Whole-transcriptome RNAseq analysis from minute amount of total RNA. etc

1.	Whole-transcriptome RNAseq analysis from minute amount of total RNA.
	Tariq MA, Kim HJ, Jejelowo O, Pourmand N.
	Nucleic Acids Res. 2011 Oct 1;39(18):e120. Epub 2011 Jul 6.
	PMID: 21737426 [PubMed - in process] Free Article Abstract RNA sequencing approaches to transcriptome analysis require a large amount of input total RNA to yield sufficient mRNA using either poly-A selection or depletion of rRNA. This feature makes it difficult to miniaturize transcriptome analysis for greater efficiency. To address this challenge, we devised and validated a simple procedure for the preparation of whole-transcriptome cDNA libraries from a minute amount (500 pg) of total RNA. We compared a single-sample library prepared by this Ovation® RNA-Seq system with two available methods of mRNA enrichment (TruSeq™ poly-A enrichment and RiboMinus™ rRNA depletion). Using the Ovation® preparation method for a set of eight mouse tissue samples, the RNA sequencing data obtained from two different next-generation sequencing platforms (SOLiD and Illumina Genome Analyzer IIx) yielded negligible rRNA reads (<3.5%) while retaining transcriptome sequencing fidelity. We further validated the Ovation® amplification technique by examining the resulting library complexity, reproducibility, evenness of transcript coverage, 5' and 3' bias and platform-specific biases. Notably, in this side-by-side comparison, SOLiD sequencing chemistry is biased toward higher GC content of transcriptome and Illumina Genome analyzer IIx is biased away from neutral to lower GC content of the transcriptomics regions. PMID: 21737426 [PubMed - in process] PMCID: PMC3185437 Free full text
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2.	Next-generation insights into regulatory T cells: expression profiling and FoxP3 occupancy in Human.
	Birzele F, Fauti T, Stahl H, Lenter MC, Simon E, Knebel D, Weith A, Hildebrandt T, Mennerich D.
	Nucleic Acids Res. 2011 Oct 1;39(18):7946-60. Epub 2011 Jul 4.
	PMID: 21729870 [PubMed - in process] Free Article Abstract Regulatory T-cells (Treg) play an essential role in the negative regulation of immune answers by developing an attenuated cytokine response that allows suppressing proliferation and effector function of T-cells (CD4(+) Th). The transcription factor FoxP3 is responsible for the regulation of many genes involved in the Treg gene signature. Its ablation leads to severe immune deficiencies in human and mice. Recent developments in sequencing technologies have revolutionized the possibilities to gain insights into transcription factor binding by ChiP-seq and into transcriptome analysis by mRNA-seq. We combine FoxP3 ChiP-seq and mRNA-seq in order to understand the transcriptional differences between primary human CD4(+) T helper and regulatory T-cells, as well as to study the role of FoxP3 in generating those differences. We show, that mRNA-seq allows analyzing the transcriptomal landscape of T-cells including the expression of specific splice variants at much greater depth than previous approaches, whereas 50% of transcriptional regulation events have not been described before by using diverse array technologies. We discovered splicing patterns like the expression of a kinase-dead isoform of IRAK1 upon T-cell activation. The immunoproteasome is up-regulated in both Treg and CD4(+) Th cells upon activation, whereas the 'standard' proteasome is up-regulated in Tregs only upon activation.
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