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

Whole genome sequences of 70 indigenous Ethiopian cattle

Indigenous animal genetic resources play a crucial role in preserving global genetic diversity and supporting the livelihoods of millions of people. In Ethiopia, the majority of the cattle population consists of indigenous breeds. Understanding the genetic architecture of these cattle breeds is essential for effective management and conservation efforts. In this study, we sequenced DNA samples from 70 animals from seven indigenous cattle breeds, generating about two terabytes of pair-end reads with an average coverage of 14X. The sequencing data were pre-processed and mapped to the cattle reference genome (ARS-UCD1.2) with an alignment rate of 99.2%. Finally, the variant calling process produced approximately 35 million high-quality SNPs. These data provide a deeper understanding of the genetic landscape, facilitate the identification of causal mutations, and enable the exploration of evolutionary patterns to assist cattle improvement and sustainable utilization, particularly in the face of unpredictable climate changes.

A pipeline for the development and analysis of extracellular vesicle-based transcriptomic biomarkers in molecular diagnostics

Extracellular vesicles are shed by every cell type and can be found in any biofluid. They contain different molecules that can be utilized as biomarkers, including several RNA species which they protect from degradation. Here, we present a pipeline for the development and analysis of extracellular vesicle-associated transcriptomic biomarkers that our group has successfully applied multiple times. We highlight the key steps of the pipeline and give particular emphasis to the necessary quality control checkpoints, which are linked to numerous available guidelines that should be considered along the workflow. Our pipeline starts with patient recruitment and continues with blood sampling and processing. The purification and characterization of extracellular vesicles is explained in detail, as well as the isolation and quality control of extracellular vesicle-associated RNA. We point out the possible pitfalls during library preparation and RNA sequencing and present multiple bioinformatic tools to pinpoint biomarker signature candidates from the sequencing data. Finally, considerations and pitfalls during the validation of the biomarker signature using RT-qPCR will be elaborated.

Description of a 'plankton filtration bias' in sequencing-based bacterial community analysis and of an Arduino microcontroller-based flowmeter device that can help to resolve it

Diversity studies of aquatic picoplankton (bacterioplankton) communities using size-class filtration, DNA extraction, PCR and sequencing of phylogenetic markers, require a robust methodological pipeline, since biases have been demonstrated essentially at all levels, including DNA extraction, primer choice and PCR. Even different filtration volumes of the same plankton sample and, thus, different biomass loading of the filters, can distort the sequencing results. In this study, we designed an Arduino microcontroller-based flowmeter that records the decrease of initial (maximal) flowrate as proxy for increasing biomass loading and clogging of filters during plankton filtration. The device was tested using freshwater plankton of Lake Constance, and total DNA was extracted and an 16S rDNA amplicon was sequenced. We confirmed that different filtration volumes used for the same water sample affect the sequencing results. Differences were visible in alpha and beta diversities and across all taxonomic ranks. Taxa most affected were typical freshwater Actinobacteria and Bacteroidetes, increasing up to 38% and decreasing up to 29% in relative abundance, respectively. In another experiment, a lake water sample was filtered undiluted and three-fold diluted, and each filtration was stopped once the flowrate had reduced to 50% of initial flowrate, hence, at the same degree of filter clogging. The three-fold diluted sample required three-fold filtration volumes, while equivalent amounts of total DNA were extracted and differences across all taxonomic ranks were not statistically significant compared to the undiluted controls. In conclusion, this work confirms a volume/biomass-dependent bacterioplankton filtration bias for sequencing-based community analyses and provides an improved procedure for controlling biomass loading during filtrations and recovery of equivalent amounts of DNA from samples independent of the plankton density. The application of the device can also avoid the distorting of sequencing results as caused by the plankton filtration bias.

Deep mining of antibody phage-display selections using Oxford Nanopore Technologies and Dual Unique Molecular Identifiers

Antibody phage-display technology identifies antibody-antigen interactions through multiple panning rounds, but traditional screening gives no information on enrichment or diversity throughout the process. This results in the loss of valuable binders. Next Generation Sequencing can overcome this problem. We introduce a high accuracy long-read sequencing method based on the recent Oxford Nanopore Technologies (ONT) Q20 + chemistry in combination with dual unique molecular identifiers (UMIs) and an optimized bioinformatic analysis pipeline to monitor the selections. We identified binders from two single-domain antibody libraries selected against a model protein. Traditional colony-picking was compared with our ONT-UMI method. ONT-UMI enabled monitoring of diversity and enrichment before and after each selection round. By combining phage antibody selections with ONT-UMIs, deep mining of output selections is possible. The approach provides an alternative to traditional screening, enabling diversity quantification after each selection round and rare binder recovery, even when the dominating binder was > 99% abundant. Moreover, it can give insights on binding motifs for further affinity maturation and specificity optimizations. Our results demonstrate a platform for future data guided selection strategies.

Structural determinants for tRNA selective cleavage by RNase 2/EDN

tRNA-derived fragments (tRFs) have emerged as key players of immunoregulation. Some RNase A superfamily members participate in the shaping of the tRFs population. By comparing wild-type and knockout macrophage cell lines, our previous work revealed that RNase 2 can selectively cleave tRNAs. Here, we confirm the in vitro protein cleavage pattern by screening of synthetic tRNAs, single-mutant variants, and anticodon-loop DNA/RNA hairpins. By sequencing of tRF products, we identified the cleavage selectivity of recombinant RNase 2 with base specificity at B1 (U/C) and B2 (A) sites, consistent with a previous cellular study. Lastly, protein-hairpin complexes were predicted by MD simulations. Results reveal the contribution of the α1, loop 3 and loop 4, and β6 RNase 2 regions, where residues Arg36/Asn39/Gln40/Asn65/Arg68/Arg132 provide interactions, spanning from P-1 to P2 sites that are essential for anticodon loop recognition. Knowledge of RNase 2-specific tRFs generation might guide new therapeutic approaches for infectious and immune-related diseases.

Spitting in the wind?-The challenges of RNA sequencing for biomarker discovery from saliva

Forensic trace contextualization, i.e., assessing information beyond who deposited a biological stain, has become an issue of great and steadily growing importance in forensic genetic casework and research. The human transcriptome encodes a wide variety of information and thus has received increasing interest for the identification of biomarkers for different aspects of forensic trace contextualization over the past years. Massively parallel sequencing of reverse-transcribed RNA ("RNA sequencing") has emerged as the gold standard technology to characterize the transcriptome in its entirety and identify RNA markers showing significant expression differences not only between different forensically relevant body fluids but also within a single body fluid between forensically relevant conditions of interest. Here, we analyze the quality and composition of four RNA sequencing datasets (whole transcriptome as well as miRNA sequencing) from two different research projects (the RNAgE project and the TrACES project), aiming at identifying contextualizing forensic biomarker from the forensically relevant body fluid saliva. We describe and characterize challenges of RNA sequencing of saliva samples arising from the presence of oral bacteria, the heterogeneity of sample composition, and the confounding factor of degradation. Based on these observations, we formulate recommendations that might help to improve RNA biomarker discovery from the challenging but forensically relevant body fluid saliva.

Implementation of Exome Sequencing to Identify Rare Genetic Diseases

Modern high-throughput genomic testing using next-generation sequencing (NGS) has led to a significant increase in the successful diagnosis of rare genetic disorders. Recent advances in NGS tools and techniques have led to accurate and timely diagnosis of a large proportion of genetic diseases by finding sequence variations in clinical samples. One of the NGS techniques, exome sequencing (ES), is considered as a powerful and easily approachable method for genetic disorders in terms of rapid and cost-effective diagnostic yields. In this chapter, we describe an overview of whole exome sequencing (ES) in the context of experimental and analytical methodologies. Approaches to ES include sequencing capture technique, quality control processes at various stages of sequencing analysis, exome data filtering strategy that incorporates both primary and secondary filtering, and prioritization of candidate variants in diagnosing genetic diseases.

A novel method for quantitation of AAV genome integrity using duplex digital PCR

Recombinant adeno-associated virus (rAAV) vectors have become a reliable strategy for delivering gene therapies. As rAAV capsid content is known to be heterogeneous, methods for rAAV characterization are critical for assessing the efficacy and safety of drug products. Multiplex digital PCR (dPCR) has emerged as a popular molecular approach for characterizing capsid content due to its high level of throughput, accuracy, and replicability. Despite growing popularity, tools to accurately analyze multiplexed data are scarce. Here, we introduce a novel statistical model to estimate genome integrity from duplex dPCR assays. This work demonstrates that use of a Poisson-multinomial mixture distribution significantly improves the accuracy and quantifiable range of duplex dPCR assays over currently available models.

Microarray Analysis for Transcriptomic Profiling of Myocardium in Patients with Fatal Myocardial Infarction

Transcriptomic evidence from human myocardium in myocardial infarction (MI) is still not sufficient. Thus, there is a need for studies on human cardiac samples in relation to the clinical data of patients. The purpose of our pilot study was to investigate the transcriptomic profile of myocardium in the infarct zone, in comparison to the remote myocardium, in patients with fatal MI, via microarray analysis. This study included four patients with fatal MI type 1. We selected histologically verified samples from within the infarct area (n = 4) and remote myocardium (n = 4). The whole transcriptome was evaluated using microarray analysis. Differentially expressed genes (DEGs) clustered in the infarct area and in the remote myocardium allowed their differentiation. We identified a total of 1785 DEGs (8.32%) in the infarct area, including 1692 up-regulated (94.79%) and 93 down-regulated (5.21%) genes. The top 10 up-regulated genes were TRAIL, SUCLA2, NAE1, PDCL3, OSBPL5, FCGR2C, SELE, CEP63, ST3GAL3 and C4orf3. In the infarct area, we found up-regulation of seventeen apoptosis-related genes, eleven necroptosis-related, and six necrosis-related genes. Transcriptome profiling of the myocardium in patients with MI remains a relevant area of research for the formation of new scientific hypotheses and a potential way to increase the translational significance of studies into myocardial infarction.

Computational approaches for modeling and structural design of biological systems: A comprehensive review

The convergence of biology and computational science has ushered in a revolutionary era, revolutionizing our understanding of biological systems and providing novel solutions to global problems. The field of genetic engineering has facilitated the manipulation of genetic codes, thus providing opportunities for the advancement of innovative disease therapies and environmental enhancements. The emergence of bio-molecular simulation represents a significant advancement in this particular field, as it offers the ability to gain microscopic insights into molecular-level biological processes over extended periods. Biomolecular simulation plays a crucial role in advancing our comprehension of organismal mechanisms by establishing connections between molecular structures, interactions, and biological functions. The field of computational biology has demonstrated its significance in deciphering intricate biological enigmas through the utilization of mathematical models and algorithms. The process of decoding the human genome has resulted in the advancement of therapies for a wide range of genetic disorders, while the simulation of biological systems contributes to the identification of novel pharmaceutical compounds. The potential of biomolecular simulation and computational biology is vast and limitless. As the exploration of the underlying principles that govern living organisms progresses, the potential impact of this understanding on cancer treatment, environmental restoration, and other domains is anticipated to be transformative. This review examines the notable advancements achieved in the field of computational biology, emphasizing its potential to revolutionize the comprehension and enhancement of biological systems.

Sequence Alignment/Map format: a comprehensive review of approaches and applications

The Sequence Alignment/Map (SAM) format file is the text file used to record alignment information. Alignment is the core of sequencing analysis, and downstream tasks accept mapping results for further processing. Given the rapid development of the sequencing industry today, a comprehensive understanding of the SAM format and related tools is necessary to meet the challenges of data processing and analysis. This paper is devoted to retrieving knowledge in the broad field of SAM. First, the format of SAM is introduced to understand the overall process of the sequencing analysis. Then, existing work is systematically classified in accordance with generation, compression and application, and the involved SAM tools are specifically mined. Lastly, a summary and some thoughts on future directions are provided.

Differentiation and Identification of Endophytic Bacteria from Populus Based on Mass Fingerprints and Gene Sequences

Plant endophytic bacteria play important roles in plants' growth and resistance to stress. It is important to characterize endophytic bacteria to be able to understand their benefits. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has become a powerful technique for bacterial identification due to its high throughput and simple procedures. In this study, the endophytic bacteria separated from Populus (the leaves, roots and stems of Populus tomentosa Carrière; stems of Populus nigra Linn. var. nigra; and stems of Populus canadensis Moench) were identified and classified based on MALDI-TOF MS data and 16S rRNA gene sequencing. The sampling and preparation of bacteria were optimized to obtain meaningful protein mass fingerprints. The composite correlation index (CCI) values of the inter-genera and inter-species protein mass fingerprints demonstrated sufficient differences between the strains. In the CCI value matrix for ten species in the same genus, all the CCI values were less than 0.5. Among the species, 95.6% of all the CCI values were less than 0.5. After data processing, the classification capacity of the protein mass fingerprints was verified using inter-specific and inter-generic PCoA. To compare different methods' potential for differentiation and phylogenetic analysis, a dendrogram of the MS profiles and a phylogenetic tree based on the 16S rRNA gene sequences were constructed using 61 endophytic bacteria found in Populus. The clustering and grouping results show that the phylogenetic analysis based on MALDI-TOF MS is similar to that based on 16S rRNA gene sequencing. This study provides a valuable reference for differentiating and identifying endophytic bacteria according to their protein mass fingerprints.

CapTrap-Seq: A platform-agnostic and quantitative approach for high-fidelity full-length RNA transcript sequencing

Long-read RNA sequencing is essential to produce accurate and exhaustive annotation of eukaryotic genomes. Despite advancements in throughput and accuracy, achieving reliable end-to-end identification of RNA transcripts remains a challenge for long-read sequencing methods. To address this limitation, we developed CapTrap-seq, a cDNA library preparation method, which combines the Cap-trapping strategy with oligo(dT) priming to detect 5'capped, full-length transcripts, together with the data processing pipeline LyRic. We benchmarked CapTrap-seq and other popular RNA-seq library preparation protocols in a number of human tissues using both ONT and PacBio sequencing. To assess the accuracy of the transcript models produced, we introduced a capping strategy for synthetic RNA spike-in sequences that mimics the natural 5'cap formation in RNA spike-in molecules. We found that the vast majority (up to 90%) of transcript models that LyRic derives from CapTrap-seq reads are full-length. This makes it possible to produce highly accurate annotations with minimal human intervention.

Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq

Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug repositioning. Initially, microarrays are used to study the bulk transcriptome; but now short-read RNA sequencing (RNA-seq) predominates. Positioned as a superior technology, that makes the discovery of novel transcripts routine, most RNA-seq analyses are in fact modeled on the known transcriptome. Limitations of the RNA-seq methodology have emerged, while the design of, and the analysis strategies applied to, arrays have matured. An equitable comparison between these technologies is provided, highlighting advantages that modern arrays hold over RNA-seq. Array protocols more accurately quantify constitutively expressed protein coding genes across tissue replicates, and are more reliable for studying lower expressed genes. Arrays reveal long noncoding RNAs (lncRNA) are neither sparsely nor lower expressed than protein coding genes. Heterogeneous coverage of constitutively expressed genes observed with RNA-seq, undermines the validity and reproducibility of pathway analyses. The factors driving these observations, many of which are relevant to long-read or single-cell sequencing are discussed. As proposed herein, a reappreciation of bulk transcriptomic methods is required, including wider use of the modern high-density array data-to urgently revise existing anatomical RNA reference atlases and assist with more accurate study of lncRNAs.

choros: correction of sequence-based biases for accurate quantification of ribosome profiling data

Ribosome profiling quantifies translation genome-wide by sequencing ribosome-protected fragments, or footprints. Its single-codon resolution allows identification of translation regulation, such as ribosome stalls or pauses, on individual genes. However, enzyme preferences during library preparation lead to pervasive sequence artifacts that obscure translation dynamics. Widespread over- and under-representation of ribosome footprints can dominate local footprint densities and skew estimates of elongation rates by up to five fold. To address these biases and uncover true patterns of translation, we present choros, a computational method that models ribosome footprint distributions to provide bias-corrected footprint counts. choros uses negative binomial regression to accurately estimate two sets of parameters: (i) biological contributions from codon-specific translation elongation rates; and (ii) technical contributions from nuclease digestion and ligation efficiencies. We use these parameter estimates to generate bias correction factors that eliminate sequence artifacts. Applying choros to multiple ribosome profiling datasets, we are able to accurately quantify and attenuate ligation biases to provide more faithful measurements of ribosome distribution. We show that a pattern interpreted as pervasive ribosome pausing near the beginning of coding regions is likely to arise from technical biases. Incorporating choros into standard analysis pipelines will improve biological discovery from measurements of translation.

An expectation-maximization algorithm for estimating proportions of deletions among bacterial populations with application to study antibiotic resistance gene transfer in Enterococcus faecalis

The emergence of antibiotic resistance in bacteria limits the availability of antibiotic choices for treatment and infection control, thereby representing a major threat to human health. The de novo mutation of bacterial genomes is an essential mechanism by which bacteria acquire antibiotic resistance. Previously, deletion mutations within bacterial immune systems, ranging from dozens to thousands of base pairs (bps) in length, have been associated with the spread of antibiotic resistance. Most current methods for evaluating genomic structural variations (SVs) have concentrated on detecting them, rather than estimating the proportions of populations that carry distinct SVs. A better understanding of the distribution of mutations and subpopulations dynamics in bacterial populations is needed to appreciate antibiotic resistance evolution and movement of resistance genes through populations. Here, we propose a statistical model to estimate the proportions of genomic deletions in a mixed population based on Expectation-Maximization (EM) algorithms and next-generation sequencing (NGS) data. The method integrates both insert size and split-read mapping information to iteratively update estimated distributions. The proposed method was evaluated with three simulations that demonstrated the production of accurate estimations. The proposed method was then applied to investigate the horizontal transfers of antibiotic resistance genes in concert with changes in the CRISPR-Cas system of E. faecalis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-022-00144-z.

Focus on the frontier issue: progress in noninvasive prenatal screening for fetal trisomy from clinical perspectives

The discovery of cell-free fetal DNA (cffDNA) in maternal blood and the rapid development of massively parallel sequencing have revolutionized prenatal testing from invasive to noninvasive. Noninvasive prenatal screening (NIPS) based on cffDNA enables the detection of fetal trisomy through sequencing, comparison, and bioassays. Its accuracy is better than that of traditional screening methods, and it is the most advanced clinical application of high-throughput sequencing technologies. However, the existing sequencing methods are limited by high costs and complex sequencing procedures. These limitations restrict the availability of NIPS for pregnant women. Many amplification methods have been developed to overcome the limitations of sequencing methods. The rapid development of non-sequencing methods has not been accompanied by reviews to summarize them. In this review, we initially describe the detection principles for sequencing-based NIPS. We summarize the rapidly evolving amplification technologies, focusing on the need to reduce costs and simplify the procedures. To ensure that the testing systems are feasible and that the testing processes are reliable, we expand our vision to the clinic. We evaluate the clinical validity of NIPS in terms of sensitivity, specificity, and positive predictive value. Finally, we summarize the application guidelines and discuss the corresponding quality control methods for NIPS. In addition to cffDNA, extracellular vesicle DNA, RNA, protein/peptide, and fetal cells can also be detected as biomarkers of NIPS. With the development of prenatal testing, NIPS has become increasingly important. Notably, NIPS is a screening test instead of a diagnostic test. The testing methods and procedures used in the NIPS process require standardization.

From Samples to Germline and Somatic Sequence Variation: A Focus on Next-Generation Sequencing in Melanoma Research

Next-generation sequencing (NGS) applications have flourished in the last decade, permitting the identification of cancer driver genes and profoundly expanding the possibilities of genomic studies of cancer, including melanoma. Here we aimed to present a technical review across many of the methodological approaches brought by the use of NGS applications with a focus on assessing germline and somatic sequence variation. We provide cautionary notes and discuss key technical details involved in library preparation, the most common problems with the samples, and guidance to circumvent them. We also provide an overview of the sequence-based methods for cancer genomics, exposing the pros and cons of targeted sequencing vs. exome or whole-genome sequencing (WGS), the fundamentals of the most common commercial platforms, and a comparison of throughputs and key applications. Details of the steps and the main software involved in the bioinformatics processing of the sequencing results, from preprocessing to variant prioritization and filtering, are also provided in the context of the full spectrum of genetic variation (SNVs, indels, CNVs, structural variation, and gene fusions). Finally, we put the emphasis on selected bioinformatic pipelines behind (a) short-read WGS identification of small germline and somatic variants, (b) detection of gene fusions from transcriptomes, and (c) de novo assembly of genomes from long-read WGS data. Overall, we provide comprehensive guidance across the main methodological procedures involved in obtaining sequencing results for the most common short- and long-read NGS platforms, highlighting key applications in melanoma research.

Exosome RNA Sequencing as a Tool in the Search for Cancer Biomarkers

Numerous noninvasive methods are currently being used to determine biomarkers for diseases such as cancer. However, these methods are not always precise and reliable. Thus, there is an unmet need for better diagnostic and prognostic biomarkers that will be used to diagnose cancer in early, more treatable stages of the disease. Exosomes are extracellular vesicles of endocytic origin released by the majority of cells. Exosomes contain and transport nucleic acids, proteins, growth factors, and cytokines from their parent cells to surrounding or even distant cells via circulation in biofluids. Exosomes have attracted the interest of researchers, as recent data indicate that exosome content may be indicative of disease stages and may contribute to disease progression via exosome-mediated extracellular communication. Therefore, the contents of these vesicles are being investigated as possible biomarkers for disease diagnosis and prognosis. The functions of exosomes and their contents in disease development are becoming clearer as isolation and analytical methods, such as RNA sequencing, advance. In this review, we discuss current advances and challenges in exosomal content analyses with emphasis on information that can be generated using RNA sequencing. We also discuss how the RNA sequencing of exosomes may be used to discover novel biomarkers for the detection of different stages for various cancers using specific microRNAs that were found to be differentially expressed between healthy controls and cancer-diagnosed subjects.

SELEX: Critical factors and optimization strategies for successful aptamer selection

Within the last decade, the application range of aptamers in biochemistry and medicine has expanded rapidly. More than just a replacement for antibodies, these intrinsically structured RNA- or DNA-oligonucleotides show great potential for utilization in diagnostics, specific drug delivery, and treatment of certain medical conditions. However, what is analyzed less frequently is the process of aptamer identification known as systematic evolution of ligands by exponential enrichment (SELEX) and the functional mechanisms that lie at its core. SELEX involves numerous singular processes, each of which contributes to the success or failure of aptamer generation. In this review, critical steps during aptamer selection are discussed in-depth, and specific problems are presented along with potential solutions. The discussed aspects include the size and molecule type of the selected target, the nature and stringency of the selection process, the amplification step with its possible PCR bias, the efficient regeneration of RNA or single-stranded DNA, and the different sequencing procedures and screening assays currently available. Finally, useful quality control steps and their role within SELEX are presented. By understanding the mechanisms through which aptamer selection is influenced, the design of more efficient SELEX procedures leading to a higher success rate in aptamer identification is enabled.

Experimental and computational workflow for the analysis of tRNA pools from eukaryotic cells by mim-tRNAseq

Quantifying tRNAs is crucial for understanding how they regulate mRNA translation but is hampered by their extensive sequence similarity and premature termination of reverse transcription at multiple modified nucleotides. Here, we describe the use of modification-induced misincorporation tRNA sequencing (mim-tRNAseq), which overcomes these limitations with optimized library construction and a comprehensive toolkit for data analysis and visualization. We outline algorithm improvements that enhance the efficiency and accuracy of read alignment and provide details on data analysis outputs using example datasets.

For complete details on the use and execution of this protocol, please refer to Behrens et al. (2021).

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mim-tRNAseq enables efficient quantitation and analysis of eukaryotic tRNA pools

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Combined library generation and computational package ensures user-friendly workflow

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Improved multiplexing enables more cost-effective sample analysis

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Novel deconvolution algorithm enhances read alignment accuracy and sensitivity

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Application of High-Throughput Sequencing Technology in Identifying the Pathogens in Endophthalmitis

Infectious endophthalmitis is an important cause of vision loss worldwide. It is an inflammatory reaction caused by bacteria, fungi, and other micro-organisms and often occurs as a complication of intraocular surgery, especially following cataract surgery or intravitreal injection. The focus of the prevention and treatment of infectious endophthalmitis is the early detection of microbial flora, such as fungi or bacteria. Current identification methods for bacteria include Gram staining-based, culture-based, and polymerase chain reaction (PCR)-based methods. The matrix-assisted laser desorption/ionization time-of-flight mass spectrometry technology is now the standard identification method of bacteria and fungi after their isolation in culture. The remarkable sensitivity of PCR technology for the direct detection of micro-organisms in clinical samples makes it particularly useful in culture-positive and culture-negative endophthalmitis. Furthermore, PCR increases the rate of microorganism detection in intraocular samples by 20% and can provide a microbiology diagnosis in approximately 44.7–100% of the culture-negative cases. This review aims to introduce the development of different methods for the detection and identification of micro-organisms causing endophthalmitis through a literature review; introduce the research status of the first, second, and third-generation sequencing technologies in infectious endophthalmitis; and understand the research status of endophthalmitis microbial flora. For slow-growing and rare micro-organisms, high-throughput sequencing (HTS) offers advantages over conventional methods and provides a basis for the identification of pathogens in endophthalmitis cases with negative culture. It is a reliable platform for the identification of pathogenic bacteria of infectious endophthalmitis in the future and provides a reference for the clinical diagnosis and treatment of infectious endophthalmitis. The application of HTS technology may also be transformative for clinical microbiology and represents an exciting future direction for the epidemiology of ocular infections.

Small but strong: Pivotal roles and potential applications of snoRNAs in hematopoietic malignancies

Small nucleolar RNAs (snoRNAs) belong to a family of noncoding RNAs that are 60-300 nucleotides in length, and they are classified into two classes according to their structure and function: C/D box snoRNAs, playing an essential role in 2’-O-methylation modification on ribosomal RNA; H/ACA box snoRNAs, involved in the pseudouridylation of rRNA. SnoRNAs with unclear functions, no predictable targets, and unusual subcellular locations are called orphan snoRNAs. Recent studies have revealed abnormal expression and demonstrated the pivotal roles of snoRNAs and their host genes in various types of hematological malignancies. This review discusses recent discoveries concerning snoRNAs in a variety of hematological malignancies, including multiple myeloma, lymphoma and leukemia, and sheds light on the application of snoRNAs as diagnostic and prognostic markers as well as therapeutic targets of hematological malignancies in the future.

Probe Capture Enrichment Methods for HIV and HCV Genome Sequencing and Drug Resistance Genotyping

Human immunodeficiency virus (HIV) infections remain a significant public health concern worldwide. Over the years, sophisticated sequencing technologies such as next-generation sequencing (NGS) have emerged and been utilized to monitor the spread of HIV drug resistance (HIVDR), identify HIV drug resistance mutations, and characterize transmission dynamics. Similar applications also apply to the Hepatitis C virus (HCV), another bloodborne viral pathogen with significant intra-host genetic diversity. Several advantages to using NGS over conventional Sanger sequencing include increased data throughput, scalability, cost-effectiveness when batched sample testing is performed, and sensitivity for quantitative detection of minority resistant variants. However, NGS alone may fail to detect genomes from pathogens present in low copy numbers. As with all sequencing platforms, the primary determinant in achieving quality sequencing data is the quality and quantity of the initial template input. Samples containing degraded RNA/DNA and/or low copy number have been a consistent sequencing challenge. To overcome this limitation probe capture enrichment is a method that has recently been employed to target, enrich, and sequence the genome of a pathogen present in low copies, and for compromised specimens that contain poor quality nucleic acids. It involves the hybridization of sequence-specific DNA or RNA probes to a target sequence, which is followed by an enrichment step via PCR to increase the number of copies of the targeted sequences after which the samples are subjected to NGS procedures. This method has been performed on pathogens such as bacteria, fungus, and viruses and allows for the sequencing of complete genomes, with high coverage. Post NGS, data analysis can be performed through various bioinformatics pipelines which can provide information on genetic diversity, genotype, virulence, and drug resistance. This article reviews how probe capture enrichment helps to increase the likelihood of sequencing HIV and HCV samples that contain low viral loads and/or are compromised.

Sensitive and Low-Bias Transcriptome Sequencing Using Agarose PCR

Transcriptome sequencing has emerged as an important research tool for exploring the mysteries of life at the single-cell level. However, its wide application is limited by the bias associated with the amplification reactions which is essential for library building of trace RNA. In this study, low-melting-point agarose was added to the amplification reactions to take advantage of its molecular crowding effect and polymer cross-linked structure to improve the sensitivity of the reactions and reduce bias. To further evaluate the performance of the method, it was applied to transcriptome sequencing of microregion samples from brain tissue sections of mice with Parkinson's disease at the single cell level. The results showed that agarose PCR had better performance than in-tube PCR. Further application of agarose PCR to transcriptome library sequencing could obtain data closer to that of unamplified. With the addition of low melting point agarose, the sensitivity of the amplification reaction was significantly increased, while homogeneity was increased by approximately 2-fold. Not only that, but this work also provides 11% sensitivity improvement for spatial transcriptomic study on Parkinson's disease-associated gene detection. The agarose PCR provides a new tool for efficient and homogeneous amplification of trace samples and can be widely used for spatial transcriptome library sequencing and studies.

Whole Transcriptome Profiling of the Effects of Cadmium on the Liver of the Xiangxi Yellow Heifer

Cadmium (Cd) is a major heavy metal toxicant found in industrial zones. Humans and animals are exposed to it through their diet, which results in various physiological problems. In the current study, the toxic effects of Cd on the liver were investigated by whole-transcriptome sequencing (RNA-seq) of the livers of Xiangxi heifers fed a diet with excess Cd. We randomly divided six healthy heifers into two groups. The first group received a control diet, whereas the second group received Cd-exceeding diets for 100 days. After 100 days, the livers were collected. A total of 551 differentially expressed mRNAs, 24 differentially expressed miRNAs, and 169 differentially expressed lncRNAs were identified (p < 0.05, |log2FC| >1). Differentially expressed genes (DEGs) were analyzed by gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. We found that under Cd exposure, DEGs were enriched in the adenosine 5'-monophosphate-activated protein kinase pathway, which is involved in autophagy regulation, and the peroxisome proliferator-activated receptor pathway, which is involved in lipid metabolism. In addition, the apolipoprotein A4 gene, which has anti-inflammatory and antioxidant effects, the anti-apoptotic gene ATPase H+/K+ transporting the nongastric alpha2 subunit, and the cholesterol metabolism-associated gene endothelial lipase gene were significantly downregulated. C-X-C motif chemokine ligand 3, cholesterol 7α-hydroxylase, and stearoyl-CoA desaturase, which are involved in the development of fatty liver, were significantly upregulated. These genes revealed the main effects of Cd on the liver of Xiangxi yellow heifers. The current study provides insightful information regarding the DEGs involved in autophagy regulation, apoptosis, lipid metabolism, anti-inflammation, and antioxidant enzyme activity. These may serve as useful biomarkers for predicting and treating Cd-related diseases in the future.

Whole-genome sequencing and genetic characteristics of representative porcine reproductive and respiratory syndrome virus (PRRSV) isolates in Korea

Background

Porcine reproductive and respiratory syndrome virus (PRRSV) is a macrophage-tropic arterivirus with extremely high genetic and pathogenic heterogeneity that causes significant economic losses in the swine industry worldwide. PRRSV can be divided into two species [PRRSV1 (European) and PRRSV2 (North American)] and is usually diagnosed and genetically differentiated into several lineages based on the ORF5 gene, which constitutes only 5% of the whole genome. This study was conducted to achieve nonselective amplification and whole-genome sequencing (WGS) based on a simplified sequence-independent, single-primer amplification (SISPA) technique with next-generation sequencing (NGS), and to genetically characterize Korean PRRSV field isolates at the whole genome level.

Methods

The SISPA-NGS method coupled with a bioinformatics pipeline was utilized to retrieve full length PRRSV genomes of 19 representative Korean PRRSV strains by de novo assembly. Phylogenetic analysis, analysis of the insertion and deletion (INDEL) pattern of nonstructural protein 2 (NSP2), and recombination analysis were conducted.

Results

Nineteen complete PRRSV genomes were obtained with a high depth of coverage by the SISPA-NGS method. Korean PRRSV1 belonged to the Korean-specific subtype 1A and vaccine-related subtype 1C lineages, showing no evidence of recombination and divergent genetic heterogeneity with conserved NSP2 deletion patterns. Among Korean PRRSV2 isolates, modified live vaccine (MLV)-related lineage 5 viruses, lineage 1 viruses, and nation-specific Korean lineages (KOR A, B and C) could be identified. The NSP2 deletion pattern of the Korean lineages was consistent with that of the MN-184 strain (lineage 1), which indicates the common ancestor and independent evolution of Korean lineages. Multiple recombination signals were detected from Korean-lineage strains isolated in the 2010s, suggesting natural interlineage recombination between circulating KOR C and MLV strains. Interestingly, the Korean strain GGYC45 was identified as a recombinant KOR C and MLV strain harboring the KOR B ORF5 gene and might be the ancestor of currently circulating KOR B strains. Additionally, two novel lineage 1 recombinants of NADC30-like and NADC34-like viruses were detected.

Conclusion

Genome-wide analysis of Korean PRRSV isolates retrieved by the SISPA-NGS method and de novo assembly, revealed complex evolution and recombination in the field. Therefore, continuous surveillance of PRRSV at the whole genome level should be conducted, and new vaccine strategies for more efficient control of the virus are needed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-022-01790-6.

Genome-wide association study and genomic prediction of white rust resistance in USDA GRIN spinach germplasm

White rust, caused by Albugo occidentalis, is one of the major yield-limiting diseases of spinach (Spinacia oleracea) in some major commercial production areas, particularly in southern Texas in the United States. The use of host resistance is the most economical and environment-friendly approach to managing white rust in spinach production. The objectives of this study were to conduct a genome-wide associating study (GWAS), to identify single nucleotide polymorphism (SNP) markers associated with white rust resistance in spinach, and to perform genomic prediction (GP) to estimate the prediction accuracy (PA). A GWAS panel of 346 USDA (US Dept. of Agriculture) germplasm accessions was phenotyped for white rust resistance under field conditions and GWAS was performed using 13 235 whole-genome resequencing (WGR) generated SNPs. Nine SNPs, chr2_53 049 132, chr3_58 479 501, chr3_95 114 909, chr4_9 176 069, chr4_17 807 168, chr4_83 938 338, chr4_87 601 768, chr6_1 877 096, and chr6_31 287 118, located on chromosomes 2, 3, 4, and 6 were associated with white rust resistance in this GWAS panel. Four scenarios were tested for PA using Pearson's correlation coefficient (r) between the genomic estimation breeding value (GEBV) and the observed values: (1) different ratios between the training set and testing set (fold), (2) different GP models, (3) different SNP numbers in three different SNP sets, and (4) the use of GWAS-derived significant SNP markers. The results indicated that a 2- to 10-fold difference in the various GP models had similar, although not identical, averaged r values in each SNP set; using GWAS-derived significant SNP markers would increase PA with a high r-value up to 0.84. The SNP markers and the high PA can provide valuable information for breeders to improve spinach by marker-assisted selection (MAS) and genomic selection (GS).

Obtaining Reliable RT-qPCR Results in Molecular Diagnostics—MIQE Goals and Pitfalls for Transcriptional Biomarker Discovery

In this review, we discuss the development pipeline for transcriptional biomarkers in molecular diagnostics and stress the importance of a reliable gene transcript quantification strategy. Hence, a further focus is put on the MIQE guidelines and how to adapt them for biomarker discovery, from signature validation up to routine diagnostic applications. First, the advantages and pitfalls of the holistic RNA sequencing for biomarker development will be described to establish a candidate biomarker signature. Sequentially, the RT-qPCR confirmation process will be discussed to validate the discovered biomarker signature. Examples for the successful application of RT-qPCR as a fast and reproducible quantification method in routinemolecular diagnostics are provided. Based on the MIQE guidelines, the importance of “key steps” in RT-qPCR is accurately described, e.g., reverse transcription, proper reference gene selection and, finally, the application of automated RT-qPCR data analysis software. In conclusion, RT-qPCR proves to be a valuable tool in the establishment of a disease-specific transcriptional biomarker signature and will have a great future in molecular diagnostics or personalized medicine.

Novel RNase H Inhibitors Blocking RNA-directed Strand Displacement DNA Synthesis by HIV-1 Reverse Transcriptase

In retroviruses, strand displacement DNA-dependent DNA polymerization catalyzed by the viral reverse transcriptase (RT) is required to synthesize double-stranded proviral DNA. In addition, strand displacement during RNA-dependent DNA synthesis is critical to generate high-quality cDNA for use in molecular biology and biotechnology. In this work, we show that the loss of RNase H activity due to inactivating mutations in HIV-1 RT (e.g. D443N or E478Q) has no significant effect on strand displacement while copying DNA templates, but has a large impact on DNA polymerization in reactions carried out with RNA templates. Similar effects were observed with β-thujaplicinol and other RNase H active site inhibitors, including compounds with dual activity (i.e., characterized also as inhibitors of HIV-1 integrase and/or the RT DNA polymerase). Among them, dual inhibitors of HIV-1 RT DNA polymerase/RNase H activities, containing a 7-hydroxy-6-nitro-2H-chromen-2-one pharmacophore were found to be very potent and effective strand displacement inhibitors in RNA-dependent DNA polymerization reactions. These findings might be helpful in the development of transcriptomics technologies to obtain more uniform read coverages when copying long RNAs and for the construction of more representative libraries avoiding biases towards 5' and 3' ends, while providing valuable information for the development of novel antiretroviral agents.

Systematic comparative analysis of strand-specific RNA-seq library preparation methods for low input samples

Despite the recent precipitous decline in the cost of genome sequencing, library preparation for RNA-seq is still laborious and expensive for applications such as high throughput screening. Limited availability of RNA generated by some experimental workflows poses an additional challenge and increases the cost of RNA library preparation. In a search for low cost, automation-compatible RNA library preparation kits that maintain strand specificity and are amenable to low input RNA quantities, we systematically tested two recent commercial technologies—Swift RNA and Swift Rapid RNA, presently offered by Integrated DNA Technologies (IDT) —alongside the Illumina TruSeq stranded mRNA, the de facto standard workflow for bulk transcriptomics. We used the Universal Human Reference RNA (UHRR) (composed of equal quantities of total RNA from 10 human cancer cell lines) to benchmark gene expression in these kits, at input quantities ranging between 10 to 500 ng. We found normalized read counts between all treatment groups to be in high agreement. Compared to the Illumina TruSeq stranded mRNA kit, both Swift RNA library kits offer shorter workflow times enabled by their patented Adaptase technology. We also found the Swift RNA kit to produce the fewest number of differentially expressed genes and pathways directly attributable to input mRNA amount.

System analysis of the sequencing quality of human whole exome samples on BGI NGS platform

Human exome sequencing is a classical method used in most medical genetic applications. The leaders in the field are the manufacturers of enrichment kits based on hybridization of cRNA or cDNA biotinylated probes specific for a genomic region of interest. Recently, the platforms manufactured by the Chinese company MGI Tech have become widespread in Europe and Asia. The reliability and quality of the obtained data are already beyond any doubt. However, only a few kits compatible with these sequencers can be used for such specific tasks as exome sequencing. We developed our own solution for library pre-capture pooling and exome enrichment with Agilent probes. In this work, using a set of the standard benchmark samples from the Platinum Genome collection, we demonstrate that the qualitative and quantitative parameters of our protocol which we called "RSMU_exome" exceed those of the MGI Tech kit. Our protocol allows for identifying more SNV and indels, generates fewer PCR duplicates, enables pooling of more samples in a single enrichment procedure, and requires less raw data to obtain results comparable with the MGI Tech's protocol. The cost of our protocol is also lower than that of MGI Tech's solution.

Nanopore Whole Transcriptome Analysis and Pathogen Surveillance by a Novel Solid-Phase Catalysis Approach

The requirement of a large input amount (500 ng) for Nanopore direct RNA-seq presents a major challenge for low input transcriptomic analysis and early pathogen surveillance. The high RNA input requirement is attributed to significant sample loss associated with library preparation using solid-phase reversible immobilization (SPRI) beads. A novel solid-phase catalysis strategy for RNA library preparation to circumvent the need for SPRI bead purification to remove enzymes is reported here. This new approach leverages concurrent processing of non-polyadenylated transcripts with immobilized poly(A) polymerase and T4 DNA ligase, followed by directly loading the prepared library onto a flow cell. Whole transcriptome sequencing, using a human pathogen Listeria monocytogenes as a model, demonstrates this new method displays little sample loss, takes much less time, and generates higher sequencing throughput correlated with reduced nanopore fouling compared to the current library preparation for 500 ng input. Consequently, this approach enables Nanopore low-input direct RNA-seq, improving pathogen detection and transcript identification in a microbial community standard with spike-in transcript controls. Besides, as evident in the bioinformatic analysis, the new method provides accurate RNA consensus with high fidelity and identifies higher numbers of expressed genes for both high and low input RNA amounts.

Characterization of M116.1p, a murine cytomegalovirus protein required for efficient infection of mononuclear phagocytes

Broad tissue tropism of cytomegaloviruses (CMVs) is facilitated by different glycoprotein entry complexes, which are conserved between human CMV (HCMV) and murine CMV (MCMV). Among the wide array of cell types susceptible to the infection, mononuclear phagocytes (MNPs) play a unique role in the pathogenesis of the infection as they contribute both to the virus spread and immune control. CMVs have dedicated numerous genes for the efficient infection and evasion of macrophages and dendritic cells. In this study, we have characterized the properties and function of M116, a previously poorly described but highly transcribed MCMV gene region which encodes M116.1p, a novel protein necessary for the efficient infection of MNPs and viral spread in vivo. Our study further revealed that M116.1p shares similarities with its positional homologs in HCMV and RCMV, UL116 and R116, respectively, such as late kinetics of expression, N-glycosylation, localization to the virion assembly compartment, and interaction with gH - a member of the CMVs fusion complex. This study, therefore, expands our knowledge about virally encoded glycoproteins that play important roles in viral infectivity and tropism. Importance Human cytomegalovirus (HCMV) is a species-specific herpesvirus that causes severe disease in immunocompromised individuals and immunologically immature neonates. Murine cytomegalovirus (MCMV) is biologically similar to HCMV, and it serves as a widely used model for studying the infection, pathogenesis, and immune responses to HCMV. In our previous work, we have identified the M116 ORF as one of the most extensively transcribed regions of the MCMV genome without an assigned function. This study shows that the M116 locus codes for a novel protein, M116.1p, which shares similarities with UL116 and R116 in HCMV and RCMV, respectively, and is required for the efficient infection of mononuclear phagocytes and virus spread in vivo. Furthermore, this study establishes the α-M116 monoclonal antibody and MCMV mutants lacking M116, generated in this work, as valuable tools for studying the role of macrophages and dendritic cells in limiting CMV infection following different MCMV administration routes.

Automated library preparation for whole genome sequencing by centrifugal microfluidics

Next generation sequencing is evolving from a research tool into a method applied in diagnostic routine. The complete sequencing workflow includes sample pre-processing, library preparation, sequencing and bioinformatics. High quality in each of these steps is necessary to obtain excellent sequencing results. The tedious and error-prone library preparation poses a significant challenge for smaller laboratories, where high throughput pipetting robots are not cost-effective. Here we present an automated library preparation for whole genome sequencing using centrifugal microfluidics. Two samples can be run per cartridge. Precise metering of reagents allows the required liquid volumes to be reduced by 40% and the amount of sample used by 60%. The functionality of the cartridge is demonstrated with bacteria and DNA extracted from a human FFPE sample. For the bacterial sample, mean sequencing depths from 140 to 183 reads and a coverage of 99.8% of the reference genome were detected. For the human DNA, mean sequencing depths of 4.4-5.7 reads and a coverage of 78.2% of the effective reference genome were observed.

Prospects and challenges of cancer systems medicine: from genes to disease networks

It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches.

Nanopore Sequencing Provides Rapid and Reliable Insight Into Microbial Profiles of Intensive Care Units

Fast and accurate identification of pathogens is an essential task in healthcare settings. Second-generation sequencing platforms such as Illumina have greatly expanded the capacity with which different organisms can be detected in hospital samples, and third-generation nanopore-driven sequencing devices such as Oxford Nanopore's minION have recently emerged as ideal sequencing platforms for routine healthcare surveillance due to their long-read capacity and high portability. Despite its great potential, protocols and analysis pipelines for nanopore sequencing are still being extensively validated. In this work, we assess the ability of nanopore sequencing to provide reliable community profiles based on 16S rRNA sequencing in comparison to traditional Illumina platforms using samples collected from Intensive Care Units of a hospital in Brazil. While our results demonstrate that lower throughputs may be a shortcoming of the method in more complex samples, we show that the use of single-use Flongle flowcells in nanopore sequencing runs can provide insightful information on the community composition in healthcare settings.

Next-Generation Sequencing Somatic and Germline Assay Troubleshooting Guide Derived From Proficiency Testing Data

CONTEXT.—

Next-generation sequencing-based assays are increasingly used in clinical molecular laboratories to detect somatic variants in solid tumors and hematologic malignancies and to detect constitutional variants. Proficiency testing data are potential sources of information about challenges in performing these assays.

OBJECTIVE.—

To examine the most common sources of unacceptable results from the College of American Pathologists Next-Generation Sequencing Bioinformatics, Hematological Malignancies, Solid Tumor, and Germline surveys, and provide recommendations on how to avoid these pitfalls and improve performance.

DESIGN.—

The College of American Pathologists next-generation sequencing somatic and germline proficiency testing survey results from 2016 to 2019 were analyzed to identify the most common causes of unacceptable results.

RESULTS.—

On somatic and germline proficiency testing surveys, 95.9% (18 815/19 623) and 97.8% (33 890/34 641) of all variants were correctly identified, respectively. The most common causes of unacceptable results related to sequencing were false-negative errors in genomic regions that were difficult to sequence because of high GC content. False-positive errors occurred in the context of homopolymers and pseudogenes. Recurrent errors in variant annotation were seen for dinucleotide and duplication variants and included unacceptable transcript selection and outdated variant nomenclature. A small percentage of preanalytic or postanalytic errors were attributed to specimen swaps and transcription errors.

CONCLUSIONS.—

Laboratories demonstrate overall excellent performance for detecting variants in both somatic and germline proficiency testing surveys. Proficiency testing survey results highlight infrequent, but recurrent, analytic and nonanalytic challenges in performing next- generation sequencing-based assays and point to remedies to help laboratories improve performance.

CLIP-Seq to identify targets and interactions of RNA binding proteins and RNA modifying enzymes

The study of RNA chemical modifications is currently one of the most rapid-growing fields. Many types of RNA modifications in diverse RNA species have been shown to play versatile roles in a wide array of cellular processes. These modifications are installed and erased by writer and eraser enzymes, respectively. Additionally, RNA chemical modifications have downstream biological effects through either influencing changes in the chemistry or structure of RNA molecules or through recognition of the modification; these functions are primarily executed by the modification reader proteins. Reader proteins may bind to the modification site and cause a downstream signal cascade. One of the essential tools for studying erasers, writers, and readers is cross-linking immunoprecipitation followed by high-throughput sequencing (CLIP-seq). This method can detect the sites on endogenous RNAs bound by RNA-binding proteins or RNA modifying enzymes. Essentially, this strategy allows for snapshots of the epitranscriptome and molecular events occurring within the cell. In this article, we go through in detail the various steps involved in CLIP-seq.

Evaluation of a high-throughput, cost-effective Illumina library preparation kit

Library preparation for high-throughput sequencing applications is a critical step in producing representative, unbiased sequencing data. The iGenomX Riptide High Throughput Rapid Library Prep Kit purports to provide high-quality sequencing data with lower costs compared to other Illumina library kits. To test these claims, we compared sequence data quality of Riptide libraries to libraries constructed with KAPA Hyper and NEBNext Ultra. Across several single-source genome samples, mapping performance and de novo assembly of Riptide libraries were similar to conventional libraries prepared with the same DNA. Poor performance of some libraries resulted in low sequencing depth. In particular, degraded DNA samples may be challenging to sequence with Riptide. There was little cross-well plate contamination with the overwhelming majority of reads belong to the proper source genomes. The sequencing of metagenome samples using different Riptide primer sets resulted in variable taxonomic assignment of reads. Increased adoption of the Riptide kit will decrease library preparation costs. However, this method might not be suitable for degraded DNA.

Genomic reconfiguration in parasitic plants involves considerable gene losses alongside global genome size inflation and gene births

Parasitic plant genomes and transcriptomes reveal numerous genetic innovations, the functional-evolutionary relevance and roles of which open unprecedented research avenues.

Benchmarking and optimization of a high-throughput sequencing based method for transgene sequence variant analysis in biotherapeutic cell line development

In recent years, High-Throughput Sequencing (HTS) based methods to detect mutations in biotherapeutic transgene products have become a key quality step deployed during the development of manufacturing cell line clones. Previously we reported on a higher throughput, rapid mutation detection method based on amplicon sequencing (targeting transgene RNA) and detailed its implementation to facilitate cell line clone selection. By gaining experience with our assay in a diverse set of cell line development programs, we improved the computational analysis as well as experimental protocols. Here we report on these improvements as well as on a comprehensive benchmarking of our assay. We evaluated assay performance by mixing amplicon samples of a verified mutated antibody clone with a non-mutated antibody clone to generate spike-in mutations from ∼60% down to ∼0.3% frequencies. We subsequently tested the effect of 16 different sample and HTS library preparation protocols on the assay's ability to quantify mutations and on the occurrence of false-positive background error mutations (artifacts). Our evaluation confirmed assay robustness, established a high confidence limit of detection of ∼0.6%, and identified protocols that reduce error levels thereby significantly reducing a source of false positives that bottlenecked the identification of low-level true mutations.

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.