Rapid identification of angulata leaf mutations using next-generation sequencing

Map-based (positional) cloning has traditionally been the preferred strategy for identifying the causal genes underlying the phenotypes of mutants isolated in forward genetic screens. Massively parallel sequencing technologies are enabling the rapid cloning of genes identified in such screens. We have used a combination of linkage mapping and whole-genome re-sequencing to identify the causal mutations in four loss-of-function angulata (anu) mutants. These mutants were isolated in a screen for mutants with defects in leaf shape and leaf pigmentation. Our results show that the anu1-1, anu4-1, anu9-1 and anu12-1 mutants carry new alleles of the previously characterized SECA2, TRANSLOCON AT THE OUTER MEMBRANE OF CHLOROPLASTS 33 (TOC33), NON-INTRINSIC ABC PROTEIN 14 (NAP14) and CLP PROTEASE PROTEOLYTIC SUBUNIT 1 (CLPR1) genes. Re-sequencing the genomes of fine mapped mutants is a feasible approach that has allowed us to identify a moderate number of candidate mutations, including the one that causes the mutant phenotype, in a nonstandard genetic background. Our results indicate that anu mutations specifically affect plastid-localized proteins involved in diverse processes, such as the movement of peptides through chloroplast membranes (ANU1 and ANU4), metal homeostasis (ANU9) and protein degradation (ANU12).     

First insights into fern matK phylogeny

MatK, the only maturase gene in the land plant plastid genome, is a very popular phylogenetic marker that has been extensively applied in reconstructing angiosperm phylogeny. However, the use of matK in fern phylogeny is largely unknown, due to difficulties with amplification: ferns have lost the flanking trnK exons, typically the region used for designing stable priming sites. We developed primers that are either universal or lineage-specific that successfully amplify matK across all fern families. To evaluate whether matK is as powerful a phylogenetic marker in ferns as in angiosperms, we compared its sequence characteristics and phylogenetic performance to those of rbcL and atpA. Among these three genes, matK has the highest variability and substitution evenness, yet shows the least homoplasy. Most importantly, applying matK in fern phylogenetics better resolved relationships among families, especially within eupolypods I and II. Here we demonstrate the power of matK for fern phylogenetic reconstruction, as well as provide primers and extensive sequence data that will greatly facilitate future evolutionary studies of ferns.     

A new era of the vaginal microbiome: advances using next-generation sequencing

Until recently, bacterial species that inhabit the human vagina have been primarily studied using organism-centric approaches. Understanding how these bacterial species interact with each other and the host vaginal epithelium is essential for a more complete understanding of vaginal health. Molecular approaches have already led to the identification of uncultivated bacterial taxa associated with bacterial vaginosis. Here, we review recent studies of the vaginal microbiome and discuss how culture-independent approaches, such as applications of next-generation sequencing, are advancing the field and shifting our understanding of how vaginal health is defined. This work may lead to improved diagnostic tools and treatments for women who suffer from, or are at risk for, vaginal imbalances, pregnancy complications, and sexually acquired infections. These approaches may also transform our understanding of how host genetic factors, physiological conditions (e.g., menopause), and environmental exposures (e.g., smoking, antibiotic usage) influence the vaginal microbiome.     

New insights into adaptation and population structure of cork oak using genotyping by sequencing

Species respond to global climatic changes in a local context. Understanding this process, including its speed and intensity, is paramount due to the pace at which such changes are currently occurring. Tree species are particularly interesting to study in this regard due to their long generation times, sedentarism, and ecological and economic importance. Quercus suber L. is an evergreen forest tree species of the Fagaceae family with an essentially Western Mediterranean distribution. Despite frequent assessments of the species’ evolutionary history, large‐scale genetic studies have mostly relied on plastidial markers, whereas nuclear markers have been used on studies with locally focused sampling strategies. In this work, “Genotyping by sequencing” is used to derive 1,996 single nucleotide polymorphism markers to assess the species’ evolutionary history from a nuclear DNA perspective, gain insights into how local adaptation is shaping the species’ genetic background, and to forecast how Q. suber may respond to global climatic changes from a genetic perspective. Results reveal (a) an essentially unstructured species, where (b) a balance between gene flow and local adaptation keeps the species’ gene pool somewhat homogeneous across its distribution, but still allowing (c) variation clines for the individuals to cope with local conditions. “Risk of Non‐Adaptedness” (RONA) analyses suggest that for the considered variables and most sampled locations, (d) the cork oak should not require large shifts in allele frequencies to survive the predicted climatic changes. Future directions include integrating these results with ecological niche modeling perspectives, improving the RONA methodology, and expanding its use to other species. With the implementation presented in this work, the RONA can now also be easily assessed for other organisms.     

Next-generation sequencing offers new insights into DNA degradation

The processes underlying DNA degradation are central to various disciplines, including cancer research, forensics and archaeology. The sequencing of ancient DNA molecules on next-generation sequencing platforms provides direct measurements of cytosine deamination, depurination and fragmentation rates that previously were obtained only from extrapolations of results from in vitro kinetic experiments performed over short timescales. For example, recent next-generation sequencing of ancient DNA reveals purine bases as one of the main targets of postmortem hydrolytic damage, through base elimination and strand breakage. It also shows substantially increased rates of DNA base-loss at guanosine. In this review, we argue that the latter results from an electron resonance structure unique to guanosine rather than adenosine having an extra resonance structure over guanosine as previously suggested.     

Combinatorial analysis and algorithms for quasispecies reconstruction using next-generation sequencing

Background  

Next-generation sequencing (NGS) offers a unique opportunity for high-throughput genomics and has potential to replace Sanger sequencing in many fields, including de-novo sequencing, re-sequencing, meta-genomics, and characterisation of infectious pathogens, such as viral quasispecies. Although methodologies and software for whole genome assembly and genome variation analysis have been developed and refined for NGS data, reconstructing a viral quasispecies using NGS data remains a challenge. This application would be useful for analysing intra-host evolutionary pathways in relation to immune responses and antiretroviral therapy exposures. Here we introduce a set of formulae for the combinatorial analysis of a quasispecies, given a NGS re-sequencing experiment and an algorithm for quasispecies reconstruction. We require that sequenced fragments are aligned against a reference genome, and that the reference genome is partitioned into a set of sliding windows (amplicons). The reconstruction algorithm is based on combinations of multinomial distributions and is designed to minimise the reconstruction of false variants, called in-silico recombinants.     

Genomics through the lens of next-generation sequencing

A report on the 23rd annual meeting on 'The Biology of Genomes', 11-15 May 2010, Cold Spring Harbor, USA.     

Analysis of the genetic diversity of influenza A viruses using next-generation DNA sequencing

Background

Influenza viruses exist as a large group of closely related viral genomes, also called quasispecies. The composition of this influenza viral quasispecies can be determined by an accurate and sensitive sequencing technique and data analysis pipeline. We compared the suitability of two benchtop next-generation sequencers for whole genome influenza A quasispecies analysis: the Illumina MiSeq sequencing-by-synthesis and the Ion Torrent PGM semiconductor sequencing technique.

Results

We first compared the accuracy and sensitivity of both sequencers using plasmid DNA and different ratios of wild type and mutant plasmid. Illumina MiSeq sequencing reads were one and a half times more accurate than those of the Ion Torrent PGM. The majority of sequencing errors were substitutions on the Illumina MiSeq and insertions and deletions, mostly in homopolymer regions, on the Ion Torrent PGM. To evaluate the suitability of the two techniques for determining the genome diversity of influenza A virus, we generated plasmid-derived PR8 virus and grew this virus in vitro. We also optimized an RT-PCR protocol to obtain uniform coverage of all eight genomic RNA segments. The sequencing reads obtained with both sequencers could successfully be assembled de novo into the segmented influenza virus genome. After mapping of the reads to the reference genome, we found that the detection limit for reliable recognition of variants in the viral genome required a frequency of 0.5% or higher. This threshold exceeds the background error rate resulting from the RT-PCR reaction and the sequencing method. Most of the variants in the PR8 virus genome were present in hemagglutinin, and these mutations were detected by both sequencers.

Conclusions

Our approach underlines the power and limitations of two commonly used next-generation sequencers for the analysis of influenza virus gene diversity. We conclude that the Illumina MiSeq platform is better suited for detecting variant sequences whereas the Ion Torrent PGM platform has a shorter turnaround time. The data analysis pipeline that we propose here will also help to standardize variant calling in small RNA genomes based on next-generation sequencing data.     

Molecular diagnosis of neonatal diabetes mellitus using next-generation sequencing of the whole exome

Background

Accurate molecular diagnosis of monogenic non-autoimmune neonatal diabetes mellitus (NDM) is critical for patient care, as patients carrying a mutation in KCNJ11 or ABCC8 can be treated by oral sulfonylurea drugs instead of insulin therapy. This diagnosis is currently based on Sanger sequencing of at least 42 PCR fragments from the KCNJ11, ABCC8, and INS genes. Here, we assessed the feasibility of using the next-generation whole exome sequencing (WES) for the NDM molecular diagnosis.

Methodology/Principal Findings

We carried out WES for a patient presenting with permanent NDM, for whom mutations in KCNJ11, ABCC8 and INS and abnormalities in chromosome 6q24 had been previously excluded. A solution hybridization selection was performed to generate WES in 76 bp paired-end reads, by using two channels of the sequencing instrument. WES quality was assessed using a high-resolution oligonucleotide whole-genome genotyping array. From our WES with high-quality reads, we identified a novel non-synonymous mutation in ABCC8 (c.1455G>C/p.Q485H), despite a previous negative sequencing of this gene. This mutation, confirmed by Sanger sequencing, was not present in 348 controls and in the patient''s mother, father and young brother, all of whom are normoglycemic.

Conclusions/Significance

WES identified a novel de novo ABCC8 mutation in a NDM patient. Compared to the current Sanger protocol, WES is a comprehensive, cost-efficient and rapid method to identify mutations in NDM patients. We suggest WES as a near future tool of choice for further molecular diagnosis of NDM cases, negative for chr6q24, KCNJ11 and INS abnormalities.     

A high-throughput belowground plant diversity assay using next-generation sequencing of the trnL intron

Plant and Soil - Arbuscular mycorrhizal fungi (AMF) are ubiquitous in wetland habitats, but their diversity and distribution pattern in these habitats is poorly understood. Under varying...     

Linkage analysis in the next-generation sequencing era

Linkage analysis was developed to detect excess co-segregation of the putative alleles underlying a phenotype with the alleles at a marker locus in family data. Many different variations of this analysis and corresponding study design have been developed to detect this co-segregation. Linkage studies have been shown to have high power to detect loci that have alleles (or variants) with a large effect size, i.e. alleles that make large contributions to the risk of a disease or to the variation of a quantitative trait. However, alleles with a large effect size tend to be rare in the population. In contrast, association studies are designed to have high power to detect common alleles which tend to have a small effect size for most diseases or traits. Although genome-wide association studies have been successful in detecting many new loci with common alleles of small effect for many complex traits, these common variants often do not explain a large proportion of disease risk or variation of the trait. In the past, linkage studies were successful in detecting regions of the genome that were likely to harbor rare variants with large effect for many simple Mendelian diseases and for many complex traits. However, identifying the actual sequence variant(s) responsible for these linkage signals was challenging because of difficulties in sequencing the large regions implicated by each linkage peak. Current 'next-generation' DNA sequencing techniques have made it economically feasible to sequence all exons or the whole genomes of a reasonably large number of individuals. Studies have shown that rare variants are quite common in the general population, and it is now possible to combine these new DNA sequencing methods with linkage studies to identify rare causal variants with a large effect size. A brief review of linkage methods is presented here with examples of their relevance and usefulness for the interpretation of whole-exome and whole-genome sequence data.