Role of ChIP-seq in the discovery of transcription factor binding sites, differential gene regulation mechanism, epigenetic marks and beyond

Many biologically significant processes, such as cell differentiation and cell cycle progression, gene transcription and DNA replication, chromosome stability and epigenetic silencing etc. depend on the crucial interactions between cellular proteins and DNA. Chromatin immunoprecipitation (ChIP) is an important experimental technique for studying interactions between specific proteins and DNA in the cell and determining their localization on a specific genomic locus. In recent years, the combination of ChIP with second generation DNA-sequencing technology (ChIP-seq) allows precise genomic functional assay. This review addresses the important applications of ChIP-seq with an emphasis on its role in genome-wide mapping of transcription factor binding sites, the revelation of underlying molecular mechanisms of differential gene regulation that are governed by specific transcription factors, and the identification of epigenetic marks. Furthermore, we also describe the ChIP-seq data analysis workflow and a perspective for the exciting potential advancement of ChIP-seq technology in the future

Using gene co-expression network analysis to predict biomarkers for chronic lymphocytic leukemia

<p>Abstract</p> <p>Background</p> <p>Chronic lymphocytic leukemia (CLL) is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Immunoglobin heavy chain variable region (IgV_H) mutational status was found to be associated with patient survival outcome, and biomarkers linked to the IgV_H status has been a focus in the CLL prognosis research field. However, biomarkers highly correlated with IgV_H mutational status which can accurately predict the survival outcome are yet to be discovered.</p> <p>Results</p> <p>In this paper, we investigate the use of gene co-expression network analysis to identify potential biomarkers for CLL. Specifically we focused on the co-expression network involving ZAP70, a well characterized biomarker for CLL. We selected 23 microarray datasets corresponding to multiple types of cancer from the Gene Expression Omnibus (GEO) and used the frequent network mining algorithm CODENSE to identify highly connected gene co-expression networks spanning the entire genome, then evaluated the genes in the co-expression network in which ZAP70 is involved. We then applied a set of feature selection methods to further select genes which are capable of predicting IgV_H mutation status from the ZAP70 co-expression network.</p> <p>Conclusions</p> <p>We have identified a set of genes that are potential CLL prognostic biomarkers IL2RB, CD8A, CD247, LAG3 and KLRK1, which can predict CLL patient IgV_H mutational status with high accuracies. Their prognostic capabilities were cross-validated by applying these biomarker candidates to classify patients into different outcome groups using a CLL microarray datasets with clinical information.</p

Effects of DNA topoisomerase IIα splice variants on acquired drug resistance

DNA topoisomerase IIα (170 kDa, TOP2α/170) induces transient DNA double-strand breaks in proliferating cells to resolve DNA topological entanglements during chromosome condensation, replication, and segregation. Therefore, TOP2α/170 is a prominent target for anticancer drugs whose clinical efficacy is often compromised due to chemoresistance. Although many resistance mechanisms have been defined, acquired resistance of human cancer cell lines to TOP2α interfacial inhibitors/poisons is frequently associated with a reduction of Top2α/170 expression levels. Recent studies by our laboratory, in conjunction with earlier findings by other investigators, support the hypothesis that a major mechanism of acquired resistance to TOP2α-targeted drugs is due to alternative RNA processing/splicing. Specifically, several TOP2α mRNA splice variants have been reported which retain introns and are translated into truncated TOP2α isoforms lacking nuclear localization sequences and subsequent dysregulated nuclear-cytoplasmic disposition. In addition, intron retention can lead to truncated isoforms that lack both nuclear localization sequences and the active site tyrosine (Tyr805) necessary for forming enzyme-DNA covalent complexes and inducing DNA damage in the presence of TOP2α-targeted drugs. Ultimately, these truncated TOP2α isoforms result in decreased drug activity against TOP2α in the nucleus and manifest drug resistance. Therefore, the complete characterization of the mechanism(s) regulating the alternative RNA processing of TOP2α pre-mRNA may result in new strategies to circumvent acquired drug resistance. Additionally, novel TOP2α splice variants and truncated TOP2α isoforms may be useful as biomarkers for drug resistance, prognosis, and/or direct future TOP2α-targeted therapies

Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing

The genome-wide discoveries such as detection of copy number alterations (CNA) from high-throughput whole-genome sequencing data enabled new developments in personalized medicine. The CNAs have been reported to be associated with various diseases and cancers including acute myeloid leukemia. However, there are multiple challenges to the use of current CNA detection tools that lead to high false-positive rates and thus impede widespread use of such tools in cancer research. In this paper, we discuss these issues and propose possible solutions. First, since the entire genome cannot be mapped due to some regions lacking sequence uniqueness, current methods cannot be appropriately adjusted to handle these regions in the analyses. Thus, detection of medium-sized CNAs is also being directly affected by these mappability problems. The requirement for matching control samples is also an important limitation because acquiring matching controls might not be possible or might not be cost efficient. Here we present an approach that addresses these issues and detects medium-sized CNAs in cancer genomes by (1) masking unmappable regions during the initial CNA detection phase, (2) using pool of a few normal samples as control, and (3) employing median filtering to adjust CNA ratios to its surrounding coverage and eliminate false positives

Down-regulation of homeobox genes MEIS1 and HOXA in MLL-rearranged acute leukemia impairs engraftment and reduces proliferation

Rearrangements of the MLL (ALL1) gene are very common in acute infant and therapy-associated leukemias. The rearrangements underlie the generation of MLL fusion proteins acting as potent oncogenes. Several most consistently up-regulated targets of MLL fusions, MEIS1, HOXA7, HOXA9, and HOXA10 are functionally related and have been implicated in other types of leukemias. Each of the four genes was knocked down separately in the human precursor B-cell leukemic line RS4;11 expressing MLL-AF4. The mutant and control cells were compared for engraftment in NOD/SCID mice. Engraftment of all mutants into the bone marrow (BM) was impaired. Although homing was similar, colonization by the knockdown cells was slowed. Initially, both types of cells were confined to the trabecular area; this was followed by a rapid spread of the WT cells to the compact bone area, contrasted with a significantly slower process for the mutants. In vitro and in vivo BrdU incorporation experiments indicated reduced proliferation of the mutant cells. In addition, the CXCR4/SDF-1 axis was hampered, as evidenced by reduced migration toward an SDF-1 gradient and loss of SDF-1–augmented proliferation in culture. The very similar phenotype shared by all mutant lines implies that all four genes are involved and required for expansion of MLL-AF4 associated leukemic cells in mice, and down-regulation of any of them is not compensated by the others