A Galaxy-based bioinformatics pipeline for optimised, streamlined microsatellite development from Illumina next-generation sequencing data

© 2016, The Author(s). Microsatellites are useful tools for ecologists and conservationist biologists, but are taxa-specific and traditionally expensive and time-consuming to develop. New methods using next-generation sequencing (NGS) have reduced these problems, but the plethora of software available for processing NGS data may cause confusion and difficulty for researchers new to the field of bioinformatics. We developed a bioinformatics pipeline for microsatellite development from Illumina paired-end sequences, which is packaged in the open-source bioinformatics tool Galaxy. This optimises and streamlines the design of a microsatellite panel and provides a user-friendly graphical user interface. The pipeline utilises existing programs along with our own novel program and wrappers to: quality-filter and trim reads (Trimmomatic); generate sequence quality reports (FastQC); identify potentially-amplifiable microsatellite loci (Pal_finder); design primers (Primer3); assemble pairs of reads to enhance marker amplification success rates (PANDAseq); and filter optimal loci (Pal_filter). The complete pipeline is freely available for use via a pre-configured Galaxy instance, accessible at https://palfinder.ls.manchester.ac.uk

Information Flows in Community-Based Monitoring Exercises in the Ecuadorian Amazon

Community-based monitoring schemes provide alternatives to costly scientific monitoring projects. While evidence shows that local community inhabitants can consistently measure environmental changes, few studies have examined how learned monitoring skills get passed on within communities. Here, we trained members of indigenous Kichwa communities in the Ecuadorian Amazon to measure fern and dung beetle species richness and examined how well they could pass on the information they had learned to other members of their community. We subsequently compared locally gathered species richness data to estimates gathered by trained biologists. Our results provide further evidence that devolved monitoring protocols can provide similar data to that gathered by scientists. In addition, our results show that local inhabitants can effectively pass on learned information to other community members, which is particularly important for the longevity of community-based monitoring initiatives

Testing the accuracy of non-experts in biodiversity monitoring exercises using fern species richness in the Ecuadorian Amazon

Assessing environmental change is often constrained by time, money and expertise. Community-based monitoring schemes attempt to address these limitations by providing local communities with the skills to measure changes in natural resources and contribute locally relevant information for local and regional management decisions. Despite the increasing popularity of community-based monitoring schemes, there is little information about the accuracy of the data they produce. In this study we use visual guides and hands-on training to teach groups of leaders from local communities in the Ecuadorian Amazon to measure the species richness of ferns. We compare their results to data obtained by experienced field biologists and show strong positive correlations in species richness estimates between the results obtained by groups receiving visual guides, groups receiving hands-on training and biologists. Our results show that, even with relatively little training, communities can use simple and cost-effective methodologies to yield data that accurately reflect levels of species richness. © 2011 Springer Science+Business Media B.V

Data from: Evaluating tools for the spatial management of fisheries

1. The ability to define the spatial dynamics of fish stocks is critical to fisheries management. Combating illegal, unreported and unregulated (IUU) fishing and the implementation of area based management through physical patrols and port side controls are growing areas of management attention. Augmenting the existing approaches to fisheries management with forensic techniques has the potential to increase compliance and enforcement success rates. 2. We tested the accuracy of three techniques that can be used to identify geographic origin (genotyping, otolith microchemistry and morphometrics). We used fish caught from three fishing grounds separated by a minimum of 5km and a maximum of 60km to list the accuracy of these approaches at relatively small spatial scales. 3. Using nearest-neighbor analyses, morphometric analysis was the most accurate (79.5%) in assigning individual fish to their fishing ground of origin. Neither otolith microchemistry (54.0%) or genetic analyses (52.4%) had sufficient assignment accuracy at the spatial scales we examined. 4. The combination of accuracy and minimal resource requirements make morphometric analyses a promising tool for assessing compliance with area based fishing restrictions at the scale of kilometers and have promising application especially in small scale fisheries through to community-based management approaches where technical and financial resources are limited.22-Jun-201

Isolation and characterization of 10 polymorphic microsatellite loci for the endangered Galapagos-endemic whitespotted sandbass (Paralabrax albomaculatus)

The white-spotted sandbass (Paralabrax albomaculatus) is a commercially important species in the Galapagos Marine Reserve, but is classified as endangered in the IUCN Red List. For this study, 10 microsatellite loci were isolated and characterized using Illumina paired-end sequencing. These loci can be used for genetic studies of population structure and connectivity to aid in the management of the white-spotted sandbass and other closely-related species. The 10 characterized loci were polymorphic, with 11–49 alleles per locus, and observed heterozygosity ranged from 0.575 to 0.964. This set of markers is the first to be developed for this species

Contribution of common and rare species to general patterns of species richness.

<p>Solid lines: Commonest species. Dashed lines: Rarest species. Subsets of species were constructed by ranking species according to relative abundances from common to rare or rare to common. Subsets were then successively correlated to overall species richness. CT = Control transects, HH = Household transects.</p

Correlation between total species richness, and rare and common species.

*<p>denotes significance after Bonferroni correction.</p

Differences in NDVI, canopy cover and species richness.

<p>A) Differences in NDVI and canopy cover (gap fraction). B) Differences in epiphytic fern species. C) Differences in leaf litter frogs. D) Differences in dung beetles. Solid lines represent all species while dashed and dotter lines represent the 25% commonest and 25% rarest subsets. With the exception of NDVI in A), which also includes individual data points, data are presented as means with error bars representing one standard error. Points not connected by the same letter denote single degree of freedom contrast tests that differ significantly after Bonferroni correction. HH = Household transects, CT = Control transects.</p

Correlation results between rare and common species.

*<p>denotes significance after Bonferroni correction.</p