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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Genet.</journal-id>
<journal-title>Frontiers in Genetics</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Genet.</abbrev-journal-title>
<issn pub-type="epub">1664-8021</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">1346903</article-id>
<article-id pub-id-type="doi">10.3389/fgene.2024.1346903</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Genetics</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Association analysis between Acetyl-Coenzyme A Acyltransferase-1 gene polymorphism and growth traits in Xiangsu pigs</article-title>
<alt-title alt-title-type="left-running-head">Xiao et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fgene.2024.1346903">10.3389/fgene.2024.1346903</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Xiao</surname>
<given-names>Meimei</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2591347/overview"/>
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<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ruan</surname>
<given-names>Yong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Huang</surname>
<given-names>Jiajin</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
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<contrib contrib-type="author">
<name>
<surname>Dai</surname>
<given-names>Lingang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
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<xref ref-type="aff" rid="aff3">
<sup>3</sup>
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<contrib contrib-type="author">
<name>
<surname>Xu</surname>
<given-names>Jiali</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
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<contrib contrib-type="author" corresp="yes">
<name>
<surname>Xu</surname>
<given-names>Houqiang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<xref ref-type="fn" rid="fn1">
<sup>&#x2020;</sup>
</xref>
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<aff id="aff1">
<sup>1</sup>
<institution>Key Laboratory of Animal Genetics</institution>, <institution>Breeding and Reproduction in the Plateau Mountainous Region</institution>, <institution>Ministry of Education</institution>, <institution>Guizhou University</institution>, <addr-line>Guiyang</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Guizhou Provincial Key Laboratory of Animal Genetics</institution>, <institution>Breeding and Reproduction</institution>, <institution>Guizhou University</institution>, <addr-line>Guiyang</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>College of Animal Science</institution>, <institution>Guizhou University</institution>, <addr-line>Guiyang</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1262114/overview">Nuno Carolino</ext-link>, National Institute for Agricultural and Veterinary Research (INIAV), Portugal</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1546329/overview">Karine Assis Costa</ext-link>, Universidade Estadual Paulista&#x2014;UNESP, Brazil</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/885557/overview">Lucas Lima Verardo</ext-link>, Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM), Brazil</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2641661/overview">Larissa Graciano Braga</ext-link>, S&#xe3;o Paulo State University S&#xe3;o Paulo, Brazil in collaboration with reviewer LV</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Houqiang Xu, <email>gzdxxhq@163.com</email>
</corresp>
<fn fn-type="other" id="fn1">
<label>
<sup>&#x2020;</sup>
</label>
<p>ORCID: Houqiang Xu, <ext-link ext-link-type="uri" xlink:href="https://orcid.org/0000-0002-4696-5671">orcid.org/0000-0002-4696-5671</ext-link>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>02</day>
<month>05</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>15</volume>
<elocation-id>1346903</elocation-id>
<history>
<date date-type="received">
<day>30</day>
<month>11</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>15</day>
<month>04</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2024 Xiao, Ruan, Huang, Dai, Xu and Xu.</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Xiao, Ruan, Huang, Dai, Xu and Xu</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Introduction</title>
<p>Acetyl-Coenzyme A Acyltransferase-1 (<italic>ACAA1</italic>) is a peroxisomal acyltransferase involved in fatty acid metabolism. Current evidence does not precisely reveal the effect of the <italic>ACAA1</italic> gene on pig growth performance.</p>
</sec>
<sec>
<title>Methods</title>
<p>The present study assessed the mRNA expression levels of the <italic>ACAA1</italic> gene in the heart, liver, spleen, lung, kidney of 6-month-old Xiangsu pigs and in the longissimus dorsi muscle at different growth stages (newborn, 6&#xa0;months and 12&#xa0;months of age) using RT-qPCR. The relationship between single-nucleotide polymorphisms (SNPs) of <italic>ACAA1</italic> gene and growth traits in 6-month-old and 12-month-old Xiangsu pigs was investigated on 184 healthy Xiangsu pigs using Sanger sequencing.</p>
</sec>
<sec>
<title>Results</title>
<p>The <italic>ACAA1</italic> gene was expressed in heart, liver, spleen, lung, kidney, and longissimus dorsi muscle of 6-month-old pigs, with the highest level of expression in the liver. <italic>ACAA1</italic> gene expression in the longissimus dorsi muscle decreased with age (<italic>p</italic> &#x003c; 0.01). In addition, four SNPs were identified in the <italic>ACAA1</italic> gene, including exon g.48810 A&#x003e;G (rs343060194), intron g.51546 T&#x003e;C (rs319197012), exon g.55035 T&#x003e;C (rs333279910), and exon g.55088 C&#x003e;T (rs322138947). Hardy-Weinberg equilibrium (<italic>p</italic> &#x003e; 0.05) was found for the four SNPs, and linkage disequilibrium (LD) analysis revealed a strong LD between g.55035 T&#x003e;C (rs333279910) and g.55088 C&#x003e;T (rs322138947) (<italic>r</italic>
<sup>
<italic>2</italic>
</sup> &#x003D; 1.000). Association analysis showed that g.48810 A&#x003e;G (rs343060194), g.51546 T&#x003e;C (rs319197012), g.55035 T&#x003e;C (rs333279910), and g.55088 C&#x003e;T (rs322138947) varied in body weight, body length, body height, abdominal circumference, leg and hip circumference and living backfat thickness between 6-month-old and 12-month-old Xiangsu pigs.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>These findings strongly demonstrate that the <italic>ACAA1</italic> gene can be exploited for marker-assisted selection to improve growth-related phenotypes in Xiangsu pigs and present new candidate genes for molecular pig breeding.</p>
</sec>
</abstract>
<kwd-group>
<kwd>Xiangsu pigs</kwd>
<kwd>
<italic>ACAA1</italic>
</kwd>
<kwd>single-nucleotide polymorphism</kwd>
<kwd>fat deposition</kwd>
<kwd>growth traits</kwd>
</kwd-group>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Livestock Genomics</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1">
<title>1 Introduction</title>
<p>Pork is one of the important sources of animal protein for humans. Improving the growth traits of pigs is an ongoing goal in the field of animal husbandry. Growth traits such as living backfat thickness (LBT), body length (BL), body height (BH), chest circumference (CC), chest depth (CD), and rump circumference (RC) are directly related to the economic efficiency of pigs (<xref ref-type="bibr" rid="B20">Liu et al., 2021</xref>; <xref ref-type="bibr" rid="B49">Zhang et al., 2021</xref>).Growth traits are quantitative traits that are regulated by a few major genes and a large number of minor genes (<xref ref-type="bibr" rid="B3">Boyle et al., 2017</xref>). With the rapid development of molecular breeding and sequencing technologies, many genes that regulate pig growth traits have been identified and confirmed (<xref ref-type="bibr" rid="B33">Shi et al., 2022</xref>).</p>
<p>Acetyl-Coenzyme A Acyltransferase-1 (<italic>ACAA1</italic>) cleaves 3-ketoacyl-CoA to acetyl-CoA and acyl-CoA by catalyzing the &#x3b2;-oxidation of fatty acids in peroxisomes, driving the synthesis and secretion of fatty acids (<xref ref-type="bibr" rid="B42">Wanders et al., 2001</xref>; <xref ref-type="bibr" rid="B43">Wang et al., 2021</xref>). This enzyme is also key in regulating fatty acid oxidation and lipid metabolism (<xref ref-type="bibr" rid="B21">Luo et al., 2018</xref>). The <italic>ACAA1</italic> gene is downstream in the peroxisome proliferator&#x2013;activated receptor (PPAR) signaling pathway. The <italic>PPAR</italic> enzyme critically regulates fatty acid synthesis and transport, catalyzes the synthesis of esterified cholesterol from free cholesterol and long-chain fatty acids, and plays a crucial role in fatty acid metabolism (<xref ref-type="bibr" rid="B15">Li et al., 2017</xref>). Recent research on the <italic>ACAA1</italic> gene has primarily focused on human cancer and metabolic diseases. Emerging evidence indicates that <italic>ACAA1</italic> gene expression is downregulated in hepatocellular carcinoma and renal clear cell carcinoma (<xref ref-type="bibr" rid="B15">Li et al., 2017</xref>; <xref ref-type="bibr" rid="B19">Liu et al., 2015</xref>; <xref ref-type="bibr" rid="B26">Nwosu et al., 2018</xref>; <xref ref-type="bibr" rid="B47">Yan et al., 2017</xref>; <xref ref-type="bibr" rid="B48">Zhang et al., 2019</xref>). The <italic>ACAA1</italic> gene was revealed to be highly expressed in triple-negative breast cancer cells, and inhibiting the <italic>ACAA1</italic> gene decreased the proliferation of triple-negative breast cancer cells (<xref ref-type="bibr" rid="B28">Peng et al., 2023</xref>). <italic>ACAA1</italic> is a type 2 diabetes (T2D) biomarker that can predict the metabolic characteristics of pre-diabetes in mouse models (<xref ref-type="bibr" rid="B12">Kumar et al., 2015</xref>). Research on the <italic>ACAA1</italic> gene in animal husbandry has linked ACAA1 mutation to milk production traits of buffalo. Analysis of the liver transcriptomes and the microarray dataset of Hereford (beef breed) and Holstein-Friesian (dairy breed) bulls with different genetic backgrounds revealed that Hereford bulls were highly involved in fatty acid biosynthesis and lipid metabolism by up-regulating <italic>ACAA1</italic> gene expression as compared to Holstein-Friesian (<xref ref-type="bibr" rid="B17">Lisowski et al., 2014</xref>).</p>
<p>Single Nucleotide Polymorphism (SNP) refers to the DNA sequence polymorphism caused by single nucleotide variation at the chromosome genomic level, and the frequency of this variation is more than 1% in at least one population (<xref ref-type="bibr" rid="B39">Taylor et al., 2001</xref>; <xref ref-type="bibr" rid="B41">Vignal et al., 2002</xref>). Five SNPs (g.-681 A&#x003e;T, g.-24348 G&#x003e;T, g.-806 C&#x003e;T, g.-1868 C&#x003e;T and g.-23117 C&#x003e;T) were identified in the buffalo <italic>ACAA1</italic> gene, among which g.-681 A&#x003e;T, g.-24348 G&#x003e;T, and g.-23117 C&#x003e;T are significantly associated with milk production traits in buffaloes. In addition, the g.-681 A&#x003e;T mutation in the promoter region significantly changed the transcriptional activity (<xref ref-type="bibr" rid="B6">Deng et al., 2023</xref>). A missense variant rs117916664 of the <italic>ACAA1</italic> gene was identified in a Han Chinese early-onset familial Alzheimer&#x2019;s disease (AD) family and found to be associated with early-onset familial AD (<xref ref-type="bibr" rid="B22">Luo et al., 2021</xref>). A genetic polymorphism in the <italic>ACAA1</italic> gene alters the association between endotoxin exposure and asthma (<xref ref-type="bibr" rid="B36">Sordillo et al., 2011</xref>). However, data on the polymorphism of the <italic>ACAA1</italic> gene in pigs is scarce.</p>
<p>Xiangsu pig is a novel breeding strain that utilizes Sutai pig and Congjiang Xiang pig as parents and repeatedly backcrossed with Congjiang Xiang pig as male parent. Congjiang Xiang pig has early sexual maturity, strong fat deposition capacity, and strong disease resistance but slow growth (<xref ref-type="bibr" rid="B18">Liu et al., 2018</xref>; <xref ref-type="bibr" rid="B38">Tang et al., 2018</xref>; <xref ref-type="bibr" rid="B46">Xu et al., 2022</xref>). The SuTai pig is a breed characterized by its high reproductive rate and strong adaptability (<xref ref-type="bibr" rid="B2">Bao et al., 2012</xref>). The Congjiang xiang pig accounts for 87.5% of the genetic lineage within the Xiangsu pig population, allowing for the full inheritance of its genetic traits in subsequent generations (<xref ref-type="bibr" rid="B46">Xu et al., 2022</xref>). Therefore, we selected <italic>ACAA1</italic> gene as a candidate gene for the growth traits of the Xiangsu pig and evaluated the relationship between <italic>ACAA1</italic> gene polymorphism and the growth traits of the Xiangsu pig, which is valuable for Xiangsu pig breeding in the future.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>2 Materials and methods</title>
<sec id="s2-1">
<title>2.1 Experimental animals</title>
<p>The animal experiments fully adhered to the guidelines of the Animal Welfare Committee of Guizhou University (EAE-GZU-2022-E031). The production cycle (farrowing to growing-finishing) of Xiangsu pig is 12&#xa0;months. A total of 184 healthy Xiangsu pigs under the same feeding level were selected to track and record the growth traits (body weight, body length, body height, chest circumference, abdominal circumference, tube circumference, leg and hip circumference and living backfat thickness) of 6-month-old and 12-month-old Xiangsu pigs. The measurement method of body weight, body length, body height, chest circumference, abdominal circumference, tube circumference, leg and hip circumference was referred to as NY/T2894-2016. The probe of the handheld veterinary ultrasound diagnostic device (KX5200) had been positioned vertically on the 10th and 11th thoracic vertebrae of pigs to measure the living backfat thickness of 6-month-old and 12-month-old pigs.</p>
</sec>
<sec id="s2-2">
<title>2.2 Primer design</title>
<p>The upstream and downstream primers were designed by Primer Premier 5.0 software using the pig <italic>ACAA1</italic> gene (accession number: NC_010455.5) and mRNA sequence (accession number: XM_003132103.4); <italic>GADPH</italic> gene (accession number: NC_010447.5) and mRNA sequence (accession number: NM_001206359.1) available in NCBI GeneBank. The primers were synthesized by Beijing Qingke Biotechnology Co., Ltd., (<xref ref-type="table" rid="T1">Table 1</xref>).</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Primer information of <italic>ACAA1</italic> gene sequence.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Primer names</th>
<th align="center">Primer sequences (5&#x2032;&#x2192;3&#x2032;)</th>
<th align="center">Product size/bp</th>
<th align="center">Annealing temperature/&#xb0;C</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center" rowspan="2">ACAA1-Exon7</td>
<td align="left">F:GACTCTTCAGAGGAAGAGAGAGGAG</td>
<td align="center" rowspan="2">649</td>
<td align="center" rowspan="2">57</td>
</tr>
<tr>
<td align="left">R:CAGCAGACGATGACTCTGCTGAT</td>
</tr>
<tr>
<td align="center" rowspan="2">ACAA1-Exon9</td>
<td align="left">F:TTGTTAGATGTGTCCTTCACTGTGG</td>
<td align="center" rowspan="2">675</td>
<td align="center" rowspan="2">63</td>
</tr>
<tr>
<td align="left">R:TCAACTTTCTAGGCCTCCAGAGTT</td>
</tr>
<tr>
<td align="center" rowspan="2">ACAA1-Exon15</td>
<td align="left">F:TGAGGTCTGGCATCTTCTGTGC</td>
<td align="center" rowspan="2">615</td>
<td align="center" rowspan="2">63</td>
</tr>
<tr>
<td align="left">R:CTCAGAGGTGGAGCAGTACAAAGAG</td>
</tr>
<tr>
<td align="center" rowspan="2">ACAA1-qPCR</td>
<td align="left">F:ATGGGGATAACCTCAGAGAACGT</td>
<td align="center" rowspan="2">175</td>
<td align="center" rowspan="2">55</td>
</tr>
<tr>
<td align="left">R:TCTCATTGCCCTTGTCATCGTAG</td>
</tr>
<tr>
<td align="center" rowspan="2">GADPH</td>
<td align="left">F:GGTCGGAGTGAACGGATTT</td>
<td align="center" rowspan="2">247</td>
<td align="center" rowspan="2">60</td>
</tr>
<tr>
<td align="left">R:CCATTTGATGTTGGCGGGA</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: F denotes the upstream primer, and R denotes the downstream primer. bp: base pair.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s2-3">
<title>2.3 Collection of blood and tissue samples</title>
<p>The blood (5&#xa0;mL) of 184 3-month-old Xiangsu pigs was drawn through the jugular vein using an EDTA anticoagulant tube, labeled with the number and date, and stored in a refrigerator at &#x2212;20&#xb0;C for DNA extraction. Three 6-month-old Xiangsu pigs were randomly selected from Xiangsu pigs for slaughter. The heart, liver, spleen, lung, kidney and longissimus dorsi muscle were collected in 2&#xa0;mL cryopreservation tubes and stored in a refrigerator at &#x2212;80&#xb0;C for RNA extraction in order to compare the expression of <italic>ACAA1</italic> gene in different tissues of 6-month-old pigs. Three pigs are selected for slaughter from each age group (newborn and 12&#xa0;months old) at each stage, and the longissimus dorsi muscle was collected and preserved in 2&#xa0;mL cryopreservation tubes in a refrigerator at &#x2212;80&#xb0;C for RNA extraction in order to compare the expression of <italic>ACAA1</italic> at different ages.</p>
</sec>
<sec id="s2-4">
<title>2.4 DNA and RNA extraction</title>
<p>DNA was extracted from 184 blood samples of Xiangsu pigs using the whole blood DNA extraction kit (D3392-01, Omega). Total RNA of heart, liver, spleen, lung and kidney of Xiangsu pigs at 6&#xa0;months of age and total RNA of longissimus dorsi muscle at newborn, 6&#xa0;months and 12&#xa0;months of age was extracted using the TRIzol Extraction Kit (15,596,026; Thermo Fisher). The concentration and purity of DNA and RNA were determined using an ultra-micro spectrophotometer (Thermo Mano Drop 2000), followed DNA by storage at &#x2212;20&#xb0;C and RNA by storage at &#x2212;80&#xb0;C (<xref ref-type="sec" rid="s12">Supplementary Table S1</xref>).</p>
</sec>
<sec id="s2-5">
<title>2.5 cDNA synthesis</title>
<p>cDNA was synthesized using the RNA Reverse Transcription Kit (A234-10; GenStar). By this kit 1&#xa0;&#x3bc;g RNA, 1&#xa0;&#x3bc;L Primer Mix, 10&#xa0;&#x3bc;L 2&#xd7; StarScript III Buffer, 1&#xa0;&#x3bc;L StarScript III Enzyme Mix, and then supplemented with Nuclease-free Water to a final volume of 20&#xa0;&#x3bc;L. The mixture was incubated at 50&#xb0;C for 15&#xa0;min, followed at 85&#xb0;C for 5&#xa0;min. The resulting cDNA was stored at &#x2212;20&#xb0;C for subsequent experiments.</p>
</sec>
<sec id="s2-6">
<title>2.6 Amplification</title>
<p>A 30&#xa0;&#x3bc;L system was used for PCR amplification. The PCR reaction mixture was prepared as follows: 15&#xa0;&#x3bc;L 2&#xd7;Taq PCR Starmix, 10.5&#xa0;&#x3bc;L ddH<sub>2</sub>O, 1.5&#xa0;&#x3bc;L DNA template (40&#xa0;ng/&#x3bc;L), forward and reverse primers, 1.5&#xa0;&#x3bc;L each. The PCR amplification procedure included a pre-denaturation at 94&#xb0;C for 3&#xa0;min; after 35 cycles, 94&#xb0;C denaturation for 30&#xa0;s (Tm see <xref ref-type="table" rid="T1">Table 1</xref>), annealing for 30&#xa0;s, 72&#xb0;C extension for 1&#xa0;min; 72&#xb0;C final extension for 5&#xa0;min; infinite hold at 4&#xb0;C. The PCR products (184) were visualized with 1% agarose gel electrophoresis and sent to Qingke Biological Co., Ltd. for sequencing.</p>
</sec>
<sec id="s2-7">
<title>2.7 Real-time fluorescent quantitative PCR</title>
<p>The total RNA concentration was standardized (1000&#xa0;ng/&#x3bc;L), and 1&#xa0;&#x3bc;g total RNA, 2&#xa0;&#x3bc;L 5 &#xd7; gDNA Eraser Buffer gDNA Eraser, and RNase-Free water were added to the enzyme-free PCR tube to obtain a 10&#xa0;&#x3bc;L reaction volume. The samples were incubated at 37&#xb0;C for 5&#xa0;min to remove gDNA. In addition, a 10&#xa0;&#x3bc;L Master Mix (including 1&#xa0;&#x3bc;L PrimeScript RT Enzyme Mix I, 1&#xa0;&#x3bc;L RT Primer Mix, 4&#xa0;&#x3bc;L 5&#xd7; PrimeScript Buffer 2, and 4&#xa0;&#x3bc;L RNase-Free ddH<sub>2</sub>O) was prepared on ice. Total RNA (without gDNA) and Master Mix were mixed in an enzyme-free PCR tube, incubated at 42&#xb0;C for 15&#xa0;min, then at 85&#xb0;C for 5&#xa0;min, and the resultant cDNA was stored at &#x2212;20&#xb0;C.</p>
<p>A 10&#xa0;&#x3bc;L real-time fluorescence quantitative PCR reaction mixture was constituted as follows: 5&#xa0;&#x3bc;L 2&#xd7; PowerUp SYBP Green Master Mix (A25742; Thermo Fisher), 0.5&#xa0;&#x3bc;L cDNA template, 0.4&#xa0;&#x3bc;L (10&#xa0;&#x3bc;mol/L) forward and reverse primers, and 3.7&#xa0;&#x3bc;L ddH<sub>2</sub>O. The quantitative real-time PCR amplification steps were set as follows: 50&#xb0;C UDG enzyme activation 2&#xa0;min; pre-denaturation at 95&#xb0;C for 2&#xa0;min; 95&#xb0;C denaturation 15&#xa0;s, 55&#xb0;C annealing 30&#xa0;s, 72&#xb0;C extension 30&#xa0;s, 40 cycles; from 72&#xb0;C to 95&#xb0;C, a temperature increase step by 1.6&#xb0;C per second for 15&#xa0;s, and then a temperature decrease step by 1.6&#xb0;C per second from 95&#xb0;C to 60&#xb0;C. Each sample had 3 replicates.</p>
</sec>
<sec id="s2-8">
<title>2.8 Statistical analysis</title>
<p>The presence of SNPs in <italic>ACAA1</italic> sequence was determined via peak plotting against the PCR sequencing reads using the SeqMan software. The genotype, allele frequency, and Hardy-Weinberg equilibrium (HWE) of each mutation site were computed directly, and whether the genotype conformed to HWE was analyzed using the &#x3c7;2 test and <italic>p</italic>-value. Nei&#x2019;s method was employed to analyze the genetic indexes of the population, including gene heterozygosity (<italic>He</italic>), gene homozygosity (<italic>Ho</italic>), and polymorphism information content (<italic>PIC</italic>) (<xref ref-type="bibr" rid="B25">Nei and Roychoudhury, 1974</xref>). The effective number of alleles (<italic>Ae</italic>) is related to the distribution of gene frequency in the population, and the markers were calculated with GenAlEx 6.5 (New Brunswick, NJ, United States) (<xref ref-type="bibr" rid="B27">Peakall and Smouse, 2012</xref>). <italic>PIC</italic> refers to a measure used to assess the ability to detect polymorphism among individuals in a population. The range of polymorphic information content is between 0 and 1, with higher values indicating greater information content and polymorphism in genetic markers (<xref ref-type="bibr" rid="B30">Serrote et al., 2020</xref>). The SHEsis platform (<ext-link ext-link-type="uri" xlink:href="http://analysis.bio-x.cn">http://analysis.bio-x.cn</ext-link>) was used for linkage disequilibrium (LD) analysis and haplotype analysis of single-nucleotide polymorphisms (SNPs) in the <italic>ACAA1</italic> gene (<xref ref-type="bibr" rid="B16">Li et al., 2009</xref>; <xref ref-type="bibr" rid="B34">Shi and He, 2005</xref>). Squared allele-frequency correlations (<italic>r</italic>
<sup>
<italic>2</italic>
</sup>) and Standardized disequilibrium coefficients (<italic>D&#x2032;</italic>) were used to estimate the level of LD (<xref ref-type="bibr" rid="B7">Du et al., 2007</xref>). The <italic>r</italic>
<sup>
<italic>2</italic>
</sup> value is commonly used to evaluate the degree of linkage disequilibrium. When <italic>r</italic>
<sup>
<italic>2</italic>
</sup> &#x003e; 0.33, it is a strong linkage disequilibrium state (<xref ref-type="bibr" rid="B1">Ardlie et al., 2002</xref>). <italic>D&#x2032;</italic> is the normalized coefficient of linkage disequilibrium (LD) divided by the theoretical maximum difference between the observed and expected allele frequencies (<xref ref-type="bibr" rid="B4">Bozorgmehr et al., 2020</xref>). Haplotype and diplotypes analyses were performed based on SNPs.</p>
<p>
<italic>ACAA1</italic> genotype association analysis was performed using IBM SPSS 22.0 (IBM, New York, NY, United States). The least square method was applied to the general linear model (GLM) to examine the association between genotypes and growth traits of 184 Xiangsu pigs. A statistical model, <italic>Y</italic>
<sub>
<italic>ij</italic>
</sub> <italic>&#x003D; &#x3bc;&#x002B;G</italic>
<sub>
<italic>i</italic>
</sub> <italic>&#x002B; Sj &#x002B; e</italic>
<sub>
<italic>ij</italic>
</sub>, was developed where <italic>Y</italic>
<sub>
<italic>ij</italic>
</sub> denotes the observed growth trait; <italic>&#x3bc;</italic> denotes the overall population means; <italic>G</italic>
<sub>
<italic>i</italic>
</sub> represents the fixed effect of the genotype, <italic>Sj</italic> represents the random effect of sire, and <italic>eij</italic> denotes the random error (<xref ref-type="bibr" rid="B24">Naicy et al., 2017</xref>).</p>
<p>The relative expression of the <italic>ACAA1</italic> gene was calculated using the 2<sup>&#x2212;&#x394;&#x394;Ct</sup> method (<xref ref-type="bibr" rid="B29">Saitou and Nei, 1987</xref>), with glyceraldehyde-3-phosphate dehydrogenase (<italic>GAPDH</italic>) gene as the endogenous reference gene, where &#x2206; Ct &#x003D; Ct (target gene)-Ct (<italic>GADPH</italic>), and 2<sup>&#x2212;&#x394;&#x394;Ct</sup> represents the differetial expression multiple relative to <italic>GADPH</italic> expression A one-way analysis of variance (ANOVA) was conducted to compare the differences among the heart, liver, spleen, lung, kidney, and longissimus dorsi muscle of 6-month-old pigs. Additionally, ANOVA was performed to assess the differences in the longissimus dorsi muscle of newborns, 6-month-old, and 12-month-old pigs.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>3 Results</title>
<sec id="s3-1">
<title>3.1 Expression level of <italic>ACAA1</italic> gene in Xiangsu pig tissues</title>
<p>The <italic>ACAA1</italic> gene was expressed in the heart, liver, spleen, lung, kidney, and longissimus dorsi muscle of 6-month-old Xiangsu pigs, with higher levels in the liver and kidney and lower levels in the spleen and longissimus dorsi muscle (<italic>p</italic> &#x003c; 0.01) (<xref ref-type="fig" rid="F1">Figure 1</xref>). Newborn piglets exhibited the highest expression of the <italic>ACAA1</italic> gene (<italic>p</italic> &#x003c; 0.01) in the longissimus dorsi muscle, and it decreased with age (<xref ref-type="fig" rid="F2">Figure 2</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Analysis of the differential expression of the <italic>ACAA1</italic> gene in various tissues at 6&#xa0;months of age. Note: Relative mRNA expression levels were calculated by 2<sup>&#x2212;&#x394;&#x394;Ct</sup> method. &#x201c;A, B, C&#x201d; indicate extremely significant differences among different tissues of six-month-old Xiangsu pigs (<italic>p</italic> &#x003c; 0.01); the same uppercase letters indicate no significant difference.</p>
</caption>
<graphic xlink:href="fgene-15-1346903-g001.tif"/>
</fig>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Analysis of the differential expression of the <italic>ACAA1</italic> gene in dorsal longest muscle at newborn, 6&#xa0;months, and 12&#xa0;months of age. Note: Relative mRNA expression levels were calculated by 2<sup>&#x2212;&#x394;&#x394;Ct</sup> method. &#x201c;A, B, C&#x201d; denotes extremely significant differences in dorsal longest muscle at birth, 6&#xa0;months and 12&#xa0;months of age (<italic>p</italic> &#x003c; 0.01).</p>
</caption>
<graphic xlink:href="fgene-15-1346903-g002.tif"/>
</fig>
</sec>
<sec id="s3-2">
<title>3.2 Analysis of the <italic>ACAA1</italic> gene polymorphism</title>
<p>The presence of SNPs in <italic>ACAA1</italic> gene sequence was determined via peak plotting against the PCR sequencing reads using the SeqMan. Four SNPs were detected in the <italic>ACAA1</italic> gene of Xiangsu pigs, including exon 7 g.48810 A&#x003e;G (rs343060194), intron 9 g.51546 T&#x003e;C (rs319197012), exon 15 g.55035 T&#x003e;C (rs333279910), and exon 15 g.55088 C&#x003e;T (rs322138947) (<xref ref-type="fig" rid="F3">Figure 3</xref>). Using DNA Star software to compare the sequences of three exon mutation sites g.48810 A&#x003e;G (rs343060194), g.55035 T&#x003e;C (rs333279910), g.55088 C&#x003e;T (rs322138947) with the NCBI amino acid reference sequence of the ACAA1 (XP_003132151.1). Three exon mutation sites indicated no changes in the amino acid sequence, therefore they are synonymous mutations.</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Sequencing peaks of four SNPs in the <italic>ACAA1</italic> gene. <bold>(A)</bold> g.48810 A&#x003e;G (rs343060194), <bold>(B)</bold> g.51546 T&#x003e;C (rs319197012), <bold>(C)</bold> g.55035 T&#x003e;C (rs333279910), <bold>(D)</bold> g.55088 C&#x003e;T (rs322138947).</p>
</caption>
<graphic xlink:href="fgene-15-1346903-g003.tif"/>
</fig>
</sec>
<sec id="s3-3">
<title>3.3 Genetic polymorphism analysis of the <italic>ACAA1</italic> gene</title>
<p>Each mutation site had three genotypes. The chi-square test (&#x3c7;2) revealed that the four SNPs loci g.48810 A&#x003e;G (rs343060194), g.51546 T&#x003e;C (rs319197012), g.55035 T&#x003e;C (rs333279910) and g.55088 C&#x003e;T (rs322138947) were in HWE (<italic>p</italic> &#x003e; 0.05) (<xref ref-type="table" rid="T2">Table 2</xref>).</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Genotype frequencies and allele frequencies of <italic>ACAA1</italic> gene in Xiangsu pigs.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">SNPs</th>
<th align="center">rs number</th>
<th align="center" colspan="3">Genotypic frequency</th>
<th align="center" colspan="2">Allele frequency</th>
<th align="center">&#x3c7;2</th>
<th align="center">
<italic>p</italic>
</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center" rowspan="2">g.48810 A&#x003e;G</td>
<td align="center" rowspan="2">rs343060194</td>
<td align="center">AA</td>
<td align="center">AG</td>
<td align="center">GG</td>
<td align="center">A</td>
<td align="center">G</td>
<td align="center" rowspan="2">3.32</td>
<td align="center" rowspan="2">0.19</td>
</tr>
<tr>
<td align="center">0.14 (25)</td>
<td align="center">0.38 (70)</td>
<td align="center">0.48 (89)</td>
<td align="center">0.33</td>
<td align="center">0.67</td>
</tr>
<tr>
<td align="center" rowspan="2">g.51546 T&#x003e;C</td>
<td align="center" rowspan="2">rs319197012</td>
<td align="center">TT</td>
<td align="center">TC</td>
<td align="center">CC</td>
<td align="center">T</td>
<td align="center">C</td>
<td align="center" rowspan="2">1.87</td>
<td align="center" rowspan="2">0.39</td>
</tr>
<tr>
<td align="center">0.39 (72)</td>
<td align="center">0.43 (79)</td>
<td align="center">0.18 (33)</td>
<td align="center">0.61</td>
<td align="center">0.39</td>
</tr>
<tr>
<td align="center" rowspan="2">g.55035 T&#x003e;C</td>
<td align="center" rowspan="2">rs333279910</td>
<td align="center">TT</td>
<td align="center">TC</td>
<td align="center">CC</td>
<td align="center">T</td>
<td align="center">C</td>
<td align="center" rowspan="2">1.20</td>
<td align="center" rowspan="2">0.55</td>
</tr>
<tr>
<td align="center">0.36 (67)</td>
<td align="center">0.45 (82)</td>
<td align="center">0.19 (35)</td>
<td align="center">0.59</td>
<td align="center">0.41</td>
</tr>
<tr>
<td align="center" rowspan="2">g.55088 C&#x003e;T</td>
<td align="center" rowspan="2">rs322138947</td>
<td align="center">CC</td>
<td align="center">CT</td>
<td align="center">TT</td>
<td align="center">C</td>
<td align="center">T</td>
<td align="center" rowspan="2">1.20</td>
<td align="center" rowspan="2">0.55</td>
</tr>
<tr>
<td align="center">0.36 (67)</td>
<td align="center">0.45 (82)</td>
<td align="center">0.19 (35)</td>
<td align="center">0.59</td>
<td align="center">0.41</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: <italic>p</italic> &#x003e; 0.05 indicates that the gene frequency in the population is at Hardy-Weinberg equilibrium. The number of samples is indicated in brackets.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>The homozygosity (<italic>Ho</italic>) of the four SNPs of the <italic>ACAA1</italic> gene was 0.5151&#x2013;0.5605, and the heterozygosity (<italic>He</italic>) was 0.4395&#x2013;0.4849 (<xref ref-type="table" rid="T3">Table 3</xref>). The homozygosity (<italic>Ho</italic>) was higher than the heterozygosity (<italic>He</italic>), demonstrating that the four loci in this population showed a low degree of variation; effective number of alleles (<italic>Ae</italic>) was 1.7841&#x2013;1.9413. The polymorphism information content ranged from 0.3429 to 0.3673, indicating a moderate polymorphism level (0.25&#x003c;<italic>PIC</italic> &#x003c; 0.5).</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Genetic information of <italic>ACAA1</italic> gene population.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">SNPs</th>
<th align="center">rs number</th>
<th align="center">Effective allele number (<italic>Ae</italic>)</th>
<th align="center">Homozygosity (<italic>Ho)</italic>
</th>
<th align="center">Heterozygosity (<italic>He</italic>)</th>
<th align="center">Polymorphism information content (<italic>PIC</italic>)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">g.48810 A&#x003e;G</td>
<td align="center">rs343060194</td>
<td align="center">1.7841</td>
<td align="center">0.5605</td>
<td align="center">0.4395</td>
<td align="center">0.3429</td>
</tr>
<tr>
<td align="center">g.51546 T&#x003e;C</td>
<td align="center">rs319197012</td>
<td align="center">1.8918</td>
<td align="center">0.5225</td>
<td align="center">0.4775</td>
<td align="center">0.3635</td>
</tr>
<tr>
<td align="center">g.55035 T&#x003e;C</td>
<td align="center">rs333279910</td>
<td align="center">1.9413</td>
<td align="center">0.5151</td>
<td align="center">0.4849</td>
<td align="center">0.3673</td>
</tr>
<tr>
<td align="center">g.55088 C&#x003e;T</td>
<td align="center">rs322138947</td>
<td align="center">1.9413</td>
<td align="center">0.5151</td>
<td align="center">0.4849</td>
<td align="center">0.3673</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: <italic>PIC</italic> &#x003c; 0.25 is low polymorphism, 0.25&#x003c;<italic>PIC</italic> &#x003c; 0.5 is medium polymorphism, and <italic>PIC</italic> &#x003e; 0.5 is high polymorphism.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-4">
<title>3.4 Linkage disequilibrium and haplotype analysis of SNPs in the <italic>ACAA1</italic> gene</title>
<p>Linkage disequilibrium (LD) analysis was performed on the four SNPs in the <italic>ACAA1</italic> gene (<xref ref-type="fig" rid="F4">Figure 4</xref>). The <italic>D&#x2019;</italic> values of the four SNPs ranged between 0.414 and 1.000, and the <italic>r</italic>
<sup>2</sup> values ranged between 0.058 and 1.000. The <italic>r</italic>
<sup>2</sup> for g.55035 T&#x003e;C (rs333279910) and g.55088&#xa0;C&#x003e;T (rs322138947) was 1.000, indicating a strong LD.</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>
<italic>r</italic>
<sup>
<italic>2</italic>
</sup> and <italic>D&#x2019;</italic> values in linkage disequilibrium analysis of <italic>ACAA1</italic> gene SNPs.</p>
</caption>
<graphic xlink:href="fgene-15-1346903-g004.tif"/>
</fig>
<p>
<xref ref-type="table" rid="T4">Table 4</xref> displays the findings of the <italic>ACAA1</italic> gene haplotype analysis. The population had six haplotypes with a frequency greater than 5.00%, and less than 5.00% were excluded from statistical analysis. Among the six haplotypes, Hap 1 (-GCCT-) had the highest frequency (25.00%), while Hap 6 (-ATCT-) had the lowest frequency (5.70%). Based on the paired combinations of six haplotypes, five diplotypes combinations with frequencies greater than 5.00% were obtained, including Hap1/3, -GCCT/ATTC-; Hap2/2, -GTTC/GTTC-; Hap2/5, -GTTC/GCTC-; Hap2/4, -GTTC/GTCT-; Hap1/1, -GCCT/GCCT- (<xref ref-type="table" rid="T5">Table 5</xref>).</p>
<table-wrap id="T4" position="float">
<label>TABLE 4</label>
<caption>
<p>Haplotype frequencies of 4 SNPs in Xiangsu pig.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Haplotype</th>
<th align="center">g.48810 A&#x003e;G (rs343060194)</th>
<th align="center">g.51546 T&#x003e;C (rs319197012)</th>
<th align="center">g.55035 T&#x003e;C (rs333279910)</th>
<th align="center">g.55088 C&#x003e;T (rs322138947)</th>
<th align="center">Frequency (%)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">Hap1</td>
<td align="center">G</td>
<td align="center">C</td>
<td align="center">C</td>
<td align="center">T</td>
<td align="center">25.00</td>
</tr>
<tr>
<td align="center">Hap2</td>
<td align="center">G</td>
<td align="center">T</td>
<td align="center">T</td>
<td align="center">C</td>
<td align="center">24.20</td>
</tr>
<tr>
<td align="center">Hap3</td>
<td align="center">A</td>
<td align="center">T</td>
<td align="center">T</td>
<td align="center">C</td>
<td align="center">21.30</td>
</tr>
<tr>
<td align="center">Hap4</td>
<td align="center">G</td>
<td align="center">T</td>
<td align="center">C</td>
<td align="center">T</td>
<td align="center">9.40</td>
</tr>
<tr>
<td align="center">Hap5</td>
<td align="center">G</td>
<td align="center">C</td>
<td align="center">T</td>
<td align="center">C</td>
<td align="center">8.80</td>
</tr>
<tr>
<td align="center">Hap6</td>
<td align="center">A</td>
<td align="center">T</td>
<td align="center">C</td>
<td align="center">T</td>
<td align="center">5.70</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: Haplotypes with frequencies &#x003c;5.00% were excluded from the analysis.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T5" position="float">
<label>TABLE 5</label>
<caption>
<p>Diplotypes and frequency of <italic>ACAA1</italic> gene.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Diplotypes</th>
<th align="center">g.48810 A&#x003e;G (rs343060194)</th>
<th align="center">g.51546 T&#x003e;C (rs319197012)</th>
<th align="center">g.55035 T&#x003e;C (rs333279910)</th>
<th align="center">g.55088 C&#x003e;T (rs322138947)</th>
<th align="center">Frequency (%)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">Hap1/3</td>
<td align="center">GA</td>
<td align="center">CT</td>
<td align="center">CT</td>
<td align="center">TC</td>
<td align="center">19.02</td>
</tr>
<tr>
<td align="center">Hap2/2</td>
<td align="center">GG</td>
<td align="center">TT</td>
<td align="center">TT</td>
<td align="center">CC</td>
<td align="center">11.96</td>
</tr>
<tr>
<td align="center">Hap2/5</td>
<td align="center">GG</td>
<td align="center">TC</td>
<td align="center">TT</td>
<td align="center">CC</td>
<td align="center">7.61</td>
</tr>
<tr>
<td align="center">Hap2/4</td>
<td align="center">GG</td>
<td align="center">TT</td>
<td align="center">TC</td>
<td align="center">CT</td>
<td align="center">5.98</td>
</tr>
<tr>
<td align="center">Hap1/1</td>
<td align="center">GG</td>
<td align="center">CC</td>
<td align="center">CC</td>
<td align="center">TT</td>
<td align="center">5.43</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: Diplotypes with frequencies &#x003c;5.00% were excluded from the analysis.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-5">
<title>3.5 Association analysis between <italic>ACAA1</italic> gene and growth performance</title>
<p>The association between 4 SNP loci g.48810 A&#x003e;G (rs343060194), g.51546 T&#x003e;C (rs319197012), g.55035 T&#x003e;C (rs333279910) and g.55088 C&#x003e;T (rs322138947)) and 8 growth traits at 6&#xa0;months (<xref ref-type="table" rid="T6">Table 6</xref>) was examined using the SPSS 22 software. The results showed that in the 6-month-old pigs, there was a significant difference in body weight between the AG genotype and the GG genotype at the exon g.48810 A&#x003e;G (rs343060194) locus (<italic>p</italic> &#x003c; 0.05). The leg and hip circumference of the CC genotype at the intron g.51546 T&#x003e;C (rs319197012) locus were significantly different from that of the TC genotype (<italic>p</italic> &#x003c; 0.05). Furthermore, the body weight of the TC genotype at the exon g.55035 T&#x003e;C (rs333279910) locus was significantly different from that of the TT genotype (<italic>p</italic> &#x003c; 0.05), while the living backfat thickness of the TT genotype was significantly different from that of the CC genotype (<italic>p</italic> &#x003c; 0.01). In addition, at the g.55088 C&#x003e;T (rs322138947) locus, the body weight of the CT genotype was significantly different from that of the CC genotype (<italic>p</italic> &#x003c; 0.05), and the living backfat thickness of the CC genotype was significantly different from that of the TT genotype (<italic>p</italic> &#x003c; 0.01).</p>
<table-wrap id="T6" position="float">
<label>TABLE 6</label>
<caption>
<p>Association analysis between <italic>ACAA1</italic> gene and growth traits of 6-month-old Xiangsu pigs.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">SNPS</th>
<th align="center">Genotypes</th>
<th align="center">B W (kg)</th>
<th align="center">B L (cm)</th>
<th align="center">B H (cm)</th>
<th align="center">C C (cm)</th>
<th align="center">A C (cm)</th>
<th align="center">T C (cm)</th>
<th align="center">L H C (cm)</th>
<th align="center">L B T (mm)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center" rowspan="3">g.48810 A&#x003e;G (rs343060194)</td>
<td align="center">AA</td>
<td align="center">70.56 &#xb1; 1.76<sup>ab</sup>
</td>
<td align="center">95.56 &#xb1; 3.11</td>
<td align="center">63.76 &#xb1; 3.02</td>
<td align="center">95.72 &#xb1; 3.73</td>
<td align="center">96.88 &#xb1; 3.28</td>
<td align="center">17.96 &#xb1; 0.79</td>
<td align="center">62.88 &#xb1; 2.01</td>
<td align="center">10.88 &#xb1; 0.89</td>
</tr>
<tr>
<td align="center">AG</td>
<td align="center">70.97 &#xb1; 1.83<sup>a</sup>
</td>
<td align="center">94.97 &#xb1; 4.49</td>
<td align="center">64.84 &#xb1; 4.63</td>
<td align="center">95.47 &#xb1; 2.86</td>
<td align="center">97.17 &#xb1; 2.86</td>
<td align="center">18.00 &#xb1; 0.92</td>
<td align="center">62.20 &#xb1; 2.04</td>
<td align="center">10.88 &#xb1; 1.01</td>
</tr>
<tr>
<td align="center">GG</td>
<td align="center">70.29 &#xb1; 2.19<sup>b</sup>
</td>
<td align="center">94.91 &#xb1; 3.16</td>
<td align="center">63.79 &#xb1; 3.28</td>
<td align="center">94.93 &#xb1; 3.32</td>
<td align="center">97.06 &#xb1; 3.71</td>
<td align="center">17.94 &#xb1; 0.94</td>
<td align="center">62.20 &#xb1; 1.83</td>
<td align="center">10.60 &#xb1; 1.51</td>
</tr>
<tr>
<td align="center" rowspan="3">g.51546 T&#x003e;C (rs319197012)</td>
<td align="center">TT</td>
<td align="center">70.28 &#xb1; 2.04</td>
<td align="center">95.15 &#xb1; 3.22</td>
<td align="center">63.54 &#xb1; 3.19</td>
<td align="center">95.08 &#xb1; 3.12</td>
<td align="center">96.88 &#xb1; 3.05</td>
<td align="center">17.83 &#xb1; 0.95</td>
<td align="center">62.23 &#xb1; 1.80<sup>ab</sup>
</td>
<td align="center">10.65 &#xb1; 1.61</td>
</tr>
<tr>
<td align="center">TC</td>
<td align="center">70.70 &#xb1; 1.97</td>
<td align="center">94.65 &#xb1; 4.34</td>
<td align="center">64.53 &#xb1; 4.54</td>
<td align="center">95.13 &#xb1; 3.17</td>
<td align="center">97.05 &#xb1; 3.59</td>
<td align="center">17.95 &#xb1; 0.93</td>
<td align="center">62.09 &#xb1; 2.02<sup>b</sup>
</td>
<td align="center">10.89 &#xb1; 1.01</td>
</tr>
<tr>
<td align="center">CC</td>
<td align="center">71.00 &#xb1; 2.03</td>
<td align="center">95.63 &#xb1; 2.97</td>
<td align="center">64.76 &#xb1; 3.10</td>
<td align="center">95.88 &#xb1; 3.52</td>
<td align="center">97.58 &#xb1; 3.35</td>
<td align="center">18.15 &#xb1; 0.91</td>
<td align="center">62.91 &#xb1; 1.97<sup>a</sup>
</td>
<td align="center">10.59 &#xb1; 0.93</td>
</tr>
<tr>
<td align="center" rowspan="3">g.55035 T&#x003e;C (rs333279910)</td>
<td align="center">TT</td>
<td align="center">70.13 &#xb1; 1.99<sup>b</sup>
</td>
<td align="center">94.72 &#xb1; 2.74</td>
<td align="center">63.66 &#xb1; 3.05</td>
<td align="center">94.90 &#xb1; 3.08</td>
<td align="center">96.45 &#xb1; 3.22</td>
<td align="center">17.78 &#xb1; 0.95</td>
<td align="center">62.03 &#xb1; 1.65</td>
<td align="center">10.99 &#xb1; 0.97<sup>A</sup>
</td>
</tr>
<tr>
<td align="center">TC</td>
<td align="center">70.93 &#xb1; 1.98<sup>a</sup>
</td>
<td align="center">95.04 &#xb1; 4.52</td>
<td align="center">64.52 &#xb1; 4.39</td>
<td align="center">95.27 &#xb1; 3.10</td>
<td align="center">97.41 &#xb1; 3.47</td>
<td align="center">18.05 &#xb1; 0.94</td>
<td align="center">62.30 &#xb1; 2.12</td>
<td align="center">10.75 &#xb1; 0.98<sup>AB</sup>
</td>
</tr>
<tr>
<td align="center">CC</td>
<td align="center">70.66 &#xb1; 2.02<sup>ab</sup>
</td>
<td align="center">95.57 &#xb1; 3.19</td>
<td align="center">64.40 &#xb1; 3.78</td>
<td align="center">95.86 &#xb1; 3.70</td>
<td align="center">97.49 &#xb1; 3.15</td>
<td align="center">18.00 &#xb1; 0.87</td>
<td align="center">62.77 &#xb1; 1.97</td>
<td align="center">10.26 &#xb1; 2.01<sup>B</sup>
</td>
</tr>
<tr>
<td align="center" rowspan="3">g.55088 C&#x003e;T (rs322138947)</td>
<td align="center">CC</td>
<td align="center">70.13 &#xb1; 1.99<sup>b</sup>
</td>
<td align="center">94.72 &#xb1; 2.74</td>
<td align="center">63.66 &#xb1; 3.05</td>
<td align="center">94.90 &#xb1; 3.08</td>
<td align="center">96.45 &#xb1; 3.22</td>
<td align="center">17.78 &#xb1; 0.95</td>
<td align="center">62.03 &#xb1; 1.65</td>
<td align="center">10.99 &#xb1; 0.97<sup>A</sup>
</td>
</tr>
<tr>
<td align="center">CT</td>
<td align="center">70.93 &#xb1; 1.98<sup>a</sup>
</td>
<td align="center">95.03 &#xb1; 4.52</td>
<td align="center">64.52 &#xb1; 4.39</td>
<td align="center">95.27 &#xb1; 3.10</td>
<td align="center">97.41 &#xb1; 3.47</td>
<td align="center">18.05 &#xb1; 0.94</td>
<td align="center">62.30 &#xb1; 2.12</td>
<td align="center">10.75 &#xb1; 0.98<sup>AB</sup>
</td>
</tr>
<tr>
<td align="center">TT</td>
<td align="center">70.6 &#xb1; 2.04<sup>ab</sup>
</td>
<td align="center">95.57 &#xb1; 3.19</td>
<td align="center">64.40 &#xb1; 3.78</td>
<td align="center">95.86 &#xb1; 3.70</td>
<td align="center">97.49 &#xb1; 3.15</td>
<td align="center">18.00 &#xb1; 0.87</td>
<td align="center">62.77 &#xb1; 1.97</td>
<td align="center">10.26 &#xb1; 2.01<sup>B</sup>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: BW, Body weight/kg; BL, Body length/cm; BH, Body height/cm; CC, Chest circumference/cm, AC, Abdominal circumference/cm; TC, Tube circumference/cm; LHC, Leg and hip circumference/cm; LBT, Living backfat thickness/mm. The data are expressed as mean &#xb1; standard deviation. Different lowercase letters represent significant differences at 0.05 level (<italic>p</italic> &#x003c; 0.05), different uppercase letters indicate significant differences at 0.01 level (<italic>p</italic> &#x003c; 0.01)<italic>,</italic> and the same letters (case-insensitive) show no significant difference (<italic>p</italic> &#x003e; 0.05).</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>The association between 4 SNP loci g.48810 A&#x003e;G (rs343060194), g.51546 T&#x003e;C (rs319197012), g.55035 T&#x003e;C (rs333279910), and g.55088 C&#x003e;T (rs322138947)) and 8 growth traits at 12&#xa0;months (<xref ref-type="table" rid="T7">Table 7</xref>) was examined using the SPSS 22 software. The results showed that the body length of pigs with the GG genotype at the g.48810 A&#x003e;G (rs343060194) locus was significantly different from that of the AG genotype (<italic>p</italic> &#x003c; 0.01). The abdominal circumference of pigs with the AG genotype was significantly different from that of the GG genotype (<italic>p</italic> &#x003c; 0.05). The body weight and abdominal circumference of pigs with the TC genotype at the g.51546 T&#x003e;C (rs319197012) intron locus were significantly different from that of the TT genotype (<italic>p</italic> &#x003c; 0.05), and the same was observed for the leg and hip circumference and living backfat thickness with the TC genotype from that of the TT genotype (<italic>p</italic> &#x003c; 0.01). The body weight of pigs with the TC genotype at the g.55035 T&#x003e;C (rs333279910) exon locus was significantly different from that of the TT genotype (<italic>p</italic> &#x003c; 0.05), and the same was observed for the living backfat thickness with the TC genotype from that of the TT genotype (<italic>p</italic> &#x003c; 0.01). The body height of pigs with the CC genotype was significantly different from that of the TC and TT genotypes (<italic>p</italic> &#x003c; 0.05). The leg and hip circumference of pigs with the TC and CC genotypes were significantly different from that of the TT genotype (<italic>p</italic> &#x003c; 0.05). The body weight of pigs with the CT genotype at the g.55088 C&#x003e;T (rs322138947) locus was significantly different from that of the CC genotype (<italic>p</italic> &#x003c; 0.05); and the same was observed for the living backfat thickness with the CT genotype from that of the CC genotype (<italic>p</italic> &#x003c; 0.01). The body height of pigs with the TT genotype was significantly different from that of the CC and CT genotypes (<italic>p</italic> &#x003c; 0.05); the leg and hip circumference of pigs with the CT and TT genotypes were significantly different from that of the CC genotype (<italic>p</italic> &#x003c; 0.05); there were no significant differences in other indicators (<italic>p</italic> &#x003e; 0.05).</p>
<table-wrap id="T7" position="float">
<label>TABLE 7</label>
<caption>
<p>Association analysis between <italic>ACAA1</italic> gene and growth traits of 12-month-old Xiangsu pigs.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">SNPS</th>
<th align="center">Genotypes</th>
<th align="center">B W (kg)</th>
<th align="center">B L (cm)</th>
<th align="center">B H (cm)</th>
<th align="center">C C (cm)</th>
<th align="center">A C (cm)</th>
<th align="center">T C (cm)</th>
<th align="center">L H C (cm)</th>
<th align="center">L B T (mm)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center" rowspan="3">g.48810 A&#x003e;G (rs343060194)</td>
<td align="center">AA</td>
<td align="center">137.72 &#xb1; 4.77</td>
<td align="center">130.44 &#xb1; 1.39<sup>AB</sup>
</td>
<td align="center">72.20 &#xb1; 1.29</td>
<td align="center">119.52 &#xb1; 1.94</td>
<td align="center">126.88 &#xb1; 3.77<sup>ab</sup>
</td>
<td align="center">19.64 &#xb1; 0.86</td>
<td align="center">87.16 &#xb1; 3.08</td>
<td align="center">13.88 &#xb1; 1.22</td>
</tr>
<tr>
<td align="center">AG</td>
<td align="center">138.17 &#xb1; 4.10</td>
<td align="center">130.04 &#xb1; 1.26<sup>B</sup>
</td>
<td align="center">71.57 &#xb1; 1.48</td>
<td align="center">119.83 &#xb1; 1.98</td>
<td align="center">128.14 &#xb1; 3.52<sup>a</sup>
</td>
<td align="center">19.76 &#xb1; 0.79</td>
<td align="center">87.96 &#xb1; 2.52</td>
<td align="center">14.18 &#xb1; 1.13</td>
</tr>
<tr>
<td align="center">GG</td>
<td align="center">137.12 &#xb1; 4.06</td>
<td align="center">130.56 &#xb1; 1.17<sup>A</sup>
</td>
<td align="center">71.92 &#xb1; 1.60</td>
<td align="center">119.91 &#xb1; 2.20</td>
<td align="center">126.69 &#xb1; 3.43<sup>b</sup>
</td>
<td align="center">19.69 &#xb1; 1.35</td>
<td align="center">87.19 &#xb1; 2.73</td>
<td align="center">14.02 &#xb1; 1.04</td>
</tr>
<tr>
<td align="center" rowspan="3">g.51546 T&#x003e;C (rs319197012)</td>
<td align="center">TT</td>
<td align="center">136.76 &#xb1; 4.38<sup>b</sup>
</td>
<td align="center">130.49 &#xb1; 1.30</td>
<td align="center">71.72 &#xb1; 1.62</td>
<td align="center">119.71 &#xb1; 2.11</td>
<td align="center">126.71 &#xb1; 3.46<sup>b</sup>
</td>
<td align="center">19.60 &#xb1; 0.76</td>
<td align="center">86.86 &#xb1; 2.88<sup>B</sup>
</td>
<td align="center">13.71 &#xb1; 1.22<sup>B</sup>
</td>
</tr>
<tr>
<td align="center">TC</td>
<td align="center">138.25 &#xb1; 3.86<sup>a</sup>
</td>
<td align="center">130.20 &#xb1; 1.19</td>
<td align="center">71.89 &#xb1; 1.51</td>
<td align="center">119.77 &#xb1; 1.98</td>
<td align="center">127.87 &#xb1; 3.46<sup>a</sup>
</td>
<td align="center">19.82 &#xb1; 1.40</td>
<td align="center">88.02 &#xb1; 2.42<sup>A</sup>
</td>
<td align="center">14.37 &#xb1; 0.90<sup>A</sup>
</td>
</tr>
<tr>
<td align="center">CC</td>
<td align="center">137.88 &#xb1; 4.29<sup>ab</sup>
</td>
<td align="center">130.39 &#xb1; 1.27</td>
<td align="center">71.91 &#xb1; 1.35</td>
<td align="center">120.21 &#xb1; 2.26</td>
<td align="center">127.03 &#xb1; 3.86<sup>ab</sup>
</td>
<td align="center">19.67 &#xb1; 0.85</td>
<td align="center">87.52 &#xb1; 2.80<sup>AB</sup>
</td>
<td align="center">14.08 &#xb1; 1.04<sup>AB</sup>
</td>
</tr>
<tr>
<td align="center" rowspan="3">g.55035 T&#x003e;C (rs333279910)</td>
<td align="center">TT</td>
<td align="center">136.66 &#xb1; 4.32<sup>b</sup>
</td>
<td align="center">130.43 &#xb1; 1.26</td>
<td align="center">71.70 &#xb1; 1.56<sup>b</sup>
</td>
<td align="center">119.94 &#xb1; 2.04</td>
<td align="center">126.72 &#xb1; 3.60</td>
<td align="center">19.75 &#xb1; 1.50</td>
<td align="center">86.78 &#xb1; 2.89<sup>b</sup>
</td>
<td align="center">13.74 &#xb1; 1.19<sup>B</sup>
</td>
</tr>
<tr>
<td align="center">TC</td>
<td align="center">138.27 &#xb1; 3.97<sup>a</sup>
</td>
<td align="center">130.21 &#xb1; 1.23</td>
<td align="center">71.68 &#xb1; 1.52<sup>b</sup>
</td>
<td align="center">119.71 &#xb1; 1.98</td>
<td align="center">127.62 &#xb1; 3.48</td>
<td align="center">19.73 &#xb1; 0.80</td>
<td align="center">87.83 &#xb1; 2.50<sup>a</sup>
</td>
<td align="center">14.30 &#xb1; 0.99<sup>A</sup>
</td>
</tr>
<tr>
<td align="center">CC</td>
<td align="center">137.86 &#xb1; 4.20<sup>ab</sup>
</td>
<td align="center">130.51 &#xb1; 1.27</td>
<td align="center">72.40 &#xb1; 1.35<sup>a</sup>
</td>
<td align="center">119.89 &#xb1; 2.39</td>
<td align="center">127.49 &#xb1; 3.62</td>
<td align="center">19.57 &#xb1; 0.74</td>
<td align="center">88.00 &#xb1; 2.66<sup>a</sup>
</td>
<td align="center">14.11 &#xb1; 1.05<sup>AB</sup>
</td>
</tr>
<tr>
<td align="center" rowspan="3">g.55088 C&#x003e;T (rs322138947)</td>
<td align="center">CC</td>
<td align="center">136.66 &#xb1; 4.32<sup>b</sup>
</td>
<td align="center">130.43 &#xb1; 1.26</td>
<td align="center">71.70 &#xb1; 1.56<sup>b</sup>
</td>
<td align="center">119.94 &#xb1; 2.04</td>
<td align="center">126.72 &#xb1; 3.60</td>
<td align="center">19.75 &#xb1; 1.50</td>
<td align="center">86.78 &#xb1; 2.89<sup>b</sup>
</td>
<td align="center">13.74 &#xb1; 1.19<sup>B</sup>
</td>
</tr>
<tr>
<td align="center">CT</td>
<td align="center">138.27 &#xb1; 3.97<sup>a</sup>
</td>
<td align="center">130.21 &#xb1; 1.23</td>
<td align="center">71.68 &#xb1; 1.52<sup>b</sup>
</td>
<td align="center">119.71 &#xb1; 1.98</td>
<td align="center">127.62 &#xb1; 3.48</td>
<td align="center">19.73 &#xb1; 0.80</td>
<td align="center">87.83 &#xb1; 2.50<sup>a</sup>
</td>
<td align="center">14.30 &#xb1; 0.99<sup>A</sup>
</td>
</tr>
<tr>
<td align="center">TT</td>
<td align="center">137.86 &#xb1; 4.20<sup>ab</sup>
</td>
<td align="center">130.51 &#xb1; 1.27</td>
<td align="center">72.40 &#xb1; 1.35<sup>a</sup>
</td>
<td align="center">119.89 &#xb1; 2.39</td>
<td align="center">127.49 &#xb1; 3.62</td>
<td align="center">19.57 &#xb1; 0.74</td>
<td align="center">88.00 &#xb1; 2.66<sup>a</sup>
</td>
<td align="center">14.11 &#xb1; 1.05<sup>AB</sup>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: BW, Body weight/kg; BL, Body Length/cm; BH, Body height/cm; CC, Chest circumference/cm; AC, Abdominal circumference/cm; TC, Tube circumference/cm; LHC, Leg and hip circumference/cm; LBT, Living backfat thickness/mm. The data are expressed as mean &#xb1; standard deviation. Different lowercase letters represent significant differences at 0.05 level (<italic>p</italic> &#x003c; 0.05), different uppercase letters indicate significant differences at 0.01 level (<italic>p</italic> &#x003c; 0.01), and the same letters (case-insensitive) show no significant difference (<italic>p</italic> &#x003e; 0.05).</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-6">
<title>3.6 Association analysis between <italic>ACAA1</italic> gene diplotypes and growth performance</title>
<p>Association analysis was performed between five diploid combinations and the growth traits of 6-month-old of Xiangsu pigs. Hap1/3, -GCCT/ATTC- outperformed Hap2/2, -GTTC/GTTC- in terms of body weight. Hap1/1, -GCCT/GCCT-was superior to Hap2/2, -GTTC/GTTC- in chest circumference, Hap2/5, -GTTC/GCTC- outperformed Hap2/2, -GTTC/GTTC- in terms of tube circumference, Hap1/1, -GCCT/GCCT-outperformed Hap1/3, -GCCT/ATTC- Hap2/5, -GTTC/GCTC-, Hap2/4, -GTTC/GTCT-in terms of leg and hip circumference (<xref ref-type="table" rid="T8">Table 8</xref>). The association analysis between five diplotypes and growth traits of 12-month-old Xiangsu pigs revealed that Hap1/1, -GCCT/GCCT-was superior to Hap2/2, -GTTC/GTTC- in body weight and leg and hip circumference. Hap2/4, -GTTC/GTCT-was superior Hap1/3, -GCCT/ATTC- in body length, Hap2/5, -GTTC/GCTC- outperformed Hap2/2, -GTTC/GTTC in terms of body height and tube circumference (<xref ref-type="table" rid="T9">Table 9</xref>). In a nutshell, Hap1/1, -GCCT/GCCT-can be employed as an advantageous genotype combination for subsequent breeding.</p>
<table-wrap id="T8" position="float">
<label>TABLE 8</label>
<caption>
<p>Relationship between diploid types and growth traits at 6 months of age in Xinagsu pigs.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Diplotype</th>
<th align="center">Frequency (%)</th>
<th align="center">B W (kg)</th>
<th align="center">B L (cm)</th>
<th align="center">B H (cm)</th>
<th align="center">C C (cm)</th>
<th align="center">A C (cm)</th>
<th align="center">T C (cm)</th>
<th align="center">L H C (cm)</th>
<th align="center">L B T (mm)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">Hap1/3</td>
<td align="center">19.0</td>
<td align="center">71.20 &#xb1; 1.69<sup>a</sup>
</td>
<td align="center">94.54 &#xb1; 5.6</td>
<td align="center">65.34 &#xb1; 5.66</td>
<td align="center">95.23 &#xb1; 2.49<sup>ab</sup>
</td>
<td align="center">97.00 &#xb1; 2.73</td>
<td align="center">18.03 &#xb1; 0.89<sup>ab</sup>
</td>
<td align="center">62.06 &#xb1; 2.10<sup>b</sup>
</td>
<td align="center">10.82 &#xb1; 1.08</td>
</tr>
<tr>
<td align="center">Hap2/2</td>
<td align="center">12.0</td>
<td align="center">69.55 &#xb1; 2.20<sup>b</sup>
</td>
<td align="center">94.22 &#xb1; 3.2</td>
<td align="center">63.18 &#xb1; 3.29</td>
<td align="center">94.00 &#xb1; 2.64<sup>b</sup>
</td>
<td align="center">95.77 &#xb1; 2.81</td>
<td align="center">17.50 &#xb1; 0.91<sup>b</sup>
</td>
<td align="center">62.13 &#xb1; 1.46<sup>ab</sup>
</td>
<td align="center">10.65 &#xb1; 1.12</td>
</tr>
<tr>
<td align="center">Hap2/5</td>
<td align="center">7.6</td>
<td align="center">70.79 &#xb1; 1.85<sup>ab</sup>
</td>
<td align="center">95.50 &#xb1; 2.9</td>
<td align="center">64.71 &#xb1; 2.95</td>
<td align="center">95.93 &#xb1; 3.08<sup>ab</sup>
</td>
<td align="center">98.21 &#xb1; 4.04</td>
<td align="center">18.29 &#xb1; 1.07<sup>a</sup>
</td>
<td align="center">61.86 &#xb1; 1.17<sup>b</sup>
</td>
<td align="center">11.27 &#xb1; 0.86</td>
</tr>
<tr>
<td align="center">Hap2/4</td>
<td align="center">6.0</td>
<td align="center">70.91 &#xb1; 2.12<sup>ab</sup>
</td>
<td align="center">95.45 &#xb1; 3.7</td>
<td align="center">64.45 &#xb1; 2.66</td>
<td align="center">95.09 &#xb1; 3.14<sup>ab</sup>
</td>
<td align="center">97.63 &#xb1; 4.06</td>
<td align="center">17.91 &#xb1; 1.14<sup>ab</sup>
</td>
<td align="center">61.91 &#xb1; 1.81<sup>b</sup>
</td>
<td align="center">10.59 &#xb1; 0.92</td>
</tr>
<tr>
<td align="center">Hap1/1</td>
<td align="center">5.4</td>
<td align="center">70.80 &#xb1; 2.25<sup>ab</sup>
</td>
<td align="center">95.50 &#xb1; 3.8</td>
<td align="center">65.60 &#xb1; 3.17</td>
<td align="center">96.30 &#xb1; 2.50<sup>a</sup>
</td>
<td align="center">97.30 &#xb1; 3.13</td>
<td align="center">17.90 &#xb1; 0.88<sup>ab</sup>
</td>
<td align="center">63.40 &#xb1; 1.51<sup>a</sup>
</td>
<td align="center">10.47 &#xb1; 1.07</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: BW, Body weight/kg; B L, Body length/cm; BH: Body height/cm; CC, Chest circumference/cm; AC, Abdominal circumference/cm; TC, Tube circumference/cm; LHC, Leg and hip circumference/cm; LBT, Living backfat thickness/mm. The data are expressed as mean &#xb1; standard deviation.Different lowercase letters represent significant differences at 0.05 level (<italic>p</italic> &#x003c; 0.05), different uppercase letters indicate significant differences at 0.01 level (<italic>p</italic> &#x003c; 0.01), and the same letters (case-insensitive) show no significant difference (<italic>p</italic> &#x003e; 0.05).</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T9" position="float">
<label>TABLE 9</label>
<caption>
<p>Relationship between diploid types and growth traits at 12 months of age in Xinagsu pigs.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Diplotype</th>
<th align="center">Frequency (%)</th>
<th align="center">B W (kg)</th>
<th align="center">B L (cm)</th>
<th align="center">B H (cm)</th>
<th align="center">C C (cm)</th>
<th align="center">A C (cm)</th>
<th align="center">T C (cm)</th>
<th align="center">L H C (cm)</th>
<th align="center">L B T (mm)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">Hap1/3</td>
<td align="center">19.0</td>
<td align="center">138.37 &#xb1; 3.88<sup>ab</sup>
</td>
<td align="center">129.80 &#xb1; 1.21<sup>b</sup>
</td>
<td align="center">71.60 &#xb1; 1.50<sup>ab</sup>
</td>
<td align="center">119.77 &#xb1; 1.85</td>
<td align="center">128.57 &#xb1; 3.08</td>
<td align="center">19.71 &#xb1; 0.83<sup>ab</sup>
</td>
<td align="center">88.29 &#xb1; 2.23<sup>ab</sup>
</td>
<td align="center">14.38 &#xb1; 0.97</td>
</tr>
<tr>
<td align="center">Hap2/2</td>
<td align="center">12.0</td>
<td align="center">135.86 &#xb1; 3.91<sup>b</sup>
</td>
<td align="center">130.63 &#xb1; 1.18<sup>ab</sup>
</td>
<td align="center">71.09 &#xb1; 1.60<sup>b</sup>
</td>
<td align="center">120.45 &#xb1; 2.06</td>
<td align="center">126.68 &#xb1; 3.26</td>
<td align="center">19.41 &#xb1; 0.67<sup>b</sup>
</td>
<td align="center">86.41 &#xb1; 2.79<sup>b</sup>
</td>
<td align="center">13.61 &#xb1; 1.08</td>
</tr>
<tr>
<td align="center">Hap2/5</td>
<td align="center">7.6</td>
<td align="center">138.00 &#xb1; 3.80<sup>ab</sup>
</td>
<td align="center">130.43 &#xb1; 1.28<sup>ab</sup>
</td>
<td align="center">72.50 &#xb1; 1.40<sup>a</sup>
</td>
<td align="center">120.00 &#xb1; 2.04</td>
<td align="center">126.07 &#xb1; 3.67</td>
<td align="center">20.50 &#xb1; 2.85<sup>a</sup>
</td>
<td align="center">87.71 &#xb1; 2.55<sup>ab</sup>
</td>
<td align="center">14.23 &#xb1; 0.98</td>
</tr>
<tr>
<td align="center">Hap2/4</td>
<td align="center">6.0</td>
<td align="center">136.91 &#xb1; 3.91<sup>ab</sup>
</td>
<td align="center">131.18 &#xb1; 0.87<sup>a</sup>
</td>
<td align="center">72.18 &#xb1; 1.66<sup>ab</sup>
</td>
<td align="center">119.45 &#xb1; 2.25</td>
<td align="center">127.27 &#xb1; 3.32</td>
<td align="center">19.73 &#xb1; 0.79<sup>ab</sup>
</td>
<td align="center">86.73 &#xb1; 2.33<sup>ab</sup>
</td>
<td align="center">13.90 &#xb1; 1.28</td>
</tr>
<tr>
<td align="center">Hap1/1</td>
<td align="center">5.4</td>
<td align="center">139.10 &#xb1; 3.78<sup>a</sup>
</td>
<td align="center">130.60 &#xb1; 1.35<sup>ab</sup>
</td>
<td align="center">72.30 &#xb1; 1.57<sup>ab</sup>
</td>
<td align="center">120.40 &#xb1; 2.37</td>
<td align="center">128.20 &#xb1; 3.58</td>
<td align="center">19.70 &#xb1; 0.82<sup>ab</sup>
</td>
<td align="center">88.40 &#xb1; 2.22<sup>a</sup>
</td>
<td align="center">14.40 &#xb1; 0.94</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: BW, Body weight/kg; BL, Body length/cm; BH, Body height/cm; CC, Chest circumference/cm; AC, Abdominal circumference/cm; TC, Tube circumference/cm; LHC, Leg and hip circumference/cm; LBT, Living backfat thickness/mm. The data are expressed as mean &#xb1; standard deviation.Different lowercase letters represent significant differences at 0.05 level (<italic>p</italic> &#x003c; 0.05), different uppercase letters indicate significant differences at 0.01 level (<italic>p</italic> &#x003c; 0.01), and the same letters (case-insensitive) show no significant difference (<italic>p</italic> &#x003e; 0.05).</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>4 Discussion</title>
<p>This study investigated and analyzed the expression levels of the <italic>ACAA1</italic> gene in different tissues (heart, liver, spleen, lung, kidney, and longissimus dorsi muscle) of Xiangsu pigs at 6&#xa0;months of age The results revealed that the <italic>ACAA1</italic> gene was expressed in all examined tissues, including the heart, liver, spleen, lung, kidney, and longissimus dorsi muscle of Xiangsu pigs. Among them, the expression of <italic>ACAA1</italic> gene in liver was significantly different from that in other tissues (<italic>p</italic> &#x003c; 0.01). ACAA1 regulates fatty acid oxidation and lipid metabolism by catalyzing peroxisomal fatty acid &#x3b2;-oxidation (<xref ref-type="bibr" rid="B21">Luo et al., 2018</xref>). Lipid metabolism is tightly linked to fat deposition in muscle, which directly influences the meat taste of pork products. Liver and muscle are the main metabolic organs involved in the regulation of lipid metabolism, and investigation of the expression level and spatial and temporal changes of the <italic>ACAA1</italic> gene in critical visceral organs, and longissimus dorsi muscle of Xiangsu pigs is highly imperative.</p>
<p>We further examined the expression trend of ACAA1 mRNA in longissimus dorsi muscle of Xiangsu pigs at different ages (newborn, 6-month-old and 12-month-old). Interestingly, the expression level of the <italic>ACAA1</italic> gene in the longissimus dorsi muscle decreased with age. Previous studies have shown that gene expression in tissues varies during different growth stages. The intramuscular fat content in the longissimus thoracis muscle of Tibetan sheep shows an increasing trend from 4&#xa0;months to 1.5&#xa0;years old (<italic>p</italic> &#x003c; 0.05), while the <italic>MYH4</italic> gene exhibits differential expression between the longissimus thoracis muscles at 4&#xa0;months and 1.5&#xa0;years old (<xref ref-type="bibr" rid="B44">Wen et al., 2022</xref>). Transcriptional analysis was conducted on the longissimus dorsi muscle of pigs at different growth stages, identifying many differentially expressed genes (DEGs) related to lipid metabolism and muscle development, the majority of which are involved in intramuscular fat (IMF) deposition (<xref ref-type="bibr" rid="B14">Li et al., 2023</xref>). Knockdown of the <italic>ACAA1</italic> gene promoted lipid droplet formation and lipid accumulation in sheep preadipocytes (<xref ref-type="bibr" rid="B43">Wang et al., 2021</xref>), inhibiting the <italic>ACAA1</italic> gene expression promoted intramuscular fat deposition in chicken (<xref ref-type="bibr" rid="B13">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B45">Xie et al., 2014</xref>). In another investigation, upregulated expression of the <italic>ACAA1</italic> gene in mice was revealed to inhibit abdominal fat and liver lipid accumulation in high-fat diet mice (<xref ref-type="bibr" rid="B45">Xie et al., 2014</xref>). Therefore, the <italic>ACAA1</italic> gene could influence fat deposition in the longissimus dorsi muscle of Xiangsu pigs at different ages by regulating lipid metabolism.</p>
<p>In the present investigation, we analyzed blood DNA extracted from 184 Xiangsu pigs to determine the effect of <italic>ACAA1</italic> gene polymorphism on fat deposition in the longissimus dorsi muscle of Xiangsu pigs. Amplification of the <italic>ACAA1</italic> gene sequence yielded four SNP loci: g.48810 A&#x003e;G (rs343060194), g.51546 T&#x003e;C (rs319197012), g.55035 T&#x003e;C (rs333279910), and g.55088 C&#x003e;T (rs322138947). g.51546 T&#x003e;C (rs319197012) is an intron mutation, g.48810 A&#x003e;G (rs343060194), g.55035 T&#x003e;C (rs333279910), and g.55088 C&#x003e;T (rs322138947) are exon synonymous mutations identified using gene polymorphism parameter evaluation. The four mutation sites were consistent with HWE (<italic>p</italic> &#x003e; 0.05) and had moderate polymorphism (0.25&#x003c;<italic>PIC</italic> &#x003c; 0.50). At the same time, synonymous mutations have been shown to alter mRNA splicing and secondary structure, as well as amino acid co-translation and post-translational folding pathways (<xref ref-type="bibr" rid="B31">Sharma et al., 2019</xref>; <xref ref-type="bibr" rid="B37">Supek et al., 2014</xref>). Human cancer research has also demonstrated that synonymous mutations potentially change RNA binding proteins and miRNA binding sites (<xref ref-type="bibr" rid="B40">Teng et al., 2020</xref>). In this view, it is critical to investigate the association between SNPs in introns and exons of the <italic>ACAA1</italic> gene and backfat deposition in Xiangsu pigs.</p>
<p>LD analysis of the four SNPs revealed that the g.55035 T&#x003e;C (rs333279910) and g.55088 C&#x003e;T (rs322138947) had the strongest linkage and belonged to a strong LD (<italic>r</italic>
<sup>2</sup> &#x003D; 1.000) (<xref ref-type="bibr" rid="B10">Guryev et al., 2006</xref>; <xref ref-type="bibr" rid="B35">Slatkin, 2008</xref>). Furthermore, previous studies revealed a strong LD between gene exon mutations, which exert a potential synergistic effect on animal phenotypes (<xref ref-type="bibr" rid="B50">Zhao et al., 2021</xref>). Therefore, we hypothesize that the strong linkage mutation sites of g.55035 T&#x003e;C (rs333279910) and g.55088 C&#x003e;T (rs322138947) in the <italic>ACAA1</italic> gene may influence pig growth traits.</p>
<p>The relationship between four SNPs of the <italic>ACAA1</italic> gene and the growth traits of Xiangsu pigs revealed that the strong linkage imbalance sites g.55035 T&#x003e;C (rs333279910) and g.55088 C&#x003e;T (rs322138947) significantly differed from the body weight (<italic>p</italic> &#x003c; 0.05) and the living backfat thickness of Xiangsu pigs (<italic>p</italic> &#x003c; 0.01). Moreover, the heterozygous genotypes of the two loci revealed a dominant genotype in the body weight and living backfat thickness of 12-month-old Xiangsu pigs. These data provided more evidence that these two sites may have a synergistic effect on pig growth and backfat deposition. The g.48810 A&#x003e;G (rs343060194) locus may primarily influence pig body weight, body length and abdominal circumference, while the g.51546 T&#x003e;C (rs319197012) locus may influence the growth and backfat deposition of pigs in the later stages of fattening. Emerging evidence indicates that genes related to adipogenesis (<xref ref-type="bibr" rid="B23">Martinez-Montes et al., 2018</xref>; <xref ref-type="bibr" rid="B32">Shi et al., 2019</xref>) and fatty acid metabolism (<xref ref-type="bibr" rid="B5">Chen et al., 2019</xref>; <xref ref-type="bibr" rid="B9">Guo et al., 2017</xref>) signaling pathways play a role in pig backfat development (<xref ref-type="bibr" rid="B8">Gozalo-Marcilla et al., 2021</xref>) and that pig backfat thickness and body weight are moderately positively correlated (r &#x003D; 0.632) (<xref ref-type="bibr" rid="B11">Hoa et al., 2021</xref>). Diplotypes analysis revealed that Hap1/1, -GCCT/GCCT-were beneficial to growth traits at 6&#xa0;months of age. Hap1/1, -GCCT/GCCT-, Hap2/5, -GTTC/GCTC- were favorable for growth traits at 12&#xa0;months of age and could be utilized as advantageous genotype combinations for breeding. The <italic>ACAA1</italic> gene mutations g.55035 T&#x003e;C (rs333279910) and g.55088 C&#x003e;T (rs322138947) may be linked to the body weight and living backfat thickness of Xiangsu pigs. Therefore, the <italic>ACAA1</italic> gene is a promising candidate gene for pig growth and development and backfat deposition.</p>
</sec>
<sec id="s5" sec-type="conclusion">
<title>5 Conclusion</title>
<p>This study investigated the tissue-specific expression of the <italic>ACAA1</italic> gene in Xiangsu pigs. The results showed that the expression level of <italic>ACAA1</italic> gene mRNA was highest in the liver of 6-month-old pigs. The expression level of <italic>ACAA1</italic> gene mRNA in the longissimus dorsi muscle of Xiangsu pigs decreased with age. In addition, this study conducted an association analysis of <italic>ACAA1</italic> gene SNPs with the growth traits of Xiangsu pigs. The results showed that there are four SNPs in the <italic>ACAA1</italic> gene of Xiangsu pigs; g.55035 T&#x003e;C (rs333279910) and g.55088 C&#x003e;T (rs322138947) were strongly linked (<italic>r</italic>
<sup>
<italic>2</italic>
</sup> &#x003D; 1.000). The strong linkage loci exhibited significant differences in body weight and body height and living backfat thickness. These SNPs potentially influence the growth traits of Xiangsu pigs and are valuable SNP markers for improving the growth performance of Xiangsu pigs.</p>
</sec>
</body>
<back>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s12">Supplementary Materials</xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s7">
<title>Ethics statement</title>
<p>The animal studies were approved by the Animal Welfare Committee of Guizhou University. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent was obtained from the owners for the participation of their animals in this study.</p>
</sec>
<sec id="s8">
<title>Author contributions</title>
<p>MX: Conceptualization, Writing&#x2013;original draft. YR: Data curation, Methodology, Writing&#x2013;review and editing. JH: Methodology, Resources, Writing&#x2013;review and editing. LD: Investigation, Methodology, Writing&#x2013;review and editing. JX: Data curation, Software, Writing&#x2013;review and editing. HX: Funding acquisition, Supervision, Validation, Writing&#x2013;review and editing.</p>
</sec>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by the Guizhou Provincial Science and Technology Project (QKHFQ-2018,4007, (002)), and the Guizhou Provincial Agricultural Major Industrial Scientific Research Project (QKHKYZ-2019,011).</p>
</sec>
<ack>
<p>Thanks to the Xiangsu Pig breeding Farm of Guizhou University, China for providing Xiangsu pigs.</p>
</ack>
<sec id="s10" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s12">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fgene.2024.1346903/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fgene.2024.1346903/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table1.docx" id="SM1" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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