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十二种河流型水牛组织定量 RT-PCR(RT-qPCR)表达数据归一化中合适参照基因的选择。

Selection of suitable reference genes for normalization of quantitative RT-PCR (RT-qPCR) expression data across twelve tissues of riverine buffaloes (Bubalus bubalis).

机构信息

Department of Animal Biotechnology, ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana, India.

Department of Zoology, Panjab University, Chandigarh, India.

出版信息

PLoS One. 2018 Mar 6;13(3):e0191558. doi: 10.1371/journal.pone.0191558. eCollection 2018.

DOI:10.1371/journal.pone.0191558
PMID:29509770
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5839537/
Abstract

Selection of reference genes has become an integral step in any real time quantitative PCR (RT-qPCR) based expression studies. The importance of this study stems from the fact that riverine buffaloes are major dairy species of Indian sub-continent and the information generated here will be of great interest to the investigators engaged in functional genomic studies of this important livestock species. In this study, an effort was made to evaluate a panel of 10 candidate reference genes (glyceraldehyde 3-phosphate dehydrogenase (GAPDH), beta- actin (ACTB), ubiquitously expressed transcript (UXT), ribosomal protein S15 (RPS15), ribosomal protein L-4 (RPL4), ribosomal protein S9 (RPS9), ribosomal protein S23 (RPS23), hydroxymethylbilane synthase (HMBS), β2 Microglobulin (β2M) and eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) across 12 tissues (mammary gland, kidney, spleen, liver, heart, intestine, ovary, lung, muscle, brain, subcutaneous fat and testis) of riverine buffaloes. In addition to overall analysis, tissue wise evaluation of expression stability of individual RG was also performed. Three different algorithms provided in geNorm, NormFinder and BestKeeper softwares were used to evaluate the stability of 10 potential reference genes from different functional classes. The M-value given by geNorm ranged from 0.9797 (RPS9 and UXT) to 1.7362 (RPS15). From the most stable to the least stable, genes were ranked as: UXT/RPS9> RPL4> RPS23> EEF1A1> ACTB> HMBS> GAPDH> B2M> RPS15. While NormFinder analysis ranked the genes as: UXT> RPS23> RPL4> RPS9> EEF1A1> HMBS> ACTB> β2M> GAPDH> RPS15. Based on the crossing point SD value and range of fold change expression, BestKeeper analysis ranked the genes as: RPS9> RPS23/UXT> RPL4> GAPDH> EEF1A1> ACTB> HMBS> β2M> RPS15. Overall the study has identified RPS23, RPS9, RPL4 and UXT genes to be the most stable and appropriate RGs that could be utilized for normalization of transcriptional data in various tissues of buffaloes. This manuscript thus provide useful information on panel of reference genes that could be helpful for researchers conducting functional genomic studies in riverine buffaloes.

摘要

在任何基于实时定量 PCR (RT-qPCR) 的表达研究中,选择参考基因已成为不可或缺的一步。这项研究的重要性源于这样一个事实,即印度次大陆的河流水牛是主要的奶牛品种,这里产生的信息将引起从事该重要家畜种功能基因组研究的研究人员的极大兴趣。在这项研究中,我们努力评估了一组 10 个候选参考基因(甘油醛 3-磷酸脱氢酶 (GAPDH)、β-肌动蛋白 (ACTB)、普遍表达转录物 (UXT)、核糖体蛋白 S15 (RPS15)、核糖体蛋白 L-4 (RPL4)、核糖体蛋白 S9 (RPS9)、核糖体蛋白 S23 (RPS23)、羟甲基胆素合酶 (HMBS)、β2 微球蛋白 (β2M)和真核翻译延伸因子 1α1 (EEF1A1)在印度河流水牛的 12 种组织(乳腺、肾脏、脾脏、肝脏、心脏、肠、卵巢、肺、肌肉、大脑、皮下脂肪和睾丸)中。除了进行全面分析外,还对每个组织中个体 RG 的表达稳定性进行了评估。使用 geNorm、NormFinder 和 BestKeeper 软件中的三种不同算法来评估来自不同功能类别的 10 个潜在参考基因的稳定性。geNorm 给出的 M 值范围为 0.9797(RPS9 和 UXT)至 1.7362(RPS15)。从最稳定到最不稳定,基因的排序为:UXT/RPS9>RPL4>RPS23>EEF1A1>ACTB>HMBS>GAPDH>B2M>RPS15。而 NormFinder 分析将基因排序为:UXT>RPS23>RPL4>RPS9>EEF1A1>HMBS>ACTB>β2M>GAPDH>RPS15。根据临界点 SD 值和表达倍数变化范围,BestKeeper 分析将基因排序为:RPS9>RPS23/UXT>RPL4>GAPDH>EEF1A1>ACTB>HMBS>β2M>RPS15。总的来说,这项研究确定了 RPS23、RPS9、RPL4 和 UXT 基因是最稳定和合适的 RG,可以用于水牛各种组织中转录数据的归一化。本研究因此提供了有关参考基因的有用信息,这可能有助于从事河流水牛功能基因组研究的研究人员。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/fb1c6f2ae832/pone.0191558.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/06731443675c/pone.0191558.g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/77ee5b301c8f/pone.0191558.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/e568fd04196a/pone.0191558.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/687f40c08e61/pone.0191558.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/ddad3ed5fdb4/pone.0191558.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/e4126079ccf9/pone.0191558.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/fb1c6f2ae832/pone.0191558.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/06731443675c/pone.0191558.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/7890a03ebf1b/pone.0191558.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/cb13d3add937/pone.0191558.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/77ee5b301c8f/pone.0191558.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/e568fd04196a/pone.0191558.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/687f40c08e61/pone.0191558.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/ddad3ed5fdb4/pone.0191558.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/e4126079ccf9/pone.0191558.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac48/5839537/fb1c6f2ae832/pone.0191558.g009.jpg

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