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315 results for “gene diversity”
Linked collectors and determiners for: Uncovering a hidden diversity: a new species of freshwater shrimp Macrobrachium (Decapoda: Caridea: Palaemonidae) from Neotropical region (Brazil) revealed by morphological review and mitochondrial genes analyses.
Natural history specimen data linked to collectors and determiners held within, "Uncovering a hidden diversity: a new species of freshwater shrimp Macrobrachium (Decapoda: Caridea: Palaemonidae) from Neotropical region (Brazil) revealed by morphological review and mitochondrial genes analyses". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/de12a630-0709-4600-b356-971f170b10be">https://bionomia.net/dataset/de12a630-0709-4600-b356-971f170b10be</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/de12a630-0709-4600-b356-971f170b10be">https://gbif.org/dataset/de12a630-0709-4600-b356-971f170b10be</a>. Formatted as a Frictionless Data package.
Balancing selection at a wing pattern locus is associated with major shifts in genome-wide patterns of diversity and gene flow
<p>Selection shapes genetic diversity around target mutations, yet little is known about how selection on specific loci affects the genetic trajectories of populations, including their genome-wide patterns of diversity and demographic responses. Here we study the patterns of genetic variation and geographic structure in a neotropical butterfly, <em>Heliconius numata</em>, and its closely related allies in the so-called melpomene-silvaniform clade. <em>H. numata</em> is known to have evolved an inversion supergene which controls variation in wing patterns involved in mimicry associations with distinct groups of co-mimics. Butterflies show disassortative mate preferences and heterozygote advantage at this locus. We contrasted patterns of genetic diversity and structure 1) among extant polymorphic and monomorphic populations of <em>H. numata</em>, 2) between <em>H. numata</em> and its close relatives, and 3) between ancestral lineages. We show that <em>H. numata</em> populations which carry the inversions as a balanced polymorphism show markedly distinct patterns of diversity compared to all other taxa. They show the highest genetic diversity and effective population size estimates in the entire clade, as well as a low level of geographic structure and isolation by distance across the entire Amazon basin. By contrast, monomorphic populations of <em>H. numata</em> as well as its sister species and their ancestral lineages all show lower effective population sizes and genetic diversity, and higher levels of geographical structure across the continent. One hypothesis is that the large effective population size of polymorphic populations could be caused by the shift to a regime of balancing selection due to the genetic load and disassortative preferences associated with inversions. Testing this hypothesis with forward simulations supported the observation of increased diversity in populations with the supergene. Our results are consistent with the hypothesis that the formation of a supergene triggered a change in gene flow, causing a general increase in genetic diversity and the homogenisation of genomes at the continental scale.</p>
Glue genes are subjected to diverse selective forces in Drosophila during Drosophila development
<p>Molecular evolutionary studies usually focus on genes with clear roles in adult fitness or on developmental genes expressed at multiple time points during the life of the organism. Here, we examine the evolutionary dynamics of Drosophila glue genes, a set of eight genes tasked with a singular primary function during a specific developmental stage: the production of glue that allows animal pupa to attach to a substrate for several days during metamorphosis. Using phenotypic assays and available data from transcriptomics, PacBio genomes, and genetic variation from global populations, we explore the selective forces acting on the glue genes within the cosmopolitan <i>D. melanogaster</i> species and its five closely related species, <i>D. simulans</i>, <i>D. sechellia</i>, <i>D. mauritiana</i>, <i>D. yakuba</i>, and <i>D. teissieri</i>. We observe a three-fold difference in glue adhesion between the least and the most adhesive <i>D. melanogaster</i> strain, indicating a strong genetic component to phenotypic variation. These eight glue genes are among the most highly expressed genes in salivary glands yet they display no notable codon bias. New copies of <i>Sgs3</i> and <i>Sgs7 </i>are found in <i>D. yakuba </i>and<i> D. teissieri</i> with the <i>Sgs3</i> coding sequence evolving rapidly after duplication in the <i>D. yakuba</i> branch. Multiple sites along the various glue genes appear to be constrained. Our population genetics analysis in <i>D. melanogaster</i> suggests signs of local adaptive evolution for <i>Sgs3</i>, <i>Sgs5</i> and <i>Sgs5bis</i> and traces of recent selection for <i>Sgs1</i>, <i>Sgs3</i>, <i>Sgs7 </i>and<i> Sgs8</i>. Our work shows that stage-specific genes can be subjected to various dynamic evolutionary forces.</p>
Data from: Fungal symbionts generate water-saver and water-spender plant drought strategies via diverse effects on host gene expression
<p><em>Panicum</em> <em>hallii</em> var <em>hallii</em> HAL2 plants were inoculated individually with six foliar fungal endophytes or fungus-free controls and subjected to 5% or 20% soil moisture treatments. The fungi were selected for their previously observed effects on plant drought physiology, inducing either a "water saver" or a "water spender" strategy in the host. Plants were grown in enclosed microcosms to prevent cross-contamination and each treatment and control included 6 replicates. All fungi were Ascomycetes isolated from plants in central Texas. Plants were monitored for height, wilt, water loss, and survival. At the harvest, we also measured biomass and leaf colonization by the fungi and flash-froze leaf tissue for transcriptomic analyses. Both plant response and gene expression data are provided.</p>
Data for: Single-gene resolution of diversity-driven overyielding in plant genotype mixtures
<p>In plant communities, diversity often increases productivity and functioning, but the specific underlying drivers are difficult to identify. Most ecological theories attribute positive diversity effects to complementary niches occupied by different species or genotypes. However, the specific nature of niche complementarity often remains unclear, including how it is expressed in terms of trait differences between plants. Here, we use a gene-centred approach to study positive diversity effects in mixtures of natural <em>Arabidopsis </em><em>thaliana</em> genotypes. Using two orthogonal genetic mapping approaches, we find that between-plant allelic differences at the <em>AtSUC8</em> locus are strongly associated with mixture overyielding. <em>AtSUC8</em> encodes a proton-sucrose symporter and is expressed in root tissues. Genetic variation in <em>AtSUC8</em> affects the biochemical activities of protein variants and natural variation at this locus is associated with different sensitivities of root growth to changes in substrate pH. We thus speculate that - in the particular case studied here - evolutionary divergence along an edaphic gradient resulted in the niche complementarity between genotypes that now drives overyielding in mixtures. Identifying such genes important for ecosystem functioning may ultimately allow linking ecological processes to evolutionary drivers, help identify traits underlying positive diversity effects, and facilitate the development of high-performing crop variety mixtures.</p>
Sexual recombination and temporal gene flow maintain host resistance and genetic diversity
<p>Infectious disease can threaten host populations. Hosts can rapidly evolve resistance during epidemics, with this evolution often modulated by fitness trade-offs (e.g., between resistance and fecundity). However, many organisms switch between asexual and sexual reproduction, and this shift in reproductive strategy can also alter how resistance in host populations persists through time. Recombination can shuffle alleles selected for during an asexual phase, uncoupling the combinations of alleles that facilitated resistance to parasites and altering the distribution of resistance phenotypes in populations. Furthermore, in host species that produce diapausing propagules (e.g., seeds, spores, or resting eggs) after sex, accumulation of propagules into and gene flow out of a germ bank introduce allele combinations from past populations. Thus, recombination and gene flow might shift populations away from the trait distribution reached after selection by parasites. To understand how recombination and gene flow alter host population resistance, we tracked the genotypic diversity and resistance distributions of two wild populations of cyclical parthenogens. In one population, resistance and genetic diversity increased after recombination whereas, in the other, recombination did not shift already high resistance and genetic diversity. In both lakes, resistance remained high after temporal gene flow. This observation surprised us: due to costs to resistance imposed by a fecundity-resistance trade-off, we expected that high population resistance would be a transient state that would be eroded through time by recombination and gene flow. Instead, low resistance was the transient state, while recombination and gene flow re-established or maintained high resistance to this virulent parasite. We propose this outcome may have been driven by the joint influence of fitness trade-offs, genetic slippage after recombination, and temporal gene flow via the egg bank.</p>
Transcriptome analysis of anuran breeding glands reveals a surprisingly high expression and diversity of NNMT-like genes
<p><strong>Abstract</strong></p> <p>In many amphibians, males have sexually dimorphic breeding glands, which can produce proteinaceous or volatile pheromones, used for intraspecific communication. In this study we analyse two types of glands in the Mexican treefrog species <em>Ptychohyla macrotympanum </em>(Hylidae) – large ventrolateral glands and small nuptial pads on their fingers – using histology, whole-transcriptome sequencing and phylogenetic analyses. We found strong differences in glandular tissue composition and gene expression patterns between the two breeding gland types. In both glands we only found low expression of protein pheromone candidates. Instead, in the ventrolateral glands, gene expression was strikingly dominated by nicotinamide N-methyltransferase (NNMT)-like genes. Diversity of these genes was remarkably high, with at least 68 distinct NNMT-like genes. Our phylogenetic comparative analysis of the diversity of NNMT-like genes across vertebrates indicates that the extreme diversity of this gene is largely a frog-specific phenomenon and can be traced to large numbers of relatively recent gene duplications occurring independently in many lineages. The strong dominance and astonishing diversity of NNMT-like genes found in anurans in general, and in their sexually dimorphic breeding glands specifically, suggests an important function of NNMT-like proteins for anuran reproduction, possibly being related to volatile pheromone production.In many amphibians, males have sexually dimorphic breeding glands, which can produce proteinaceous or volatile pheromones, used for intraspecific communication. In this study we analyse two types of glands in the Mexican treefrog species <em>Ptychohyla macrotympanum </em>(Hylidae) – large ventrolateral glands and small nuptial pads on their fingers – using histology, whole-transcriptome sequencing and phylogenetic analyses. We found strong differences in glandular tissue composition and gene expression patterns between the two breeding gland types. In both glands we only found low expression of protein pheromone candidates. Instead, in the ventrolateral glands, gene expression was strikingly dominated by nicotinamide N-methyltransferase (NNMT)-like genes. Diversity of these genes was remarkably high, with at least 68 distinct NNMT-like genes. Our phylogenetic comparative analysis of the diversity of NNMT-like genes across vertebrates indicates that the extreme diversity of this gene is largely a frog-specific phenomenon and can be traced to large numbers of relatively recent gene duplications occurring independently in many lineages. The strong dominance and astonishing diversity of NNMT-like genes found in anurans in general, and in their sexually dimorphic breeding glands specifically, suggests an important function of NNMT-like proteins for anuran reproduction, possibly being related to volatile pheromone production.</p> <p> </p> <p><strong>Supplementary datasets accompanying the paper:</strong></p> <p>- final RNAseq assemblies of the ventrolateral glands and the nuptial pads of <em>Ptychohyla macrotympanum</em><br> - fasta-file of all <em>Ptychohyla</em>-NNMT-like genes found in this study</p>
Ancient diversity in host-parasite interaction genes in a model parasitic nematode
<p>Files associated with the "Ancient diversity in host-parasite interaction genes in a model parasitic nematode" manuscript. </p> <p><strong>VCF files:</strong></p> <p>HB1_vs_nxHelBake1.biallelic_noRefCall.qual.repeat_filtered.vcf.gz<br> HB2_vs_nxHelBake1.biallelic_noRefCall.qual.repeat_filtered.vcf.gz<br> HB3_vs_nxHelBake1.biallelic_noRefCall.qual.repeat_filtered.vcf.gz<br> HP1_vs_ngHelPoly1.biallelic_noRefCall.qual.repeat_filtered.vcf.gz<br> HP2_vs_ngHelPoly1.biallelic_noRefCall.qual.repeat_filtered.vcf.gz</p> <p><strong><em>H. mixtum</em> genome assemblies:</strong><br> Hm16_merged_spades_scaffolds.fa.gz<br> Hm2_merged_spades_scaffolds.fa.gz</p> <p><strong>Strongylomorph phylogeny:</strong></p> <p>Strongylomorph_phylogeny_18Jan2023_20spp_511orthos.astral.nwk.gz</p> <p><strong>Gene annotation files:</strong><br> ngHelPoly1.1.primary.final_annotations.cds.fa.gz<br> ngHelPoly1.1.primary.final_annotations.gff3.gz<br> ngHelPoly1.1.primary.final_annotations.proteins.fa.gz</p> <p>nxHelBake1.1.primary.final_annotations.cds.fa.gz<br> nxHelBake1.1.primary.final_annotations.gff3.gz<br> nxHelBake1.1.primary.final_annotations.proteins.fa.gz</p> <p><strong>Curated repeat libraries:</strong><br> ngHelPoly1.1.repeats.01062023.fa.gz<br> nxHelBake1.1.repeats.01062023.fa.gz</p> <p><strong>Assembled transcripts:</strong></p> <p>ngHelPoly1_hq_transcripts.fa.gz</p> <p>nxHelBake1_hq_transcripts.fa.gz</p>
Data from: Possible involvement of ghost introgressions in the striking diversity of Vomeronasal type 1 receptor genes in East African cichlids
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Data from: Fungal symbionts generate water-saver and water-spender plant drought strategies via diverse effects on host gene expression
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Sexual recombination and temporal gene flow maintain host resistance and genetic diversity
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Functional genomics and co-occurrence in a diverse tropical tree genus: The roles of drought and defense related genes
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Data from: Pesticide and pathogen exposure causes idiosyncratic gene expression responses across four diverse North American bumble bee species
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Glue genes are subjected to diverse selective forces in Drosophila during Drosophila development
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A novel method to assess the integrity of frozen archival DNA samples: Alpha-diversity ratios of short and long-read 16S rRNA gene sequences
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Diverse environmental perturbations reveal the evolution and context-dependency of genetic effects on gene expression levels
<pre>This repository contains data related to: Diverse environmental perturbations reveal the evolution and context-dependency of genetic effects on gene expression levels Amanda J. Lea, Julie Peng, Julien F. Ayroles A preprint of this work can be found here: https://www.biorxiv.org/content/10.1101/2021.11.04.467311v2 Specifically, the filtered, normalized, and batch corrected gene expression data file (31Mar21_all_runs_voom_resid.txt) is provided along with the metadata. We also provide the output from matrix eQTL that was used as input for mashR. Scripts used to generate and analyze these data are provided here: https://github.com/AmandaJLea/LCLs_gene_exp</pre>
Datasets for "Micromonosporaceae Biosynthetic Gene Cluster Diversity Highlights the Need for Broad Spectrum Investigation"
<p>In this data collection is:<br><strong>Data S1</strong>: A folder with all the fasta files, representing the 42 strains (41 <em>Micromonosporaceae</em>, 1 <em>Streptomycetaceae</em>).<br><strong>Data S2</strong>: A folder with all the .gbk files for the BGC regions predicted by antiSMASH v5.1.1. These files were used as inputs for BiG-SCAPE and BiG-SLiCE.<br><strong>Data S3</strong>: A folder with all the .gbk files for the BGC regions predicted by antiSMASH v6.1.0.<br><strong>Data S4</strong>: A folder containing all the Quast outputs for the 42 strains.<br><strong>Data S5</strong>: A folder containing all the BUSCO outputs for the 42 strains. Example scripts are provided for scraping relevant information from the individual BUSCO outputs.<br><strong>Data S6</strong>: A folder containing GTDB (Genome Taxonomy Database) classification results, and species-level grouping results using FastANI (95% cutoff).<br><strong>Data S7</strong>: A folder containing an Interactive Tree of Life (iTOL)-compatible bar chart annotation using antiSMASH v5.1.1 BGC region information.<br><strong>Data S8</strong>: A folder containing a word document that describes the parameters used with Ubuntu WSL (Windows Subsystem for Linux) on the command line for programs antiSMASH v6.1.2, BiG-SCAPE v1.1.2, and BiG-SLiCE v1.1.1. Also included are parameters for MDSC in python. An example script is also provided for batch queries of BGCs against BiG-SLiCE v1.1.1’s pre-processed dataset of ~1.2 million BGCs.<br><strong>Data S9</strong>: A folder containing the BiG-SCAPE visualization of the 38 <em>Micromonosporaceae</em> (post-QC filtering, excluding WMMA1363, WMMB482, WMMB486, and WMMC500) in Cytoscape.<br><strong>Data S10</strong>: A folder containing:<br>The pre-processed dataset of 1.2 million BGCs from BiG-SLiCE.<br>All report folders generated by BiG-SLiCE for the 779 <em>Micromonosporaceae </em>BGCs queried against the 1.2 million BGCs.<br>The results data.db and associated folders for the pre-processed dataset of 1.2 million BGCs.<br><strong>Data S11</strong>: A folder containing the scripts necessary to regenerate the figures and perform independent analyses, and the relevant data used for the analyses.<br><strong>Data S12: </strong>A folder containing the results of the nucleotide blast of WMMA1947.region12's siderophore contig against WMMD1120.region14's siderophore contig.</p> <p><strong>Supplementary Information: </strong>Supplementary Table S1 and Supplementary Figures S1-S181.</p>
Data from: Genetic analysis of red deer (Cervus elaphus) administrative management units in a human-dominated landscape - patterns of genetic diversity, population structure and gene flow
<p><span><span>Red deer (</span><span><em>Cervus elaphus</em></span><span>) throughout central Europe are</span> impacted by different anthropogenic activities including habitat fragmentation, selective hunting, and translocations<span>. This has substantial influences on genetic diversity and the long-term conservation of local populations of this species. Here we use genetic samples from 480 red deer individuals to assess the genetic diversity and differentiation of the 12 administrative management units located in Schleswig Holstein, the northernmost federal state in Germany. </span></span><span><span>We applied multiple analytical approaches and show that the history of local populations (i.e., translocations, culling of individuals outside of designated red deer zones, and anthropogenic infrastructures) has led to comparably low levels of genetic diversity. The mean expected heterozygosity was below 0.6 and we observed on average 4.2 alleles across 12 microsatellite loci. Effective population sizes below the recommended level of 50 were estimated for multiple local populations. </span></span><span><span>Our estimates of genetic structure and gene flow show that red deer in northern Germany are best described as a complex network of asymmetrically connected subpopulations, with high genetic exchange among some local populations and reduced connectivity of others. Genetic diversity was also correlated with population densities of neighboring management units. </span></span></p> <p><span><span>Based on these findings, we suggest that connectivity among existing management units needs to be considered in the practical management of the species, which means that some administrative management units should be managed together, while the effective isolation of other units needs to be mitigated.</span></span></p>
Data from: Diversity and molecular evolution of non-visual opsin genes across environmental, developmental, and morphological adaptations in frogs
<p>Dataset for the article Diversity and molecular evolution of non-visual opsin genes across environmental, developmental, and morphological adaptations in frogs. Includes non-visual opsin coding sequences from frogs, sequence alingments, phylogenetics trees, and raw PAML results files.</p>
Exploring the global metaplasmidome: unravelling plasmid landscapes and the spread of antibiotic resistance genes across diverse ecosystems
<p>Plasmid content was predicted from assembled data already publicly available or constructed from reads for this study. The assembled data supplied by Pasolli and colleagues (Pasolli <em>et al.</em>, 2019) , metasub consortium (Danko <em>et al.</em>, 2020) and TARA ocean (Tully <em>et al.</em>, 2018) were used for the human microbiome, the built environment and the marine ecosystem respectively. For assembly in the current study, reads from metagenomes were selected from two main databases. For the soil ecosystem, the metagenomes were selected from the dedicated curated database “TerrestrialMetagenomeDB” (Corrêa <em>et al.</em>, 2020). </p> <p>If the metagenomes were not assembled, reads were assembled by using megahit 1.2.9 with the metalarge option (Li <em>et al.</em>, 2015) after cleaning the data with bbduk2 (qtrim=rl trimq=28 minlen=25 maq=20 ktrim=r k=25 mink=11 and a list of adapters to remove) from the bbtools suite (<a href="https://jgi.doe.gov/data-and-tools/software-tools/bbtools/">https://jgi.doe.gov/data-and-tools/software-tools/bbtools/</a>).</p> <p>Plasmids were predicted for each assembly by using both reference-based and reference-free approaches as described in previous works (Hilpert <em>et al.</em>, 2021; Hennequin <em>et al.</em>, 2022) and available on the github website (https://github.com/meb-team/PlasSuite/). The databases used for the first approach included those for chromosomes (archaea and bacteria) and plasmids from RefSeq, as well as the MOB-suite tool (Robertson and Nash, 2018), SILVA (Quast <em>et al.</em>, 2013) and phylogenetic markers hosted by chromosomes (Wu <em>et al.</em>, 2013). The database created for this purpose is available at this address <a href="https://github.com/meb-team/PlasSuite/?tab=readme-ov-file#1-prepare-or-download-your-databases">https://github.com/meb-team/PlasSuite/?tab=readme-ov-file#1-prepare-or-download-your-</a><a href="https://github.com/meb-team/PlasSuite/?tab=readme-ov-file#1-prepare-or-download-your-databases">databases</a>. Two reference-free methods were applied to contigs that were not affiliated with chromosomes (discarded) or plasmids (retained in the first step): PlasFlow (Krawczyk <em>et al.</em>, 2018) and PlasClass (Pellow <em>et al.</em>, 2020). Previously undetected viruses were removed by using ViralVerify (<a href="https://github.com/ablab/viralVerify">https://github.com/ablab/viralVerify</a>)(Antipov <em>et al.</em>, 2020) that provides in parallel plasmid/non-plasmid classification. This step would also remove potential plasmid-phage elements as described by Pfeifer <em>et al.</em> (Pfeifer <em>et al.</em>, 2021), but would minimise false positives. Eukaryotic contamination was removed by aligning the sequences against the NT database and human chromosomes (GRCh38) using minimap2 (Li, 2018) with -x asm5 option. Contigs mapping with 95% identity for at least 80% coverage were removed. The predicted plasmids, hereafter referred as plasmid-like sequences (PLSs), were grouped by "scientific names" (<em>i.e.</em> 27) such as defined in the SRA metadata (air, lake, wetland…) and subsequently named ecosystems. These ecosystems were grouped in 9 biomes (Tab Supplementary 4). The data were then dereplicated by ecosystems using cd-hit-est with a threshold of 99%. The dereplicated PLSs were then clustered using MMseqs2 (Steinegger and Söding, 2017) with 80% of coverage an 90% of identity (--min-seq-id 0.90 -c 0.8 --cov-mode 1 --cluster-mode 2 --alignment-mode 3 --kmer-per-seq-scale 0.2) to define plasmid-like clusters (PLCs).</p> <div> <p>The PLC sequences are included in the file "predicted_PLC.fasta" and the main features are dercribed in the file "metadata_PLC.tsv"</p> <ul> <li>fasta_id: fasta identification of the PLC</li> <li>ecosystem: ecosystem from which the PLC originates</li> <li>biome: biome of the ecosystem</li> <li>latitude, longitude: GPS coordinate of the ecosystem</li> <li>length: PLC length</li> <li>map_markers: plasmid marker genes detected by PlasSuite (Hilpert et al., 2021)</li> <li>map_ncbi: PLCs present in the RefSeq plasmid database(Hilpert et al., 2021)</li> <li>nb_genes: Number of genes detected by Prokka implemented in PlasSuite</li> <li>nb_args: ARGs detected by PlasSuite</li> <li>plascad: results from plascad (Che et al., 2021)</li> </ul> <p> </p> <p> </p> <p>Antipov, D., Raiko, M., Lapidus, A., and Pevzner, P.A. (2020) MetaviralSPAdes: assembly of viruses from metagenomic data. <em>Bioinformatics</em> <strong>36</strong>: 4126–4129.</p> <p>Che, Y., Yang, Y., Xu, X., Břinda, K., Polz, M.F., Hanage, W.P., and Zhang, T. (2021) Conjugative plasmids interact with insertion sequences to shape the horizontal transfer of antimicrobial resistance genes. Proceedings of the National Academy of Sciences 118: e2008731118.</p> <p>Corrêa, F.B., Saraiva, J.P., Stadler, P.F., and da Rocha, U.N. (2020) TerrestrialMetagenomeDB: a public repository of curated and standardized metadata for terrestrial metagenomes. <em>Nucleic Acids Res</em> <strong>48</strong>: D626–D632.</p> <p>Danko, D., Bezdan, D., Afshinnekoo, E., Ahsanuddin, S., Bhattacharya, C., Butler, D.J., et al. (2020) Global Genetic Cartography of Urban Metagenomes and Anti-Microbial Resistance. <em>bioRxiv</em> 724526.</p> <p>Hennequin, C., Forestier, C., Traore, O., Debroas, D., and Bricheux, G. (2022) Plasmidome analysis of a hospital effluent biofilm: Status of antibiotic resistance. <em>Plasmid</em> <strong>122</strong>: 102638.</p> <p>Hilpert, C., Bricheux, G., and Debroas, D. (2021) Reconstruction of plasmids by shotgun sequencing from environmental DNA: which bioinformatic workflow? <em>Briefings in Bioinformatics</em> <strong>22</strong>: bbaa059.</p> <p>Krawczyk, P.S., Lipinski, L., and Dziembowski, A. (2018) PlasFlow: predicting plasmid sequences in metagenomic data using genome signatures. <em>Nucleic Acids Res</em> <strong>46</strong>: e35.</p> <p>Li, D., Liu, C.-M., Luo, R., Sadakane, K., and Lam, T.-W. (2015) MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. <em>Bioinformatics</em> <strong>31</strong>: 1674–1676.</p> <p>Li, H. (2018) Minimap2: pairwise alignment for nucleotide sequences. <em>Bioinformatics</em> <strong>34</strong>: 3094–3100.</p> <p>Pasolli, E., Asnicar, F., Manara, S., Zolfo, M., Karcher, N., Armanini, F., et al. (2019) Extensive Unexplored Human Microbiome Diversity Revealed by Over 150,000 Genomes from Metagenomes Spanning Age, Geography, and Lifestyle. <em>Cell</em> <strong>176</strong>: 649-662.e20.</p> <p>Pellow, D., Mizrahi, I., and Shamir, R. (2020) PlasClass improves plasmid sequence classification. <em>PLOS Computational Biology</em> <strong>16</strong>: e1007781.</p> <p>Pfeifer, E., Moura de Sousa, J.A., Touchon, M., and Rocha, E.P.C. (2021) Bacteria have numerous distinctive groups of phage–plasmids with conserved phage and variable plasmid gene repertoires. <em>Nucleic Acids Res</em> <strong>49</strong>: 2655–2673.</p> <p>Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., et al. (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. <em>Nucleic Acids Res</em> <strong>41</strong>: D590–D596.</p> <p>Robertson, J. and Nash, J.H.E. (2018) MOB-suite: software tools for clustering, reconstruction and typing of plasmids from draft assemblies. <em>Microbial Genomics</em> <strong>4</strong>:.</p> <p>Steinegger, M. and Söding, J. (2017) MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. <em>Nature Biotechnology</em>.</p> <p>Tully, B.J., Graham, E.D., and Heidelberg, J.F. (2018) The reconstruction of 2,631 draft metagenome-assembled genomes from the global oceans. <em>Scientific Data</em> <strong>5</strong>: 170203.</p> <p>Wu, D., Jospin, G., and Eisen, J.A. (2013) Systematic Identification of Gene Families for Use as “Markers” for Phylogenetic and Phylogeny-Driven Ecological Studies of Bacteria and Archaea and Their Major Subgroups. <em>PLoS One</em> <strong>8</strong>:.</p> </div> <p> </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.