基于高通量测序技术鉴定松辽黑猪与长白猪背最长肌差异基因

doi:10.7668/hbnxb.20193162

摘要/Abstract

摘要：

旨在利用高通量测序技术对松辽黑猪和长白猪背最长肌组织样本进行mRNA测序和差异分析,筛选影响猪肌肉生长、肉质和脂肪沉积的关键基因,从而为猪肉品质研究提供新的参考信息。采集6头松辽黑猪和6头长白猪的背最长肌组织样本,提取其RNA,采用Illumina HiSeq 2500高通量测序技术对mRNA进行测序,并对获得的reads进行比对、注释和差异表达分析,用NOISeq筛选出差异表达基因并进行相关生物学功能富集分析。结果表明,从2个猪种间共筛选出了664个差异表达基因,其中,364个基因在松辽黑猪中高表达,300个基因在长白猪中高表达。通过对差异表达基因进行生物学功能分析,筛选出LPIN1、FADS1、FADS2、PLIN2、PPARGC1A、PRKAG2和ACSL1等基因参与脂类代谢和肌肉发育相关的调控,相关通路为脂肪酸代谢、PPAR信号通路、AMPK信号通路、胰岛素信号通路和脂肪细胞因子信号通路等。

关键词: 松辽黑猪, 长白猪, 高通量测序, 背最长肌, 差异基因

Abstract:

This study aims to use high-throughput sequencing technology to perform mRNA sequencing and differential analysis of longissimus dorsi muscle tissue samples from Songliao black pigs and Landrace pigs,and screen out key genes that affect pig muscle growth,meat quality and fat deposition,so as to provide pork quality research provides new reference information.The longissimus dorsi muscle tissue samples of 6 Songliao black pigs and 6 Landrace pigs were collected,their RNA was extracted,and the mRNA was sequenced by Illumina HiSeq 2500 high-throughput sequencing technology,and the obtained reads were compared,annotated and differentiated.For expression analysis,NOISeq was used to screen out differentially expressed genes and perform enrichment analysis of related biological functions.The results showed that 664 differentially expressed genes were screened from the two pig species,of which 364 genes were highly expressed in Songliao black pigs and 300 genes were highly expressed in Landrace pigs.Through the biological function analysis of differentially expressed genes,LPIN1,FADS1,FADS2,PLIN2,PPARGC1A,PRKAG2 and ACSL1 were screened to participate in the regulation of lipid metabolism and muscle development.The related pathways were fatty acid metabolism,PPAR signaling pathway,AMPK signaling pathway,insulin signaling pathway and adipocytokine signaling pathway and so on.

Key words: Songliao black pig, Landrace pig, High-throughput sequencing, Longissimus dorsi muscle, Differential genes

侍玉梅, 陈少康, 邢凯, 赵延辉, 原佳妮, 盛熙晖, 齐晓龙, 倪和民, 郭勇, 王楚端. 基于高通量测序技术鉴定松辽黑猪与长白猪背最长肌差异基因[J]. 华北农学报, 2022, 37(5): 222-229. doi: 10.7668/hbnxb.20193162.

SHI Yumei, CHEN Shaokang, XING Kai, ZHAO Yanhui, YUAN Jiani, SHENG Xihui, QI Xiaolong, NI Hemin, GUO Yong, WANG Chuduan. Identification of Differential Genes of Longissimus Dorsi Muscle of Songliao Black Pig and Landrace Pig Based on High-throughput Sequencing Technology[J]. Acta Agriculturae Boreali-Sinica, 2022, 37(5): 222-229. doi: 10.7668/hbnxb.20193162.

http://www.hbnxb.net/CN/Y2022/V37/I5/222

图/表 7

表1 样本比对结果统计

Tab.1 Statistics of sample comparison results

样本 Sample	分组 Grouping	总读长 Total reads	比对率/% Comparison rate	样本 Sample	分组 Grouping	总读长 Total reads	比对率/% Comparison rate
SL1	松辽	10 295 863	88.53	L1	长白	9 152 284	90.49
SL2	松辽	9 800 893	88.08	L2	长白	11 620 495	88.87
SL3	松辽	10 984 670	88.19	L3	长白	9 395 823	88.28
SL4	松辽	12 227 762	88.14	L4	长白	10 226 545	86.66
SL5	松辽	10 516 442	87.66	L5	长白	12 804 405	87.70
SL6	松辽	10 332 247	88.58	L6	长白	10 644 773	87.37

图1 基因表达整体分析 A为动态表达范围图,该图显示了每个样本中CPM值超过0的基因的分布;B图反映了低表达基因在总转录本中所占的比例。

Fig.1 Global analysis of gene expression A is the dynamic expression range map,which shows the distribution of differentially expressed genes with CPM values over 0 in each sample;B map reflects the proportion of low-expressed genes in total transcripts.

图2 生物型分布

Fig.2 Biotype distribution(per sample)

图3 转录组差异分析结果 A图代表2个品种猪的表达值总图,其中,红点代表差异表达基因;横坐标代表基因在长白猪中的表达水平,纵坐标代表基因在松辽黑猪中的表达水平。B图代表(M,D)值和差异表达基因汇总图。横坐标表示M=log₂(

x ¯

healty/

x ¯

tumoral)值,而纵坐标表示D=

x ¯

healty-

x ¯

tumoral值,黑点表示(M,D)值,其中(|M|>1),红点表示差异表达基因。

Fig.3 Transcriptome differential analysis results Panel A represents the overall graph of the expression values of the two breeds of pigs,in which the red dots represent the differentially expressed genes.The abscissa represents the expression level of the gene in Landrace pigs,and the ordinate represents the expression level of the gene in Songliao Black pigs.Panel B represents(M,D)values and summary plots of differentially expressed genes.The abscissa represents the value of M=log₂(

x ¯

healty/

x ¯

tumoral),while the ordinate represents the value of D=

x ¯

healty-

x ¯

tumoral,the black point represents the(M,D)value,where(|M|>1),the red point represents differentially expressed genes.

x ¯

healty/

x ¯

tumoral)值,而纵坐标表示D=

x ¯

healty-

x ¯

tumoral值,黑点表示(M,D)值,其中(|M|>1),红点表示差异表达基因。

x ¯

healty/

x ¯

tumoral),while the ordinate represents the value of D=

x ¯

healty-

x ¯

tumoral,the black point represents the(M,D)value,where(|M|>1),the red point represents differentially expressed genes.

图4 GO富集分析 1.细胞过程; 2.生物调节; 3.生物过程的调节; 4.对刺激的反应; 5.代谢过程; 6.多细胞有机体过程; 7.生物过程的正向调控; 8.信令; 9.发展过程; 10.定位; 11.细胞成分组织或生物发生; 12.生物过程负调控; 13.免疫系统过程; 14.运动; 15.多组织进程; 16.细胞增殖; 17.生物黏附; 18.繁殖; 19.生殖过程; 20.行为; 21.成长; 22.细胞杀伤; 23.有节奏的过程; 24.解毒; 25.色素沉着; 26.细胞聚集; 27.细胞; 28.细胞部分; 29.细胞器; 30.膜; 31.膜部分; 32.细胞器部分; 33.细胞外区; 34.含蛋白质的复合物; 35.胞外区部分; 36.膜封闭内腔; 37.突触; 38.超分子配合物; 39.细胞连接; 40.突触部分; 41.黏合物; 42.催化活性; 43.分子功能调节剂; 44.分子换能器活性; 45.运输活动; 46.结构分子活性; 47.转录调节活性; 48.抗氧化活性; 49.自噬受体活性; 50.蛋白质标签; 51.分子载体活性; 52.翻译调节活动。

Fig.4 GO enrichment analysis 1.Cellular process; 2.Biological regulation; 3.Regulation of biological process; 4.Response to stimulus; 5.Metabolic process; 6.Multicellular organismal process; 7.Positive regulation of biological process; 8.Signaling; 9.Developmental process; 10.Localization; 11.Cellular component organization or biogenesis; 12.Negative regulation of biological process; 13.Immune system process; 14.Locomotion; 15.Multi-organism process; 16.Cell proliferation; 17.Biological adhesion; 18.Reproduction; 19.Reproductive process; 20.Behavior; 21.Growth; 22.Cell killing; 23.Rhythmic process; 24.Detoxification; 25.Pigmentation; 26.Cell aggregation; 27.Cell; 28.Cell part; 29.Organelle; 30.Membrane; 31.Membrane part; 32.Organelle part; 33.Extracellular region; 34.Protein-containing complex; 35.Extracellular region part; 36.Membrane-enclosed lumen; 37.Synapse; 38.Supramolecular complex; 39.Cell junction; 40.Synapse part; 41.Binding; 42.Catalytic activity; 43.Molecular function regulator; 44.Molecular transducer activity; 45.Transporter activity; 46.Structural molecule activity; 47.Transcription regulator activity; 48.Antioxidant activity; 49.Cargo receptor activity; 50.Protein tag; 51.Molecular carrier activity; 52.Translation regulator activity.

图5 KEGG通路富集分析

Fig.5 KEGG pathway enrichment analysis

表2 脂质代谢相关KEGG通路

Tab.2 Lipid metabolism-related KEGG pathway

基因名 Gene name	中文名 Chinese name	基因号 Gene number	富集通路 Enrichment pathway
LPIN1	脂质1基因	ENSSSCG00000008624	mTOR信号通路
FADS1	脂肪酸去饱和酶1基因	ENSSSCG00000024015	脂肪酸代谢
FADS2	脂肪酸去饱和酶2基因	ENSSSCG00000013072	PPAR信号通路
			脂肪酸代谢
PLIN2	脂滴包被蛋白2基因	ENSSSCG00000035863	PPAR信号通路
PPARGC1A	过氧化物酶体增殖物激活受体γ	ENSSSCG00000029275	AMPK信号通路
	辅助激活因子1α基因		胰岛素抵抗
			脂肪细胞因子信号通路
			胰岛素信号通路
PRKAG2	蛋白激酶腺嘌呤核糖核苷酸	ENSSSCG00000016432	AMPK信号通路
	激活的非催化亚基γ2基因		长寿调节途径-多物种
			紧密连接
			胰岛素抵抗
			脂肪细胞因子信号通路
			胰岛素信号通路
			昼夜节律
			肥厚型心肌病
ACSL1	酰基辅酶A合成酶长链家	ENSSSCG00000015784	PPAR信号通路
	族成员1基因		脂肪酸代谢
			脂肪细胞因子信号通路

参考文献 30

[1]	Ali M, Baek K H, Lee S Y, Kim H C, Park J Y, Jo C, Jung J H, Park H C, Nam K C. Comparative meat qualities of boston butt muscles (M. subscapularis) from different pig breeds available in Korean market[J]. Food Science of Animal Resources, 2021, 41(1):71-84. doi: 10.5851/kosfa.2020.e79. doi: 10.5851/kosfa.2020.e79 URL
[2]	Gaballa A, Guariglia-Oropeza V, Wiedmann M, Boor K J. Cross talk between SigB and PrfA in Listeria monocytogenes facilitates transitions between extra-and intracellular environments[J]. Microbiology and Molecular Biology Reviews, 2019, 83(4):e00034-e00019.doi: 10.1128/mmbr.00034-19. doi: 10.1128/mmbr.00034-19
[3]	简晨晨, 邵俊红, 白俊艳, 冀祥, 韩志洪, 王龙威, 崔晗晗, 彭彬, 杨浩杰, 王淑艳. 影响新美系长白猪初生重的因素分析[J]. 当代畜禽养殖业, 2021(1):42-43.doi: 10.14070/j.cnki.15-1150.2021.01.019. doi: 10.14070/j.cnki.15-1150.2021.01.019
	Jian C C, Shao J H, Bai J Y, Ji X, Han Z H, Wang L W, Cui H H, Peng B, Yang H J, Wang S Y. Analysis of factors affecting the birth weight of Xinmei Landrace pigs[J]. Modern Animal Husbandry, 2021(1):42-43.
[4]	王志秀. 基于转录组和蛋白组数据鉴定猪肌肉生长和脂肪沉积相关的基因[D]. 北京: 中国农业大学, 2017.
	Wang Z X. Identification of genes related to muscle growth and lipid deposition from transcriptomic and proteomic profiles of pig[D]. Beijing: China Agricultural University, 2017.
[5]	Xu Y J, Qian H, Feng X T, Xiong Y Z, Lei M G, Ren Z Q, Zuo B, Xu D Q, Ma Y, Yuan H. Differential proteome and transcriptome analysis of porcine skeletal muscle during development[J]. Journal of Proteomics, 2012, 75(7):2093-2108.doi: 10.1016/j.jprot.2012.01.013. doi: 10.1016/j.jprot.2012.01.013 pmid: 22270015
[6]	Tarazona S, Furi-Tarí P, Turrà D, Pietro A D, Nueda M J, Ferrer A, Conesa A. Data quality aware analysis of differential expression in RNA-seq with NOISeq R/Bioc package[J]. Nucleic Acids Research, 2015, 43(21):e140.doi: 10.1093/nar/gkv711. doi: 10.1093/nar/gkv711
[7]	李江华. GB/T 17236—2008《生猪屠宰操作规程》的主要内容[J]. 肉类研究, 2014, 28(7):3-4.
	Li J H. The main content of GB/T 17236—2008 "Operation Rules for Slaughtering Live Pigs"[J]. Meat Research,2014, 28(7):3-4.
[8]	Bolger A M, Lohse M, Usadel B. Trimmomatic:a flexible trimmer for Illumina sequence data[J]. Bioinformatics, 2014, 30(15):2114-2120.doi: 10.1093/bioinformatics/btu170. doi: 10.1093/bioinformatics/btu170 URL
[9]	de Sena Brandine G, Smith A D. Falco:high-speed FastQC emulation for quality control of sequencing data[J]. F1000Res, 2019, 8:1874.doi: 10.12688/f1000research.21142.2. doi: 10.12688/f1000research.21142.2 URL
[10]	Wingett S W, Andrews S. FastQ Screen:A tool for multi-genome mapping and quality control[J]. F1000Research, 2018, 7:1338.doi: 10.12688/f1000research.15931.2. doi: 10.12688/f1000research.15931.2 pmid: 30254741
[11]	Musich R, Cadle-Davidson L, Osier M V. Comparison of short-read sequence aligners indicates strengths and weaknesses for biologists to consider[J]. Frontiers in Plant Science, 2021, 12: 657240. doi: 10.3389/fpls.2021.657240. doi: 10.3389/fpls.2021.657240 URL
[12]	Sarantopoulou D, Brooks T G, Nayak S, Mrcˇela A, Lahens N F, Grant G R. Comparative evaluation of full-length isoform quantification from RNA-Seq[J]. BMC Bioinformatics, 2021, 22(1): 266. doi: 10.1186/s12859-021-04198-1. doi: 10.1186/s12859-021-04198-1 pmid: 34034652
[13]	Putri G H, Anders S, Pyl P T, Pimanda J E, Zanini F. Analysing high-throughput sequencing data in Python with HTSeq 2.0[J]. Bioinformatics, 2022, 38(10): 2943-2945. doi: 10.1093/bioinformatics/btac166. doi: 10.1093/bioinformatics/btac166 URL
[14]	Tarazona S, García-Alcalde F, Dopazo J, Ferrer A, Conesa A. Differential expression in RNA-seq:A matter of depth[J]. Genome Res, 2011, 21(12):2213-2223.doi: 10.1101/gr.124321.111. doi: 10.1101/gr.124321.111 pmid: 21903743
[15]	Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms[J]. Nucleic Acids Research, 2020, 49(D1): D545-D551. doi: 10.1093/nar/gkaa970. doi: 10.1093/nar/gkaa970 URL
[16]	Carnero A, Blanco-Aparicio C, Renner O, Link W, Leal J F M. The PTEN/PI3K/AKT signalling pathway in cancer,therapeutic implications[J]. Current Cancer Drug Targets, 2008, 8(3):187-198.doi: 10.2174/156800908784293659. doi: 10.2174/156800908784293659 URL
[17]	He X P, Xu X W, Zhao S H, Fan B, Yu M, Zhu M J, Li C C, Peng Z Z, Liu B. Investigation of Lpin1 as a candidate gene for fat deposition in pigs[J]. Molecular Biology Reports, 2009, 36(5):1175-1180.doi: 10.1007/s11033-008-9294-4. doi: 10.1007/s11033-008-9294-4 pmid: 18581256
[18]	胡濒月, 黄英, 杨明华, 潘洪彬, 赵素梅. PLIN2对脂类代谢的调控研究[J]. 中国医药科学, 2018, 8(15):40-43.doi: 10.3969/j.issn.2095-0616.2018.15.011. doi: 10.3969/j.issn.2095-0616.2018.15.011
	Hu B Y, Huang Y, Yang M H, Pan H B, Zhao S M. Research on the regulation of lipid metabolism by PLIN[J]. China Medicine and Pharmacy, 2018, 8(15):40-43.
[19]	Davoli R, Gandolfi G, Braglia S, Comella M, Zambonelli P, Buttazzoni L, Russo V. New SNP of the porcine Perilipin 2(PLIN2)gene,association with carcass traits and expression analysis in skeletal muscle[J]. Molecular Biology Reports, 2011, 38(3):1575-1583.doi: 10.1007/s11033-010-0266-0. doi: 10.1007/s11033-010-0266-0 URL
[20]	宋文莉, 田雨, 王宪娥, 张立, 徐莉, 释栋, 冯向辉, 路瑞芳, 陈智滨, 孟焕新. FADS1 rs174537基因多态性与侵袭性牙周炎患者血清蛋白的相关性[J]. 北京大学学报(医学版), 2016, 48(1):10-15.doi: 10.3969/j.issn.1671-167X.2016.01.003. doi: 10.3969/j.issn.1671-167X.2016.01.003
	Song W L, Tian Y, Wang X E, Zhang L, Xu L, Shi D, Feng X H, Lu R F, Chen Z B, Meng H X. Association between FADS1 rs174537 polymorphism and serum proteins in patients with aggressive periodontitis[J]. Journal of Peking University (Health Sciences), 2016, 48(1):10-15.
[21]	Koletzko B, Reischl E, Tanjung C, Gonzalez-Casanova I, Ramakrishnan U, Meldrum S, Simmer K, Heinrich J, Demmelmair H. FADS1 and FADS2 polymorphisms modulate fatty acid metabolism and dietary impact on health[J]. Annual Review of Nutrition, 2019, 39:21-44. doi: 10.1146/annurev-nutr-082018-124250. doi: 10.1146/annurev-nutr-082018-124250 URL
[22]	Tian J B, Lou J, Cai Y M, Rao M L, Lu Z Q, Zhu Y, Zou D Y, Peng X T, Wang H X, Zhang M, Niu S Y, Li Y, Zhong R, Chang J, Miao X P. Risk SNP-mediated enhancer-promoter interaction drives colorectal cancer through both FADS2 and AP002754.2[J]. Cancer Research, 2020, 80(9): 1804-1818. doi: 10.1158/0008-5472.can-19-2389. doi: 10.1158/0008-5472.can-19-2389 URL
[23]	Moradi S, Mirzaei K, Maghbooli Z, Abdurahman A A, Keshavarz S A. Variants in the PPARGC1A gene may influence the effect of fat intake on resting metabolic rate in obese women[J]. Lipids, 2018, 53(3): 291-300. doi: 10.1002/lipd.12024. doi: 10.1002/lipd.12024 URL
[24]	Tan H W S, Anjum B, Shen H M, Ghosh S, Yen P M, Sinha R A. Lysosomal inhibition attenuates peroxisomal gene transcription via suppression of PPARA and PPARGC1A levels[J]. Autophagy, 2019, 15(8): 1455-1459. doi: 10.1080/15548627.2019.1609847. doi: 10.1080/15548627.2019.1609847 pmid: 31032705
[25]	Gandolfi G, Cinar M U, Ponsuksili S, Wimmers K, Tesfaye D, Looft C, Jüngst H, Tholen E, Phatsara C, Schellander K, Davoli R. Association of PPARGC1A and CAPNS1 gene polymorphisms and expression with meat quality traits in pigs[J]. Meat Science, 2011, 89(4):478-485.doi: 10.1016/j.meatsci.2011.05.015. doi: 10.1016/j.meatsci.2011.05.015 pmid: 21680104
[26]	Mazur I I, Drozdovska S, Andrieieva O, Vinnichuk Y, Polishchuk A, Dosenko V, Andreev I, Pickering C, Ahmetov I I. PPARGC1A gene polymorphism is associated with exercise-induced fat loss[J]. Molecular Biology Reports, 2020, 47(10): 7451-7457. doi: 10.1007/s11033-020-05801-z. doi: 10.1007/s11033-020-05801-z URL
[27]	Jing L, Hou Y, Wu H, Miao Y X, Li X Y, Cao J H, Brameld J M, Parr T, Zhao S H. Transcriptome analysis of mRNA and miRNA in skeletal muscle indicates an important network for differential Residual Feed Intake in pigs[J]. Scientific Reports, 2015, 5:11953.doi: 10.1038/srep11953. doi: 10.1038/srep11953 pmid: 26150313
[28]	Jung H S, Shimizu-Albergine M, Shen X, Kramer F, Shao D, Vivekanandan-Giri A, Pennathur S, Tian R, Kanter J E, Bornfeldt K E. TNF-α induces acyl-CoA synthetase 3 to promote lipid droplet formation in human endothelial cells[J]. Journal of Lipid Research, 2020, 61(1): 33-44. doi: 10.1194/jlr.ra119000256. doi: 10.1194/jlr.RA119000256 pmid: 31722970
[29]	Zhao Z D, Abbas Raza S H, Tian H S, Shi B G, Luo Y Z, Wang J Q, Liu X, Li S B, Bai Y B, Hu J. Effects of overexpression of ACSL1 gene on the synthesis of unsaturated fatty acids in adipocytes of bovine[J]. Arch Biochem Biophys, 2020, 695: 108648. doi: 10.1016/j.abb.2020.108648. doi: 10.1016/j.abb.2020.108648 URL
[30]	Zhang J, Zhang Y, Gong H, Cui L, Huang T, Ai H, Ren J, Huang L, Yang B. Genetic mapping using 1.4M SNP array refined loci for fatty acid composition traits in Chinese Erhualian and Bamaxiang pigs[J]. Journal of Animal Breeding and Genetics, 2017, 134(6):472-483.doi: 10.1111/jbg.12297. doi: 10.1111/jbg.12297 pmid: 28940847

选择文件类型/文献管理软件名称

选择包含的内容