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Munger, S. C.

Publications and source records attributed to Munger, S. C..

At least 19 recordsLinked to original sources

The Flame Retardant Triphenyl Phosphate Induces Varying Responses in Genetically Diverse Mouse Induced Pluripotent Stem Cells

Genetic variation impacts biological response to chemical and environmental exposures, contributing to differences in resistance or susceptibility. Forward genetic screens of genetically diverse cell populations can be used to identify the precise genetic variants that drive response variation. Cell lines from laboratory mouse genetic reference populations like the Diversity Outbred (DO) population are well powered for genetic mapping. Diverse stem cell panels are especially beneficial for studying early developmental effects of chemical exposures like triphenyl phosphate (TPHP), an organophosphate flame retardant linked to adverse developmental effects, including altered cell cycle in stem cells. Self-renewal and pluripotency are defining properties of stem cells during development; therefore, it is important to understand how chemicals like TPHP may alter these critical characteristics. To better understand the influence of genetic variation on TPHP exposure response, we utilized a genetically diverse panel of DO induced pluripotent stem cells (DO iPSCs). Our analyses characterize interline variation in gene expression through differential gene expression analysis and expression quantitative trait locus (eQTL) mapping. We identified genomic loci that contribute to variation in gene expression following TPHP exposure, including a regulatory hotspot on chromosome 15. Gene set enrichment highlighted several pathways affected by TPHP including lipid metabolism, steroid hormone signaling, and cell cycle. Our study shows that genetic variation modulates the effects of TPHP on gene expression and cell cycle in stem cells. Additionally, our work demonstrates that genetically diverse cell panels like the DO iPSC resource offer a tractable and scalable approach for identifying the genetic determinants of chemical toxicity.

genomics↗

A panel of Diversity Outbred mouse embryonic stem cells: enabling the functional characterization of natural genetic variation in vitro

Phenotypic variation in pluripotent stem cells arises largely from genetic variants that impact stability of the pluripotent state, response to differentiation cues, and cell fate diversification. Panels derived from genetic reference populations leverage genetic diversity to map the loci influencing these molecular and cellular traits. Here we describe the first publicly available resource for in vitro systems genetics in Mus musculus: 299 genetically diverse, highly heterozygous embryonic stem cell lines derived from Diversity Outbred mice, with minimal kinship across the panel. We characterize genomic integrity and allelic variation across the panel and describe differences in pluripotency and differentiation networks in embryoid bodies. Mapping the genetic determinants of gene expression differences in response to cadmium exposure in embryoid bodies identified 13 regulatory hotspots, the largest acting on ribosome biogenesis genes. This panel enables mapping of loci and gene-by-environment interactions that influence molecular identity in pluripotent cells and their derived cell types.

systems biology↗

Molecular and genetic heterogeneity in iPSCs derived from an outbred laboratory mouse population

Genetically diverse panels of human pluripotent stem cells enable genetic dissection of cellular phenotypes, but comparable induced pluripotent stem cell (iPSC) resources in model organisms remain limited. We generated a panel of iPSCs from the Diversity Outbred (DO) mouse population and established 288 genetically unique lines that retain the allele frequency distribution, heterozygosity, and low population structure of the source population. The lines exhibit consistent growth, pluripotent gene expression profiles, and capacity to form embryoid bodies. Transcriptomic profiling of the lines revealed significant variation in gene expression driven in part by genetic background. We used expression quantitative trait locus (eQTL) mapping to identify over 10,000 regulatory loci that influence gene expression variation, including multiple distal eQTL hotspots that are key gene regulatory hubs and are shared with DO embryonic stem cells (ESCs). The largest hotspot, mediated by Lifr, showed a shift in founder allele effects relative to ESCs, consistent with differences in cellular state and culture conditions. These results establish the DO iPSC panel as a genetically diverse, publicly accessible platform derived from a laboratory mouse genetic reference population, enabling integration of in vitro cellular phenotypes with in vivo traits within a closed, outbred population.

genetics↗

Simplifying Systems Genetics with QTLretrievR: An R Package for Molecular QTL Identification

MotivationOver the past two decades, integrating "-omics" scale molecular profiling with genetic mapping in diverse populations--termed "systems genetics"--has proven powerful for linking complex disease phenotypes to genetic variants and their regulatory effects. However, these combined genomic and genetic analyses remain computationally intensive and often inaccessible to researchers without a strong computational background, a problem compounded in studies with multiple tissues or thousands of molecular -omics phenotypes. ResultsWe developed QTLretrievR, an R package designed to simplify and streamline the identification and downstream analysis of molecular quantitative trait loci in genetically diverse populations. QTLretrievR builds on widely used R packages such as r/qtl2 for quantitative trait locus mapping and r/intermediate for mediation analysis, and incorporates substantial parallelization features to improve computational efficiency. Benchmarking demonstrates that QTLretrievR can reproduce results from previous quantitative trait locus studies while significantly reducing the time required for quantitative trait locus peak detection and downstream analyses. Additionally, QTL-retrievR includes plotting functions to visualize results of the included downstream analyses. AvailabilitySource code is available at https://github.com/deweyhannah/QTLretrievR. ContactSteven Munger, steven.munger@jax.org

genetics↗

Mammalian oocytes receive maternal-effect RNAs from granulosa cells

It is currently thought that growing mammalian oocytes receive only small molecules via gap junctions from surrounding support cells, the granulosa cells. From the study of chimeric preantral oocyte and granulosa cell reaggregations, we provide evidence that growing mouse oocytes receive mRNAs from granulosa cells. Among the >1,000 granulosa-transcribed RNAs we identified in the oocyte, those that contribute to proper oocyte maturation and early embryo development were highly enriched. Predicted motifs for two RNA-binding proteins that function in RNA trafficking, FMRP and TDP43, were abundant in the UTRs of the granulosa-derived transcripts. Immunostaining demonstrated that both FMRP and TDP43 co-localize with the actin-rich granulosa cell protrusions that span the zone pellucida and connect to the oocyte, suggesting their role in importing mRNAs. Our results offer the possibility that oocyte failure may not always reflect an intrinsic oocyte deficiency but could arise from insufficient supply of maternal transcripts by granulosa cells during oocyte growth.

developmental biology↗

Cross cell-type systems genetics reveals the influence of eQTL at multiple points in the developmental trajectory of mouse neural progenitor cells

Genetic variation leads to phenotypic variability in pluripotent stem cells that presents challenges for regenerative medicine. Although recent studies have investigated the impact of genetic variation on pluripotency maintenance and differentiation capacity, less is known about how genetic variants affecting the pluripotent state influence gene regulation in later stages of development. Here, we characterized expression of more than 12,000 genes in 127 donor-matched Diversity Outbred (DO) mouse embryonic stem cell (mESC) and neural progenitor cell (mNPC) lines. Quantitative trait locus (QTL) mapping identified 2,947 expression QTL (eQTL) unique to DO mNPCs and 1,113 eQTL observed in both mNPCs and mESCs with highly concordant allele effects. We mapped three eQTL hotspots on Chromosomes (Chrs) 1, 10, and 11 that were unique to mNPCs. Target genes of the Chr 1 hotspot were overrepresented for those involved in mRNA processing, DNA repair, chromatin organization, protein degradation, and cell cycle. Mediation analysis of the Chr 1 hotspot identified Rnf152 as the best candidate mediator expressed in mNPCs, while cross-cell type mediation using mESC gene expression along with partial correlation analysis strongly implicated genetic variant(s) affecting Pign expression in the mESC state as regulating the mNPC Chr 1 eQTL hotspot. Together these findings highlight that many local eQTL confer similar effects on gene expression in multiple cell states; distant eQTL in DO mNPCs are numerous and largely unique to that cell state, with many co-localizing to mNPC-specific hotspots; and mediation analysis across cell types suggests that expression of Pign early in development (mESCs) shapes the transcriptome of the more specialized mNPC state.

genetics↗

Chromosome X Dosage Modulates Development of Aneuploidy in Genetically Diverse Mouse Embryonic Stem Cells

The genetic integrity of pluripotent stem cells (PSC) is critical to their applications in research and therapy, but it is compromised by frequent development of structural chromosome variants associated with malignancy. Many cell lines exhibit remarkable genetic stability, but little is known about the basis of the known variation in genomic integrity amongst different PSC isolates. Here we identify aneuploidies using RNA-seq and proteomics data from a panel of mouse embryonic stem cell (mESC) lines derived from 170 Diversity Outbred mice. We found 62 lines with detectable aneuploid subpopulations and a subset of originally XX lines that lost one Chromosome X (XO). Strikingly, a much lower proportion of XX lines were aneuploid, compared to XY or XO lines. Two single-cell RNA-seq data sets demonstrated that aneuploid XY DO mESC also show lower Chromosome X gene expression, and a prospective study confirmed that XY mESC accumulate higher aneuploid proportions in culture than isogenic XX lines. We identify potential mechanisms for this protective effect of X chromosome dosage, including our findings that the lines with two active X Chromosomes have a higher proportion of 2-cell-like cells, a state associated with maintenance of genetic integrity of mESC, and that they show differential expression of X-linked tumor suppressor genes associated with the DNA damage response. HighlightsO_LIFirst genetic analysis of predisposition to aneuploidy in pluripotent stem cell cultures C_LIO_LIChromosomal regions duplicated in aneuploid mouse embryonic stem cells are syntenic with regions overrepresented in human pluripotent stem cell lines bearing recurrent genetic abnormalities C_LIO_LIX-Chromosome dosage strongly influences susceptibility to aneuploidy in mouse embryonic stem cells and to a lesser degree in human pluripotent stem cells C_LIO_LIXX mouse embryonic stem cell lines show a higher proportion of cells in 2 cell-like state and higher expression of tumor suppressor genes associated with DNA damage response C_LI

genetics↗

Methods to study xenografted human cancer in genetically diverse mice

Xenografting human cancer tissues into mice to test new cures against cancers is critical for understanding and treating the disease. However, only a few inbred strains of mice are used to study cancers, and derivatives of mainly one strain, mostly NOD/ShiLtJ, are used for therapy efficacy studies. As it has been demonstrated when human cancer cell lines or patient-derived tissues (PDX) are xenografted into mice, the neoplastic cells are human but the supporting cells that comprise the tumor (the stroma) are from the mouse. Therefore, results of studies of xenografted tissues are influenced by the host strain. We previously published that when the same neoplastic cells are xenografted into different mouse strains, the pattern of tumor growth, histology of the tumor, number of immune cells infiltrating the tumor, and types of circulating cytokines differ depending on the strain. Therefore, to better comprehend the behavior of cancer in vivo, one must xenograft multiple mouse strains. Here we describe and report a series of methods that we used to reveal the genes and proteins expressed when the same cancer cell line, MDA-MB-231, is xenografted in different hosts. First, using proteomic analysis, we show how to use the same cell line in vivo to reveal the protein changes in the neoplastic cell that help it adapt to its host. Then, we show how different hosts respond molecularly to the same cell line. We also find that using multiple strains can reveal a more suitable host than those traditionally used for a "difficult to xenograft" PDX. In addition, using complex trait genetics, we illustrate a feasible method for uncovering the alleles of the host that support tumor growth. Finally, we demonstrate that Diversity Outbred mice, the epitome of a model of mouse-strain genetic diversity, can be xenografted with human cell lines or PDX using 2-deoxy-D-glucose treatment.

cancer biology↗

Multi-omics analysis identifies drivers of protein phosphorylation

Phosphorylation of proteins is a key step in the regulation of many cellular processes including activation of enzymes and signaling cascades. The abundance of a phosphorylated peptide (phosphopeptide) is determined by the abundance of its parent protein and the proportion of target sites that are phosphorylated. We quantified phosphopeptides, proteins, and transcripts in heart, liver, and kidney tissue samples of mice from 58 strains of the Collaborative Cross strain panel. We mapped [~]700 phosphorylation quantitative trait loci (phQTL) across the three tissues and applied genetic mediation analysis to identify causal drivers of phosphorylation. We identified kinases, phosphatases, cytokines, and other factors, including both known and potentially novel interactions between target proteins and genes that regulate site-specific phosphorylation. Our analysis highlights multiple targets of pyruvate dehydrogenase kinase 1 (PDK1), a regulator of mitochondrial function that shows reduced activity in the NZO/HILtJ mouse, a polygenic model of obesity and type 2 diabetes.

genomics↗

Genetic dissection of the pluripotent proteome through multi-omics data integration

Genetic background is a major driver of phenotypic variability in pluripotent stem cells (PSCs). Most studies of variation in PSCs have relied on transcript abundance as the primary molecular readout of cell state. However, little is known about how proteins, the primary functional units in the cell, vary across genetically diverse PSCs, how protein abundance relates to variation in other cell characteristics, and how genetic background confers these effects. Here we present a comprehensive genetic study characterizing the pluripotent proteome of 190 unique mouse embryonic stem cell lines (mESCs) derived from genetically heterogeneous Diversity Outbred (DO) mice. The quantitative proteome is highly variable across DO mESCs, and we identified differentially activated pluripotency-associated pathways in the proteomics data that were not evident in transcriptome data from the same cell lines. Comparisons of protein abundance to transcript levels and chromatin accessibility show broad co-variation across molecular layers and variable correlation across samples, with some lines showing high and others low correlation between these multi-omics datasets. Integration of these three molecular data types using multi-omics factor analysis revealed shared and unique drivers of quantitative variation in pluripotency-associated pathways. QTL mapping localized the genetic drivers of this quantitative variation to a number of genomic hotspots, and demonstrated that multi-omics data integration consolidates the influence of genetic signals shared across molecular traits to increase QTL detection power and overcome the limitations inherent in mapping individual molecular features. This study reveals transcriptional and post-transcriptional mechanisms and genetic interactions that underlie quantitative variability in the pluripotent proteome, and in so doing provides a regulatory map for mouse ESCs that can provide a rational basis for future mechanistic studies, including studies of human PSCs.

genetics↗

Imputation of 3D genome structure by genetic-epigenetic interaction modeling in mice

Gene expression is known to be affected by interactions between local genetic variation and DNA accessibility, with the latter organized into three-dimensional chromatin structures. Analyses of these interactions has previously been limited, obscuring their regulatory context, and the extent to which they occur throughout the genome. Here we undertake a genome-scale analysis of these interactions in a genetically diverse population to systematically identify global genetic-epigenetic interaction, and reveal constraints imposed by chromatin structure. We establish the extent and structure of genotype-by-epigenotype interaction using embryonic stem cells derived from Diversity Outbred mice. This mouse population segregates millions of variants from eight inbred founders, enabling precision genetic mapping with extensive genotypic and phenotypic diversity. With 176 samples profiled for genotype, gene expression, and open chromatin, we used regression modeling to infer genetic-epigenetic interactions on a genome-wide scale. Our results demonstrate that statistical interactions between genetic variants and chromatin accessibility are common throughout the genome. We found that these interactions occur within the local area of the affected gene, and that this locality corresponds to topologically associated domains (TADs). The likelihood of interaction was most strongly defined by the three-dimensional (3D) domain structure rather than linear DNA sequence. We show that stable 3D genome structure is an effective tool to guide searches for regulatory elements and, conversely, that regulatory elements in genetically diverse populations provide a means to infer 3D genome structure. We confirmed this finding with CTCF ChIP-seq that revealed strain-specific binding in the inbred founder mice. In stem cells, open chromatin participating in the most significant regression models demonstrated an enrichment for developmental genes and the TAD-forming CTCF binding complex, providing an opportunity for statistical inference of shifting TAD boundaries operating during early development. These findings provide evidence that genetic and epigenetic factors operate within the context of three- dimensional chromatin structure. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/479436v3_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@14d4221org.highwire.dtl.DTLVardef@130a812org.highwire.dtl.DTLVardef@16a6069org.highwire.dtl.DTLVardef@df9d9c_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

Genetic Control of Pluripotency Epigenome Determines Differentiation Bias in Mouse Embryonic Stem Cells

Genetically diverse pluripotent stem cells (PSCs) display varied, heritable responses to differentiation cues in the culture environment. By harnessing these disparities through derivation of embryonic stem cells (ESCs) from the BXD mouse genetic reference panel, along with C57BL/6J (B6) and DBA/2J (D2) parental strains, we demonstrate genetically determined biases in lineage commitment and identify major regulators of the pluripotency epigenome. Upon transition to formative pluripotency using epiblast-like cells (EpiLCs), B6 quickly dissolves naive networks adopting gene expression modules indicative of neuroectoderm lineages; whereas D2 retains aspects of naive pluripotency with little bias in differentiation. Genetic mapping identifies 6 major trans-acting loci co-regulating chromatin accessibility and gene expression in ESCs and EpiLCs, indicating a common regulatory system impacting cell state transition. These loci distally modulate occupancy of pluripotency factors, including TRIM28, P300, and POU5F1, at hundreds of regulatory elements. One trans-acting locus on Chr 12 primarily impacts chromatin accessibility in ESCs; while in EpiLCs the same locus subsequently influences gene expression, suggesting early chromatin priming. Consequently, the distal gene targets of this locus are enriched for neurogenesis genes and were more highly expressed when cells carried B6 haplotypes at this Chr 12 locus, supporting genetic regulation of biases in cell fate. Spontaneous formation of embryoid bodies validated this with B6 showing a propensity towards neuroectoderm differentiation and D2 towards definitive endoderm, confirming the fundamental importance of genetic variation influencing cell fate decisions.

genomics↗

Genotype-free individual genome reconstruction of Multiparental Population Models by RNA sequencing data

AbstractMulti-parent populations (MPPs), model organisms derived from two or more inbred founder strains, are widely used in biomedical and agricultural research. Gene expression profiling by direct RNA sequencing (RNA-Seq) is commonly applied to MPPs to investigate gene expression regulation and to identify candidate genes. In genetically diverse populations, including MPPs, quantification of gene expression is improved when the RNA-Seq reads are aligned to individualized transcriptomes that incorporate known polymorphic loci. However, the process of constructing and analyzing individual genomes can be computationally demanding and error prone. We propose a new approach, genome reconstruction by RNA-Seq (GBRS), that relies on simultaneous alignment of RNA-Seq reads to founder strain transcriptomes to reconstruct the diploid genome and quantify total and allele-specific gene expression in MPPs. We demonstrate that GBRS performs as well as methods that rely on high-density genotyping arrays. When used in conjunction with other genotyping methods, GBRS provides quality control for detecting sample mix-ups or contamination. GBRS software is freely available at https://github.com/churchill-lab/gbrs.

bioinformatics↗

Regulation of protein abundance in genetically diverse mouse populations

Proteins constitute much of the structure and functional machinery of cells, forming signaling networks, metabolic pathways, and large multi-component complexes. Protein abundance is regulated at multiple levels spanning transcription, translation, recycling, and degradation to maintain proper balance and optimal function. To better understand how protein abundances are maintained across varying genetic backgrounds, we analyzed liver proteomes of three genetically diverse mouse populations. We observe strong concordance of genetic and sex effects across populations. Differences between the populations arise from the contributions of additive, dominance, and epistatic components of heritable variation. We find that the influence of genetic variation on proteins that form complexes relates to their co-abundance. We identify effects on protein abundance from mutations that arose and became fixed during breeding and can lead to unique regulatory responses and disease states. Genetically diverse mouse populations provide powerful tools for understanding proteome regulation and its relationship to whole-organism phenotypes. O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/296657v3_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1c8a941org.highwire.dtl.DTLVardef@e022b6org.highwire.dtl.DTLVardef@106e361org.highwire.dtl.DTLVardef@13a2c2c_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

Genome-wide transcript and protein analysis reveals distinct features of aging in the mouse heart

Investigation of the molecular mechanisms of aging in the human heart is challenging due to confounding factors, such as diet and medications, as well limited access to tissues. The laboratory mouse provides an ideal model to study aging in healthy individuals in a controlled environment. However, previous mouse studies have examined only a narrow range of the genetic variation that shapes individual differences during aging. Here, we analyzed transcriptome and proteome data from hearts of genetically diverse mice at ages 6, 12 and 18 months to characterize molecular changes that occur in the aging heart. Transcripts and proteins reveal distinct biological processes that are altered through the course of natural aging. Transcriptome analysis reveals a scenario of cardiac hypertrophy, fibrosis, and reemergence of fetal gene expression patterns. Proteome analysis reveals changes in energy metabolism and protein homeostasis. We found that for many protein complexes there is a decline in correlation between their component proteins with age, indicating age-related loss of stoichiometry. Some of the most affected complexes are themselves involved in protein homeostasis, which potentially contributes to a viscious cycle of progressive breakdown in protein quality control with age. In addition, we identified genetic loci that modulate age-related changes in a variety of cellular processes, including protein degradation and sorting, suggesting that genetic variation can alter the rate of molecular aging.

genomics↗

Facial shape and allometry quantitative trait locus intervals in the Diversity Outbred mouse are enriched for known skeletal and facial development genes

The biology of how faces are built and come to differ from one another is complex. Discovering the genes that contribute to differences in facial morphology is one key to untangling this complexity, with important implications for medicine and evolutionary biology. This study maps quantitative trait loci (QTL) for skeletal facial shape using Diversity Outbred (DO) mice. The DO is a randomly outcrossed population with high heterozygosity that captures the allelic diversity of eight inbred mouse lines from three subspecies. The study uses a sample of 1147 DO animals (the largest sample yet employed for a shape QTL study in mouse), each characterized by 22 three-dimensional landmarks, 56,885 autosomal and X-chromosome markers, and sex and age classifiers. We identified 37 facial shape QTL across 20 shape principal components (PCs) using a mixed effects regression that accounts for kinship among observations. The QTL include some previously identified intervals as well as new regions that expand the list of potential targets for future experimental study. Three QTL characterized shape associations with size (allometry). Median support interval size was 3.5 Mb. Narrowing additional analysis to QTL for the five largest magnitude shape PCs, we found significant overrepresentation of genes with known roles in growth, skeletal development, and sensory organ development. For most intervals, one or more of these genes lies within 0.25 Mb of the QTLs peak. QTL effect sizes were small, with none explaining more than 0.5% of facial shape variation. Thus, our results are consistent with a model of facial diversity that is influenced by key genes in skeletal and facial development and, simultaneously, is highly polygenic.\n\nAuthor SummaryThe mammalian face is a complex structure serving many functions. We studied the genetic basis for facial skeletal diversity in a large sample of mice from an experimental population designed for the study of complex traits. We quantified the contribution of genetic variation to variation in three-dimensional facial shape across more than 55,000 genetic markers spread throughout the mouse genome. We found 37 genetic regions which are very likely to contribute to differences in facial shape. We then conducted a more detailed analysis of the genetic regions associated with the most variable aspects of facial shape. For these regions, a disproportionately large number of genes are known to be important to growth and to skeletal and facial development. The magnitude of these genetic contributions to differences in facial shape are consistently small. Our results therefore support the notion that facial skeletal diversity is influenced by many genes of small effect, but that some of these small effects may be related to genes that are fundamental to skeletal and facial development.

genetics↗

Genetic variation influences pluripotent ground state stability in mouse embryonic stem cells through a hierarchy of molecular phenotypes

Mouse embryonic stem cells (mESCs) cultured under controlled conditions occupy a stable ground state where pluripotency-associated transcriptional and epigenetic circuitry are highly active. However, mESCs from some genetic backgrounds exhibit metastability, where ground state pluripotency is lost in the absence of ERK1/2 and GSK3 inhibition. We dissected the genetic basis of metastability by profiling gene expression and chromatin accessibility in 185 genetically heterogeneous mESCs. We mapped thousands of loci affecting chromatin accessibility and/or transcript abundance, including eleven instances where distant QTL co-localized in clusters. For one cluster we identified Lifr transcript abundance as the causal intermediate regulating 122 distant genes enriched for roles in maintenance of pluripotency. Joint mediation analysis implicated a single enhancer variant ~10kb upstream of Lifr that alters chromatin accessibility and precipitates a cascade of molecular events affecting maintenance of pluripotency. We validated this hypothesis using reciprocal allele swaps, revealing mechanistic details underlying variability in ground state metastability in mESCs.

genomics↗

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 10.5 (E10.5). These cells undergo rapid mitotic proliferation, then enter a prolonged period of 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 germ cells fail to enter G1/G0, and give rise to teratomas, tumors in which many embryonic cell types are represented. To investigate the origin of these tumors, we sequenced the transcriptome of male germ cells in DND1Ter/Ter mutants at E12.5, E13.5, and E14.5, just prior to the formation of teratomas, and correlated this information with direct targets of DND1 identified by DO-RIP-Seq. Consistent with previous results, we found that DND1 controls the down regulation of many genes associated with pluripotency and active cell cycle, including elements of the mTor, Hippo and Bmp/Nodal signaling pathways. However, DND1 targets also include genes associated with male differentiation including a large group of chromatin regulators activated in wild type but not mutant germ cells during the transition between E13.5 and E14.5. These results suggest multiple functions of DND1, and link DND1 to the initiation of epigenetic modifications in male germ cells.

cell biology↗