Open Access Highly Accessed Research article

Characterization of human plasma-derived exosomal RNAs by deep sequencing

Xiaoyi Huang1, Tiezheng Yuan1, Michael Tschannen2, Zhifu Sun3, Howard Jacob2, Meijun Du1, Meihua Liang4, Rachel L Dittmar1, Yong Liu5, Mingyu Liang5, Manish Kohli6, Stephen N Thibodeau7, Lisa Boardman6 and Liang Wang1*

Author Affiliations

1 Department of Pathology and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, 53226, USA

2 Human Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, WI, 53226, USA

3 Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA

4 Department of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China

5 Department of Physiology, Medical College of Wisconsi, Milwaukee, WI, 53226, USA

6 Department of Oncology, Mayo Clinic, Rochester, MN, 55905, USA

7 Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA

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BMC Genomics 2013, 14:319  doi:10.1186/1471-2164-14-319

Published: 10 May 2013

Additional files

Additional file 1:

Percentage of read counts with different insert sizes among the total mappable reads. The NEBNext multiplex small RNA library preparation kit (NEB) generated more sequences with 21–23 nt inserts than did the other two kits that were tested. Overall represents the averages of the three different kits that were tested.

Format: TIFF Size: 1.5MB Download file

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Additional file 2:

Read counts of the miRNAs detected in the 14 libraries (normalized to read number per million mappable miRNA seqeuences).

Format: XLSX Size: 62KB Download file

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Additional file 3:

Top 20 RNAs in other RNA species (normalized to read number per million all mappable RNA seqeuences).

Format: XLSX Size: 28KB Download file

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Additional file 4:

Putative miRNAs predicted by miRDeep2.

Format: XLSX Size: 24KB Download file

Open Data