A Survey of Bottlenose Dolphins (Tursiops truncatus) in the Shannon Estuary

The bottlenose dolphin Tursiops truncatus is a ubiquitous species found throughout the temperate and tropical oceans of the world. The bottlenose dolphin population that occurs in the Shannon is one of only six known resident European populations. Since 1994, a small dolphin watching industry has been operating in the estuary, with plans for expansion. The objectives of this were to a) assess the degree of residency of bottlenose dolphins in the Shannon; b) estimate the population size and assess the production of calves; c) examine the social structure of the population; d) study habitat use and e) examine the effects of boats on dolphin behaviour. Boat-based surveys and photo-identification techniques were used to derive a population estimate and to examine distribution and movements of individually identifiable dolphins over a two-year period. Land-based scan samples were used to examine behavioural activity and interactions of dolphins with all categories of boat traffic. Trips on dolphin watching boats examined whether these boats were interacting with the same individual dolphins on a trip, daily or weekly basis. Dolphins were recorded in all months of the year but with a seasonal peak between May and September. Many of the identifiable dolphins were resighted throughout the study indicating a high degree of residency. Using photo-identification and mark-recapture analyses, the population estimate for the Shannon is 113 dolphins (CV 0.14, 95% C.I. 94 - 161). The presence of neonatal calves only from July – September indicates that there is a marked breeding season for this population and that the area is important as a nursery area. Group sizes ranged from singletons to groups of 32 animals and while dolphins were seen throughout the study area, groups were frequently encountered in the narrow water at Kilcredaun and in the mouth of the estuary. A second area of concentrated sightings was identified further up-river around Moneypoint and Tarbert/Killimer. This group comprised a smaller number of individuals, and the re-encounter rate of these individuals in the same area suggests a degree of habitat partitioning. These dolphins may be more vulnerable to dolphin watching activities than the more diffuse numbers in the outer estuary. The influence of tidal cycle was recorded at Kilcredaun and at Killimer/Tarbert with a distinct peak in sightings in the four-hour period before low tide. The frequency distribution of association indices shows that there are few "strong" associations between individuals and supports the notion of a fluid and gregarious social structure. Dolphin watching boats were involved in 61.8% of all interactions with dolphin groups, higher than any other category of boat. At present, two operators make approximately 200 dolphin watching trips annually, carrying a total of 2,400 passengers per year. The operators are highly successful in locating dolphins (97%) and the tour boats rarely come into contact with each other on the water and generally search in different areas and watch different groups. The potential for land-based dolphin watching was examined and possible sites identified. The information from this study provides a basis from which sound conservation management strategies can be developed, in order to properly conserve the species and its habitat, to develop a sustainable dolphin watching industry and to develop/monitor other coastal zone industries such as oil and gas exploration and shipping development within the Shannon.Funder: Marine Institut

GRISOTTO: A greedy approach to improve combinatorial algorithms for motif discovery with prior knowledge

<p>Abstract</p> <p>Background</p> <p>Position-specific priors (PSP) have been used with success to boost EM and Gibbs sampler-based motif discovery algorithms. PSP information has been computed from different sources, including orthologous conservation, DNA duplex stability, and nucleosome positioning. The use of prior information has not yet been used in the context of combinatorial algorithms. Moreover, priors have been used only independently, and the gain of combining priors from different sources has not yet been studied.</p> <p>Results</p> <p>We extend RISOTTO, a combinatorial algorithm for motif discovery, by post-processing its output with a greedy procedure that uses prior information. PSP's from different sources are combined into a scoring criterion that guides the greedy search procedure. The resulting method, called GRISOTTO, was evaluated over 156 yeast TF ChIP-chip sequence-sets commonly used to benchmark prior-based motif discovery algorithms. Results show that GRISOTTO is at least as accurate as other twelve state-of-the-art approaches for the same task, even without combining priors. Furthermore, by considering combined priors, GRISOTTO is considerably more accurate than the state-of-the-art approaches for the same task. We also show that PSP's improve GRISOTTO ability to retrieve motifs from mouse ChiP-seq data, indicating that the proposed algorithm can be applied to data from a different technology and for a higher eukaryote.</p> <p>Conclusions</p> <p>The conclusions of this work are twofold. First, post-processing the output of combinatorial algorithms by incorporating prior information leads to a very efficient and effective motif discovery method. Second, combining priors from different sources is even more beneficial than considering them separately.</p

A Primer on Regression Methods for Decoding cis-Regulatory Logic

The rapidly emerging field of systems biology is helping us to understand the molecular determinants of phenotype on a genomic scale [1]. Cis-regulatory elements are major sequence-based determinants of biological processes in cells and tissues [2]. For instance, during transcriptional regulation, transcription factors (TFs) bind to very specific regions on the promoter DNA [2,3] and recruit the basal transcriptional machinery, which ultimately initiates mRNA transcription (Figure 1A). Learning cis-Regulatory Elements from Omics Data A vast amount of work over the past decade has shown that omics data can be used to learn cis-regulatory logic on a genome-wide scale [4-6]--in particular, by integrating sequence data with mRNA expression profiles. The most popular approach has been to identify over-represented motifs in promoters of genes that are coexpressed [4,7,8]. Though widely used, such an approach can be limiting for a variety of reasons. First, the combinatorial nature of gene regulation is difficult to explicitly model in this framework. Moreover, in many applications of this approach, expression data from multiple conditions are necessary to obtain reliable predictions. This can potentially limit the use of this method to only large data sets [9]. Although these methods can be adapted to analyze mRNA expression data from a pair of biological conditions, such comparisons are often confounded by the fact that primary and secondary response genes are clustered together--whereas only the primary response genes are expected to contain the functional motifs [10]. A set of approaches based on regression has been developed to overcome the above limitations [11-32]. These approaches have their foundations in certain biophysical aspects of gene regulation [26,33-35]. That is, the models are motivated by the expected transcriptional response of genes due to the binding of TFs to their promoters. While such methods have gathered popularity in the computational domain, they remain largely obscure to the broader biology community. The purpose of this tutorial is to bridge this gap. We will focus on transcriptional regulation to introduce the concepts. However, these techniques may be applied to other regulatory processes. We will consider only eukaryotes in this tutorial

Patients accessing ambulatory care for HIV-infection: epidemiology and prevalence assessment.

This study describes the demographics and treatment status of HIV-infected adults accessing ambulatory care in the Republic of Ireland and estimates diagnosed HIV prevalence rates. 3254 HIV-infected adults attended 1 of the 6 specialist HIV centres in the 12- month period 1st July 2009 to 30th June 2010. 2023/3254 (62%) were male, 1761/3133 (56%) Irish and 1048/3133 (34%) African. 1924/3098 (62%) resided in the Dublin area. The mean age was 39.8 years (SD 9.3); probable route of acquisition was available for 2898/3254 (89%); heterosexual acquisition accounted for 1442 (50%), MSM 777 (27%) and IDU 598 (21%). 2574/3202 (80%) were on highly active antiretroviral therapy (HAART). Of these 87% had HIV-RNA levels \u3c 50cpm and 94% \u3c 500cpm. The HIV diagnosed prevalence rate is estimated at 1.09/1000 nationally and at 2.25/1000 in the Dublin area for 15-59 year olds

A comparison of hepatitis B seroepidemiology in ten European countries

To inform current and future vaccination strategies, we describe the seroepidemiology of hepatitis B virus (HBV) infection in ten representative European countries using standardized serology that allowed international comparisons. Between 1996 and 2003, national serum banks were compiled by collecting residual sera or by community sampling; sera were then tested by each country using its preferred enzyme immunoassays and testing algorithm, and assay results were standardized. Information on current and past HBV vaccination programmes in each country was also collected. Of the ten countries, six reported low levels