Molecular genetics of the imprinted gene - SPROUTY3 (SPRY3)

Sprouty proteins are key regulators of cell growth and branching morphogenesis during development. Human SPRY3 which maps to the pseudoautosomal region 2, undergoes random X-inactivation in females and preferential Y-inactivation in males, behaving as though genetically X-linked. Spry3 is widely expressed in neuronal tissues, being found at high levels in the cerebellum and particularly in the Purkinje cells which, notably, are deficient in the autistic brain. Spry3 is also highly expressed in other ganglia in adults including retinal ganglion cells, dorsal root ganglion and superior cervical ganglion. SPRY3 enhancer can drive SPRY3 expression in the lung airway, which is consistent with a role in branching morphogenesis and the function of the original Drosophila Spry gene, which is critical for lung morphogenesis, providing a possible explanation for an observed anatomic abnormality in the autistic lung airway. In the human and mouse, the SPRY3 core promoter contains an AG-rich repeat and we found evidence of coexpression, promoter binding and regulation of SPRY3 expression by transcription factors EGR1, ZNF263 and PAX6. Spry3 over-expression in mouse superior cervical ganglion cells inhibits axon branching and Spry3 knockdown in those cells increases axon branching, consistent with known functions of other Sprouty proteins. Novel SPRY3 upstream transcripts that I characterised originate from three start sites in the X-linked F8A3 – TMLHE gene region, which is recently implicated in autism causation. Arising from these findings, I propose that the lung airway abnormality and low levels of blood carnitine found in autism suggest that deregulation of SPRY3 may underpin a subset of autism cases.

Textual criticism and medieval Irish studies

Many textual scholars will be aware that the title of the present thesis has been composed in a conscious revisionary relation to Tim William Machan’s influential Textual Criticism and Middle English Texts. (Tim William Machan, Textual Criticism and Middle English Texts (Charlottesville, 1994)). The primary subjects of Machan’s study are works written in English between the fourteenth and sixteenth centuries, the latter part of the period conventionally labelled Middle English. In contrast, the works with which I am primarily concerned are those written by scholars of Old and Middle Irish in the nineteenth, twentieth and twenty-first centuries. Where Machan aims to articulate the textual and cultural factors that characterise Middle English works as Middle English, the purposes of this thesis are (a) to identify the underlying ideological and epistemological perspectives which have informed much of the way in which medieval Irish documents and texts are rendered into modern editions, and (b) to begin to place the editorial theory and methodology of medieval Irish studies within the broader context of Biblical, medieval and modern textual criticism. Hence, the title is Textual Criticism and Medieval Irish Studies, rather than Textual Criticism and Medieval Irish Texts

Content-aware compression for big textual data analysis

A substantial amount of information on the Internet is present in the form of text. The value of this semi-structured and unstructured data has been widely acknowledged, with consequent scientific and commercial exploitation. The ever-increasing data production, however, pushes data analytic platforms to their limit. This thesis proposes techniques for more efficient textual big data analysis suitable for the Hadoop analytic platform. This research explores the direct processing of compressed textual data. The focus is on developing novel compression methods with a number of desirable properties to support text-based big data analysis in distributed environments. The novel contributions of this work include the following. Firstly, a Content-aware Partial Compression (CaPC) scheme is developed. CaPC makes a distinction between informational and functional content in which only the informational content is compressed. Thus, the compressed data is made transparent to existing software libraries which often rely on functional content to work. Secondly, a context-free bit-oriented compression scheme (Approximated Huffman Compression) based on the Huffman algorithm is developed. This uses a hybrid data structure that allows pattern searching in compressed data in linear time. Thirdly, several modern compression schemes have been extended so that the compressed data can be safely split with respect to logical data records in distributed file systems. Furthermore, an innovative two layer compression architecture is used, in which each compression layer is appropriate for the corresponding stage of data processing. Peripheral libraries are developed that seamlessly link the proposed compression schemes to existing analytic platforms and computational frameworks, and also make the use of the compressed data transparent to developers. The compression schemes have been evaluated for a number of standard MapReduce analysis tasks using a collection of real-world datasets. In comparison with existing solutions, they have shown substantial improvement in performance and significant reduction in system resource requirements.