Summary
The developmental origins of most adult stem cells are poorly understood. Here, we report the identification of a transcription factor—RHOX10—that is critical for the initial establishment of spermatogonial stem cells (SSCs). Conditional loss of the entire 33-gene X-linked homeobox gene cluster that includes Rhox10 causes progressive spermatogenic decline, a phenotype indistinguishable from that caused by loss of only Rhox10. We demonstrate that this phenotype results from dramatically reduced SSC generation. Using a battery of approaches, including single cell-RNAseq (scRNAseq) analysis, we show that Rhox10 drives SSC generation by promoting Pro-spermatogonia differentiation. Rhox10 also regulates batteries of migration genes and promotes the migration of Pro-spermatogonia into the SSC niche. The identification of an X-linked homeobox gene that drives the initial generation of SSCs has implications for the evolution of X-linked gene clusters and sheds light on regulatory mechanisms influencing adult stem cell generation in general.
Event based analysis plays an important role in reducing the latency of information delivery in an event driven world. Also, the perception of an 'event' by a user is at a higher level (a meta event), and would involve the analysis of several less complex or lower order events (basic events) in order to convey meaningful information. This is especially true of real world events and it is often necessary to completely capture the attributes of events and the relationships between them, so that the process of retrieval of event related information is efficient. In this paper, we discuss a formal system for representing and analyzing real world events to address these issues. The event representation discussed in this paper accounts for three important event attributes, namely, time, space, and label. We introduce the notion of sequence templates that appears natural for capturing event related semantics. It can also help in semantically analyzing user queries. To harness this potential, we present a formal structure to represent the queries related to real world events as well as an approach to semantically analyze a user query, and collate event related information to be dispatched to the user. Finally, we discuss the design and implementation of the Query-Event Analysis System (QEAS), which is an integrated system to (a) identify a best-matching sequence template(s) given a user query; (b) derive the meta-events based on the selected sequence templates; and (c) and use the meta-event information to answer the user query.
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