Inflammation is a powerful response of the immune system against invading pathogens, and must be cancelled when unneeded or otherwise death inevitably follows. In macrophages, the anti-inflammatory response (AIR) is driven by STAT3 upon IL-10 signaling. The role of STAT3 is to stimulate the expression of specific genes that in-turn suppress the transcription of proinflammatory genes. Here we describe a systematic approach to identify the elusive STAT3-controlled effectors of the AIR. In vivo STAT3-binding sites were identified by ChIP-seq, coupled to expression analysis by RNA-seq, both in resting and IL-10-treated peritoneal macrophages. We report the genomic targets of STAT3 and show that STAT3's transcriptional program during the AIR is highly specific to IL-10-stimulated macrophages, that STAT3 is a positive transcriptional regulator, and we predict severalputative AIR factors that merit further investigation. This is the first in-depth study of the AIR by next-generation sequencing and provides an unprecedented degree of detail into this fundamental physiologic response.

Transcripts in all eukaryotes are characterized by the 5'-end specific cap structure in mRNAs. Cap Analysis Gene Expression or CAGE makes use of these caps to specifically obtain cDNA fragments from the 5'-end of RNA and sequences those at high throughput for transcript identification and genome-wide mapping of transcription start sites for coding and noncoding genes. Here, we provide an improved version of our nanoCAGE protocol that has been developed for preparing CAGE libraries from as little as 50 ng of total RNA within three standard working days. Key steps in library preparation have been improved over our previously published protocol to obtain libraries having a good 5'-end selection and a more equal size distribution for higher sequencing efficiency on Illumina MiSeq and HiSeq sequencers. We recommend nanoCAGE as the method of choice for transcriptome profiling projects even from limited amounts of RNA, and as the best approach for genome-wide mapping of transcription start sites within promoter regions.

In the present study, we evaluated the performance of different protocols for the hepatic differentiation of human-induced pluripotent stem cells (hiPSCs) in microfluidic biochips. Strategies for complete and partial on-chip differentiation were

Despite the routine application of RNA-seq technology to profile cellular transcriptomes and report novel splice variants, the identification and validation of new transcripts remain underexplored. We prepared two RNA-seq libraries from resting and T cell receptor-stimulated mouse CD4(+) T cells. Transcripts unknown to Ensembl represent as much as 5% of the assembled transcripts and are robustly expressed but do not show the same degree of evolutionary conservation or exon distribution of known transcripts, or of novel splice isoforms. Here we present a straightforward and generally applicable computational/experimental workflow that we apply to characterise and experimentally validate 23 mouse transcripts from the RNA-seq libraries that were uncharacterised by Ensembl. Of these, 7 are not supported by any transcript database and therefore are likely to encode new messages. Furthermore, we also report the fast up-regulation of important regulatory molecules only 4 h post-stimulation of the T cell receptor, which calls for a more detailed investigation into early CD4(+) T cell activation mechanisms.