Please wait a minute...
Journal of Integrative Agriculture  2026, Vol. 25 Issue (3): 1099-1113    DOI: 10.1016/j.jia.2024.05.004
Animal Science · Veterinary Medicine Advanced Online Publication | Current Issue | Archive | Adv Search |
Unraveling genetic underpinnings of purine content in pork

Cong Huang, Min Zheng, Yizhong Huang, Liping Cai, Xiaoxiao Zou, Tianxiong Yao, Xinke Xie, Bin Yang, Shijun Xiao, Junwu Ma#, Lusheng Huang#

National Key Laboratory for Pig Genetic Improvement and Germplasm Innovation, Jiangxi Agricultural University, Nanchang 330045, China

 Highlights 
First study to systematically elucidate the molecular mechanism underlying purine content modulation in pork.
Two highly significant quantitative trait loci (QTLs) on Sus scrofa chromosome 12 (SSC12) were identified, independently influencing guanine content and adenine/hypoxanthine content in pork.
Provides a robust foundation for selecting pig breeds with reduced purine base content.
Download:  PDF in ScienceDirect  
Export:  BibTeX | EndNote (RIS)      
摘要  作为食物中一种重要的营养指标,嘌呤碱基含量的重要性源于它拥有通过高嘌呤饮食引起人体高尿酸血症或痛风的潜在能力。包括猪肉在内的畜肉中普遍含有中等偏高的总嘌呤含量。近期的研究表明不同猪种内或猪种间在嘌呤含量上存在着巨大差异,意味着遗传因素对该性状上的影响。因此,本研究旨在解析调控猪肉中嘌呤碱基含量的遗传基础。结果显示,四种嘌呤性状(鸟嘌呤、腺嘌呤、次黄嘌呤、总嘌呤)的遗传力估计值从0.140.35不等,且四种嘌呤碱基总共识别到的数量性状位点(QTL)总数分别为14361925。关于总嘌呤的基因集富集分析和基因网络分析结果显示,一个由15个强候选基因互相交织形成的复杂网络涉及了众多的嘌呤代谢通路,如嘌呤核糖核苷酸代谢过程、嘌呤核苷酸代谢和转运、嘌呤回收途径等。特别的,我们发现大多数与总嘌呤含量显著相关的遗传变异位点对多个嘌呤碱基表现出类似的影响。我们还在猪的12号染色体上识别到两个极显著(P < 10-12)的QTL,其中一个影响鸟嘌呤含量,另一个同时影响腺嘌呤和次黄嘌呤含量水平。我们发现位于12号染色体上与鸟嘌呤相关的最显著位点处在TMEM238L基因下游1.1kb处并且在H3K27me3组蛋白修饰包含的基因组片段内,而通过精细定位策略将位于同一染色体上与腺嘌呤及次黄嘌呤均相关的QTL位点缩小至了172kb的区域,此区域内包含了GAS7MYH13两个基因。然而,此QTL的效应并不能被这两个基因中的任一错义突变解释。本研究首次揭示了与家畜嘌呤含量相关的遗传变异位点及候选基因,为低嘌呤含量猪品系的选择性育种奠定了坚实的基础。

Abstract  

The significance of purine base content as an important nutrition indicator in foods arises from its potential to trigger hyperuricemia or gout via high-purine diet.  Livestock meats, including pork, generally contain moderate to high total purine content (TP).  Recent research revealed substantial variations within and across pig breeds, implying genetic factors influencing this trait.  Thus, this study aimed to unravel the genetic underpinnings governing purine base content in pork.  The heritability estimates (h2) for the four purine traits ranged from 0.14 to 0.35.  A total of 14, 36, 19 and 25 quantitative trait loci (QTLs) were identified for guanine, adenine, hypoxanthine, and TP, respectively.  Our comprehensive gene set enrichment analysis and gene network analysis revealed 15 promising candidate genes intricately interwoven within diverse purine metabolism pathways, such as purine ribonucleotide metabolic process, purine nucleotide metabolism and transport, and purine salvage pathways, all contributing to TP.  Strikingly, most genetic variants significantly associated with TP displayed analogous effects on multiple purine bases.  Two distinct and highly significant QTLs (P<10–12) emerged on Sus scrofa chromosome (SSC) 12: one impacting guanine content and the other concurrently influencing adenine and hypoxanthine levels.  The peak of the guanine QTL on SSC12 resided 1.1 kb downstream of the transmembrane protein 238 like (TMEM238L) gene and is encapsulated within a genomic segment characterized by the histone modification H3K27me3.  Focused fine-mapping for the SSC12 QTL associated with adenine and hypoxanthine levels narrowed its scope to around 172 kb, encompassing the growth arrest specific 7 (GAS7) and myosin heavy chain 13 (MYH13) genes.  However, the observed QTL effect was not attributed to any missense mutations within the two genes.  This pioneering study unveils the genetic variations and candidate genes associated with purine content in livestock, laying a robust foundation for the selective breeding of pig lines with reduced purine base content.

Keywords:  pig        purine content        genetic architecture        GWAS        QTL  
Received: 30 October 2023   Accepted: 11 March 2024 Online: 24 May 2024  
Fund: The authors are grateful for the support from the National Natural Science Foundation of China (32272855) and STI 2030-Major Projects, China (2023ZD0404501).  
About author:  Cong Huang, E-mail: 1714182072@qq.com; #Correspondence Junwu Ma, E-mail: mjwjxlab@jxau.edu.cn; Lusheng Huang, E-mail: lushenghuang@hotmail.com

Cite this article: 

Cong Huang, Min Zheng, Yizhong Huang, Liping Cai, Xiaoxiao Zou, Tianxiong Yao, Xinke Xie, Bin Yang, Shijun Xiao, Junwu Ma, Lusheng Huang. 2026. Unraveling genetic underpinnings of purine content in pork. Journal of Integrative Agriculture, 25(3): 1099-1113.

Agrawal A A, McLaughlin K J, Jenkins J L, Kielkopf C L. 2014. Structure-guided U2AF65 variant improves recognition and splicing of a defective pre-mRNA. Proceedings of the National Academy of Sciences of the United States of America111, 17420–17425.

Barkas F, Elisaf M, Liberopoulos E, Kalaitzidis R, Liamis G. 2018. Uric acid and incident chronic kidney disease in dyslipidemic individuals. Current Medical Research and Opinion34, 1193–1199.

Barrett J C, Fry B, Maller J, Daly M J. 2005. Haploview: Analysis and visualization of LD and haplotype maps. Bioinformatics21, 263–265.

Bhole V, Choi J W, Kim S W, de Vera M, Choi H. 2010. Serum uric acid levels and the risk of type 2 diabetes: A prospective study. The American Journal of Medicine123, 957–961.

Blanco J, Canela E J, Sayos J, Mallol J, Llyis C, Franco R. 1993. Adenine nucleotides and adenosine metabolism in pig kidney proximal tubule membranes. Journal of Cellular Physiology157, 77–83.

Browning S R, Browning B L. 2007. Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. The American Journal of Human Genetics81, 1084–1097.

Camiaa F, Novo-Rodriguez M I, Rodriguez-Segade S, Castro-Gago M. 1995. Purine and carnitine metabolism in muscle of patients with Duchenne muscular dystrophy. Clinica Chimica Acta243, 151–164.

Caulfield M J, Munroe P B, O’Neill D, Witkowska K, Charchar F J, Doblado M, Evans S, Eyheramendy S, Onipinla A, Howard P, Shaw-Hawkins S, Dobson R J, Wallace C, Newhouse S J, Brown M, Connell J M, Dominiczak A, Farrall M, Lathrop G M, Samani N J, et al. 2008. SLC2A9 is a high-capacity urate transporter in humans. PLoS Medicine5, e197.

Chang C, Chow C, Tellier L, Vattikuti S, Purcell S, Lee J. 2015. Second-generation PLINK: Rising to the challenge of larger and richer datasets. Gigascience4, 7.

Cho I, Park H, Ahn J, Han , Lee J, Lim H, Yoo C, Jung E, Kim D, Sun W, Ramayo-Caldas Y, Kim S, Kang Y, Kim Y, Shin H, Seong P, Hwang I, Park B, Hwang S, Lee S, et al. 2019. A functional regulatory variant of MYH3 influences muscle fiber-type composition and intramuscular fat content in pigs. PLoS Genetics15, e1008279.

Choi H K, Atkinson K, Karlson E W, Willett W, Curhan G. 2004. Purine-rich foods, dairy and protein intake, and the risk of gout in men. The New England Journal of Medicine350, 1093–1103.

Cicero A F G, Fogacci F, Di Micoli V, Angeloni C, Giovannini M, Borghi C. 2023. Purine metabolism dysfunctions: experimental methods of detection and diagnostic potential. International Journal of Molecular Sciences24, 1–14.

Danve A, Sehra S T, Neogi T. 2021. Role of diet in hyperuricemia and gout. Best Practice & Research in Clinical Rheumatology35, 101723.

Davoli R, Ros-Freixedes R, Gol S, Pena R N, Tor M, Ibáñez-Escriche N, Dekkers J C M, Estany J. 2016. Genome-wide association study singles out SCD and LEPR as the two main loci influencing intramuscular fat content and fatty acid composition in Duroc pigs. PLoS ONE11, e0152496.

Dehlin M, Jacobsson L, Roddy E. 2020. Global epidemiology of gout: Prevalence, incidence, treatment patterns and risk factors. Nature Reviews Rheumatology16, 380–390.

Devlin B. 1999. Genomic control for association studies. Biometrics55, 997–1004.

Dobin A, Davis C A, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras T R. 2013. STAR: Ultrafast universal RNA-seq aligner. Bioinformatics29, 15–21.

Duan Y, Guo Q, Wen C, Wang W, Li Y, Tan B, Li F, Yin Y. 2016. Free amino acid profile and expression of genes implicated in protein metabolism in skeletal muscle of growing pigs fed low-protein diets supplemented with branched-chain amino acids. Journal of Agricultural and Food Chemistry64, 9390–9400.

Duval N, Luhrs K, Wilkinson T G, Baresova V, Skopova V, Kmoch S, Vacano G N, Zikanova M, Patterson D. 2013. Genetic and metabolomic analysis of AdeD and AdeI mutants of de novo purine biosynthesis: Cellular models of de novo purine biosynthesis deficiency disorders. Molecular Genetics and Metabolism108, 178–189.

Falconer D S, Mackay Trudy F C. 1996. Introduction to Quantitative Genetics. Longman Group Ltd. Publishing, Edinburgh Gate, UK. pp. 1-479.

Freedman M L, Reich D, Penney K L, McDonald G J, Mignault A A, Patterson N, Gabriel S B, Topol E J, Smoller J W, Pato C N, Pato M T, Petryshen T L, Kolonel L N, Lander E S, Sklar P, Henderson B, Hirschhorn J N, Altshuler D. 2004. Assessing the impact of population stratification on genetic association studies. Nature Genetics36, 388–393.

Guo T, Gao J, Yang B, Yan G, Xiao S, Zhang Z, Huang L. 2020. A whole genome sequence association study of muscle fiber traits in a White Duroc×Erhualian Fresource population. Asian–Australasian Journal of Animal Sciences33, 704–711.

Huang C, Zheng M, Huang Y, Liu X, Zhong L, Ji J, Zhou L, Zeng Q, Ma J, Huang L. 2020. The effect of purine content on sensory quality of pork. Meat Science172, 108346.

Huang Y, Cai L, Duan Y, Zeng Q, He M, Wu Z, Zou X, Zhou M, Zhang Z, Xiao S, Yang B, Ma J, Huang L. 2022. Whole-genome sequence-based association analyses on an eight-breed crossed heterogeneous stock of pigs reveal the genetic basis of skeletal muscle fiber characteristics. Meat Science194, 108974.

Ji J, Zhou L, Huang Y, Zheng M, Liu X, Zhang Y, Huang C, Peng S, Zeng Q, Zhong L, Yang B, Li W, Xiao S, Ma J, Huang L. 2018. A whole-genome sequence based association study on pork eating quality traits and cooking loss in a specially designed heterogeneous F6 pig population. Meat Science146, 160–167.

Kanbay M, Segal M, Afsar B, Kang D H, Rodriguez-Iturbe B, Johnson R J. 2013. The role of uric acid in the pathogenesis of human cardiovascular disease. Heart99, 759–766.

Kern C, Wang Y, Xu X, Pan Z, Halstead M, Chanthavixay G, Saelao P, Waters S, Xiang R, Chamberlain A, Korf I, Delany M E, Cheng H H, Medrano J F, Van Eenennaam A L, Tuggle C K, Ernst C, Flicek P, Quon G, Ross P, et al. 2021. Functional annotations of three domestic animal genomes provide vital resources for comparative and agricultural research. Nature Communication12, 1821.

Kottgen A, Albrecht E, Teumer A, Vitart V, Krumsiek J, Hundertmark C, Pistis G, Ruggiero D, O’Seaghdha C M, Haller T, Yang Q, Tanaka T, Johnson A D, Kutalik Z, Smith A V, Shi J, Struchalin M, Middelberg R P, Brown M J, Gaffo A L, et al. 2013. Genome-wide association analyses identify 18 new loci associated with serum urate concentrations. Nature Genetics45, 145–154.

Lanaspa M A, Sanchez-Lozada L G, Choi Y J, Cicerchi C, Kanbay M, Roncal-Jimenez C A, Ishimoto T, Li N, Marek G, Duranay M, Schreiner G, Rodriguez-Iturbe B, Nakagawa T, Kang D H, Sautin Y Y, Johnson R J. 2012. Uric acid induces hepatic steatosis by generation of mitochondrial oxidative stress: Potential role in fructose-dependent and -independent fatty liver. The Journal of Biological Chemistry287, 40732–40744.

Lee I, Blom U M, Wang P I, Shim J E, Marcotte E M. 2011. Prioritizing candidate disease genes by network-based boosting of genome-wide association data. Genome Research21, 1109–1121.

Li C, Li Z, Liu S, Wang C, Han L, Cui L, Zhou J, Zou H, Liu Z, Chen J, Cheng X, Zhou Z, Ding C, Wang M, Chen T, Cui Y, He H, Zhang K, Yin C, Wang Y, et al. 2015. Genome-wide association analysis identifies three new risk loci for gout arthritis in Han Chinese. Nature Communication6, 7041.

Li H, Durbin R. 2010. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics26, 589–595.

Li H, Handsaker B, Wysoker A, Fennell T, Ruan J. 2009. The sequence alignment/map format and SAMtools. Bioinformatics25, 2078–2079.

Li H D, Lund M S, Christensen O F, Gregersen V R, Henckel P, Bendixen C. 2010. Quantitative trait loci analysis of swine meat quality traits. Journal of Animal Science88, 2904–2912.

Liang J S, Hung K L, Lin L J, Ong W P, Keng W T, Lu J F. 2023. Novel PEX1 mutations in fibroblasts from children with Zellweger spectrum disorders exhibit temperature sensitive characteristics. Epilepsy & Behavior145,1–9.

Liao Y, Smyth G K, Shi W. 2014. featureCounts: An efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics30, 923–930.

Liu X, Xiong X, Yang J, Zhou L, Yang B, Ai H, Ma H, Xie X, Huang Y, Fang S, Xiao S, Ren J, Ma J, Huang L. 2015. Genome-wide association analyses for meat quality traits in Chinese Erhualian pigs and a Western Duroc×(Landrace×Yorkshire) commercial population. Genetics Selection Evolution47, 44.

Lopez B I, Santiago K G, Lee D, Cho Y, Lim D, Seo K. 2020. Single-step genomic evaluation for meat quality traits, sensory characteristics, and fatty-acid composition in Duroc pigs. Genes (Basel), 11, 1–13.

Lourenco V M, Pires A M, Kirst M. 2011. Robust linear regression methods in association studies. Bioinformatics27, 815–821.

Love M I, Huber W, Anders S. 2014. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology15, 550.

Ma J, Yang J, Zhou L, Ren J, Liu X, Zhang H, Yang B, Zhang Z, Ma H, Xie X, Xing Y, Guo Y, Huang L. 2014. A splice mutation in the PHKG1 gene causes high glycogen content and low meat quality in pig skeletal muscle. PLoS Genetics10, e1004710.

Marchini J, Cardon L R, Phillips M S, Donnelly P. 2004. The effects of human population structure on large genetic association studies. Nature Genetics36, 512–517.

Okada Y, Sim X, Go M J, Wu J Y, Gu D, Takeuchi F, Takahashi A, Maeda S, Tsunoda T, Chen P, Lim S C, Wong T Y, Liu J, Young T L, Aung T, Seielstad M, Teo Y Y, Kim Y J, Lee J Y, Han B G, et al. 2012. Meta-analysis identifies multiple loci associated with kidney function-related traits in east Asian populations. Nature Genetics44, 904–909.

Pearson T A, Manolio T A. 2008. How to interpret a genome-wide association study. JAMA299, 1335–1344.

Pertea M, Pertea G M, Antonescu C M, Chang T C, Mendell J T, Salzberg S L. 2015. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nature Biotechnology33, 290–295.

Randall C, Johnson G W N, Jennifer L Troyer, James A Lautenberger, Bailey D Kessing, Cheryl A Winkler, Stephen J O’Brien. 2010. Accounting for multiple comparisons in a genome-wide association study (GWAS). BMC Genomics11, 1–6

Rimmer A, Phan H, Mathieson I, Iqbal Z, Twigg S R F, Consortium W G S, Wilkie A O M, McVean G, Lunter G. 2014. Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications. Nature Genetics46, 912–918.

Rong S, Zou L, Zhang Y, Zhang G, Li X, Li M, Yang F, Li C, He Y, Guan H, Guo Y, Wang D, Cui X, Ye H, Liu F, Pan H, Yang Y. 2015. Determination of purine contents in different parts of pork and beef by high performance liquid chromatography. Food Chemistry170, 303–307.

Smith E U, Diaz-Torne C, Perez-Ruiz F, March L M. 2010. Epidemiology of gout: An update. Best Practice & Research in Clinical Rheumatology24, 811–827.

Smith H S, Bracken D, Smith J M. 2011. Gout: Current insights and future perspectives. The Journal of Pain12, 1113–1129.

So A, Thorens B. 2010. Uric acid transport and disease. The Journal of Clinical Investigation120, 1791–1799.

Soare E, Chiurciu I A. 2017. Study on the pork market worldwide. Scientific Papers Series ManagementEconomic Engineering in Agriculture and Rural Development17, 321–326.

Sulem P, Gudbjartsson D F, Walters G B, Helgadottir H T, Helgason A, Gudjonsson S A, Zanon C, Besenbacher S, Bjornsdottir G, Magnusson O T, Magnusson G, Hjartarson E, Saemundsdottir J, Gylfason A, Jonasdottir A, Holm H, Karason A, Rafnar T, Stefansson H, Andreassen O A, et al. 2011. Identification of low-frequency variants associated with gout and serum uric acid levels. Nature Genetics43, 1127–1130.

Taylor M W, Pipkorn J H, Tokito M K, Pozzatti Jr R O. 1977. Purine mutants of mammalian cell lines: Iii control of purine biosynthesis in adenine phosphoribosyl transferase mutants of CHO cells. Somatic Cell Genetics3, 195–206.

Tin A, Woodward O M, Kao W H L, Liu C-T, Lu X, Nalls M A, Shriner D, Semmo M, Akylbekova E L, Wyatt S B, Hwang S J, Yang Q, Zonderman A B, Adeyemo A A, Palmer C, Meng Y, Reilly M, Shlipak M G, Siscovick D, Evans M K, Rotimi C N, et al. 2011. Genome-wide association study for serum urate concentrations and gout among African Americans identifies genomic risk loci and a novel URAT1 loss-of-function allele. Human Molecular Genetics20, 4056–4068.

Viterbo V S, Lopez B I M, Kang H, Kim H, Song C W, Seo K S. 2018. Genome wide association study of fatty acid composition in Duroc swine. Asian–Australasian Journal of Animal Sciences31, 1127–1133.

Willer C J, Li Y, Abecasis G R. 2010. METAL: Fast and efficient meta-analysis of genomewide association scans. Bioinformatics26, 2190–2191.

Wu B, Roseland J M, Haytowitz D B, Pehrsson P R, Ershow A G. 2019. Availability and quality of published data on the purine content of foods, alcoholic beverages, and dietary supplements. Journal of Food Composition and Analysis84, 1–8.

Wu Z, Gong H, Zhou Z, Jiang T, Lin Z, Li J, Xiao S, Yang B, Huang L. 2022. Mapping short tandem repeats for liver gene expression traits helps prioritize potential causal variants for complex traits in pigs. Journal of Animal Science Biotechnology13, 8.

Yang J, Lee S H, Goddard M E, Visscher P M. 2011. GCTA: A tool for genome-wide complex trait analysis. The American Journal of Human Genetics88, 76–82.

Zhang F, Patel D M, Colavita K, Rodionova I, Buckley B, Scott D A, Kumar A, Shabalina S A, Saha S, Chernov M, Osterman A L, Kashina A. 2015. Arginylation regulates purine nucleotide biosynthesis by enhancing the activity of phosphoribosyl pyrophosphate synthase. Nature Communication6, 7517.

Zheng M, Huang Y, Ji J, Xiao S, Ma J, Huang L. 2018. Effects of breeds, tissues and genders on purine contents in pork and the relationships between purine content and other meat quality traits. Meat Science143, 81–86.

Zhou X, Stephens M. 2012. Genome-wide efficient mixed-model analysis for association studies. Nature Genetics44, 821–824.

Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi A H, Tanaseichuk O, Benner C, Chanda S K. 2019. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nature Communication10, 1523.

[1] Xiaoqin Liu, Xinhao Fan, Junyu Yan, Longchao Zhang, Lixian Wang, Honor Calnan, Yalan Yang, Graham Gardner, Rong Zhou, Zhonglin Tang. An InDel in the promoter of ribosomal protein S27-like gene regulates skeletal muscle growth in pigs[J]. >Journal of Integrative Agriculture, 2026, 25(3): 1114-1124.
[2] Chenyang Wang, Yinuo Zhang, Qiming Sun, Lin Li, Fang Guan, Yazhou He, Yidong Wu. Species-specific evolution of lepidopteran TspC5 tetraspanins associated with dominant resistance to Bacillus thuringiensis toxin Cry1Ac[J]. >Journal of Integrative Agriculture, 2025, 24(8): 3127-3140.
[3] Tengteng Xu, Mengya Zhang, Qiuchen Liu, Xin Wang, Pengfei Luo, Tong Liu, Yelian Yan, Naru Zhou, Yangyang Ma, Tong Yu, Yunsheng Li, Zubing Cao, Yunhai Zhang. 18S ribosomal RNA methyltransferase METTL5-mediated CDX2 translation regulates porcine early embryo development[J]. >Journal of Integrative Agriculture, 2025, 24(8): 3185-3198.
[4] Jie Zhang, Qi Wang, Jinxi Yuan, Zhen Tian, Shanchun Yan, Wei Liu.
Development of a piggyBac transgenic system in Bactrocera dorsalis and its potential for research on olfactory molecular targets
[J]. >Journal of Integrative Agriculture, 2025, 24(6): 2311-2326.
[5] Zipeng Zhang, Siyuan Xing, Ao Qiu, Ning Zhang, Wenwen Wang, Changsong Qian, Jia’nan Zhang, Chuduan Wang, Qin Zhang, Xiangdong Ding. The development of a porcine 50K SNP panel using genotyping by target sequencing and its application[J]. >Journal of Integrative Agriculture, 2025, 24(5): 1930-1943.
[6] Qi Han, Xingguo Huang, Jun He, Yiming Zeng, Jie Yin, Yulong Yin. Intramuscular fat deposition in pig: A key target for improving pork quality[J]. >Journal of Integrative Agriculture, 2025, 24(12): 4461-4483.
[7] Mianyan Li, Lei Pu, David E. MacHugh, Jingjing Tian, Xiaoqing Wang, Qingyao Zhao, Lijun Shi, Hongmei Gao, Ying Yu, Lixian Wang, Fuping Zhao. Genome-wide association studies of novel resilience traits identify important immune QTL regions and candidate genes in Duroc pigs[J]. >Journal of Integrative Agriculture, 2025, 24(11): 4355-4369.
[8] Kaiyuan Ji, Yiwei Zhao, Xin Yuan, Chun’e Liang, Xueqing Zhang, Wenli Tian, Tong Yu, Yangyang Ma, Yinghui Ling, Yunhai Zhang. circKIF27 inhibits melanogenesis and proliferation by targeting miR-129-5p/TGIF2 pathway in goat melanocytes[J]. >Journal of Integrative Agriculture, 2025, 24(10): 3997-4011.
[9] Xi Tang, Lei Xie, Min Yan, Longyun Li, Tianxiong Yao, Siyi Liu, Wenwu Xu, Shijun Xiao, Nengshui Ding, Zhiyan Zhang, Lusheng Huang . Genomic selection for meat quality traits based on VIS/NIR spectral information[J]. >Journal of Integrative Agriculture, 2025, 24(1): 235-245.
[10] Jialing Fu, Qingjiang Wu, Xia Wang, Juan Sun, Li Liao, Li Li, Qiang Xu. A novel histone methyltransferase gene CgSDG40 positively regulates carotenoid biosynthesis during citrus fruit ripening[J]. >Journal of Integrative Agriculture, 2024, 23(8): 2633-2648.
[11] Jun Zhou, Qing Lin, Xueyan Feng, Duanyang Ren, Jinyan Teng, Xibo Wu, Dan Wu, Xiaoke Zhang, Xiaolong Yuan, Zanmou Chen, Jiaqi Li, Zhe Zhang, Hao Zhang.

Evaluating the performance of genomic selection on purebred population by incorporating crossbred data in pigs [J]. >Journal of Integrative Agriculture, 2024, 23(2): 639-648.

[12] Lei Wu, Yujie Chang, Lanfen Wang, Shumin Wang, Jing Wu. Genome-wide association study dissecting drought resistance-associated loci based on physiological traits in common bean[J]. >Journal of Integrative Agriculture, 2024, 23(11): 3657-3671.
[13] Liang Ma, Tingli Hu, Meng Kang, Xiaokang Fu, Pengyun Chen, Fei Wei, Hongliang Jian, Xiaoyan Lü, Meng Zhang, Yonglin Yang. Identification of candidate genes for early-maturity traits by combining BSA-seq and QTL mapping in upland cotton (Gossypium hirsutum L.)[J]. >Journal of Integrative Agriculture, 2024, 23(10): 3472-3486.
[14] Caiyun Liu, Lulu Wu, Shuyue Fan, Yongsheng Tao, Yunkui Li.

The protective effect of cyclodextrin on the color quality and stability of Cabernet Sauvignon red wine [J]. >Journal of Integrative Agriculture, 2024, 23(1): 310-323.

[15] Mu Zeng, Binhu Wang, Lei Liu, Yalan Yang, Zhonglin Tang. Genome-wide association study identifies 12 new genetic loci associated with growth traits in pigs[J]. >Journal of Integrative Agriculture, 2024, 23(1): 217-227.
No Suggested Reading articles found!