Primer designs for the HPeV genome.

Preliminary NGS prediction and PCR or ELISA detection.

The advent of next generation sequencing (NGS) technologies have revolutionised the way biologists produce, analyse and interpret data. Although NGS platforms provide a cost-effective way to discover genome-wide variants from a single experiment, variants discovered by NGS need follow up validation due to the high error rates associated with various sequencing chemistries. Recently, whole exome sequencing has been proposed as an affordable option compared to whole genome runs but it still requires follow up validation of all the novel exomic variants. Customarily, a consensus approach is used to overcome the systematic errors inherent to the sequencing technology, alignment and post alignment variant detection algorithms. However, the aforementioned approach warrants the use of multiple sequencing chemistry, multiple alignment tools, multiple variant callers which may not be viable in terms of time and money for individual investigators with limited informatics know-how. Biologists often lack the requisite training to deal with the huge amount of data produced by NGS runs and face difficulty in choosing from the list of freely available analytical tools for NGS data analysis. Hence, there is a need to customise the NGS data analysis pipeline to preferentially retain true variants by minimising the incidence of false positives and make the choice of right analytical tools easier. To this end, we have sampled different freely available tools used at the alignment and post alignment stage suggesting the use of the most suitable combination determined by a simple framework of pre-existing metrics to create significant datasets.

Selection of existing software packages available for amplicon sequencing data analysis.

The data included here are part of a collection of different types of reference data used in the bioinformatic analysis pipeline called Twist Solid GMS560. The pipeline is based on the Hydra-genetics framework and analyses NGS short read data from the GMS560 Twist panel which is used on solid cancer samples.The data in this specific item include general publicly available reference files used in the pipeline by many different programs. Downloading data from here will ensure compatible and correct versions for v0.7.0 of the pipeline.

Using high-throughput sequencing for precise genotyping of multi-locus gene families, such as the Major Histocompatibility Complex (MHC), remains challenging, due to the complexity of the data and difficulties in distinguishing genuine from erroneous variants. Several dedicated genotyping pipelines for data from high-throughput sequencing, such as next-generation sequencing (NGS), have been developed to tackle the ensuing risk of artificially inflated diversity. Here, we thoroughly assess three such multi-locus genotyping pipelines for NGS data, the DOC method, AmpliSAS and ACACIA, using MHC class IIβ datasets of three-spined stickleback gDNA, cDNA, and "artificial" plasmid samples with known allelic diversity. We show that genotyping of gDNA and plasmid samples at optimal pipeline parameters was highly accurate and reproducible across methods. However, for cDNA data, gDNA-optimal parameter configuration yielded decreased overall genotyping precision and consistency between pipelines. Further adjustments of key clustering parameters were required tο account for higher error rates and larger variation in sequencing depth per allele, highlighting the importance of template-specific pipeline optimization for reliable genotyping of multi-locus gene families. Through accurate paired gDNA-cDNA typing and MHC-II haplotype inference, we show that MHC-II allele-specific expression levels correlate negatively with allele number across haplotypes. Lastly, sibship-assisted cDNA-typing of MHC-I revealed novel variants linked in haplotype blocks and a higher-than-previously-reported individual MHC-I allelic diversity. In conclusion, we provide novel genotyping protocols for the three-spined stickleback MHC-I and -II genes and evaluate the performance of popular NGS-genotyping pipelines. We also show that fine-tuned genotyping of paired gDNA-cDNA samples facilitates amplification bias-corrected MHC allele expression analysis.

Overview of the parameters investigated for the variant calling pipeline with GLM.

Next-generation DNA sequencing (NGS) produces vast amounts of DNA sequence data, but it is not specifically designed to generate data suitable for genetic mapping. Recently developed DNA library preparation methods for NGS have helped solve this problem, however, by combining the use of reduced representation libraries with DNA sample barcoding to generate genome-wide genotype data from a common set of genetic markers across a large number of samples. Here we use such a method, called genotyping-by-sequencing (GBS), to produce a data set for genetic mapping in an F1 population of apples (Malus x domestica) segregating for skin color. We show that GBS produces a relatively large, but extremely sparse, genotype matrix: over 270,000 SNPs were discovered, but most SNPs have too much missing data across samples to be useful for genetic mapping. After filtering for genotype quality and missing data, only 6% of the 85 million DNA sequence reads contributed to useful genotype calls. Despite this limitation, using existing software and a set of simple heuristics, we generated a final genotype matrix containing 3967 SNPs from 89 DNA samples from a single lane of Illumina HiSeq and used it to create a saturated genetic linkage map and to identify a known QTL underlying apple skin color. We therefore demonstrate that GBS is a cost effective method for generating genome-wide SNP data suitable for genetic mapping in a highly diverse and heterozygous agricultural species. We anticipate future improvements to the GBS analysis pipeline presented here that will enhance the utility of next-generation DNA sequence data for the purposes of genetic mapping across diverse species.

Next generation sequencing allows access to a large quantity of genomic data. In plants, several studies used whole chloroplast genome sequences for inferring phylogeography or phylogeny. Even though the chloroplast is a haploid organelle, NGS plastome data identified a non negligible number of intra-individual polymorphic SNPs. Such observations could have several causes such as sequencing errors, the presence of heteroplasmy or transfer of chloroplast sequences in the nuclear and mitochondrial genomes. The occurrence of allelic diversity has practical important impacts on the identification of diversity, the analysis of the chloroplast data and beyond that, significant evolutionary questions. In this study, we show that the observed intra-individual polymorphism of chloroplast sequence data is probably the result of plastid DNA transferred into the mitochondrial and/or the nuclear genomes. We further assess nine different bioinformatics pipelines’ error rates for SNP and genotypes calling using SNPs identified in Sanger sequencing. Specific pipelines are adequate to deal with this issue, optimizing both specificity and sensitivity. Our results will allow a proper use of whole chloroplast NGS sequence and will allow a better handling of NGS chloroplast sequence diversity.

Fish gill tissue samples were processed and underwent PCR. Amplicons were sent to UIC Sequencing Core (Chicago, IL, USA) for library construction and sequencing. Sequence data was analyzed using the Dada2 pipeline using R package ‘dada2’. For each amplicon sequence variant (ASV), taxonomy (up to the species level) was inferred by alignment to the Silva non-redundant small subunit ribosomal RNA database. For data analysis and generation of figures, the online tool MicrobiomeAnalyst (https://www.microbiomeanalyst.ca/MicrobiomeAnalyst/home.xhtml) was used. Taxonomy labels were assigned using the SILVA taxonomic framework (https://www.arb-silva.de/documentation/silva-taxonomy/).

Raw NGS sequence data (FASTQ data) and analytical pipeline (full analytical pipeline for the analysis of mtDNA from FASTQ to annotated variant call data). Data and pipeline available upon request (unrestricted after publication) via email with corresponding authors (detailed below).

Please email Dr Gavin Hudson for access - Gavin.Hudson@ncl.ac.uk and Prof Mary Herbert.

The data included here are part of a collection of different types of reference data used in the bioinformatic analysis pipeline called Twist Solid GMS560. The pipeline is based on the Hydra-genetics framework and analyses NGS short read data from the GMS560 Twist panel which is used on solid cancer samples. The data in this specific item include panel of normals and artifact filer files generated for the Twist GMS560 panel. Panel of normals and artifacts are specific to panel used and sequencing machine. Programs using these files include MSIsensor-Pro, GATK CNV, CNVkit, SVDB, PureCN, and small variant filtering.

Normalized relative variable importance for all parameters characterizing SNVs, considering 454, Ion Torrent and Illumina NextSeq sequencing data.

BACKGROUND: Rise of temperatures and shortening of available water as result of predicted climate change will impose significant pressure on long-lived forest tree species. Discovering allelic variation present in drought related genes of two Austrian oak species can be the key to understand mechanisms of natural selection and provide forestry with key tools to cope with future challenges. RESULTS: In the present study we have used Roche 454 sequencing and developed a bioinformatic pipeline to process multiplexed tagged amplicons in order to identify single nucleotide polymorphisms and allelic sequences of ten candidate genes related to drought/osmotic stress from sessile oak (Quercus robur) and pedunculate oak (Q. petraea) individuals. Out of these, eight genes of 336 oak individuals growing in Austria have been detected with a total number of 158 polymorphic sites. Allele numbers ranged from ten to 52 with observed heterozygosity ranging from 0.115 to 0.640. All loci deviated from Hardy-Weinberg equilibrium and linkage disequilibrium was found among six combinations of loci. CONCLUSIONS: We have characterized 183 alleles of drought related genes from oak species and detected first evidences of natural selection. Beside the potential for marker development, we have created an expandable bioinformatic pipeline for the analysis of next generation sequencing data.

Overview of the subjects sequenced on 454, Ion Torrent and Illumina NextSeq (comparison set marked with a c, re-sequencing set marked with an r).

Background: Viral infections are common complications following allogeneic hematopoietic stem cell transplantation (allo-HSCT). Allo-HSCT recipients with steroid-refractory/dependent graft-versus-host disease (GvHD) are highly immunosuppressed and are more vulnerable to infections with weakly pathogenic or commensal viruses. Here, twenty-five adult allo-HSCT recipients from 2016 to 2019 with acute or chronic steroid-refractory/dependent GvHD were enrolled in a prospective cohort of patients at Geneva University Hospitals. We performed metagenomics next-generation sequencing (mNGS) analysis using a validated viral pipeline and de novo analysis on pooled stored routine plasma samples collected throughout the period of intensive steroid treatment or second-line GvHD therapy to identify weakly pathogenic, commensal and unexpected viruses.

Results: Median duration of intensive immunosuppression was 5.1 months (IQR 5.5). GvHD-related mortality rate was 36%. mNGS analysis detected viral nucle...

Groundwater samples for eDNA analysis were collected in June 2015 approximately 18 months after the formal commissioning of the Pawsey Centre GWC system located in suburban Perth, Western Australia, in November 2013. DNA was extracted from filtered bore water samples from Production bores and monitoring bores from the Pawsey bores and Water Corporation bores. Lineage: Groundwater was filtered on 0.1 µm Durapore® membrane filters using a peristaltic pump. Cells were harvested on the on 0.1 µm Durapore® membrane filters and 0.2 g biomass from the filters was used for extracting DNA the Powersoil DNA isolation kit with extended incubation steps and an extra ethanol wash before the final elution in 100 µL of C6 (elution buffer). DNA samples were amplified using EMP 16S rRNA primers to analyse bacteria communities and EMP 18S v4 rRNA primers for eukaryote community analysis. Bacterial and archaeal 16S rRNA genes were amplified using the standard Earth Microbiome project (EMP) 16S Illumina amplicon protocol (http://press.igsb.anl.gov/earthmicrobiome/protocols-and-standards/16s/) with primers: 515F (GTGCCAGCMGCCGCGGTAA) and 806R (GGACTACHVGGGTWTCTAAT) (Caporaso et al., 2011). Eukaryotic 18S rRNA genes were amplified using EMP 18S Illumina amplicon protocol (http://press.igsb.anl.gov/earthmicrobiome/protocols-and-standards/18s/) with primers Euk_1391f (GTACACACCGCCCGTC) and EukBr (TGATCCTTCTGCAGGTTCACCTAC) (Amaral-Zettler et al. 2009). Amplicon libraries were prepared with Illumina Nextera kit. Next generation sequencing (NGS) was carried out using the Illumina MiSeq platform (Illumina, Inc., San Diego, USA), 2x250 bp with paired reads, and performed according to manufacturer’s directions at the Ramaciotti Centre for Genomics (UNSW Sydney, Australia). The 18S and 16S rRNA gene sequence data were processed using a custom pipeline Greenfield Hybrid Amplicon Pipeline (GHAP) which is based around USEARCH tools (Edgar, 2013).

The marine eDNA biomonitoring market is experiencing significant growth, driven by increasing environmental regulations, a rising awareness of biodiversity loss, and the demand for efficient and cost-effective monitoring solutions. The market size is estimated at XXX million in 2025, with a compound annual growth rate (CAGR) of XX% projected from 2025 to 2033. This expansion is fueled by several key drivers: the increasing adoption of eDNA techniques by governmental and research institutions for species monitoring and habitat assessment; the growing need for accurate and timely data in fisheries management to support sustainable fishing practices and combat illegal fishing; and the expanding application of eDNA in the energy sector for environmental impact assessments and risk mitigation related to offshore activities like oil and gas exploration and renewable energy development. Trends within the market include the ongoing development of more sensitive and specific eDNA assays, utilizing advanced techniques like Next-Generation Sequencing (NGS) to detect a wider range of species and analyze complex microbial communities. Miniaturization of sample processing equipment and the development of user-friendly field kits are lowering the barriers to entry, further expanding market reach. However, the market faces some restraints including the high initial investment costs associated with advanced NGS technology, the need for standardized protocols and quality control measures for data reliability, and the potential for false positives or negatives caused by environmental factors influencing eDNA preservation and detection. Segmentation of the market includes PCR-based methods, offering a more cost-effective and simpler approach, versus NGS, which provides greater sensitivity and species resolution. Applications span fisheries management, energy industry compliance, and other areas like conservation biology and invasive species detection. Key players like Illumina, Stantec, Eurofins Genomics, and others are actively involved in developing and commercializing eDNA biomonitoring solutions, fostering innovation and competition within this rapidly growing sector. Geographically, North America currently holds a substantial share of the market, owing to strong regulatory frameworks and robust research infrastructure. However, the Asia-Pacific region is anticipated to witness the fastest growth during the forecast period (2025-2033), driven by increasing environmental concerns, economic development, and investments in marine research and conservation initiatives within countries like China, Japan, and India. Europe also presents a substantial market due to its commitment to environmental protection and biodiversity monitoring. The Middle East and Africa, and South America, while currently holding smaller market shares, are projected to experience gradual growth as awareness of eDNA technology increases and regulatory demands strengthen. The competitive landscape is characterized by a mix of large multinational companies offering comprehensive services and smaller specialized firms focusing on specific niche applications or geographic regions. The market's future depends on continued technological advancements, expanding regulatory support, decreasing costs, and the ongoing development of robust and standardized data analysis pipelines to ensure the widespread adoption of this innovative biomonitoring technique.

Previous phylogenetic studies in oaks (Quercus, Fagaceae) have failed to resolve the backbone topology of the genus with strong support. Here, we utilize next-generation sequencing of restriction-site associated DNA (RAD-Seq) to resolve a framework phylogeny of a predominantly American clade of oaks whose crown age is estimated at 23–33 million years old. Using a recently developed analytical pipeline for RAD-Seq phylogenetics, we created a concatenated matrix of 1.40 E06 aligned nucleotides, constituting 27,727 sequence clusters. RAD-Seq data were readily combined across runs, with no difference in phylogenetic placement between technical replicates, which overlapped by only 43–64% in locus coverage. 17% (4,715) of the loci we analyzed could be mapped with high confidence to one or more expressed sequence tags in NCBI Genbank. A concatenated matrix of the loci that BLAST to at least one EST sequence provides approximately half as many variable or parsimony-informative characters as equal-sized datasets from the non-EST loci. The EST-associated matrix is more complete (fewer missing loci) and has slightly lower homoplasy than non-EST subsampled matrices of the same size, but there is no difference in phylogenetic support or relative attribution of base substitutions to internal versus terminal branches of the phylogeny. We introduce a partitioned RAD visualization method (implemented in the R package RADami; http://cran.r-project.org/web/packages/RADami) to investigate the possibility that suboptimal topologies supported by large numbers of loci—due, for example, to reticulate evolution or lineage sorting—are masked by the globally optimal tree. We find no evidence for strongly-supported alternative topologies in our study, suggesting that the phylogeny we recover is a robust estimate of large-scale phylogenetic patterns in the American oak clade. Our study is one of the first to demonstrate the utility of RAD-Seq data for inferring phylogeny in a 23–33 million year-old clade.