Library preparation methods for next-generation sequencing: tone down the bias

Cutaneous Melanoma Classification: The Importance of High-Throughput Genomic Technologies

Cutaneous melanoma is an aggressive tumor responsible for 90% of mortality related to skin cancer. In the recent years, the discovery of driving mutations in melanoma has led to better treatment approaches. The last decade has seen a genomic revolution in the field of cancer. Such genomic revolution has led to the production of an unprecedented mole of data. High-throughput genomic technologies have facilitated the genomic, transcriptomic and epigenomic profiling of several cancers, including melanoma. Nevertheless, there are a number of newer genomic technologies that have not yet been employed in large studies. In this article we describe the current classification of cutaneous melanoma, we review the current knowledge of the main genetic alterations of cutaneous melanoma and their related impact on targeted therapies, and we describe the most recent high-throughput genomic technologies, highlighting their advantages and disadvantages. We hope that the current review will also help scientists to identify the most suitable technology to address melanoma-related relevant questions. The translation of this knowledge and all actual advancements into the clinical practice will be helpful in better defining the different molecular subsets of melanoma patients and provide new tools to address relevant questions on disease management. Genomic technologies might indeed allow to better predict the biological - and, subsequently, clinical - behavior for each subset of melanoma patients as well as to even identify all molecular changes in tumor cell populations during disease evolution toward a real achievement of a personalized medicine.

diffBUM-HMM: a robust statistical modeling approach for detecting RNA flexibility changes in high-throughput structure probing data

Advancing RNA structural probing techniques with next-generation sequencing has generated demands for complementary computational tools to robustly extract RNA structural information amidst sampling noise and variability. We present diffBUM-HMM, a noise-aware model that enables accurate detection of RNA flexibility and conformational changes from high-throughput RNA structure-probing data. diffBUM-HMM is widely compatible, accounting for sampling variation and sequence coverage biases, and displays higher sensitivity than existing methods while robust against false positives. Our analyses of datasets generated with a variety of RNA probing chemistries demonstrate the value of diffBUM-HMM for quantitatively detecting RNA structural changes and RNA-binding protein binding sites.

Bias in RNA-seq Library Preparation: Current Challenges and Solutions

Although RNA sequencing (RNA-seq) has become the most advanced technology for transcriptome analysis, it also confronts various challenges. As we all know, the workflow of RNA-seq is extremely complicated and it is easy to produce bias. This may damage the quality of RNA-seq dataset and lead to an incorrect interpretation for sequencing result. Thus, our detailed understanding of the source and nature of these biases is essential for the interpretation of RNA-seq data, finding methods to improve the quality of RNA-seq experimental, or development bioinformatics tools to compensate for these biases. Here, we discuss the sources of experimental bias in RNA-seq. And for each type of bias, we discussed the method for improvement, in order to provide some useful suggestions for researcher in RNA-seq experimental.

Next-generation sequencing technologies: An overview

Since the days of Sanger sequencing, next-generation sequencing technologies have significantly evolved to provide increased data output, efficiencies, and applications. These next generations of technologies can be categorized based on read length. This review provides an overview of these technologies as two paradigms: short-read, or "second-generation," technologies, and long-read, or "third-generation," technologies. Herein, short-read sequencing approaches are represented by the most prevalent technologies, Illumina and Ion Torrent, and long-read sequencing approaches are represented by Pacific Biosciences and Oxford Nanopore technologies. All technologies are reviewed along with reported advantages and disadvantages. Until recently, short-read sequencing was thought to provide high accuracy limited by read-length, while long-read technologies afforded much longer read-lengths at the expense of accuracy. Emerging developments for third-generation technologies hold promise for the next wave of sequencing evolution, with the co-existence of longer read lengths and high accuracy.

Engineered yeast genomes accurately assembled from pure and mixed samples

Yeast whole genome sequencing (WGS) lacks end-to-end workflows that identify genetic engineering. Here we present Prymetime, a tool that assembles yeast plasmids and chromosomes and annotates genetic engineering sequences. It is a hybrid workflow-it uses short and long reads as inputs to perform separate linear and circular assembly steps. This structure is necessary to accurately resolve genetic engineering sequences in plasmids and the genome. We show this by assembling diverse engineered yeasts, in some cases revealing unintended deletions and integrations. Furthermore, the resulting whole genomes are high quality, although the underlying assembly software does not consistently resolve highly repetitive genome features. Finally, we assemble plasmids and genome integrations from metagenomic sequencing, even with 1 engineered cell in 1000. This work is a blueprint for building WGS workflows and establishes WGS-based identification of yeast genetic engineering.

An improved method for specific-target preamplification PCR analysis of single blastocysts useful for embryo sexing and high-throughput gene expression analysis

Gene expression analysis in preimplantation embryos has been used for answering fundamental questions related to development, prediction of pregnancy outcome, and other topics. Limited amounts of mRNA in preimplantation embryos hinders progress in studying the preimplantation embryo. Here, a method was developed involving direct synthesis and specific-target preamplification (STA) of cDNA for gene expression analysis in single blastocysts. Effective cell lysis and genomic DNA removal steps were incorporated into the method. In addition, conditions for real-time PCR of cDNA generated from these processes were improved. By using this system, reliable embryo sexing results based on expression of sex-chromosome linked genes was demonstrated. Calibration curve analysis of PCR results using the Fluidigm Biomark microfluidic platform (Fluidigm, South San Francisco, CA) was performed to evaluate 96 STA cDNA from single blastocysts. In total, 93.75% of the genes were validated. Robust amplification was detected even when STA cDNA from a single blastocyst was diluted 1,024-fold. Further analysis showed that within-assay variation increased when cycle threshold values exceeded 18. Overall, STA quantitative real-time PCR analysis was shown to be useful for analysis of gene expression of multiple specific targets in single blastocysts.

Evidence for multiple introductions of an invasive wild bee species currently under rapid range expansion in Europe

BACKGROUND

Invasive species are increasingly driving biodiversity decline, and knowledge of colonization dynamics, including both drivers and dispersal modes, are important to prevent future invasions. The bee species Megachile sculpturalis (Hymenoptera: Megachilidae), native to East-Asia, was first recognized in Southeast-France in 2008, and has since spread throughout much of Europe. The spread is very fast, and colonization may result from multiple fronts.

RESULT

To track the history of this invasion, codominant markers were genotyped using Illumina sequencing and the invasion history and degree of connectivity between populations across the European invasion axis were investigated. Distinctive genetic clusters were detected with east-west differentiations in Middle-Europe.

CONCLUSION

We hypothesize that the observed cluster formation resulted from multiple, independent introductions of the species to the European continent. This study draws a first picture of an early invasion stage of this wild bee and forms a foundation for further investigations, including studies of the species in their native Asian range and in the invaded range in North America.

A proof-of-concept study of an automated solution for clinical metagenomic next-generation sequencing

AIMS

Metagenomic next-generation sequencing (mNGS) has been utilized for diagnosing infectious diseases. It is a culture-free and hypothesis-free nucleic acid test for diagnosing all pathogens with known genomic sequences, including bacteria, fungi, viruses and parasites. While this technique greatly expands the clinical capacity of pathogen detection, it is a second-line choice due to lengthy procedures and microbial contaminations introduced from wet-lab processes. As a result, we aimed to reduce the hands-on time and exogenous contaminations in mNGS.

METHODS AND RESULTS

We developed a device (NGSmaster) that automates the wet-lab workflow, including nucleic acid extraction, PCR-free library preparation and purification. It shortens the sample-to-results time to 16 and 18·5 h for DNA and RNA sequencing respectively. We used it to test cultured bacteria for validation of the workflow and bioinformatic pipeline. We also compared PCR-free with PCR-based library prep and discovered no differences in microbial reads. Moreover we analysed results by automation and manual testing and found that automation can significantly reduce microbial contaminations. Finally, we tested artificial and clinical samples and showed mNGS results were concordant with traditional culture.

CONCLUSION

NGSmaster can fulfil the microbiological diagnostic needs in a variety of sample types.

SIGNIFICANCE AND IMPACT OF THE STUDY

This study opens up an opportunity of performing in-house mNGS to reduce turnaround time and workload, instead of transferring potentially contagious specimen to a third-party laboratory.

Detection of genetic variation and base modifications at base-pair resolution on both DNA and RNA

Accurate decoding of nucleic acid variation is critical to understand the complexity and regulation of genome function. Here we use a single-molecule magnetic tweezer (MT) platform to identify sequence variation and map a range of important epigenetic base modifications with high sensitivity, specificity, and precision in the same single molecules of DNA or RNA. We have also developed a highly specific amplification-free CRISPR-Cas enrichment strategy to isolate genomic regions from native DNA. We demonstrate enrichment of DNA from both E. coli and the FMR1 5'UTR coming from cells derived from a Fragile X carrier. From these kilobase-length enriched molecules we could characterize the differential levels of adenine and cytosine base modifications on E. coli, and the repeat expansion length and methylation status of FMR1. Together these results demonstrate that our platform can detect a variety of genetic, epigenetic, and base modification changes concomitantly within the same single molecules.

Exact mapping of Illumina blind spots in the Mycobacterium tuberculosis genome reveals platform-wide and workflow-specific biases

Whole-genome sequencing (WGS) is fundamental to Mycobacterium tuberculosis basic research and many clinical applications. Coverage across Illumina-sequenced M. tuberculosis genomes is known to vary with sequence context, but this bias is poorly characterized. Here, through a novel application of phylogenomics that distinguishes genuine coverage bias from deletions, we discern Illumina ‘blind spots’ in the M. tuberculosis reference genome for seven sequencing workflows. We find blind spots to be widespread, affecting 529 genes, and provide their exact coordinates, enabling salvage of unaffected regions. Fifty-seven pe/ppe genes (the primary families assumed to exhibit Illumina bias) lack blind spots entirely, while the remaining pe/ppe genes account for 55.1 % of blind spots. Surprisingly, we find coverage bias persists in homopolymers as short as 6 bp, shorter tracts than previously reported. While G+C-rich regions challenge all Illumina sequencing workflows, a modified Nextera library preparation that amplifies DNA with a high-fidelity polymerase markedly attenuates coverage bias in G+C-rich and homopolymeric sequences, expanding the ‘Illumina-sequenceable’ genome. Through these findings, and by defining workflow-specific exclusion criteria, we spotlight effective strategies for handling bias in M. tuberculosis Illumina WGS. This empirical analysis framework may be used to systematically evaluate coverage bias in other species using existing sequencing data.

Optimization and Validation of Multimodular, Long-Range PCR-Based Next-Generation Sequencing Assays for Comprehensive Detection of Mutation in Tuberous Sclerosis Complex

The genetic diagnosis of tuberous sclerosis complex is difficult because of its broad spectrum of mutations. In addition to point mutations in coding regions, intragenic or chromosomal-level large deletions, deep intronic splicing mutations, and mosaic mutations represent a significant proportion of the mutations. In this study, multimodular, long-range PCR-based next-generation sequencing assays were optimized and validated using >100 samples with known TSC1 and TSC2 variants. Multiplex, long-range PCR covering the entire genomic region of both genes detected all 138 known variants; however, it also yielded false-positive results. Intragenic large deletions were detected with accurate breakpoint sequences. Chromosomal-level deletions were estimated by discordant allele segregation in the family and confirmed by DNA microarray. Deep intronic mutations were verified using a combination of long-range DNA PCR and full-length mRNA sequencing. DNA samples were mixed to simulate mosaic mutations, and most variants were detected but could not be distinguished from equivalently detected false-positive results. Repeated false-positive results were classified, and the strategy of selecting the common variants detected in the duplicate analysis and eliminating known false-positive results improved the sensitivity (85.2%) and positive predictive value (96.6%) of a 10% mosaic simulation. Long-range PCRbased next-generation sequencing is a highly versatile genetic test; however, confirmation tests remain necessary for clinical use because false-positive results cannot be completely eliminated from single experiments.

A Small RNA-Seq Protocol with Less Bias and Improved Capture of 2'-O-Methyl RNAs

The study of small RNAs (sRNAs) by next-generation sequencing (NGS) is challenged by bias issues during library preparation. Several types of sRNAs such as plant microRNAs (miRNAs) carry a 2'-O-methyl (2'-OMe) modification at their 3' terminal nucleotide. This modification adds another level of difficulty as it inhibits 3' adapter ligation. We previously demonstrated that modified versions of the "TruSeq (TS)" protocol have less bias and an improved detection of 2'-OMe RNAs. Here we describe in detail protocol "TS5," which showed the best overall performance. We also provide guidelines for bioinformatics analysis of the sequencing data.

Low-Bias Manipulation of DNA Oligo Pool for Robust Data Storage

In DNA data storage, the massive sequence complexity creates challenges in repeatable and efficient information readout. Here, our study clearly demonstrated that PCR created significant DNA amplification biases due to its inherent mechanism of inefficient priming, product-as-template, and error-spreading prone, which greatly hinder subsequent applications such as data retrieval in DNA-based storage. To mitigate the amplification bias, we recruited an isothermal DNA amplification by combining strand displacement amplification (SDA) with magnetic beads (MB) DNA immobilization for robust, repeated, and low-bias amplification of DNA oligo pool, comprising over 100 thousand oligos, in a primer-free and low-error-spreading fashion. Furthermore, we introduced oligo pool normalization (OPN), a cost-effective and scalable method for normalizing an oligo pool, by which oligo pools comprising from 256 to 1024 distinct oligos were simply modified with improved Gini-index. Therefore, we believe that the combination of SDA and OPN can provide an ideal amplification mechanism for a low-bias copy of a large oligo pool, which is of vital importance for successful data retrieval in DNA information storage.

What determines eukaryotic translation elongation: recent molecular and quantitative analyses of protein synthesis

Protein synthesis from mRNA is an energy-intensive and tightly controlled cellular process. Translation elongation is a well-coordinated, multifactorial step in translation that undergoes dynamic regulation owing to cellular state and environmental determinants. Recent studies involving genome-wide approaches have uncovered some crucial aspects of translation elongation including the mRNA itself and the nascent polypeptide chain. Additionally, these studies have fuelled quantitative and mathematical modelling of translation elongation. In this review, we provide a comprehensive overview of the key determinants of translation elongation. We discuss consequences of ribosome stalling or collision, and how the cells regulate translation in case of such events. Next, we review theoretical approaches and widely used mathematical models that have become an essential ingredient to interpret complex molecular datasets and study translation dynamics quantitatively. Finally, we review recent advances in live-cell reporter and related analysis techniques, to monitor the translation dynamics of single cells and single-mRNA molecules in real time.

Currently Applied Molecular Assays for Identifying ESR1 Mutations in Patients with Advanced Breast Cancer

Approximately 70% of breast cancers, the leading cause of cancer-related mortality worldwide, are positive for the estrogen receptor (ER). Treatment of patients with luminal subtypes is mainly based on endocrine therapy. However, ER positivity is reduced and ESR1 mutations play an important role in resistance to endocrine therapy, leading to advanced breast cancer. Various methodologies for the detection of ESR1 mutations have been developed, and the most commonly used method is next-generation sequencing (NGS)-based assays (50.0%) followed by droplet digital PCR (ddPCR) (45.5%). Regarding the sample type, tissue (50.0%) was more frequently used than plasma (27.3%). However, plasma (46.2%) became the most used method in 2016-2019, in contrast to 2012-2015 (22.2%). In 2016-2019, ddPCR (61.5%), rather than NGS (30.8%), became a more popular method than it was in 2012-2015. The easy accessibility, non-invasiveness, and demonstrated usefulness with high sensitivity of ddPCR using plasma have changed the trends. When using these assays, there should be a comprehensive understanding of the principles, advantages, vulnerability, and precautions for interpretation. In the future, advanced NGS platforms and modified ddPCR will benefit patients by facilitating treatment decisions efficiently based on information regarding ESR1 mutations.

Implementation of High-Throughput Sequencing (HTS) in Aptamer Selection Technology

Aptamers are nucleic acid ligands that bind specifically to a target of interest. Aptamers have gained in popularity due to their high potential for different applications in analysis, diagnostics, and therapeutics. The procedure called systematic evolution of ligands by exponential enrichment (SELEX) is used for aptamer isolation from large nucleic acid combinatorial libraries. The huge number of unique sequences implemented in the in vitro evolution in the SELEX process imposes the necessity of performing extensive sequencing of the selected nucleic acid pools. High-throughput sequencing (HTS) meets this demand of SELEX. Analysis of the data obtained from sequencing of the libraries produced during and after aptamer isolation provides an informative basis for precise aptamer identification and for examining the structure and function of nucleic acid ligands. This review discusses the technical aspects and the potential of the integration of HTS with SELEX.

The SSV-Seq 2.0 PCR-Free Method Improves the Sequencing of Adeno-Associated Viral Vector Genomes Containing GC-Rich Regions and Homopolymers

Adeno-associated viral vectors (AAV) are efficient engineered tools for delivering genetic material into host cells. The commercialization of AAV-based drugs must be accompanied by the development of appropriate quality control (QC) assays. Given the potential risk of co-transfer of oncogenic or immunogenic sequences with therapeutic vectors, accurate methods to assess the level of residual DNA in AAV vector stocks are particularly important. An assay based on high-throughput sequencing (HTS) to identify and quantify DNA species in recombinant AAV batches is developed. Here, it is shown that PCR amplification of regions that have a local GC content >90% and include successive mononucleotide stretches, such as the CAG promoter, can introduce bias during DNA library preparation, leading to drops in sequencing coverage. To circumvent this problem, SSV-Seq 2.0, a PCR-free protocol for sequencing AAV vector genomes containing such sequences, is developed. The PCR-free protocol improves the evenness of the rAAV genome coverage and consequently leads to a more accurate relative quantification of residual DNA. HTS-based assays provide a more comprehensive assessment of DNA impurities and AAV vector genome integrity than conventional QC tests based on real-time PCR and are useful methods to improve the safety and efficacy of these viral vectors.

Characterization and Dynamics of Repeatomes in Closely Related Species of Hieracium (Asteraceae) and Their Synthetic and Apomictic Hybrids

The repetitive content of the plant genome (repeatome) often represents its largest fraction and is frequently correlated with its size. Transposable elements (TEs), the main component of the repeatome, are an important driver in the genome diversification due to their fast-evolving nature. Hybridization and polyploidization events are hypothesized to induce massive bursts of TEs resulting, among other effects, in an increase of copy number and genome size. Little is known about the repeatome dynamics following hybridization and polyploidization in plants that reproduce by apomixis (asexual reproduction via seeds). To address this, we analyzed the repeatomes of two diploid parental species, Hieracium intybaceum and H. prenanthoides (sexual), their diploid F1 synthetic and their natural triploid hybrids (H. pallidiflorum and H. picroides, apomictic). Using low-coverage next-generation sequencing (NGS) and a graph-based clustering approach, we detected high overall similarity across all major repeatome categories between the parental species, despite their large phylogenetic distance. Medium and highly abundant repetitive elements comprise ∼70% of Hieracium genomes; most prevalent were Ty3/Gypsy chromovirus Tekay and Ty1/Copia Maximus-SIRE elements. No TE bursts were detected, neither in synthetic nor in natural hybrids, as TE abundance generally followed theoretical expectations based on parental genome dosage. Slight over- and under-representation of TE cluster abundances reflected individual differences in genome size. However, in comparative analyses, apomicts displayed an overabundance of pararetrovirus clusters not observed in synthetic hybrids. Substantial deviations were detected in rDNAs and satellite repeats, but these patterns were sample specific. rDNA and satellite repeats (three of them were newly developed as cytogenetic markers) were localized on chromosomes by fluorescence in situ hybridization (FISH). In a few cases, low-abundant repeats (5S rDNA and certain satellites) showed some discrepancy between NGS data and FISH results, which is due partly to the bias of low-coverage sequencing and partly to low amounts of the satellite repeats or their sequence divergence. Overall, satellite DNA (including rDNA) was markedly affected by hybridization, but independent of the ploidy or reproductive mode of the progeny, whereas bursts of TEs did not play an important role in the evolutionary history of Hieracium.

Unlocking the efficiency of genomics laboratories with robotic liquid-handling

In research and clinical genomics laboratories today, sample preparation is the bottleneck of experiments, particularly when it comes to high-throughput next generation sequencing (NGS). More genomics laboratories are now considering liquid-handling automation to make the sequencing workflow more efficient and cost effective. The question remains as to its suitability and return on investment. A number of points need to be carefully considered before introducing robots into biological laboratories. Here, we describe the state-of-the-art technology of both sophisticated and do-it-yourself (DIY) robotic liquid-handlers and provide a practical review of the motivation, implications and requirements of laboratory automation for genome sequencing experiments.

OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data

Over the past decade, a large amount of RNA sequencing (RNA-seq) data were deposited in public repositories, and more are being produced at an unprecedented rate. However, there are few open source tools with point-and-click interfaces that are versatile and offer streamlined comprehensive analysis of RNA-seq datasets. To maximize the capitalization of these vast public resources and facilitate the analysis of RNA-seq data by biologists, we developed a web application called OneStopRNAseq for the one-stop analysis of RNA-seq data. OneStopRNAseq has user-friendly interfaces and offers workflows for common types of RNA-seq data analyses, such as comprehensive data-quality control, differential analysis of gene expression, exon usage, alternative splicing, transposable element expression, allele-specific gene expression quantification, and gene set enrichment analysis. Users only need to select the desired analyses and genome build, and provide a Gene Expression Omnibus (GEO) accession number or Dropbox links to sequence files, alignment files, gene-expression-count tables, or rank files with the corresponding metadata. Our pipeline facilitates the comprehensive and efficient analysis of private and public RNA-seq data.

Sediment-associated bacterial community and predictive functionalities are influenced by choice of 16S ribosomal RNA hypervariable region(s): An amplicon-based diversity study

Meta-omics approaches such as high-throughput sequencing of 16S hypervariable region(s) [HVR(s)] is extensively applied for profiling microbial community. Several studies have deciphered the influence of HVR(s) on bacterial diversity; most of these were devoted to human body habitats. Extent to which targeted HVR(s) influences the diversity estimates of environmental samples is rather unclear. Here, we evaluated the performance of five widely used universal primer pairs spanning V1-V3, V3-V4, V4, V5-V6 and V7-V9 HVRs to characterize bacterial diversity and predictive functionality of complex marine sediments. Obtained results revealed that the HVR(s) V4 and V5-V6 represented the higher species richness than others while, V1-V3 and V7-V9 were unsuccessful to detect Bacteroidetes and Planctomycetes. Further, PICRUSt analysis showed that the selected HVR(s) also had significant impact on the predictive functional profile. Conclusively, this study proved that HVR selection has a profound effect on overall results and thus should be selected with utmost caution.

Improved normalization of species count data in ecology by scaling with ranked subsampling (SRS): application to microbial communities

Background

Analysis of species count data in ecology often requires normalization to an identical sample size. Rarefying (random subsampling without replacement), which is the current standard method for normalization, has been widely criticized for its poor reproducibility and potential distortion of the community structure. In the context of microbiome count data, researchers explicitly advised against the use of rarefying. Here we introduce a normalization method for species count data called scaling with ranked subsampling (SRS) and demonstrate its suitability for the analysis of microbial communities.

Methods

SRS consists of two steps. In the scaling step, the counts for all species or operational taxonomic units (OTUs) are divided by a scaling factor chosen in such a way that the sum of scaled counts equals the selected total number of counts C_min. The relative frequencies of all OTUs remain unchanged. In the subsequent ranked subsampling step, non-integer count values are converted into integers by an algorithm that minimizes subsampling error with regard to the population structure (relative frequencies of species or OTUs) while keeping the total number of counts equal C_min. SRS and rarefying were compared by normalizing a test library representing a soil bacterial community. Common parameters of biodiversity and population structure (Shannon index H’, species richness, species composition, and relative abundances of OTUs) were determined for libraries normalized to different size by rarefying as well as SRS with 10,000 replications each. An implementation of SRS in R is available for download (https://doi.org/10.20387/BONARES-2657-1NP3).

Results

SRS showed greater reproducibility and preserved OTU frequencies and alpha diversity better than rarefying. The variance in Shannon diversity increased with the reduction of the library size after rarefying but remained zero for SRS. Relative abundances of OTUs strongly varied among libraries generated by rarefying, whereas libraries normalized by SRS showed only negligible variation. Bray–Curtis index of dissimilarity among replicates of the same library normalized by rarefying revealed a large variation in species composition, which reached complete dissimilarity (not a single OTU shared) among some libraries rarefied to a small size. The dissimilarity among replicated libraries normalized by SRS remained negligibly low at each library size. The variance in dissimilarity increased with the decreasing library size after rarefying, whereas it remained either zero or negligibly low after SRS.

Conclusions

Normalization of OTU or species counts by scaling with ranked subsampling preserves the original community structure by minimizing subsampling errors. We therefore propose SRS for the normalization of biological count data.

Discovery of a transcriptomic core of genes shared in 8 primary retinoblastoma with a novel detection score analysis

PURPOSE

Expression microarrays are powerful technology that allows large-scale analysis of RNA profiles in a tissue; these platforms include underexploited detection scores outputs. We developed an algorithm using the detection score, to generate a detection profile of shared elements in retinoblastoma as well as to determine its transcriptomic size and structure.

METHODS

We analyzed eight briefly cultured primary retinoblastomas with the Human transcriptome array 2.0 (HTA2.0). Transcripts and genes detection scores were determined using the Detection Above Background algorithm (DABG). We used unsupervised and supervised computational tools to analyze detected and undetected elements; WebGestalt was used to explore functions encoded by genes in relevant clusters and performed experimental validation.

RESULTS

We found a core cluster with 7,513 genes detected and shared by all samples, 4,321 genes in a cluster that was commonly absent, and 7,681 genes variably detected across the samples accounting for tumor heterogeneity. Relevant pathways identified in the core cluster relate to cell cycle, RNA transport, and DNA replication. We performed a kinome analysis of the core cluster and found 4 potential therapeutic kinase targets. Through analysis of the variably detected genes, we discovered 123 differentially expressed transcripts between bilateral and unilateral cases.

CONCLUSIONS

This novel analytical approach allowed determining the retinoblastoma transcriptomic size, a shared active transcriptomic core among the samples, potential therapeutic target kinases shared by all samples, transcripts related to inter tumor heterogeneity, and to determine transcriptomic profiles without the need of control tissues. This approach is useful to analyze other cancer or tissue types.

Reverse Transcriptase: From Transcriptomics to Genome Editing

Reverse transcriptases (RTs) are enzymes that can generate a complementary strand of DNA (cDNA) from RNA. Coupled with PCR, RTs have been widely used to detect RNAs and to clone expressed genes. Classical retroviral RTs have been improved by protein engineering. These enzymes and newly characterized RTs are key elements in the development of next-generation sequencing techniques that are now being applied to the study of transcriptomics. In addition, engineered RTs fused to a CRISPR/Cas9 nickase have recently shown great potential as tools to manipulate eukaryotic genomes. In this review, we discuss the properties and uses of wild type and engineered RTs in biotechnological applications, from conventional RT-PCR to recently introduced prime editing.

A bioinformatics approach to identify novel long, non-coding RNAs in breast cancer cell lines from an existing RNA-sequencing dataset

Breast cancer research has traditionally centred on genomic alterations, hormone receptor status and changes in cancer-related proteins to provide new avenues for targeted therapies. Due to advances in next generation sequencing technologies, there has been the emergence of long, non-coding RNAs (lncRNAs) as regulators of normal cellular events, with links to various disease states, including breast cancer. Here we describe our bioinformatic analyses of a previously published RNA sequencing (RNA-seq) dataset to identify lncRNAs with altered expression levels in a subset of breast cancer cell lines. Using a previously published RNA-seq dataset of 675 cancer cell lines, a subset of 18 cell lines was selected for our analyses that included 16 breast cancer lines, one ductal carcinoma in situ line and one normal-like breast epithelial cell line. Principal component analysis demonstrated correlation with well-established categorisation methods of breast cancer (i.e. luminal A/B, HER2 enriched and basal-like A/B). Through detailed comparison of differentially expressed lncRNAs in each breast cancer sub-type with normal-like breast epithelial cells, we identified 15 lncRNAs with consistently altered expression, including three uncharacterised lncRNAs. Utilising data from The Cancer Genome Atlas (TCGA) and The Genotype Tissue Expression (GETx) project via Gene Expression Profiling Interactive Analysis (GEPIA2), we assessed clinical relevance of several identified lncRNAs with invasive breast cancer. Lastly, we determined the relative expression level of six lncRNAs across a spectrum of breast cancer cell lines to experimentally confirm the findings of our bioinformatic analyses. Overall, we show that the use of existing RNA-seq datasets, if re-analysed with modern bioinformatic tools, can provide a valuable resource to identify lncRNAs that could have important biological roles in oncogenesis and tumour progression.

Next-generation forward genetic screens: using simulated data to improve the design of mapping-by-sequencing experiments in Arabidopsis

Forward genetic screens have successfully identified many genes and continue to be powerful tools for dissecting biological processes in Arabidopsis and other model species. Next-generation sequencing technologies have revolutionized the time-consuming process of identifying the mutations that cause a phenotype of interest. However, due to the cost of such mapping-by-sequencing experiments, special attention should be paid to experimental design and technical decisions so that the read data allows to map the desired mutation. Here, we simulated different mapping-by-sequencing scenarios. We first evaluated which short-read technology was best suited for analyzing gene-rich genomic regions in Arabidopsis and determined the minimum sequencing depth required to confidently call single nucleotide variants. We also designed ways to discriminate mutagenesis-induced mutations from background Single Nucleotide Polymorphisms in mutants isolated in Arabidopsis non-reference lines. In addition, we simulated bulked segregant mapping populations for identifying point mutations and monitored how the size of the mapping population and the sequencing depth affect mapping precision. Finally, we provide the computational basis of a protocol that we already used to map T-DNA insertions with paired-end Illumina-like reads, using very low sequencing depths and pooling several mutants together; this approach can also be used with single-end reads as well as to map any other insertional mutagen. All these simulations proved useful for designing experiments that allowed us to map several mutations in Arabidopsis.

Defective Strand-Displacement DNA Synthesis Due to Accumulation of Thymidine Analogue Resistance Mutations in HIV-2 Reverse Transcriptase

Retroviral reverse transcriptases (RTs) have the ability to carry out strand displacement DNA synthesis in the absence of accessory proteins. Although studies with RTs and other DNA polymerases suggest that fingers subdomain residues participate in strand displacement, molecular determinants of this activity are still unknown. A mutant human immunodeficiency virus type 2 (HIV-2) RT (M41L/D67N/K70R/S215Y) with low strand displacement activity was identified after screening a panel of purified enzymes, including several antiretroviral drug-resistant HIV-1 and HIV-2 RTs. In HIV-1, resistance to zidovudine and other thymidine analogues is conferred by different combinations of M41L, D67N, K70R, L210W, T215F/Y, and K219E/Q (designated as thymidine analogue resistance-associated mutations (TAMs)). However, those changes are rarely selected in HIV-2. We show that the strand displacement activity of HIV-2_ROD mutants M41L/S215Y and D67N/K70R was only slightly reduced compared to the wild-type RT. In contrast, mutants D67N/K70R/S215Y and M41L/D67N/K70R/S215Y were the most defective RTs in reactions carried out with nicked and gapped substrates. Moreover, these enzymes showed the lowest nucleotide incorporation rates in assays carried out with strand displacement substrates. Unlike in HIV-2, substitutions M41L/T215Y and D67N/K70R/T215Y/K219Q had no effect on the strand displacement activity of HIV-1_BH10 RT. The strand displacement efficiencies of HIV-2_ROD RTs were consistent with the lower replication capacity of HIV-2 strains bearing the four major TAMs in their RT. Our results highlight the role of the fingers subdomain in strand displacement. These findings might be important for the development of strand-displacement defective RTs.

Food authentication in real life: How to link nontargeted approaches with routine analytics?

In times of increasing globalization and the resulting complexity of trade flows, securing food quality is an increasing challenge. The development of analytical methods for checking the integrity and, thus, the safety of food is one of the central questions for actors from science, politics, and industry. Targeted methods, for the detection of a few selected analytes, still play the most important role in routine analysis. In the past 5 years, nontargeted methods that do not aim at individual analytes but on analyte profiles that are as comprehensive as possible have increasingly come into focus. Instead of investigating individual chemical structures, data patterns are collected, evaluated and, depending on the problem, fed into databases that can be used for further nontargeted approaches. Alternatively, individual markers can be extracted and transferred to targeted methods. Such an approach requires (i) the availability of authentic reference material, (ii) the corresponding high-resolution laboratory infrastructure, and (iii) extensive expertise in processing and storing very large amounts of data. Probably due to the requirements mentioned above, only a few methods have really established themselves in routine analysis. This review article focuses on the establishment of nontargeted methods in routine laboratories. Challenges are summarized and possible solutions are presented.

Consistent RNA sequencing contamination in GTEx and other data sets

A challenge of next generation sequencing is read contamination. We use Genotype-Tissue Expression (GTEx) datasets and technical metadata along with RNA-seq datasets from other studies to understand factors that contribute to contamination. Here we report, of 48 analyzed tissues in GTEx, 26 have variant co-expression clusters of four highly expressed and pancreas-enriched genes (PRSS1, PNLIP, CLPS, and/or CELA3A). Fourteen additional highly expressed genes from other tissues also indicate contamination. Sample contamination is strongly associated with a sample being sequenced on the same day as a tissue that natively expresses those genes. Discrepant SNPs across four contaminating genes validate the contamination. Low-level contamination affects ~40% of samples and leads to numerous eQTL assignments in inappropriate tissues among these 18 genes. This type of contamination occurs widely, impacting bulk and single cell (scRNA-seq) data set analysis. In conclusion, highly expressed, tissue-enriched genes basally contaminate GTEx and other datasets impacting analyses.

Development of a RACE-based RNA-Seq approach to characterize the T-cell receptor repertoire of porcine γδ T cells

Recent data suggest that porcine γδ T cells exhibit a similar degree of functional plasticity as human and murine γδ T cells. Due to the high frequency of TCR-γδ⁺ cells in blood and secondary lymphatic organs, the pig is an attractive model to study these cells, especially their combined features of the innate and the adaptive immune system. Using a 5' RACE-like approach, we translated a human/murine NGS library preparation strategy to capture full-length V-(D)-J TRG and TRD clonotypes in swine. After oligo(dT) primed conversion of input RNA, the cDNA population was enriched for full-length V(D)J TCR transcripts with porcine-specific primers including Illumina adaptor sequences as overhangs for Illumina MiSeq analysis. After quality control and processing by FastQC and ea-utils, porcine TRG and TRD sequences were mapped against the human IMGT reference directory. Porcine blood-derived CD2⁺ and CD2‾ TCR-γδ⁺ cells exhibited two distinct clonotypes Vγ11JγP1 (74.6%) and Vγ10JγP1 (57.7%), respectively. Despite the high TCR-δ diversity among CD2⁺ cells (39 clonotypes), both subsets shared the same abundant Vδ1DδxJδ4 clonotype at approximately identically frequencies (CD2⁺: 31.2%; CD2‾: 37.0%). The flexible nature of this approach will facilitate the assessment of organ-specific phenotypes of γδ T cell subsets alongside with their respective TCR diversity at single cell resolution.

Comparison of the sequencing bias of currently available library preparation kits for Illumina sequencing of bacterial genomes and metagenomes

In bacterial genome and metagenome sequencing, Illumina sequencers are most frequently used due to their high throughput capacity, and multiple library preparation kits have been developed for Illumina platforms. Here, we systematically analysed and compared the sequencing bias generated by currently available library preparation kits for Illumina sequencing. Our analyses revealed that a strong sequencing bias is introduced in low-GC regions by the Nextera XT kit. The level of bias introduced is dependent on the level of GC content; stronger bias is generated as the GC content decreases. Other analysed kits did not introduce this strong sequencing bias. The GC content-associated sequencing bias introduced by Nextera XT was more remarkable in metagenome sequencing of a mock bacterial community and seriously affected estimation of the relative abundance of low-GC species. The results of our analyses highlight the importance of selecting proper library preparation kits according to the purposes and targets of sequencing, particularly in metagenome sequencing, where a wide range of microbial species with various degrees of GC content is present. Our data also indicate that special attention should be paid to which library preparation kit was used when analysing and interpreting publicly available metagenomic data.

The Tempo and Mode of Angiosperm Mitochondrial Genome Divergence Inferred from Intraspecific Variation in Arabidopsis thaliana

The mechanisms of sequence divergence in angiosperm mitochondrial genomes have long been enigmatic. In particular, it is difficult to reconcile the rapid divergence of intergenic regions that can make non-coding sequences almost unrecognizable even among close relatives with the unusually high levels of sequence conservation found in genic regions. It has been hypothesized that different mutation and repair mechanisms act on genic and intergenic sequences or alternatively that mutational input is relatively constant but that selection has strikingly different effects on these respective regions. To test these alternative possibilities, we analyzed mtDNA divergence within Arabidopsis thaliana, including variants from the 1001 Genomes Project and changes accrued in published mutation accumulation (MA) lines. We found that base-substitution frequencies are relatively similar for intergenic regions and synonymous sites in coding regions, whereas indel and nonsynonymous substitutions rates are greatly depressed in coding regions, supporting a conventional model in which mutation/repair mechanisms are consistent throughout the genome but differentially filtered by selection. Most types of sequence and structural changes were undetectable in 10-generation MA lines, but we found significant shifts in relative copy number across mtDNA regions for lines grown under stressed vs. benign conditions. We confirmed quantitative variation in copy number across the A. thaliana mitogenome using both whole-genome sequencing and droplet digital PCR, further undermining the classic but oversimplified model of a circular angiosperm mtDNA structure. Our results suggest that copy number variation is one of the most fluid features of angiosperm mitochondrial genomes.

Comparison of Mendeliome exome capture kits for use in clinical diagnostics

Next generation sequencing has disrupted genetic testing, allowing far more scope in the tests applied. The appropriate sections of the genome to be tested can now be readily selected, from single mutations to whole-genome sequencing. One product offering within this spectrum are focused exomes, targeting ~5,000 genes know to be implicated in human disease. These are designed to offer a flexible platform offering high diagnostic yield with a reduction in sequencing requirement compared to whole exome sequencing. Here, we have undertaken sequencing of control DNA samples and compare two kits, the Illumina TruSight One and the Agilent SureSelect Focused Exome. Characteristics of the kits are comprehensively evaluated. Despite the larger design region of the Agilent kit, we find that the Illumina kit performs better in terms of gene coverage, as well as coverage of clinically relevant loci. We provide exhaustive coverage statistics for each kit to aid the assessment of their suitability and provide read data for control DNA samples to allow for bioinformatic benchmarking by users developing pipelines for these data.

GC bias affects genomic and metagenomic reconstructions, underrepresenting GC-poor organisms

BACKGROUND

Metagenomic sequencing is a well-established tool in the modern biosciences. While it promises unparalleled insights into the genetic content of the biological samples studied, conclusions drawn are at risk from biases inherent to the DNA sequencing methods, including inaccurate abundance estimates as a function of genomic guanine-cytosine (GC) contents.

RESULTS

We explored such GC biases across many commonly used platforms in experiments sequencing multiple genomes (with mean GC contents ranging from 28.9% to 62.4%) and metagenomes. GC bias profiles varied among different library preparation protocols and sequencing platforms. We found that our workflows using MiSeq and NextSeq were hindered by major GC biases, with problems becoming increasingly severe outside the 45-65% GC range, leading to a falsely low coverage in GC-rich and especially GC-poor sequences, where genomic windows with 30% GC content had >10-fold less coverage than windows close to 50% GC content. We also showed that GC content correlates tightly with coverage biases. The PacBio and HiSeq platforms also evidenced similar profiles of GC biases to each other, which were distinct from those seen in the MiSeq and NextSeq workflows. The Oxford Nanopore workflow was not afflicted by GC bias.

CONCLUSIONS

These findings indicate potential sources of difficulty, arising from GC biases, in genome sequencing that could be pre-emptively addressed with methodological optimizations provided that the GC biases inherent to the relevant workflow are understood. Furthermore, it is recommended that a more critical approach be taken in quantitative abundance estimates in metagenomic studies. In the future, metagenomic studies should take steps to account for the effects of GC bias before drawing conclusions, or they should use a demonstrably unbiased workflow.

Deep sequencing of tRNA's 3'-termini sheds light on CCA-tail integrity and maturation

The 3'-termini of tRNA are the point of amino acid linkage and thus crucial for their function in delivering amino acids to the ribosome and other enzymes. Therefore, to provide tRNA functionality, cells have to ensure the integrity of the 3'-terminal CCA-tail, which is generated during maturation by the 3'-trailer processing machinery and maintained by the CCA-adding enzyme. We developed a new tRNA sequencing method that is specifically tailored to assess the 3'-termini of E. coli tRNA. Intriguingly, we found a significant fraction of tRNAs with damaged CCA-tails under exponential growth conditions and, surprisingly, this fraction decreased upon transition into stationary phase. Interestingly, tRNAs bearing guanine as a discriminator base are generally unaffected by CCA-tail damage. In addition, we showed tRNA species-specific 3'-trailer processing patterns and reproduced in vitro findings on preferences of the maturation enzyme RNase T in vivo.

A tunable filter for high molecular weight DNA selection and linked-read sequencing

In third generation sequencing, the production of quality data requires the selection of molecules longer than ∼20 kbp, but the size selection threshold of most purification technologies is smaller than this target. Here, we describe a technology operated in a capillary with a tunable selection threshold in the range of 3 to 40 kbp controlled by an electric field. We demonstrate that the selection cut-off is sharp, the purification yield is high, and the purification throughput is scalable. We also provide an analytical model that the actuation settings of the filter. The selection of high molecular weight genomic DNA from the melon Cucumis melo L., a diploid organism of ∼0.45 Gbp, is then reported. Linked-read sequencing data show that the N50 phase block size, which scores the correct representation of two chromosomes, is enhanced by a factor of 2 after size selection, establishing the relevance and versatility of our technology.

Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics

Clinical genetics has an important role in the healthcare system to provide a definitive diagnosis for many rare syndromes. It also can have an influence over genetics prevention, disease prognosis and assisting the selection of the best options of care/treatment for patients. Next-generation sequencing (NGS) has transformed clinical genetics making possible to analyze hundreds of genes at an unprecedented speed and at a lower price when comparing to conventional Sanger sequencing. Despite the growing literature concerning NGS in a clinical setting, this review aims to fill the gap that exists among (bio)informaticians, molecular geneticists and clinicians, by presenting a general overview of the NGS technology and workflow. First, we will review the current NGS platforms, focusing on the two main platforms Illumina and Ion Torrent, and discussing the major strong points and weaknesses intrinsic to each platform. Next, the NGS analytical bioinformatic pipelines are dissected, giving some emphasis to the algorithms commonly used to generate process data and to analyze sequence variants. Finally, the main challenges around NGS bioinformatics are placed in perspective for future developments. Even with the huge achievements made in NGS technology and bioinformatics, further improvements in bioinformatic algorithms are still required to deal with complex and genetically heterogeneous disorders.

Bradyrhizobium as the Only Rhizobial Inhabitant of Mung Bean (Vigna radiata) Nodules in Tropical Soils: A Strategy Based on Microbiome for Improving Biological Nitrogen Fixation Using Bio-Products

The mung bean has a great potential under tropical conditions given its high content of grain protein. Additionally, its ability to benefit from biological nitrogen fixation (BNF) through association with native rhizobia inhabiting nodule microbiome provides most of the nitrogen independence on fertilizers. Soil microbial communities which are influenced by biogeographical factors and soil properties, represent a source of rhizobacteria capable of stimulating plant growth. The objective of this study is to support selection of beneficial bacteria that form positive interactions with mung bean plants cultivated in tropical soils, as part of a seed inoculation program for increasing grain yield based on the BNF and other mechanisms. Two mung bean genotypes (Camaleão and Esmeralda) were cultivated in 10 soil samples. Nodule microbiome was characterized by next-generation sequencing using Illumina MiSeq 16S rRNA. More than 99% of nodule sequences showed similarity with Bradyrhizobium genus, the only rhizobial present in nodules in our study. Higher bacterial diversity of soil samples collected in agribusiness areas (MW_MT-I, II or III) was associated with Esmeralda genotype, while an organic agroecosystem soil sample (SE_RJ-V) showed the highest bacterial diversity independent of genotype. Furthermore, OTUs close to Bradyrhizobium elkanii have dominated in all soil samples, except in the sample from the organic agroecosystem, where just B. japonicum was present. Bacterial community of mung bean nodules is mainly influenced by soil pH, K, Ca, and P. Besides a difference on nodule colonization by OTU sequences close to the Pseudomonas genus regarding the two genotypes was detected too. Although representing a small rate, around 0.1% of the total, Pseudomonas OTUs were only retrieved from nodules of Esmeralda genotype, suggesting a different trait regarding specificity between macro- and micro-symbionts. The microbiome analysis will guide the next steps in the development of an inoculant for mung bean aiming to promote plant growth and grain yield, composed either by an efficient Bradyrhizobium strain on its own or co-inoculated with a Pseudomonas strain. Considering the results achieved, the assessment of microbial ecology parameters is a potent coadjuvant capable to accelerate the inoculant development process and to improve the benefits to the crop by soil microorganisms.

High efficiency error suppression for accurate detection of low-frequency variants

Detection of cancer-associated somatic mutations has broad applications for oncology and precision medicine. However, this becomes challenging when cancer-derived DNA is in low abundance, such as in impure tissue specimens or in circulating cell-free DNA. Next-generation sequencing (NGS) is particularly prone to technical artefacts that can limit the accuracy for calling low-allele-frequency mutations. State-of-the-art methods to improve detection of low-frequency mutations often employ unique molecular identifiers (UMIs) for error suppression; however, these methods are highly inefficient as they depend on redundant sequencing to assemble consensus sequences. Here, we present a novel strategy to enhance the efficiency of UMI-based error suppression by retaining single reads (singletons) that can participate in consensus assembly. This 'Singleton Correction' methodology outperformed other UMI-based strategies in efficiency, leading to greater sensitivity with high specificity in a cell line dilution series. Significant benefits were seen with Singleton Correction at sequencing depths ≤16 000×. We validated the utility and generalizability of this approach in a cohort of >300 individuals whose peripheral blood DNA was subjected to hybrid capture sequencing at ∼5000× depth. Singleton Correction can be incorporated into existing UMI-based error suppression workflows to boost mutation detection accuracy, thus improving the cost-effectiveness and clinical impact of NGS.

Rapid, multiplexed, whole genome and plasmid sequencing of foodborne pathogens using long-read nanopore technology

U.S. public health agencies have employed next-generation sequencing (NGS) as a tool to quickly identify foodborne pathogens during outbreaks. Although established short-read NGS technologies are known to provide highly accurate data, long-read sequencing is still needed to resolve highly-repetitive genomic regions and genomic arrangement, and to close the sequences of bacterial chromosomes and plasmids. Here, we report the use of long-read nanopore sequencing to simultaneously sequence the entire chromosome and plasmid of Salmonella enterica subsp. enterica serovar Bareilly and Escherichia coli O157:H7. We developed a rapid and random sequencing approach coupled with de novo genome assembly within a customized data analysis workflow that uses publicly-available tools. In sequencing runs as short as four hours, using the MinION instrument, we obtained full-length genomes with an average identity of 99.87% for Salmonella Bareilly and 99.89% for E. coli in comparison to the respective MiSeq references. These nanopore-only assemblies provided readily available information on serotype, virulence factors, and antimicrobial resistance genes. We also demonstrate the potential of nanopore sequencing assemblies for rapid preliminary phylogenetic inference. Nanopore sequencing provides additional advantages as very low capital investment and footprint, and shorter (10 hours library preparation and sequencing) turnaround time compared to other NGS technologies.

Transcriptome profiling of mouse samples using nanopore sequencing of cDNA and RNA molecules

Our vision of DNA transcription and splicing has changed dramatically with the introduction of short-read sequencing. These high-throughput sequencing technologies promised to unravel the complexity of any transcriptome. Generally gene expression levels are well-captured using these technologies, but there are still remaining caveats due to the limited read length and the fact that RNA molecules had to be reverse transcribed before sequencing. Oxford Nanopore Technologies has recently launched a portable sequencer which offers the possibility of sequencing long reads and most importantly RNA molecules. Here we generated a full mouse transcriptome from brain and liver using the Oxford Nanopore device. As a comparison, we sequenced RNA (RNA-Seq) and cDNA (cDNA-Seq) molecules using both long and short reads technologies and tested the TeloPrime preparation kit, dedicated to the enrichment of full-length transcripts. Using spike-in data, we confirmed that expression levels are efficiently captured by cDNA-Seq using short reads. More importantly, Oxford Nanopore RNA-Seq tends to be more efficient, while cDNA-Seq appears to be more biased. We further show that the cDNA library preparation of the Nanopore protocol induces read truncation for transcripts containing internal runs of T’s. This bias is marked for runs of at least 15 T’s, but is already detectable for runs of at least 9 T’s and therefore concerns more than 20% of expressed transcripts in mouse brain and liver. Finally, we outline that bioinformatics challenges remain ahead for quantifying at the transcript level, especially when reads are not full-length. Accurate quantification of repeat-associated genes such as processed pseudogenes also remains difficult, and we show that current mapping protocols which map reads to the genome largely over-estimate their expression, at the expense of their parent gene.

Inside the Black Box: What Makes SELEX Better?

Aptamers are small oligonucleotides that are capable of binding specifically to a target, with impressive potential for analysis, diagnostics, and therapeutics applications. Aptamers are isolated from large nucleic acid combinatorial libraries using an iterative selection process called SELEX (Systematic Evolution of Ligands by EXponential enrichment). Since being implemented 30 years ago, the SELEX protocol has undergone many modifications and improvements, but it remains a laborious, time-consuming, and costly method, and the results are not always successful. Each step in the aptamer selection protocol can influence its results. This review discusses key technical points of the SELEX procedure and their influence on the outcome of aptamer selection.

Contributions of single-cell genomics to our understanding of planktonic marine archaea

Single-cell genomics has transformed many fields of biology, marine microbiology included. Here, we consider the impact of single-cell genomics on a specific group of marine microbes-the planktonic marine archaea. Despite single-cell enabled discoveries of novel metabolic function in the marine thaumarchaea, population-level investigations are hindered by an overall lower than expected recovery of thaumarchaea in single-cell studies. Metagenome-assembled genomes have so far been a more useful method for accessing genome-resolved insights into the Marine Group II euryarchaea. Future progress in the application of single-cell genomics to archaeal biology in the ocean would benefit from more targeted sorting approaches, and a more systematic investigation of potential biases against archaea in single-cell workflows including cell lysis, genome amplification and genome screening. This article is part of a discussion meeting issue 'Single cell ecology'.

Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application

There has been an exponential growth in the performance and output of sequencing technologies (omics data) with full genome sequencing now producing gigabases of reads on a daily basis. These data may hold the promise of personalized medicine, leading to routinely available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing (HTS), computational considerations, data governance and clinical translation are the greatest rate-limiting steps. To ensure that the analysis, management and interpretation of such extensive omics data is exploited to its full potential, key factors, including sample sourcing, technology selection and computational expertise and resources, need to be considered, leading to an integrated set of high-performance tools and systems. This article provides an up-to-date overview of the evolution of HTS and the accompanying tools, infrastructure and data management approaches that are emerging in this space, which, if used within in a multidisciplinary context, may ultimately facilitate the development of personalized medicine.

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.

Directional high-throughput sequencing of RNAs without gene-specific primers

Ribosomal RNA analysis is a useful tool for characterization of microbial communities. However, the lack of broad-range primers has hampered the simultaneous analysis of eukaryotic and prokaryotic members by amplicon sequencing. We present a complete workflow for directional, primer-independent sequencing of size-selected small subunit ribosomal RNA fragments. The library preparation protocol includes gel extraction of the target RNA, ligation of an RNA oligo to the 5'-end of the target, and cDNA synthesis with a tailed random-hexamer primer and further barcoding. The sequencing results of a phytoplankton mock community showed a highly similar profile to the biomass indicators. This method has universal potential for microbiome studies, and is compatible for the 5'-end sequencing of other RNA types with minimum library preparation costs.

Hybrid gene misregulation in multiple developing tissues within a recent adaptive radiation of Cyprinodon pupfishes

Genetic incompatibilities constitute the final stages of reproductive isolation and speciation, but little is known about incompatibilities that occur within recent adaptive radiations among closely related diverging populations. Crossing divergent species to form hybrids can break up coadapted variation, resulting in genetic incompatibilities within developmental networks shaping divergent adaptive traits. We crossed two closely related sympatric Cyprinodon pupfish species–a dietary generalist and a specialized molluscivore–and measured expression levels in their F1 hybrids to identify regulatory variation underlying the novel craniofacial morphology found in this recent microendemic adaptive radiation. We extracted mRNA from eight day old whole-larvae tissue and from craniofacial tissues dissected from 17–20 day old larvae to compare gene expression between a total of seven F1 hybrids and 24 individuals from parental species populations. We found 3.9% of genes differentially expressed between generalists and molluscivores in whole-larvae tissues and 0.6% of genes differentially expressed in craniofacial tissue. We found that 2.1% of genes were misregulated in whole-larvae hybrids whereas 19.1% of genes were misregulated in hybrid craniofacial tissues, after correcting for sequencing biases. We also measured allele specific expression across 15,429 heterozygous sites to identify putative compensatory regulatory mechanisms underlying differential expression between generalists and molluscivores. Together, our results highlight the importance of considering misregulation as an early indicator of genetic incompatibilities in the context of rapidly diverging adaptive radiations and suggests that compensatory regulatory divergence drives hybrid gene misregulation in developing tissues that give rise to novel craniofacial traits.