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Shepherd, S. J.

Publications and source records attributed to Shepherd, S. J..

2 recordsLinked to original sources

The G-box transcriptional regulatory code in Arabidopsis

Plants have significantly more transcription factor (TF) families than animals and fungi, and plant TF families tend to contain more genes--these expansions are linked to adaptation to environmental stressors (1, 2). Many TF family members bind to similar or identical sequence motifs, such as G-boxes (CACGTG), so it is difficult to predict regulatory relationships. We determine that the flanking sequences near G-boxes help determine in vitro specificity, but that this is insufficient to predict the transcription pattern of genes near G-boxes. Therefore, we construct a gene regulatory network that identifies the set of bZIPs and bHLHs that are most predictive of the gene expression of genes downstream of perfect G-boxes. This network accurately predicts transcriptional patterns and reconstructs known regulatory subnetworks. Finally, we present Ara-BOX-cis (araboxcis.org), a website that provides interactive visualisations of the G-box regulatory network, a useful resource for generating predictions for gene regulatory relations.

plant biology

Integrating Patient And Whole Genome Sequencing Data To Provide Insights Into The Epidemiology Of Seasonal Influenza A(H3N2) Viruses

Genetic surveillance of seasonal influenza is largely focused upon sequencing of the haemagglutinin gene. Consequently, our understanding of the contribution of the remaining seven gene segments to the evolution and epidemiological dynamics of seasonal influenza is relatively limited. The increased availability of next generation sequencing technologies allows rapid and economic whole genome sequencing (WGS). Here, 150 influenza A(H3N2) positive clinical specimens with linked epidemiological data, from the 2014/15 season in Scotland, were sequenced directly using both Sanger sequencing of the HA1 region and WGS using the Illumina MiSeq platform. Sequences generated by both methods were highly consistent and WGS provided on average >90% whole genome coverage. As reported in other European countries during 2014/15, all strains belonged to genetic group 3C, with subgroup 3C.2a predominating. Inter-subgroup reassortants were identified (9%), including three 3C.3 viruses descended from a single reassortment event, which had persisted in the population. Significant phylogenetic associations with cases of severe acute respiratory illness observed herein warrant further investigation. Severe cases were also more likely to be associated with reassortant viruses (odds ratio: 4.4 (1.3-15.5)) and occur later in the season. These results suggest that increased levels of WGS, linked to clinical and epidemiological data, could improve influenza surveillance.

microbiology