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Environmental DNA (eDNA) metabarcoding is an increasingly popular method for rapid biodiversity assessment. As with any ecological survey, false negatives can arise during sampling and, if unaccounted for, lead to biased results and potentially misdiagnosed environmental assessments. We developed a multi-scale, multi-species occupancy model for the analysis of community biodiversity data resulting from eDNA metabarcoding; this model accounts for imperfect detection and additional sources of environmental and experimental variation. We present methods for model assessment and model comparison and demonstrate how these tools improve the inferential power of eDNA metabarcoding data using a case study in a coastal, marine environment. Using occupancy models to account for factors often overlooked in the analysis of eDNA metabarcoding data will dramatically improve ecological inference, sampling design, and methodologies, empowering practitioners with an approach to wield the high-resolution biodiversity data of next-generation sequencing platforms.

India has the highest burden of Tuberculosis (TB) and multidrug-resistant TB (MDR-TB) worldwide. Innovative technology is the need of the hour to identify these cases that remain either undiagnosed or inadequately diagnosed due to the unavailability of appropriate tools at primary healthcare settings. We developed and evaluated 3 kits, namely ‘TB Detect’ (containing BioFM-Filter device), ‘TB Concentration and Transport’ (containing Trans-Filter device) and ‘TB DNA Extraction’ kits. These kits enable bio-safe equipment-free concentration of sputum on filters and improved fluorescence microscopy at primary healthcare centres, ambient temperature transport of dried inactivated sputum filters to central laboratories and molecular detection of drug resistance by PCR and DNA sequencing (Mol-DST). In a 2-site evaluation (n = 1190 sputum specimens) on presumptive TB patients, BioFM-Filter smear exhibited a significant increase in positivity of 7% and 4% over ZN smear and LED-FM smear (p

Deep sequencing of T-cell receptor (TCR) genes is powerful at profiling immune repertoire. To prepare a TCR sequencing library, multiplex polymerase chain reaction (mPCR) is widely applied and is highly efficient. That is, most mPCR products contain the region critical for antigen recognition, which also indicates regular V(D)J recombination. Multiplex PCR, however, may suffer from primer bias. A promising alternative is 5’-RACE, which avoids primer bias by applying only one primer pair. In 5’-RACE data, however, non-regular V(D)J recombination (e.g., TCR sequences without a V gene segment) has been observed and the frequency varies (30–80%) between studies. This suggests that the cause of or how to reduce non-regular TCR sequences is not yet well known by the science community. Although it is possible to speculate the cause by comparing the 5’-RACE protocols, careful experimental confirmation is needed and such a systematic study is still not available. Here, we examined the 5’-RACE protocol of a commercial kit and demonstrated how a modification increased the fraction of regular TCR-β sequences to >85%. We also found a strong linear correlation between the fraction of short DNA fragments and the percentage of non-regular TCR-β sequences, indicating that the presence of short DNA fragments in the library was the main cause of non-regular TCR-β sequences. Therefore, thorough removal of short DNA fragments from a 5’-RACE library is the key to high data efficiency. We highly recommend conducting a fragment length analysis before sequencing, and the fraction of short DNA fragments can be used to estimate the percentage of non-regular TCR sequences. As deep sequencing of TCR genes is still relatively expensive, good quality control should be valuable.

We describe herein a method of recharging used commercial spin columns or assembling homemade spin columns using filter paper as binding material for cost-effective, low throughput nucleic acid purification. The efficiency of filter paper-based spin columns was evaluated for purification of nucleic acids from various sources. Following protocols of commercial kits, we found filter paper to be a useful binding material for purification of nucleic acids, including plant genomic DNA, plant total RNA, PCR products, and DNA from agarose gels. However, filter paper has a weak binding affinity to plasmid DNA in tested miniprep protocols. Protocols for the use of filter paper recharged spin columns or homemade spin columns for low throughput purification of plant genomic DNA and total RNA with unused commercial kit buffers or less expensive homemade buffers are presented.

In the era of CRISPR gene editing and genetic screening, there is an increasing demand for quick and reliable nucleic acid extraction pipelines for rapid genotyping of large and diverse sample sets. Despite continuous improvements of current workflows, the handling-time and material costs per sample remain major limiting factors. Here we present a robust method for low-cost DIY-pipet tips addressing these needs; i.e. using a cellulose filter disc inserted into a regular pipet tip. These filter-in-tips allow for a rapid, stand-alone four-step genotyping workflow by simply binding the DNA contained in the primary lysate to the cellulose filter, washing it in water and eluting it directly into the buffer for the downstream application (e.g. PCR). This drastically cuts down processing time to maximum 30 seconds per sample, with the potential for parallelizing and automation. We show the ease and sensitivity of our procedure by genotyping genetically modified medaka (Oryzias latipes) and zebrafish (Danio rerio) embryos (targeted by CRISPR/Cas9 knock-out and knock-in) in a 96-well plate format. The robust isolation and detection of multiple alleles of various abundancies in a mosaic genetic background allows phenotype-genotype correlation already in the injected generation, demonstrating the reliability and sensitivity of the protocol. Our method is applicable across kingdoms to samples ranging from cells to tissues i. e. plant seedlings, adult flies, mouse cell culture and tissue as well as adult fish fin-clips.

The accuracy of next-generation sequencing (NGS) for detecting tumor-specific mutations in plasma DNA is hindered by errors introduced during PCR/sequencing, base substitutions caused by DNA damage, and pre-existing mutations in normal cells that are present at a low frequency. Here, we performed NGS of genes related to pancreatic cancer (comprising 2.8 kb of genomic DNA) in plasma DNA (average 4.5 ng) using molecular barcodes. The average number of sequenced molecules was 900, and the sequencing depth per molecule was 100 or more. We also developed a bioinformatic variant filter, called CV78, to remove variants that were not considered to be tumor-specific, i.e., those that are either absent or occur at low frequencies in the Catalogue of Somatic Mutations in Cancer database. In a cohort comprising 57 pancreatic cancer patients and 12 healthy individuals, sequencing initially identified variants in 31 (54%) and 5 (42%), respectively, whereas after applying the CV78 filter, 19 (33%) and zero were variant-positive. In a validation cohort consisting of 86 patients with pancreatic cancer and 20 patients with intraductal papillary mucinous neoplasm (IPMN), 62 (72%) with pancreatic cancer patients and 10 (50%) IPMN patients were initially variant positive. After CV78 filtering, these values were reduced to 32 (37%) and 1 (5%), respectively. The variant allele frequency of filtered variants in plasma ranged from 0.25% to 76.1%. Therefore, combining NGS and molecular barcodes with subsequent filtering is likely to eliminate most non-tumor-specific mutations.

Amphimeriasis, a fish-borne zoonotic disease caused by the liver fluke Amphimerus spp., has recently been reported as an emerging disease affecting an indigenous Ameridian group, the Chachi, living in Ecuador. The only method for diagnosing amphimeriasis was the microscopic detection of eggs from the parasite in patients' stool samples with very low sensitivity. Our group developed an ELISA technique for detection of anti-Amphimerus IgG in human sera and a molecular method based on LAMP technology (named LAMPhimerus) for specific and sensitive parasite DNA detection. The LAMPhimerus method showed to be much more sensitive than classical parasitological methods for amphimeriasis diagnosis using human stool samples for analysis. The objective of this work is to demonstrate the feasibility of using dried stool samples on filter paper as source of DNA in combination with the effectiveness of our previously designed LAMPhimerus assay for successfully Amphimerus sp. detection in clinical stool samples. A total of 102 untreated and undiluted stool samples collected from Chachi population were spread as thin layer onto common filter paper for easily transportation to our laboratory and stored at room temperature for one year until DNA extraction. When LAMPhimerus method was applied for Amphimerus sp. DNA detection, a higher number of positive results was detected (61/102; 59.80%) in comparison to parasitological methods (38/102; 37.25%), including 28/61 (45.90%) microscopy-confirmed Amphimerus sp. infections. The diagnostic parameters for the sensitivity and specificity werecalculated for our LAMPhimerus assay, which were 79.17% and 65.98%, respectively. We demonstrate, for the first time, that common filter paper is useful for easy collection and long-term storage of human stool samples for later DNA extraction and molecular analysis of human-parasitic trematode eggs. This simple, economic and easily handling method combined with the specific and sensible LAMPhimerus assay has the potential to beused as an effective molecular large-scale screening test for amphimeriasis-endemic areas.

This is the final version of the following article: Alsos, I.G., Lammers, Y., Yoccoz, N.G., Jørgensen, T., Sjögren, P., Gielly, L. & Edwards, M.E. (2018). Plant DNA metabarcoding of lake sediments: How does it represent the contemporary vegetation. PLoS ONE, 13(4). https://doi.org/10.1371/journal.pone.0195403, which can be retrieved from https://doi.org/10.1371/journal.pone.0195403. Licensed CC BY-NC-ND 4.0. Metabarcoding of lake sediments have been shown to reveal current and past biodiversity, but little is known about the degree to which taxa growing in the vegetation are represented in environmental DNA (eDNA) records. We analysed composition of lake and catchment vegetation and vascular plant eDNA at 11 lakes in northern Norway. Out of 489 records of taxa growing within 2 m from the lake shore, 17–49% (mean 31%) of the identifiable taxa recorded were detected with eDNA. Of the 217 eDNA records of 47 plant taxa in the 11 lakes, 73% and 12% matched taxa recorded in vegetation surveys within 2 m and up to about 50 m away from the lakeshore, respectively, whereas 16% were not recorded in the vegetation surveys of the same lake. The latter include taxa likely overlooked in the vegetation surveys or growing outside the survey area. The percentages detected were 61, 47, 25, and 15 for dominant, common, scattered, and rare taxa, respectively. Similar numbers for aquatic plants were 88, 88, 33 and 62%, respectively. Detection rate and taxonomic resolution varied among plant families and functional groups with good detection of e.g. Ericaceae, Roseaceae, deciduous trees, ferns, club mosses and aquatics. The representation of terrestrial taxa in eDNA depends on both their distance from the sampling site and their abundance and is sufficient for recording vegetation types. For aquatic vegetation, eDNA may be comparable with, or even superior to, in-lake vegetation surveys and may therefore be used as an tool for biomonitoring. For reconstruction of terrestrial vegetation, technical improvements and more intensive sampling is needed to detect a higher proportion of rare taxa although DNA of some taxa may never reach the lake sediments due to taphonomical constrains. Nevertheless, eDNA performs similar to conventional methods of pollen and macrofossil analyses and may therefore be an important tool for reconstruction of past vegetation.

© 2017, Public Library of Science. All rights reserved. This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Introduction: Biological particles deposit on air handling system filters as they process air. This study reports and interprets abundance and diversity information regarding biomass accumulation on ordinarily used filters acquired from several locations in a university environment. Methods: DNA-based analysis was applied both to quantify (via DNA fluorometry and qPCR) and to characterize (via high-throughput sequencing) the microbial material on filters, which mainly processed recirculated indoor air. Results were interpreted in relation to building occupancy and ventilation system operational parameters. Results: Based on accumulated biomass, average DNA concentrations per AHU filter surface area across nine indoor locations after twelve weeks of filter use were in the respective ranges 1.1 to 41 ng per cm2 for total DNA, 0.02 to 3.3 ng per cm2 for bacterial DNA and 0.2 to 2.0 ng DNA per cm2 for fungal DNA. The most abundant genera detected on the AHU filter samples were Clostridium, Streptophyta, Bacillus, Acinetobacter and Ktedonobacter for bacteria and Aspergillus, Cladosporium, Nigrospora, Rigidoporus and Lentinus for fungi. Conditional indoor airborne DNA concentrations (median (range)) were estimated to be 13 (2.6–107) pg/m3 for total DNA, 0.4 (0.05–8.4) pg/m3 for bacterial DNA and 2.3 (1.0–5.1) pg/m3 for fungal DNA. Conclusion: Conditional airborne concentrations and the relative abundances of selected groups of genera correlate well with occupancy level. Bacterial DNA was found to be more responsive than fungal DNA to differences in occupancy level and indoor environmental conditions.

Environmental DNA (eDNA) has recently been used for detecting the distribution of macroor-ganisms in various aquatic habitats. In this study, we applied an eDNA method to estimate the distribution of the Japanese clawed salamander, Onychodactylus japonicus, in headwater streams. Additionally, we compared the detection of eDNA and hand-capturing methods used for determining the distribution of O. japonicus. For eDNA detection, we designed a qPCR primer/probe set for O. japonicus using the 12S rRNA region. We detected the eDNA of O. japonicus at all sites (with the exception of one), where we also observed them by hand-capturing. Additionally, we detected eDNA at two sites where we were unable to observe individuals using the hand-capturing method. Moreover, we found that eDNA concentrations and detection rates of the two water sampling areas (stream surface and under stones) were not significantly different, although the eDNA concentration in the water under stones was more varied than that on the surface. We, therefore, conclude that eDNA methods could be used to determine the distribution of macroorganisms inhabiting headwater systems by using samples collected from the surface of the water.

Bog turtles (Glyptemys muhlenbergii) are listed as Species of Greatest Conservation Need (SGCN) for wildlife action plans in every state it occurs and multi-state efforts are underway to better characterize extant populations and prioritize restoration efforts. However, traditional sampling methods can be ineffective due to the turtle's wetland habitat, small size, and burrowing nature. Molecular methods, such as qPCR, provide the ability to overcome this challenge by effectively quantifying minute amounts of turtle DNA left behind in its environment (eDNA). Developing such methods for bog turtles has proved difficult partly because of the high sequence similarity between bog turtles and closely-related, cohabitating species, most often wood turtles (Glyptemys insculpta). Additionally, substrates containing bog turtle eDNA are often rich in organics or other substances that frequently inhibit both DNA extraction and qPCR amplification. Here, we describe the development and validation of a qPCR assay, BT3, targeting the mitochondrial cytochrome oxidase I gene that correctly identifies bog turtles with 100% specificity and sensitivity when tested on 201 blood samples collected from six species over a wide geographic range. We also developed a full-process internal control employing a genetically modified strain of Caenorhabditis elegans to improve DNA extraction methods, limit false negative results due to qPCR inhibition, and measure total DNA recovery from each sample. Using the internal control, we found that DNA recovery varied by over an order of magnitude between samples and likely explains the lack of bog turtle detection in some cases. Methods presented herein are highly-specific and may offer a more cost effective, non-invasive tool to supplement bog turtle population assessments in the Eastern United States. Poor or differential DNA recovery, which remains unmeasured in the vast majority of eDNA studies, significantly reduced the ability to detect bog turtle in their natural environment.

Multiscale signal processing techniques such as wavelet filtering have proved to be particularly successful in predicting exon sequences. Traditional wavelet predictor is domain filtering, and enforces exon features by weighting nucleotide values with coefficients. Such a measure performs linear filtering and is not suitable for preserving the short coding exons and the exon-intron boundaries. This paper describes a prediction framework that is capable of non-linearly processing DNA sequences while achieving high prediction rates. There are two key contributions. The first is the introduction of a genomic-inspired multiscale bilateral filtering (MSBF) which exploits both weighting coefficients in the spatial domain and nucleotide similarity in the range. Similarly to wavelet transform, the MSBF is also defined as a weighted sum of nucleotides. The difference is that the MSBF takes into account the variation of nucleotides at a specific codon position. The second contribution is the exploitation of inter-scale correlation in MSBF domain to find the inter-scale dependency on the differences between the exon signal and the background noise. This favourite property is used to sharp the important structures while weakening noise. Three benchmark data sets have been used in the evaluation of considered methods. By comparison with four existing techniques, the prediction results demonstrate that: the proposed method reveals at least improvement of 4.1%, 50.5%, 25.6%, 2.5%, 10.8%, 15.5%, 11.1%, 12.3%, 9.2% and 2.4% on the exons length of 1–24, 25–49, 50–74, 75–99, 100–124, 125–149, 150–174, 175–199, 200–299 and 300–300+, respectively. The MSBF of its nonlinear nature is good at energy compaction, which makes it capable of locating the sharp variations around short exons. The direct scale multiplication of coefficients at several adjacent scales obviously enhanced exon features while the noise contents were suppressed. We show that the non-linear nature and correlation-based property achieved in proposed predictor is greater than that for traditional filtering, which leads to better exon prediction performance. There are some possible applications of this predictor. Its good localization and protection of sharp variations will make the predictor be suitable to perform fault diagnosis of aero-engine.

Environmental DNA (eDNA) techniques have only recently been applied in the marine environment to detect the presence of marine species. Species-specific primers and probes were designed to detect the eDNA of the endangered Maugean skate (Zearaja maugeana) from as little as 1 L of water collected at depth (10-15 m) in Macquarie Harbour (MH), Tasmania. The identity of the eDNA was confirmed as Z. maugeana by sequencing the qPCR products and aligning these with the target sequence for a 100% match. This result has validated the use of this eDNA technique for detecting a rare species, Z. maugeana, in the wild. Being able to investigate the presence, and possibly the abundance, of Z. maugeana in MH and Bathurst harbour (BH), would be addressing a conservation imperative for the endangered Z. maugeana. For future application of this technique in the field, the rate of decay was determined for Z. maugeana eDNA under ambient dissolved oxygen (DO) levels (55% saturation) and lower DO (20% saturation) levels, revealing that the eDNA can be detected for 4 and 16 hours respectively, after which eDNA concentration drops below the detection threshold of the assay. With the rate of decay being influenced by starting eDNA concentrations, it is recommended that samples be filtered as soon as possible after collection to minimize further loss of eDNA prior to and during sample processing.

Background A simple and reliable DNA extraction of hepatitis B virus (HBV) is critical in developing an ultrasensitive detection method for HBV infection. Current commercially available serum Hepatitis B Virus (HBV) DNA extraction methods are time-consuming, expensive and/or require specialized equipment, which hinders wide adoption of clinical laboratories. This study offers a report on an ultrasensitive HBV DNA detection method by coupling serum HBV DNA extraction by ultrafiltration (UF) with real-time PCR (qPCR) detection. Methods Serum proteins were precipitated by phenol to release HBV DNA in the supernatant which was then transferred to the UF devices. The resultant DNA concentrate was eluted and released into qPCR pre-mixture. The UF-qPCR assay performance, including recovery rate, linearity, detection sensitivity, precision and diagnostic accuracy that compared to the CAP-CTM V2.0 assay by analyzing batched low viral load clinical samples was evaluated. Results The recovery rate of the UF-based HBV DNA extraction method was above 80%. The assay linearity was demonstrated with a slope of 0.95 and R2 values of 0.99. Limit-of-detection (LOD) of the UF-qPCR assay was determined to be 12.1IU/ml. The coefficient of variation (CV) of HBV quantitation for high, low and limit titer samples was 2.28%, 5.77% and 25.59%, respectively. Accuracy of the UF-qPCR assay was confirmed with the reference panel, and there was a strong correlation between these two methods (R2 = 0.55, p < 0.01). Conclusions The UF-qPCR assay is reliable, highly sensitive, affordable and time-saving, and the method can be used for ultrasensitive detection of serum HBV.

Environmental stewardship requires timely, accurate information related to the status of a given ecosystem and the species that occupy it. Recent advances in the application of the highly sensitive real-time quantitative polymerase chain reaction (qPCR) towards identification of constituents within environmental DNA (eDNA) now allow targeted detection of the presence of species-specific biological material within a localized geographic region. However, as with all molecular techniques predicated on the specificity and sensitivity of the PCR assay, careful validation of each eDNA qPCR assay in development must be performed both under controlled laboratory conditions and when challenged with field-derived eDNA samples. Such a step-wise approach forms the basis for incorporation of innovative qPCR design features that strengthen the implementation and interpretation of the eDNA assay. This includes empirical determination that the qPCR assay is refractory to the presence of human DNA and the use of a tripartite assay approach comprised of 1) a primer set targeting plant chloroplast that evaluates the presence of amplifiable DNA from field samples to increase confidence in a negative result, 2) an animal group primer set to increase confidence in the assay result, and 3) a species-specific primer set to assess presence of DNA from the target species. To demonstrate this methodology, we generated eDNA assays specific for the North American bullfrog (Lithobates (Rana) catesbeiana) and the Rocky Mountain tailed frog (Ascaphus montanus) and characterized each with respect to detection sensitivity and specificity with demonstrated performance in a field survey scenario. The qPCR design features presented herein address specific challenges of eDNA assays thereby increasing their interpretative power.

Understanding the cell-specific binding patterns of transcription factors (TFs) is fundamental to studying gene regulatory networks in biological systems, for which ChIP-seq not only provides valuable data but is also considered as the gold standard. Despite tremendous efforts from the scientific community to conduct TF ChIP-seq experiments, the available data represent only a limited percentage of ChIP-seq experiments, considering all possible combinations of TFs and cell lines. In this study, we demonstrate a method for accurately predicting cell-specific TF binding for TF-cell line combinations based on only a small fraction (4%) of the combinations using available ChIP-seq data. The proposed model, termed TFImpute, is based on a deep neural network with a multi-task learning setting to borrow information across transcription factors and cell lines. Compared with existing methods, TFImpute achieves comparable accuracy on TF-cell line combinations with ChIP-seq data; moreover, TFImpute achieves better accuracy on TF-cell line combinations without ChIP-seq data. This approach can predict cell line specific enhancer activities in K562 and HepG2 cell lines, as measured by massively parallel reporter assays, and predicts the impact of SNPs on TF binding., Author summary Transcription factors play a central role in regulating various cellular processes. They bind to DNA in a cell-specific way. To study where a TF would bind to DNA, ChIP-seq experiment has been developed and widely adopted by the science community to study genome-wide in vivo protein-DNA interactions. However, for each TF, only a limited number of cell types have been explored by ChIP-seq experiments. To study the binding of a TF to a DNA sequence in a cell line without corresponding ChIP-seq data, researchers would check whether there is a motif for the TF in the sequence. However, motif alone contains only sequence information and therefore cannot reflect the cell specificity of TF binding. In this work, we demonstrate how to model the TF binding problem using deep learning and achieve cell specific binding prediction for TF-cell line combinations without ChIP-seq data.

Homologous recombination in the genetic transformation model organism Streptococcus pneumoniae is thought to be important in the adaptation and evolution of this pathogen. While competent pneumococci are able to scavenge DNA added to laboratory cultures, large-scale transfers of multiple kb are rare under these conditions. We used whole genome sequencing (WGS) to map transfers in recombinants arising from contact of competent cells with non-competent ‘target’ cells, using strains with known genomes, distinguished by a total of ~16,000 SNPs. Experiments designed to explore the effect of environment on large scale recombination events used saturating purified donor DNA, short-term cell assemblages on Millipore filters, and mature biofilm mixed cultures. WGS of 22 recombinants for each environment mapped all SNPs that were identical between the recombinant and the donor but not the recipient. The mean recombination event size was found to be significantly larger in cell-to-cell contact cultures (4051 bp in filter assemblage and 3938 bp in biofilm co-culture versus 1815 bp with saturating DNA). Up to 5.8% of the genome was transferred, through 20 recombination events, to a single recipient, with the largest single event incorporating 29,971 bp. We also found that some recombination events are clustered, that these clusters are more likely to occur in cell-to-cell contact environments, and that they cause significantly increased linkage of genes as far apart as 60,000 bp. We conclude that pneumococcal evolution through homologous recombination is more likely to occur on a larger scale in environments that permit cell-to-cell contact., Author summary Bacteria shuffle their genes far less often than humans do and genes or traits are more directly linked with the singular bacterial parent cell rather than the two parents that are involved in sexual reproduction. However, bacteria do occasionally have sex in the form of homologous recombination by taking up external DNA and incorporating it into their genomes. This happens far less regularly than sexual reproduction happens in human generations but is a known way that bacteria undergo ‘Horizontal gene transfer’. This means that genes can be acquired without being inherited. In this study we show that this form of horizontal gene transfer is more likely to happen in certain environments over others in Streptococcus pneumoniae. In particular, we show that this is more likely to happen in environments that closely mirror the nasopharynx which is the natural habitat of S. pneumoniae.

Genotyping-by-sequencing (GBS) was conducted on 333 Cercospora isolates collected from Beta vulgaris (sugar beet, table beet and swiss chard) in the USA and Europe. Cercospora beticola was confirmed as the species predominantly isolated from leaves with Cercospora leaf spot (CLS) symptoms. However, C. cf. flagellaris also was detected at a frequency of 3% in two table beet fields in New York. Resolution of the spatial structure and identification of clonal lineages in C. beticola populations using genome-wide single nucleotide polymorphisms (SNPs) obtained from GBS was compared to genotyping using microsatellites. Varying distance thresholds (bitwise distance = 0, 1.854599 × 10-4, and 1.298 × 10-3) were used for delineation of clonal lineages in C. beticola populations. Results supported previous reports of long distance dispersal of C. beticola through genotype flow. The GBS-SNP data set provided higher resolution in discriminating clonal lineages; however, genotype identification was impacted by filtering parameters and the distance threshold at which the multi-locus genotypes (MLGs) were contracted to multi-locus lineages. The type of marker or different filtering strategies did not impact estimates of population differentiation and structure. Results emphasize the importance of robust filtering strategies and designation of distance thresholds for delineating clonal lineages in population genomics analyses that depend on individual assignment and identification of clonal lineages. Detection of recurrent clonal lineages shared between the USA and Europe, even in the relaxed-filtered SNP data set and with a conservative distance threshold for contraction of MLGs, provided strong evidence for global genotype flow in C. beticola populations. The implications of intercontinental migration in C. beticola populations for CLS management are discussed.

For several hundred years freshwater crayfish (Crustacea-Decapoda-Astacidea) have played an important ecological, cultural and culinary role in Scandinavia. However, many native populations of noble crayfish Astacus astacus have faced major declines during the last century, largely resulting from human assisted expansion of non-indigenous signal crayfish Pacifastacus leniusculus that carry and transmit the crayfish plague pathogen. In Denmark, also the non-indigenous narrow-clawed crayfish Astacus leptodactylus has expanded due to anthropogenic activities. Knowledge about crayfish distribution and early detection of non-indigenous and invasive species are crucial elements in successful conservation of indigenous crayfish. The use of environmental DNA (eDNA) extracted from water samples is a promising new tool for early and non-invasive detection of species in aquatic environments. In the present study, we have developed and tested quantitative PCR (qPCR) assays for species-specific detection and quantification of the three above mentioned crayfish species on the basis of mitochondrial cytochrome oxidase 1 (mtDNA-CO1), including separate assays for two clades of A. leptodactylus. The limit of detection (LOD) was experimentally established as 5 copies/PCR with two different approaches, and the limit of quantification (LOQ) were determined to 5 and 10 copies/PCR, respectively, depending on chosen approach. The assays detected crayfish in natural freshwater ecosystems with known populations of all three species, and show promising potentials for future monitoring of A. astacus, P. leniusculus and A. leptodactylus. However, the assays need further validation with data 1) comparing traditional and eDNA based estimates of abundance, and 2) representing a broader geographical range for the involved crayfish species.

Determining the success of invasive species eradication efforts is challenging because populations at very low abundance are difficult to detect. Environmental DNA (eDNA) sampling has recently emerged as a powerful tool for detecting rare aquatic animals; however, detectable fragments of DNA can persist over time despite absence of the targeted taxa and can therefore complicate eDNA sampling after an eradication event. This complication is a large concern for fish eradication efforts in lakes since killed fish can sink to the bottom and slowly decay. DNA released from these carcasses may remain detectable for long periods. Here, we evaluated the efficacy of eDNA sampling to detect invasive Northern pike (Esox lucius) following piscicide eradication efforts in southcentral Alaskan lakes. We used field observations and experiments to test the sensitivity of our Northern pike eDNA assay and to evaluate the persistence of detectable DNA emitted from Northern pike carcasses. We then used eDNA sampling and traditional sampling (i.e., gillnets) to test for presence of Northern pike in four lakes subjected to a piscicide-treatment designed to eradicate this species. We found that our assay could detect an abundant, free-roaming population of Northern pike and could also detect low-densities of Northern pike held in cages. For these caged Northern pike, probability of detection decreased with distance from the cage. We then stocked three lakes with Northern pike carcasses and collected eDNA samples 7, 35 and 70 days post-stocking. We detected DNA at 7 and 35 days, but not at 70 days. Finally, we collected eDNA samples ~ 230 days after four lakes were subjected to piscicide-treatments and detected Northern pike DNA in 3 of 179 samples, with a single detection at each of three lakes, though we did not catch any Northern pike in gillnets. Taken together, we found that eDNA can help to inform eradication efforts if used in conjunction with multiple lines of inquiry and sampling is delayed long enough to allow full degradation of DNA in the water.

We describe the sampling of sixty-three uncultured hospital air samples collected over a six-month period and analysis using shotgun metagenomic sequencing. Our primary goals were to determine the longitudinal metagenomic variability of this environment, identify and characterize genomes of potential pathogens and determine whether they are atypical to the hospital airborne metagenome. Air samples were collected from eight locations which included patient wards, the main lobby and outside. The resulting DNA libraries produced 972 million sequences representing 51 gigabases. Hierarchical clustering of samples by the most abundant 50 microbial orders generated three major nodes which primarily clustered by type of location. Because the indoor locations were longitudinally consistent, episodic relative increases in microbial genomic signatures related to the opportunistic pathogens Aspergillus, Penicillium and Stenotrophomonas were identified as outliers at specific locations. Further analysis of microbial reads specific for Stenotrophomonas maltophilia indicated homology to a sequenced multi-drug resistant clinical strain and we observed broad sequence coverage of resistance genes. We demonstrate that a shotgun metagenomic sequencing approach can be used to characterize the resistance determinants of pathogen genomes that are uncharacteristic for an otherwise consistent hospital air microbial metagenomic profile.

RNA editing is one of the post- or co-transcriptional processes that can lead to amino acid substitutions in protein sequences, alternative pre-mRNA splicing, and changes in gene expression levels. Although several methods have been suggested to identify RNA editing sites, there remains challenges to be addressed in distinguishing true RNA editing sites from its counterparts on genome and technical artifacts. In addition, there lacks a software framework to identify and visualize potential RNA editing sites. Here, we presented a software − ‘RED’ (RNA Editing sites Detector) − for the identification of RNA editing sites by integrating multiple rule-based and statistical filters. The potential RNA editing sites can be visualized at the genome and the site levels by graphical user interface (GUI). To improve performance, we used MySQL database management system (DBMS) for high-throughput data storage and query. We demonstrated the validity and utility of RED by identifying the presence and absence of C→U RNA-editing sites experimentally validated, in comparison with REDItools, a command line tool to perform high-throughput investigation of RNA editing. In an analysis of a sample data-set with 28 experimentally validated C→U RNA editing sites, RED had sensitivity and specificity of 0.64 and 0.5. In comparison, REDItools had a better sensitivity (0.75) but similar specificity (0.5). RED is an easy-to-use, platform-independent Java-based software, and can be applied to RNA-seq data without or with DNA sequencing data. The package is freely available under the GPLv3 license at http://github.com/REDetector/RED or https://sourceforge.net/projects/redetector.