AABArchives Animal BreedingAABArch. Anim. Breed.2363-9822Copernicus PublicationsGöttingen, Germany10.5194/aab-60-285-2017Evaluation of novel SNPs and haplotypes within the
ATBF1 gene and their effects on economically
important production traits in cattleXuHanZhangSihuanZhangXiaoyanDangRuihuaLeiChuzhaoChenHongchenhong1212@126.comLanXianyonglanxianyong79@126.comCollege of Animal Science and Technology, Northwest A&F University,
Shaanxi Key Laboratory of Molecular Biology for Agriculture, Yangling,
Shaanxi 712100, ChinaXianyong Lan (lanxianyong79@126.com) and Hong Chen (chenhong1212@126.com)29August201760328529614April201710July201724July2017This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/This article is available from https://aab.copernicus.org/articles/60/285/2017/aab-60-285-2017.htmlThe full text article is available as a PDF file from https://aab.copernicus.org/articles/60/285/2017/aab-60-285-2017.pdf
AT motif binding factor 1 (ATBF1) gene can promote the expression level of the growth hormone 1 (GH1) gene by
binding to the enhancers of the POU1F1 and PROP1 genes; thus, it affects the growth and
development of livestock. Considering that the ATBF1 gene also has a close
relationship with the Janus kinase–signal transductor and activator of transcription (JAK–STAT) pathway, the objective of this work was to
identify novel single-nucleotide polymorphism (SNP) variations and their
association with growth traits in native Chinese cattle breeds. Five novel
SNPs within the ATBF1 gene were found in 644 Qinchuan and Jinnan cattle for first time using 25 pairs of screening and genotyping
primers. The five novel SNPs were named as AC_000175:g.140344C>G (SNP1), g.146573T>C (SNP2),
g.205468C>T (SNP3), g.205575A>G (SNP4) and
g.297690C<T (SNP5). Among them, SNP1 and SNP2 were synonymous
coding SNPs, while SNP5 was a missense coding SNP, and the other SNPs were
intronic. Haplotype analysis found 18 haplotypes in the two breeds,
and three and five closely linked loci were revealed in Qinchuan and Jinnan
breeds, respectively. Association analysis revealed that SNP1 was
significantly associated with the height across the hip in Qinchuan cattle. SNP2 was found to be significantly related to chest circumference and body side
length traits in Jinnan cattle. SNP3 was found to have significant
associations with four growth traits in Qinchuan cattle. Moreover, the
different combined genotypes, SNP1–SNP3, SNP1–SNP4 and SNP2–SNP5 were
significantly associated with the growth traits in cattle. These findings
indicated that the bovine ATBF1 gene had marked effects on growth traits, and the
growth-trait-related loci can be used as DNA markers for maker-assisted selection (MAS) breeding
programs in cattle.
Introduction
With the fast improvement in living standards in developing countries,
especially China, the demand for beef consumption has increased quickly.
Although cattle breed resources are very abundant in China, poor quality and
low growth rate of many breeds are still barriers to an increase in
cattle production. It is difficult to meet our needs and improve the
breeding speed by using traditional methods; thus, the efficient genetical
methods, such as DNA marker-assisted selection (MAS), should be used to
improve the efficiency of production and lay the foundation for breeding new
breeds (Pedersen et al., 2009). As the most practical and economic method,
the MAS strategy relies on the numerous single-nucleotide polymorphisms (SNPs) associated with production traits. Therefore, more functional SNPs, which could be
applied in MAS breeding of domestic livestock, should be discovered. An
example is the single A-to-G substitution near the ovine CLPG gene, which has been
used for double-muscle livestock breeding (Cockett et al., 1994).
The AT motif binding factor 1 (ATBF1) gene encodes a transcription factor with multiple homeodomains and zinc
finger motifs; thus, it is also named zinc finger homeobox 3 (ZFHX3). ATBF1 was first isolated as
an AT (adenine and thymine)-binding factor of human α-fetoprotein
(AFP) (Morinaga et al., 1991). It was reported to function as a tumor
suppressor in several cancers (Kawaguchi et al., 2016; Sun et al., 2014, 2015). More importantly, it plays an important role in regulating
myogenesis, adipose tissue development and transactivating the cell cycle
inhibitor (Jung et al., 2005; Postigo and Dean, 1997,
1999; Richard and Stephens, 2014).
Furthermore, ATBF1 could promote the expression level of the growth hormone 1 (GH1) gene by binding
to the enhancers of the POU1F1 and PROP1 genes (Araujo et al., 2013; Qi et al., 2008),
which are the key genes in mammalian growth, development and the lactation-related hypothalamic–pituitary–adrenal (HPA) axis pathway (PITX2/PITX1 – HESX1 – LHX3/LHX4 – PROP1 – POU1F1) (Davis et al., 2010; Ma et al., 2017). In addition, another key gene in
the HPA axis pathway, PITX2, has a positive regulation relationship with ATBF1 under the
participation of miR-1 (Huang et al., 2015).
Meanwhile, ATBF1 has close relationships with STAT family genes, which are growth-related genes. STAT3 and STAT5A are two key genes in Janus kinase–signal transducer and
activator of transcription pathway (JAK–STAT), and JAK–STAT is responsible
for promoting the secretion of a variety of cytokines, growth factors and
GH1 (Herrington et al., 2000; Liongue and Ward, 2013; Trovato et
al., 2012). ATBF1 could enhance the suppression of STAT3 signaling by
interaction with PIAS3, which is a protein inhibitor of the activated STAT
family (Lao et al., 2016; Nojiri et al., 2004; S. F. Yang et al., 2016). Thus, it
was surmised that the ATBF1 gene plays an important role in regulating mammalian
growth and development.
SNP research is a crucial step for the application of the genome project in
human and MAS breeding in mammals. The genes mentioned above, CLPG, STAT3,
STAT5A, POU1F1 and PROP1, all have SNPs associated with growth traits, and some SNP genotypes were
found to be significantly associated with mRNA expression levels (Jia et al.,
2015; Lan et al., 2007, 2009; Wu et al., 2014; Zhao et al.,
2013). In humans, functional SNPs that were associated
with disease were found in the ATBF1 gene (Liu et al., 2014; Tsai et al., 2015). Moreover, four SNPs that were significantly associated with goat
growth traits were
identified in the goat ATBF1 gene (Zhang et al., 2015b).
Considering the important roles of the ATBF1 gene in the HPA axis and JAK–STAT pathways, which are related to mammalian growth and development, and the significance of
SNP in biological process and livestock breeding, the purpose of this study
was to identify crucial SNP variations within the ATBF1 gene in native Chinese
cattle breeds. This will also help to promote the understanding of ATBF1 gene function and
better apply the excellent local cattle germplasm resources in cattle MAS
breeding.
Materials and methodsAnimal samples and data collection
Experimental animal samples used in this study were approved by the Faculty
Animal Policy and Welfare Committee of Northwest A&F University
under contract. The care and use of experimental animals fully complied with
local animal welfare laws, guidelines and policies.
Sequence chromas of five novel SNP loci in the bovine ATBF1 gene.
Note: panels (a), (b), (c), (d) and (e) represent the pooling sequence chromas of
SNP1, SNP2, SNP3, SNP4 and SNP5, respectively.
A total of 644 blood samples were collected from healthy and unrelated adult
cattle belonging to two well-known Chinese native cattle breeds, Qinchuan
cattle (459) and Jinnan cattle (185). All Qinchuan individuals were reared
in a native breeding farm in Fufeng County, Shaanxi Province. Jinnan
individuals were reared on a Yuncheng cattle farm in Shanxi Province.
The growth trait data of the Qinchuan cattle were collected from the Qinchuan breeding
farm, including body weight, body height, body length, chest circumference,
hucklebone width, height across the hip, chest width, chest depth, rump length
and hip width. The growth trait data of the Jinnan cattle, including body height, height across the hip, chest
circumference, rump length and body side length, were collected from the Jinnan
cattle farm. All growth trait data were
measured as described by Zhang et al. (2015a).
Amplification PCR primers for screening the novel SNPs
within the bovine ATBF1 gene; bp: base pair.
PCR primer sequences for ATBF1 gene genotyping in cattle; bp: base pairs.
LociPrimer sequence (5′→3′)AT* (∘C)Size (bp)Detection methodP21-SNP1 (g.140344C>G)F inner: AAGAGGAGGAGGAGGGCTGCAAAGGAGTC R inner: AGCTCGTCGTCCAGCTCGCTTGGATAC F outer:GGGGCAGCAGAAGGAGAGAAGCAAGAAG par R outer: TCGACAGGGTCTGGAGCACATTAGGCATTouchdown PCR180/200/325T-ARMS-PCR C allele: 180 bp; G allele: 200 bp; Product size of two outer primers: 325 bpP22-SNP2 (g.146573T>C)F: GGGCAGTGCCTCAGGTAGGA R: CAGCAGGTCCAGGGTGTCCAT61.7231Forced PCR-RFLP (EcoT14 I (StyI)) (TT=231 bp;TC=231+209+22 bp; CC=209+22 bp)P23-SNP3 (g.205468C>T)F: GATTATTGTGCCAGGAAGCC R: GATCTGAACCCAAAGACTGAA60714PCR-RFLP (DdeI) (CC=589 bp; CT=589+440 bp; TT=440 bp)P24-SNP4 (g.205575A>G)F-inner: AGGGCACGTCCCTCTCTCTCACCCGCA R-inner: CACTCTCGTGCTGCTGCAGGTGCGGCF-outer: GGAAGGGCCCCCTGGGAAACCGAGTCACR-outer: TCCTCGTCCTCCTCGGGGAGGCCCTTCTTouch down PCR216/153/316T-ARMS-PCR A allele: 216 bp G allele: 153 bp Product size of two outerprimers: 316 bpP25-SNP5 (g.297690C<T)F: TACAGCATCCTCTGCGTTCT R: CCGTGCCTTCCACCTTGA601235PCR-RFLP (HhaI) (TT=594 bp; CT=594+564 bp; CC=564 bp)
Note: the single nucleic acid that is underlined is
different from the reference sequence, and the change is required for forced
PCR-RFLP and T-ARMS-PCR primer designing.*AT: annealing temperature.
DNA isolation and genomic DNA pool construction
Genomic DNA samples were extracted from the leukocytes of the blood samples
as described by Dang et al. (2014). All genomic DNA samples were diluted to
the working concentration 50 ng µL-1 for the DNA pool construction and
polymerase chain reaction (PCR) amplification. To construct DNA pools, 30 DNA samples were randomly and selected
from the Qinchuan and Jinnan cattle. The two DNA
pools were used as templates for PCR amplification, and the product of
amplification was used to sequence and explore genetic variations in the ATBF1 gene.
Primer design and PCR amplification for SNP screening
To expose novel SNPs in the bovine ATBF1 gene, 20 pairs of primer were designed
using the Primer Premier 5 software based on the bovine ATBF1 gene DNA sequence (NCBI
reference sequence: AC_000175.1) (Table 1). The 25 µL
PCR reaction volume includes 50 ng of genomic DNA from the DNA pool, 0.5 µM of
each primer and 12.5 µL 2 × EcoTaq PCR SuperMix (+dye) (Beijing
TransGen Biotech Co., Ltd., Beijing, China). The touchdown PCR program was
executed as follows: pre-denaturation at 95 ∘C for 4 min, followed by
18 cycles of denaturation at 94 ∘C for 30 s, annealing at 68 ∘C
for 30 s (decreased by 1 ∘C per cycle) and extending at 72 ∘C for
1 kb min-1, then another 22 cycles at 94 ∘C for 30 s, 50 ∘C for
30 s
and 72 ∘C for 1 kb min-1, finally extending at 72 ∘C for 10 min.
The products of PCR amplification were sequenced to screen the SNP loci.
Primer design and genotyping by PCR-RFLP, forced PCR-RFLP and
T-ARMS-PCR methods
DNA pool sequencing and sequence analysis identified five novel SNPs within
the Qinchuan and Jinnan bovine ATBF1 gene, namely, AC_000175:g.140344C>G (SNP1), g.146573T>C (SNP2),
g.205468C>T (SNP3), g.205575A>G (SNP4) and
g.297690C<T (SNP5) (Fig. 1). According to the sequencing results,
PCR restriction fragment length polymorphism (PCR-RFLP), forced PCR-RFLP and
tetra-primer amplification refractory mutation system PCR (T-ARMS-PCR)
methods were used to detect genotypes of Qinchuan and Jinnan individuals
(Table 2). The primers of PCR-RFLP and forced PCR-RFLP were designed by
the Primer Premier 5 software, and T-ARMS-PCR primers were designed on the Primer1
website (http://primer1.soton.ac.uk/primer1.html) (Collins, 2012; Ye et al.,
2001). The genotyping methods used on different SNP loci were introduced as
below:
Agarose gel electrophoresis patterns of five novel SNPs of
the bovine ATBF1 gene.
Note that the letter “M” above the figure represents the DNA marker.
SNPs genotyped with the PCR-RFLP and forced PCR-RFLP methods: SNP3 and SNP5 were
detected using the PCR-RFLP method, and the PCR amplification products were
digested with DdeI and HhaI restriction enzymes. SNP2 was genotyped
using the forced PCR-RFLP method, and the C nucleic acid on g.146575 was
changed to T to make a locus that can be recognized by the EcoT14I (StyI)
restriction enzyme. The PCR reaction volume for the two methods was 13 µL, including 25 ng of genomic DNA, 0.2 µM of each primer and 6.5 µL
of 2 × EcoTaq PCR SuperMix (+dye). The amplification system was as follows:
pre-denaturation at 95 ∘C for 4 min, followed by 35 cycles of
denaturation at 94 ∘C for 30 s, optimal annealing temperature for 30 s
and extending at 72 ∘C for 1 kb min-1, finally extending at 72 ∘C
for 10 min. Then the amplification products were digested with a special
restriction enzyme and special temperature for 12 to 16 h. The volume of
digestion contains 2 U (U is unit of restriction enzyme) restriction enzyme, 2 µL of 10 × buffer,
10 µL of PCR product and 6 µL of distillation H2O.
Then the enzyme-digested products were genotyped using agarose gel
electrophoresis. The electrophoretic band size and genotyping information
are shown in Table 2.
SNPs genotyped with the T-ARMS-PCR method: SNP1 and SNP4 were genotyped using
the
T-ARMS-PCR method for failing to search for a suitable restriction enzyme. The
special primers and genotyping information are exhibited in Table 2. The
PCR reaction volume was 13 µL. The touchdown PCR program (from 68 to
50 ∘C; decreased by 1 ∘C per cycle) was executed for PCR
amplification. Then the products were genotyped using agarose gel
electrophoresis directly.
Statistical analysis
Genotypic frequencies and allelic frequencies were calculated according to
Botstein's method (Botstein et al., 1980). Population genetic diversity
index, homozygosity (Ho), effective allele number (Ne) and polymorphism
information content (PIC) were calculated successively on the MSRcall website
(http://www.msrcall.com/). Hardy–Weinberg equilibrium (HWE), linkage
disequilibrium (LD) structure and haplotypes of the five SNP loci in
Qinchuan and Jinnan breeds were calculated using the SHEsis program
(http://analysis.bio-x.cn) (Li et al., 2009; Q. Yang et al., 2016).
The relationship between genotypes, haplotypes and the growth traits in
Qinchuan and Jinnan populations were analyzed using the SPSS software (version
17.0) (IBM Corp., Armonk, NY, USA). Since all cattle were adult females and
each breed was fed the same nutritional diet on their respective farms, the
basic linear model Y=μ+G+e was used to determine the
relationship between genotypes, haplotypes and growth traits for each breed.
In the formulate, Y denotes the trait data of each animal, μ the overall
mean for each trait, G the effect of genotype and e the random error
(Dang et al., 2014; Zhang et al., 2015a).
ResultsNovel SNP identification and genotyping of the bovine
ATBF1 gene
According to the sequence chromas, five novel SNPs (SNP1 to SNP5) were
identified within the Qinchuan and Jinnan cattle ATBF1 gene (Fig. 1). Among them,
SNP1 and SNP2 were synonymous mutations, which were located at exon 2 and exon 3,
respectively. SNP1 and SNP2 loci code the 503th leucine and the
963th threonine of the cattle ATBF1 protein, respectively. SNP3 and SNP4
were located at intron 3, and SNP4 was close to the exon 4 splicing site (four base
distances). SNP5 was a missense coding SNP at exon 9, resulting in the
2488th amino acid valine to alanine. The genotyping results can be
seen from the agarose gel electrophoresis photos, which shows that SNP1–SNP5 were
successfully genotyped by their own methods (Fig. 2).
Genetic diversity analysis of the bovine
ATBF1 gene
Genotype frequency and allelic frequency were calculated according to the
genotyping results. At the SNP1 locus, the frequency of allele C was
distinctly higher than allele G in the two breeds. Genotype
CC is the most prevalent. At the SNP2 locus, the frequency of TT
was significantly higher than the other genotypes. At the SNP3 locus, the
frequency of allele T is higher than C. At the SNP4 locus, there was
no GG genotype, and the frequency of AG was higher than AA. At the SNP5 locus, genotype frequency of the heterozygote was higher
than the other genotypes, and the frequency of allele T was higher than
C (Table 3).
The genetic diversity parameters Ho, Ne and PIC
of the five loci of the Qinchuan and Jinnan populations were calculated and are shown in Table 3. These results
suggest that these loci are polymorphic in these two cattle breeds. However,
the values of PIC suggest that these loci are low polymorphisms
(0 < PIC < 0.25) and intermediate polymorphisms (0.25 < PIC < 0.5) (Table 3) (Pan et al., 2013). The Hardy–Weinberg equilibrium P value
shows that some loci were at Hardy–Weinberg equilibrium (P > 0.05)
and some were in disequilibrium (P < 0.05).
Linkage disequilibrium (LD) plot (D′ and r2) of five
novel SNP loci within the ATBF1 gene in Qinchuan and Jinnan cattle.
Genotype, allelic distribution and genetic diversity of
five SNP loci of the bovine ATBF1 gene.
Note: aP value (HWE): Hardy–Weinberg equilibrium P value.b Diversity parameters: Ho: gene homozygosity; Ne: effective allele numbers;
PIC: polymorphism information content.
Haplotype frequency within the ATBF1 gene in Qinchuan and Jinnan
cattle.
Haplotype nameSNP1SNP2SNP3SNP4SNP5HaplotypeHaplotype frequencies Qinchuan cattleJinnan cattleHap 1CCCACCCCAC0.0520Hap 2CCTATCCTAT0.0300Hap 3CCTGCCCTGC0.0400.050Hap 4CTCACCTCAC0.1290.059Hap 5CTCATCTCAT0.1290.391Hap 6CTCGCCTCGC0.0490.100Hap 7CTCGTCTCGT0.1630Hap 8CTTACCTTAC0.1110Hap 9CTTGCCTTGC0.0010.100Hap 10GCCATGCCAT0.0220.150Hap 11GCCGCGCCGC0.0140Hap 12GCTATGCTAT0.0180Hap 13GTCACGTCAC0.0480.050Hap 14GTCATGTCAT0.1350Hap 15GTCGCGTCGC0.0440Hap 16GTTATGTTAT0.0170Hap 17GTTGCGTTGC00.041Hap 18GTTGTGTTGT00.059Haplotype and linkage disequilibrium analysis of the five SNP
loci
Haplotype pairwise linkage disequilibrium analysis indicated that there were
a total of 18 haplotypes in Qinchuan and Jinnan cattle. Among these
haplotypes, seven were shared by these two populations. Nine haplotypes were
unique to Qinchuan cattle and two haplotypes were unique to Jinnan cattle. The
frequencies of the haplotypes showed that Hap 7 (CTCGT) and Hap 5 (CTCAT)
were the main haplotypes in the Qinchuan and Jinnan cattle populations,
respectively (Table 4). Based on the D′ and r2 values, three
closely linked loci were revealed in the Qinchuan breed and five were revealed
in the Jinnan breed (Fig. 3). The D′ values were 0.756 (SNP1 and SNP3), 0.608
(SNP1 and SNP4) and 0.624 (SNP2 and SNP5) in the Qinchuan cattle breed. In
the Jinnan cattle breed, the D′ values were 0.640 (SNP1 and SNP3), 0.999 (SNP1
and SNP4), 0.997 (SNP2 and SNP4), 1.000 (SNP3 and SNP4) and 0.696 (SNP4 and
SNP5) (Fig. 3). Thus, we further analyzed the effects of the combined
genotypes above and growth traits in cattle.
Relationships between the genetic variations and growth-related
traits
Association analysis found that different genotypes of the SNP1 locus were
similar, with a significant association with the height across the hip in Qinchuan
cattle (P=0.05), and the heterozygote carriers had the highest value
(Table 5). At the SNP2 locus, the different genotypes were significantly
associated with chest circumference and body side length traits in Jinnan
cattle, and the CC genotype carriers had the highest growth trait index
(Table 5). For SNP3, the different genotypes were found to have a significant
association with chest width, chest depth and hucklebone width growth
traits, and CC carriers had the best growth trait index in Qinchuan
cattle. Moreover, the genotypes had a similar significant association with
body height (P=0.05), and the heterozygote carriers had the best value in
Qinchuan cattle (Table 5). However, no significant association between
different genotypes of SNP4 and SNP5 loci and growth-related traits were
found.
The association analysis found that three and one combined genotypes were
associated with growth traits in Qinchuan and Jinnan breeds, respectively.
At the SNP1–SNP3 loci, the combined genotype CG–CC carriers had significantly
wider chests than the CC–TT carriers in the Qinchuan breed (P<0.05)
(Table 6). At the SNP1–SNP4 loci, the CG–AG carriers had a higher height across the hip than CC–AA carriers in the Qinchuan breed (P=0.05) (Table 6). For
the SNP2–SNP5 loci in Qinchuan cattle, TC–CC had the smallest chest
circumference, chest width and hucklebone width values among all the combined
genotypes (P<0.05) (Table 6). For the SNP1–SNP3 loci in Jinnan cattle, CG–CT
carriers had the smallest body height, height across the hip and body side
length, and CG-CC had the largest chest circumference and rump length, among
all the combined genotypes (Table 6). In addition, no significant association
was found between the other combined genotypes and growth-related traits.
Association of ATBF1 gene SNP3 genotypes and cattle growth
traits.
Note: *(LSM ± SE), LSM: least squares mean; SE: standard error. The LSM values with different superscripts within the same row differ significantly at P<0.05 for a and b and
P<0.01 for A and B.
Associations between combined genotypes and growth traits
in Qinchuan and Jinnan cattle.
Note: *(LSM ± SE), LSM: least squares mean; SE: standard error. The LSM values with different superscripts within the same row differ significantly at P<0.05 for a and b and
P<0.01 for A and B.
Discussion
Due to the important roles of ATBF1 in regulating myogenesis and adipose tissue
development and its close relationship with the HPA axis and JAK–STAT pathways
in livestock science (Huang et al., 2015; Jiang et al., 2014; S. F. Yang et al.,
2016; Zhao et al., 2016), ATBF1 was chosen as the candidate gene. In this study,
we recovered five SNPs in the bovine ATBF1 gene for the first time. Three novel SNPs
were exonic, while the other two novel SNPs were intronic. For
individual genotype identification, three methods, namely PCR-RFLP, forced
PCR-RFLP and T-ARMS-PCR, were applied. For the SNP locus, where the nucleotide
sequence could be recognized using restriction enzymes, the PCR-RFLP method can be used to
identify
individual genotypes (Wang et al., 2013). For the SNP locus without the
sequence that could be recognized using restriction enzymes, the forced PCR-RFLP
primers were designed. This method needs to change one or two nucleotides,
which are close to the SNP locus, to make this sequence recognizable
using restriction enzymes and genotyping (Huang et al., 2014). For the SNP locus,
which is difficult to genotype using the two methods above, T-ARMS-PCR is
available (Li et al., 2014; Wang et al., 2014; Zhang et al., 2015a).
The preferred methods are PCR-RFLP and forced PCR-RFLP because they are
more accurate and mature than T-ARMS-PCR (Cai et al., 2013; Sun et al.,
2013). T-ARMS-PCR is easy to operate, using less time and money, but the
accuracy is lower than the other two methods. This study performed both
PCR-RFLP and T-ARMS-PCR methods to calculate the accuracy of them (Li et
al., 2014). The result showed that the consistency of these two methods is
98.8 %, 40 % of inconsistency was caused by PCR-RFLP and 60 % of inconsistency was caused by
the T-ARMS-PCR method (Li et al., 2014). Our previous study also identified that
the accuracy of T-ARMS-PCR and PCR-RFLP reached 99.07 and 99.69 %,
respectively, based on the sequencing result (Zhang et al., 2015a).
Genetic diversity analysis found that three loci were not at Hardy–Weinberg
equilibrium. The disequilibrium of SNP4 in the two breeds may be caused by
the deficiency of genotype GG. A possible explanation for the
disequilibrium is that artificial selection promotes the mutation of these loci,
and these mutations only happened a few generations ago.
The association analysis found that the synonymous coding SNPs, SNP1 and
SNP2, were associated with three growth-related traits. There are studies
that have the same results as this study, which are that coding SNPs are
associated with economically important production traits. For example, the
synonymous mutation AC_000163:g.18161C>G SNP in
the goat PITX2 gene is associated with milk density in the Guanzhong dairy goat (Zhao et
al., 2013). The synonymous mutation might produce codon usage bias, thereby
influencing the production traits (Lan et al., 2007).
Furthermore, the different genotypes of intronic variation SNP3 were significantly associated with four growth-related traits in Qinchuan cattle. The combined genotypes
containing the
SNP3 locus were significantly associated with chest width in the Qinchuan breed
and five other traits in the Jinnan breed. Studies showed that the intronic mutation
G3072A in sheep IGF2 was associated with skeletal muscle development (Cockett et
al., 1994) and the intronic mutation AC_000163:g.18353TNC in the goat
PITX2 gene was associated with more than 10 milk production traits (Zhao et al.,
2013). The intronic mutation might affect the binding of the DNA sequence
and DNA binding factors, such as transcription factors and splicing factors.
Moreover, intronic mutation might influence the transcriptional efficiency
as well as stability of mRNA (Zhao et al., 2013).
Furthermore, association analysis of genotypes of single SNP loci and growth-related traits is an important way to evaluate the effects of a gene in animal
breeding. However, the association analysis between combined genotypes and
growth related traits will be more reliable and efficient for evaluating the
effects of genetic variations in a gene (Akey et al., 2001; Schaid, 2004).
Thus, we analyzed the association between the combined genotypes with higher
D′
value and growth straits. A total of three different combined genotypes
were found to have effects on four and five different growth traits in Qinchuan
and Jinnan cattle, respectively. These results demonstrated the important
roles of ATBF1 single-nucleotide variations in cattle.
Conclusions
In the present study, three novel SNPs (SNP1, SNP2 and SNP3) and three
combined genotypes (SNP1–SNP3, SNP1–SNP4 and SNP2–SNP5) in the ATBF1 gene were
significantly associated with growth-related traits in cattle. SNP1 was
similarly
significantly associated with the height across the hip in Qinchuan cattle
(P=0.05), and the heterozygote carriers had the highest value. SNP2 was
significantly associated with chest circumference (P<0.05) and body
side length traits (P<0.05) in Jinnan cattle, and the CC
genotype carriers had the highest growth trait index. For SNP3,
associations between ATBF1 genotypes and body height (P=0.05), chest width
(P<0.05), chest depth (P<0.01) and hucklebone width (P=0.05) of Qinchuan cattle were found, and CC carriers had the best
growth trait indexes for the first three traits. Moreover, a total of three
different combined genotypes (SNP1–SNP3, SNP1–SNP4 and SNP2–SNP5) were found to have effects on four and five different
growth traits in Qinchuan and Jinnan cattle, respectively. Thus, SNP1, SNP2
and SNP3 have the potential to be useful DNA markers for the improvement of
growth-related traits in cattle.
The original data are available upon request to the corresponding authors.
The authors declare that they have no conflict of
interest.
Acknowledgements
This work was supported by the National Natural
Science Foundation of China (no. 31672400), Science and Technology
Coordinator Innovative engineering projects of Shaanxi Province
(2014KTZB02-02-02-02) and the Program of National Beef Cattle and Yak Industrial
Technology System (no. CARS-37).
Edited by: Steffen Maak
Reviewed by: Faruk Balci and one anonymous referee
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