Genomic resources for a commercial flatfish, the Senegalese sole (Solea senegalensis): EST sequencing, oligo microarray design, and development of the Soleamold bioinformatic platform.

BACKGROUND: The Senegalese sole, Solea senegalensis, is a highly prized flatfish of growing commercial interest for aquaculture in Southern Europe. However, despite the industrial production of Senegalese sole being hampered primarily by lack of information on the physiological mechanisms involved in reproduction, growth and immunity, very limited genomic information is available on this species. RESULTS: Sequencing of a S. senegalensis multi-tissue normalized cDNA library, from adult tissues (brain, stomach, intestine, liver, ovary, and testis), larval stages (pre-metamorphosis, metamorphosis), juvenile stages (post-metamorphosis, abnormal fish), and undifferentiated gonads, generated 10,185 expressed sequence tags (ESTs). Clones were sequenced from the 3'-end to identify isoform specific sequences. Assembly of the entire EST collection into contigs gave 5,208 unique sequences of which 1,769 (34%) had matches in GenBank, thus showing a low level of redundancy. The sequence of the 5,208 unigenes was used to design and validate an oligonucleotide microarray representing 5,087 unique Senegalese sole transcripts. Finally, a novel interactive bioinformatic platform, Soleamold, was developed for the Senegalese sole EST collection as well as microarray and ISH data. CONCLUSION: New genomic resources have been developed for S. senegalensis, an economically important fish in aquaculture, which include a collection of expressed genes, an oligonucleotide microarray, and a publicly available bioinformatic platform that can be used to study gene expression in this species. These resources will help elucidate transcriptional regulation in wild and captive Senegalese sole for optimization of its production under intensive culture conditions.

A roadside study of observable driver distractions.

OBJECTIVE: This study investigated the prevalence of observable distractions while driving and the effect of drivers' characteristics and time-related variables on their prevalence. METHODS: Using roadside observation, 2 independent observers collected data at 4 randomly selected locations in St. Albans, UK. RESULTS: Of the 10,984 drivers observed, 16.8% were engaged in a secondary task, with talking to passengers being the most common distraction (8.8%), followed by smoking (1.9%) and talking on a hands-free mobile phone (1.7%). An additional 1.0% were observed talking on a handheld phone, and the rest of the distractions (e.g., texting, drinking) were recorded in less than 1% of the drivers observed. Gender-related differences were found for a number of different distractions (i.e., talking to passengers, drinking, and handheld mobile phone conversations), but age emerged as a significant predictor for most secondary tasks, including talking to passengers, smoking, hands-free mobile phone use, handheld mobile phone use, texting/keying numbers, drinking, and engagement in any type of distraction (all distractions combined). The overall pattern for age was that middle-aged and older drivers were less likely to be distracted than younger drivers. CONCLUSIONS: This work provides further evidence of the relatively high rate of distracted driving in the UK. The findings clearly indicate that younger drivers are more likely to drive distracted, which probably contributes to their higher crash rates.