Dorota L. Porazinska

Bio: Dorota L. Porazinska is an academic researcher from University of Florida. The author has contributed to research in topics: Cryoconite & Ecosystem. The author has an hindex of 26, co-authored 61 publications receiving 3225 citations. Previous affiliations of Dorota L. Porazinska include Colorado State University & University of Colorado Boulder.

Sequencing our way towards understanding global eukaryotic biodiversity

Abstract: Microscopic eukaryotes are abundant, diverse and fill critical ecological roles across every ecosystem on Earth, yet there is a well-recognized gap in understanding of their global biodiversity. Fundamental advances in DNA sequencing and bioinformatics now allow accurate en masse biodiversity assessments of microscopic eukaryotes from environmental samples. Despite a promising outlook, the field of eukaryotic marker gene surveys faces significant challenges: how to generate data that are most useful to the community, especially in the face of evolving sequencing technologies and bioinformatics pipelines, and how to incorporate an expanding number of target genes.

Ultrasequencing of the meiofaunal biosphere: practice, pitfalls and promises.

Abstract: Biodiversity assessment is the key to understanding the relationship between biodiversity and ecosystem functioning, but there is a well-acknowledged biodiversity identification gap related to eukaryotic meiofaunal organisms. Meiofaunal identification is confounded by the small size of taxa, morphological convergence and intraspecific variation. However, the most important restricting factor in meiofaunal ecological research is the mismatch between diversity and the number of taxonomists that are able to simultaneously identify and catalogue meiofaunal diversity. Accordingly, a molecular operational taxonomic unit (MOTU)-based approach has been advocated for en mass meiofaunal biodiversity assessment, but it has been restricted by the lack of throughput afforded by chain termination sequencing. Contemporary pyrosequencing offers a solution to this problem in the form of environmental metagenetic analyses, but this represents a novel field of biodiversity assessment. Here, we provide an overview of meiofaunal metagenetic analyses, ranging from sample preservation and DNA extraction to PCR, sequencing and the bioinformatic interrogation of multiple, independent samples using 454 Roche sequencing platforms. We report two examples of environmental metagenetic nuclear small subunit 18S (nSSU) analyses of marine and tropical rainforest habitats and provide critical appraisals of the level of putative recombinant DNA molecules (chimeras) in metagenetic data sets. Following stringent quality control measures, environmental metagenetic analyses achieve MOTU formation across the eukaryote domain of life at a fraction of the time and cost of traditional approaches. The effectiveness of Roche 454 sequencing brings substantial advantages to studies aiming to elucidate the molecular genetic richness of not only meiofaunal, but also all complex eukaryotic communities.

The ecologist's field guide to sequence‐based identification of biodiversity

Abstract: Summary The past 100 years of ecological research has seen substantial progress in understanding the natural world and likely effects of change, whether natural or anthropogenic. Traditional ecological approaches underpin such advances, but would additionally benefit from recent developments in the sequence-based quantification of biodiversity from the fields of molecular ecology and genomics. By building on a long and rich history of molecular taxonomy and taking advantage of the new generation of DNA sequencing technologies, we are gaining previously impossible insights into alpha and beta diversity from all domains of life, irrespective of body size. While a number of complementary reviews are available in specialist journals, our aim here is to succinctly describe the different technologies available within the omics toolbox and showcase the opportunities available to contemporary ecologists to advance our understanding of biodiversity and its potential roles in ecosystems. Starting in the field, we walk the reader through sampling and preservation of genomic material, including typical taxonomy marker genes used for species identification. Moving on to the laboratory, we cover nucleic acid extraction approaches and highlight the principal features of using marker gene assessment, metagenomics, metatranscriptomics, single-cell genomics and targeted genome sequencing as complementary approaches to assess the taxonomic and functional characteristics of biodiversity. We additionally provide clear guidance on the forms of DNA found in the environmental samples (e.g. environmental vs. ancient DNA) and highlight a selection of case studies, including the investigation of trophic relationships/food webs. Given the maturity of sequence-based identification of prokaryotes and microbial eukaryotes, more exposure is given to macrobial communities. We additionally illustrate current approaches to genomic data analysis and highlight the exciting prospects of the publicly available data underpinning published sequence-based studies. Given that ecology ‘has to count’, we identify the impact that molecular genetic analyses have had on stakeholders and end-users and predict future developments for the fields of biomonitoring. Furthermore, we conclude by highlighting future opportunities in the field of systems ecology afforded by effective engagement between the fields of traditional and molecular ecology.

Relationships at the aboveground-belowground interface: plants, soil biota and soil processes

Abstract: Interactions at the aboveground-below ground interface provide important feedbacks that regulate ecosystem processes. Organisms within soil food webs are involved in processes of decomposition and nutrient mineralization, and their abundance and activity have been linked to plant ecophysiological traits such as species identity and the quality and quantity of plant tissue. We tested aboveground-below ground diversity relationships in a naturally developed plant community of native tallgrass prairie by taking soil samples from beneath naturally established grass tillers of chosen characteristics (e.g., homogeneous vs. heterogeneous plant combinations or C-4 vs. C-3 photosynthetic pathway) without imposing any disturbances to existing plant-soil relationships. The goal of this study was to elucidate the consequences, for soil microbiota (microflora phospholipid fatty acids, protozoa, and nematode functional groups) and for C and N mineralization, of plant community properties such as species richness, resource quality, resource heterogeneity, species identity, and presence of exotics. None of the biotic or abiotic soil variables was related to plant resource heterogeneity. Protozoa were not responsive to any of the plant community traits. Some bacterial and nematode groups were affected by plant characteristics specific to a particular plant species, but no uniform pattern emerged. Invasive and native plants generally were similar with respect to soil variables tested in this study. The lack of clear responses of soil variables to plant community traits indicates that idiosyncratic effects dominate both at the plant and soil biotic level and that generalized plant and soil diversity effects are hard to predict.

Evaluating high-throughput sequencing as a method for metagenomic analysis of nematode diversity

Abstract: Nematodes play an important role in ecosystem processes, yet the relevance of nematode species diversity to ecology is unknown. Because nematode identification of all individuals at the species level using standard techniques is difficult and time-consuming, nematode communities are not resolved down to the species level, leaving ecological analysis ambiguous. We assessed the suitability of massively parallel sequencing for analysis of nematode diversity from metagenomic samples. We set up four artificial metagenomic samples involving 41 diverse reference nematodes in known abundances. Two samples came from pooling polymerase chain reaction products amplified from single nematode species. Two additional metagenomic samples consisted of amplified products of DNA extracted from pooled nematode species. Amplified products involved two rapidly evolving ~400-bp sections coding for the small and large subunit of rRNA. The total number of reads ranged from 4159 to 14771 per metagenomic sample. Of these, 82% were > 199 bp in length. Among the reads > 199 bp, 86% matched the referenced species with less than three nucleotide differences from a reference sequence. Although neither rDNA section recovered all nematode species, the use of both loci improved the detection level of nematode species from 90 to 97%. Overall, results support the suitability of massively parallel sequencing for identification of nematodes. In contrast, the frequency of reads representing individual species did not correlate with the number of individuals in the metagenomic samples, suggesting that further methodological work is necessary before it will be justified for inferring the relative abundances of species within a nematode community.

The Theory of Island Biogeography

Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Ecological linkages between aboveground and belowground biota.

Abstract: All terrestrial ecosystems consist of aboveground and belowground components that interact to influence community- and ecosystem-level processes and properties. Here we show how these components are closely interlinked at the community level, reinforced by a greater degree of specificity between plants and soil organisms than has been previously supposed. As such, aboveground and belowground communities can be powerful mutual drivers, with both positive and negative feedbacks. A combined aboveground-belowground approach to community and ecosystem ecology is enhancing our understanding of the regulation and functional significance of biodiversity and of the environmental impacts of human-induced global change phenomena.

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

Abstract: Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

A general species delimitation method with applications to phylogenetic placements

Abstract: Motivation: Sequence-based methods to delimit species are central to DNA taxonomy, microbial community surveys and DNA metabarcoding studies. Current approaches either rely on simple sequence similarity thresholds (OTU-picking) or on complex and compute-intensive evolutionary models. The OTU-picking methods scale well on large datasets, but the results are highly sensitive to the similarity threshold. Coalescent-based species delimitation approaches often rely on Bayesian statistics and Markov Chain Monte Carlo sampling, and can therefore only be applied to small datasets. Results: We introduce the Poisson tree processes (PTP) model to infer putative species boundaries on a given phylogenetic input tree. We also integrate PTP with our evolutionary placement algorithm (EPA-PTP) to count the number of species in phylogenetic placements. We compare our approaches with popular OTU-picking methods and the General Mixed Yule Coalescent (GMYC) model. For de novo species delimitation, the stand-alone PTP model generally outperforms GYMC as well as OTU-picking methods when evolutionary distances between species are small. PTP neither requires an ultrametric input tree nor a sequence similarity threshold as input. In the open reference species delimitation approach, EPA-PTP yields more accurate results than de novo species delimitation methods. Finally, EPA-PTP scales on large datasets because it relies on the parallel implementations of the EPA and RAxML, thereby allowing to delimit species in high-throughput sequencing data. Availability and implementation: The code is freely available at www.