Analyzing the massive and heterogenous datasets from genome-wide chromatin immunoprecipitation (ChIP) datasets presents several computational and statistical challenges. Ji et al. present a software suite that integrates all steps in ChIP-chip and ChIP-seq data analyses and illustrate the use of these tools by comparing the ability of the two platforms to identify transcription factor binding sites. We present CisGenome, a software system for analyzing genome-wide chromatin immunoprecipitation (ChIP) data. CisGenome is designed to meet all basic needs of ChIP data analyses, including visualization, data normalization, peak detection, false discovery rate computation, gene-peak association, and sequence and motif analysis. In addition to implementing previously published ChIP–microarray (ChIP-chip) analysis methods, the software contains statistical methods designed specifically for ChlP sequencing (ChIP-seq) data obtained by coupling ChIP with massively parallel sequencing. The modular design of CisGenome enables it to support interactive analyses through a graphic user interface as well as customized batch-mode computation for advanced data mining. A built-in browser allows visualization of array images, signals, gene structure, conservation, and DNA sequence and motif information. We demonstrate the use of these tools by a comparative analysis of ChIP-chip and ChIP-seq data for the transcription factor NRSF/REST, a study of ChIP-seq analysis with or without a negative control sample, and an analysis of a new motif in Nanog- and Sox2-binding regions.

A broad set of sufficient conditions consisting of systems of linear partial differential equations is presented which guarantees that the Wronskian determinant solves the Korteweg-de Vries equation in the bilinear form. A systematical analysis is made for solving the resultant linear systems of second-order and third-order partial differential equations, along with solution formulas for their representative systems. The key technique is to apply variation of parameters in solving the involved non-homogeneous partial differential equations. The obtained solution formulas provide us with a comprehensive approach to construct the existing solutions and many new solutions including rational solutions, solitons, positons, negatons, breathers, complexitons and interaction solutions of the Korteweg-de Vries equation.

X chromosome inactivation (XCI) silences most genes on one X chromosome in female mammals, but some genes escape XCI. To identify escape genes in vivo and to explore molecular mechanisms that regulate this process we analyzed the allele-specific expression and chromatin structure of X-linked genes in mouse tissues and cells with skewed XCI and distinguishable alleles based on single nucleotide polymorphisms. Using a binomial model to assess allelic expression, we demonstrate a continuum between complete silencing and expression from the inactive X (Xi). The validity of the RNA-seq approach was verified using RT-PCR with species-specific primers or Sanger sequencing. Both common escape genes and genes with significant differences in XCI status between tissues were identified. Such genes may be candidates for tissue-specific sex differences. Overall, few genes (3–7%) escape XCI in any of the mouse tissues examined, suggesting stringent silencing and escape controls. In contrast, an in vitro system represented by the embryonic-kidney-derived Patski cell line showed a higher density of escape genes (21%), representing both kidney-specific escape genes and cell-line specific escape genes. Allele-specific RNA polymerase II occupancy and DNase I hypersensitivity at the promoter of genes on the Xi correlated well with levels of escape, consistent with an open chromatin structure at escape genes. Allele-specific CTCF binding on the Xi clustered at escape genes and was denser in brain compared to the Patski cell line, possibly contributing to a more compartmentalized structure of the Xi and fewer escape genes in brain compared to the cell line where larger domains of escape were observed. X inactivation is a female-specific phenomenon that occurs during early development and results in the silencing of one X chromosome in female mammals. However, some genes escape inactivation and remain expressed from both X chromosomes. To date, the identity of escape genes and the molecular mechanisms of this process are still being explored. Here, we use a new binomial model combined with a mouse system with identifiable alleles and skewed X inactivation to identify and further define the chromatin landscape of escape genes in vivo. We find that some escape genes are common to multiple tissues while others are tissue-specific. We also show that expression levels of alleles on the inactive X correlate with factors associated with open chromatin such as RNA Polymerase II and DNase I hypersensitive sites. Additionally, escape genes co-localized with CTCF binding clusters on the Xi, suggesting a role for CTCF binding in delineating regions of escape and inactivation. Our findings represent the first comprehensive analysis of escape in vivo. Identification of tissue-specific escape genes could lead to a better understanding of the underlying causes of sex-linked disorders such as X-linked intellectual disability and Turner syndrome.

Telomerase serves a critical role in stem cell function and tissue homeostasis. This role depends on its ability to synthesize telomere repeats in a manner dependent on the reverse transcriptase (RT) function of its protein component telomerase RT (TERT), as well as on a novel pathway whose mechanism is poorly understood. Here, we use a TERT mutant lacking RT function (TERT^ci) to study the mechanism of TERT action in mammalian skin, an ideal tissue for studying progenitor cell biology. We show that TERT^ci retains the full activities of wild-type TERT in enhancing keratinocyte proliferation in skin and in activating resting hair follicle stem cells, which triggers initiation of a new hair follicle growth phase and promotes hair synthesis. To understand the nature of this RT-independent function for TERT, we studied the genome-wide transcriptional response to acute changes in TERT levels in mouse skin. We find that TERT facilitates activation of progenitor cells in the skin and hair follicle by triggering a rapid change in gene expression that significantly overlaps the program controlling natural hair follicle cycling in wild-type mice. Statistical comparisons to other microarray gene sets using pattern-matching algorithms revealed that the TERT transcriptional response strongly resembles those mediated by Myc and Wnt, two proteins intimately associated with stem cell function and cancer. These data show that TERT controls tissue progenitor cells via transcriptional regulation of a developmental program converging on the Myc and Wnt pathways. Stem cells and progenitor cells within a tissue are required to maintain tissue homeostasis and to repair tissues after injury by giving rise to differentiated daughter cells. Many progenitor cells express telomerase, a reverse transcriptase enzyme that adds DNA repeats to telomeres, the protective structures that cap chromosome ends. Telomere addition by telomerase is important for normal progenitor cell function and is crucial for enabling cancer cells to divide an unlimited number of times. In addition to its telomere-lengthening function, telomerase reverse transcriptase (TERT) can directly activate quiescent epidermal stem cells. However, the mechanism underlying this novel function for TERT is still not understood. In this study, we demonstrate that the catalytic activity of TERT is dispensable for its ability to activate tissue progenitor cells in vivo. Furthermore, using gene microarrays, we show that TERT controls a developmental program that overlaps the natural transcriptional program of hair follicle cycling in mouse skin. Using pattern-matching algorithms, we find that the TERT-controlled genetic program significantly resembles programs regulated by Myc and Wnt, two pathways critical for stem cell function and tumorigenesis. This paper reveals critical new insights into novel mechanisms of non-telomerase functions of TERT, identifying TERT as a developmental regulator linked to control of transcriptional responses.