Dealing with paralogy in RADseq data: in silico detection and single nucleotide polymorphism validation in Robinia pseudoacacia L.

peer reviewedThe RADseq technology allows researchers to efficiently develop thousands of polymorphic loci across multiple individuals with little or no prior information on the genome. However, many questions remain about the biases inherent to this technology. Notably, sequence misalignments arising from paralogy may affect the development of single nucleotide polymorphism (SNP) markers and the estimation of genetic diversity. We evaluated the impact of putative paralog loci on genetic diversity estimation during the development of SNPs from a RADseq dataset for the nonmodel tree species Robinia pseudoacacia L. We sequenced nine genotypes and analyzed the frequency of putative paralogous RAD loci as a function of both the depth of coverage and the mismatch threshold allowed between loci. Putative paralogy was detected in a very variable number of loci, from 1% to more than 20%, with the depth of coverage having a major influence on the result. Putative paralogy artificially increased the observed degree of polymorphism and resulting estimates of diversity. The choice of the depth of coverage also affected diversity estimation and SNP validation: A low threshold decreased the chances of detecting minor alleles while a high threshold increased allelic dropout. SNP validation was better for the low threshold (4×) than for the high threshold (18×) we tested. Using the strategy developed here, we were able to validate more than 80% of the SNPs tested by means of individual genotyping, resulting in a readily usable set of 330 SNPs, suitable for use in population genetics applications

Toward the Integrated Marine Debris Observing System

Plastics and other artificial materials pose new risks to the health of the ocean. Anthropogenic debris travels across large distances and is ubiquitous in the water and on shorelines, yet, observations of its sources, composition, pathways, and distributions in the ocean are very sparse and inaccurate. Total amounts of plastics and other man-made debris in the ocean and on the shore, temporal trends in these amounts under exponentially increasing production, as well as degradation processes, vertical fluxes, and time scales are largely unknown. Present ocean circulation models are not able to accurately simulate drift of debris because of its complex hydrodynamics. In this paper we discuss the structure of the future integrated marine debris observing system (IMDOS)thatisrequiredtoprovidelong-termmonitoringofthestateofthisanthropogenic pollution and support operational activities to mitigate impacts on the ecosystem and on the safety of maritime activity. The proposed observing system integrates remote sensing and in situ observations. Also, models are used to optimize the design of the system and, in turn, they will be gradually improved using the products of the system. Remote sensing technologies will provide spatially coherent coverage and consistent surveying time series at local to global scale. Optical sensors, including high-resolution imaging, multi- and hyperspectral, fluorescence, and Raman technologies, as well as SAR will be used to measure different types of debris. They will be implemented in a variety of platforms, from hand-held tools to ship-, buoy-, aircraft-, and satellite-based sensors. A network of in situ observations, including reports from volunteers, citizen scientists and ships of opportunity, will be developed to provide data for calibration/validation of remote sensors and to monitor the spread of plastic pollution and other marine debris. IMDOS will interact with other observing systems monitoring physical, chemical, and biological processes in the ocean and on shorelines as well as the state of the ecosystem, maritime activities and safety, drift of sea ice, etc. The synthesized data will support innovative multi-disciplinary research and serve a diverse community of users

The genome and population genomics of allopolyploid Coffea arabica reveal the diversification history of modern coffee cultivars.

Coffea arabica, an allotetraploid hybrid of Coffea eugenioides and Coffea canephora, is the source of approximately 60% of coffee products worldwide, and its cultivated accessions have undergone several population bottlenecks. We present chromosome-level assemblies of a di-haploid C. arabica accession and modern representatives of its diploid progenitors, C. eugenioides and C. canephora. The three species exhibit largely conserved genome structures between diploid parents and descendant subgenomes, with no obvious global subgenome dominance. We find evidence for a founding polyploidy event 350,000–610,000 years ago, followed by several pre-domestication bottlenecks, resulting in narrow genetic variation. A split between wild accessions and cultivar progenitors occurred ~30.5 thousand years ago, followed by a period of migration between the two populations. Analysis of modern varieties, including lines historically introgressed with C. canephora, highlights their breeding histories and loci that may contribute to pathogen resistance, laying the groundwork for future genomics-based breeding of C. arabica

Breakdown of phylogenetic signal: a survey of microsatellite densities in 454 shotgun sequences from 154 non model Eukaryote species

Microsatellites are ubiquitous in Eukaryotic genomes. A more complete understanding of their origin and spread can be gained from a comparison of their distribution within a phylogenetic context. Although information for model species is accumulating rapidly, it is insufficient due to a lack of species depth, thus intragroup variation is necessarily ignored. As such, apparent differences between groups may be overinflated and generalizations cannot be inferred until an analysis of the variation that exists within groups has been conducted. In this study, we examined microsatellite coverage and motif patterns from 454 shotgun sequences of 154 Eukaryote species from eight distantly related phyla (Cnidaria, Arthropoda, Onychophora, Bryozoa, Mollusca, Echinodermata, Chordata and Streptophyta) to test if a consistent phylogenetic pattern emerges from the microsatellite composition of these species. It is clear from our results that data from model species provide incomplete information regarding the existing microsatellite variability within the Eukaryotes. A very strong heterogeneity of microsatellite composition was found within most phyla, classes and even orders. Autocorrelation analyses indicated that while microsatellite contents of species within clades more recent than 200 Mya tend to be similar, the autocorrelation breaks down and becomes negative or non-significant with increasing divergence time. Therefore, the age of the taxon seems to be a primary factor in degrading the phylogenetic pattern present among related groups. The most recent classes or orders of Chordates still retain the pattern of their common ancestor. However, within older groups, such as classes of Arthropods, the phylogenetic pattern has been scrambled by the long independent evolution of the lineages.Emese Meglécz, Gabriel Nève, Ed Biffin and Michael G. Gardne

Whole-genome genotyping of grape using a panel of microsatellite

The use of microsatellite markers in large-scale genetic studies is limited by its low throughput and high cost and labor requirements. Here, we provide a panel of 45 multiplex PCRs for fast and cost-efficient genome-wide fluorescence-based microsatellite analysis in grapevine. The developed multiplex PCRs panel (with up to 15-plex) enables the scoring of 270 loci covering all the grapevine genome (9 to 20 loci/chromosome) using only 45 PCRs and sequencer runs. The 45 multiplex PCRs were validated using a diverse grapevine collection of 207 accessions, selected to represent most of the cultivated Vitis vinifera genetic diversity. Particular attention was paid to quality control throughout the whole process (assay replication, null allele detection, ease of scoring). Genetic diversity summary statistics and features of electrophoretic profiles for each studied marker are provided, as are the genotypes of 25 common cultivars that could be used as references in other studies

Exploring Pandora's Box: potential and pitfalls of low coverage genome surveys for evolutionary biology

High throughput sequencing technologies are revolutionizing genetic research. With this ‘‘rise of the machines’’, genomic sequences can be obtained even for unknown genomes within a short time and for reasonable costs. This has enabled evolutionary biologists studying genetically unexplored species to identify molecular markers or genomic regions of interest (e.g. micro- and minisatellites, mitochondrial and nuclear genes) by sequencing only a fraction of the genome. However, when using such datasets from non-model species, it is possible that DNA from non-target contaminant species such as bacteria, viruses, fungi, or other eukaryotic organisms may complicate the interpretation of the results. In this study we analysed 14 genomic pyrosequencing libraries of aquatic non-model taxa from four major evolutionary lineages. We quantified the amount of suitable micro- and minisatellites, mitochondrial genomes, known nuclear genes and transposable elements and searched for contamination from various sources using bioinformatic approaches. Our results show that in all sequence libraries with estimated coverage of about 0.02–25%, many appropriate micro- and minisatellites, mitochondrial gene sequences and nuclear genes from different KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways could be identified and characterized. These can serve as markers for phylogenetic and population genetic analyses. A central finding of our study is that several genomic libraries suffered from different biases owing to non-target DNA or mobile elements. In particular, viruses, bacteria or eukaryote endosymbionts contributed significantly (up to 10%) to some of the libraries analysed. If not identified as such, genetic markers developed from high-throughput sequencing data for non-model organisms may bias evolutionary studies or fail completely in experimental tests. In conclusion, our study demonstrates the enormous potential of low-coverage genome survey sequences and suggests bioinformatic analysis workflows. The results also advise a more sophisticated filtering for problematic sequences and non-target genome sequences prior to developing markers

A sensitive cell-based assay for the detection of residual infectious West Nile virus

Ensuring complete viral inactivation is critical for the safety of vaccines based on an inactivated virus. Detection of residual infectious virus is dependent on sensitivity of the assay, sample volume analyzed and the absence of interference with viral infection. Here we describe the development and qualification of a sensitive cell-based assay for the detection of residual infectious West Nile Virus (WNV). The results of the assay are in good agreement with the assumption that at low concentrations the number of infectious units in relatively small samples follows a Poisson distribution. The assay can detect 1 infectious unit with a confidence of 99%, provides statistical controls for interference and can easily be scaled up to test large amounts of vaccine material. Furthermore, we show equivalence in sensitivity between the cell-based assay and an in vivo assay for detection of infectious WNV. Finally, the assay has been used for successful release testing of clinical lots of inactivated WNV vaccine. Given the principle and generic setup of the method we envision broad applicability to the detection of very low concentrations of infectious viru