Biology subjects

Hajibabaei, M.

Publications and source records attributed to Hajibabaei, M..

27 records · Page 2Linked to original sources

bioRxiv2019

Variations in terrestrial arthropod DNA metabarcoding methods recovers robust beta diversity but variable richness and site indicators based on exact sequence variants

Terrestrial arthropod fauna have been suggested as a key indicator of ecological integrity in forest systems. Because phenotypic identification is expert-limited, a shift towards DNA metabarcoding could improve scalability and democratize the use of forest floor arthropods for biomonitoring applications. The objective of this study was to establish the level of field sampling and DNA extraction replication needed for soil arthropod biodiversity assessments. Processing individually collected field samples recovered significantly higher richness (539-596 ESVs) than pooling the same number of field samples (126-154 ESVs), and we found no significant richness differences when using 1 or 3 pooled DNA extractions. Variations in the number of individual or composite samples or DNA extractions resulted in similar sample clustering based on community dissimilarities. Though our ability to identify taxa to species rank was limited, we were able to use arthropod COI metabarcodes from forest soil to assess richness, distinguish among sites, and recover site indicators based on unnamed exact sequence variants. Our results highlight the need to continue DNA barcoding of local taxa during COI metabarcoding studies to help build reference databases. All together, these sampling considerations support the use of soil arthropod COI metabarcoding as a scalable method for biomonitoring.

ecology↗

bioRxiv2019

Studying ecosystems with DNA metabarcoding: lessons from aquatic biomonitoring

An ongoing challenge for ecological studies has been the collection of data with high precision and accuracy at a sufficient scale to detect effects relevant to management of critical global change processes. A major hurdle for many workflows has been the time-consuming and challenging process of sorting and identification of organisms, but the rapid development of DNA metabarcoding as a biodiversity observation tool provides a potential solution. As high-throughput sequencing becomes more rapid and cost-effective, a big data revolution is anticipated, based on higher and more accurate taxonomic resolution, more efficient detection, and greater sample processing capacity. These advances have the potential to amplify the power of ecological studies to detect change and diagnose its cause, through a methodology termed Biomonitoring 2.0.\n\nDespite its promise, the unfamiliar terminology and pace of development in high-throughput sequencing technologies has contributed to a growing concern that an unproven technology is supplanting tried and tested approaches, lowering trust among potential users, and reducing uptake by ecologists and environmental management practitioners. While it is reasonable to exercise caution, we argue that any criticism of new methods must also acknowledge the shortcomings and lower capacity of current observation methods. Broader understanding of the statistical properties of metabarcoding data will help ecologists to design, test and review evidence for new hypotheses.\n\nWe highlight the uncertainties and challenges underlying DNA metabarcoding and traditional methods for compositional analysis, focusing on issues of taxonomic resolution, sample similarity, taxon misidentification, sample contamination, and taxon abundance. Using the example of freshwater benthic ecosystems, one of the most widely-applied non-microbial applications of DNA metabarcoding to date, we explore the ability of this new technology to improve the quality and utility of ecological data, recognising that the issues raised have widespread applicability across all ecosystem types.

ecology↗

bioRxiv2019

Watered-down biodiversity? A comparison of metabarcoding results from DNA extracted from matched water and bulk tissue biomonitoring samples

Biomonitoring programs have evolved beyond the sole use of morphological identification to determine the composition of invertebrate species assemblages in an array of ecosystems. The application of DNA metabarcoding in freshwater systems for assessing benthic invertebrate communities is now being employed to generate biological information for environmental monitoring and assessment. A possible shift from the extraction of DNA from net-collected bulk benthic samples to its extraction directly from water samples for metabarcoding has generated considerable interest based on the assumption that taxon detectability is comparable when using either method. To test this, we studied paired water and benthos samples from a taxon-rich wetland complex, to investigate differences in the detection of taxa from each sample type. We demonstrate that metabarcoding of DNA extracted directly from water samples is a poor surrogate for DNA extracted from bulk benthic samples, focusing on key bioindicator groups. Our results continue to support the use of bulk benthic samples as a basis for metabarcoding-based biomonitoring, with nearly three times greater total richness in benthic samples compared to water samples. We also demonstrated that few arthropod taxa are shared between collection methods, with a notable lack of key bioindicator EPTO taxa in the water samples. Although species coverage in water could likely be improved through increased sample replication and/or increased sequencing depth, benthic samples remain the most representative, cost-effective method of generating aquatic compositional information via metabarcoding.

ecology↗

bioRxiv2019

COI metabarcoding primer choice affects richness and recovery of indicator taxa in freshwater systems

DNA-based biodiversity analysis has gained major attention due to the use of high throughput sequencing technology in approaches such as mixed community or environmental DNA metabarcoding. Many cytochrome c oxidase subunit I (COI) primer sets are now available for such work. The purpose of this study is to look at how COI primer choice affects the recovery of arthropod richness, beta diversity, and recovery of site indicator taxa in benthos kick-net samples typically used in freshwater biomonitoring. We examine 6 commonly used COI primer sets, on samples collected from 6 freshwater sites. Richness is sensitive to primer choice and the combined use of additional multiple COI amplicons recovers higher richness. Thus, to recover maximum richness, multiple primer sets should be used with COI metabarcoding. Samples consistently cluster by site regardless of amplicon choice or PCR replicate. Thus, for broadscale community analyses, overall beta diversity patterns are robust to COI marker choice. Additionally, the recovery of traditional freshwater bioindicator assemblages such as Ephemeroptera, Trichoptera, Plectoptera, and Diptera may not fully capture the diversity of broadscale arthropod site indicators that can be recovered from COI metabarcoding. Based on these results, studies that use different COI amplicons may not be directly comparable. This work will help future biodiversity and biomonitoring studies develop not just standardized, but optimized workflows that maximize taxon-detection or order taxa along gradients.

genomics↗

bioRxiv2019

Comprehensive biodiversity analysis via ultra-deep patterned flow cell technology: a case study of eDNA metabarcoding seawater

1The characterization of biodiversity is a crucial element of ecological investigations as well as environmental assessment and monitoring activities. Increasingly, amplicon-based environmental DNA metabarcoding (alternatively, marker gene metagenomics) is used for such studies given its ability to provide biodiversity data from various groups of organisms simply from analysis of bulk environmental samples such as water, soil or sediments. The Illumina MiSeq is currently the most popular tool for carrying out this work, but we set out to determine whether typical studies were reading enough DNA to detect rare organisms (i.e., those that may be of greatest interest such as endangered or invasive species) present in the environment. We collected sea water samples along two transects in Conception Bay, Newfoundland and analyzed them on the MiSeq with a sequencing depth of 100,000 reads per sample (exceeding the 60,000 per sample that is typical of similar studies). We then analyzed these same samples on Illuminas newest high-capacity platform, the NovaSeq, at a depth of 7 million reads per sample. Not surprisingly, the NovaSeq detected many more taxa than the MiSeq thanks to its much greater sequencing depth. However, contrary to our expectations this pattern was true even in depth-for-depth comparisons. In other words, the NovaSeq can detect more DNA sequence diversity within samples than the MiSeq, even at the exact same sequencing depth. Even when samples were reanalyzed on the MiSeq with a sequencing depth of 1 million reads each, the MiSeqs ability to detect new sequences plateaued while the NovaSeq continued to detect new sequence variants. These results have important biological implications. The NovaSeq found 40% more metazoan families in this environment than the MiSeq, including some of interest such as marine mammals and bony fish so the real-world implications of these findings are significant. These results are most likely associated to the advances incorporated in NovaSeq especially patterned flow cell, which prevents similar sequences that are neighbours on the flow cell (common in metabarcoding studies) from being erroneously merged into single spots by the sequencing instrument. This study sets the stage for incorporating eDNA metabarcoding in comprehensive analysis of oceanic samples in a wide range of ecological and environmental investigations.

genomics↗

bioRxiv2018

Over 2.5 million COI sequences in GenBank and growing

The increasing popularity of cytochrome c oxidase subunit 1 (COI) DNA metabarcoding warrants a careful look at the underlying reference databases used to make high-throughput taxonomic assignments. The objectives of this study are to document trends and assess the future usability of COI records for metabarcode identification. Over 2.5 million COI sequences were found in GenBank, half of which were fully identified to the species rank. From 2003 to 2017, the number of COI Eukaryote records deposited has grown by two orders of magnitude representing a nearly 42-fold increase in unique species. For fully identified records, 92% are at least 500 bp in length, 74% have a country annotation, and 51% have latitude-longitude annotations. To ensure the future usability of COI records in GenBank we suggest: 1) Improving the geographic representation of COI records 2) Improving the cross-referencing of COI records in the Barcode of Life Data System and GenBank to facilitate consolidation and incorporation into existing bioinformatic pipelines, 3) Adherence to the minimum information about a marker gene sequence guidelines, and 4) Integrating metabarcodes from eDNA and mixed community studies with existing sequences. COI metabarcoders are normally considered consumers of taxonomic data. Here we discuss the potential for taxonomists to reverse this pattern and instead mine metabarcode data to guide species discovery. The growth of COI reference records over the past 15 years has been substantial and is likely to be a resource across many fields for years to come.

ecology↗

bioRxiv2017

Automated high throughput animal DNA metabarcode classification

Until now, there has been difficulty assigning names to animal barcode sequences isolated directly from eDNA in a rapid, high-throughput manner, providing a measure of confidence for each assignment. To address this gap, we have compiled nearly 1 million marker gene DNA barcode sequences appropriate for classifying chordates, arthropods, and flag members of other major eukaryote groups. We show that the RDP naive Bayesian classifier can assign the same number of queries 19 times faster than the popular BLAST top hit method and reduce the false positive rate by two-thirds. As reference databases become more representative of current species diversity, confidence in taxonomic assignments should continue to improve. We recommend that investigators can improve the performance of species-level assignments immediately by supplementing existing reference databases with full-length DNA barcode sequences from representatives of local fauna.

bioinformatics↗

bioRxiv2017

DNA Metabarcoding For High-Throughput Monitoring Of Estuarine Macrobenthic Communities

Benthic communities are key components of aquatic ecosystems biomonitoring. However, morphology-based species identifications remain a low-throughput, and sometimes ambiguous, approach. Despite metabarcoding methodologies have been applied for above-species taxa inventories in marine meiofaunal communities, a comprehensive approach providing species-level identifications for estuarine macrobenthic communities is still lacking. Here we report a combination of experimental and field studies demonstrating the aptitude of COI metabarcoding to provide robust species-level identifications within a framework of high-throughput monitoring of estuarine macrobenthic communities. To investigate the ability to recover DNA barcodes from all species present in a bulk DNA extract, we assembled 3 phylogenetically diverse communities, using 4 different primer pairs to generate PCR products of the COI barcode region. Between 78 and 83% of the species in the tested communities were recovered through HTS. Subsequently, we compared morphology and metabarcoding-based approaches to determine the species composition from four distinct sites of an estuary. Our results indicate that the species richness would be considerably underestimated if only morphological methods were used. Although further refinement is required for improving the efficiency and output of this approach, here we show the great aptitude of COI metabarcoding to provide high quality and auditable species identifications in macrobenthos monitoring.

genetics↗

bioRxiv2016

Environmental DNA Barcode Sequence Capture: Targeted, PCR-free Sequence Capture for Biodiversity Analysis from Bulk Environmental Samples

Environmental DNA analysis using PCR amplified marker genes has been a key application of high-throughput sequencing (HTS). However, PCR bias is a major drawback to gain accurate qualitative and quantitative biodiversity data. We developed a PCR-free approach using enrichment baits for species-specific mitochondrial cytochrome c oxidase 1(COI) DNA barcodes. The sequence capture was tested on species-rich bulk terrestrial and aquatic benthic samples. Hybridization capture recovered an average of 6 and 4.7 more arthropod orders than amplicon sequencing for terrestrial and benthic samples, respectively. For the terrestrial sample, the four most abundant arthropod orders comprised 94.0% of the sample biomass. These same four orders comprised 95.5% and 97.5% of the COI sequences recovered by amplification and capture, respectively. Hybridization capture recovered three arthropod orders that were detected by biomass analysis, but not by amplicon sequencing and two other insect orders that were not detected by either biomass or amplicon methods. These results indicate the advantage of using sequence capture for a more accurate analysis of biodiversity in bulk environmental samples. The protocol can be easily customized to other DNA barcode markers or gene regions of interest for a wide range of taxa or for a specific target group.

genomics↗