Biomedical subjects

Lavinia Hyde

Publications and source records attributed to Lavinia Hyde.

3 recordsLinked to original sources

PubMed2006

Nedd4-WW domain-binding protein 5 (Ndfip1) is associated with neuronal survival after acute cortical brain injury.

Understanding the transcriptional response to neuronal injury after trauma is a necessary prelude to formulation of therapeutic strategies. We used Serial Analysis of Gene Expression (SAGE) to identify 50,000 sequence tags representing 18,000 expressed genes in the cortex 2 h after traumatic brain injury (TBI). A similar tag library was obtained from sham-operated cortex. The SAGE data were validated on biological replicates using quantitative real-time-PCR on multiple samples at 2, 6, 12, and 24 h after TBI. This analysis revealed that the vast majority of genes showed a downward trend in their pattern of expression over 24 h. This was confirmed for a subset of genes using in situ hybridization and immunocytochemistry on brain sections. Of the overexpressed genes in the trauma library, Nedd4-WW (neural precursor cell expressed, developmentally downregulated) domain-binding protein 5 (N4WBP5) (also known as Ndfip1) is strongly expressed in surviving neurons around the site of injury. Overexpression of N4WBP5 in cultured cortical neurons increased the number of surviving neurons after gene transfection and growth factor starvation compared with control transfections. These results identify N4WBP5 as a neuroprotective protein and, based on its known interaction with the ubiquitin ligase Nedd4, would suggest protein ubiquitination as a possible survival strategy in neuronal injury.

Acute Disease↗

PubMed2004

A comparative analysis of transcribed genes in the mouse hypothalamus and neocortex reveals chromosomal clustering.

The hypothalamus and neocortex are subdivisions of the mammalian forebrain, and yet, they have vastly different evolutionary histories, cytoarchitecture, and biological functions. In an attempt to define these attributes in terms of their genetic activity, we have compared their genetic repertoires by using the Serial Analysis of Gene Expression database. From a comparison of 78,784 hypothalamus tags with 125,296 neocortical tags, we demonstrate that each structure possesses a different transcriptional profile in terms of gene ontological characteristics and expression levels. Despite its more recent evolutionary history, the neocortex has a more complex pattern of gene activity. Gene identities and levels of gene expression were mapped to their chromosomal positions by using in silico definition of GC-rich and GC-poor genome bands. This analysis shows contrasting views of gene activity on a genome scale that is unique to each brain substructure. We show that genes that are more highly expressed in one tissue tend to be clustered together on a chromosomal scale, further defining the genetic identity of either the hypothalamus or neocortex. We propose that physical proximity of coregulated genes may facilitate transcriptional access to the genetic substrates of evolutionary selection that ultimately shape the functional subdivisions of the mammalian brain.

Animals↗

PubMed2004

Statistical modeling of sequencing errors in SAGE libraries.

MOTIVATION: Sequencing errors may bias the gene expression measurements made by Serial Analysis of Gene Expression (SAGE). They may introduce non-existent tags at low abundance and decrease the real abundance of other tags. These effects are increased in the longer tags generated in LongSAGE libraries. Current sequencing technology generates quite accurate estimates of sequencing error rates. Here we make use of the sequence neighborhood of SAGE tags and error estimates from the base-calling software to correct for such errors. RESULTS: We introduce a statistical model for the propagation of sequencing errors in SAGE and suggest an Expectation-Maximization (EM) algorithm to correct for them given observed sequences in a library and base-calling error estimates. We tested our method using simulated and experimental SAGE libraries. When comparing SAGE libraries, we found that sequencing errors can introduce considerable bias. High abundance tags may be falsely called as significantly differentially expressed, especially when comparing libraries with different levels of sequencing errors and/or of different size. Truly, differentially expressed tags have decreased significance as 'true'-tag counts are generally underestimated. This may alter if tags near the threshold of differential expression are called significant. Moreover, the number of different transcripts present in a library is overestimated as false tags are introduced at low abundance. Our correction method adjusts the tag counts to be closer to the true counts and is able to partly correct for biases introduced by sequencing errors. AVAILABILITY: An implementation using R is distributed as an R package. An online version is available at http://tagcalling.mbgproject.org

Algorithms↗