title: Gene expression and splicing alterations analyzed by high throughput RNA sequencing of chronic lymphocytic leukemia specimens.
abstract: BACKGROUND
  To determine differentially expressed and spliced RNA transcripts in chronic lymphocytic leukemia specimens a high throughput RNA-sequencing (HTS RNA-seq) analysis was performed.
  
  
  METHODS
  Ten CLL specimens and five normal peripheral blood CD19+ B cells were analyzed by HTS RNA-seq. The library preparation was performed with Illumina TrueSeq RNA kit and analyzed by Illumina HiSeq 2000 sequencing system.
  
  
  RESULTS
  An average of 48.5 million reads for B cells, and 50.6 million reads for CLL specimens were obtained with 10396 and 10448 assembled transcripts for normal B cells and primary CLL specimens respectively. With the Cuffdiff analysis, 2091 differentially expressed genes (DEG) between B cells and CLL specimens based on FPKM (fragments per kilobase of transcript per million reads and false discovery rate, FDR q < 0.05, fold change >2) were identified. Expression of selected DEGs (n = 32) with up regulated and down regulated expression in CLL from RNA-seq data were also analyzed by qRT-PCR in a test cohort of CLL specimens. Even though there was a variation in fold expression of DEG genes between RNA-seq and qRT-PCR; more than 90 % of analyzed genes were validated by qRT-PCR analysis. Analysis of RNA-seq data for splicing alterations in CLL and B cells was performed by Multivariate Analysis of Transcript Splicing (MATS analysis). Skipped exon was the most frequent splicing alteration in CLL specimens with 128 significant events (P-value <0.05, minimum inclusion level difference >0.1).
  
  
  CONCLUSIONS
  The RNA-seq analysis of CLL specimens identifies novel DEG and alternatively spliced genes that are potential prognostic markers and therapeutic targets. High level of validation by qRT-PCR for a number of DEG genes supports the accuracy of this analysis. Global comparison of transcriptomes of B cells, IGVH non-mutated CLL (U-CLL) and mutated CLL specimens (M-CLL) with multidimensional scaling analysis was able to segregate CLL and B cell transcriptomes but the M-CLL and U-CLL transcriptomes were indistinguishable. The analysis of HTS RNA-seq data to identify alternative splicing events and other genetic abnormalities specific to CLL is an added advantage of RNA-seq that is not feasible with other genome wide analysis.
authors.affiliation: Division of Hematology-Oncology, UCLA-VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA. ericliaowei@gmail.com.
authors.forename: Wei
authors.initials: W
authors.lastname: Liao
authors.affiliation: Division of Hematology-Oncology, UCLA-VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA. gwenrobyn@yahoo.com.
authors.forename: Gwen
authors.initials: G
authors.lastname: Jordaan
authors.affiliation: Department of Pathology, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA. Phillipp.Nham@va.gov.
authors.forename: Phillipp
authors.initials: P
authors.lastname: Nham
authors.affiliation: Department of Pathology, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA. Ryan.Phan@va.gov.
authors.forename: Ryan T
authors.initials: RT
authors.lastname: Phan
authors.affiliation: Department of Molecular, Cell and Developmental Biology, UCLA, Los Angeles, CA, USA. matteop@mcdb.ucla.edu.
authors.forename: Matteo
authors.initials: M
authors.lastname: Pelegrini
authors.affiliation: Division of Hematology-Oncology, UCLA-VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA. sasharma@mednet.ucla.edu.|UCLA West Los Angeles VA Medical Center, 11301 Wilshire Blvd, Bldg 304, Rm E1-115, Los Angeles, CA, 90073, USA. sasharma@mednet.ucla.edu.
authors.forename: Sanjai
authors.initials: S
authors.lastname: Sharma
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D017398:Alternative Splicing / Q000235:genetics*; D001402:B-Lymphocytes / Q000378:metabolism / Q000473:pathology; D005091:Exons / Q000235:genetics; D005260:Female; D020869:Gene Expression Profiling; D015973:Gene Expression Regulation, Leukemic; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D015451:Leukemia, Lymphocytic, Chronic, B-Cell / Q000235:genetics* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D012326:RNA Splicing / Q000235:genetics*; D017423:Sequence Analysis, RNA; D059467:Transcriptome / Q000235:genetics