The RNA binding protein DND1 is elevated in a subpopulation of pro-spermatogonia and targets chromatin modifiers and translational machinery during late gestation.

DND1 is essential to maintain germ cell identity. Loss of Dnd1 function results in germ cell differentiation to teratomas in some inbred strains of mice or to somatic fates in zebrafish. Using our knock-in mouse line in which a functional fusion protein between DND1 and GFP is expressed from the endogenous locus (Dnd1GFP), we distinguished two male germ cell (MGC) populations during late gestation cell cycle arrest (G0), consistent with recent reports of heterogeneity among MGCs. Most MGCs express lower levels of DND1-GFP (DND1-GFP-lo), but some MGCs express elevated levels of DND1-GFP (DND1-GFP-hi). A RNA-seq time course confirmed high Dnd1 transcript levels in DND1-GFP-hi cells along with 5-10-fold higher levels for multiple epigenetic regulators. Using antibodies against DND1-GFP for RNA immunoprecipitation (RIP)-sequencing, we identified multiple epigenetic and translational regulators that are binding targets of DND1 during G0 including DNA methyltransferases (Dnmts), histone deacetylases (Hdacs), Tudor domain proteins (Tdrds), actin dependent regulators (Smarcs), and a group of ribosomal and Golgi proteins. These data suggest that in DND1-GFP-hi cells, DND1 hosts coordinating mRNA regulons that consist of functionally related and localized groups of epigenetic enzymes and translational components.

A transgenic DND1GFP fusion allele reports in vivo expression and RNA-binding targets in undifferentiated mouse germ cells†.

In vertebrates, the RNA-binding protein (RBP) dead end 1 (DND1) is essential for primordial germ cell (PGC) survival and maintenance of cell identity. In multiple species, Dnd1 loss or mutation leads to severe PGC loss soon after specification or, in some species, germ cell transformation to somatic lineages. Our investigations into the role of DND1 in PGC specification and differentiation have been limited by the absence of an available antibody. To address this problem, we used CRISPR/Cas9 gene editing to establish a transgenic mouse line carrying a DND1GFP fusion allele. We present imaging analysis of DND1GFP expression showing that DND1GFP expression is heterogeneous among male germ cells (MGCs) and female germ cells (FGCs). DND1GFP was detected in MGCs throughout fetal life but lost from FGCs at meiotic entry. In postnatal and adult testes, DND1GFP expression correlated with classic markers for the premeiotic spermatogonial population. Utilizing the GFP tag for RNA immunoprecipitation (RIP) analysis in MGCs validated this transgenic as a tool for identifying in vivo transcript targets of DND1. The DND1GFP mouse line is a novel tool for isolation and analysis of embryonic and fetal germ cells, and the spermatogonial population of the postnatal and adult testis.

The RNA-binding protein DND1 acts sequentially as a negative regulator of pluripotency and a positive regulator of epigenetic modifiers required for germ cell reprogramming.

The adult spermatogonial stem cell population arises from pluripotent primordial germ cells (PGCs) that enter the fetal testis around embryonic day (E)10.5. PGCs undergo rapid mitotic proliferation, then enter prolonged cell cycle arrest (G1/G0), during which they transition to pro-spermatogonia. In mice homozygous for the Ter mutation in the RNA-binding protein Dnd1 (Dnd1Ter/Ter ), many male germ cells (MGCs) fail to enter G1/G0 and instead form teratomas: tumors containing many embryonic cell types. To investigate the origin of these tumors, we sequenced the MGC transcriptome in Dnd1Ter/Ter mutants at E12.5, E13.5 and E14.5, immediately prior to teratoma formation, and correlated this information with DO-RIP-Seq-identified DND1 direct targets. Consistent with previous results, we found DND1 controls downregulation of many genes associated with pluripotency and active cell cycle, including mTor, Hippo and Bmp/Nodal signaling pathway elements. However, DND1 targets also include genes associated with male differentiation, including a large group of chromatin regulators activated in wild-type but not mutant MGCs during the E13.5 and E14.5 transition. Results suggest multiple DND1 functions and link DND1 to initiation of epigenetic modifications in MGCs.

Ras Post-transcriptionally Enhances a Pre-malignantly Primed EMT to Promote Invasion.

Epithelial-to-mesenchymal transition (EMT) is integral to cancer progression, with considerable evidence that EMT has multiple intermediary stages. Understanding the mechanisms of this stepwise activation is of great interest. We recreated a genetically defined model in which primary cells were immortalized, resulting in migratory capacity, and subsequently H-Ras-transformed, causing malignancy and invasion. To determine the mechanisms coordinating stepwise malignancy, we quantified the changes in messenger RNA (mRNA) and protein abundance. During immortalization, we found dramatic changes in mRNA, consistent with EMT, which correlated with protein abundance. Many of these same proteins also changed following Ras transformation, suggesting that pre-malignant cells were primed for malignant conversion. Unexpectedly, changes in protein abundance did not correlate with changes in mRNA following transformation. Importantly, proteins involved in cellular adhesion and cytoskeletal structure decreased during immortalization and decreased further following Ras transformation, whereas their encoding mRNAs only changed during the immortalization step. Thus, Ras induced EMT-associated invasion via post-transcriptional mechanisms in primed pre-malignant cells.

DO-RIP-seq to quantify RNA binding sites transcriptome-wide.

Post-transcriptional processes orchestrate gene expression through dynamic protein-RNA interactions. These interactions occur at specific sites determined by RNA sequence, secondary structure, or nucleotide modifications. Methods have been developed either to quantify binding of whole transcripts or to identify the binding sites, but there is none proven to quantify binding at both the whole transcript and binding site levels. Here we describe digestion optimized RNA immunoprecipitation with deep sequencing (DO-RIP-seq) as a method that quantitates at the whole transcript target (RIP-Seq-Like or RSL) level and at the binding site level (BSL) using continuous metrics. DO-RIP-seq methodology was developed using the RBP HuR/ELAVL1 as a test case (Nicholson et al., 2016). DO-RIP-seq employs treatment of cell lysates with a nuclease under optimized conditions to yield partially digested RNA fragments bound by RNA binding proteins, followed by immunoprecipitations that capture the digested RNA-protein complexes and assess non-specific or background interactions. Analyses of sequenced cDNA libraries made from the bound RNA fragments yielded two types of enrichment scores; one for RSL binding events and the other for BSL events (Nicholson et al., 2016). These analyses plus the extensive read coverage of DO-RIP-seq allows seamless integration of binding site and whole transcript information. Therefore, DO-RIP-seq is useful for quantifying RBP binding events that are regulated during dynamic biological processes.

Advancing the functional utility of PAR-CLIP by quantifying background binding to mRNAs and lncRNAs.

BACKGROUND: Sequence specific RNA binding proteins are important regulators of gene expression. Several related crosslinking-based, high-throughput sequencing methods, including PAR-CLIP, have recently been developed to determine direct binding sites of global protein-RNA interactions. However, no studies have quantitatively addressed the contribution of background binding to datasets produced by these methods. RESULTS: We measured non-specific RNA background in PAR-CLIP data, demonstrating that covalently crosslinked background binding is common, reproducible and apparently universal among laboratories. We show that quantitative determination of background is essential for identifying targets of most RNA-binding proteins and can substantially improve motif analysis. We also demonstrate that by applying background correction to an RNA binding protein of unknown binding specificity, Caprin1, we can identify a previously unrecognized RNA recognition element not otherwise apparent in a PAR-CLIP study. CONCLUSIONS: Empirical background measurements of global RNA-protein crosslinking are a necessary addendum to other experimental controls, such as performing replicates, because covalently crosslinked background signals are reproducible and otherwise unavoidable. Recognizing and quantifying the contribution of background extends the utility of PAR-CLIP and can improve mechanistic understanding of protein-RNA specificity, protein-RNA affinity and protein-RNA association dynamics.

Coordinated posttranscriptional mRNA population dynamics during T-cell activation.

Although RNA-binding proteins (RBPs) coordinate many key decisions during cell growth and differentiation, the dynamics of RNA-RBP interactions have not been extensively studied on a global basis. We immunoprecipitated endogenous ribonucleoprotein complexes containing HuR and PABP throughout a T-cell activation time course and identified the associated mRNA populations using microarrays. We used Gaussian mixture modeling as a discriminative model, treating RBP association as a discrete variable (target or not target), and as a generative model, treating RBP-association as a continuous variable (probability of association). We report that HuR interacts with different populations of mRNAs during T-cell activation. These populations encode functionally related proteins that are members of the Wnt pathway and proteins mediating T-cell receptor signaling pathways. Moreover, the mRNA targets of HuR were found to overlap with the targets of other posttranscriptional regulatory factors, indicating combinatorial interdependence of posttranscriptional regulatory networks and modules after activation. Applying HuR mRNA dynamics as a quantitative phenotype in the drug-gene-phenotype Connectivity Map, we identified candidate small molecule effectors of HuR and T-cell activation. We show that one of these candidates, resveratrol, exerts T-cell activation-dependent posttranscriptional effects that are rescued by HuR. Thus, we describe a strategy to systematically link an RBP and condition-specific posttranscriptional effects to small molecule drugs.

RIP-Chip: the isolation and identification of mRNAs, microRNAs and protein components of ribonucleoprotein complexes from cell extracts.

RNA targets of multitargeted RNA-binding proteins (RBPs) can be studied by various methods including mobility shift assays, iterative in vitro selection techniques and computational approaches. These techniques, however, cannot be used to identify the cellular context within which mRNAs associate, nor can they be used to elucidate the dynamic composition of RNAs in ribonucleoprotein (RNP) complexes in response to physiological stimuli. But by combining biochemical and genomics procedures to isolate and identify RNAs associated with RNA-binding proteins, information regarding RNA-protein and RNA-RNA interactions can be examined more directly within a cellular context. Several protocols--including the yeast three-hybrid system and immunoprecipitations that use physical or chemical cross-linking--have been developed to address this issue. Cross-linking procedures in general, however, are limited by inefficiency and sequence biases. The approach outlined here, termed RNP immunoprecipitation-microarray (RIP-Chip), allows the identification of discrete subsets of RNAs associated with multi-targeted RNA-binding proteins and provides information regarding changes in the intracellular composition of mRNPs in response to physical, chemical or developmental inducements of living systems. Thus, RIP-Chip can be used to identify subsets of RNAs that have related functions and are potentially co-regulated, as well as proteins that are associated with them in RNP complexes. Using RIP-Chip, the identification and/or quantification of RNAs in RNP complexes can be accomplished within a few hours or days depending on the RNA detection method used.