Polymorphism in promoter of SIX4 gene shows association with its transcription and body measurement traits in Qinchuan cattle

Gene 656 (2018) 9–16

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Gene journal homepage: www.elsevier.com/locate/gene

Research paper

Polymorphism in promoter of SIX4 gene shows association with its transcription and body measurement traits in Qinchuan cattle

T

Dawei Weia,b,1, Sayed Haidar Abbas Razaa,b,1, Jiupan Zhangc, Linsheng Guia, Siddiq Ur Rahmand, ⁎ Rajwali Khana, Seyed Mahdi Hosseinie, Hubdar Ali Kalerif, Linsen Zana,b, a

College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China National Beef Cattle Improvement Center of Northwest A&F University, Yangling 712100, China c Guyuan Branch of Ningxia Academy of Agriculture and Forestry Sciences, 756000 Guyuan, China d College of Life Sciences, Northwest A&F University, 712100 Yangling, China e College of Animal Science and Technology, Huazhaong Agricultural University, Wuhan, Hubei 430070, China f Department of Animal Science and Aquaculture, Dalhousie University, Canada b

A R T I C L E I N F O

A B S T R A C T

Keywords: SIX4 gene promoter SNPs Body measurement traits Qinchuan cattle

The sine oculis homeobox homolog 4 (SIX4) gene belongs to the SIX gene family, which plays a critical role in muscle regeneration and early stages of ontogeny. This study aimed to detect promoter variations of bovine SIX4 genes in Qinchuan cattle, and to evaluate the effect of transcription regulations and body measurement traits. Quantitative real-time PCR (qPCR) results showed that the mRNA expression levels of SIX4 gene were found significantly highest in longissimus thoracis tissue and individual before attaining the stage of physiological maturity. Using sequencing technology on a total of 428 Qinchuan cattle, seven single nucleotide polymorphisms (SNPs) were identified in the promoter region of SIX4, and seven haplotypes representing 18 potential transcription factor compositions of polymorphic potential cis-acting elements. Association analysis indicated that the H3-H3 diplotype performed greater withers height, chest depth, chest circumference, back fat thickness and ultrasound loin muscle area (P < 0.05) than H5-H6, which were consistent with the promoter activity of Hap3 haplotype was higher than the Hap5 and Hap6 haplotype in vitro. These potential transcription factor information and combined genotypes H3-H3 of the SIX4 gene can be used as a molecular marker for selection of economic traits in Qinchuan cattle.

1. Introduction China cattle beef industry is growing rapidly to meet the meat demand of large population. The Qinchuan breed of cattle (Bos taurus) is an indigenous beef breed having peculiar qualities and physical features. This breed is utilized widely in beef production in China and elsewhere. However, Qinchuan cattle exhibit a number of limitations compared to imported commercial beef cattle breeds, such as slow growth rate and underdeveloped hind hips. Therefore, these traits have been recognized as primary goals for genetic improvement of the Qinchuan breed. Traditional methods of breed improvement through breeding and selection in large ruminants such as cattle needs decades and still very difficult to be achieved due to long generation interval

and low fertility rate. Rapid progress depends on the identification of reliable molecular markers linked with trait(s) of interests Quantitative trait loci (QTL) analyses have shown that body measurement traits (BMTs) are quantitative traits controlled by numerous genes with only minor individual effects (Boucher et al., 1996). The identification of statistically significant associations between genetic variants within candidate genes provides potentially powerful approach to accelerate breeding efforts with these traits for Qinchuan cattle breed improvement (Hirwa et al., 2011). The Drosophila sine oculis (so) locus gene plays an essential role in patterning the eye imaginal disk In mammals, the so gene family, designated SIX, consist of six members designated as SIX1 to SIX6 and Six proteins are characterized by presence of a Six domain (SD) and Six-

Abbreviations: qPCR, Quantitative real-time PCR; SNPs, single nucleotide polymorphisms; QTL, Quantitative trait loci; BMTs, body measurement traits; SD, Six domain; HD, Six-type homeodomain; MAS, Marker assistant selection; BL, body length; WH, withers height; CD, chest depth; CC, chest circumference; ULA, loin muscle area; BF, back fat thickness; IFC, intramuscular fat content; PIC, polymorphism information content; LD, linkage disequalibrium; GLM, general linear models ⁎ Corresponding author at: College of Animal Science and Technology, Northwest A&F University, 712100 Yangling, China. E-mail address: [email protected] (L. Zan). 1 These authors contributed equally to this study. https://doi.org/10.1016/j.gene.2018.02.059 Received 3 January 2018; Received in revised form 14 February 2018; Accepted 23 February 2018 Available online 26 February 2018 0378-1119/ © 2018 Published by Elsevier B.V.

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type homeodomain (HD) (Kawakami et al., 2000), which confer specific DNA binding activity and transcription factor function (Liu et al., 2010). Among the SIX gene family members, SIX1 and SIX4 are known to play important roles in myogenesis, and expression of SIX1 and SIX4 is readily detectable in myogenic cells in the precursor of trunk musculature, particularly in muscle precursors of the developing limb buds (Ozaki et al., 2001) In addition, SIX4 participates in myogenesis during muscle regeneration through enhancing expression of MyoD (Relaix et al., 2013). Also, SIX4 and Eya cooperatively regulate transcription from the myogenin promoter through direct binding to the MEF3 site in cultured cells (Liu et al., 2010). Furthermore, SIX1 and SIX4 drive the transformation of slow-twitch toward fast-twitch (glycolytic) fate during myogenesis in adult mouse muscle (Grifone et al., 2004). Slow-twitch and fast-twitch muscles fibers are principal factors influencing muscles characteristics and meat tenderness (Renand et al., 2001). Taken together, these data indicate that SIX4 is critical for skeletal myogenesis and skeleton muscle development. Previous studies have demonstrated that SIX4 gene function appears to be closely associated with muscle development. In addition, G. Wang et al. (2014) has reported that three single nucleotide polymorphisms (SNPs) exist in the bovine SIX4 exon 2 and 3 were significantly associated with BMTs. For gene promoter region variants influence the enzyme activity by altering the gene expression and transcriptional activity, thereby affecting the individual development (Pastinen and Hudson, 2004). Hence, we hypothesized that the promoter region variants of SIX4 gene might influence transcriptional regulation and association with its BMTs in Qinchuan cattle. Here in, the objectives of this study were to identify the genetic polymorphisms at the 5′UTR of the bovine SIX4 gene and analyze the effect of transcriptional activities that are associated with BMTs in Qinchuan cattle. The knowledge of SIX4 obtained in this study may contribute to further understanding of the roles of SIX4 in myogenesis and provide a new tool for BMTs.

Qinchuan cattle, including 1, 6, 9, 12, 18, 24, 36 and 60 months after birth, and three parallel individuals for each period. Total RNA was extracted using the Total RNA kit (TaKaRa, Dalian, China) and cDNA was synthesized using the PrimeScript™ RT Reagent Kit (Perfect Real Time) (TaKaRa). RT-PCR reaction mixtures (20 μL) contained SYBR Green Real-time PCR Master Mix (TaKaRa), gene-specific primers (Table S1) and template cDNA. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and beta-actin (β-actin) were used as endogenous control gene. The cycling conditions consisted of an initial 5 min at 95 °C, 34 cycles of 30 s at 95 °C, 30 s at 60 °C and 30 s at 72 °C. Reactions were run in triplicate using a 7500 System SDS V 1.4.0 thermocycler (Applied Biosystems, USA). The relative expression levels of the target mRNAs were calculated using the 2−ΔΔCt method (Livak and Schmittgen, 2001).

2. Materials and methods

Potential cis-acting elements with variations located in or adjacent to their recognition sequences within the ~1.3 kb SIX4 promoter were identified using the Genomatix database and web server (http://www. genomatix.de).

2.3. SNP detection and genotyping Two pairs of PCR primers (primer A and B) were designed to amplify a ~1.3 kb promoter region, up to and including the translational start site, of the bovine SIX4 gene (NCBI accession AC_000167, from 73124222 to 73125547). The primer sequences are shown in Table S1. Firstly, we detected the mutations of the SIX4 gene by using the 428 individual DNA samples were mixed with equal molar ratio to form a DNA pool (Sham et al., 2002). Then, PCR amplifications were performed using 428 Qinchuan cattle individual DNA. PCR reactions (50 μL) contained 100 ng of pooled genomic DNA (individual DNA), 1 μM of primer, 1 × buffer (including 1.2 mM MgCl2), 400 μM dNTPs, and 0.8 units of KOD DNA Polymerase (Toyobo, Osaka, Japan). All PCR products were sequenced to verify amplification of the intended target. Finally, the sequences were imported into BioXM software (Version 2.6) for SNP analysis. 2.4. Potential cis-acting elements identification

2.1. DNA samples and data collections This study was performed with a total of 428 female cows (aged 18 to 24 months, and unrelated for at least three generations) randomly selected from the Experimental Farm of National Beef Cattle Improvement Center's experimental farm in Yangling, China. And for this trial, the blood samples of trail animals were collected from the population treated in the condition as coincident as possible, to reduce the background error. They were fed with the same of roughage to concentrate ratio (6:4), in the similar rearing environment (similar temperature, humidly etc.), and in alike management process. BMTs, including body length (BL), withers height (WH), chest depth (CD), chest circumference (CC) were measured as described previously (Gui et al., 2015). Back fat thickness (BF), ultrasound loin muscle area (ULA) and intramuscular fat content (IFC) were measured by ultrasound using Sono-grader (Renco, USA) according to the manufacturer's protocol. Briefly, the measurement parts of BF, ULA and IFC between the numbers 12 to 13 of ribs. Place ultrasonic probe within 5 cm of the spinal and vertical alignment. The data of BF, ULA and IFC were collected by system program. Genomic DNA was extracted from blood samples using a standard method phenol-chloroform protocol (Sambrook and Russell, 2001).

2.5. Cell culture and transfection C2C12 myoblast cells were maintained in DMEM Medium supplemented with 10% fetal bovine serum (FBS) (NBCS; Invitrogen, USA),100 IU/mL penicillin and 100 μg/mL streptomycin at 37 °C and 5% CO2 in an atmospheric incubator. Cells were grown in 24-well plates, overnight to 80–90% confluence at a density of 1.2 × 105 cells. The fragment of 1376 bp of the promoter ranged from −1326 bp to +50 bp harbored different haplotypes were generated by specific primers with the sequence of the XhoI and HindIII restriction sites (Table S1). Amplification products were cloned into vector pMD19-T (TaKaRa) and ligated into the XhoI and HindIII sites of the luciferase reporter vector pGL3-basic digested with the same restriction enzymes XhoI and HindIII (TaKaRa). These plasmids were named pGL3-Haps. The reporter plasmid was co-transfected with plasmid Renilla luciferase reporter plasmid (Promega, USA) into C2C12 myoblast cells with X-tremeGENE HP DNA transfection reagent (Roche, USA). Firefly luciferase activity and Renilla luciferase activity were measured according to the dualluciferase reporter assay standard protocol in three independent experiments. Luciferase activity was measured using the Dual Reporter assay system (Promega Corp) and NanoQuantPlate™ (TECAN, infinite M200PRO)·The level of firefly luciferase activity was normalized to Renilla luciferase activity and expressed as arbitrary units.

2.2. Quantitative PCR analysis of SIX4 gene expression patterns Fourteen tissues (heart, liver, spleen, lung, kidney, rumen, reticulum, omasum, abomasum, small intestine, large intestine, abdominal fat, longissimus thoracis and testicular tissue) were obtained from three two-year-old bulls of Qinchuan cattle. The longissimus thoracis samples were collected from eight developmental stages of male

2.6. Data analyses Allelic frequencies, genotype frequencies, observed and expected 10

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Expression analysis demonstrated that SIX4 had a broader distribution among cattle tissues and organs, but was mostly expressed in longissimus thoracis muscle and testicular tissue. Moderate expression was seen in the abomasum, rumen, large intestine omasum, lung, reticulum and kidney and extremely low levels in abdominal fat, heart, liver and spleen (Fig. 1c).

heterozygosity, Hardy-Weinberg equilibriums and polymorphism information content (PIC) were analyzed statistically according to Nei's methods (Nei, 1979). Linkage disequalibrium (LD) including D' and r2 was assessed using HAPLOVIEW (version 3.32) (Barrett et al., 2004).Haplotypes were obtained using PHASE software (http://www. bioinf.manchester.ac.uk/phase/).Thegeneral linear models (GLM) procedure in SPSS (version 13.0) was performed to associate between single SNPs and BMTs. The linear model 1 was used: Yijkm = u + Gi + Aj + Ak + Sm + Eijkm, where Yijkm were the traits measured on each individual cow, μ was the overall population mean for the traits, Gi was the fixed genotype effect, Aj was the fixed effect of age, Ak was the fixed effect due to the age of dam, Sm was the fixed effect due to the sireand Eijkm was the standard error. We tested for an association between combined genotypes for different haplotypes with ultrasound carcass and body measurement traits, to explore any possible interaction between the different haplotypes. The following statistical linear model 2 was used: Yijkm = u + Gi + Aj + Ak + Sm + Eijkm where Yijkm, μ, Aj, Ak, Sm and Eijkm were the same as for model 1, and Gi was the fixed effect associated with combined genotype.

3.2. Expression pattern of SIX4 in longissimus thoracis at different developmental stages The expression of bovine SIX4 gene in longissimus thoracis at the stages of 6 and 9 months were significantly higher compared with any other stages (Fig. 1d). However, the expression level was dropped dramatically after 12 months, but no significant difference in expression after 18 months and the expression level trend remains table (Fig. 1d). Above all, there seem to be a closely objective fact between growth rate traits and SIX4 gene in Qinchuan cattle.

3.3. Seven SNPs were identified in the 1.326 kb upstream region of the bovine SIX4 gene

3. Results 3.1. Detection of SIX4 expression in bovine tissues and organs

The bovine SIX4 gene is located on chromosome 10, contains three exons and three introns, and encodes a protein of 568 amino acids. In the current study, seven SNPs were identified in the 1.326 kb genomic region upstream of the bovine SIX4 gene by DNA pool sequencing (AC_000167.1: g. −1264 G > A (SNP7); −903 T > G (SNP6); −611 C > T (SNP5); −528 A > T (SNP4); −527 A > C (SNP3); g.−379 C > T (SNP2); −84 A > C (SNP1), respectively) (Fig. 2).

To detect the relative mRNA expression of bovine SIX4 in various organs and tissues, cDNA was used to carry out qPCR from 14 bovine tissues and organs: heart, liver, spleen, lung, kidney, rumen, reticulum, omasum, abomasum, small intestine, large intestine, abdominal fat, longissimus thoracis and testicular tissue. Results showed that RNA of high quality had been obtained from different tissues, which can be used for the further molecular biology research (Fig. 1a and b).

Fig. 1. Expression pattern analysis of bovine SIX4 (a) Fourteen tissues mRNA from one individual were analyzed by agarose gel electrophoresis. Lane 1 to 14 denotes the tissues mRNA of heart, spleen, lung, liver, kidney, rumen, reticulum, omasum, abomasum, longissimus thoracis, small intestine, large intestine, abdominal fat and testicular tissue, respectively. (b) longissimus thoracis mRNA from eight individual development stages were analyzed by agarose gel electrophoresis. Lane 1 to 8 denotes longissimus thoracis mRNA was taken from 1, 6, 9, 12, 18, 24, 36 and 60 months after birth, respectively. (c) Analysis of bovine SIX4 expression pattern in tissues and organs. (d) Expression pattern of bovine SIX4 gene at different developmental stages of Qinchuan cattle. The samples of longissimus thoracis were taken from 1, 6, 9, 12, 18, 24, 36 and 60 months after birth, respectively. SIX4 mRNA expression in was normalized against that of the housekeeping gene GAPDH expressed relative to gene expression in the liver and 24 months, respectively. The value of each column represents the mean ± standard deviation based on three independent experiments. The unpaired Student's t-test was used to detect significant differences. “*” P < 0.05 and “**” P < 0.01.

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Fig. 2. Identification of SNPs in the bovine SIX4 upstream region. A graphical representation of the SIX4 gene upstream region from −1326 to +1 base pairs, predicting the regions with high GC content. Solid line indicates GC percentage on the y-axis, whereas the bp position on the 5′ untranslated region is given on the x-axis. The bottom of the blue area indicates the relative positions of CpG islands. Coordinates are given relative to the translational start site (shown as TSS-1). Arrows indicate the position of the seven SNP loci. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Table 1 Genotype frequencies (%) of the SIX4 gene for the SNPs in the Qinchuan cattle populations. Loci

Genotypic frequencies (N)

SNP1

AA 0.6449 CC 0.7944 AA 0.4696 AA/CC/TT 0.0935 GG 0.5841

SNP2 SNP3 SNP4/5/6 SNP7

AC 0.3154 CT 0.2056 AC 0.3972 AT/CT/TG 0.3505 GA 0.3458

CC 0.0397 TT 0.0000 CC 0.1332 TT/TT/GG 0.5561 AA 0.0701

Total

Allelic frequencies

χ2 (HWE)

He

Ne

PIC

428

A 0.8026 C 0.8972 A 0.6682 A/C/T 0.2687 G 0.7570

0.0094

0.3169

1.4639

0.2667

5.6194

0.1845

1.2262

0.1675

4.6476

0.4434

1.7966

0.3451

5.0116

0.3930

1.6474

0.3158

1.5442

0.3679

1.5820

0.3002

428 428 428 428

C 0.1974 T 0.1028 C 0.3318 T/T/G 0.7313 A 0.2430

Note: HWE, Hardy-Weinberg equilibrium; χ20.05 = 5.991, χ20.01 = 9.210.

3.4. Genetic polymorphism in 1.326 kb upstream region of Qinchuan cattle SIX4 gene

and ULA in Qinchuan cattle respectively.

We confirmed all seven SNPs by direct sequencing. The genetic parameters of the SIX4 gene, including genotype and allele frequencies, were directly calculated for all 428 animals (Table 1). All of them were displayed three kinds of genotypes expect SNP2 appeared CC and CT genotypes. Genotype distributions of the seven mutations were all in Hardy-Weinberg equilibrium (chi-square test, χ2 < χ20.05). The value of PIC determined by both the Ne and their frequency distribution within the population was used to assess their informativeness level (high, PIC > 0.5; moderate, 0.5 < PIC > 0.25; low, PIC < 0.25) (Sham et al., 2002). In our study, SNP2 had low polymorphism, while the others had intermediate level of polymorphism. Theχ2 test showed that genotypic distributions of these mutations agreed with HardyWeinberg disequilibrium (chi-square test, χ2 < χ20.05).

3.6. The potential cis-acting elements in haplotypes of SIX4 gene To assess the linkage relationships among the seven SNPs, values for D' and r2 between these four SNPs were estimated. The resulting r2 values implied that SNP4, SNP5 and SNP6 were in complete LD (r2 = 1), because r2 values above 0.33 imply LD (Nei, 1979). Thus, these three SNPs (SNP4, SNP5 and SNP6) were analyzed together and marked as a single locus, designated SNP4/5/6 (Table S2). Meanwhile, different haplotypes were constructed in this sample of Qinchuan cattle using PHASE computer program, so as to perform haplotype-based association analysis. Hap1 (-GTCAACA-) had the highest haplotype frequencies (25.8%), followed by Hap2 (-GTCAATC-), Hap3 (-GTCAACC-), Hap4 (-GGTTCCA-), Hap5 (-GGTTACA-), Hap6 (-ATCAACC-) andHap7 (-AGTTCCC-) (Table 3). Analysis of this regions with Genomatix (http://www.genomatix.de) revealed 315 potential cis-acting elements in the ~1.3 kb region when the threshold value was > 0.8, including these seven SNPs. Therefore, those recognition sequences containing wild type or SNPs were evaluated. A total of 18 known and distinct regulatory motifs were screened out, of which nine were scored on wild type and nine were scored on SNPs (Table 4). The potential cis-acting elements number 1,3,4,5,6,10,13,14 and 17 were located in wild type sequences, and 2,7,8,9,11,12,15,16 and 18 were located in SNPs sequences. Detailed information on the SNPs and potential cis-acting elements are presented in Table 4. Compared with the SNP loci and haplotype frequencies, the result showed that Hap7 led to the most mutated sequences, followed by Hap4, which led to 4 mutated sequences. Hap3, which resulted in only one variation in this sequence, had a higher frequency among the Qinchuan cattle studied. We have concluded that individuals with fewer variations were mainly composed of this cattle population.

3.5. Association analysis between single marker and BMTs The seven SNPs were associated with seven economic traits (BL, WH, CD, CC, BF, ULA and IFC) (Table 2). For SNP1, individuals with genotype AA had significantly greater BL (P < 0.01),CD (P < 0.05) and CC (P < 0.05) than those with genotype CC. For SNP2, individuals with genotype TT had significantly (P < 0.05) greater BL compared with genotype CC. For SNP3, individuals with genotype AA had significantly greater BL (P < 0.05), CD (P < 0.05),CC (P < 0.01),BF (P < 0.05) and ULA (P < 0.05) compared with genotype CC. For SNP4/5/6, individuals with genotype AA/CC/TT had significantly greater BL (P < 0.01), WH (P < 0.05), CD (P < 0.05), CC (P < 0.01), BF (P < 0.05) and ULA (P < 0.01) compared with genotype TT/TT/GG. For SNP7, individuals with genotype GG had significantly greater ULA (P < 0.05) than those with genotype AA. These result suggested that allele A in g. −84 A > C, A in g. −527 A > C,T/ C/A in g. −903 T > G/−611 C > T/−528 A > T and G in g. −1264 G > A are associated with an increase in BL, WH, CD, CC,BF 12

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Table 2 Association of different SNP genotypes with body measurement traits in Qinchuan cattle. Loci

Genotypes

BL (cm)

SNP1

AA (276) AC (135) CC (17) P CC (340) TT (88) P AA (201) AC (170) CC (57) P AA/CC/TT (40) AT/CT/TG (150) TT/TT/GG (238) P GG (250) GA (148) AA (30) P

132.034 131.957 125.000 0.001 128.673 132.091 0.020 134.419 129.703 128.298 0.039 137.975 131.071 131.097 0.004 131.618 131.535 133.633 0.208

SNP2

SNP3

SNP4/5/6

SNP7

± 0.492A ± 0.704a ± 1.983Bb ± 0.438b ± 0.860a ± 0.556a ± 0.604 ± 1.044b ± 1.272A ± 0.657B ± 0.521B ± 0.523 ± 0.680 ± 1.511

WH (cm)

CD (cm)

119.159 119.193 116.471 0.062 119.443 117.597 0.486 120.634 117.444 118.351 0.228 124.988 118.827 118.216 0.039 119.068 119.111 118.783 0.776

58.112 58.000 54.941 0.028 58.331 56.483 0.358 59.537 56.774 55.868 0.041 61.663 57.450 57.643 0.028 57.848 58.115 58.000 0.658

± 0.346 ± 0.494 ± 1.393 ± 0.312 ± 0.613 ± 0.393 ± 0.427 ± 0.737 ± 0.859a ± 0.444b ± 0.352b ± 0.365 ± 0.474 ± 1.053

CC (cm)

± 0.347a ± 0.497 ± 2.399b ± 0.312 ± 0.613 ± 0.395a ± 0.429 ± 0.742b ± 0.898a ± 0.464b ± 0.368b ± 0.367 ± 0.477 ± 1.059

161.846 159.886 155.118 0.041 161.793 157.761 0.711 164.791 158.232 155.614 0.003 169.125 159.660 160.414 0.007 161.122 160.878 160.067 0.680

± 0.791a ± 1.131 ± 2.186b ± 0.711 ± 1.397 ± 0.985A ± 0.973 ± 1.681B ± 1.255A ± 1.058B ± 0.840B ± 0.836 ± 1.087 ± 1.414

BF (cm)

ULA (cm2)

IFC (%)

0.875 0.871 0.805 0.292 0.882 0.828 0.086 0.912 0.831 0.848 0.023 0.952 0.851 0.870 0.031 0.862 0.894 0.837 0.236

45.509 43.905 41.907 0.135 44.936 44.567 0.763 46.301 44.065 42.147 0.035 51.159 43.448 44.691 0.000 44.847 44.238 48.043 0.024

7.581 7.391 7.722 0.054 7.486 7.684 0.071 7.482 7.557 7.589 0.440 7.476 7.481 7.564 0.387 7.557 7.483 7.487 0.440

± 0.016 ± 0.023 ± 0.064 ± 0.014 ± 0.028 ± 0.019a ± 0.020 ± 0.035b ± 0.042a ± 0.022b ± 0.017 ± 0.017 ± 0.022 ± 0.048

± 0.613 ± 0.877 ± 1.470 ± 0.554 ± 1.089 ± 0.714a ± 0.776 ± 1.341b ± 1.583A ± 0.817B ± 0.649B ± 0.644b ± 0.837b ± 1.460a

± 0.055 ± 0.079 ± 0.123 ± 0.050 ± 0.098 ± 0.065 ± 0.071 ± 0.122 ± 0.146 ± 0.075 ± 0.060 ± 0.058 ± 0.076 ± 0.168

Note: Values are shown as the least squares means ± standard error. Values with different superscripts within the same column differ significantly at P < 0.05 (a, b) and P < 0.01 (A, B) after Bonferroni correction. Body length (BL),withers height (WH), chest depth (CD), chest circumference (CC), back fat thickness (BF), ultrasound loin muscle area (ULA) and intramuscular fat content (IFC).

Wang et al., 2014) SIX4 has emerged as a candidate for an important regulator of vertebrate development and maintenance of the differentiated state of tissues (Grifone et al., 2005; Yajima et al., 2010). Our work supports the notion that SIX4 is one of the genes that control myogenesis and may influence BMTs. In the present study, the tissue distribution of bovine SIX4 mRNA was highly expressed in longissimus thoracis, which is consistent with the studies of SIX families in mRNA distribution in tissues of other species of such as in human (Boucher et al., 1996), porcine (Wu et al., 2011) and duck (H. Wang et al., 2014). This suggests that SIX4 might play a functional role in skeletal muscle development-differentiation and maturation of muscle cells. In addition, we detected the expression pattern of SIX4 up regulation of expression from 1 to 9 months. However, it's down regulation after 12 months among to eight different developmental stages after birth of male Qinchuan cattle (Fig. 1b). Increasing in skeletal muscle mass is largely determined by muscle fibers hypertrophy during postnatal growth, because of the number and size of muscle fibers unchanged after birth (BROWN, 1987). Additionally, increase in muscle mass solely through muscle fibers hypertrophy would influence body measurement and meat quality (Rehfeldt et al., 2000). Male Qinchuan cattle take 12 and 24 months to attain the stage of physiological and skeletal maturity, which seems closely related with SIX4 higher expression in this stage. Previous studies have shown that genetic polymorphisms in SIX4 are associated with growth and production traits in cattle. G. Wang et al. (2014) identified three polymorphisms (g.1726C > T, g.1886G > T and g.5456G > A) in the exons of the SIX4 gene that were associated with body length, hip height, chest depth and chest circumference traits in Qinchuan cattle. In the present study, a total

3.7. Effects of diplotypes on BMTs To further analyze the associations between the diplotypes of the identified SNPs and BMTs, six diplotypes were identified. However, because the frequencies of other diplotypes were lower than 0.05, they were ignored in further analysis. Compared with the diplotype association results, the H3-H3 diplotypes had significantly greater WH (P < 0.05), CD (P < 0.05), CC (P < 0.05), BF (P < 0.01) and ULA (P < 0.01) than H5-H6 (Table 5). 3.8. Transcriptional activities of SIX4 haplotypes To detect the transcriptional activities of haplotypes, the various haplotypes in the upstream region were cloned and used to drive a luciferase reporter named pGL3-Hap1–7. Transcriptional output was evaluated upon transfection of the corresponding luciferase reporter plasmids into C2C12 cells. We found that Hap3 had a 0.20-fold (P < 0.05), 0.23-fold (P < 0.05), 0.34-fold (P < 0.05), 0.53-fold (P < 0.05), 0.95-fold (P < 0.01) and 1.02-fold (P < 0.01) higher activity comparing with Hap1, Hap6, Hap4, Hap5, Hap2 and Hap7, respectively (Fig. 3). 4. Discussion Identifying the QTLs and candidate gene can be utilized in markerassisted breeding through the manifestation of economically important traits, which will facilitate Qinchuan cattle breeding programs. The variants of candidate gene would be associated with economically important traits such as growth and carcass traits (G. Wang et al., 2014; H. Table 3 Haplotypes of the bovine SIX4 gene and their frequencies in Qinchuan cattle. Haplotype

g.−1264 G > A

g.−903 T>G

g.−611 C>T

g.−528 A>T

g.−527 A>C

g.−379 C>T

g.−84 A>C

Frequency (%)

Hap1 Hap2 Hap3 Hap4 Hap5 Hap6 Hap7

G G G G G A A

T T T G G T G

C C C T T C T

A A A T T A T

A A A C A A C

C T C C C C C

A C C A A C C

0.258 0.151 0.126 0.105 0.081 0.065 0.055

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Table 4 The different potential cis-acting elements between wild types and SNPs sequence in 1.326 kb upstream region of bovine SIX4. Number

Transcription factors

Optimized

Target strand

Cis-acting elements (recognition sequence)

SNPs

1 2 3

KRAB domain zinc finger protein 57 (ZF57) X-box binding factors (XBBF) Nascent polypeptide associated complex and coactivator alpha (NACA) Cell cycle regulators (CDEF) E2F-myc activator (E2FF) ZF5 POZ domain zinc finger (ZF5F) Glucocorticoid responsive and related elements (GREF) Hypoxia inducible factor (HIFF) p53 tumor suppressor (P53F) Fetal Alz-50 clone 1 (FAC1) Hepatocyte nuclear factor 1 beta (HNF1B) Zinc finger and SCAN domain containing 16 (ZNF435.01) Core promoter motif ten elements (MTEN) E-box binding factors (EBOX) PREB core-binding element (PCBE) Zinc finger protein of the cerebellum (ZICF) EGR/nerve growth factor induced protein C & related factors GC-Box factors SP1/GC

0.84 0.9 0.92

− − −

agtTGCCgcggcc cagttgccgTGGCcgcgaa aacaCAGAgactc

WT7 SNP7 (g.−1264 G > A) WT6

0.87 0.85 0.84 0.84 0.93 0.92 0.91 0.88 0.91 0.88 0.93 0.86 0.88 0.88 0.87

− + + − + − + − + − + + + − −

ggggCGCGttttg aaaacGCGCcccgcgac aaaCGCGccccgcga ggggcacgtttTGTTttgg aaacaaaACGTgccccg acgccggtcgcggggCACGttttgt gtaacAACAcg ggcgtgtaGTTAccaag ctTGGTaacaccacgccac tgAGCGtggcggaggagaccc tccgCCACgctcagcct catgcTCAGcctgct atgctCAGCctgctt gggacgggGGGCgtataac acggggGGCGtagaaca

WT5 WT5 WT5 SNP5 (g.−611 C > T) SNP 5 (g.−611 C > T) SNP 5 (g.−611 C > T) WT 3–4 SNP 4 (g.−528 A > T) SNP 3 (g.−527 A > C) WT2 WT2 SNP2 (g.−379 C > T) SNP2 (g.−379 C > T) WT1 SNP1 (g.−84 A > C)

4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

WT stand for wild type. SNP loci are underlined in tables; capital letters are core sequence of the transcription factors, and the value > 80 of this letters Sequence combination with Cisacting elements.

(Ephrussi et al., 1985). Previous studies have shown that the myogenic regulatory factors (MRFs) of MyoD and MyoG can bind to the E-box motif, initiating muscle differentiation and expression of muscle-specific proteins (Liu et al., 2010; Shklover et al., 2007). Further, all SNPs, except SNP7 and SNP6, found within the upstream region were under 5′CpG island methylation regulation according to evaluation of the methylated status (Fig. 2). DNA methylation is involved in stable gene silencing either through interference with transcription-factor binding or through the recruitment of repressors that specifically bind sites containing methylated CG (Tang and Goldman, 2006; Huang et al., 2014). Above all, we hypothesized that the transcriptional activities of haplotypes was associated with the potential transcription factor regulation and the mechanism of hypermethylation. However, for this speculative conclusion, we are required to confirm whether transcription-factor binding and DNA methylation regulation will affect the transcriptional activities of haplotypes in the future. In combination, the H3-H3 diplotypes had significantly greater WH, CD, CC,BF and ULA than H5-H6, which were consistent with the results showing that transcriptional activities of Hap3 were higher than the others. Using the TFSEARCH online tool and dual-luciferase reporter assay to correlation analysis the candidate gene transcriptional

seven SNP loci were identified in the 1.3 kb upstream region. The gene promoter region contains cis-acting elements that interact with transcription factors (Zhao et al., 2016). Association analysis revealed seven economic traits for 428 Qinchuan cattle, which indicated that cattle with the allele A in g. −84 A > C, T in g. −379 C > T,A in g. −527 A > C and T/C/A in g. −903 T > G/−611 C > T/−528 A > T and G in g. −1264 G > Aloci had superior body measurements. Combined with the potential elements in Table 4, we postulate that the potential transcription factors may affect the transcriptional activity, thereby altering metabolism and expression of SIX4, thus affecting growth and carcass quality in Qinchuan cattle. For the haplotypes transcriptional activities analysis, we found that Hap3 had a signification higher activity comparing with Hap1, Hap6, Hap4, Hap5, Hap2 and Hap7 respectively (Fig. 3). The transcriptional activities of Hap3 were significantly higher (P < 0.01) than Hap2, however, only in locus g. −379 C > T exist difference. From the potential cis-acting elements (Table 4), we found that g. −379 C > T mutation resulting in the potential transcription factors E-box binding factors (optimized = 0.93), which is a response element found in some eukaryotes that acts as a protein-binding site and has been found play a major role in regulating gene expression and transcriptional activity

Table 5 Associations of diplotypes with body measurements in Qinchuan cattle. Diplotype

Body measurement BL (cm)

H1-H5 (31) H1-H6 (29) H3-H3 (58) H3-H6 (25) H5-H6 (61) H6-H6 (24) P-value

Meat quality trait WH (cm)

CD (cm)

CC (cm) a

ULA (cm2)

BF (cm) a

IFC (%) a

164.762 ± 1.679

0.927 ± 0.050

46.310 ± 1.327

57.823 ± 0.741

160.344 ± 1.772

0.868 ± 0.033

44.490 ± 1.539

59.300 ± 1.326a

163.267 ± 1.170a

1.016 ± 0.059A

46.425 ± 1.753A

7.270 ± 0.233

a

a

A

7.263 ± 0.207

132.357 ± 1.450

118.524 ± 1.078

59.476 ± 1.120

132.521 ± 0.959

118.740 ± 0.713

133.100 ± 1.715

120.267 ± 1.276a

7.810 ± 0.197 7.528 ± 0.130

0.923 ± 0.053

47.105 ± 1.446

156.588 ± 1.281b

0.751 ± 0.061Bb

42.424 ± 1.850Bb

7.370 ± 0.241

59.108 ± 0.719

162.588 ± 1.719

0.895 ± 0.032

47.443 ± 1.493A

7.638 ± 0.126

0.040

0.023

0.007

0.001

0.056

132.947 ± 1.524

119.211 ± 1.133

58.237 ± 1.178

165.852 ± 1.817

128.857 ± 1.775

116.214 ± 1.320b

56.250 ± 1.327b

132.857 ± 0.930

119.686 ± 0.692

0.071

0.0008

Note: Values are shown as the least squares means ± standard error. Values with different superscripts within the same column differ significantly at P < 0.05 (a, b) and P < 0.01 (A, B) after Bonferroni correction. Body length (BL),withers height (WH), chest depth (CD), chest circumference (CC), back fat thickness (BF), ultrasound loin muscle area (ULA) and intramuscular fat content (IFC).

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Fig. 3. Constitutive activities of the bovine SIX4 haplotypes in vitro. The relative luciferase activities of the haplotypes were used to normalize the promoter activity. The numbers in the left part of the figure refers to the potential cis-acting elements (Table 4) and the histograms in the right part of the figure refer to the transcriptional activities of the candidate haplotypes. Results are expressed as the mean ± standard deviation in arbitrary units based on the firefly luciferase activity normalized against the Renilla luciferase activity for triplicate transfections. The unpaired Student's t-test was used to detect significant differences. “*” P < 0.05 and “**” P < 0.01.

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activities and BMTs was an effective method (Wang et al., 2015). For example, in present study, the activity of Hap3 haplotype was higher than that of the Hap5 and Hap6 haplotype, and the H3-H3 diplotype had the better BMTs than the H5-H6 diplotype. Above all, we infer that the combined genotypes ofH3-H3 diplotypes could be used as a molecular marker of for future selection of BMTs in Qinchuan cattle. 5. Conclusions In summary, we showed that the SIX4 gene was highly expressed in longissimus thoracis tissue, and was highly expressed individual before attaining the stage of physiological maturity. Seven SNPs were identified in the 1.326 kb genomic region upstream of the bovine SIX4 gene. Association analysis with seven economic traits with a population of 428 Qinchuan cattle revealed that individuals with the allele A in g. −84 A > C, T in g. −379 C > T,A in g. −527 A > C, T/C/A in g. −903 T > G/−611 C > T/−528 A > T and G in g. −1264 G > A loci had better BMTs. Additionally, association analysis indicated that the H3-H3 diplotype had better BMTs than others diplotypes, due to alteration of SIX4 transcriptional activity. This information may be used in molecular marker-assisted selection of beef cattle breeding in the future. Conflicts of interest None. Acknowledgements This research was supported by the National Science and Technology Support Projects (No. 2015BAD03B04), the National Modern Agricultural Industry Special Program (No. CARS-37) and the Shaanxi Technological Innovation Engineering Program (No. 2014KTZB02-02-01). Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.gene.2018.02.059. References Barrett, J.C., Fry, B., Maller, J., Daly, M.J., 2004. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263–265. Boucher, C.A., Carey, N., Edwards, Y.H., Siciliano, M.J., Johnson, K.J., 1996. Cloning of the human SIX1 gene and its assignment to chromosome 14. Genomics 33, 140–142.

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polymorphisms of SIX4 gene and their association with body measurement traits in Qinchuan cattle. Gene 539, 107–110. Wang, J., Hua, L., Pan, H., Zhang, L., Li, M., Huang, Y., Li, Z., Lan, X., Lei, C., Li, C., 2015. Haplotypes in the promoter region of the CIDEC gene associated with growth traits in Nanyang cattle. Sci. Rep. 5, 12075. Wu, W., Ren, Z., Wang, Y., Chao, Z., Xu, D., Xiong, Y., 2011. Molecular characterization, expression patterns and polymorphism analysis of porcine Six1 gene. Mol. Biol. Rep.

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