RT Journal Article
SR Electronic
T1 Dumpster diving in RNA-sequencing to find the source of every last read
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 053041
DO 10.1101/053041
A1 Mangul, Serghei
A1 Yang, Harry Taegyun
A1 Strauli, Nicolas
A1 Gruhl, Franziska
A1 Daley, Timothy
A1 Christenson, Stephanie
A1 Wesolowska-Andersen, Agata
A1 Spreafico, Roberto
A1 Rios, Cydney
A1 Eng, Celeste
A1 Smith, Andrew D.
A1 Hernandez, Ryan D.
A1 Ophoff, Roel A.
A1 Santana, Jose Rodriguez
A1 Woodruff, Prescott G.
A1 Burchard, Esteban
A1 Seibold, Max A.
A1 Shifman, Sagiv
A1 Eskin, Eleazar
A1 Zaitlen, Noah
YR 2016
UL http://biorxiv.org/content/early/2016/05/13/053041.abstract
AB High throughput RNA sequencing technologies have provided invaluable research opportunities across distinct scientific domains by producing quantitative readouts of the transcriptional activity of both entire cellular populations and single cells. The majority of RNA-Seq analyses begin by mapping each experimentally produced sequence (i.e., read) to a set of annotated reference sequences for the organism of interest. For both biological and technical reasons, a significant fraction of reads remains unmapped. In this work we develop a read origin protocol (ROP) aimed at discovering the source of all reads, originated from complex RNA molecules, recombinant antibodies and microbial communities. Our approach can account for 98.8% of all reads across poly(A) and ribo-depletion protocols. Furthermore, using ROP we show that immune profiles of asthmatic individuals are significantly different from the control individuals with decreased average per sample T-cell/B-cell receptor diversity and that immune diversity is inversely correlated with microbial load. This demonstrates the potential of ROP to exploit unmapped reads to better understand the functional mechanisms underlying the connection between immune system, microbiome, human gene expression, and disease etiology.The ROP pipeline is freely available at https://sergheimangul.wordpress.com/rop/