Library construction for next-generation sequencing: overviews and challenges

The Many Faces of Gene Regulation in Cancer: A Computational Oncogenomics Outlook

Cancer is a complex disease at many different levels. The molecular phenomenology of cancer is also quite rich. The mutational and genomic origins of cancer and their downstream effects on processes such as the reprogramming of the gene regulatory control and the molecular pathways depending on such control have been recognized as central to the characterization of the disease. More important though is the understanding of their causes, prognosis, and therapeutics. There is a multitude of factors associated with anomalous control of gene expression in cancer. Many of these factors are now amenable to be studied comprehensively by means of experiments based on diverse omic technologies. However, characterizing each dimension of the phenomenon individually has proven to fall short in presenting a clear picture of expression regulation as a whole. In this review article, we discuss some of the more relevant factors affecting gene expression control both, under normal conditions and in tumor settings. We describe the different omic approaches that we can use as well as the computational genomic analysis needed to track down these factors. Then we present theoretical and computational frameworks developed to integrate the amount of diverse information provided by such single-omic analyses. We contextualize this within a systems biology-based multi-omic regulation setting, aimed at better understanding the complex interplay of gene expression deregulation in cancer.

De novo whole genome sequencing data of two mangrove-isolated microalgae from Terengganu coastal waters

Interest in harvesting potential benefits from microalgae renders it necessary to have the many ecological niches of a single species to be investigated. This dataset comprises de novo whole genome assembly of two mangrove-isolated microalgae (from division Chlorophyta); Chlorella vulgaris UMT-M1 and Messastrum gracile SE-MC4 from Universiti Malaysia Terengganu, Malaysia. Library runs were carried out with 2 × 150 base paired-ends reads, whereas sequencing was conducted using Illumina Novaseq 2500 platform. Sequencing yielded raw reads amounting to ∼11 Gb in total bases for both species and was further assembled de novo. Genome assembly resulted in a 50.15 Mbp and 60.83 Mbp genome size for UMT-M1 and SE-MC4, respectively. All filtered and assembled genomic data sequences have been submitted to National Centre for Biotechnology Information (NCBI) and can be located at DDBJ/ENA/GenBank under the accession of VJNP00000000 (UMT-M1) and VIYE00000000 (SE-MC4).

Highly efficient library preparation for Ion Torrent sequencing using Y-adapters

Library preparation is a crucial step in next-generation sequencing workflows. Key determinants of successful library preparation are the available amount of input DNA and the efficiency of the conversion of this DNA into functional library molecules. While the standard blunt-end ligation protocol for Ion Torrent libraries has a theoretical maximum efficiency of 25%, Y-adapters enable highly efficient library preparation by (i) sticky-end ligation and (ii) rendering both DNA strands functional for sequencing, hence resulting in a theoretical efficiency of up to 100%. Moreover, the generation of adapter dimers is reduced. Therefore, we designed, optimized and validated Y-adapters compatible with Ion Torrent sequencing. These facilitate higher library yields combined with overall high sequencing performance regarding the key characteristics read-length, base quality, and library complexity.

Adapterama I: universal stubs and primers for 384 unique dual-indexed or 147,456 combinatorially-indexed Illumina libraries (iTru & iNext)

Massively parallel DNA sequencing offers many benefits, but major inhibitory cost factors include: (1) start-up (i.e., purchasing initial reagents and equipment); (2) buy-in (i.e., getting the smallest possible amount of data from a run); and (3) sample preparation. Reducing sample preparation costs is commonly addressed, but start-up and buy-in costs are rarely addressed. We present dual-indexing systems to address all three of these issues. By breaking the library construction process into universal, re-usable, combinatorial components, we reduce all costs, while increasing the number of samples and the variety of library types that can be combined within runs. We accomplish this by extending the Illumina TruSeq dual-indexing approach to 768 (384 + 384) indexed primers that produce 384 unique dual-indexes or 147,456 (384 × 384) unique combinations. We maintain eight nucleotide indexes, with many that are compatible with Illumina index sequences. We synthesized these indexing primers, purifying them with only standard desalting and placing small aliquots in replicate plates. In qPCR validation tests, 206 of 208 primers tested passed (99% success). We then created hundreds of libraries in various scenarios. Our approach reduces start-up and per-sample costs by requiring only one universal adapter that works with indexed PCR primers to uniquely identify samples. Our approach reduces buy-in costs because: (1) relatively few oligonucleotides are needed to produce a large number of indexed libraries; and (2) the large number of possible primers allows researchers to use unique primer sets for different projects, which facilitates pooling of samples during sequencing. Our libraries make use of standard Illumina sequencing primers and index sequence length and are demultiplexed with standard Illumina software, thereby minimizing customization headaches. In subsequent Adapterama papers, we use these same primers with different adapter stubs to construct amplicon and restriction-site associated DNA libraries, but their use can be expanded to any type of library sequenced on Illumina platforms.

PAIPline: pathogen identification in metagenomic and clinical next generation sequencing samples

Motivation

Next generation sequencing (NGS) has provided researchers with a powerful tool to characterize metagenomic and clinical samples in research and diagnostic settings. NGS allows an open view into samples useful for pathogen detection in an unbiased fashion and without prior hypothesis about possible causative agents. However, NGS datasets for pathogen detection come with different obstacles, such as a very unfavorable ratio of pathogen to host reads. Alongside often appearing false positives and irrelevant organisms, such as contaminants, tools are often challenged by samples with low pathogen loads and might not report organisms present below a certain threshold. Furthermore, some metagenomic profiling tools are only focused on one particular set of pathogens, for example bacteria.

Results

We present PAIPline, a bioinformatics pipeline specifically designed to address problems associated with detecting pathogens in diagnostic samples. PAIPline particularly focuses on userfriendliness and encapsulates all necessary steps from preprocessing to resolution of ambiguous reads and filtering up to visualization in a single tool. In contrast to existing tools, PAIPline is more specific while maintaining sensitivity. This is shown in a comparative evaluation where PAIPline was benchmarked along other well-known metagenomic profiling tools on previously published well-characterized datasets. Additionally, as part of an international cooperation project, PAIPline was applied to an outbreak sample of hemorrhagic fevers of then unknown etiology. The presented results show that PAIPline can serve as a robust, reliable, user-friendly, adaptable and generalizable stand-alone software for diagnostics from NGS samples and as a stepping stone for further downstream analyses.

Availability and implementation

PAIPline is freely available under https://gitlab.com/rki_bioinformatics/paipline.

Understanding sequencing data as compositions: an outlook and review

Motivation

Although seldom acknowledged explicitly, count data generated by sequencing platforms exist as compositions for which the abundance of each component (e.g. gene or transcript) is only coherently interpretable relative to other components within that sample. This property arises from the assay technology itself, whereby the number of counts recorded for each sample is constrained by an arbitrary total sum (i.e. library size). Consequently, sequencing data, as compositional data, exist in a non-Euclidean space that, without normalization or transformation, renders invalid many conventional analyses, including distance measures, correlation coefficients and multivariate statistical models.

Results

The purpose of this review is to summarize the principles of compositional data analysis (CoDA), provide evidence for why sequencing data are compositional, discuss compositionally valid methods available for analyzing sequencing data, and highlight future directions with regard to this field of study.

Supplementary information

Supplementary data are available at Bioinformatics online.

Deconvolution of nucleic-acid length distributions: a gel electrophoresis analysis tool and applications

Next-generation DNA-sequencing (NGS) technologies, which are designed to streamline the acquisition of massive amounts of sequencing data, are nonetheless dependent on various preparative steps to generate DNA fragments of required concentration, purity and average size (molecular weight). Current automated electrophoresis systems for DNA- and RNA-sample quality control, such as Agilent's Bioanalyzer® and TapeStation® products, are costly to acquire and use; they also provide limited information for samples having broad size distributions. Here, we describe a software tool that helps determine the size distribution of DNA fragments in an NGS library, or other DNA sample, based on gel-electrophoretic line profiles. The software, developed as an ImageJ plug-in, allows for straightforward processing of gel images, including lane selection and fitting of univariate functions to intensity distributions. The user selects the option of fitting either discrete profiles in cases where discrete gel bands are visible or continuous profiles, having multiple bands buried under a single broad peak. The method requires only modest imaging capabilities and is a cost-effective, rigorous alternative characterization method to augment existing techniques for library quality control.

Metagenomic deep sequencing reveals association of microbiome signature with functional biases in bovine mastitis

Milk microbiomes significantly influence the pathophysiology of bovine mastitis. To assess the association between microbiome diversity and bovine mastitis, we compared the microbiome of clinical mastitis (CM, n = 14) and healthy (H, n = 7) milk samples through deep whole metagenome sequencing (WMS). A total of 483.38 million reads generated from both metagenomes were analyzed through PathoScope (PS) and MG-RAST (MR), and mapped to 380 bacterial, 56 archaeal, and 39 viral genomes. We observed distinct shifts and differences in abundance between the microbiome of CM and H milk in phyla Proteobacteria, Bacteroidetes, Firmicutes and Actinobacteria with an inclusion of 68.04% previously unreported and/or opportunistic strains in CM milk. PS identified 363 and 146 bacterial strains in CM and H milk samples respectively, and MR detected 356 and 251 bacterial genera respectively. Of the identified taxa, 29.51% of strains and 63.80% of genera were shared between both metagenomes. Additionally, 14 archaeal and 14 viral genera were found to be solely associated with CM. Functional annotation of metagenomic sequences identified several metabolic pathways related to bacterial colonization, proliferation, chemotaxis and invasion, immune-diseases, oxidative stress, regulation and cell signaling, phage and prophases, antibiotic and heavy metal resistance that might be associated with CM. Our WMS study provides conclusive data on milk microbiome diversity associated with bovine CM and its role in udder health.

Is reliance on an inaccurate genome sequence sabotaging your experiments?

Advances in genomics have made whole genome studies increasingly feasible across the life sciences. However, new technologies and algorithmic advances do not guarantee flawless genomic sequences or annotation. Bias, errors, and artifacts can enter at any stage of the process from library preparation to annotation. When planning an experiment that utilizes a genome sequence as the basis for the design, there are a few basic checks that, if performed, may better inform the experimental design and ideally help avoid a failed experiment or inconclusive result.

Pharmacogenetics: Role of Single Nucleotide Polymorphisms

Genome sequencing methods have basically similar algorithms, although they show a few differences between the platforms. The human genome contains approximately three billion base pairs, and this amount is huge and therefore impossible to sequence at one step. However, this amount is not a problem for developed technology. Researchers break DNA into small random pieces and then sequence and reassemble. Library preparation, sequencing, bioinformatic approaches and reporting. High-quality library preparation is critical and the most important part of the next-generation sequencing workflow. Successful sequencing directly requires high-quality libraries. Sequencing is second step and all high-throughput sequencing approaches are generally based on conventional Sanger sequencing. After preparation of library and sequencing, later steps are completely computer-based (in silico) approaches called as bioinformatics.

A field guide for the compositional analysis of any-omics data

BACKGROUND

Next-generation sequencing (NGS) has made it possible to determine the sequence and relative abundance of all nucleotides in a biological or environmental sample. A cornerstone of NGS is the quantification of RNA or DNA presence as counts. However, these counts are not counts per se: their magnitude is determined arbitrarily by the sequencing depth, not by the input material. Consequently, counts must undergo normalization prior to use. Conventional normalization methods require a set of assumptions: they assume that the majority of features are unchanged and that all environments under study have the same carrying capacity for nucleotide synthesis. These assumptions are often untestable and may not hold when heterogeneous samples are compared.

RESULTS

Methods developed within the field of compositional data analysis offer a general solution that is assumption-free and valid for all data. Herein, we synthesize the extant literature to provide a concise guide on how to apply compositional data analysis to NGS count data.

CONCLUSIONS

In highlighting the limitations of total library size, effective library size, and spike-in normalizations, we propose the log-ratio transformation as a general solution to answer the question, "Relative to some important activity of the cell, what is changing?"

Enzyme Immobilization for Solid-Phase Catalysis

The covalent immobilization of an enzyme to a solid support can broaden its applicability in various workflows. Immobilized enzymes facilitate catalyst re-use, adaptability to automation or high-throughput applications and removal of the enzyme without heat inactivation or reaction purification. In this report, we demonstrate a step-by-step procedure to carry out the bio-orthogonal immobilization of DNA modifying enzymes employing the self-labelling activity of the SNAP-tag to covalently conjugate the enzyme of interest to the solid support. We also demonstrate how modifying the surface functionality of the support can improve the activity of the immobilized enzyme. Finally, the utility of immobilized DNA-modifying enzymes is depicted through sequential processing of genomic DNA libraries for Illumina next-generation sequencing (NGS), resulting in improved read coverage across AT-rich sequences.

A cross-cancer metastasis signature in the microRNA-mRNA axis of paired tissue samples

In the progression of cancer, cells acquire genetic mutations that cause uncontrolled growth. Over time, the primary tumour may undergo additional mutations that allow for the cancerous cells to spread throughout the body as metastases. Since metastatic development typically results in markedly worse patient outcomes, research into the identity and function of metastasis-associated biomarkers could eventually translate into clinical diagnostics or novel therapeutics. Although the general processes underpinning metastatic progression are understood, no clear cross-cancer biomarker profile has emerged. However, the literature suggests that some microRNAs (miRNAs) may play an important role in the metastatic progression of several cancer types. Using a subset of The Cancer Genome Atlas (TCGA) data, we performed an integrated analysis of mRNA and miRNA expression with paired metastatic and primary tumour samples to interrogate how the miRNA-mRNA regulatory axis influences metastatic progression. From this, we successfully built mRNA- and miRNA-specific classifiers that can discriminate pairs of metastatic and primary samples across 11 cancer types. In addition, we identified a number of miRNAs whose metastasis-associated dysregulation could predict mRNA metastasis-associated dysregulation. Among the most predictive miRNAs, we found several previously implicated in cancer progression, including miR-301b, miR-1296, and miR-423. Taken together, our results suggest that metastatic samples have a common cross-cancer signature when compared with their primary tumour pair, and that these miRNA biomarkers can be used to predict metastatic status as well as mRNA expression.

Fragmentation of Pooled PCR Products for Highly Multiplexed TILLING

Improvements to massively parallel sequencing have allowed the routine recovery of natural and induced sequence variants. A broad range of biological disciplines have benefited from this, ranging from plant breeding to cancer research. The need for high sequence coverage to accurately recover single nucleotide variants and small insertions and deletions limits the applicability of whole genome approaches. This is especially true in organisms with a large genome size or for applications requiring the screening of thousands of individuals, such as the reverse-genetic technique known as TILLING. Using PCR to target and sequence chosen genomic regions provides an attractive alternative as the vast reduction in interrogated bases means that sample size can be dramatically increased through amplicon multiplexing and multi-dimensional sample pooling while maintaining suitable coverage for recovery of small mutations. Direct sequencing of PCR products is limited, however, due to limitations in read lengths of many next generation sequencers. In the present study we show the optimization and use of ultrasonication for the simultaneous fragmentation of multiplexed PCR amplicons for TILLING highly pooled samples. Sequencing performance was evaluated in a total of 32 pooled PCR products produced from 4096 chemically mutagenized Hordeum vulgare DNAs pooled in three dimensions. Evaluation of read coverage and base quality across amplicons suggests this approach is suitable for high-throughput TILLING and other applications employing highly pooled complex sampling schemes. Induced mutations previously identified in a traditional TILLING screen were recovered in this dataset further supporting the efficacy of the approach.

Comparison of library construction kits for mRNA sequencing in the Illumina platform

BACKGROUND

The emergence of next-generation sequencing (NGS) technologies has made a tremendous contribution to the deciphering and significance of transcriptome analysis in biological fields. Since the advent of NGS technology in 2007, Illumina, Inc. has provided one of the most widely used sequencing platforms for NGS analysis.

OBJECTIVE

Although reagents and protocols provided by Illumina are adequately performed in transcriptome sequencing, recently, alternative reagents and protocols which are relatively cost effective are accessible. However, the kits derived from various manufacturers have advantages and disadvantages when researchers carry out the transcriptome library construction.

METHODS

We compared them using a variety of protocols to produce Illumina-compatible libraries based on transcriptome. Three different mRNA sequencing kits were selected for this study: TruSeq^® RNA Sample Preparation V2 (Illumina, Inc., USA), Universal Plus mRNA-Seq (NuGEN, Ltd., UK), and NEBNext^® Ultra™ Directional RNA Library Prep Kit for Illumina^® (New England BioLabs, Ltd., USA). We compared them focusing on cost, experimental time, and data output.

RESULTS

The quality and quantity of sequencing data obtained through the NGS technique were strongly influenced by the type of the sequencing library kits. It suggests that for transcriptome studies, researchers should select a suitable library construction kit according to the goal and resources of experiments.

CONCLUSION

The present work will help researchers to choose the right sequencing library construction kit for transcriptome analyses.

RNase H-dependent PCR-enabled T-cell receptor sequencing for highly specific and efficient targeted sequencing of T-cell receptor mRNA for single-cell and repertoire analysis

RNase H-dependent PCR-enabled T-cell receptor sequencing (rhTCRseq) can be used to determine paired alpha/beta T-cell receptor (TCR) clonotypes in single cells or perform alpha and beta TCR repertoire analysis in bulk RNA samples. With the enhanced specificity of RNase H-dependent PCR (rhPCR), it achieves TCR-specific amplification and addition of dual-index barcodes in a single PCR step. For single cells, the protocol includes sorting of single cells into plates, generation of cDNA libraries, a TCR-specific amplification step, a second PCR on pooled sample to generate a sequencing library, and sequencing. In the bulk method, sorting and cDNA library steps are replaced with a reverse-transcriptase (RT) reaction that adds a unique molecular identifier (UMI) to each cDNA molecule to improve the accuracy of repertoire-frequency measurements. Compared to other methods for TCR sequencing, rhTCRseq has a streamlined workflow and the ability to analyze single cells in 384-well plates. Compared to TCR reconstruction from single-cell transcriptome sequencing data, it improves the success rate for obtaining paired alpha/beta information and ensures recovery of complete complementarity-determining region 3 (CDR3) sequences, a prerequisite for cloning/expression of discovered TCRs. Although it has lower throughput than droplet-based methods, rhTCRseq is well-suited to analysis of small sorted populations, especially when analysis of 96 or 384 single cells is sufficient to identify predominant T-cell clones. For single cells, sorting typically requires 2-4 h and can be performed days, or even months, before library construction and data processing, which takes ~4 d; the bulk RNA protocol takes ~3 d.

Survey of the Bradysia odoriphaga Transcriptome Using PacBio Single-Molecule Long-Read Sequencing

The damage caused by Bradysia odoriphaga is the main factor threatening the production of vegetables in the Liliaceae family. However, few genetic studies of B. odoriphaga have been conducted because of a lack of genomic resources. Many long-read sequencing technologies have been developed in the last decade; therefore, in this study, the transcriptome including all development stages of B. odoriphaga was sequenced for the first time by Pacific single-molecule long-read sequencing. Here, 39,129 isoforms were generated, and 35,645 were found to have annotation results when checked against sequences available in different databases. Overall, 18,473 isoforms were distributed in 25 various Clusters of Orthologous Groups, and 11,880 isoforms were categorized into 60 functional groups that belonged to the three main Gene Ontology classifications. Moreover, 30,610 isoforms were assigned into 44 functional categories belonging to six main Kyoto Encyclopedia of Genes and Genomes functional categories. Coding DNA sequence (CDS) prediction showed that 36,419 out of 39,129 isoforms were predicted to have CDS, and 4319 simple sequence repeats were detected in total. Finally, 266 insecticide resistance and metabolism-related isoforms were identified as candidate genes for further investigation of insecticide resistance and metabolism in B. odoriphaga.

Computational Workflow for Small RNA Profiling in Virus-Infected Plants

In this chapter we describe a series of computational pipelines for the in silico analysis of small RNAs (sRNA) produced in response to viral infections in plants. Our workflow is primarily focused on the analysis of sRNA populations derived from known or previously undescribed viruses infecting host plants. Furthermore, we provide an additional pipeline to examine host-specific endogenous sRNAs activated or specifically expressed during viral infections in plants. We present some key points for a successful and cost-efficient processing of next generation sequencing sRNA libraries, from purification of high quality RNA to guidance for library preparation and sequencing strategies. We report a series of free available tools and programs as well as in-house Perl scripts to perform customized sRNA-seq data mining. Previous bioinformatic background is not required, but experience with basic Unix commands is desirable.

Comprehensive assessment of multiple biases in small RNA sequencing reveals significant differences in the performance of widely used methods

BACKGROUND

RNA sequencing offers advantages over other quantification methods for microRNA (miRNA), yet numerous biases make reliable quantification challenging. Previous evaluations of these biases have focused on adapter ligation bias with limited evaluation of reverse transcription bias or amplification bias. Furthermore, evaluations of the quantification of isomiRs (miRNA isoforms) or the influence of starting amount on performance have been very limited. No study had yet evaluated the quantification of isomiRs of altered length or compared the consistency of results derived from multiple moderate starting inputs. We therefore evaluated quantifications of miRNA and isomiRs using four library preparation kits, with various starting amounts, as well as quantifications following removal of duplicate reads using unique molecular identifiers (UMIs) to mitigate reverse transcription and amplification biases.

RESULTS

All methods resulted in false isomiR detection; however, the adapter-free method tested was especially prone to false isomiR detection. We demonstrate that using UMIs improves accuracy and we provide a guide for input amounts to improve consistency.

CONCLUSIONS

Our data show differences and limitations of current methods, thus raising concerns about the validity of quantification of miRNA and isomiRs across studies. We advocate for the use of UMIs to improve accuracy and reliability of miRNA quantifications.

Excess primer degradation by Exo I improves the preparation of 3' cDNA ligation-based sequencing libraries

RNA sequencing library construction using single-stranded ligation of a DNA adapter to 3' ends of cDNAs often produces primer-adapter byproducts, which compete with cDNA-adapter ligation products during library amplification and, therefore, reduces the number of informative sequencing reads. We find that Escherichia coli Exo I digestion efficiently and selectively removes surplus reverse transcription primer and thereby reduces the primer-adapter product contamination in 3' cDNA ligation-based sequencing libraries, including small RNA libraries, which are typically similar in size to the primer-adapter products. We further demonstrate that Exo I treatment does not lead to trimming of the cDNA 3' end when duplexed with the RNA template. Exo I digestion is easy to perform and implement in other protocols and could facilitate a more widespread use of 3' cDNA ligation for sequencing-based applications.

PROBABILISTIC MODELING AND ANALYSIS OF DNA FRAGMENTATION

Deoxyribonucleic Acid (DNA) sequencing has become indispensable to the modern biological and medicine sciences. DNA fragmentation is a preliminary step in a dominant technique called shotgun sequencing that provides a time and cost effective strategy for the DNA sequencing. In this paper, we propose a probabilistic model for the random DNA fragmentation and derive an average number of fragments with the suitable length along with the probability of covering the entire DNA strand through the de novo assembly or the referenced-based mapping assembly. We formulate the coverage problem in terms of the probability of bond breaking between nucleotides and the number of DNA molecules participating in the fragmentation process, and provide insights into the optimal DNA fragmentation. We obtain the lower bound for the minimum number of suitable fragments required to reconstruct the DNA strand with the specified reliability. We evaluate the derived results with our DNA Fragmentation Tool which demonstrate, the validity of these results based on our model. Finally, we update our model with respect to the fragments’ size distribution of real data.

Circulating tumor DNA detection is correlated to histologic types in patients with early-stage non-small-cell lung cancer

OBJECTIVES

Circulating tumor DNA (ctDNA) testing in plasma in patients with non-small-cell lung cancer (NSCLC) has the potential to be a supplemental or surrogate tool for tissue biopsy. Detection of genomic abnormalities in ctDNA and their association with clinical characteristics in early-stage NSCLC need to be clarified.

MATERIALS AND METHODS

Here, we comprehensively analyzed gene variations of 48 tumor tissues and 48 matched preoperative (pre-op) plasma and 25 postoperative (post-op) plasma from early-stage NSCLC patients using a targeted 546 genes capture-based next generation sequencing (NGS) assay.

RESULTS

In early-stage NSCLC, the average mutation allele frequency (MAF) in pre-op plasma ctDNA was lower than that in tissue DNA (tDNA). The concordant gene variations between pre-op ctDNA and tDNA were difficult to detect. However, we found the tissue- pre-op plasma concordant ctDNA mutation detection ratio in lung squamous cell carcinoma (LUSC) was much higher than that in lung adenocarcinoma (LUAD). We also established a LUSC-LUAD classification model by a least absolute shrinkage and selection operator (LASSO) based approach to help separate LUAD from LUSC based on ctDNA profiling. This model included 14 gene mutations and extracted an accuracy of 89.2% in the training set and 91.5% in the testing set. Correlation analysis showed tDNA-ctDNA concordant ratio was related to histologic subtype, gene mutations and tumor size in early-stage NSCLC.

CONCLUSION

This study suggests histology subtype and gene mutations could affect ctDNA detection in early-stage NSCLC. NGS-based ctDNA profile has the potential utility in LUSC-LUAD classification.

Improved TGIRT-seq methods for comprehensive transcriptome profiling with decreased adapter dimer formation and bias correction

Thermostable group II intron reverse transcriptases (TGIRTs) with high fidelity and processivity have been used for a variety of RNA sequencing (RNA-seq) applications, including comprehensive profiling of whole-cell, exosomal, and human plasma RNAs; quantitative tRNA-seq based on the ability of TGIRT enzymes to give full-length reads of tRNAs and other structured small ncRNAs; high-throughput mapping of post-transcriptional modifications; and RNA structure mapping. Here, we improved TGIRT-seq methods for comprehensive transcriptome profiling by rationally designing RNA-seq adapters that minimize adapter dimer formation. Additionally, we developed biochemical and computational methods for remediating 5′- and 3′-end biases, the latter based on a random forest regression model that provides insight into the contribution of different factors to these biases. These improvements, some of which may be applicable to other RNA-seq methods, increase the efficiency of TGIRT-seq library construction and improve coverage of very small RNAs, such as miRNAs. Our findings provide insight into the biochemical basis of 5′- and 3′-end biases in RNA-seq and suggest general approaches for remediating biases and decreasing adapter dimer formation.

Computational Methods for Mapping, Assembly and Quantification for Coding and Non-coding Transcripts

The measurement of gene expression has long provided significant insight into biological functions. The development of high-throughput short-read sequencing technology has revealed transcriptional complexity at an unprecedented scale, and informed almost all areas of biology. However, as researchers have sought to gather more insights from the data, these new technologies have also increased the computational analysis burden. In this review, we describe typical computational pipelines for RNA-Seq analysis and discuss their strengths and weaknesses for the assembly, quantification and analysis of coding and non-coding RNAs. We also discuss the assembly of transposable elements into transcripts, and the difficulty these repetitive elements pose. In summary, RNA-Seq is a powerful technology that is likely to remain a key asset in the biologist's toolkit.

LncRNA Rik-203 contributes to anesthesia neurotoxicity via microRNA-101a-3p and GSK-3β-mediated neural differentiation

The mechanism of anesthesia neurotoxicity remains largely to be determined. The effects of long noncoding RNAs (LncRNAs) on neural differentiation and the underlying mechanisms are unknown. We thus identified LncRNA Rik-203 (C130071C03Rik) and studied its role on neural differentiation and its interactions with anesthetic sevoflurane, miRNA and GSK-3β. We found that levels of Rik-203 were higher in hippocampus than other tissues and increased during neural differentiation. Sevoflurane decreased the levels of Rik-203. Rik-203 knockdown reduced mRNA levels of Sox1 and Nestin, the markers of neural progenitor cells, and decreased the count of Sox1 positive cells. RNA-RNA pull-down showed that miR-101a-3p was highly bound to Rik-203. Finally, sevoflurane, knockdown of Rik-203, and miR-101a-3p overexpression all decreased GSK-3β levels. These data suggest that Rik-203 facilitates neural differentiation by inhibiting miR-101a-3p's ability to reduce GSK-3β levels and that LncRNAs would serve as the mechanism of the anesthesia neurotoxicity.

Gel-on-a-chip: continuous, velocity-dependent DNA separation using nanoscale lateral displacement

We studied the trajectories of polymers being advected while diffusing in a pressure driven flow along a periodic pillar nanostructure known as nanoscale deterministic lateral displacement (nanoDLD) array. We found that polymers follow different trajectories depending on their length, flow velocity and pillar array geometry, demonstrating that nanoDLD devices can be used as a continuous polymer fractionation tool. As a model system, we used double-stranded DNA (dsDNA) with various contour lengths and demonstrated that dsDNA in the range of 100-10 000 base pairs (bp) can be separated with a size-selective resolution of 200 bp. In contrast to spherical colloids, a polymer elongates by shear flow and the angle of polymer trajectories with respect to the mean flow direction decreases as the mean flow velocity increases. We developed a phenomenological model that explains the qualitative dependence of the polymer trajectories on the gap size and on the flow velocity. Using this model, we found the optimal separation conditions for dsDNA of different sizes and demonstrated the separation and extraction of dsDNA fragments with over 75% recovery and 3-fold concentration. Importantly, this velocity dependence provides a means of fine-tuning the separation efficiency and resolution, independent of the nanoDLD pillar geometry.

Towards high quality real-time whole genome sequencing during outbreaks using Usutu virus as example

Recently, protocols for amplicon based whole genome sequencing using Nanopore technology have been described for Ebola virus, Zika virus, yellow fever virus and West Nile virus. However, there is some debate regarding reliability of sequencing using this technology, which is important for applications beyond diagnosis such as linking lineages to outbreaks, tracking transmission pathways and pockets of circulation, or mapping specific markers. To our knowledge, no in depth analyses of the required read coverage to compensate for the error profile in Nanopore sequencing have been described. Here, we describe the validation of a protocol for whole genome sequencing of USUV using Nanopore sequencing by direct comparison to Illumina sequencing. To that point we selected brain tissue samples with high viral loads, typical for birds which died from USUV infection. We conclude that the low-cost MinION Nanopore sequencing platform can be used for characterization and tracking of Usutu virus outbreaks.

Fragmentation Through Polymerization (FTP): A new method to fragment DNA for next-generation sequencing

Fragmentation of DNA is the very important first step in preparing nucleic acids for next-generation sequencing. Here we report a novel Fragmentation Through Polymerization (FTP) technique, which is a simple, robust, and low-cost enzymatic method of fragmentation. This method generates double-stranded DNA fragments that are suitable for direct use in NGS library construction and allows the elimination of the additional step of reparation of DNA ends.

Synthetic cell-like membrane interfaces for probing dynamic protein-lipid interactions

The ability to rapidly screen interactions between proteins and membrane-like interfaces would aid in establishing the structure-function of protein-lipid interactions, provide a platform for engineering lipid-interacting protein tools, and potentially inform the signaling mechanisms and dynamics of membrane-associated proteins. Here, we describe the preparation and application of water-in-oil (w/o) emulsions with lipid-stabilized droplet interfaces that emulate the plasma membrane inner leaflet with tunable composition. Fluorescently labeled proteins are easily visualized in these synthetic cell-like droplets on an automated inverted fluorescence microscope, thus allowing for both rapid screening of relative binding and spatiotemporally resolved analyses of for example, protein-interface association and dissociation dynamics and competitive interactions, using commonplace instrumentation. We provide protocols for droplet formation, automated imaging assays and analysis, and the production of the positive control protein BcLOV4, a natural photoreceptor with a directly light-regulated interaction with anionic membrane phospholipids that is useful for optogenetic membrane recruitment.

Novel parameter describing restriction endonucleases: Secondary-Cognate-Specificity and chemical stimulation of TsoI leading to substrate specificity change

Over 470 prototype Type II restriction endonucleases (REases) are currently known. Most recognise specific DNA sequences 4–8 bp long, with very few exceptions cleaving DNA more frequently. TsoI is a thermostable Type IIC enzyme that recognises the DNA sequence TARCCA (R = A or G) and cleaves downstream at N11/N9. The enzyme exhibits extensive top-strand nicking of the supercoiled single-site DNA substrate. The second DNA strand of such substrate is specifically cleaved only in the presence of duplex oligonucleotides containing a cognate site. We have previously shown that some Type IIC/IIG/IIS enzymes from the Thermus-family exhibit ‘affinity star’ activity, which can be induced by the S-adenosyl-L-methionine (SAM) cofactor analogue—sinefungin (SIN). Here, we define a novel type of inherently built-in ‘star’ activity, exemplified by TsoI. The TsoI ‘star’ activity cannot be described under the definition of the classic ‘star’ activity as it is independent of the reaction conditions used and cannot be separated from the cognate specificity. Therefore, we define this phenomenon as Secondary-Cognate-Specificity (SCS). The TsoI SCS comprises several degenerated variants of the cognate site. Although the efficiency of TsoI SCS cleavage is lower in comparison to the cognate TsoI recognition sequence, it can be stimulated by S-adenosyl-L-cysteine (SAC). We present a new route for the chemical synthesis of SAC. The TsoI/SAC REase may serve as a novel tool for DNA manipulation.

Reliable multiplex sequencing with rare index mis-assignment on DNB-based NGS platform

BACKGROUND

Massively-parallel-sequencing, coupled with sample multiplexing, has made genetic tests broadly affordable. However, intractable index mis-assignments (commonly exceeds 1%) were repeatedly reported on some widely used sequencing platforms.

RESULTS

Here, we investigated this quality issue on BGI sequencers using three library preparation methods: whole genome sequencing (WGS) with PCR, PCR-free WGS, and two-step targeted PCR. BGI's sequencers utilize a unique DNA nanoball (DNB) technology which uses rolling circle replication for DNA-nanoball preparation; this linear amplification is PCR free and can avoid error accumulation. We demonstrated that single index mis-assignment from free indexed oligos occurs at a rate of one in 36 million reads, suggesting virtually no index hopping during DNB creation and arraying. Furthermore, the DNB-based NGS libraries have achieved an unprecedentedly low sample-to-sample mis-assignment rate of 0.0001 to 0.0004% under recommended procedures.

CONCLUSIONS

Single indexing with DNB technology provides a simple but effective method for sensitive genetic assays with large sample numbers.

CRISPR/CAS9 targeted CAPTURE of mammalian genomic regions for characterization by NGS

The robust detection of structural variants in mammalian genomes remains a challenge. It is particularly difficult in the case of genetically unstable Chinese hamster ovary (CHO) cell lines with only draft genome assemblies available. We explore the potential of the CRISPR/Cas9 system for the targeted capture of genomic loci containing integrated vectors in CHO-K1-based cell lines followed by next generation sequencing (NGS), and compare it to popular target-enrichment sequencing methods and to whole genome sequencing (WGS). Three different CRISPR/Cas9-based techniques were evaluated; all of them allow for amplification-free enrichment of target genomic regions in the range from 5 to 60 fold, and for recovery of ~15 kb-long sequences with no sequencing artifacts introduced. The utility of these protocols has been proven by the identification of transgene integration sites and flanking sequences in three CHO cell lines. The long enriched fragments helped to identify Escherichia coli genome sequences co-integrated with vectors, and were further characterized by Whole Genome Sequencing (WGS). Other advantages of CRISPR/Cas9-based methods are the ease of bioinformatics analysis, potential for multiplexing, and the production of long target templates for real-time sequencing.

High-throughput, Efficient, and Unbiased Capture of Small RNAs from Low-input Samples for Sequencing

MicroRNAs hold great promise as biomarkers of disease. However, there are few efficient and robust methods for measuring microRNAs from low input samples. Here, we develop a high-throughput sequencing protocol that efficiently captures small RNAs while minimizing inherent biases associated with library production. The protocol is based on early barcoding such that all downstream manipulations can be performed on a pool of many samples thereby reducing reagent usage and workload. We show that the optimization of adapter concentrations along with the addition of nucleotide modifications and random nucleotides increases the efficiency of small RNA capture. We further show, using unique molecular identifiers, that stochastic capture of low input RNA rather than PCR amplification influences the biased quantitation of intermediately and lowly expressed microRNAs. Our improved method allows the processing of tens to hundreds of samples simultaneously while retaining high efficiency quantitation of microRNAs in low input samples from tissues or bodily fluids.

Testing of library preparation methods for transcriptome sequencing of real life glioblastoma and brain tissue specimens: A comparative study with special focus on long non-coding RNAs

Current progress in the field of next-generation transcriptome sequencing have contributed significantly to the study of various malignancies including glioblastoma multiforme (GBM). Differential sequencing of transcriptomes of patients and non-tumor controls has a potential to reveal novel transcripts with significant role in GBM. One such candidate group of molecules are long non-coding RNAs (lncRNAs) which have been proved to be involved in processes such as carcinogenesis, epigenetic modifications and resistance to various therapeutic approaches. To maximize the value of transcriptome sequencing, a proper protocol for library preparation from tissue-derived RNA needs to be found which would produce high quality transcriptome sequencing data and increase the number of detected lncRNAs. It is important to mention that success of library preparation is determined by the quality of input RNA, which is in case of real-life tissue specimens very often altered in comparison to high quality RNA commonly used by manufacturers for development of library preparation chemistry. In the present study, we used GBM and non-tumor brain tissue specimens and compared three different commercial library preparation kits, namely NEXTflex Rapid Directional qRNA-Seq Kit (Bioo Scientific), SENSE Total RNA-Seq Library Prep Kit (Lexogen) and NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (NEB). Libraries generated using SENSE kit were characterized by the most normal distribution of normalized average GC content, the least amount of over-represented sequences and the percentage of ribosomal RNA reads (0.3–1.5%) and highest numbers of uniquely mapped reads and reads aligning to coding regions. However, NEBNext kit performed better having relatively low duplication rates, even transcript coverage and the highest number of hits in Ensembl database for every biotype of our interest including lncRNAs. Our results indicate that out of three approaches the NEBNext library preparation kit was most suitable for the study of lncRNAs via transcriptome sequencing. This was further confirmed by highly consistent data reached in an independent validation on an expanded cohort.

Application of next-generation sequencing technology to precision medicine in cancer: joint consensus of the Tumor Biomarker Committee of the Chinese Society of Clinical Oncology

Next-generation sequencing (NGS) technology is capable of sequencing millions or billions of DNA molecules simultaneously. Therefore, it represents a promising tool for the analysis of molecular targets for the initial diagnosis of disease, monitoring of disease progression, and identifying the mechanism of drug resistance. On behalf of the Tumor Biomarker Committee of the Chinese Society of Clinical Oncology (CSCO) and the China Actionable Genome Consortium (CAGC), the present expert group hereby proposes advisory guidelines on clinical applications of NGS technology for the analysis of cancer driver genes for precision cancer therapy. This group comprises an assembly of laboratory cancer geneticists, clinical oncologists, bioinformaticians, pathologists, and other professionals. After multiple rounds of discussions and revisions, the expert group has reached a preliminary consensus on the need of NGS in clinical diagnosis, its regulation, and compliance standards in clinical sample collection. Moreover, it has prepared NGS criteria, the sequencing standard operation procedure (SOP), data analysis, report, and NGS platform certification and validation.

Expression profiling of snoRNAs in normal hematopoiesis and AML

Small nucleolar RNAs (snoRNAs) are noncoding RNAs that contribute to ribosome biogenesis and RNA splicing by modifying ribosomal RNA and spliceosome RNAs, respectively. We optimized a next-generation sequencing approach and a custom analysis pipeline to identify and quantify expression of snoRNAs in acute myeloid leukemia (AML) and normal hematopoietic cell populations. We show that snoRNAs are expressed in a lineage- and development-specific fashion during hematopoiesis. The most striking examples involve snoRNAs located in 2 imprinted loci, which are highly expressed in hematopoietic progenitors and downregulated during myeloid differentiation. Although most snoRNAs are expressed at similar levels in AML cells compared with CD34⁺, a subset of snoRNAs showed consistent differential expression, with the great majority of these being decreased in the AML samples. Analysis of host gene expression, splicing patterns, and whole-genome sequence data for mutational events did not identify transcriptional patterns or genetic alterations that account for these expression differences. These data provide a comprehensive analysis of the snoRNA transcriptome in normal and leukemic cells and should be helpful in the design of studies to define the contribution of snoRNAs to normal and malignant hematopoiesis.

DEBrowser: interactive differential expression analysis and visualization tool for count data

Background

Sequencing data has become a standard measure of diverse cellular activities. For example, gene expression is accurately measured by RNA sequencing (RNA-Seq) libraries, protein-DNA interactions are captured by chromatin immunoprecipitation sequencing (ChIP-Seq), protein-RNA interactions by crosslinking immunoprecipitation sequencing (CLIP-Seq) or RNA immunoprecipitation (RIP-Seq) sequencing, DNA accessibility by assay for transposase-accessible chromatin (ATAC-Seq), DNase or MNase sequencing libraries. The processing of these sequencing techniques involves library-specific approaches. However, in all cases, once the sequencing libraries are processed, the result is a count table specifying the estimated number of reads originating from each genomic locus. Differential analysis to determine which loci have different cellular activity under different conditions starts with the count table and iterates through a cycle of data assessment, preparation and analysis. Such complex analysis often relies on multiple programs and is therefore a challenge for those without programming skills.

Results

We developed DEBrowser as an R bioconductor project to interactively visualize every step of the differential analysis, without programming. The application provides a rich and interactive web based graphical user interface built on R’s shiny infrastructure. DEBrowser allows users to visualize data with various types of graphs that can be explored further by selecting and re-plotting any desired subset of data. Using the visualization approaches provided, users can determine and correct technical variations such as batch effects and sequencing depth that affect differential analysis. We show DEBrowser’s ease of use by reproducing the analysis of two previously published data sets.

Conclusions

DEBrowser is a flexible, intuitive, web-based analysis platform that enables an iterative and interactive analysis of count data without any requirement of programming knowledge.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5362-x) contains supplementary material, which is available to authorized users.

Identification and Analysis of Genes Associated with Inherited Retinal Diseases

Inherited retinal diseases (IRDs) display a very high degree of clinical and genetic heterogeneity, which poses challenges in finding the underlying defects in known IRD-associated genes and in identifying novel IRD-associated genes. Knowledge on the molecular and clinical aspects of IRDs has increased tremendously in the last decade. Here, we outline the state-of-the-art techniques to find the causative genetic variants, with special attention for next-generation sequencing which can combine molecular diagnostics and retinal disease gene identification. An important aspect is the functional assessment of rare variants with RNA and protein effects which can only be predicted in silico. We therefore describe the in vitro assessment of putative splice defects in human embryonic kidney cells. In addition, we outline the use of stem cell technology to generate photoreceptor precursor cells from patients' somatic cells which can subsequently be used for RNA and protein studies. Finally, we outline the in silico methods to interpret the causality of variants associated with inherited retinal disease and the registry of these variants.

High-Throughput Sequencing in Respiratory, Critical Care, and Sleep Medicine Research. An Official American Thoracic Society Workshop Report

High-throughput, "next-generation" sequencing methods are now being broadly applied across all fields of biomedical research, including respiratory disease, critical care, and sleep medicine. Although there are numerous review articles and best practice guidelines related to sequencing methods and data analysis, there are fewer resources summarizing issues related to study design and interpretation, especially as applied to common, complex, nonmalignant diseases. To address these gaps, a single-day workshop was held at the American Thoracic Society meeting in May 2017, led by the American Thoracic Society Section on Genetics and Genomics. The aim of this workshop was to review the design, analysis, interpretation, and functional follow-up of high-throughput sequencing studies in respiratory, critical care, and sleep medicine research. This workshop brought together experts in multiple fields, including genetic epidemiology, biobanking, bioinformatics, and research ethics, along with physician-scientists with expertise in a range of relevant diseases. The workshop focused on application of DNA and RNA sequencing research in common chronic diseases and did not cover sequencing studies in lung cancer, monogenic diseases (e.g., cystic fibrosis), or microbiome sequencing. Participants reviewed and discussed study design, data analysis and presentation, interpretation, functional follow-up, and reporting of results. This report summarizes the main conclusions of the workshop, specifically addressing the application of these methods in respiratory, critical care, and sleep medicine research. This workshop report may serve as a resource for our research community as well as for journal editors and reviewers of sequencing-based manuscript submissions in our research field.

A Guide to Next Generation Sequence Analysis of Leishmania Genomes

Next generation sequencing (NGS) technology transformed Leishmania genome studies and became an indispensable tool for Leishmania researchers. Recent Leishmania genomics analyses facilitated the discovery of various genetic diversities including single nucleotide polymorphisms (SNPs), copy number variations (CNVs), somy variations, and structural variations in detail and provided valuable insights into the complexity of the genome and gene regulation. Many aspects of Leishmania NGS analyses are similar to those of related pathogens like trypanosomes. However, the analyses of Leishmania genomes face a unique challenge because of the presence of frequent aneuploidy. This makes characterization and interpretation of read depth and somy a key part of Leishmania NGS analyses because read depth affects the accuracy of detection of all genetic variations. However, there are no general guidelines on how to explore and interpret the impact of aneuploidy, and this has made it difficult for biologists and bioinformaticians, especially for beginners, to perform their own analyses and interpret results across different analyses. In this guide we discuss a wide range of topics essential for Leishmania NGS analyses, ranging from how to set up a computational environment for genome analyses, to how to characterize genetic variations among Leishmania samples, and we will particularly focus on chromosomal copy number variation and its impact on genome analyses.

Vaccinia Virus Transcriptome Analysis by RNA Sequencing

RNA-sequencing (RNA-Seq) using next-generation sequencing (NGS) technique is a powerful tool for simultaneous analysis of global transcripts from both vaccinia virus and host cell. Here, we describe an RNA-Seq method for analyzing the vaccinia virus transcriptome from virus-infected HeLa cells. We pay particular attention to vaccinia virus-specific aspects of sample preparation, sequencing, and data analyses, but our method could be modified to analyze transcriptomes of other cells or tissues infected with different poxviruses.

SMARTcleaner: identify and clean off-target signals in SMART ChIP-seq analysis

Background

Noises and artifacts may arise in several steps of the next-generation sequencing (NGS) process. Recently, an NGS library preparation method called SMART, or Switching Mechanism At the 5′ end of the RNA Transcript, is introduced to prepare ChIP-seq (chromatin immunoprecipitation and deep sequencing) libraries from small amount of DNA material, using the DNA SMART ChIP-seq Kit. The protocol adds Ts to the 3′ end of DNA templates, which is subsequently recognized and used by SMART poly(dA) primers for reverse transcription and then addition of PCR primers and sequencing adapters. The poly(dA) primers, however, can anneal to poly(T) sequences in a genome and amplify DNA fragments that are not enriched in the immunoprecipitated DNA templates. This off-target amplification results in false signals in the ChIP-seq data.

Results

Here, we show that the off-target ChIP-seq reads derived from false amplification of poly(T/A) genomic sequences have unique and strand-specific features. Accordingly, we develop a tool (called “SMARTcleaner”) that can exploit these features to remove SMART ChIP-seq artifacts. Application of SMARTcleaner to several SMART ChIP-seq datasets demonstrates that it can remove reads from off-target amplification effectively, leading to significantly improved ChIP-seq peaks and results.

Conclusions

SMARTcleaner could identify and clean the false signals in SMART-based ChIP-seq libraries, leading to improvement in peak calling, and downstream data analysis and interpretation.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2577-4) contains supplementary material, which is available to authorized users.

Belowground fungal community diversity and composition associated with Norway spruce along an altitudinal gradient

Altitudinal gradients provide valuable information about the effects of environmental variables on changes in species richness and composition as well as the distribution of below ground fungal communities. Since most knowledge in this respect has been gathered on aboveground communities, we focused our study towards the characterization of belowground fungal communities associated with two different ages of Norway spruce (Picea abies) trees along an altitudinal gradient. By sequencing the internal transcribed spacer (ITS) region on the Illumina platform, we investigated the fungal communities in a floristically and geologically relatively well explored forest on the slope of Mt. Iseler of the Bavarian Alps. From fine roots and rhizosphere of a total of 90 of Norway spruce trees from 18 plots we detected 1285 taxa, with a range of 167 to 506 (average 377) taxa per plot. Fungal taxa are distributed over 96 different orders belonging to the phyla Ascomycota, Basidiomycota, Chrytridiomycota, Glomeromycota, and Mucoromycota. Overall the Agaricales (438 taxa) and Tremellales (81 taxa) belonging to the Basidiomycota and the Hypocreales (65 spp.) and Helotiales (61 taxa) belonging to the Ascomycota represented the taxon richest orders. The evaluation of our multivariate generalized mixed models indicate that the altitude has a significant influence on the composition of the fungal communities (p < 0.003) and that tree age determines community diversity (p < 0.05). A total of 47 ecological guilds were detected, of which the ectomycorrhizal and saprophytic guilds were the most taxon-rich. Our ITS amplicon Illumina sequencing approach allowed us to characterize a high fungal community diversity that would not be possible to capture with fruiting body surveys alone. We conclude that it is an invaluable tool for diverse monitoring tasks and inventorying biodiversity, especially in the detection of microorganisms developing very ephemeral and/or inconspicuous fruiting bodies or lacking them all together. Results suggest that the altitude mainly influences the community composition, whereas fungal diversity becomes higher in mature/older trees. Finally, we demonstrate that novel techniques from bacterial microbiome analyses are also useful for studying fungal diversity and community structure in a DNA metabarcoding approach, but that incomplete reference sequence databases so far limit effective identification.

Modelling DNA extension and fragmentation in contractive microfluidic devices: a Brownian dynamics and computational fluid dynamics approach

Fragmenting DNA into short pieces is an essential manipulation in many biological studies, ranging from genome sequencing to molecular diagnosis. Among various DNA fragmentation methods, microfluidic hydrodynamic DNA fragmentation has huge advantages especially in terms of handling small-volume samples and being integrated into automatic and all-in-one DNA analysis equipment. Despite the fast progress in experimental studies and applications, a systematic understanding of how DNA molecules are distributed, stretched and fragmented in a confined microfluidic field is still lacking. In this work, we investigate the extension and fragmentation of DNA in a typical contractive microfluidic field, which consists of a shear flow-dominated area and an elongational flow-dominated area, using the Brownian dynamics-computational fluid dynamics method. Our results show that the shear flow at the straight part of the microfluidic channel and the elongational flow at the contractive bottleneck together determine the performance of DNA fragmentation. The average fragment size of DNA decreases with the increase of the strain rate of the elongational flow, and the upstream shear flow can significantly precondition the conformation of DNA to produce shorter and more uniform fragments. A systematic study of the dynamics of DNA fragmentation shows that DNA tends to break at the mid-point when the strain rate of elongational flow is small, and the breakage point largely deviates from the midpoint as the strain rate increases. Our simulation of the thorough DNA fragmentation process in a realistic microfluidic field agrees well with experimental results. We expect that our study can shed new light on the development of future microfluidic devices for DNA fragmentation and integrated DNA analysis devices.

Three decades of nucleic acid aptamer technologies: Lessons learned, progress and opportunities on aptamer development

Aptamers are short single-stranded nucleic acid sequences capable of binding to target molecules in a way similar to antibodies. Due to various advantages such as prolonged shelf life, low batch to batch variation, low/no immunogenicity, freedom to incorporate chemical modification for enhanced stability and targeting capacity, aptamers quickly found their potential in diverse applications ranging from therapy, drug delivery, diagnosis, and functional genomics to bio-sensing. Aptamers are generated by a process called SELEX. However, the current overall success rate of SELEX is far from being satisfactory, and still presents a major obstacle for aptamer-based research and application. The need for an efficient selection strategy consisting of defined procedures to deal with a wide variety of targets is significantly important. In this work, by analyzing key aspects of SELEX including initial library design, target preparation, PCR optimization, and single strand DNA separation, we provide a comprehensive analysis of individual steps to facilitate researchers intending to develop personalized protocols to address many of the obstacles in SELEX. In addition, this review provides suggestions and opinions for future aptamer development procedures to address the concerns on key SELEX steps, and post-SELEX modifications.