Cryptosporidium species and subtypes in river water and riverbed sediment using next-generation sequencing

This study uncovered the prevalence, harboured species, and subtype diversity of Cryptosporidium species in river water and its sediment from the Apies River in South Africa. Cryptosporidium spp. concentrations in freshwater and its sediment were determined using Ziehl-Neelsen staining and quantitative Polymerase Chain Reaction (qPCR) techniques. Next-generation sequencing (NGS) targeting the 60 kDa glycoprotein (gp60) gene of Cryptosporidium spp. was performed to reveal the species, subtype families and subtypes harboured in freshwater and its sediment. Although the results revealed that water samples had a higher prevalence (30%) compared with sediment (28%), the number of observable Cryptosporidium spp. oocysts in sediment samples (ranging from 4.90 to 5.81 log₁₀ oocysts per 1 Liter) was higher than that of river water samples (ranging from 4.60 to 5.58 log₁₀ oocysts per 1 L) using Ziehl-Neelsen staining. The 18S ribosomal ribonucleic acid (rRNA) gene copy of Cryptosporidium in riverbed sediments ranged from 6.03 to 7.65 log₁₀, whereas in river water, it was found to be between 4.20 and 6.79 log₁₀. Subtyping results showed that in riverbed sediments, Cryptosporidium parvum accounted for 40.72% of sequences, followed by Cryptosporidium hominis with 23.64%, Cryptosporidium cuniculus with 7.10%, Cryptosporidium meleagridis with 4.44% and the least was Cryptosporidium wrairi with 2.59%. A considerable percentage of reads in riverbed sediment (21.25%) was not assigned to any subtype. River water samples had 45.63% of sequences assigned to C. parvum, followed by 30.32% to C. hominis, 17.99% to C. meleagridis and 5.88% to C. cuniculus. The data obtained are concerning, as Cryptosporidium spp. have intrinsic resistance to water treatment processes and low infectious doses, which can pose a risk to human health due to the various uses of water (for human consumption, leisure, and reuse).     

Alta-Cyclic: a self-optimizing base caller for next-generation sequencing

Next-generation sequencing is limited to short read lengths and by high error rates. We systematically analyzed sources of noise in the Illumina Genome Analyzer that contribute to these high error rates and developed a base caller, Alta-Cyclic, that uses machine learning to compensate for noise factors. Alta-Cyclic substantially improved the number of accurate reads for sequencing runs up to 78 bases and reduced systematic biases, facilitating confident identification of sequence variants.     

ART: a next-generation sequencing read simulator

ART is a set of simulation tools that generate synthetic next-generation sequencing reads. This functionality is essential for testing and benchmarking tools for next-generation sequencing data analysis including read alignment, de novo assembly and genetic variation discovery. ART generates simulated sequencing reads by emulating the sequencing process with built-in, technology-specific read error models and base quality value profiles parameterized empirically in large sequencing datasets. We currently support all three major commercial next-generation sequencing platforms: Roche's 454, Illumina's Solexa and Applied Biosystems' SOLiD. ART also allows the flexibility to use customized read error model parameters and quality profiles. AVAILABILITY: Both source and binary software packages are available at http://www.niehs.nih.gov/research/resources/software/art.     

BIGpre: a quality assessment package for next-generation sequencing data

The emergence of next-generation sequencing (NGS) technologies has significantly improved sequencing throughput and reduced costs. However, the short read length, duplicate reads and massive volume of data make the data processing much more difficult and complicated than the first-generation sequencing technology. Although there are some software packages developed to assess the data quality, those packages either are not easily available to users or require bioinformatics skills and computer resources. Moreover, almost all the quality assessment software currently available didn’t taken into account the sequencing errors when dealing with the duplicate assessment in NGS data. Here, we present a new user-friendly quality assessment software package called BIGpre, which works for both Illumina and 454 platforms. BIGpre contains all the functions of other quality assessment software, such as the correlation between forward and reverse reads, read GC-content distribution, and base Ns quality. More importantly, BIGpre incorporates associated programs to detect and remove duplicate reads after taking sequencing errors into account and trimming low quality reads from raw data as well. BIGpre is primarily written in Perl and integrates graphical capability from the statistics package R. This package produces both tabular and graphical summaries of data quality for sequencing datasets from Illumina and 454 platforms. Processing hundreds of millions reads within minutes, this package provides immediate diagnostic information for user to manipulate sequencing data for downstream analyses. BIGpre is freely available at http://bigpre.sourceforge.net/.     

二代测序技术在结核分枝杆菌研究中的应用进展

结核病是由结核分枝杆菌引起的全球第二大传染病。二代测序技术为从基因组水平研究结核分枝杆菌提供了重要的研究方法。本文从结核病流行病学、结核分枝杆菌耐药和进化及相关生物信息学等方面,介绍二代测序技术在结核分枝杆菌研究中的应用进展。     

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.     

Base-calling for next-generation sequencing platforms

Next-generation sequencing platforms are dramatically reducing the cost of DNA sequencing. With these technologies, bases are inferred from light intensity signals, a process commonly referred to as base-calling. Thus, understanding and improving the quality of sequence data generated using these approaches are of high interest. Recently, a number of papers have characterized the biases associated with base-calling and proposed methodological improvements. In this review, we summarize recent development of base-calling approaches for the Illumina and Roche 454 sequencing platforms.     

Family-based association studies for next-generation sequencing

An individual's disease risk is determined by the compounded action of both common variants, inherited from remote ancestors, that segregated within the population and rare variants, inherited from recent ancestors, that segregated mainly within pedigrees. Next-generation sequencing (NGS) technologies generate high-dimensional data that allow a nearly complete evaluation of genetic variation. Despite their promise, NGS technologies also suffer from remarkable limitations: high error rates, enrichment of rare variants, and a large proportion of missing values, as well as the fact that most current analytical methods are designed for population-based association studies. To meet the analytical challenges raised by NGS, we propose a general framework for sequence-based association studies that can use various types of family and unrelated-individual data sampled from any population structure and a universal procedure that can transform any population-based association test statistic for use in family-based association tests. We develop family-based functional principal-component analysis (FPCA) with or without smoothing, a generalized T(2), combined multivariate and collapsing (CMC) method, and single-marker association test statistics. Through intensive simulations, we demonstrate that the family-based smoothed FPCA (SFPCA) has the correct type I error rates and much more power to detect association of (1) common variants, (2) rare variants, (3) both common and rare variants, and (4) variants with opposite directions of effect from other population-based or family-based association analysis methods. The proposed statistics are applied to two data sets with pedigree structures. The results show that the smoothed FPCA has a much smaller p value than other statistics.     

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).     

jMHC: software assistant for multilocus genotyping of gene families using next-generation amplicon sequencing

Genotyping of multilocus gene families, such as the major histocompatibility complex (MHC), may be challenging because of problems with assigning alleles to loci and copy number variation among individuals. Simultaneous amplification and genotyping of multiple loci may be necessary, and in such cases, next-generation deep amplicon sequencing offers a great promise as a genotyping method of choice. Here, we describe jMHC, a computer program developed for analysing and assisting in the visualization of deep amplicon sequencing data. Software operates on FASTA files; therefore, output from any sequencing technology may be used. jMHC was designed specifically for MHC studies but it may be useful for analysing amplicons derived from other multigene families or for genotyping other polymorphic systems. The program is written in Java with user-friendly graphical interface (GUI) and can be run on Microsoft Windows, Linux OS and Mac OS.     

Environmental and occupational biomonitoring using the Comet assay

Biomonitoring of human populations exposed to potential mutagens or carcinogens can provide an early detection system for the initiation of cell disregulation in the development of cancer. In recent years, the Comet assay, also known as a “single cell gel” (SCG) electrophoresis assay, has become an important tool for assessing DNA damage in exposed populations. This is the method of choice for population-based studies of environmental and occupational exposure to air pollutants, metals, pesticides, radiation, and other xenobiotics as we show in this review. To appreciate the role of the Comet assay in the field of biomonitoring, we review data from 122 studies that employed the assay. These studies evaluated environmental versus occupational exposures and the levels of DNA damage in cells of individuals exposed in each case. Our review of the literature reveals the importance of the need to establish standard methodological conditions that affect unwinding and electrophoresis times and tail values (tail length, tail DNA, tail moment), with the goal of being able to compare data collected in different laboratories throughout the world. The Comet assay is susceptible to subtle artifacts of manipulation depending on the type and timing of sampling performed. Therefore, in the reporting of DNA damage detected by the Comet assay, the context of how the DNA damage was created also needs to be reported and considered in the interpretation of Comet assay results. The success of the Comet assay is reflected by its use over the past 20 years in the field of biomonitoring, and by the increasing number of studies that continue to report its use. As the shortcomings of the assay are identified and considered in the interpretation of DNA damage detection, the Comet assay will continue to provide improved reliability as a biomarker in human biomonitoring studies.     

T-lex: a program for fast and accurate assessment of transposable element presence using next-generation sequencing data

Transposable elements (TEs) are repetitive DNA sequences that are ubiquitous, extremely abundant and dynamic components of practically all genomes. Much effort has gone into annotation of TE copies in reference genomes. The sequencing cost reduction and the newly available next-generation sequencing (NGS) data from multiple strains within a species offer an unprecedented opportunity to study population genomics of TEs in a range of organisms. Here, we present a computational pipeline (T-lex) that uses NGS data to detect the presence/absence of annotated TE copies. T-lex can use data from a large number of strains and returns estimates of population frequencies of individual TE insertions in a reasonable time. We experimentally validated the accuracy of T-lex detecting presence or absence of 768 previously identified TE copies in two resequenced Drosophila melanogaster strains. Approximately 95% of the TE insertions were detected with 100% sensitivity and 97% specificity. We show that even at low levels of coverage T-lex produces accurate results for TE copies that it can identify reliably but that the rate of 'no data' calls increases as the coverage falls below 15×. T-lex is a broadly applicable and flexible tool that can be used in any genome provided the availability of the reference genome, individual TE copy annotation and NGS data.