Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study.

Assessing the reproducibility, accuracy and utility of massively parallel DNA sequencing platforms remains an ongoing challenge. Here the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Study benchmarks the performance of a set of sequencing instruments (HiSeq/NovaSeq/paired-end 2 × 250-bp chemistry, Ion S5/Proton, PacBio circular consensus sequencing (CCS), Oxford Nanopore Technologies PromethION/MinION, BGISEQ-500/MGISEQ-2000 and GS111) on human and bacterial reference DNA samples. Among short-read instruments, HiSeq 4000 and X10 provided the most consistent, highest genome coverage, while BGI/MGISEQ provided the lowest sequencing error rates. The long-read instrument PacBio CCS had the highest reference-based mapping rate and lowest non-mapping rate. The two long-read platforms PacBio CCS and PromethION/MinION showed the best sequence mapping in repeat-rich areas and across homopolymers. NovaSeq 6000 using 2 × 250-bp read chemistry was the most robust instrument for capturing known insertion/deletion events. This study serves as a benchmark for current genomics technologies, as well as a resource to inform experimental design and next-generation sequencing variant calling.

Assessment of REPLI-g Multiple Displacement Whole Genome Amplification (WGA) Techniques for Metagenomic Applications.

Amplification of minute quantities of DNA is a fundamental challenge in low-biomass metagenomic and microbiome studies because of potential biases in coverage, guanine-cytosine (GC) content, and altered species abundances. Whole genome amplification (WGA), although widely used, is notorious for introducing artifact sequences, either by amplifying laboratory contaminants or by nonrandom amplification of a sample's DNA. In this study, we investigate the effect of REPLI-g multiple displacement amplification (MDA; Qiagen, Valencia, CA, USA) on sequencing data quality and species abundance detection in 8 paired metagenomic samples and 1 titrated, mixed control sample. We extracted and sequenced genomic DNA (gDNA) from 8 environmental samples and compared the quality of the sequencing data for the MDA and their corresponding non-MDA samples. The degree of REPLI-g MDA bias was evaluated by sequence metrics, species composition, and cross-validating observed species abundance and species diversity estimates using the One Codex and MetaPhlAn taxonomic classification tools. Here, we provide evidence of the overall efficacy of REPLI-g MDA on retaining sequencing data quality and species abundance measurements while providing increased yields of high-fidelity DNA. We find that species abundance estimates are largely consistent across samples, even with REPLI-g amplification, as demonstrated by the Spearman's rank order coefficient (R2 > 0.8). However, REPLI-g MDA often produced fewer classified reads at the species, genera, and family level, resulting in decreased species diversity. We also observed some areas with the PCR "jackpot effect," with varying input DNA values for the Metagenomics Research Group (MGRG) controls at specific genomic loci. We visualize this effect in whole genome coverage plots and with sequence composition analyses and note these caveats of the MDA method. Despite overall concordance of species abundance between the amplified and unamplified samples, these results demonstrate that amplification of DNA using the REPLI-g method has some limitations. These concerns could be addressed by future improvements in the enzymes or methods for REPLI-g to be considered a >99% robust method for increasing the amount of high-fidelity DNA from low-biomass samples or at the very least, accounted for during computational analysis of MDA samples.

Genomic approaches to the assessment of human spina bifida risk.

Structural birth defects are a leading cause of mortality and morbidity in children world-wide, affecting as much as 6% of all live births. Among these conditions, neural tube defects (NTDs), including spina bifida and anencephaly, arise from a combination of complex gene and environment interactions that are as yet poorly understood within human populations. Rapid advances in massively parallel DNA sequencing and bioinformatics allow for analyses of the entire genome beyond the 2% of the genomic sequence covering protein coding regions. Efforts to collect and analyze these large datasets hold promise for illuminating gene network variations and eventually epigenetic events that increase individual risk for failure to close the neural tube. In this review, we discuss current challenges for DNA genome sequence analysis of NTD affected populations, and compare experience in the field with other complex genetic disorders for which large datasets are accumulating. The ultimate goal of this research is to find strategies for optimizing conditions that promote healthy birth outcomes for individual couples. Birth Defects Research 109:120-128, 2017. © 2016 Wiley Periodicals, Inc.

Globalizing and crowdsourcing biomedical research.

INTRODUCTION OR BACKGROUND: Crowdfunding and crowdsourcing of medical research has emerged as a novel paradigm for many biomedical disciplines to rapidly collect, process and interpret data from high-throughput and high-dimensional experiments. The novelty and promise of these approaches have led to fundamental discoveries about RNA mechanisms, microbiome dynamics and even patient interpretation of test results. However, these methods require robust training protocols, uniform sampling methods and experimental rigor in order to be useful for subsequent research efforts. Executed correctly, crowdfunding and crowdsourcing can leverage public resources and engagement to generate support for scientific endeavors that would otherwise be impossible due to funding constraints and or the large number of participants needed for data collection. SOURCES OF DATA: We conducted a comprehensive literature review of scientific studies that utilized crowdsourcing and crowdfunding to generate data. We also discuss our own experiences conducting citizen-science research initiatives (MetaSUB and PathoMap) in ensuring data robustness, educational outreach and public engagement. AREAS OF AGREEMENT: We demonstrate the efficacy of crowdsourcing mechanisms for revolutionizing microbiome and metagenomic research to better elucidate the microbial and genetic dynamics of cities around the world (as well as non-urban areas). Crowdsourced studies have been able to create an improved and unprecedented ability to monitor, design and measure changes at the microbial and macroscopic scale. Thus, the use of crowdsourcing strategies has dramatically altered certain genomics research to create global citizen-science initiatives that reveal new discoveries about the world's genetic dynamics. AREAS OF CONTROVERSY: The effectiveness of crowdfunding and crowdsourcing is largely dependent on the study design and methodology. One point of contention for the present discussion is the validity and scientific rigor of data that are generated by non-scientists. Selection bias, limited sample sizes and limitations for scientists in enforcing standardized protocols are all challenges for those who engage in citizen-science initiatives. GROWING POINTS: Despite the aforementioned concerns, crowdsourced data allow for greater inroads into the field of personalized medicine, whereby community members take an active role in generating data about their personal and environmental health. AREAS TIMELY FOR DEVELOPING RESEARCH: Crowdsourced viral and metagenomic studies are the next step in elucidating the genomic and epigenomic characterization of urban population health.

Enhanced reduced representation bisulfite sequencing for assessment of DNA methylation at base pair resolution.

DNA methylation pattern mapping is heavily studied in normal and diseased tissues. A variety of methods have been established to interrogate the cytosine methylation patterns in cells. Reduced representation of whole genome bisulfite sequencing was developed to detect quantitative base pair resolution cytosine methylation patterns at GC-rich genomic loci. This is accomplished by combining the use of a restriction enzyme followed by bisulfite conversion. Enhanced Reduced Representation Bisulfite Sequencing (ERRBS) increases the biologically relevant genomic loci covered and has been used to profile cytosine methylation in DNA from human, mouse and other organisms. ERRBS initiates with restriction enzyme digestion of DNA to generate low molecular weight fragments for use in library preparation. These fragments are subjected to standard library construction for next generation sequencing. Bisulfite conversion of unmethylated cytosines prior to the final amplification step allows for quantitative base resolution of cytosine methylation levels in covered genomic loci. The protocol can be completed within four days. Despite low complexity in the first three bases sequenced, ERRBS libraries yield high quality data when using a designated sequencing control lane. Mapping and bioinformatics analysis is then performed and yields data that can be easily integrated with a variety of genome-wide platforms. ERRBS can utilize small input material quantities making it feasible to process human clinical samples and applicable in a range of research applications. The video produced demonstrates critical steps of the ERRBS protocol.

Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study.

High-throughput RNA sequencing (RNA-seq) greatly expands the potential for genomics discoveries, but the wide variety of platforms, protocols and performance capabilitites has created the need for comprehensive reference data. Here we describe the Association of Biomolecular Resource Facilities next-generation sequencing (ABRF-NGS) study on RNA-seq. We carried out replicate experiments across 15 laboratory sites using reference RNA standards to test four protocols (poly-A-selected, ribo-depleted, size-selected and degraded) on five sequencing platforms (Illumina HiSeq, Life Technologies PGM and Proton, Pacific Biosciences RS and Roche 454). The results show high intraplatform (Spearman rank R > 0.86) and inter-platform (R > 0.83) concordance for expression measures across the deep-count platforms, but highly variable efficiency and cost for splice junction and variant detection between all platforms. For intact RNA, gene expression profiles from rRNA-depletion and poly-A enrichment are similar. In addition, rRNA depletion enables effective analysis of degraded RNA samples. This study provides a broad foundation for cross-platform standardization, evaluation and improvement of RNA-seq.

Assessment and improvement of Indian-origin rhesus macaque and Mauritian-origin cynomolgus macaque genome annotations using deep transcriptome sequencing data.

BACKGROUND: The genome annotations of rhesus (Macaca mulatta) and cynomolgus (Macaca fascicularis) macaques, two of the most common non-human primate animal models, are limited. METHODS: We analyzed large-scale macaque RNA-based next-generation sequencing (RNAseq) data to identify un-annotated macaque transcripts. RESULTS: For both macaque species, we uncovered thousands of novel isoforms for annotated genes and thousands of un-annotated intergenic transcripts enriched with non-coding RNAs. We also identified thousands of transcript sequences which are partially or completely 'missing' from current macaque genome assemblies. We showed that many newly identified transcripts were differentially expressed during SIV infection of rhesus macaques or during Ebola virus infection of cynomolgus macaques. CONCLUSIONS: For two important macaque species, we uncovered thousands of novel isoforms and un-annotated intergenic transcripts including coding and non-coding RNAs, polyadenylated and non-polyadenylated transcripts. This resource will greatly improve future macaque studies, as demonstrated by their applications in infectious disease studies.

Faster sequencers, larger datasets, new challenges.

A report on the Advances in Genome Biology and Technology (AGBT) meeting, Marco Island, Florida, USA, 15-18 February 2012.

RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays.

Ultra-high-throughput sequencing is emerging as an attractive alternative to microarrays for genotyping, analysis of methylation patterns, and identification of transcription factor binding sites. Here, we describe an application of the Illumina sequencing (formerly Solexa sequencing) platform to study mRNA expression levels. Our goals were to estimate technical variance associated with Illumina sequencing in this context and to compare its ability to identify differentially expressed genes with existing array technologies. To do so, we estimated gene expression differences between liver and kidney RNA samples using multiple sequencing replicates, and compared the sequencing data to results obtained from Affymetrix arrays using the same RNA samples. We find that the Illumina sequencing data are highly replicable, with relatively little technical variation, and thus, for many purposes, it may suffice to sequence each mRNA sample only once (i.e., using one lane). The information in a single lane of Illumina sequencing data appears comparable to that in a single array in enabling identification of differentially expressed genes, while allowing for additional analyses such as detection of low-expressed genes, alternative splice variants, and novel transcripts. Based on our observations, we propose an empirical protocol and a statistical framework for the analysis of gene expression using ultra-high-throughput sequencing technology.