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Czech, L.

Publications and source records attributed to Czech, L..

17 recordsLinked to original sources

ybyra: Y-chromosome haplogroup calling using a tree-based scoring method

We present ybyra, a Snakemake workflow for automated Y-chromosome haplogroup assignment using a tree-based scoring method with robust and transparent heuristics. The pipeline supports both human reference genome builds 37 and 38, makes use of three different well-curated Y-SNP tree topologies and features an optional ancient DNA damage filter to accommodate low-coverage degraded samples. ybyra produces reproducible, scalable haplogroup calls with detailed scoring outputs to facilitate quality assessment and reporting. We further showcase its versatility by applying it to horse Y-chromosome data, highlighting its applicability beyond humans. Availabilityybyra is published under the MIT license and freely available at github.com/tpinotti/ybyra.

bioinformatics↗

Rapid adaptation and extinction across climates in synchronized outdoor evolution experiments of Arabidopsis thaliana

Climate change is threatening species with extinction, and rapid evolutionary adaptation may be their only option for population rescue over short ecological timescales. However, direct observations of rapid genetic adaptation and population dynamics across climates are rare across species. To fill this gap, we conducted a replicated, globally synchronized evolution experiment with the plant Arabidopsis thaliana for 5 years in over 30 outdoor experimental gardens with distinct climates across Europe, the Levant, and North America. We performed whole-genome sequencing on [~]70,000 surviving reproductive individuals and directly observed rapid and repeatable adaptation across climates. Allele frequency changes over time were parallel in experimental evolution replicates within the same climates, while they diverged across contrasting climates--with some allele frequency shifts best explained by strong selection between -46% to +60%. Screening the genome for signals of rapid climate adaptation identified a polygenic architecture with both known and novel adaptive genetic variants connected to important ecological phenotypes including environmental stress responses, CAM5 and HEAT SHOCK FACTORs, and germination and spring flowering timing, CYTOCHROME P450s and TSF. We found evolutionary adaptation trends were often predictable, but variable across environments. In warm climates, high evolutionary predictability was associated with population survival up to 5 years, while erratic trends were an early warning for population extinction. Together, these results show rapid climate adaptation may be possible, but understanding its limits across species will be key for biodiversity forecasting.

evolutionary biology↗

Population and adaptation history of 739 Thlaspi arvense natural accessions

Pennycress (Thlaspi arvense) is a promising intermediate oilseed crop, producing oil suitable for conversion to biofuels--including aviation fuels. While domestication efforts are ongoing, a deeper understanding of the genetic architecture of traits is crucial for informing future breeding efforts. Here, we conducted the largest genomic and phenotypic survey of pennycress to date, analyzing 739 accessions collected across four continents. Leveraging whole-genome sequencing and field-collected phenotypes, we characterized the standing genetic variation underlying key agronomic traits and climate resilience. Our findings revealed multiple independent migration events to North America, with substantial genetic admixture. We identified homologs of Arabidopsis thaliana flowering-time genes that contribute to adaptation and demonstrated the agronomic benefits of winter-type pennycress. Furthermore, through multi-season field trials, we identified a genomic region containing a cluster of mTERF genes strongly associated with green canopy coverage, a critical trait for biomass retention and yield stability. These insights provide a genomic roadmap for accelerating pennycress domestication and improving its resilience to climate variability.

genomics↗

Comparison of phylogenetic placements to pairwise alignments for taxonomic assignment of ciliate OTUs

Taxonomic assignment of OTUs is an important bioinformatics step in analyzing environmental sequencing data. Pairwise-alignment and phylogenetic-placement methods represent two alternative approaches to taxonomic assignments, but their results can differ. Here we used available colpodean ciliate OTUs from forest soils to compare the taxonomic assignments of VSEARCH (which performs pairwise alignments) and EPA-ng (which performs phylogenetic placements). We showed that when there are differences in taxonomic assignments between pairwise alignments and phylogenetic placements at the subtaxon level, there is a low pairwise similarity of the OTUs to the reference database. We then showcase how the output of EPA-ng can be further evaluated using GAPPA to assess the taxonomic assignments when there exist multiple equally likely placements of an OTU, by taking into account the sum over the likelihood weights of the OUT placements within a subtaxon, and the branch distances between equally likely placement locations. We also inferred evolutionary and ecological characteristics of the colpodean OTUs using their placements within subtaxa. This study demonstrates how to fully analyse the output of EPA-ng, by using GAPPA in conjunction with knowledge of the taxonomic diversity of the clade of interest.

evolutionary biology↗

Structural and functional analysis of YopR and identification of an additional key component of the SPβ phage lysis-lysogeny management system

Prophages need to tightly control their lifestyle to either be maintained within the host genome or enter the lytic cycle. The SP{beta} prophage present in the genome of Bacillus subtilis 168 was recently shown to possess an arbitrium system defining its replication stage. Using an historic B. subtilis strain harboring the heat-sensitive SP{beta} c2 mutant, we analyzed a key component of the lysis-lysogeny decision system called YopR, which is critical for maintenance of lysogeny. Here, we demonstrate that the heat-sensitive SP{beta} c2 phenotype is due to a single nucleotide exchange in the yopR gene, rendering the encoded YopRG136E protein temperature sensitive. Structural characterization of YopR revealed that the protein is a DNA-binding protein with an overall fold like tyrosine recombinases. Biochemical and functional analyses indicate that YopR has lost the recombinase function and the G136E exchange impairs its higher order structure and DNA binding activity. We further show that the heat-inducible SP{beta} excision of the c2 mutant still depends on the serine recombinase SprA. Finally, an evolution experiment identified the YosL protein of unknown function as a novel component of the lysis-lysogeny management system, as the presence of yosL is crucial for the induction of the lytic cycle of SP{beta}.

microbiology↗

pH as an eco-evolutionary driver of priority effects

Priority effects, where arrival order and initial relative abundance modulate local species interactions, can exert taxonomic, functional, and evolutionary influences on ecological communities by driving them to alternative states. It remains unclear if these wide-ranging consequences of priority effects can be explained systematically by a common underlying factor. Here, we identify such a factor in an empirical system. In a series of field and laboratory studies, we focus on how pH affects nectar-colonizing microbes and their interactions with plants and pollinators. In a field survey, we found that nectar microbial communities in a hummingbird-pollinated shrub, Diplacus aurantiacus, exhibited patterns indicative of alternative stable states through domination by either bacteria or yeasts within individual flowers. In laboratory experiments, Acinetobacter nectaris, the bacterium most commonly found in D. aurantiacus nectar, exerted a strongly negative priority effect against Metschnikowia reukaufii, the most common nectar-specialist yeast, by reducing nectar pH. This priority effect likely explains the mutually exclusive pattern of dominance found in the field survey. Furthermore, experimental evolution simulating hummingbird-assisted dispersal between flowers revealed that M. reukaufii could evolve rapidly to improve resistance against the priority effect if constantly exposed to A. nectaris-induced pH reduction. Finally, in a field experiment, we found that low nectar pH could reduce nectar consumption by hummingbirds, suggesting functional consequences of the pH-driven priority effect for plant reproduction. Taken together, these results show that it is possible to identify an overarching factor that governs the eco-evolutionary dynamics of priority effects across multiple levels of biological organization.

ecology↗

Monitoring rapid evolution of plant populations at scale with Pool-Sequencing

The change in allele frequencies within a population over time represents a fundamental process of evolution. By monitoring allele frequencies, we can analyze the effects of natural selection and genetic drift on populations. To efficiently track time-resolved genetic change, large experimental or wild populations can be sequenced as pools of individuals sampled over time using high-throughput genome sequencing (called the Evolve & Resequence approach, E&R). Here, we present a set of experiments using hundreds of natural genotypes of the model plant Arabidopsis thaliana to showcase the power of this approach to study rapid evolution at large scale. First, we validate that sequencing DNA directly extracted from pools of flowers from multiple plants -- organs that are relatively consistent in size and easy to sample -- produces comparable results to other, more expensive state-of-the-art approaches such as sampling and sequencing of individual leaves. Sequencing pools of flowers from 25-50 individuals at [~]40X coverage recovers genome-wide frequencies in diverse populations with accuracy r > 0.95. Secondly, to enable analyses of evolutionary adaptation using E&R approaches of plants in highly replicated environments, we provide open source tools that streamline sequencing data curation and calculate various population genetic statistics two orders of magnitude faster than current software. To directly demonstrate the usefulness of our method, we conducted a two-year outdoor evolution experiment with A. thaliana to show signals of rapid evolution in multiple genomic regions. We demonstrate how these laboratory and computational Pool-seq-based methods can be scaled to study hundreds of populations across many climates.

evolutionary biology↗

Quantifying the scale of genetic diversity extinction in the Anthropocene

More species than ever before are at risk of extinction due to anthropogenic habitat loss and climate change. But even species that are not threatened have seen reductions in their populations and geographic ranges, likely impacting their genetic diversity. Although preserving genetic diversity is key to maintaining adaptability of species, we lack predictive tools and global estimates of genetic diversity loss across ecosystems. By bridging theories of biodiversity and population genetics, we introduce a mathematical framework to understand the loss of naturally occurring DNA mutations within decreasing habitat within a species. Analysing genome-wide variation data of 10,095 geo-referenced individuals from 20 plant and animal species, we show that genome-wide diversity follows a power law with geographic area (the mutations-area relationship), which can predict genetic diversity loss in spatial computer simulations of local population extinctions. Given pre-21st century values of ecosystem transformations, we estimate that over 10% of genetic diversity may already be lost, surpassing the United Nations targets for genetic preservation. These estimated losses could rapidly accelerate with advancing climate change and habitat destruction, highlighting the need for forecasting tools that facilitate implementation of policies to protect genetic resources globally.

ecology↗

The windblown: possible explanations for dinophyte DNA in forest soils

Dinophytes are widely distributed in marine- and fresh-waters, but have yet to be conclusively documented in terrestrial environments. Here we evaluated the presence of these protists from an environmental DNA metabarcoding dataset of Neotropical rainforest soils. Using a phylogenetic placement approach with a reference alignment and tree, we showed that the numerous sequencing reads that were assigned to the dinophytes did not associate with taxonomy, environmental preference, nutritional mode, or dormancy. All the dinophytes in the soils are most likely windblown dispersal units of aquatic species, and are not biologically active residents of terrestrial environments.

microbiology↗

Phylogenetic analysis of SARS-CoV-2 data is difficult

Numerous studies covering some aspects of SARS-CoV-2 data analyses are being published on a daily basis, including a regularly updated phylogeny on nextstrain.org. Here, we review the difficulties of inferring reliable phylogenies by example of a data snapshot comprising all virus sequences available on May 5, 2020 from gisaid.org. We find that it is difficult to infer a reliable phylogeny on these data due to the large number of sequences in conjunction with the low number of mutations. We further find that rooting the inferred phylogeny with some degree of confidence either via the bat and pangolin outgroups or by applying novel computational methods on the ingroup phylogeny does not appear to be possible. Finally, an automatic classification of the current sequences into sub-classes based on statistical criteria is also not possible, as the sequences are too closely related. We conclude that, although the application of phylogenetic methods to disentangle the evolution and spread of COVID-19 provides some insight, results of phylogenetic analyses, in particular those conducted under the default settings of current phylogenetic inference tools, as well as downstream analyses on the inferred phylogenies, should be considered and interpreted with extreme caution.

evolutionary biology↗

SCRAPP: A tool to assess the diversity of microbial samples from phylogenetic placements

Microbial ecology research is currently driven by the continuously decreasing cost of DNA sequencing and the improving accuracy of data analysis methods. One such analysis method is phylogenetic placement, which establishes the phylogenetic identity of the anonymous environmental sequences in a sample by means of a given phylogenetic reference tree. However, assessing the diversity of a sample remains challenging, as traditional methods do not scale well with the increasing data volumes and/or do not leverage the phylogenetic placement information. Here, we present SCRAPP, a highly parallel and scalable tool that uses a molecular species delimitation algorithm to quantify the diversity distribution over the reference phylogeny for a given phylogenetic placement of the sample. SCRAPP employs a novel approach to cluster phylogenetic placements, called placement space clustering, to efficiently perform dimensionality reduction, so as to scale on large data volumes. Furthermore, it utilizes the phylogeny-aware molecular species delimitation method mPTP to quantify diversity. We evaluated SCRAPP using both, simulated and empirical datasets. We use simulated data to verify our approach. Tests on an empirical dataset show that SCRAPP-derived metrics can classify samples by their diversity-correlated features equally well or better than existing, commonly used approaches. SCRAPP is available at https://github.com/pbdas/scrapp

bioinformatics↗

Genesis and Gappa: Library and Toolkit for Working with Phylogenetic (Placement) Data

We present GENESIS, a library for working with phylogenetic data, and GAPPA, an accompanying command line tool for conducting typical analyses on such data. The tools target phylogenetic trees and phylogenetic placements, sequences, taxonomies, and other relevant data types, offer high-level simplicity as well as low-level customizability, and are computationally efficient, well-tested, and field-proven. Availability and ImplementationBoth GENESIS and GAPPA are written in modern C++11, and are freely available under GPLv3 at http://github.com/lczech/genesis and http://github.com/lczech/gappa. Contactlucas.czech@h-its.org and alexandros.stamatakis@h-its.org.

bioinformatics↗

Long metabarcoding of the eukaryotic rDNA operon to phylogenetically and taxonomically resolve environmental diversity

High-throughput environmental DNA metabarcoding has revolutionized the analysis of microbial diversity, but this approach is generally restricted to amplicon sizes below 500 base pairs. These short regions contain limited phylogenetic signal, which makes it impractical to use environmental DNA in full phylogenetic inferences. However, new long-read sequencing technologies such as the Pacific Biosciences platform may provide sufficiently large sequence lengths to overcome the poor phylogenetic resolution of short amplicons. To test this idea, we amplified soil DNA and used PacBio Circular Consensus Sequencing (CCS) to obtain a ~4500 bp region of the eukaryotic rDNA operon spanning most of the small (18S) and large subunit (28S) ribosomal RNA genes. The CCS reads were first treated with a novel curation workflow that generated 650 high-quality OTUs containing the physically linked 18S and 28S regions of the long amplicons. In order to assign taxonomy to these OTUs, we developed a phylogeny-aware approach based on the 18S region that showed greater accuracy and sensitivity than similarity-based and phylogenetic placement-based methods using shorter reads. The taxonomically-annotated OTUs were then combined with available 18S and 28S reference sequences to infer a well-resolved phylogeny spanning all major groups of eukaryotes, allowing to accurately derive the evolutionary origin of environmental diversity. A total of 1019 sequences were included, of which a majority (58%) corresponded to the new long environmental CCS reads. Comparisons to the 18S-only region of our amplicons revealed that the combined 18S-28S genes globally increased the phylogenetic resolution, recovering specific groupings otherwise missing. The long-reads also allowed to directly investigate the relationships among environmental sequences themselves, which represents a key advantage over the placement of short reads on a reference phylogeny. Altogether, our results show that long amplicons can be treated in a full phylogenetic framework to provide greater taxonomic resolution and a robust evolutionary perspective to environmental DNA.

microbiology↗

Scalable Methods for Post-Processing, Visualizing, and Analyzing Phylogenetic Placements

The exponential decrease in molecular sequencing cost generates unprecedented amounts of data. Hence, scalable methods to analyze these data are required. Phylogenetic (or Evolutionary) Placement methods identify the evolutionary provenance of anonymous sequences with respect to a given reference phylogeny. This increasingly popular method is deployed for scrutinizing metagenomic samples from environments such as water, soil, or the human gut.\n\nHere, we present novel and, more importantly, highly scalable methods for analyzing phylogenetic placements of metagenomic samples. More specifically, we introduce methods for visualizing differences between samples and their correlation with associated meta-data on the reference phylogeny, as well as for clustering similar samples using a variant of the k-means method.\n\nTo demonstrate the scalability and utility of our methods, as well as to provide exemplary interpretations of our methods, we applied them to 3 publicly available datasets comprising 9782 samples with a total of approximately 168 million sequences. The results indicate that new biological insights can be attained via our methods.

bioinformatics↗

Methods for Automatic Reference Trees and Multilevel Phylogenetic Placement

MotivationIn most metagenomic sequencing studies, the initial analysis step consists in assessing the evolutionary provenance of the sequences. Phylogenetic (or Evolutionary) Placement methods can be employed to determine the evolutionary position of sequences with respect to a given reference phylogeny. These placement methods do however face certain limitations: The manual selection of reference sequences is labor-intensive; the computational effort to infer reference phylogenies is substantially larger than for methods that rely on sequence similarity; the number of taxa in the reference phylogeny should be small enough to allow for visually inspecting the results.\n\nResultsWe present algorithms to overcome the above limitations. First, we introduce a method to automatically construct representative sequences from databases to infer reference phylogenies. Second, we present an approach for conducting large-scale phylogenetic placements on nested phylogenies. Third, we describe a preprocessing pipeline that allows for handling huge sequence data sets. Our experiments on empirical data show that our methods substantially accelerate the workflow and yield highly accurate placement results.\n\nImplementationFreely available under GPLv3 at http://github.com/lczech/gappa.\n\nContactlucas.czech@h-its.org\n\nSupplementary InformationSupplementary data are available at Bioinformatics online.

bioinformatics↗

EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequences

Next Generation Sequencing (NGS) technologies have led to a ubiquity of molecular sequence data. This data avalanche is particularly challenging in metagenetics, which focuses on taxonomic identification of sequences obtained from diverse microbial environments. To achieve this, phylogenetic placement methods determine how these sequences fit into an evolutionary context. Previous implementations of phylogenetic placement algorithms, such as the Evolutionary Placement Algorithm (EPA) included in RAxML, or O_SCPLOWPPLACERC_SCPLOW, are being increasingly used for this purpose. However, due to the steady progress in NGS technologies, the current implementations face substantial scalability limitations. Here we present EPA-O_SCPLOWNGC_SCPLOW, a complete reimplementation of the EPA that is substantially faster, offers a distributed memory parallelization, and integrates concepts from both, RAxML-EPA, and O_SCPLOWPPLACERC_SCPLOW. EPA-O_SCPLOWNGC_SCPLOW can be executed on standard shared memory, as well as on distributed memory systems (e.g., computing clusters). To demonstrate the scalability of EPA-O_SCPLOWNGC_SCPLOW we placed 1 billion metagenetic reads from the Tara Oceans Project onto a reference tree with 3,748 taxa in just under 7 hours, using 2,048 cores. Our performance assessment shows that EPA-O_SCPLOWNGC_SCPLOW outperforms RAxML-EPA and O_SCPLOWPPLACERC_SCPLOW by up to a factor of 30 in sequential execution mode, while attaining comparable parallel efficiency on shared memory systems. We further show that the distributed memory parallelization of EPA-O_SCPLOWNGC_SCPLOW scales well up to 3,520 cores. EPA-O_SCPLOWNGC_SCPLOW is available under the AGPLv3 license: https://github.com/Pbdas/epa-ng

bioinformatics↗

Quartet-based computations of internode certainty provide accurate and robust measures of phylogenetic incongruence

Incongruence, or topological conflict, is prevalent in genome-scale data sets but relatively few measures have been developed to quantify it. Internode Certainty (IC) and related measures were recently introduced to explicitly quantify the level of incongruence of a given internode (or internal branch) among a set of phylogenetic trees and complement regular branch support statistics in assessing the confidence of the inferred phylogenetic relationships. Since most phylogenomic studies contain data partitions (e.g., genes) with missing taxa and IC scores stem from the frequencies of bipartitions (or splits) on a set of trees, the calculation of IC scores requires adjusting the frequencies of bipartitions from these partial gene trees. However, when the proportion of missing data is high, current approaches that adjust bipartition frequencies in partial gene trees tend to overestimate IC scores and alternative adjustment approaches differ substantially from each other in their scores. To overcome these issues, we developed three new measures for calculating internode certainty that are based on the frequencies of quartets, which naturally apply to both comprehensive and partial trees. Our comparison of these new quartet-based measures to previous bipartition-based measures on simulated data shows that: 1) on comprehensive trees, both types of measures yield highly similar IC scores; 2) on partial trees, quartet-based measures generate more accurate IC scores; and 3) quartet-based measures are more robust to the absence of phylogenetic signal and errors in the phylogenetic relationships to be assessed. Additionally, analysis of 15 empirical phylogenomic data sets using our quartet-based measures suggests that numerous relationships remain unresolved despite the availability of genome-scale data. Finally, we provide an efficient open-source implementation of these quartet-based measures in the program QuartetScores, which is freely available at https://github.com/algomaus/QuartetScores.

evolutionary biology↗