SummaryAs the premier model organism in biomedical research, the laboratory mouse shares the majority of protein-coding genes with humans, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications, and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of other sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

Embryonic stem (ES) cells are unique in their ability to self-renew indefinitely and maintain pluripotency. These properties require transcription factors that specify the gene expression programme of ES cells. It has been possible to reverse the highly differentiated state of somatic cells back to a pluripotent state with a combination of four transcription factors: Klf4 is one of the reprogramming factors required, in conjunction with Oct4, Sox2 and c-Myc. Maintenance of self-renewal and pluripotency of ES cells requires Oct4, Sox2 and c-Myc, but Klf4 is dispensable. Here, we show that Krüppel-like factors are required for the self-renewal of ES cells. Simultaneous depletion of Klf2, Klf4 and Klf5 lead to ES cell differentiation. Chromatin immunoprecipitation coupled to microarray assay reveals that these Klf proteins share many common targets of Nanog, suggesting a close functional relationship between these factors. Expression analysis after triple RNA interference (RNAi) of the Klfs shows that they regulate key pluripotency genes, such as Nanog. Taken together, our study provides new insight into how the core Klf circuitry integrates into the Nanog transcriptional network to specify gene expression that is unique to ES cells.

Preface The 4D Nucleome Network aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes in space and time with the goal of gaining deeper mechanistic understanding of how the nucleus is organized and functions. The project will develop and benchmark experimental and computational approaches for measuring genome conformation and nuclear organization, and investigate how these contribute to gene regulation and other genome functions. Validated experimental approaches will be combined with biophysical modeling to generate quantitative models of spatial genome organization in different biological states, both in cell populations and in single cells.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Sonic hedgehog (Shh) acts as a morphogen to mediate the specification of distinct cell identities in the ventral neural tube through a Gli-mediated (Gli1-3) transcriptional network. Identifying Gli targets in a systematic fashion is central to the understanding of the action of Shh. We examined this issue in differentiating neural progenitors in mouse. An epitope-tagged Gli-activator protein was used to directly isolate cis-regulatory sequences by chromatin immunoprecipitation (ChIP). ChIP products were then used to screen custom genomic tiling arrays of putative Hedgehog (Hh) targets predicted from transcriptional profiling studies, surveying 50-150 kb of non-transcribed sequence for each candidate. In addition to identifying expected Gli-target sites, the data predicted a number of unreported direct targets of Shh action. Transgenic analysis of binding regions in Nkx2.2, Nkx2.1 (Titf1) and Rab34 established these as direct Hh targets. These data also facilitated the generation of an algorithm that improved in silico predictions of Hh target genes. Together, these approaches provide significant new insights into both tissue-specific and general transcriptional targets in a crucial Shh-mediated patterning process.

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Mammalian preimplantation embryonic development (PED) is thought to be governed by highly conserved processes. While it had been suggested that some plasticity of conserved signaling networks exists among different mammalian species, it was not known to what extent modulation of the genomes and the regulatory proteins could “rewire” the gene regulatory networks (GRN) that control PED. We therefore generated global transcriptional profiles from three mammalian species (human, mouse, and bovine) at representative stages of PED, including: zygote, two-cell, four-cell, eight-cell, 16-cell, morula and blastocyst. Coexpression network analysis suggested that 40.2% orthologous gene triplets exhibited different expression patterns among these species. Combining the expression data with genomic sequences and the ChIP-seq data of 16 transcription regulators, we observed two classes of genomic changes that contributed to interspecies expression difference, including single nucleotide mutations leading to turnover of transcription factor binding sites, and insertion of cis-regulatory modules (CRMs) by transposons. About 10% of transposons are estimated to carry CRMs, which may drive species-specific gene expression. The two classes of genomic changes act in concert to drive mouse-specific expression of MTF2, which links POU5F1/NANOG to NOTCH signaling. We reconstructed the transition of the GRN structures as a function of time during PED. A comparison of the GRN transition processes among the three species suggested that in the bovine system, POU5F1's interacting partner SOX2 may be replaced by HMGB1 (a TF sharing the same DNA binding domain with SOX2), resulting in rewiring of GRN by a trans change.