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Year : 2011  |  Volume : 2  |  Issue : 3  |  Page : 1-2  

CML patients: Decoding the miRNA Transcriptome


1 School of Computational and Integrative Sciences; Jawaharlal Nehru University; New Delhi- 110067, India
2 School of Life Sciences Jawaharlal Nehru University; New Delhi-110016, India
3 Department of Medical Oncology, Institute Rotary Cancer Hospital, All India Institute of Medical Science, New Delhi, India
4 Department of Biochemical Engineering and Biotechnology; Indian Institute of Technology; New Delhi-110067, India
5 School of Computational and Integrative Sciences; Jawaharlal Nehru University; New Delhi- 110067; School of Life Sciences Jawaharlal Nehru University; New Delhi-110016, India

Date of Web Publication26-May-2012

Correspondence Address:
Alok Bhattacharya
School of Computational and Integrative Sciences; Jawaharlal Nehru University; New Delhi- 110067; School of Life Sciences Jawaharlal Nehru University; New Delhi-110016
India
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Source of Support: None, Conflict of Interest: None


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How to cite this article:
Vaz C, Bharti R, Gupta R, Pandey P, Ahmed H, Kumar L, Kulshreshtha R, Bhattacharya A. CML patients: Decoding the miRNA Transcriptome. J Nat Sc Biol Med 2011;2, Suppl S1:1-2

How to cite this URL:
Vaz C, Bharti R, Gupta R, Pandey P, Ahmed H, Kumar L, Kulshreshtha R, Bhattacharya A. CML patients: Decoding the miRNA Transcriptome. J Nat Sc Biol Med [serial online] 2011 [cited 2020 Jan 28];2, Suppl S1:1-2. Available from: http://www.jnsbm.org/text.asp?2011/2/3/1/95663

MicroRNAs have been recognized as one of the key regulatory non coding RNAs that are involved in a number of basic cellular processes and are also thought to be a useful biological marker for disease state, such as cancer. Next generation or deep sequencing of total small RNAs is helping microRNA discovery and profiling and has led to identification of a number of differentially regulated functionally important miRNAs, both known and novel. Chronic myelogenous leukemia (CML) is a form of myeloproliferative disorder that is more common in adults and affects a number people throughout the world. Identification of suitable diagnostic and prognostic markers based on miRNAs would help in treatment of this disease.

Here next generation sequencing of small RNAs derived from CML patients, CML cell line K562 and normal individuals have been used to generate miRNA profiles using a modified computation pipeline that includes different normalization procedures and isomiR information. The sRNA profiles generated revealed lower relative miRNA levels in the CML patients (56%) versus normal individuals (72%). A comparison of three well known normalization techniques was done to indicate the effectiveness of Quantile Normalization over other methods in identifying differentially expressed genes. In-depth analysis of the isomiR profiles of all samples indicated that the most abundant isomiR sequence of about 60% miRNAs, did not match the reference miRNA sequence as entered in the miRBAse. Our analysis showed 34 miRNAs that were differentially expressed (15 up regulated and 19 down regulated)) between the cancer and normal cells. Downregulation of upto 8 members of a mir-379/656 cluster located on 14q32.31 in CML patients indicates its importance in CML disease. Comparison of the miRnome of the CML cell line vs patient samples also revealed a set of differentially expressed miRNAs. IsoMir expression profiles also suggested that there may be differential regulation in processing between the two types of cells. This was further confirmed by our finding regarding different levels of 3p and 5p variants in these cells. Single Nucleotide Variations (SNV's) in miRNAs were identified and analysis suggested that some of these may have altered target binding properties. Finally, a total of 50 novel miRNA sequences were identified. Identification of multiple variants add a further dimension to microRNAome pattern and all these can be useful in recognizing specific biomarkers for disease state.




 

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