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Massively parallel sequencing (MPS) technology has become the gold standard in mitochondrial DNA research due to its high sensitivity in detecting mtDNA heteroplasmy, a prognostic marker in various medical applications. Various MPS technologies and platforms used for mtDNA analysis exist. Obtaining reliable and sensitive results requires deep and uniform coverage of the entire mtDNA sequence, which is heavily influenced by the choice of library preparation method and sequencing platform. Here, we present a comparison of the sequencing coverage and the ability to heteroplasmy detection using two library preparation protocols (Nextera XT DNA Library Preparation Kit and Nextera DNA Flex Library Preparation Kit) and two different (MiSeq FGx and ISeq 100) Illumina MPS platforms. Our study indicates that the Nextera DNA Flex Library protocol provides a more balanced coverage along the mitogenome and a reliable heteroplasmy detection with both MiSeq and iSeq Illumina MPS systems.

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Whole-genome sequencing (WGS) is becoming the new standard for bacterial high-resolution typing and the performance of laboratories is being evaluated in interlaboratory comparisons. The use of the Illumina Nextera XT library preparation kit has been found to be associated with poorer performance due to a GC-content-dependent coverage bias. The bias is especially strong when sequencing low GC-content species. Here, we have made an in-depth analysis of the Nextera XT coverage bias problem using data from a proficiency test of the low GC-content species Campylobacter jejuni. We have compared Nextera XT with Nextera Flex/DNA Prep and examined the consequences on downstream WGS analysis when using different quantities of raw data. We have also analyzed how the coverage bias relates to differential usage of tagmentation cleavage sites. We found that the tagmentation site was characterized by a symmetrical motif with a central AT-rich region surrounded by Gs and Cs. The Gs and Cs appeared to be the main determinant for cleavage efficiency and the genomic regions that were associated with low coverage only contained low-efficiency cleavage sites. This explains why low GC-content genomes and regions are more subjected to coverage bias. We furthermore extended our analysis to other datasets representing other bacterial species. We visualized how the coverage bias was large in low GC-content species such as C. jejuni, C. coli, Staphylococcus aureus, and Listeria monocytogenes, whereas species with neutral GC-content such as Salmonella enterica and Escherichia coli were only affected in certain regions. Species with high GC-content such as Mycobacterium tuberculosis and Pseudomonas aeruginosa were hardly affected at all. The coverage bias associated with Nextera XT was not found when Nextera Flex/DNA Prep had been used.

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Mitochondrial DNA (mtDNA) is a small but significant part of the human genome, whose applicability potential has gradually increased with the advent of massively parallel sequencing (MPS) technology. Knowledge of the particular workflow, equipment, and reagents used, along with extensive usage of negative controls to monitor all preparation steps constitute the prerequisites for confident reporting of results. In this study, we performed an assessment of Illumina® Human mtDNA Genome assay on MiSeq FGx™ instrument. Through analysis of several types of negative controls, as well as mtDNA positive controls, we established thresholds for data analysis and interpretation, consisting of several components: minimum read depth (220 reads), minimum quality score (41), percentage of minor allele sufficient for analysis (3.0%), percentage of minor allele sufficient for interpretation (6.0%), and percentage of major allele sufficient for homoplasmic variant call (97.0%). Based on these criteria, we defined internal guidelines for analysis and interpretation of mtDNA results obtained by MPS. Our study shows that the whole mtDNA assay on MiSeq FGx™ produces repeatable and reproducible results, independent of the analyst, which are also concordant with Sanger-type sequencing results for mtDNA control region, as well as with MPS results produced by NextSeq®. Overall, established thresholds and interpretation guidelines were successfully applied for the sequencing of complete mitochondrial genomes from high-quality samples. The underlying principles and proposed methodology on the definition of internal laboratory guidelines for analysis and interpretation of MPS results may be applicable to similar MPS workflows, e.g. targeting good-quality samples in forensic genetics and molecular diagnostics.

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In the last few years single-cell RNA sequencing (scRNA-seq) has enabled the investigation of cellular heterogeneity at the transcriptional level, the characterization of rare cell types as well as the detailed analysis of the stochastic nature of gene expression. A large number of methods have been developed, varying in their throughput, sensitivity, and scalability. A major distinction is whether they profile only 5'- or 3'-terminal part of the transcripts or allow for the characterization of the entire length of the transcripts. Among the latter, Smart-seq2 is still considered the "gold standard" due to its sensitivity, precision, lower cost, scalability and for being easy to set up on automated platforms. In this chapter I describe how to efficiently generate sequencing-ready libraries, highlight common issues and pitfalls, and offer solutions for generating high-quality data.

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Single-cell RNA-seq technology allows for the identification of heterogeneous cell populations, measures stochastic gene expressions, and identifies highly variable genes. Thus, with this technology it is possible to identify relevant pathways involved in development or in disease progression. Herein, we describe a protocol to capture and process single-cell transcriptomes that will be used for RNA sequencing. This chapter discusses the use of the Fluidigm C1 System and Integrated Fluidic Circuit microfluidics system, TapeStation 4200, SMART-Seq v4, Nextera XT Library Preparation Kit, and AMPure XP beads.

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Single-cell genomics allows bypassing the culturing step and to directly access environmental microbes one cell at a time. The method has been successfully applied to explore archaeal and bacterial candidate phyla, referred to as microbial dark matter. Here I summarize the single-cell genomics workflow, including sample preparation and preservation, high-throughput fluorescence-activated cell sorting, cell lysis and amplification of environmental samples. Furthermore I describe phylogenetic screening based on 16S rRNA genes and suggest a suitable library preparation and sequencing approach.

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Generating mitochondrial genome (mitogenome) data from reference samples in a rapid and efficient manner is critical to harnessing the greater power of discrimination of the entire mitochondrial DNA (mtDNA) marker. The method of long-range target enrichment, Nextera XT library preparation, and Illumina sequencing on the MiSeq is a well-established technique for generating mitogenome data from high-quality samples. To this end, a validation was conducted for this mitogenome method processing up to 24 samples simultaneously along with analysis in the CLC Genomics Workbench and utilizing the AQME (AFDIL-QIAGEN mtDNA Expert) tool to generate forensic profiles. This validation followed the Federal Bureau of Investigation's Quality Assurance Standards (QAS) for forensic DNA testing laboratories and the Scientific Working Group on DNA Analysis Methods (SWGDAM) validation guidelines. The evaluation of control DNA, non-probative samples, blank controls, mixtures, and nonhuman samples demonstrated the validity of this method. Specifically, the sensitivity was established at ≥25 pg of nuclear DNA input for accurate mitogenome profile generation. Unreproducible low-level variants were observed in samples with low amplicon yields. Further, variant quality was shown to be a useful metric for identifying sequencing error and crosstalk. Success of this method was demonstrated with a variety of reference sample substrates and extract types. These studies further demonstrate the advantages of using NGS techniques by highlighting the quantitative nature of heteroplasmy detection. The results presented herein from more than 175 samples processed in ten sequencing runs, show this mitogenome sequencing method and analysis strategy to be valid for the generation of reference data.

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Next-generation sequencing (NGS) facilitates the rapid and high-throughput generation of human mitochondrial genome (mitogenome) data to build population and reference databases for forensic comparisons. To this end, long-range amplification provides an effective method of target enrichment that is amenable to library preparation assays employing DNA fragmentation. This study compared the Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA) and the KAPA HyperPlus Library Preparation Kit (Kapa Biosystems, Wilmington, MA) for enzymatic fragmentation and indexing of ∼8500bp mitogenome amplicons for Illumina sequencing. The Nextera XT libraries produced low-coverage regions that were consistent across all samples, while the HyperPlus libraries resulted in uniformly high coverage across the mitogenome, even with reduced-volume reaction conditions. The balanced coverage observed from KAPA HyperPlus libraries enables not only low-level variant calling across the mitogenome but also increased sample multiplexing for greater processing efficiency.

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High-throughput sequencing libraries are typically limited by the requirement for nanograms to micrograms of input DNA. This bottleneck impedes the microscale analysis of ecosystems and the exploration of low biomass samples. Current methods for amplifying environmental DNA to bypass this bottleneck introduce considerable bias into metagenomic profiles. Here we describe and validate a simple modification of the Illumina Nextera XT DNA library preparation kit which allows creation of shotgun libraries from sub-nanogram amounts of input DNA. Community composition was reproducible down to 100 fg of input DNA based on analysis of a mock community comprising 54 phylogenetically diverse Bacteria and Archaea. The main technical issues with the low input libraries were a greater potential for contamination, limited DNA complexity which has a direct effect on assembly and binning, and an associated higher percentage of read duplicates. We recommend a lower limit of 1 pg (∼100-1,000 microbial cells) to ensure community composition fidelity, and the inclusion of negative controls to identify reagent-specific contaminants. Applying the approach to marine surface water, pronounced differences were observed between bacterial community profiles of microliter volume samples, which we attribute to biological variation. This result is consistent with expected microscale patchiness in marine communities. We thus envision that our benchmarked, slightly modified low input DNA protocol will be beneficial for microscale and low biomass metagenomics.