Next Generation Sequencing Reveals the Hidden Diversity of Zooplankton Assemblages

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 richness and diversity of a mixed zooplankton assemblage from a productive time series site in the Western English Channel.

Methodology/Principle Findings

Plankton net hauls (200 µm) were taken at the Western Channel Observatory 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 419,041 sequences were obtained for all samples. The sequences clustered into 205 operational taxonomic units using a 97% similarity cut-off. Allocation of taxonomy by comparison with the National Centre for Biotechnology Information database identified 135 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 58 taxonomic groups.

Conclusions

Metagenetics reveals a previously hidden taxonomic richness, especially for Copepoda and hard-to-identify 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 elucidating the true diversity and species richness of zooplankton communities. While this approach allows for broad diversity assessments of plankton it may become increasingly attractive in future if sequence reference libraries of accurately identified individuals are better populated.     

Next Generation Sequencing Reveals Regulation of Distinct Aedes microRNAs during Chikungunya Virus Development

Background

Application of genomics and Next Generation sequencing has led to the identification of new class of cellular functional molecules, namely, small RNAs. Of the several classes of ncRNAs (non-coding RNA), microRNAs have been demonstrated to exert determinative influence on various cellular processes. It is becoming abundantly clear that host/vector/pathogen encoded microRNAs impact eventual pathogenesis. In this context, the participation of vector based microRNAs in disease transmission and pathogen development is being investigated intensively. A few studies have highlighted the role of vector encoded microRNAs in pathogen infection. We conducted this study to evaluate the role of host miRNAs upon CHIKV (Chikungunya Virus) infection in an important vector, Aedes albopictus.

Findings

We identified 88 and 79 known miRNAs in uninfected and CHIKV infected Ae. albopictus Singh''s cell line respectively. We further identified nine novel miRNAs in Ae. albopictus. Comparison of the two libraries revealed differential expression of 77 common miRNAs between them. CHIKV infection specifically altered the miRNA profile of a specific set of eight miRNAs. Putative targets of these regulated miRNAs were identified and classified into their pathways.

Conclusions

In our study we have identified and described the profiles of various miRNAs upon CHIKV infection in Ae. albopictus. This investigation provides an insight about cellular modification by miRNAs during CHIKV infection and the results provide leads for identifying potential candidates for vector based antiviral strategies.     

ANGSD: Analysis of Next Generation Sequencing Data

Background

High-throughput DNA sequencing technologies are generating vast amounts of data. Fast, flexible and memory efficient implementations are needed in order to facilitate analyses of thousands of samples simultaneously.

Results

We present a multithreaded program suite called ANGSD. This program can calculate various summary statistics, and perform association mapping and population genetic analyses utilizing the full information in next generation sequencing data by working directly on the raw sequencing data or by using genotype likelihoods.

Conclusions

The open source c/c++ program ANGSD is available at http://www.popgen.dk/angsd. The program is tested and validated on GNU/Linux systems. The program facilitates multiple input formats including BAM and imputed beagle genotype probability files. The program allow the user to choose between combinations of existing methods and can perform analysis that is not implemented elsewhere.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0356-4) contains supplementary material, which is available to authorized users.     

Next-Generation Sequencing Analysis Reveals Differential Expression Profiles of MiRNA-mRNA Target Pairs in KSHV-Infected Cells

Kaposi’s sarcoma associated herpesvirus (KSHV) causes several tumors, including primary effusion lymphoma (PEL) and Kaposi’s sarcoma (KS). Cellular and viral microRNAs (miRNAs) have been shown to play important roles in regulating gene expression. A better knowledge of the miRNA-mediated pathways affected by KSHV infection is therefore important for understanding viral infection and tumor pathogenesis. In this study, we used deep sequencing to analyze miRNA and cellular mRNA expression in a cell line with latent KSHV infection (SLKK) as compared to the uninfected SLK line. This approach revealed 153 differentially expressed human miRNAs, eight of which were independently confirmed by qRT-PCR. KSHV infection led to the dysregulation of ~15% of the human miRNA pool and most of these cellular miRNAs were down-regulated, including nearly all members of the 14q32 miRNA cluster, a genomic locus linked to cancer and that is deleted in a number of PEL cell lines. Furthermore, we identified 48 miRNAs that were associated with a total of 1,117 predicted or experimentally validated target mRNAs; of these mRNAs, a majority (73%) were inversely correlated to expression changes of their respective miRNAs, suggesting miRNA-mediated silencing mechanisms were involved in a number of these alterations. Several dysregulated miRNA-mRNA pairs may facilitate KSHV infection or tumor formation, such as up-regulated miR-708-5p, associated with a decrease in pro-apoptotic caspase-2 and leukemia inhibitory factor LIF, or down-regulated miR-409-5p, associated with an increase in the p53-inhibitor MDM2. Transfection of miRNA mimics provided further evidence that changes in miRNAs are driving some observed mRNA changes. Using filtered datasets, we also identified several canonical pathways that were significantly enriched in differentially expressed miRNA-mRNA pairs, such as the epithelial-to-mesenchymal transition and the interleukin-8 signaling pathways. Overall, our data provide a more detailed understanding of KSHV latency and guide further studies of the biological significance of these changes.     

Unveiling Distribution Patterns of Freshwater Phytoplankton by a Next Generation Sequencing Based Approach

The recognition and discrimination of phytoplankton species is one of the foundations of freshwater biodiversity research and environmental monitoring. This step is frequently a bottleneck in the analytical chain from sampling to data analysis and subsequent environmental status evaluation. Here we present phytoplankton diversity data from 49 lakes including three seasonal surveys assessed by next generation sequencing (NGS) of 16S ribosomal RNA chloroplast and cyanobacterial gene amplicons and also compare part of these datasets with identification based on morphology. Direct comparison of NGS to microscopic data from three time-series showed that NGS was able to capture the seasonality in phytoplankton succession as observed by microscopy. Still, the PCR-based approach was only semi-quantitative, and detailed NGS and microscopy taxa lists had only low taxonomic correspondence. This is probably due to, both, methodological constraints and current discrepancies in taxonomic frameworks. Discrepancies included Euglenophyta and Heterokonta that were scarce in the NGS but frequently detected by microscopy and Cyanobacteria that were in general more abundant and classified with high resolution by NGS. A deep-branching taxonomically unclassified cluster was frequently detected by NGS but could not be linked to any group identified by microscopy. NGS derived phytoplankton composition differed significantly among lakes with different trophic status, showing that our approach can resolve phytoplankton communities at a level relevant for ecosystem management. The high reproducibility and potential for standardization and parallelization makes our NGS approach an excellent candidate for simultaneous monitoring of prokaryotic and eukaryotic phytoplankton in inland waters.     

Next Generation Sequencing in der diagnostischen Praxis

Next generation sequencing (NGS) allows whole exome or whole genome sequencing for a given patient to be performed timely and at reasonable cost. This diagnostic quantum leap not only has various legal, ethical and economical aspects but will naturally also impact upon patient care. Currently, however, the wide-spread introduction of NGS into routine diagnostics is facing many obstacles. In particular, it is to be expected that NGS will identify a large number of rare variants in a given patient that are of (yet) unknown clinical significance. As a first step towards solving this problem, we introduce the concept of a database that will systematically integrate genotypic and phenotypic information from the German health care context. Not only will this resource be of great scientific value, but the database shall also provide human geneticists with the evidence base necessary for the reliable evaluation of their patient-related sequencing data.     

Expression and Localization of GEN1 in Mouse Mammary Epithelial Cells

GEN1, a Holliday junction resolvase, is involved in homologous repair of DNA double strand break and in maintaining centrosome integrity. Although GEN1 mutants have been reported in breast cancer patients and cell lines, little is currently known about the functions of GEN1 in the development and oncogenic transformation of mammary gland. In the present study, we demonstrate that GEN1 expression is correlated with mammary epithelial cell proliferation, differentiation in various physiological stages as well as casein. By immunofluorescence analysis, the centrosomal association of GEN1 is confirmed in mammary epithelial cells. Additionally, GEN1 is likely involved in DNA damage response of breast cancer cell lines. These results suggest that GEN1 may play an important role in the development of mammary gland; its response upon DNA damage indicates that GEN1 gene alteration may contribute to breast cancer formation.     

Identification of the microRNA Expression Profile in the Regenerative Neonatal Mouse Heart by Deep Sequencing

MicroRNAs (miRNAs) are small noncoding RNAs that are involved in key biological processes, including development, differentiation, and regeneration. The global miRNA expression profile that regulates the regenerative potential of the neonatal mouse heart has not been reported. We performed deep sequencing to determine the genome-wide miRNA expression profile of the neonatal mouse heart at three key ages (1, 6, and 7 days). The miRNAs at least 1.4-fold differentially expressed between the three time points were selected for further analysis. Two miRNAs (mmu-miR-22-5p and mmu-miR-338-3p) were significantly upregulated, and nine miRNAs (mmu-miR-324-5p, mmu-miR-337-5p, mmu-miR-339-5p, mmu-miR-365-1-5p, mmu-miR-500-3p, mmu-miR-505-5p, mmu-miR-542-5p, mmu-miR-668-3p, and mmu-miR-92a-1-5p) were significantly downregulated in cardiac tissue of 7-day-old mice compared to 1- and 6-day-old mice. The expression patterns of five significantly different miRNAs were verified by quantitative real-time PCR. Furthermore, the potential targets of these putative miRNAs were suggested using miRNA target prediction tools. The candidate target genes are involved in the myocardial regenerative process, with a prominent role for the Notch signaling pathway. Our study provides a valuable resource for future investigation of the biological function of miRNAs in heart regeneration.     

Impact of Next Generation Sequencing Techniques in Food Microbiology

Understanding the Maxam-Gilbert and Sanger sequencing as the first generation, in recent years there has been an explosion of newly-developed sequencing strategies, which are usually referred to as next generation sequencing (NGS) techniques. NGS techniques have high-throughputs and produce thousands or even millions of sequences at the same time. These sequences allow for the accurate identification of microbial taxa, including uncultivable organisms and those present in small numbers. In specific applications, NGS provides a complete inventory of all microbial operons and genes present or being expressed under different study conditions. NGS techniques are revolutionizing the field of microbial ecology and have recently been used to examine several food ecosystems. After a short introduction to the most common NGS systems and platforms, this review addresses how NGS techniques have been employed in the study of food microbiota and food fermentations, and discusses their limits and perspectives. The most important findings are reviewed, including those made in the study of the microbiota of milk, fermented dairy products, and plant-, meat- and fish-derived fermented foods. The knowledge that can be gained on microbial diversity, population structure and population dynamics via the use of these technologies could be vital in improving the monitoring and manipulation of foods and fermented food products. They should also improve their safety.     

Genome-Wide Analyses of Radioresistance-Associated miRNA Expression Profile in Nasopharyngeal Carcinoma Using Next Generation Deep Sequencing

Background

Rapidly growing evidence suggests that microRNAs (miRNAs) are involved in a wide range of cancer malignant behaviours including radioresistance. Therefore, the present study was designed to investigate miRNA expression patterns associated with radioresistance in NPC.

Methods

The differential expression profiles of miRNAs and mRNAs associated with NPC radioresistance were constructed. The predicted target mRNAs of miRNAs and their enriched signaling pathways were analyzed via biological informatical algorithms. Finally, partial miRNAs and pathways-correlated target mRNAs were validated in two NPC radioreisitant cell models.

Results

50 known and 9 novel miRNAs with significant difference were identified, and their target mRNAs were narrowed down to 53 nasopharyngeal-/NPC-specific mRNAs. Subsequent KEGG analyses demonstrated that the 53 mRNAs were enriched in 37 signaling pathways. Further qRT-PCR assays confirmed 3 down-regulated miRNAs (miR-324-3p, miR-93-3p and miR-4501), 3 up-regulated miRNAs (miR-371a-5p, miR-34c-5p and miR-1323) and 2 novel miRNAs. Additionally, corresponding alterations of pathways-correlated target mRNAs were observed including 5 up-regulated mRNAs (ICAM1, WNT2B, MYC, HLA-F and TGF-β1) and 3 down-regulated mRNAs (CDH1, PTENP1 and HSP90AA1).

Conclusions

Our study provides an overview of miRNA expression profile and the interactions between miRNA and their target mRNAs, which will deepen our understanding of the important roles of miRNAs in NPC radioresistance.     

基于新一代测序技术的mtDNA突变检测方法学的建立

目的:大量研究证实线粒体DNA(mtDNA)突变与肿瘤发生及进展密切相关,但使用传统测序方法难以高通量、高精确度的检测mtDNA突变,为此本研究建立了基于新一代测序技术的mtDNA突变检测方法.方法:提取肝癌患者癌、癌旁组织以及外周血细胞总DNA,利用PCR技术对线粒体基因组进行富集并对PCR产物进行平末端、粘性末端连接或对PCR引物进行氨基修饰,构建mtDNA测序文库.经Illumina HiSeq 2000平台测序后利用生物信息学方法与人类mtDNA参考序列进行比对,并进行测序数据分析.结果:通过对不同质量基因组DNA进行评估后,发现三对引物法适用于大部分DNA样本的mtDNA富集.进一步我们发现PCR引物的氨基修饰可显著提高测序数据覆盖均一性,降低测序成本.结论:本研究利用新一代测序技术通过对线粒体DNA富集方法以及测序覆盖度均一性进行优化,建立了一套灵敏、特异、高通量的mtDNA突变检测策略,为mtDNA突变与疾病研究提供了新方法.     

AdapterRemoval: Easy Cleaning of Next Generation Sequencing Reads

ABSTRACT: BACKGROUND: With the advent of next-generation sequencing there is an increased demand for tools to pre-process and handle the vast amounts of data generated. One recurring problem is adapter contamination in the reads, i.e. the partial or complete sequencing of adapter sequences. These adapter sequences have to be removed as they can hinder correct mapping of the reads and influence SNP calling and other downstream analyses. FINDINGS: We present a tool called AdapterRemoval which is able to pre-process both single and paired-end data. The program locates and removes adapter residues from the reads, it is able to combine paired reads if they overlap, and it can optionally trim low-quality nucleotides. Furthermore, it can look for adapter sequence in both the 5' and 3' ends of the reads. This is a flexible method that can be tuned to accommodate different experimental settings and sequencing platforms producing FASTQ files. AdapterRemoval is shown to be good at trimming adapters from both single-end and paired-end data. CONCLUSIONS: AdapterRemoval is a comprehensive tool for analyzing next-generation sequencing data. It exhibits good performance both in terms of sensitivity and specificity. AdapterRemoval has already been used in various large projects and it is possible to extend it further to accommodate application-specific biases in the data.     

Comparison of Hepatocellular Carcinoma miRNA Expression Profiling as Evaluated by Next Generation Sequencing and Microarray

MicroRNA (miRNA) expression profiling has proven useful in diagnosing and understanding the development and progression of several diseases. Microarray is the standard method for analyzing miRNA expression profiles; however, it has several disadvantages, including its limited detection of miRNAs. In recent years, advances in genome sequencing have led to the development of next-generation sequencing (NGS) technologies, which significantly advance genome sequencing speed and discovery. In this study, we compared the expression profiles obtained by next generation sequencing (NGS) with the profiles created using microarray to assess if NGS could produce a more accurate and complete miRNA profile. Total RNA from 14 hepatocellular carcinoma tumors (HCC) and 6 matched non-tumor control tissues were sequenced with Illumina MiSeq 50-bp single-end reads. Micro RNA expression profiles were estimated using miRDeep2 software. As a comparison, miRNA expression profiles for 11 out of 14 HCCs were also established by microarray (Agilent human microRNA microarray). The average total sequencing exceeded 2.2 million reads per sample and of those reads, approximately 57% mapped to the human genome. The average correlation for miRNA expression between microarray and NGS and subtraction were 0.613 and 0.587, respectively, while miRNA expression between technical replicates was 0.976. The diagnostic accuracy of HCC, p-value, and AUC were 90.0%, 7.22×10⁻⁴, and 0.92, respectively. In summary, NGS created an miRNA expression profile that was reproducible and comparable to that produced by microarray. Moreover, NGS discovered novel miRNAs that were otherwise undetectable by microarray. We believe that miRNA expression profiling by NGS can be a useful diagnostic tool applicable to multiple fields of medicine.     

Mutation Discovery in Regions of Segmental Cancer Genome Amplifications with CoNAn-SNV: A Mixture Model for Next Generation Sequencing of Tumors

Next generation sequencing has now enabled a cost-effective enumeration of the full mutational complement of a tumor genome-in particular single nucleotide variants (SNVs). Most current computational and statistical models for analyzing next generation sequencing data, however, do not account for cancer-specific biological properties, including somatic segmental copy number alterations (CNAs)-which require special treatment of the data. Here we present CoNAn-SNV (Copy Number Annotated SNV): a novel algorithm for the inference of single nucleotide variants (SNVs) that overlap copy number alterations. The method is based on modelling the notion that genomic regions of segmental duplication and amplification induce an extended genotype space where a subset of genotypes will exhibit heavily skewed allelic distributions in SNVs (and therefore render them undetectable by methods that assume diploidy). We introduce the concept of modelling allelic counts from sequencing data using a panel of Binomial mixture models where the number of mixtures for a given locus in the genome is informed by a discrete copy number state given as input. We applied CoNAn-SNV to a previously published whole genome shotgun data set obtained from a lobular breast cancer and show that it is able to discover 21 experimentally revalidated somatic non-synonymous mutations in a lobular breast cancer genome that were not detected using copy number insensitive SNV detection algorithms. Importantly, ROC analysis shows that the increased sensitivity of CoNAn-SNV does not result in disproportionate loss of specificity. This was also supported by analysis of a recently published lymphoma genome with a relatively quiescent karyotype, where CoNAn-SNV showed similar results to other callers except in regions of copy number gain where increased sensitivity was conferred. Our results indicate that in genomically unstable tumors, copy number annotation for SNV detection will be critical to fully characterize the mutational landscape of cancer genomes.     

DNA提取对微生物多样性测序分析的影响

运用高通量测序技术分析复杂样品中微生物种群的变化情况,已经成为目前微生物研究领域的热点问题之一。而微生物的样品准备,如DNA提取和16S可变区的扩增等,对于测序完成后的数据分析以及微生物原始群落组成的影响是至关重要的。采用国产试剂盒(天根土壤微生物基因组提取试剂盒)和进口试剂盒(MOBIO土壤微生物基因组提取试剂盒)分别对土壤样品和羊瘤胃食糜样品进行DNA提取。然后选取总DNA起始量为25ng,对16S V3可变区进行PCR扩增和文库构建,最后通过数据分析比较不同试剂盒提取的DNA对微生物多样性变化的影响,包括OTU数目、稀释曲线、微生物数量及物种种类等。研究发现,在相同DNA模板量和PCR条件下,进口试剂盒提取的DNA能够获得更多的微生物种类。