The development of 20 microsatellite loci for the Australian marine mollusk, Donax deltoides, through next generation DNA sequencing

 Next Generation DNA sequencing was used to develop a suite of microsatellite markers for the marine mollusk, Donax deltoides. A total of 20 polymorphic loci were identified and 12 characterized using 30 individuals from a single population (Venus Bay) in south eastern Australia. We observed moderate to high genetic variation across most loci (mean number of alleles per locus = 7.3; mean heterozygosity = 0.633) with only a single locus (Ddel32) displaying significant deviation from Hardy–Weinberg equilibrium. Marker independence was confirmed with tests for linkage disequilibrium, however two loci were found to be influenced by null alleles. The 10 viable markers characterized in the present study provide a valuable resource for future population genetic assessments and fisheries management of D. deltoides in Australia.

Diversity of zooplankton assemblages at Station L4, Western English Channel, measured using next generation DNA sequencing

Background: Zooplankton play an important role in our oceans, in biogeochemical cycling and providing a food source for commercially important fish larvae. However, difficulties in correctly identifying zooplankton hinder our understanding of their roles in marine ecosystem functioning, and can prevent detection of long term changes in their community structure. The advent of massively parallel Next Generation Sequencing technology allows DNA sequence data to be recovered directly from whole community samples. Here we assess the ability of such sequencing to quantify the richness and diversity of a mixed zooplankton assemblage from a productive monitoring site in the Western English Channel. Methodology/Principle Findings: Plankton WP2 replicate net hauls (200 µm) were taken at the Western Channel Observatory long-term monitoring station L4 in September 2010 and January 2011. These samples were analysed by microscopy and metagenetic analysis of the 18S nuclear small subunit ribosomal RNA gene using the 454 pyrosequencing platform. Following quality control a total of 419,042 sequences were obtained for all samples. The sequences clustered in to 205 operational taxonomic units using a 97% similarity cut-off. Allocation of taxonomy by comparison with the National Centre for Biotechnology Information database identified 138 OTUs to species level, 11 to genus level and 1 to order, <2.5% of sequences were classified as unknowns. By comparison a skilled microscopic analyst was able to routinely enumerate only 75 taxonomic groups. Conclusions: The percentage of OTUs assigned to major eukaryotic taxonomic groups broadly aligns between the metagenetic and morphological analysis and are dominated by Copepoda. However, the metagenetics reveals a previously hidden taxonomic richness, especially for Copepoda and meroplankton such as Bivalvia, Gastropoda and Polychaeta. It also reveals rare species and parasites. We conclude that Next Generation Sequencing of 18S amplicons is a powerful tool for estimating diversity and species richness of zooplankton communities.

Microsatellite loci and the complete mitochondrial DNA sequence characterized through next generation sequencing and de novo genome assembly for the critically endangered orange-bellied parrot, Neophema chrysogaster

A suite of polymorphic microsatellite markers and the complete mitochondrial genome sequence was developed by next generation sequencing (NGS) for the critically endangered orange-bellied parrot, Neophema chrysogaster. A total of 14 polymorphic loci were identified and characterized using DNA extractions representing 40 individuals from Melaleuca, Tasmania, sampled in 2002. We observed moderate genetic variation across most loci (mean number of alleles per locus = 2.79; mean expected heterozygosity = 0.53) with no evidence of individual loci deviating significantly from Hardy-Weinberg equilibrium. Marker independence was confirmed with tests for linkage disequilibrium, and analyses indicated no evidence of null alleles across loci. De novo and reference-based genome assemblies performed using MIRA were used to assemble the N. chrysogaster mitochondrial genome sequence with mean coverage of 116-fold (range 89 to 142-fold). The mitochondrial genome consists of 18,034 base pairs, and a typical metazoan mitochondrial gene content consisting of 13 protein-coding genes, 2 ribosomal subunit genes, 22 transfer RNAs, and a single large non-coding region (control region). The arrangement of mitochondrial genes is also typical of Avian taxa. The annotation of the mitochondrial genome and the characterization of 14 microsatellite markers provide a valuable resource for future genetic monitoring of wild and captive N. chrysogaster populations. As found previously, NGS provides a rapid, low cost and reliable method for polymorphic nuclear genetic marker development and determining complete mitochondrial genome sequences when only a fraction of a genome is sequenced.

SNP discovery using Next Generation Transcriptomic Sequencing in Atlantic herring (Clupea harengus)

The introduction of Next Generation Sequencing (NGS) has revolutionised population genetics, providing studies of non-model species with unprecedented genomic coverage, allowing evolutionary biologists to address questions previously far beyond the reach of available resources. Furthermore, the simple mutation model of Single Nucleotide Polymorphisms (SNPs) permits cost-effective high-throughput genotyping in thousands of individuals simultaneously. Genomic resources are scarce for the Atlantic herring (Clupea harengus), a small pelagic species that sustains high revenue fisheries. This paper details the development of 578 SNPs using a combined NGS and high-throughput genotyping approach. Eight individuals covering the species distribution in the eastern Atlantic were bar-coded and multiplexed into a single cDNA library and sequenced using the 454 GS FLX platform. SNP discovery was performed by de novo sequence clustering and contig assembly, followed by the mapping of reads against consensus contig sequences. Selection of candidate SNPs for genotyping was conducted using an in silico approach. SNP validation and genotyping were performed simultaneously using an Illumina 1,536 GoldenGate assay. Although the conversion rate of candidate SNPs in the genotyping assay cannot be predicted in advance, this approach has the potential to maximise cost and time efficiencies by avoiding expensive and time-consuming laboratory stages of SNP validation. Additionally, the in silico approach leads to lower ascertainment bias in the resulting SNP panel as marker selection is based only on the ability to design primers and the predicted presence of intron-exon boundaries. Consequently SNPs with a wider spectrum of minor allele frequencies (MAFs) will be genotyped in the final panel. The genomic resources presented here represent a valuable multi-purpose resource for developing informative marker panels for population discrimination, microarray development and for population genomic studies in the wild.

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

The development of 10 novel polymorphic microsatellite markers through next generation sequencing and a preliminary population genetic analysis for the endangered Glenelg spiny crayfish, Euastacus bispinosus

The Glenelg spiny crayfish, Euastacus bispinosus, is an iconic freshwater invertebrate of south eastern Australia and listed as 'endangered' under the Environment Protection and Biodiversity Conservation Act 1999, and 'vulnerable' under the International Union for Conservation of Nature's Red List. The species has suffered major population declines as a result of over-fishing, low environmental flows, the introduction of invasive fish species and habitat degradation. In order to develop an effective conservation strategy, patterns of gene flow, genetic structure and genetic diversity across the species distribution need to be clearly understood. In this study we develop a suite of polymorphic microsatellite markers by next generation sequencing. A total of 15 polymorphic loci were identified and 10 characterized using 22 individuals from the lower Glenelg River. We observed low to moderate genetic variation across most loci (mean number of alleles per locus = 2.80; mean expected heterozygosity = 0.36) with no evidence of individual loci deviating significantly from Hardy-Weinberg equilibrium. Marker independence was confirmed with tests for linkage disequilibrium, and analyses indicated no evidence of null alleles across loci. Individuals from two additional sites (Crawford River, Victoria; Ewens Ponds Conservation Park, South Australia) were genotyped at all 10 loci and a preliminary investigation of genetic diversity and population structure was undertaken. Analyses indicate high levels of genetic differentiation among sample locations (F ST = 0.49), while the Ewens Ponds population is genetically homogeneous, indicating a likely small founder group and ongoing inbreeding. Management actions will be needed to restore genetic diversity in this and possibly other at risk populations. These markers will provide a valuable resource for future population genetic assessments so that an effective framework can be developed for implementing conservation strategies for E. bispinosus.

Sequenciamento de DNA de nova geração e suas aplicações na genômica de plantas

As plataformas de sequenciamento de nova geração são uma alternativa poderosa para estudos de genômica estrutural e funcional. Na genômica de plantas, os trabalhos com as novas plataformas têm sido destinados ao sequenciamento de transcritos, ressequenciamento ou sequenciamento de novo de genomas plastidiais. Neste trabalho, são detalhadas as tecnologias das plataformas mais utilizadas atualmente, bem como é revisada a aplicação dessas tecnologias na genômica estrutural e funcional de plantas.

Genetic Structure of the Florida Key Tree Cactus, Pilosocereus robinii, using Restriction Site associated DNA (RAD) markers

Rare plant conservation efforts must utilize current genetic methods to ensure the evolutionary potential of populations is preserved. One such effort involves the Key Tree Cactus, Pilosocereus robinii, which is an endangered columnar cactus native to the Florida Keys. The populations have precipitously declined over the past decade because of habitat loss and increasing soil salinity from rising sea levels and storm surge. Next-generation DNA sequencing was used to assess the genetic structure of the populations. Twenty individuals representative of both wild and extirpated cacti were chosen for Restriction Site Associated DNA (RAD) analysis. Samples processed using the HindIII and NotIII restriction enzymes produced 82,382,440 high quality reads used for genetic mapping, from which 5,265 Single Nucleotide Polymorphisms (SNPs) were discovered. The analysis revealed that the Keys’ populations are closely related with little population differentiation. In addition, the populations display evidence of inbreeding and low genetic diversity.

BarraCUDA - a fast short read sequence aligner using graphics processing units.

BACKGROUND: With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. FINDINGS: Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. CONCLUSIONS: BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.BarraCUDA is currently available from http://seqbarracuda.sf.net.

Dairy-Met: compositional metagenomic analysis of milk and cheeses

Unpasteurised milk and many cheeses contain a diverse microbiological population. These microorganisms play important roles in dairy foods and can, for example, contribute to the development of flavours and aromas, determine safety, cause spoilage or enhance the health of the consumer. It is thus important to understand thoroughly the microorganisms present in these food types. Traditional culture dependent and culture-independent methods have provided much detail regarding the microbial content of dairy foods. However, the development of next-generation DNA sequencing technologies has revolutionised our knowledge of complex microbial environments. Throughout this thesis we observe the benefits of applying these technologies to provide a detailed understanding of the bacterial content of dairy foods, including those present in milk pre- and post-pasteurisation, Irish farmhouse cheeses and commercially produced cheeses which encounter a discolouration defect, as well as to study genomic changes in microbes associated with dairy foods. Through the application of these state-of-the-art technologies we identified the presence of microorganisms not previously associated with dairy foods.

Syndrome du QT long: étude clinique à l’Institut Cardiologique de Montréal et recherche de nouvelles variantes causales par séquençage à haut débit

Le syndrome du QT long congénital (LQTS) est une canalopathie génétique, à l’origine de syncopes et mort subite. Le dépistage génétique identifie des variantes génétiques dans 50-70% des cas, suggérant l’implication d’autres gènes. Nous avons recueilli les caractéristiques des patients avec un LQTS à l’ICM, et recruté 12 patients avec un génotype négatif pour le LQTS pour un séquençage à haut débit des exons afin d’identifier de nouvelles variantes causales. Nous avons développé une approche analytique par étapes : (1) les gènes connus du, (2) les gènes dans des loci identifiés par des études d’association sur le QT, et (3) les gènes montrant la même variante chez plusieurs patients. L’analyse génétique a identifié de nouvelles variantes dans: (1) KCNJ2, ANK2 et AKAP9, et (2) dans NOS1AP. (3) Deux patientes avec des phénotypes semblables présentent la même variante homozygote dans TECRL, un nouveau gène candidat dont le rôle est inconnu.

STATISTICAL METHODS FOR RARE AND COMMON VARIANT ASSOCIATION STUDIES

Complex human diseases are a major challenge for biological research. The goal of my research is to develop effective methods for biostatistics in order to create more opportunities for the prevention and cure of human diseases. This dissertation proposes statistical technologies that have the ability of being adapted to sequencing data in family-based designs, and that account for joint effects as well as gene-gene and gene-environment interactions in the GWA studies. The framework includes statistical methods for rare and common variant association studies. Although next-generation DNA sequencing technologies have made rare variant association studies feasible, the development of powerful statistical methods for rare variant association studies is still underway. Chapter 2 demonstrates two adaptive weighting methods for rare variant association studies based on family data for quantitative traits. The results show that both proposed methods are robust to population stratification, robust to the direction and magnitude of the effects of causal variants, and more powerful than the methods using weights suggested by Madsen and Browning [2009]. In Chapter 3, I extended the previously proposed test for Testing the effect of an Optimally Weighted combination of variants (TOW) [Sha et al., 2012] for unrelated individuals to TOW &ndash F, TOW for Family &ndash based design. Simulation results show that TOW &ndash F can control for population stratification in wide range of population structures including spatially structured populations, is robust to the directions of effect of causal variants, and is relatively robust to percentage of neutral variants. In GWA studies, this dissertation consists of a two &ndash locus joint effect analysis and a two-stage approach accounting for gene &ndash gene and gene &ndash environment interaction. Chapter 4 proposes a novel two &ndash stage approach, which is promising to identify joint effects, especially for monotonic models. The proposed approach outperforms a single &ndash marker method and a regular two &ndash stage analysis based on the two &ndash locus genotypic test. In Chapter 5, I proposed a gene &ndash based two &ndash stage approach to identify gene &ndash gene and gene &ndash environment interactions in GWA studies which can include rare variants. The two &ndash stage approach is applied to the GAW 17 dataset to identify the interaction between KDR gene and smoking status.

Non-phenotypic tests to detect and characterize antibiotic resistance mechanisms in Enterobacteriaceae

In the past 2 decades, we have observed a rapid increase of infections due to multidrug-resistant Enterobacteriaceae. Regrettably, these isolates possess genes encoding for extended-spectrum β-lactamases (e.g., blaCTX-M, blaTEM, blaSHV) or plasmid-mediated AmpCs (e.g., blaCMY) that confer resistance to last-generation cephalosporins. Furthermore, other resistance traits against quinolones (e.g., mutations in gyrA and parC, qnr elements) and aminoglycosides (e.g., aminoglycosides modifying enzymes and 16S rRNA methylases) are also frequently co-associated. Even more concerning is the rapid increase of Enterobacteriaceae carrying genes conferring resistance to carbapenems (e.g., blaKPC, blaNDM). Therefore, the spread of these pathogens puts in peril our antibiotic options. Unfortunately, standard microbiological procedures require several days to isolate the responsible pathogen and to provide correct antimicrobial susceptibility test results. This delay impacts the rapid implementation of adequate antimicrobial treatment and infection control countermeasures. Thus, there is emerging interest in the early and more sensitive detection of resistance mechanisms. Modern non-phenotypic tests are promising in this respect, and hence, can influence both clinical outcome and healthcare costs. In this review, we present a summary of the most advanced methods (e.g., next-generation DNA sequencing, multiplex PCRs, real-time PCRs, microarrays, MALDI-TOF MS, and PCR/ESI MS) presently available for the rapid detection of antibiotic resistance genes in Enterobacteriaceae. Taking into account speed, manageability, accuracy, versatility, and costs, the possible settings of application (research, clinic, and epidemiology) of these methods and their superiority against standard phenotypic methods are discussed.