinant plasmids with rs207593520 (T/G) in the 5′ flanking region of DUSP1 gene. Underlined nucleotides represent the transcription factor binding site sequences of MYBL1 or KLF12 (in blue), and the nucleotide in red was the SNP. b Luciferase activity analysis of the recombinant plasmids in HEK 293 T cells. PGL4.14 was the empty vector, Blank was the blank cell, and *** P value < 0.0001

Discussion

Our previous RNA-Seq work considered PIK3R1 and DUSP1 as the candidate genes for milk production traits, and this follow-up investigation first demonstrated that the polymorphisms of the two genes were both mainly significantly associated with milk, fat and protein yields. To our knowledge, the PIK3R1 occupies a center role in the insulin signaling pathway, and it was reported to be associated with alterations in glucose and insulin homeostasis [17]. It can recruit protein kinase A to the lipid droplet in conveying endogenous glucocorticoid-induced lipolysis [18]. Studies also revealed that PIK3R1 influences the serum leptin and body fat [19], apolipoprotein B, and low density lipoprotein cholesterol [20] in female. DUSP1 is belongs to the MKP phosphatase family, and it regulates the MAPK signaling pathway by the dephosphorylation. Studies have uncovered an important regulatory role for DUSP1 in hepatic lipid metabolism [7, 8, 10]. Mice lacking DUSP1 were resistant to the acquisition of a fatty liver suggesting that DUSP1 negatively regulates hepatic fatty acid oxidation [10]. Lawan et al. [9, 21] have reported the contribution of DUSP1 for glucose and energy metabolisms. These data collectively illustrate that PIK3R1 and DUSP1 participate in substance metabolisms, especially lipid metabolisms, and their polymorphisms were found to be significantly associated with milk, fat and protein yields by the association analyses in this study. Additionally, the haplotype analyses were generally used to the genetic variation studies [22, 23]. Our haplotype-based association analyses showed that the six and four SNPs of PIK3R1 and DUSP1 were respectively highly linked, and the haplotype block of the two genes were all significantly associated with milk traits in Holstein cows, which were consistent with the genetic associations of SNPs with the milk traits.

In the present study, the allele T of rs207593520 in the 5′ flanking region of DUSP1 was predicted to invent the TFBSs for MYBL1 and the allele C for KLF12, and further, the transcriptional activity of DUSP1 was found significantly increased by the allele T of rs207593520 in the dual-luciferase assay. It is generally known that the SNPs in TFBSs could lead to allele-specific binding of transcription factors thereby activating or suppressing the gene expression [24, 25, 26]. MYB proteins are nuclear DNA-binding proteins that act as transcriptional transactivators of many genes [27], and MYBL1 has been reported as a master regulator of meiotic genes that are involved in multiple meiotic processes [28]. The transcription factor MYBL1 activates the murine tissue-specific lactate dehydrogenase expression by binding the cAMP-responsive element site [29]. In addition, MYBL1 can act as a transcriptional repressor to suppress the expression of multiple anthocyanin pigment pathway genes [30]. Transcription factor KLF12 is a member of KLFs family, which regulates gene transcription through binding to the CACCC sequence of target genes [31, 32]. Studies also showed that it can bind to the promoter regions of target genes and represses their expression [32, 33, 34, 35]. KLF12 acts to negatively regulate the expression of the decidual marker genes decidual prolactin and insulin like growth factor binding protein 1 in human endometrial stromal cells [32]. KLF12 binds to the promoter region of leukemia inhibitory factor and directly represses its transcription [35]. While, KLF12 can directly activate the expression of early growth response protein 1 to promote the colorectal cancer growth [36]. These data suggest that the transcription factors MYBL1 and KLF12 can activate or repress the expression of their target genes, however, MYBL1 mainly acts as an activator, and KLF12 prefers to be a repressor. Based on our results, we speculated that MYBL1 might activate the expression of DUSP1 by binding the TFBSs caused by allele T of rs207593520, thereby regulating the milk production, and KLF12 might inhibit the DUSP1 expression through binding the TFBSs caused by the allele G to affect the milk production. Hence, the SNP, rs207593520, may be a potential causal mutation for milk yield traits in dairy cows because of its ability to change the transcriptional activity of DUSP1, and the further functional studies are required to validate its role.

Genomic selection is widely used in dairy cattle breeding, and the development of efficient SNP markers can improve the accuracy of the selection. Studies have shown that the SNPs in the functional genes significantly influenced the milk production traits in dairy cattle [37, 38, 39, 40]. Thus, the SNPs with large genetic effects on milk traits could be used as markers to increase the selection efficiency in specific dairy cattle populations. Certainly, the significant SNPs of PIK3R1 and DUSP1 genes identified in this study could also be used for genomic selection in dairy cattle.

Conclusion

In conclusion, this is the first study to reveal the significant genetic effects of PIK3R1 and DUSP1 genes on milk production traits in dairy cows, and the valuable SNPs could be used for the genomic selection in dairy cattle. In addition, the rs207593520 in DUSP1 was highlighted as a functional mutation for milk traits that could change the transcriptional activity of DUSP1 gene. Further, the functional validation experiments should be performed to reveal the molecular regulatory mechanisms of PIK3R1 and DUSP1 genes on milk synthesis metabolism.

Notes

Acknowledgements

We appreciate Beijing Dairy Cattle Center for providing the phenotypic data.

Authors’ contributions

DS conceived and designed the experiments, YY prepared the DNA samples for SNP identification and genotyping with the help of LL and YL, BH, YY and LS analyzed the data, and the manuscript was prepared by BH and DS. All authors read and approved the final manuscript.

Funding

This work was financially supported by the National Natural Science Foundation of China (31872330, 31802041), Beijing Dairy Industry Innovation Team (BAIC06–2018/2019), Beijing Science and Technology Program (D171100002417001), National Science and Technology Programs of China (2013AA102504), earmarked fund for Modern Agro-industry Technology Research System (CARS-36), and the Program for Changjiang Scholar and Innovation Research Team in University (IRT_15R62).

Ethics approval and consent to participate

All experiments were carried out in accordance with Guide for the Care and Use of Laboratory Animals and approved by the Institutional Animal Care and Use Committee (IACUC) at China Agricultural University (Beijing, China; permit number: DK996).

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Supplementary material

40104_2019_392_MOESM1_ESM.xlsx (16 kb)
Additional file 1. Table S1. Primers and procedures for PCR used in SNP identification.
40104_2019_392_MOESM2_ESM.xlsx (15 kb)
Additional file 2. Table S2. Additive, dominant and allele substitution effects of SNPs on milk production traits in Chinese Holstein.

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© The Author(s). 2019

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  1. 1.Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal BreedingChina Agricultural UniversityBeijingChina
  2. 2.Beijing Dairy Cattle CenterBeijingChina

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