This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.

In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting.

Only a small proportion of the mouse genome is transcribed into mature messenger RNA transcripts. There is an international collaborative effort to identify all full-length mRNA transcripts from the mouse, and to ensure that each is represented in a physical collection of clones. Here we report the manual annotation of 60,770 full-length mouse complementary DNA sequences. These are clustered into 33,409 'transcriptional units', contributing 90.1% of a newly established mouse transcriptome database. Of these transcriptional units, 4,258 are new protein-coding and 11,665 are new non-coding messages, indicating that non-coding RNA is a major component of the transcriptome. 41% of all transcriptional units showed evidence of alternative splicing. In protein-coding transcripts, 79% of splice variations altered the protein product. Whole-transcriptome analyses resulted in the identification of 2,431 sense-antisense pairs. The present work, completely supported by physical clones, provides the most comprehensive survey of a mammalian transcriptome so far, and is a valuable resource for functional genomics.

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.

Notch signaling components such as the basic helix-loop-helix gene Hes1 are cyclically expressed by negative feedback in the presomitic mesoderm (PSM) and constitute the somite segmentation clock. Because Hes1 oscillation occurs in many cell types, this clock may regulate the timing in many biological systems. Although the Hes1 oscillator is stable in the PSM, it damps rapidly in other cells, suggesting that the oscillators in the former and the latter could be intrinsically different. Here, we have established the real-time bioluminescence imaging system of Hes1 expression and found that, although Hes1 oscillation is robust and stable in the PSM, it is unstable in the individual dissociated PSM cells, as in fibroblasts. Thus, the Hes1 oscillators in the individual PSM cells and fibroblasts are intrinsically similar, and these results, together with mathematical simulation, suggest that cell-cell communication is essential not only for synchronization but also for stabilization of cellular oscillators.Hes1 ͉ oscillation ͉ luciferase ͉ basic helix-loop-helix gene S omites, precursors for the segmental structures such as the vertebral column, ribs, and skeletal muscles, are generated in a head-to-tail order by periodic segmentation of the anterior end of the presomitic mesoderm (PSM). This periodic event is regulated by the somite segmentation clock, which is composed of Notch and Wnt signaling molecules (1-6). In the PSM, Notch components such as the basic helix-loop-helix genes Hes1 and Hes7 are cyclically expressed, and each cycle leads to segmentation of a bilateral pair of somites (7-11). This oscillatory expression occurs in a synchronous manner but with the caudalto-rostral phase delay, resulting in wave-like propagation of the expression domains from the caudal to the rostral direction. It has been shown that this oscillatory expression depends upon a negative feedback loop (12-18).Interestingly, Hes1 oscillation occurs in many cell types in addition to the PSM after serum treatment or activation of Notch signaling, suggesting that this clock may regulate the timing in many biological systems (12). Although Hes1 oscillation is stable in the PSM, it is damped after three to six cycles in other cells, raising the possibility that the Hes1 oscillator of the PSM cells is intrinsically different from that of other cell types (8, 12). However, the damping could result not only from damped oscillation in each cell but also from desynchronization between cells, and it is not clear which is the case. It was shown that PSM cells could become desynchronized when they are dissociated (19), but the nature of the segmentation clock in individual PSM cells remains to be determined.To understand the dynamics of the somite segmentation clock, we attempted real-time imaging of Hes1 expression in the PSM and the dissociated individual PSM cells. Here, we found that Hes1 oscillation is stable (both the period and amplitude are relatively constant) in the PSM but unstable (the period and amplitude are variable) in the individu...