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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

THE ASSEMBLY OF THE RED SEQUENCE AT z {approx} 1: THE COLOR AND SPECTRAL PROPERTIES OF GALAXIES IN THE Cl1604 SUPERCLUSTER

We investigate the properties of the 525 spectroscopically confirmed members of the Cl1604 supercluster at z {approx} 0.9 as part of the Observations of Redshift Evolution in Large Scale Environments survey. In particular, we focus on the photometric, stellar mass, morphological, and spectral properties of the 305 member galaxies of the eight clusters and groups that comprise the Cl1604 supercluster. Using an extensive Keck Low-Resolution Imaging Spectrometer (LRIS)/DEep Imaging Multi-Object Spectrograph (DEIMOS) spectroscopic database in conjunction with ten-band ground-based, Spitzer, and Hubble Space Telescope imaging, we investigate the buildup of the red sequence in groups and clusters at high redshift. Nearly all of the brightest and most massive red-sequence galaxies present in the supercluster environment are found to lie within the bounds of the cluster and group systems, with a surprisingly large number of such galaxies present in low-mass group systems. Despite the prevalence of these red-sequence galaxies, we find that the average cluster galaxy has a spectrum indicative of a star-forming galaxy, with a star formation rate between those of z {approx} 1 field galaxies and moderate-redshift cluster galaxies. The average group galaxy is even more active, exhibiting spectral properties indicative of a starburst. The presence of massive, red galaxies and the high fraction of starbursting galaxies present in the group environment suggest that significant processing is occurring in group environments at z {approx} 1 and earlier. There is a deficit of low-luminosity red-sequence galaxies in all Cl1604 clusters and groups, suggesting that such galaxies transition to the red sequence at later times. Extremely massive ({approx}10{sup 12} M{sub sun}) red-sequence galaxies routinely observed in rich clusters at z {approx} 0 are also absent from the Cl1604 clusters and groups. We suggest that such galaxies form at later times through merging processes. There are significant populations of transition galaxies at intermediate stellar masses (log(M{sub *})=10.25-10.75) present in the group and cluster environments, suggesting that this range is important for the buildup of the red-sequence mass function at z {approx} 1. Through a comparison of the transitional populations present in the Cl1604 cluster and group systems, we find evidence that massive blue-cloud galaxies are quenched earliest in the most dynamically relaxed systems and at progressively later times in dynamically unrelaxed systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

DISCOVERY OF A RICH CLUSTER AT z = 1.63 USING THE REST-FRAME 1.6 {mu}m 'STELLAR BUMP SEQUENCE' METHOD

We present a new two-color algorithm, the 'Stellar Bump Sequence' (SBS), that is optimized for robustly identifying candidate high-redshift galaxy clusters in combined wide-field optical and mid-infrared (MIR) data. The SBS algorithm is a fusion of the well-tested cluster red-sequence method of Gladders and Yee with the MIR 3.6 {mu}m-4.5 {mu}m cluster detection method developed by Papovich. As with the cluster red-sequence method, the SBS identifies candidate overdensities within 3.6 {mu}m-4.5 {mu}m color slices, which are the equivalent of a rest-frame 1.6 {mu}m stellar bump 'red-sequence'. In addition to employing the MIR colors of galaxies, the SBS algorithm incorporates an optical/MIR (z'-3.6 {mu}m) color cut. This cut effectively eliminates foreground 0.2 1.0 galaxies and add noise when searching for high-redshift galaxy overdensities. We demonstrate using the z {approx} 1 GCLASS cluster sample that similar to the red sequence, the stellar bump sequence appears to be a ubiquitous feature of high-redshift clusters, and that within that sample the color of the stellar bump sequence increases monotonically with redshift and provides photometric redshifts accurate to {Delta}z = 0.05. We apply the SBS method in the XMM-LSS SWIRE field and show that it robustly recovers the majority of confirmed optical, MIR, and X-ray-selected clusters at z > 1.0 in that field. Lastly, we present confirmation of SpARCS J022427-032354 at z = 1.63, a new cluster detected with the method and confirmed with 12 high-confidence spectroscopic redshifts obtained using FORS2 on the Very Large Telescope. We conclude with a discussion of future prospects for using the algorithm.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

RECONCILING THE OBSERVED STAR-FORMING SEQUENCE WITH THE OBSERVED STELLAR MASS FUNCTION

We examine the connection between the observed star-forming sequence (SFR ∝ M {sup α}) and the observed evolution of the stellar mass function in the range 0.2 < z < 2.5. We find that the star-forming sequence cannot have a slope α ≲ 0.9 at all masses and redshifts because this would result in a much higher number density at 10 < log (M/M {sub ☉}) < 11 by z = 1 than is observed. We show that a transition in the slope of the star-forming sequence, such that α = 1 at log (M/M {sub ☉}) < 10.5 and α = 0.7-0.13z (Whitaker et al.) at log (M/M {sub ☉}) > 10.5, greatly improves agreement with the evolution of the stellar mass function. We then derive a star-forming sequence that reproduces the evolution of the mass function by design. This star-forming sequence is also well described by a broken power law, with a shallow slope at high masses and a steep slope at low masses. At z = 2, it is offset by ∼0.3 dex from the observed star-forming sequence, consistent with the mild disagreement between the cosmic star formation rate (SFR) and recent observations of the growth of the stellar mass density. It is unclear whether this problem stems from errors in stellar mass estimates, errors in SFRs, or other effects. We show that a mass-dependent slope is also seen in other self-consistent models of galaxy evolution, including semianalytical, hydrodynamical, and abundance-matching models. As part of the analysis, we demonstrate that neither mergers nor hidden low-mass quiescent galaxies are likely to reconcile the evolution of the mass function and the star-forming sequence. These results are supported by observations from Whitaker et al.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Alternative Stacking Sequences in Hexagonal Boron Nitride

The relative orientation of successive sheets, i.e. the stacking sequence, in layered two-dimensional materials is central to the electronic, thermal, and mechanical properties of the material. Often different stacking sequences have comparable cohesive energy, leading to alternative stable crystal structures. Here we theoretically and experimentally explore different stacking sequences in the van der Waals bonded material hexagonal boron nitride (h-BN). We examine the total energy, electronic bandgap, and dielectric response tensor for five distinct high symmetry stacking sequences for both bulk and bilayer forms of h-BN. Two sequences, the generally assumed AA' sequence and the relatively unknown (for h-BN) AB (Bernal) sequence, are predicted to have comparably low energy. Lastly, we present a scalable modified chemical vapor deposition method that produces large flakes of virtually pure AB stacked h-BN; this new material complements the generally available AA' stacked h-BN.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ULTRA-effective labeling of tandem repeats in genomic sequence

In the age of long read sequencing, genomics researchers now have access to accurate repetitive DNA sequence (including satellites) that, due to the limitations of short read-sequencing, could previously be observed only as unmappable fragments. Tools that annotate repetitive sequence are now more important than ever, so that we can better understand newly uncovered repetitive sequences, and also so that we can mitigate errors in bioinformatic software caused by those repetitive sequences. To that end, we introduce the 1.0 release of our tool for identifying and annotating locally repetitive sequence, ULTRA Locates Tandemly Repetitive Areas (ULTRA). ULTRA is fast enough to use as part of an efficient annotation pipeline, produces state-of-the-art reliable coverage of repetitive regions containing many mutations, and provides interpretable statistics and labels for repetitive regions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Gene and translation initiation site prediction in metagenomic sequences

Gene prediction in metagenomic sequences remains a difficult problem. Current sequencing technologies do not achieve sufficient coverage to assemble the individual genomes in a typical sample; consequently, sequencing runs produce a large number of short sequences whose exact origin is unknown. Since these sequences are usually smaller than the average length of a gene, algorithms must make predictions based on very little data. We present MetaProdigal, a metagenomic version of the gene prediction program Prodigal, that can identify genes in short, anonymous coding sequences with a high degree of accuracy. The novel value of the method consists of enhanced translation initiation site identification, ability to identify sequences that use alternate genetic codes and confidence values for each gene call. We compare the results of MetaProdigal with other methods and conclude with a discussion of future improvements.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Large-scale 16S gene assembly using metagenomics shotgun sequences

Combining a 16S rRNA (16S) gene database with metagenomic shotgun sequences allows unbiased identification of known and novel microbes.To attain this, we herein report reference-based ribosome assembly (RAMBL), a computational pipeline, which integrates taxonomic tree search and Dirichlet process clustering to reconstruct full-length 16S gene sequences from metagenomic sequencing data with high accuracy. By benchmarking against the synthetic and real shotgun sequences, we demonstrated that full-length 16S gene assemblies of RAMBL were a good proxy for known and putative microbes, including Candidate Phyla Radiation. Here, we found that 30-40% of bacteria genera in the terrestrial and intestinal biomes have no closely related genome sequences. We also observed that RAMBL was able to generate a more accurate determination of environmental microbial diversity and yield better disease classification, suggesting that full-length 16S gene assemblies are a powerful alternative to marker gene set and 16S short reads. RAMBL first realizes the access to full-length 16S gene sequences in the near-terabase-scale metagenomic shotgun sequences, which markedly improve metagenomic data analysis and interpretation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Efficient DNA sequence compression with neural networks

Abstract Background The increasing production of genomic data has led to an intensified need for models that can cope efficiently with the lossless compression of DNA sequences. Important applications include long-term storage and compression-based data analysis. In the literature, only a few recent articles propose the use of neural networks for DNA sequence compression. However, they fall short when compared with specific DNA compression tools, such as GeCo2. This limitation is due to the absence of models specifically designed for DNA sequences. In this work, we combine the power of neural networks with specific DNA models. For this purpose, we created GeCo3, a new genomic sequence compressor that uses neural networks for mixing multiple context and substitution-tolerant context models. Findings We benchmark GeCo3 as a reference-free DNA compressor in 5 datasets, including a balanced and comprehensive dataset of DNA sequences, the Y-chromosome and human mitogenome, 2 compilations of archaeal and virus genomes, 4 whole genomes, and 2 collections of FASTQ data of a human virome and ancient DNA. GeCo3 achieves a solid improvement in compression over the previous version (GeCo2) of $2.4\%$, $7.1\%$, $6.1\%$, $5.8\%$, and $6.0\%$, respectively. To test its performance as a reference-based DNA compressor, we benchmark GeCo3 in 4 datasets constituted by the pairwise compression of the chromosomes of the genomes of several primates. GeCo3 improves the compression in $12.4\%$, $11.7\%$, $10.8\%$, and $10.1\%$ over the state of the art. The cost of this compression improvement is some additional computational time (1.7–3 times slower than GeCo2). The RAM use is constant, and the tool scales efficiently, independently of the sequence size. Overall, these values outperform the state of the art. Conclusions GeCo3 is a genomic sequence compressor with a neural network mixing approach that provides additional gains over top specific genomic compressors. The proposed mixing method is portable, requiring only the probabilities of the models as inputs, providing easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https://github.com/cobilab/geco3.

Silva, Milton↗
DOE OSTI2021

Chemical enrichment and radial migration in the Galactic disc – the origin of the [αFe] double sequence

The ([α/Fe], [Fe/H]) distribution of Milky Way stars shows at least two distinct sequences, which have traditionally been associated with the thin and thick disc components. The abundance distribution varies systematically with location R and |z| across the Galaxy. We reproduce this using an analytical chemodynamical model that includes the effects of radial migration and kinematic heating. Unlike some earlier models, our scheme does not require a distinct thick disc component emerging from a separate evolutionary path. The proposed model has a continuous star formation history and a continuous age velocity dispersion relation. Moreover, [α/Fe] is constant for stellar ages less than 8 Gyr, but increases sharply for older stars over a time-scale of 1.5 Gyr. The gap between the two sequences is due to this sharp transition. We show that the high-[α/Fe] sequence at the low-metallicity end is simply a pile-up of old stars, but towards the high-metallicity end, the age progressively decreases and stars have small birth radii. Our model successfully explains the uniformity of the locus of the high-[α/Fe] sequence across different locations. The low-[α/Fe] sequence contains stars with different birth radii that owes its existence to radial migration. For the low-[α/Fe] stars, angular momentum is anticorrelated with [Fe/H], while the opposite is true for high-[α/Fe] stars. We show that the later trend can be explained by the increase of circular velocity with time. If radial migration is not included, the model fails to generate the double sequence and instead shows only a single sequence. Our simple scheme has major advantages over earlier chemodynamical models, as we show.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

RNAcentral 2021: secondary structure integration, improved sequence search and new member databases

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world’s largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

MyTaxa: an advanced taxonomic classifier for genomic and metagenomic sequences

Determining the taxonomic affiliation of sequences assembled from metagenomes remains a major bottleneck that affects research across the fields of environmental, clinical and evolutionary microbiology. Here, we introduce MyTaxa, a homology-based bioinformatics framework to classify metagenomic and genomic sequences with unprecedented accuracy. The distinguishing aspect of MyTaxa is that it employs all genes present in an unknown sequence as classifiers, weighting each gene based on its (predetermined) classifying power at a given taxonomic level and frequency of horizontal gene transfer. MyTaxa also implements a novel classification scheme based on the genome-aggregate average amino acid identity concept to determine the degree of novelty of sequences representing uncharacterized taxa, i.e. whether they represent novel species, genera or phyla. Application of MyTaxa on in silico generated (mock) and real metagenomes of varied read length (100–2000 bp) revealed that it correctly classified at least 5% more sequences than any other tool. The analysis also showed that ~10% of the assembled sequences from human gut metagenomes represent novel species with no sequenced representatives, several of which were highly abundant in situ such as members of the Prevotella genus. Thus, MyTaxa can find several important applications in microbial identification and diversity studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Distributed Many-to-Many Protein Sequence Alignment using Sparse Matrices

Identifying similar protein sequences is a core step in many computational biology pipelines such as detection of homologous protein sequences, generation of similarity protein graphs for downstream analysis, functional annotation, and gene location. Performance and scalability of protein similarity search have proven to be a bottleneck in many bioinformatics pipelines due to increase in cheap and abundant sequencing data. This work presents a new distributed-memory software PASTIS. PASTIS relies on sparse matrix computations for efficient identification of possibly similar proteins. We use distributed sparse matrices for scalability and show that the sparse matrix infrastructure is a great fit for protein similarity search when coupled with a fully-distributed dictionary of sequences that allow remote sequence requests to be fulfilled. Our algorithm incorporates the unique bias in amino acid sequence substitution in search without altering basic sparse matrix model, and in turn, achieves ideal scaling up to millions of protein sequences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Anomaly Detection for Discrete Sequences: A Survey

This survey attempts to provide a comprehensive and structured overview of the existing research for the problem of detecting anomalies in discrete/symbolic sequences. The objective is to provide a global understanding of the sequence anomaly detection problem and how existing techniques relate to each other. The key contribution of this survey is the classification of the existing research into three distinct categories, based on the problem formulation that they are trying to solve. These problem formulations are: 1) identifying anomalous sequences with respect to a database of normal sequences; 2) identifying an anomalous subsequence within a long sequence; and 3) identifying a pattern in a sequence whose frequency of occurrence is anomalous. We show how each of these problem formulations is characteristically distinct from each other and discuss their relevance in various application domains. We review techniques from many disparate and disconnected application domains that address each of these formulations. Within each problem formulation, we group techniques into categories based on the nature of the underlying algorithm. For each category, we provide a basic anomaly detection technique, and show how the existing techniques are variants of the basic technique. This approach shows how different techniques within a category are related or different from each other. Our categorization reveals new variants and combinations that have not been investigated before for anomaly detection. We also provide a discussion of relative strengths and weaknesses of different techniques. We show how techniques developed for one problem formulation can be adapted to solve a different formulation, thereby providing several novel adaptations to solve the different problem formulations. We also highlight the applicability of the techniques that handle discrete sequences to other related areas such as online anomaly detection and time series anomaly detection.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

PacBio high‐throughput multi‐locus sequencing reveals high genetic diversity in mushroom‐forming fungi

Abstract Multi‐locus sequence data are widely used in fungal systematic and taxonomic studies to delimit species and infer evolutionary relationships. We developed and assessed the efficacy of a multi‐locus pooled sequencing method using PacBio long‐read high‐throughput sequencing. Samples included fresh and dried voucher specimens, cultures and archival DNA extracts of Agaricomycetes with an emphasis on the order Cantharellales. Of the 283 specimens sequenced, 93.6% successfully amplified at one or more loci with a mean of 3.3 loci amplified. Our method recovered multiple sequence variants representing alleles of rDNA loci and single copy protein‐coding genesrpb1,rpb2 andtef1. Within‐sample genetic variation differed by locus and taxonomic group, with the greatest genetic divergence observed among sequence variants ofrpb2 andtef1 from corticioid Cantharellales. Our method is a cost‐effective approach for generating accurate multi‐locus sequence data coupled with recovery of alleles from polymorphic samples and multi‐organism specimens. These results have important implications for understanding intra‐individual genomic variation among genetic loci commonly used in species delimitation of fungi.

Biochemistry & Molecular Biology↗
DOE OSTI2014

MO-G-17A-03: MR-Based Cortical Bone Segmentation for PET Attenuation Correction with a Non-UTE 3D Fast GRE Sequence

Purpose: To determine the feasibility of identifying cortical bone on MR images with a short-TE 3D fast-GRE sequence for attenuation correction of PET data in PET/MR. Methods: A water-fat-bone phantom was constructed with two pieces of beef shank. MR scans were performed on a 3T MR scanner (GE Discovery™ MR750). A 3D GRE sequence was first employed to measure the level of residual signal in cortical bone (TE{sub 1}/TE{sub 2}/TE{sub 3}=2.2/4.4/6.6ms, TR=20ms, flip angle=25°). For cortical bone segmentation, a 3D fast-GRE sequence (TE/TR=0.7/1.9ms, acquisition voxel size=2.5×2.5×3mm{sup 3}) was implemented along with a 3D Dixon sequence (TE{sub 1}/TE{sub 2}/TR=1.2/2.3/4.0ms, acquisition voxel size=1.25×1.25×3mm{sup 3}) for water/fat imaging. Flip angle (10°), acquisition bandwidth (250kHz), FOV (480×480×144mm{sup 3}) and reconstructed voxel size (0.94×0.94×1.5mm{sup 3}) were kept the same for both sequences. Soft tissue and fat tissue were first segmented on the reconstructed water/fat image. A tissue mask was created by combining the segmented water/fat masks, which was then applied on the fast-GRE image (MRFGRE). A second mask was created to remove the Gibbs artifacts present in regions in close vicinity to the phantom. MRFGRE data was smoothed with a 3D anisotropic diffusion filter for noise reduction, after which cortical bone and air was separated using a threshold determined from the histogram. Results: There is signal in the cortical bone region in the 3D GRE images, indicating the possibility of separating cortical bone and air based on signal intensity from short-TE MR image. The acquisition time for the 3D fast-GRE sequence was 17s, which can be reduced to less than 10s with parallel imaging. The attenuation image created from water-fat-bone segmentation is visually similar compared to reference CT. Conclusion: Cortical bone and air can be separated based on intensity in MR image with a short-TE 3D fast-GRE sequence. Further research is required to optimize the strategy to reduce Gibbs artifacts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

High-quality draft genome sequence of Ensifer meliloti Mlalz-1, a microsymbiont of Medicago laciniata (L.) miller collected in Lanzarote, Canary Islands, Spain

Abstract Ensifer meliloti Mlalz-1 (INSDC = ATZD00000000 ) is an aerobic, motile, Gram-negative, non-spore-forming rod that was isolated from an effective nitrogen-fixing nodule of Medicago laciniata (L.) Miller from a soil sample collected near the town of Guatiza on the island of Lanzarote, the Canary Islands, Spain. This strain nodulates and forms an effective symbiosis with the highly specific host M. laciniata . This rhizobial genome was sequenced as part of the DOE Joint Genome Institute 2010 Genomic Encyclopedia for Bacteria and Archaea-Root Nodule Bacteria (GEBA-RNB) sequencing project. Here the features of E. meliloti Mlalz-1 are described, together with high-quality permanent draft genome sequence information and annotation. The 6,664,116 bp high-quality draft genome is arranged in 99 scaffolds of 100 contigs, containing 6314 protein-coding genes and 74 RNA-only encoding genes. Strain Mlalz-1 is closely related to Ensifer meliloti IAM 12611 T , Ensifer medicae A 321 T and Ensifer numidicus ORS 1407 T , based on 16S rRNA gene sequences. gANI values of ≥98.1% support the classification of strain Mlalz-1 as E. meliloti . Nodulation of M. laciniata requires a specific nodC allele, and the nodC gene of strain Mlalz-1 shares ≥98% sequence identity with nodC of M. laciniata -nodulating Ensifer strains, but ≤93% with nodC of Ensifer strains that nodulate other Medicago species. Strain Mlalz-1 is unique among sequenced E. meliloti strains in possessing genes encoding components of a T2SS and in having two versions of the adaptive acid tolerance response lpiA-acvB operon. In E. medicae strain WSM419 , lpiA is essential for enhancing survival in lethal acid conditions. The second copy of the lpiA-acvB operon of strain Mlalz-1 has highest sequence identity (> 96%) with that of E. medicae strains, which suggests genetic recombination between strain Mlalz-1 and E. medicae and the horizontal gene transfer of lpiA-acvB .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Exploration of Noncoding Sequences in Metagenomes

Environment-dependent genomic features have been defined for different metagenomes, whose genes and their associated processes are related to specific environments. Identification of ORFs and their functional categories are the most common methods for association between functional and environmental features. However, this analysis based on finding ORFs misses noncoding sequences and, therefore, some metagenome regulatory or structural information could be discarded. In this work we analyzed 23 whole metagenomes, including coding and noncoding sequences using the following sequence patterns: (G+C) content, Codon Usage (Cd), Trinucleotide Usage (Tn), and functional assignments for ORF prediction. Herein, we present evidence of a high proportion of noncoding sequences discarded in common similarity based methods in metagenomics, and the kind of relevant information present in those. We found a high density of trinucleotide repeat sequences (TRS) in noncoding sequences, with a regulatory and adaptive function for metagenome communities. We present associations between trinucleotide values and gene function, where metagenome clustering correlate with microorganism adaptations and kinds of metagenomes. We propose here that noncoding sequences have relevant information to describe metagenomes that could be considered in a whole metagenome analysis in order to improve their organization, classification protocols, and their relation with the environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

AST: An Automated Sequence-Sampling Method for Improving the Taxonomic Diversity of Gene Phylogenetic Trees

A challenge in phylogenetic inference of gene trees is how to properly sample a large pool of homologous sequences to derive a good representative subset of sequences. Such a need arises in various applications, e.g. when (1) accuracy-oriented phylogenetic reconstruction methods may not be able to deal with a large pool of sequences due to their high demand in computing resources; (2) applications analyzing a collection of gene trees may prefer to use trees with fewer operational taxonomic units (OTUs), for instance for the detection of horizontal gene transfer events by identifying phylogenetic conflicts; and (3) the pool of available sequences is biased towards extensively studied species. In the past, the creation of subsamples often relied on manual selection. Here we present an Automated sequence-Sampling method for improving the Taxonomic diversity of gene phylogenetic trees, AST, to obtain representative sequences that maximize the taxonomic diversity of the sampled sequences. To demonstrate the effectiveness of AST, we have tested it to solve four problems, namely, inference of the evolutionary histories of the small ribosomal subunit protein S5 of E. coli, 16 S ribosomal RNAs and glycosyl-transferase gene family 8, and a study of ancient horizontal gene transfers from bacteria to plants. Our results show that the resolution of our computational results is almost as good as that of manual inference by domain experts, hence making the tool generally useful to phylogenetic studies by non-phylogeny specialists. The program is available at http://csbl.bmb.uga.edu/~zhouchan/AST.php.

59 BASIC BIOLOGICAL SCIENCES↗