Epigenetic Modulation of miR-122 Facilitates Human Embryonic Stem Cell Self-Renewal and Hepatocellular Carcinoma Proliferation

The self-renewal capacity ascribed to hESCs is paralleled in cancer cell proliferation, suggesting that a common network of genes may facilitate the promotion of these traits. However, the molecular mechanisms that are involved in regulating the silencing of these genes as stem cells differentiate into quiescent cellular lineages remain poorly understood. Here, we show that a differentiated cell specific miR-122 exemplifies this regulatory attribute by suppressing the translation of a gene, Pkm2, which is commonly enriched in hESCs and liver cancer cells (HCCs), and facilitates self-renewal and proliferation. Through a series of gene expression analysis, we show that miR-122 expression is highly elevated in quiescent human primary hepatocytes (hPHs) but lost or attenuated in hESCs and HCCs, while an opposing expression pattern is observed for Pkm2. Depleting hESCs and HCCs of Pkm2, or overexpressing miR-122, leads to a common deficiency in self-renewal and proliferation. Likewise, during the differentiation process of hESCs into hepatocytes, a reciprocal expression pattern is observed between miR-122 and Pkm2. An examination of the genomic region upstream of miR-122 uncovered hyper-methylation in hESCs and HCCs, while the same region is de-methylated and occupied by a transcription initiating protein, RNA polymerase II (RNAPII), in hPHs. These findings indicate that one possible mechanism by which hESC self-renewal is modulated in quiescent hepatic derivatives of hESCs is through the regulatory activity of a differentiated cell-specific miR-122, and that a failure to properly turn “on” this miRNA is observed in uncontrollably proliferating HCCs

Sole-Search: an integrated analysis program for peak detection and functional annotation using ChIP-seq data

Next-generation sequencing is revolutionizing the identification of transcription factor binding sites throughout the human genome. However, the bioinformatics analysis of large datasets collected using chromatin immunoprecipitation and high-throughput sequencing is often a roadblock that impedes researchers in their attempts to gain biological insights from their experiments. We have developed integrated peak-calling and analysis software (Sole-Search) which is available through a user-friendly interface and (i) converts raw data into a format for visualization on a genome browser, (ii) outputs ranked peak locations using a statistically based method that overcomes the significant problem of false positives, (iii) identifies the gene nearest to each peak, (iv) classifies the location of each peak relative to gene structure, (v) provides information such as the number of binding sites per chromosome and per gene and (vi) allows the user to determine overlap between two different experiments. In addition, the program performs an analysis of amplified and deleted regions of the input genome. This software is web-based and automated, allowing easy and immediate access to all investigators. We demonstrate the utility of our software by collecting, analyzing and comparing ChIP-seq data for six different human transcription factors/cell line combinations

Characterization of the Contradictory Chromatin Signatures at the 3′ Exons of Zinc Finger Genes

The H3K9me3 histone modification is often found at promoter regions, where it functions to repress transcription. However, we have previously shown that 3′ exons of zinc finger genes (ZNFs) are marked by high levels of H3K9me3. We have now further investigated this unusual location for H3K9me3 in ZNF genes. Neither bioinformatic nor experimental approaches support the hypothesis that the 3′ exons of ZNFs are promoters. We further characterized the histone modifications at the 3′ ZNF exons and found that these regions also contain H3K36me3, a mark of transcriptional elongation. A genome-wide analysis of ChIP-seq data revealed that ZNFs constitute the majority of genes that have high levels of both H3K9me3 and H3K36me3. These results suggested the possibility that the ZNF genes may be imprinted, with one allele transcribed and one allele repressed. To test the hypothesis that the contradictory modifications are due to imprinting, we used a SNP analysis of RNA-seq data to demonstrate that both alleles of certain ZNF genes having H3K9me3 and H3K36me3 are transcribed. We next analyzed isolated ZNF 3′ exons using stably integrated episomes. We found that although the H3K36me3 mark was lost when the 3′ ZNF exon was removed from its natural genomic location, the isolated ZNF 3′ exons retained the H3K9me3 mark. Thus, the H3K9me3 mark at ZNF 3′ exons does not impede transcription and it is regulated independently of the H3K36me3 mark. Finally, we demonstrate a strong relationship between the number of tandemly repeated domains in the 3′ exons and the H3K9me3 mark. We suggest that the H3K9me3 at ZNF 3′ exons may function to protect the genome from inappropriate recombination rather than to regulate transcription

ZNF274 Recruits the Histone Methyltransferase SETDB1 to the 3′ Ends of ZNF Genes

Only a small percentage of human transcription factors (e.g. those associated with a specific differentiation program) are expressed in a given cell type. Thus, cell fate is mainly determined by cell type-specific silencing of transcription factors that drive different cellular lineages. Several histone modifications have been associated with gene silencing, including H3K27me3 and H3K9me3. We have previously shown that genes for the two largest classes of mammalian transcription factors are marked by distinct histone modifications; homeobox genes are marked by H3K27me3 and zinc finger genes are marked by H3K9me3. Several histone methyltransferases (e.g. G9a and SETDB1) may be involved in mediating the H3K9me3 silencing mark. We have used ChIP-chip and ChIP-seq to demonstrate that SETDB1, but not G9a, is associated with regions of the genome enriched for H3K9me3. One current model is that SETDB1 is recruited to specific genomic locations via interaction with the corepressor TRIM28 (KAP1), which is in turn recruited to the genome via interaction with zinc finger transcription factors that contain a Kruppel-associated box (KRAB) domain. However, specific KRAB-ZNFs that recruit TRIM28 (KAP1) and SETDB1 to the genome have not been identified. We now show that ZNF274 (a KRAB-ZNF that contains 5 C2H2 zinc finger domains), can interact with KAP1 both in vivo and in vitro and, using ChIP-seq, we show that ZNF274 binding sites co-localize with SETDB1, KAP1, and H3K9me3 at the 3′ ends of zinc finger genes. Knockdown of ZNF274 with siRNAs reduced the levels of KAP1 and SETDB1 recruitment to the binding sites. These studies provide the first identification of a KRAB domain-containing ZNF that is involved in recruitment of the KAP1 and SETDB1 to specific regions of the human genome

Sole-Search: an integrated analysis program for peak detection and functional annotation using ChIP-seq data.

Next-generation sequencing is revolutionizing the identification of transcription factor binding sites throughout the human genome. However, the bioinformatics analysis of large datasets collected using chromatin immunoprecipitation and high-throughput sequencing is often a roadblock that impedes researchers in their attempts to gain biological insights from their experiments. We have developed integrated peak-calling and analysis software (Sole-Search) which is available through a user-friendly interface and (i) converts raw data into a format for visualization on a genome browser, (ii) outputs ranked peak locations using a statistically based method that overcomes the significant problem of false positives, (iii) identifies the gene nearest to each peak, (iv) classifies the location of each peak relative to gene structure, (v) provides information such as the number of binding sites per chromosome and per gene and (vi) allows the user to determine overlap between two different experiments. In addition, the program performs an analysis of amplified and deleted regions of the input genome. This software is web-based and automated, allowing easy and immediate access to all investigators. We demonstrate the utility of our software by collecting, analyzing and comparing ChIP-seq data for six different human transcription factors/cell line combinations