Directional DNA methylation changes and complex intermediate states accompany lineage specificity in the adult hematopoietic compartment.

DNA methylation has been implicated as an epigenetic component of mechanisms that stabilize cell-fate decisions. Here, we have characterized the methylomes of human female hematopoietic stem/progenitor cells (HSPCs) and mature cells from the myeloid and lymphoid lineages. Hypomethylated regions (HMRs) associated with lineage-specific genes were often methylated in the opposing lineage. In HSPCs, these sites tended to show intermediate, complex patterns that resolve to uniformity upon differentiation, by increased or decreased methylation. Promoter HMRs shared across diverse cell types typically display a constitutive core that expands and contracts in a lineage-specific manner to fine-tune the expression of associated genes. Many newly identified intergenic HMRs, both constitutive and lineage specific, were enriched for factor binding sites with an implied role in genome organization and regulation of gene expression, respectively. Overall, our studies represent an important reference data set and provide insights into directional changes in DNA methylation as cells adopt terminal fates.

Riborex: fast and flexible identification of differential translation from Ribo-seq data.

MOTIVATION: Global analysis of translation regulation has recently been enabled by the development of Ribosome Profiling, or Ribo-seq, technology. This approach provides maps of ribosome activity for each expressed gene in a given biological sample. Measurements of translation efficiency are generated when Ribo-seq data is analyzed in combination with matched RNA-seq gene expression profiles. Existing computational methods for identifying genes with differential translation across samples are based on sound principles, but require users to choose between accuracy and speed. RESULTS: We present Riborex, a computational tool for mapping genome-wide differences in translation efficiency. Riborex shares a similar mathematical structure with existing methods, but has a simplified implementation. Riborex directly leverages established RNA-seq analysis frameworks for all parameter estimation, providing users with a choice among robust engines for these computations. The result is a method that is dramatically faster than available methods without sacrificing accuracy. AVAILABILITY AND IMPLEMENTATION: https://github.com/smithlabcode/riborex. CONTACT: andrewds@usc.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Musashi1 Impacts Radio-Resistance in Glioblastoma by Controlling DNA-Protein Kinase Catalytic Subunit.

The conserved RNA-binding protein Musashi1 (MSI1) has been characterized as a stem cell marker, controlling the balance between self-renewal and differentiation and as a key oncogenic factor in numerous solid tumors, including glioblastoma. To explore the potential use of MSI1 targeting in therapy, we studied MSI1 in the context of radiation sensitivity. Knockdown of MSI1 led to a decrease in cell survival and an increase in DNA damage compared to control in cells treated with ionizing radiation. We subsequently examined mechanisms of double-strand break repair and found that loss of MSI1 reduces the frequency of nonhomologous end-joining. This phenomenon could be attributed to the decreased expression of DNA-protein kinase catalytic subunit, which we have previously identified as a target of MSI1. Collectively, our results suggest a role for MSI1 in double-strand break repair and that its inhibition may enhance the effect of radiotherapy.

Leveraging cross-link modification events in CLIP-seq for motif discovery.

High-throughput protein-RNA interaction data generated by CLIP-seq has provided an unprecedented depth of access to the activities of RNA-binding proteins (RBPs), the key players in co- and post-transcriptional regulation of gene expression. Motif discovery forms part of the necessary follow-up data analysis for CLIP-seq, both to refine the exact locations of RBP binding sites, and to characterize them. The specific properties of RBP binding sites, and the CLIP-seq methods, provide additional information not usually present in the classic motif discovery problem: the binding site structure, and cross-linking induced events in reads. We show that CLIP-seq data contains clear secondary structure signals, as well as technology- and RBP-specific cross-link signals. We introduce Zagros, a motif discovery algorithm specifically designed to leverage this information and explore its impact on the quality of recovered motifs. Our results indicate that using both secondary structure and cross-link modifications can greatly improve motif discovery on CLIP-seq data. Further, the motifs we recover provide insight into the balance between sequence- and structure-specificity struck by RBP binding.

High-throughput analyses of hnRNP H1 dissects its multi-functional aspect.

hnRNPs are polyvalent RNA binding proteins that have been implicated in a range of regulatory roles including splicing, mRNA decay, translation, and miRNA metabolism. A variety of genome wide studies have taken advantage of methods like CLIP and RIP to identify the targets and binding sites of RNA binding proteins. However, due to the complex nature of RNA-binding proteins, these studies are incomplete without assays that characterize the impact of RBP binding on mRNA target expression. Here we used a suite of high-throughput approaches (RIP-Seq, iCLIP, RNA-Seq and shotgun proteomics) to provide a comprehensive view of hnRNP H1s ensemble of targets and its role in splicing, mRNA decay, and translation. The combination of RIP-Seq and iCLIP allowed us to identify a set of 1,086 high confidence target transcripts. Binding site motif analysis of these targets suggests the TGGG tetramer as a prevalent component of hnRNP H1 binding motif, with particular enrichment around intronic hnRNP H1 sites. Our analysis of the target transcripts and binding sites indicates that hnRNP H1s involvement in splicing is 2-fold: it directly affects a substantial number of splicing events, but also regulates the expression of major components of the splicing machinery and other RBPs with known roles in splicing regulation. The identified mRNA targets displayed function enrichment in MAPK signaling and ubiquitin mediated proteolysis, which might be main routes by which hnRNP H1 promotes tumorigenesis.

Molecular hierarchy of mammary differentiation yields refined markers of mammary stem cells.

The partial purification of mouse mammary gland stem cells (MaSCs) using combinatorial cell surface markers (Lin(-)CD24(+)CD29(h)CD49f(h)) has improved our understanding of their role in normal development and breast tumorigenesis. Despite the significant improvement in MaSC enrichment, there is presently no methodology that adequately isolates pure MaSCs. Seeking new markers of MaSCs, we characterized the stem-like properties and expression signature of label-retaining cells from the mammary gland of mice expressing a controllable H2b-GFP transgene. In this system, the transgene expression can be repressed in a doxycycline-dependent fashion, allowing isolation of slowly dividing cells with retained nuclear GFP signal. Here, we show that H2b-GFP(h) cells reside within the predicted MaSC compartment and display greater mammary reconstitution unit frequency compared with H2b-GFP(neg) MaSCs. According to their transcriptome profile, H2b-GFP(h) MaSCs are enriched for pathways thought to play important roles in adult stem cells. We found Cd1d, a glycoprotein expressed on the surface of antigen-presenting cells, to be highly expressed by H2b-GFP(h) MaSCs, and isolation of Cd1d(+) MaSCs further improved the mammary reconstitution unit enrichment frequency to nearly a single-cell level. Additionally, we functionally characterized a set of MaSC-enriched genes, discovering factors controlling MaSC survival. Collectively, our data provide tools for isolating a more precisely defined population of MaSCs and point to potentially critical factors for MaSC maintenance.

RNA binding protein HuR regulates the expression of ABCA1.

ABCA1 is a major regulator of cellular cholesterol efflux and plasma HDL biogenesis. Even though the transcriptional activation of ABCA1 is well established, the posttranscriptional regulation of ABCA1 expression is poorly understood. Here, we investigate the potential contribution of the RNA binding protein (RBP) human antigen R (HuR) on the posttranscriptional regulation of ABCA1 expression. RNA immunoprecipitation assays demonstrate a direct interaction between HuR and ABCA1 mRNA. We found that HuR binds to the 3' untranslated region of ABCA1 and increases ABCA1 translation, while HuR silencing reduces ABCA1 expression and cholesterol efflux to ApoA1 in human hepatic (Huh-7) and monocytic (THP-1) cells. Interestingly, cellular cholesterol levels regulate the expression, intracellular localization, and interaction between HuR and ABCA1 mRNA. Finally, we found that HuR expression was significantly increased in macrophages from human atherosclerotic plaques, suggesting an important role for this RBP in controlling macrophage cholesterol metabolism in vivo. In summary, we have identified HuR as a novel posttranscriptional regulator of ABCA1 expression and cellular cholesterol homeostasis, thereby opening new avenues for increasing cholesterol efflux from atherosclerotic foam macrophages and raising circulat-ing HDL cholesterol levels.

A profile of transcriptomic changes in the rd10 mouse model of retinitis pigmentosa.

PURPOSE: Retinitis pigmentosa (RP) is a photoreceptor disease that affects approximately 100,000 people in the United States. Treatment options are limited, and the prognosis for most patients is progressive vision loss. Unfortunately, understanding of the molecular underpinnings of RP initiation and progression is still limited. However, the development of animal models of RP, coupled with high-throughput sequencing, has provided an opportunity to study the underlying cellular and molecular changes in this disease. METHODS: Using RNA-Seq, we present the first retinal transcriptome analysis of the rd10 murine model of retinal degeneration. RESULTS: Our data confirm the loss of rod-specific transcripts and the increased relative expression of Müller-specific transcripts, emphasizing the important role of reactive gliosis and innate immune activation in RP. Moreover, we report substantial changes in relative isoform usage among neuronal differentiation and morphogenesis genes, including a marked shift to shorter transcripts. CONCLUSIONS: Our analyses implicate remodeling of the inner retina and possible Müller cell dedifferentiation.

Site identification in high-throughput RNA-protein interaction data.

MOTIVATION: Post-transcriptional and co-transcriptional regulation is a crucial link between genotype and phenotype. The central players are the RNA-binding proteins, and experimental technologies [such as cross-linking with immunoprecipitation- (CLIP-) and RIP-seq] for probing their activities have advanced rapidly over the course of the past decade. Statistically robust, flexible computational methods for binding site identification from high-throughput immunoprecipitation assays are largely lacking however. RESULTS: We introduce a method for site identification which provides four key advantages over previous methods: (i) it can be applied on all variations of CLIP and RIP-seq technologies, (ii) it accurately models the underlying read-count distributions, (iii) it allows external covariates, such as transcript abundance (which we demonstrate is highly correlated with read count) to inform the site identification process and (iv) it allows for direct comparison of site usage across cell types or conditions. AVAILABILITY AND IMPLEMENTATION: We have implemented our method in a software tool called Piranha. Source code and binaries, licensed under the GNU General Public License (version 3) are freely available for download from http://smithlab.usc.edu. CONTACT: andrewds@usc.edu SUPPLEMENTARY INFORMATION: Supplementary data available at Bioinformatics online.

The RNA-binding protein Musashi1 affects medulloblastoma growth via a network of cancer-related genes and is an indicator of poor prognosis.

Musashi1 (Msi1) is a highly conserved RNA-binding protein that is required during the development of the nervous system. Msi1 has been characterized as a stem cell marker, controlling the balance between self-renewal and differentiation, and has also been implicated in tumorigenesis, being highly expressed in multiple tumor types. We analyzed Msi1 expression in a large cohort of medulloblastoma samples and found that Msi1 is highly expressed in tumor tissue compared with normal cerebellum. Notably, high Msi1 expression levels proved to be a sign of poor prognosis. Msi1 expression was determined to be particularly high in molecular subgroups 3 and 4 of medulloblastoma. We determined that Msi1 is required for tumorigenesis because inhibition of Msi1 expression by small-interfering RNAs reduced the growth of Daoy medulloblastoma cells in xenografts. To characterize the participation of Msi1 in medulloblastoma, we conducted different high-throughput analyses. Ribonucleoprotein immunoprecipitation followed by microarray analysis (RIP-chip) was used to identify mRNA species preferentially associated with Msi1 protein in Daoy cells. We also used cluster analysis to identify genes with similar or opposite expression patterns to Msi1 in our medulloblastoma cohort. A network study identified RAC1, CTGF, SDCBP, SRC, PRL, and SHC1 as major nodes of an Msi1-associated network. Our results suggest that Msi1 functions as a regulator of multiple processes in medulloblastoma formation and could become an important therapeutic target.

Genomic analyses of the RNA-binding protein Hu antigen R (HuR) identify a complex network of target genes and novel characteristics of its binding sites.

The ubiquitously expressed RNA-binding protein Hu antigen R (HuR) or ELAVL1 is implicated in a variety of biological processes as well as being linked with a number of diseases, including cancer. Despite a great deal of prior investigation into HuR, there is still much to learn about its function. We take an important step in this direction by conducting cross-linking and immunoprecipitation and RNA sequencing experiments followed by an extensive computational analysis to determine the characteristics of the HuR binding site and impact on the transcriptome. We reveal that HuR targets predominantly uracil-rich single-stranded stretches of varying size, with a strong conservation of structure and sequence composition. Despite the fact that HuR sites are observed in intronic regions, our data do not support a role for HuR in regulating splicing. HuR sites in 3'-UTRs overlap extensively with predicted microRNA target sites, suggesting interplay between the functions of HuR and microRNAs. Network analysis showed that identified targets containing HuR binding sites in the 3' UTR are highly interconnected.

Establishing a stable, repeatable platform for measuring changes in sperm DNA methylation.

BACKGROUND: Several independent research groups have shown that alterations in human sperm methylation profiles correlate with decreased fecundity and an increased risk of poor embryo development. Moving these initial findings from the lab into a clinical setting where they can be used to measure male infertility though requires a platform that is stable and robust against batch effects that can occur between sample runs. Operating parameters must be established, performance characteristics determined, and guidelines set to ensure repeatability and accuracy. The standard for technical validation of a lab developed test (LDT) in the USA comes from the Clinical Laboratory Improvement Amendments (CLIA). However, CLIA was introduced in 1988, before the advent of genome-wide profiling and associated computational analysis. This, coupled with its intentionally general nature, makes its interpretation for epigenetic assays non-trivial. RESULTS: Here, we present an interpretation of the CLIA technical validation requirements for profiling DNA methylation and calling aberrant methylation using the Illumina Infinium platform (e.g., the 450HM and MethylationEPIC). We describe an experimental design to meet these requirements, the experimental results obtained, and the operating parameters established. CONCLUSIONS: The CLIA guidelines, although not intended for high-throughput assays, can be interpreted in a way that is consistent with modern epigenetic assays. Based on such an interoperation, Illumina's Infinium platform is quite amenable to usage in a clinical setting for diagnostic work.

IGF2BP3 Modulates the Interaction of Invasion-Associated Transcripts with RISC.

Insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3) expression correlates with malignancy, but its role(s) in pathogenesis remains enigmatic. We interrogated the IGF2BP3-RNA interaction network in pancreatic ductal adenocarcinoma (PDAC) cells. Using a combination of genome-wide approaches, we have identified 164 direct mRNA targets of IGF2BP3. These transcripts encode proteins enriched for functions such as cell migration, proliferation, and adhesion. Loss of IGF2BP3 reduced PDAC cell invasiveness and remodeled focal adhesion junctions. Individual nucleotide resolution crosslinking immunoprecipitation (iCLIP) revealed significant overlap of IGF2BP3 and microRNA (miRNA) binding sites. IGF2BP3 promotes association of the RNA-induced silencing complex (RISC) with specific transcripts. Our results show that IGF2BP3 influences a malignancy-associated RNA regulon by modulating miRNA-mRNA interactions.

Aberrant sperm DNA methylation predicts male fertility status and embryo quality.

OBJECTIVE: To evaluate whether male fertility status and/or embryo quality during in vitro fertilization (IVF) therapy can be predicted based on genomewide sperm deoxyribonucleic acid (DNA) methylation patterns. DESIGN: Retrospective cohort study. SETTING: University-based fertility center. PATIENT(S): Participants were 127 men undergoing IVF treatment (where any major female factor cause of infertility had been ruled out), and 54 normozoospermic, fertile men. The IVF patients were stratified into 2 groups: patients who had generally good embryogenesis and a positive pregnancy (n = 55), and patients with generally poor embryogenesis (n = 72; 42 positive and 30 negative pregnancies) after IVF. INTERVENTION(S): Genomewide sperm DNA methylation analysis was performed to measure methylation at >485,000 sites across the genome. MAIN OUTCOME MEASURE(S): A comparison was made of DNA methylation patterns of IVF patients vs. normozoospermic, fertile men. RESULT(S): Predictive models proved to be highly accurate in classifying male fertility status (fertile or infertile), with 82% sensitivity, and 99% positive predictive value. Hierarchic clustering identified clusters enriched for IVF patient samples and for poor-quality-embryo samples. Models built to identify samples within these groups, from neat samples, achieved positive predictive value ≥ 94% while identifying >one fifth of all IVF patient and poor-quality-embryo samples in each case. Using density gradient prepared samples, the same approach recovered 46% of poor-quality-embryo samples with no false positives. CONCLUSION(S): Sperm DNA methylation patterns differ significantly and consistently for infertile vs. fertile, normozoospermic men. In addition, DNA methylation patterns may be predictive of embryo quality during IVF.

Computational challenges, tools, and resources for analyzing co- and post-transcriptional events in high throughput.

Co- and post-transcriptional regulation of gene expression is complex and multifaceted, spanning the complete RNA lifecycle from genesis to decay. High-throughput profiling of the constituent events and processes is achieved through a range of technologies that continue to expand and evolve. Fully leveraging the resulting data is nontrivial, and requires the use of computational methods and tools carefully crafted for specific data sources and often intended to probe particular biological processes. Drawing upon databases of information pre-compiled by other researchers can further elevate analyses. Within this review, we describe the major co- and post-transcriptional events in the RNA lifecycle that are amenable to high-throughput profiling. We place specific emphasis on the analysis of the resulting data, in particular the computational tools and resources available, as well as looking toward future challenges that remain to be addressed.

RNA-Binding Protein Musashi1 Is a Central Regulator of Adhesion Pathways in Glioblastoma.

The conserved RNA-binding protein Musashi1 (MSI1) has emerged as a key oncogenic factor in numerous solid tumors, including glioblastoma. However, its mechanism of action has not yet been established comprehensively. To identify its target genes comprehensively and determine the main routes by which it influences glioblastoma phenotypes, we conducted individual-nucleotide resolution cross-linking and immunoprecipitation (iCLIP) experiments. We confirmed that MSI1 has a preference for UAG sequences contained in a particular structural context, especially in 3' untranslated regions. Although numerous binding sites were also identified in intronic sequences, our RNA transcriptome sequencing analysis does not favor the idea that MSI1 is a major regulator of splicing in glioblastoma cells. MSI1 target mRNAs encode proteins that function in multiple pathways of cell proliferation and cell adhesion. Since these associations indicate potentially new roles for MSI1, we investigated its impact on glioblastoma cell adhesion, morphology, migration, and invasion. These processes are known to underpin the spread and relapse of glioblastoma, in contrast to other tumors where metastasis is the main driver of recurrence and progression.

Genomic analyses reveal broad impact of miR-137 on genes associated with malignant transformation and neuronal differentiation in glioblastoma cells.

miR-137 plays critical roles in the nervous system and tumor development; an increase in its expression is required for neuronal differentiation while its reduction is implicated in gliomagenesis. To evaluate the potential of miR-137 in glioblastoma therapy, we conducted genome-wide target mapping in glioblastoma cells by measuring the level of association between PABP and mRNAs in cells transfected with miR-137 mimics vs. controls via RIPSeq. Impact on mRNA levels was also measured by RNASeq. By combining the results of both experimental approaches, 1468 genes were found to be negatively impacted by miR-137--among them, 595 (40%) contain miR-137 predicted sites. The most relevant targets include oncogenic proteins and key players in neurogenesis like c-KIT, YBX1, AKT2, CDC42, CDK6 and TGFß2. Interestingly, we observed that several identified miR-137 targets are also predicted to be regulated by miR-124, miR-128 and miR-7, which are equally implicated in neuronal differentiation and gliomagenesis. We suggest that the concomitant increase of these four miRNAs in neuronal stem cells or their repression in tumor cells could produce a robust regulatory effect with major consequences to neuronal differentiation and tumorigenesis.