Endothelial Regeneration of Large Vessels Is a Biphasic Process Driven by Local Cells with Distinct Proliferative Capacities.

The cellular and mechanistic bases underlying endothelial regeneration of adult large vessels have proven challenging to study. Using a reproducible in vivo aortic endothelial injury model, we characterized cellular dynamics underlying the regenerative process through a combination of multi-color lineage tracing, parabiosis, and single-cell transcriptomics. We found that regeneration is a biphasic process driven by distinct populations arising from differentiated endothelial cells. The majority of cells immediately adjacent to the injury site re-enter the cell cycle during the initial damage response, with a second phase driven by a highly proliferative subpopulation. Endothelial regeneration requires activation of stress response genes including Atf3, and aged aortas compromised in their reparative capacity express less Atf3. Deletion of Atf3 reduced endothelial proliferation and compromised the regeneration. These findings provide important insights into cellular dynamics and mechanisms that drive responses to large vessel injury.

Gene expression and splicing alterations analyzed by high throughput RNA sequencing of chronic lymphocytic leukemia specimens.

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). CONCLUSION: 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.

Induced pluripotent stem cells and embryonic stem cells are distinguished by gene expression signatures.

Induced pluripotent stem cells (iPSCs) outwardly appear to be indistinguishable from embryonic stem cells (ESCs). A study of gene expression profiles of mouse and human ESCs and iPSCs suggests that, while iPSCs are quite similar to their embryonic counterparts, a recurrent gene expression signature appears in iPSCs regardless of their origin or the method by which they were generated. Upon extended culture, hiPSCs adopt a gene expression profile more similar to hESCs; however, they still retain a gene expression signature unique from hESCs that extends to miRNA expression. Genome-wide data suggested that the iPSC signature gene expression differences are due to differential promoter binding by the reprogramming factors. High-resolution array profiling demonstrated that there is no common specific subkaryotypic alteration that is required for reprogramming and that reprogramming does not lead to genomic instability. Together, these data suggest that iPSCs should be considered a unique subtype of pluripotent cell.