{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T00:43:43Z","timestamp":1790210623749,"version":"4.1.0"},"reference-count":53,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T00:00:00Z","timestamp":1630368000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T00:00:00Z","timestamp":1630368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100001458","name":"American Kennel Club Canine Health Foundation","doi-asserted-by":"publisher","award":["02066"],"award-info":[{"award-number":["02066"]}],"id":[{"id":"10.13039\/100001458","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Dogs with X-linked hereditary nephropathy (XLHN) are an animal model for Alport syndrome in humans and progressive chronic kidney disease (CKD). Using mRNA sequencing (mRNA-seq), we have characterized the gene expression profile affecting the progression of XLHN; however, the microRNA (miRNA, miR) expression remains unknown. With small RNA-seq and quantitative RT-PCR (qRT-PCR), we used 3 small RNA-seq analysis tools (QIAGEN OmicSoft Studio, miRDeep2, and CPSS 2.0) to profile differentially expressed renal miRNAs, top-ranked miRNA target genes, and enriched biological processes and pathways in CKD progression. Twenty-three kidney biopsies were collected from 5 dogs with XLHN and 4 age-matched, unaffected littermates at 3 clinical time points (T1: onset of proteinuria, T2: onset of azotemia, and T3: advanced azotemia). We identified up to 23 differentially expressed miRNAs at each clinical time point. Five miRNAs (miR-21, miR-146b, miR-802, miR-142, miR-147) were consistently upregulated in affected dogs. We identified miR-186 and miR-26b as effective reference miRNAs for qRT-PCR. This study applied small RNA-seq to identify differentially expressed miRNAs that might regulate critical pathways contributing to CKD progression in dogs with XLHN.<\/jats:p>","DOI":"10.1038\/s41598-021-96870-y","type":"journal-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T06:03:02Z","timestamp":1630389782000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Small RNA sequencing evaluation of renal microRNA biomarkers in dogs with X-linked hereditary nephropathy"],"prefix":"10.1038","volume":"11","author":[{"given":"Candice P.","family":"Chu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiguang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenping","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ethan Y.","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mary B.","family":"Nabity","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,8,31]]},"reference":[{"key":"96870_CR1","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1111\/vec.12031","volume":"23","author":"GE Lees","year":"2013","unstructured":"Lees, G. E. Kidney diseases caused by glomerular basement membrane type IV collagen defects in dogs. J. Vet. Emerg. Crit. Care (San Antonio) 23, 184\u2013193. https:\/\/doi.org\/10.1111\/vec.12031 (2013).","journal-title":"J. Vet. Emerg. Crit. Care (San Antonio)"},{"key":"96870_CR2","doi-asserted-by":"crossref","first-page":"373","DOI":"10.2460\/ajvr.1999.60.03.373","volume":"60","author":"GE Lees","year":"1999","unstructured":"Lees, G. E. et al. New form of X-linked dominant hereditary nephritis in dogs. Am. J. Vet. Res. 60, 373\u2013383 (1999).","journal-title":"Am. J. Vet. Res."},{"key":"96870_CR3","doi-asserted-by":"publisher","first-page":"16776","DOI":"10.1038\/s41598-017-16603-y","volume":"7","author":"CP Chu","year":"2017","unstructured":"Chu, C. P. et al. RNA-seq of serial kidney biopsies obtained during progression of chronic kidney disease from dogs with X-linked hereditary nephropathy. Sci. Rep. 7, 16776. https:\/\/doi.org\/10.1038\/s41598-017-16603-y (2017).","journal-title":"Sci. Rep."},{"key":"96870_CR4","doi-asserted-by":"publisher","first-page":"522","DOI":"10.1038\/nrg1379","volume":"5","author":"L He","year":"2004","unstructured":"He, L. & Hannon, G. J. MicroRNAs: Small RNAs with a big role in gene regulation. Nat. Rev. Genet. 5, 522\u2013531. https:\/\/doi.org\/10.1038\/nrg1379 (2004).","journal-title":"Nat. Rev. Genet."},{"key":"96870_CR5","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1038\/nature02871","volume":"431","author":"V Ambros","year":"2004","unstructured":"Ambros, V. The functions of animal microRNAs. Nature 431, 350\u2013355. https:\/\/doi.org\/10.1038\/nature02871 (2004).","journal-title":"Nature"},{"key":"96870_CR6","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1016\/j.cell.2009.01.002","volume":"136","author":"DP Bartel","year":"2009","unstructured":"Bartel, D. P. MicroRNAs: Target recognition and regulatory functions. Cell 136, 215\u2013233. https:\/\/doi.org\/10.1016\/j.cell.2009.01.002 (2009).","journal-title":"Cell"},{"key":"96870_CR7","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1038\/nrneph.2014.202","volume":"11","author":"P Trionfini","year":"2015","unstructured":"Trionfini, P., Benigni, A. & Remuzzi, G. MicroRNAs in kidney physiology and disease. Nat. Rev. Nephrol. 11, 23\u201333. https:\/\/doi.org\/10.1038\/nrneph.2014.202 (2015).","journal-title":"Nat. Rev. Nephrol."},{"key":"96870_CR8","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1293\/tox.2017-0051","volume":"31","author":"O Ichii","year":"2018","unstructured":"Ichii, O. & Horino, T. MicroRNAs associated with the development of kidney diseases in humans and animals. J. Toxicol. Pathol. 31, 23\u201334. https:\/\/doi.org\/10.1293\/tox.2017-0051 (2018).","journal-title":"J. Toxicol. Pathol."},{"key":"96870_CR9","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1016\/j.rvsc.2014.01.003","volume":"96","author":"O Ichii","year":"2014","unstructured":"Ichii, O. et al. MicroRNA expression profiling of cat and dog kidneys. Res. Vet. Sci. 96, 299\u2013303. https:\/\/doi.org\/10.1016\/j.rvsc.2014.01.003 (2014).","journal-title":"Res. Vet. Sci."},{"key":"96870_CR10","doi-asserted-by":"publisher","first-page":"649","DOI":"10.1186\/s12864-016-2958-x","volume":"17","author":"EM Koenig","year":"2016","unstructured":"Koenig, E. M. et al. The beagle dog MicroRNA tissue atlas: Identifying translatable biomarkers of organ toxicity. BMC Genomics 17, 649. https:\/\/doi.org\/10.1186\/s12864-016-2958-x (2016).","journal-title":"BMC Genomics"},{"key":"96870_CR11","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1093\/nar\/gkr688","volume":"40","author":"MR Friedlander","year":"2012","unstructured":"Friedlander, M. R., Mackowiak, S. D., Li, N., Chen, W. & Rajewsky, N. miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res. 40, 37\u201352. https:\/\/doi.org\/10.1093\/nar\/gkr688 (2012).","journal-title":"Nucleic Acids Res."},{"key":"96870_CR12","doi-asserted-by":"publisher","first-page":"3289","DOI":"10.1093\/bioinformatics\/btx066","volume":"33","author":"C Wan","year":"2017","unstructured":"Wan, C. et al. CPSS 2.0: A computational platform update for the analysis of small RNA sequencing data. Bioinformatics 33, 3289\u20133291. https:\/\/doi.org\/10.1093\/bioinformatics\/btx066 (2017).","journal-title":"Bioinformatics"},{"key":"96870_CR13","doi-asserted-by":"publisher","first-page":"D127","DOI":"10.1093\/nar\/gkz757","volume":"48","author":"Y Chen","year":"2020","unstructured":"Chen, Y. & Wang, X. miRDB: An online database for prediction of functional microRNA targets. Nucleic Acids Res. 48, D127\u2013D131. https:\/\/doi.org\/10.1093\/nar\/gkz757 (2020).","journal-title":"Nucleic Acids Res."},{"key":"96870_CR14","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1186\/s13059-019-1629-z","volume":"20","author":"W Liu","year":"2019","unstructured":"Liu, W. & Wang, X. Prediction of functional microRNA targets by integrative modeling of microRNA binding and target expression data. Genome Biol. 20, 18. https:\/\/doi.org\/10.1186\/s13059-019-1629-z (2019).","journal-title":"Genome Biol."},{"key":"96870_CR15","doi-asserted-by":"publisher","first-page":"D183","DOI":"10.1093\/nar\/gkw1138","volume":"45","author":"H Mi","year":"2017","unstructured":"Mi, H. et al. PANTHER version 11: Expanded annotation data from gene ontology and reactome pathways, and data analysis tool enhancements. Nucleic Acids Res. 45, D183\u2013D189. https:\/\/doi.org\/10.1093\/nar\/gkw1138 (2017).","journal-title":"Nucleic Acids Res."},{"key":"96870_CR16","doi-asserted-by":"publisher","first-page":"D649","DOI":"10.1093\/nar\/gkx1132","volume":"46","author":"A Fabregat","year":"2018","unstructured":"Fabregat, A. et al. The reactome pathway knowledgebase. Nucleic Acids Res. 46, D649\u2013D655. https:\/\/doi.org\/10.1093\/nar\/gkx1132 (2018).","journal-title":"Nucleic Acids Res."},{"key":"96870_CR17","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1177\/0300985815624494","volume":"53","author":"SL Benali","year":"2016","unstructured":"Benali, S. L. et al. X-linked hereditary nephropathy in navasota dogs: Clinical pathology, morphology, and gene expression during disease progression. Vet. Pathol. 53, 803\u2013812. https:\/\/doi.org\/10.1177\/0300985815624494 (2016).","journal-title":"Vet. Pathol."},{"key":"96870_CR18","doi-asserted-by":"publisher","first-page":"976","DOI":"10.1007\/s00335-005-0179-8","volume":"17","author":"KA Greer","year":"2006","unstructured":"Greer, K. A. et al. Gene expression analysis in a canine model of X-linked Alport syndrome. Mamm. Genome 17, 976\u2013990. https:\/\/doi.org\/10.1007\/s00335-005-0179-8 (2006).","journal-title":"Mamm. Genome"},{"key":"96870_CR19","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1038\/ki.2011.345","volume":"81","author":"O Ichii","year":"2012","unstructured":"Ichii, O. et al. Altered expression of microRNA miR-146a correlates with the development of chronic renal inflammation. Kidney Int. 81, 280\u2013292. https:\/\/doi.org\/10.1038\/ki.2011.345 (2012).","journal-title":"Kidney Int."},{"key":"96870_CR20","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.taap.2015.12.002","volume":"312","author":"KL Pellegrini","year":"2016","unstructured":"Pellegrini, K. L. et al. Application of small RNA sequencing to identify microRNAs in acute kidney injury and fibrosis. Toxicol. Appl. Pharmacol. 312, 42\u201352. https:\/\/doi.org\/10.1016\/j.taap.2015.12.002 (2016).","journal-title":"Toxicol. Appl. Pharmacol."},{"key":"96870_CR21","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1089\/hum.2018.205","volume":"30","author":"J Guo","year":"2019","unstructured":"Guo, J. et al. Dysregulated expression of microRNA-21 and disease-related genes in human patients and in a mouse model of Alport syndrome. Hum. Gene Ther. 30, 865\u2013881. https:\/\/doi.org\/10.1089\/hum.2018.205 (2019).","journal-title":"Hum. Gene Ther."},{"key":"96870_CR22","doi-asserted-by":"publisher","first-page":"663","DOI":"10.1007\/s00125-012-2804-x","volume":"56","author":"X Zhong","year":"2013","unstructured":"Zhong, X. et al. miR-21 is a key therapeutic target for renal injury in a mouse model of type 2 diabetes. Diabetologia 56, 663\u2013674. https:\/\/doi.org\/10.1007\/s00125-012-2804-x (2013).","journal-title":"Diabetologia"},{"key":"96870_CR23","doi-asserted-by":"publisher","first-page":"27209","DOI":"10.1038\/srep27209","volume":"6","author":"MF Hennino","year":"2016","unstructured":"Hennino, M. F. et al. miR-21-5p renal expression is associated with fibrosis and renal survival in patients with IgA nephropathy. Sci. Rep. 6, 27209. https:\/\/doi.org\/10.1038\/srep27209 (2016).","journal-title":"Sci. Rep."},{"key":"96870_CR24","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1681\/ASN.2013121274","volume":"26","author":"JY Lai","year":"2015","unstructured":"Lai, J. Y. et al. MicroRNA-21 in glomerular injury. J. Am. Soc. Nephrol. 26, 805\u2013816. https:\/\/doi.org\/10.1681\/ASN.2013121274 (2015).","journal-title":"J. Am. Soc. Nephrol."},{"key":"96870_CR25","doi-asserted-by":"publisher","first-page":"1668","DOI":"10.1681\/ASN.2010111168","volume":"22","author":"X Zhong","year":"2011","unstructured":"Zhong, X., Chung, A. C., Chen, H. Y., Meng, X. M. & Lan, H. Y. Smad3-mediated upregulation of miR-21 promotes renal fibrosis. J. Am. Soc. Nephrol. 22, 1668\u20131681. https:\/\/doi.org\/10.1681\/ASN.2010111168 (2011).","journal-title":"J. Am. Soc. Nephrol."},{"key":"96870_CR26","doi-asserted-by":"publisher","first-page":"F793","DOI":"10.1152\/ajprenal.00273.2011","volume":"301","author":"A Zarjou","year":"2011","unstructured":"Zarjou, A., Yang, S., Abraham, E., Agarwal, A. & Liu, G. Identification of a microRNA signature in renal fibrosis: Role of miR-21. Am. J. Physiol. Renal Physiol. 301, F793-801. https:\/\/doi.org\/10.1152\/ajprenal.00273.2011 (2011).","journal-title":"Am. J. Physiol. Renal Physiol."},{"key":"96870_CR27","doi-asserted-by":"publisher","first-page":"121ra118","DOI":"10.1126\/scitranslmed.3003205","volume":"4","author":"BN Chau","year":"2012","unstructured":"Chau, B. N. et al. MicroRNA-21 promotes fibrosis of the kidney by silencing metabolic pathways. Sci. Transl. Med. 4, 121ra118. https:\/\/doi.org\/10.1126\/scitranslmed.3003205 (2012).","journal-title":"Sci. Transl. Med."},{"key":"96870_CR28","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1177\/0300985818806050","volume":"56","author":"SD Clark","year":"2019","unstructured":"Clark, S. D. et al. Abnormal expression of miR-21 in kidney tissue of dogs with X-linked hereditary nephropathy: A canine model of chronic kidney disease. Vet. Pathol. 56, 93\u2013105. https:\/\/doi.org\/10.1177\/0300985818806050 (2019).","journal-title":"Vet. Pathol."},{"key":"96870_CR29","doi-asserted-by":"publisher","first-page":"171","DOI":"10.3233\/DMA-2011-0766","volume":"30","author":"G Wang","year":"2011","unstructured":"Wang, G. et al. Elevated levels of miR-146a and miR-155 in kidney biopsy and urine from patients with IgA nephropathy. Dis. Markers 30, 171\u2013179. https:\/\/doi.org\/10.3233\/DMA-2011-0766 (2011).","journal-title":"Dis. Markers"},{"key":"96870_CR30","doi-asserted-by":"publisher","first-page":"6477","DOI":"10.1007\/s11033-013-2763-4","volume":"40","author":"MR Alipour","year":"2013","unstructured":"Alipour, M. R., Khamaneh, A. M., Yousefzadeh, N., Mohammad-nejad, D. & Soufi, F. G. Upregulation of microRNA-146a was not accompanied by downregulation of pro-inflammatory markers in diabetic kidney. Mol. Biol. Rep. 40, 6477\u20136483. https:\/\/doi.org\/10.1007\/s11033-013-2763-4 (2013).","journal-title":"Mol. Biol. Rep."},{"key":"96870_CR31","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1111\/j.1440-1797.2012.01573.x","volume":"17","author":"J Lu","year":"2012","unstructured":"Lu, J. et al. Glomerular and tubulointerstitial miR-638, miR-198 and miR-146a expression in lupus nephritis. Nephrology (Carlton) 17, 346\u2013351. https:\/\/doi.org\/10.1111\/j.1440-1797.2012.01573.x (2012).","journal-title":"Nephrology (Carlton)"},{"key":"96870_CR32","doi-asserted-by":"publisher","first-page":"2985","DOI":"10.1681\/ASN.2016121280","volume":"28","author":"MA Baker","year":"2017","unstructured":"Baker, M. A. et al. Tissue-specific MicroRNA expression patterns in four types of kidney disease. J. Am. Soc. Nephrol. 28, 2985\u20132992. https:\/\/doi.org\/10.1681\/ASN.2016121280 (2017).","journal-title":"J. Am. Soc. Nephrol."},{"key":"96870_CR33","doi-asserted-by":"publisher","first-page":"1087","DOI":"10.1681\/ASN.2010090927","volume":"22","author":"DH Lin","year":"2011","unstructured":"Lin, D. H., Yue, P., Pan, C., Sun, P. & Wang, W. H. MicroRNA 802 stimulates ROMK channels by suppressing caveolin-1. J. Am. Soc. Nephrol. 22, 1087\u20131098. https:\/\/doi.org\/10.1681\/ASN.2010090927 (2011).","journal-title":"J. Am. Soc. Nephrol."},{"key":"96870_CR34","doi-asserted-by":"publisher","first-page":"5330","DOI":"10.1073\/pnas.0813121106","volume":"106","author":"D Anglicheau","year":"2009","unstructured":"Anglicheau, D. et al. MicroRNA expression profiles predictive of human renal allograft status. Proc Natl Acad Sci U S A 106, 5330\u20135335. https:\/\/doi.org\/10.1073\/pnas.0813121106 (2009).","journal-title":"Proc Natl Acad Sci U S A"},{"key":"96870_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.trim.2015.05.002","volume":"33","author":"E Soltaninejad","year":"2015","unstructured":"Soltaninejad, E. et al. Differential expression of microRNAs in renal transplant patients with acute T-cell mediated rejection. Transpl. Immunol. 33, 1\u20136. https:\/\/doi.org\/10.1016\/j.trim.2015.05.002 (2015).","journal-title":"Transpl. Immunol."},{"key":"96870_CR36","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.tox.2018.05.015","volume":"406\u2013407","author":"G Huang","year":"2018","unstructured":"Huang, G., Xue, J., Sun, X., Wang, J. & Yu, L. L. Necroptosis in 3-chloro-1, 2-propanediol (3-MCPD)-dipalmitate-induced acute kidney injury in vivo and its repression by miR-223-3p. Toxicology 406\u2013407, 33\u201343. https:\/\/doi.org\/10.1016\/j.tox.2018.05.015 (2018).","journal-title":"Toxicology"},{"key":"96870_CR37","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1111\/vcp.12743","volume":"48","author":"CP Chu","year":"2019","unstructured":"Chu, C. P. & Nabity, M. B. Comparison of RNA isolation and library preparation methods for small RNA sequencing of canine biofluids. Vet. Clin. Pathol. 48, 310\u2013319. https:\/\/doi.org\/10.1111\/vcp.12743 (2019).","journal-title":"Vet. Clin. Pathol."},{"key":"96870_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.imu.2019.100240","volume":"16","author":"MA Hossain","year":"2019","unstructured":"Hossain, M. A., Asa, T. A., Rahman, M. R. & Moni, M. A. Network-based approach to identify key candidate genes and pathways shared by thyroid cancer and chronic kidney disease. Inform. Med. Unlocked 16, 100240. https:\/\/doi.org\/10.1016\/j.imu.2019.100240 (2019).","journal-title":"Inform. Med. Unlocked"},{"key":"96870_CR39","doi-asserted-by":"publisher","unstructured":"Hossain, M. A., Asa, T. A., Islam, S. M., Hussain, M. S. & Moni, M. A. Identification of genetic association of thyroid cancer with Parkinsons disease, osteoporosis, chronic heart failure, chronic kidney disease, type 1 diabetes and type 2 diabetes. In 2019 5th International Conference on Advances in Electrical Engineering (ICAEE). 832\u2013837. https:\/\/doi.org\/10.1109\/ICAEE48663.2019.8975560 (2019).","DOI":"10.1109\/ICAEE48663.2019.8975560"},{"key":"96870_CR40","doi-asserted-by":"publisher","first-page":"1933","DOI":"10.1093\/bioinformatics\/bts294","volume":"28","author":"J Hu","year":"2012","unstructured":"Hu, J., Ge, H., Newman, M. & Liu, K. OSA: A fast and accurate alignment tool for RNA-Seq. Bioinformatics 28, 1933\u20131934. https:\/\/doi.org\/10.1093\/bioinformatics\/bts294 (2012).","journal-title":"Bioinformatics"},{"key":"96870_CR41","doi-asserted-by":"publisher","first-page":"R25","DOI":"10.1186\/gb-2009-10-3-r25","volume":"10","author":"B Langmead","year":"2009","unstructured":"Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25. https:\/\/doi.org\/10.1186\/gb-2009-10-3-r25 (2009).","journal-title":"Genome Biol."},{"key":"96870_CR42","doi-asserted-by":"publisher","first-page":"R18","DOI":"10.1186\/gb-2011-12-2-r18","volume":"12","author":"D Aird","year":"2011","unstructured":"Aird, D. et al. Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries. Genome Biol. 12, R18. https:\/\/doi.org\/10.1186\/gb-2011-12-2-r18 (2011).","journal-title":"Genome Biol."},{"key":"96870_CR43","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1038\/nbt.2957","volume":"32","author":"SEQC Consortium","year":"2014","unstructured":"SEQC Consortium. A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium. Nat. Biotechnol. 32, 903\u2013914. https:\/\/doi.org\/10.1038\/nbt.2957 (2014).","journal-title":"Nat. Biotechnol."},{"key":"96870_CR44","doi-asserted-by":"publisher","first-page":"1400","DOI":"10.3892\/ijmm.2015.2338","volume":"36","author":"G Lou","year":"2015","unstructured":"Lou, G. et al. Differential distribution of U6 (RNU6-1) expression in human carcinoma tissues demonstrates the requirement for caution in the internal control gene selection for microRNA quantification. Int. J. Mol. Med. 36, 1400\u20131408. https:\/\/doi.org\/10.3892\/ijmm.2015.2338 (2015).","journal-title":"Int. J. Mol. Med."},{"key":"96870_CR45","doi-asserted-by":"publisher","first-page":"5245","DOI":"10.1158\/0008-5472.CAN-04-0496","volume":"64","author":"CL Andersen","year":"2004","unstructured":"Andersen, C. L., Jensen, J. L. & Orntoft, T. F. Normalization of real-time quantitative reverse transcription-PCR data: A model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res. 64, 5245\u20135250. https:\/\/doi.org\/10.1158\/0008-5472.CAN-04-0496 (2004).","journal-title":"Cancer Res."},{"key":"96870_CR46","doi-asserted-by":"publisher","first-page":"31992","DOI":"10.1038\/srep31992","volume":"6","author":"CL Bockmeyer","year":"2016","unstructured":"Bockmeyer, C. L. et al. Comparison of different normalization strategies for the analysis of glomerular microRNAs in IgA nephropathy. Sci. Rep. 6, 31992. https:\/\/doi.org\/10.1038\/srep31992 (2016).","journal-title":"Sci. Rep."},{"key":"96870_CR47","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1111\/j.1939-1676.2012.00891.x","volume":"26","author":"MB Nabity","year":"2012","unstructured":"Nabity, M. B. et al. Urinary biomarkers of renal disease in dogs with X-linked hereditary nephropathy. J. Vet. Intern. Med. 26, 282\u2013293. https:\/\/doi.org\/10.1111\/j.1939-1676.2012.00891.x (2012).","journal-title":"J. Vet. Intern. Med."},{"key":"96870_CR48","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1186\/s13059-014-0550-8","volume":"15","author":"MI Love","year":"2014","unstructured":"Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550. https:\/\/doi.org\/10.1186\/s13059-014-0550-8 (2014).","journal-title":"Genome Biol."},{"key":"96870_CR49","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","volume":"57","author":"Y Benjamini","year":"1995","unstructured":"Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate\u2014A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B-Methodol. 57, 289\u2013300 (1995).","journal-title":"J. R. Stat. Soc. Ser. B-Methodol."},{"key":"96870_CR50","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1093\/bioinformatics\/btm595","volume":"24","author":"X Wang","year":"2007","unstructured":"Wang, X. & El Naqa, I. M. Prediction of both conserved and nonconserved microRNA targets in animals. Bioinformatics 24, 325\u2013332 (2007).","journal-title":"Bioinformatics"},{"key":"96870_CR51","doi-asserted-by":"publisher","first-page":"RESEARCH0034","DOI":"10.1186\/gb-2002-3-7-research0034","volume":"3","author":"J Vandesompele","year":"2002","unstructured":"Vandesompele, J. et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 3, RESEARCH0034. https:\/\/doi.org\/10.1186\/gb-2002-3-7-research0034 (2002).","journal-title":"Genome Biol."},{"key":"96870_CR52","doi-asserted-by":"publisher","first-page":"R19","DOI":"10.1186\/gb-2007-8-2-r19","volume":"8","author":"J Hellemans","year":"2007","unstructured":"Hellemans, J., Mortier, G., De Paepe, A., Speleman, F. & Vandesompele, J. qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol. 8, R19. https:\/\/doi.org\/10.1186\/gb-2007-8-2-r19 (2007).","journal-title":"Genome Biol."},{"key":"96870_CR53","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1006\/meth.2001.1262","volume":"25","author":"KJ Livak","year":"2001","unstructured":"Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods 25, 402\u2013408. https:\/\/doi.org\/10.1006\/meth.2001.1262 (2001).","journal-title":"Methods"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-021-96870-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-021-96870-y","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-021-96870-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T09:16:29Z","timestamp":1725700589000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-021-96870-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,31]]},"references-count":53,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["96870"],"URL":"https:\/\/doi.org\/10.1038\/s41598-021-96870-y","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,31]]},"assertion":[{"value":"11 January 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 July 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 August 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"17437"}}