Immune homeostasis is dependent on tight control over the size of a population of regulatory T (T reg ) cells capable of suppressing over-exuberant immune responses. The T reg cell subset is comprised of cells that commit to the T reg lineage by upregulating the transcription factor Foxp3 either in the thymus (tT reg ) or in the periphery (iT reg ) 1,2 . Considering a central role for Foxp3 in T reg cell differentiation and function 3,4 , we proposed that conserved non-coding DNA sequence (CNS) elements at the Foxp3 locus encode information defining the size, composition and stability of the T reg cell population. Here we describe the function of three Foxp3 CNS elements (CNS1-3) in T reg cell fate determination in mice. The pioneer element CNS3, which acts to potently increase the frequency of T reg cells generated in the thymus and the periphery, binds c-Rel in in vitro assays. In contrast, CNS1, which contains a TGF-β-NFAT response element, is superfluous for tT reg cell differentiation, but has a prominent role in iT reg cell generation in gut-associated lymphoid tissues. CNS2, although dispensable for Foxp3 induction, is required for Foxp3 expression in the progeny of dividing T reg cells. Foxp3 binds to CNS2 in a Cbf-β-Runx1 and CpG DNA demethylationdependent manner, suggesting that Foxp3 recruitment to this 'cellular memory module' facilitates the heritable maintenance of the active state of the Foxp3 locus and, therefore, T reg lineage stability.Together, our studies demonstrate that the composition, size and maintenance of the T reg cell population are controlled by Foxp3 CNS elements engaged in response to distinct cell-extrinsic orintrinsic cues.To determine cis-elements that are potentially involved in the control of T reg cell fate, we first examined permissive (mono-methylated histone H3 at Lys4 (H3K4me1), di-methylated H3K4 (H3K4me2), H3K4me3, H3K36me3, and acetylated H3K9/14 (H3K9/14Ac)) and nonpermissive (H3K9me2, H3K9me3 and H3K27me3) modifications of histone H3 bound to three Foxp3 CNS elements (CNS1-3; Fig. 1a) in CD4 + CD25 − Foxp3 − naive T cells (T N ),

miRDeepFinder is a software package developed to identify and functionally analyze plant microRNAs (miRNAs) and their targets from small RNA datasets obtained from deep sequencing. The functions available in miRDeepFinder include pre-processing of raw data, identifying conserved miRNAs, mining and classifying novel miRNAs, miRNA expression profiling, predicting miRNA targets, and gene pathway and gene network analysis involving miRNAs. The fundamental design of miRDeepFinder is based on miRNA biogenesis, miRNA-mediated gene regulation and target recognition, such as perfect or near perfect hairpin structures, different read abundances of miRNA and miRNA*, and targeting patterns of plant miRNAs. To test the accuracy and robustness of miRDeepFinder, we analyzed a small RNA deep sequencing dataset of Arabidopsis thaliana published in the GEO database of NCBI. Our test retrieved 128 of 131 (97.7%) known miRNAs that have a more than 3 read count in Arabidopsis. Because many known miRNAs are not associated with miRNA*s in small RNA datasets, miRDeepFinder was also designed to recover miRNA candidates without the presence of miRNA*. To mine as many miRNAs as possible, miRDeepFinder allows users to compare mature miRNAs and their miRNA*s with other small RNA datasets from the same species. Cleaveland software package was also incorporated into miRDeepFinder for miRNA target identification using degradome sequencing analysis. Using this new computational tool, we identified 13 novel miRNA candidates with miRNA*s from Arabidopsis and validated 12 of them experimentally. Interestingly, of the 12 verified novel miRNAs, a miRNA named AC1 spans the exons of two genes (UTG71C4 and UGT71C3). Both the mature AC1 miRNA and its miRNA* were also found in four other small RNA datasets. We also developed a tool, "miRNA primer designer" to design primers for any type of miRNAs. miRDeepFinder provides a powerful tool for analyzing small RNA datasets from all species, with or without the availability of genome information. miRDeepFinder and miRNA primer designer are freely available at http://www.leonxie.com/DeepFinder.php and at http://www.leonxie.com/miRNAprimerDesigner.php , respectively. A program (called RefFinder: http://www.leonxie.com/referencegene.php ) was also developed for assessing the reliable reference genes for gene expression analysis, including miRNAs.

Although androgen receptor (AR)-mediated signaling is central to prostate cancer, the ability to modulate AR signaling states is limited. Here we establish a chemical genomic approach for discovery and target prediction of modulators of cancer phenotypes, as exemplified by AR signaling. We first identify AR activation inhibitors, including a group of structurally related compounds comprising celastrol, gedunin, and derivatives. To develop an in silico approach for target pathway identification, we apply a gene expression-based analysis that classifies HSP90 inhibitors as having similar activity to celastrol and gedunin. Validating this prediction, we demonstrate that celastrol and gedunin inhibit HSP90 activity and HSP90 clients, including AR. Broadly, this work identifies new modes of HSP90 modulation through a gene expression-based strategy.