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1,009 results for “clonal”
Clonal decomposition and DNA replication states defined by scaled single cell genome sequencing
<p><strong>OV2295 Tables</strong></p> <p>ov2295_breakpoint_counts.csv.gz: Table of breakpoint counts per cell</p> <ul> <li>prediction_id: identifier for the breakpoint</li> <li>cell_id: identifier for the cell</li> <li>read_count: number of reads</li> <li>library_id: identifier for the DNA library</li> <li>sample_id: identifier for the sequenced sample</li> <li>chromosome_1: chromosome of breakend 1</li> <li>strand_1: orientation of break end 1</li> <li>position_1: position of break end 1</li> <li>chromosome_2: chromosome of breakend 2</li> <li>strand_2: orientation of break end 2</li> <li>position_2: position of break end 2</li> </ul> <p>ov2295_cell_cn.csv.gz: Table of cell specific copy number</p> <ul> <li>cell_id: identifier for the cell</li> <li>sample_id: identifier for the sequenced sample</li> <li>library_id: identifier for the DNA library</li> <li>chr: chromosome of bin</li> <li>start: start of bin</li> <li>end: end of bin</li> <li>reads: number of reads</li> <li>copy: raw normalized copy number</li> <li>state: copy number state</li> <li>gc: percent gc of the bin</li> <li>map: average mappability of the bin</li> </ul> <p>ov2295_cell_metrics.csv.gz: Table of cell metrics</p> <ul> <li>cell_id: identifier of the cell</li> <li>unpaired_mapped_reads: number of unpaired mapped reads</li> <li>paired_mapped_reads: number of mapped reads that were properly paired</li> <li>unpaired_duplicate_reads: number of unpaired duplicated reads</li> <li>paired_duplicate_reads: number of paired reads that were also marked as duplicate</li> <li>unmapped_reads: number of unmapped reads</li> <li>percent_duplicate_reads: percentage of duplicate reads</li> <li>estimated_library_size: scaled total number of mapped reads</li> <li>total_reads: total number of reads, regardless of mapping status</li> <li>total_mapped_reads: total number of mapped reads</li> <li>total_duplicate_reads: number of duplicate reads</li> <li>total_properly_paired: number of properly paired reads</li> <li>coverage_breadth: percentage of genome covered by some read</li> <li>coverage_depth: average reads per nucleotide position in the genome</li> <li>median_insert_size: median insert size between paired reads</li> <li>mean_insert_size: mean insert size between paired reads</li> <li>standard_deviation_insert_size: standard deviation of the insert size between paired reads</li> <li>index_sequence: index sequence of the adaptor sequence</li> <li>column: column of the cell on the nanowell chip</li> <li>img_col: column of the cell from the perspective of the microscope</li> <li>index_i5: id of the i5 index adapter sequence</li> <li>sample_type: type of the sample</li> <li>primer_i7: id of the i5 index primer sequence</li> <li>experimental_condition: experimental treatment of the cell, includes controls</li> <li>index_i7: id of the i7 index adapter sequence</li> <li>cell_call: living/dead classification of the cell based on staining usually, C1 == living, C2 == dead</li> <li>sample_id: name of the sample</li> <li>primer_i5: id of the i5 index primer sequence</li> <li>row: row of the cell on the nanowell chip</li> <li>library_id: identifier for the DNA library</li> <li>index: ignored</li> <li>multiplier: during parameter searching, the set [1..6] that was chosen</li> <li>MSRSI_non_integerness: median of segment residuals from segment integer copy number states</li> <li>MBRSI_dispersion_non_integerness: median of bin residuals from segment integer copy number states</li> <li>MBRSM_dispersion: median of bin residuals from segment median copy number values</li> <li>autocorrelation_hmmcopy: hmmcopy copy autocorrelation</li> <li>cv_hmmcopy: ignored</li> <li>empty_bins_hmmcopy: number of empty bins in hmmcopy</li> <li>mad_hmmcopy: median absolute deviation of hmmcopy copy</li> <li>mean_hmmcopy_reads_per_bin: mean reads per hmmcopy bin</li> <li>median_hmmcopy_reads_per_bin: median reads per hmmcopy bin</li> <li>std_hmmcopy_reads_per_bin: standard deviation value of reads in hmmcopy bins</li> <li>total_halfiness: summed halfiness penality score of the cell</li> <li>total_mapped_reads_hmmcopy: total mapped reads in all hmmcopy bins</li> <li>scaled_halfiness: summed scaled halfiness penalty score of the cell</li> <li>mean_state_mads: mean value for all median absolute deviation scores for each state</li> <li>mean_state_vars: variance value for all median absolute deviation scores for each state</li> <li>mad_neutral_state: median absolute deviation score of the neutral 2 copy state</li> <li>breakpoints: number of breakpoints, as indicated by state changes not at the ends of chromosomes</li> <li>mean_copy: mean hmmcopy copy value</li> <li>state_mode: the most commonly occuring state</li> <li>log_likelihood: hmmcopy log likelihood for the cell</li> <li>true_multiplier: the exact decimal value used to scale the copy number for segmentation</li> <li>order: order of the cell in the hierarchical clustering tree</li> <li>quality: random forest classifier proability score that cell is good</li> </ul> <p>ov2295_clone_alleles.csv.gz: Table of clone specific allele data</p> <ul> <li>chr: chromosome of bin</li> <li>start: start of bin</li> <li>end: end of bin</li> <li>hap_label: haplotype block identifier</li> <li>clone_id: clone identifier</li> <li>allele_1_sum: number of reads for allele 1 of the haplotype block</li> <li>allele_2_sum: number of reads for allele 2 of the haplotype block</li> <li>total_counts_sum: total reads for the haplotype block</li> </ul> <p>ov2295_clone_breakpoints.csv.gz: Table of breakpoints per clone for OV2295 samples. Columns:</p> <ul> <li>prediction_id: identifier for the breakpoint</li> <li>chromosome_1: chromosome of breakend 1</li> <li>strand_1: orientation of break end 1</li> <li>position_1: position of break end 1</li> <li>chromosome_2: chromosome of breakend 2</li> <li>strand_2: orientation of break end 2</li> <li>position_2: position of break end 2</li> <li>clone_id: clone identifier</li> <li>read_count: number of reads</li> <li>is_present: presence=1, absent=0</li> </ul> <p>ov2295_clone_clusters.csv.gz: Table of cell clusters as putative clones</p> <ul> <li>cell_id: identifier for the cell</li> <li>clone_id: clone identifier</li> </ul> <p>ov2295_clone_cn.csv.gz: Table of allele specific copy number per clone for OV2295 samples. Columns:</p> <ul> <li>chr: chromosome of bin</li> <li>start: start of bin</li> <li>end: end of bin</li> <li>total_cn: HMMCopy predicted total copy number </li> <li>minor_cn: HMM predicted minor copy number </li> <li>major_cn: HMM predicted major copy number </li> <li>clone_id: clone identifier</li> </ul> <p>ov2295_clone_snvs.csv.gz: Table of SNVs per clone for OV2295 samples. Columns:</p> <ul> <li>chrom: chromosome</li> <li>coord: genome position</li> <li>ref: reference nucleotide</li> <li>alt: alternate nucleotide</li> <li>clone_id: clone identifier</li> <li>ref_counts: number of reads at this position matching the reference nucleotide</li> <li>alt_counts: number of reads at this position matching the alternate nucleotide</li> <li>total_counts: total number of reads at this position</li> <li>is_present: presence=0, absent=1</li> <li>is_het: is heterozygous</li> <li>is_hom: is homozygous for the alternate</li> </ul> <p>ov2295_nodes.csv.gz: Table of phylogenetic information for SNV evolution</p> <ul> <li>variant_id: identifier for the SNV as chrom:coord:ref:alt</li> <li>node: node in the phylogenetic tree</li> <li>loss: probability the SNV was lost at this node</li> <li>origin: probability the SNV originated at this node</li> <li>presence: probability the SNV is present at this node</li> <li>ml_origin: binary indicator the SNV originated at this node</li> <li>ml_presence: binary indicator the SNV is present at this node</li> <li>ml_loss: binary indicator the SNV was lost at this node</li> </ul> <p>ov2295_snv_counts.csv.gz: Table of SNV counts</p> <ul> <li>chrom: chromosome</li> <li>coord: genome position</li> <li>ref: reference nucleotide</li> <li>alt: alternate nucleotide</li> <li>ref_counts: number of reads at this position matching the reference nucleotide</li> <li>alt_counts: number of reads at this position matching the alternate nucleotide</li> <li>cell_id: identifier for the cell</li> <li>total_counts: total number of reads at this position</li> <li>sample_id: identifier for the sequenced sample</li> </ul> <p>ov2295_tree.pickle: Phylogenetic tree in python pickle format. Requires installation of the stochastic dollo code at: https://bitbucket.org/dranew/dollo, version 0.4.2.</p> <p>Note the following sample mapping: ‘SA922’: ‘OV2295(R2)’, ‘SA921’: ‘TOV2295(R)’, ‘SA1090’: ‘OV2295’,</p> <p><strong>Plots</strong></p> <p>ov_supp_clone_allele_cn.png: Clone allele ratios for each OV2295 sample.</p> <p>ov_supp_clone_total_cn.png: Clone copy number for each OV2295 sample.</p> <p>ov_supp_sample_total_cn.png: Bulk copy number for each OV2295 sample.</p> <p>ov_supp_sample_allele_cn.png: Bulk allele ratios for each OV2295 sample.</p>
SDR01 Intra-clonal stem demography of Cornus drummondii in response to fire and browsing at Konza Prairie
Intra-clonal stem density, natality, mortality, flowering and relative growth rate within discrete Cornus drummondii shrubs in response to fire frequency (4- vs 20-yr burn intervals) and simulated browsing. Tagged stems within individual shrubs were tracked and measured at the beginning and end of each growing season in 2018 and 2019 to assess the interactions of fire and browsing on stem demography.
Centennial clonal stability of asexual Daphnia in Greenland lakes despite climate variability
<p><strong>Daphnia_microsatellite_data_Dane_etal.2020.csv: </strong></p> <p><strong>Microsatellite genotypes from three study lakes (SS4, SS1381, and SS1590) in the Kangerlussuaq area, West Greenland. </strong>Microsatellite loci were amplified in single, 12.5 µl multiplex reactions (Type-it PCR kit, Qiagen Inc, Valencia, CA, USA), using an Eppendorf Nexus Thermal Cycler with thermal cycle conditions recommended in the Type-it PCR kit manual. Ten microsatellite primers representing genome-wide loci were used for genotyping; details in (Colbourne et al. 2004; Frisch et al., 2014). Two primers (Dp90, Dp377) failed to amplify in a consistent manner and were therefore excluded from further analysis. Amplified microsatellites were genotyped on an Applied Biosystems 3730 genetic analyser. We used the microsatellite plugin for Geneious 7.0.6 (https://www.geneious.com) for peak calling and binning. Called peaks were visually inspected and manually adjusted when necessary. </p> <p><strong>SS4_sediment.core_data_Fig2_Dane_et_al2020.xlsx</strong>: </p> <p><strong>Information on various parameters of sediment cores collected in Lake SS4, Kangerlussuq area, West Greenland. </strong>Data used in Dane et al. 2020, Figure 2 (panels B and C) are derived from two sediment cores: one for fluorescence (section at 0.5 cm intervals, <em>Depth</em>) and one for <em>Daphnia </em>ephippia analyses (1-cm intervals). Percentage organic matter content (loss-on-ignition at 550 °C,<em>OM%</em>) was used to correlate the two cores to each other and to a previously-dated sediment core (see Dane et al. 2020, Methods). The fluorescence derived parameter Parafac component C2 was used as an indicator of the abundance of purple sulphur bacteria. The organic carbon burial rate (<em>OC AR</em>, g C m–2 yr–1) was also calculated for this core (see Anderson et al. 2019). The <em>Daphnia</em> core was used for the microsatellite analyses and the accumulation rate of ephippia (<em>ephippia AR</em>) at the core site was estimated.</p> <p>For further details please see associated publication in Ecology and Evolution.</p> <p> </p>
Data from: Radial stem growth of the clonal shrub Alnus alnobetula at treeline is constrained by summer temperature and winter desiccation and differs in carbon allocation strategy compared to co-occurring Pinus cembra
<p><strong>Data are documented in the following article:</strong></p> <p>Oberhuber W., G Wieser, F. Bernich, A. Gruber (2022) Radial stem growth of the clonal shrub <em>Alnus alnobetula</em> at treeline is constrained by summer temperature and winter desiccation and differs in carbon allocation strategy compared to co-occurring <em>Pinus cembra</em>. Forests 2022, 13, 440. doi: 10.3390/f13030440.</p> <p> </p> <p><strong>Summary:</strong></p> <p>Global change is affecting species areal distribution in many regions. A better understanding of how land-use change and climate warming affects shrub growth is essential for improved predictions of forest dynamics at the alpine treeline. Evaluation of radial stem growth of the clonal shrub <em>Alnus alnobetula</em> (= <em>Alnus viridis</em>) and the co-occurring tree species Swiss stone pine (<em>Pinus cembra</em>) within an alpine treeline ecotone revealed that mean ring width of nitrogen fixing <em>A. alnobetula</em> was about four times lower compared to <em>P. cembra</em>. Our findings are based on ring width data from <em>A. alnobetula</em> and <em>P. cembra</em> stems sampled at the alpine treeline ecotone on Mt. Patscherkofel (47°12’N, 11°27’E, Central European Alps, Austria, elevation range 2050 to 2190 m asl). Ring width time series include 86 radii from 51 stems of <em>A. alnobetula</em> (stems had mean age of 18±7 yrs) and 24 radii from 16 stems of <em>P. cembra </em>(18±4 yrs). We explain our findings by different carbon allocation strategies, i.e., preference of “vertical” stem growth in late successional <em>P. cembra</em> vs. favoring “horizontal” spread in the pioneer shrub<em> A. alnobetula.</em> By favouring clonal propagation over individual stem growth <em>A. alnobetula</em> is able to quickly spread at the alpine treeline ecotone.</p>
High resolution microsection images for: Common juniper, the oldest living non-clonal woody species across the tundra biome and the European continent
<p>Two high resolution images of the stem section are available as .czi files. These images are from a living <em>Juniperus communis</em> L. branch from Abisko (Sweden) sampled in August 2021. These high-resolution photographs (2.89 pixel/μm) were created using Axio Scan 7, Zeiss, Germany. </p> <p>One high resolution image of the same stem section is archived as a .tif file (49835x25587 pixels). This image is a composition of the two .czi images created using Axio Scan 7, Zeiss, with a reduced resolution and edited adding the ring-count reference points and the reference scale.</p>
Attack of the clones: population genetics reveals clonality of Colletotrichum lupini, the causal agent of lupin anthracnose
<p><em>Colletotrichum lupini</em>, causing lupin anthracnose, is one of the worst pathogens to lupin cultivation worldwide. Understanding its population structure and evolutionary potential is crucial to design successful disease management strategies. The objective of this study was to employ population genetics to investigate the diversity, evolutionary dynamics and molecular basis of host interaction of this notorious lupin pathogen. A collection of globally representative <em>C. lupini </em>isolates was genotyped through triple digest restriction-site associated DNA sequencing (3D-RADseq), resulting in a dataset of unparalleled resolution. Phylogenetic and structural analysis could distinguish four (I – IV) independent lineages. The strong population structure, low recombination and slow linkage decay strongly suggests that <em>C. lupini</em> reproduces clonally. Different morphologies and virulence patterns on white (<em>Lupinus albus</em>) and Andean lupin (<em>L. mutabilis</em>) were observed between and within clonal lineages. Isolates belonging to lineage II were shown to have a mini-chromosome which was also partly present in lineage III and IV, but not in lineage I isolates. Variation in the presence of this mini-chromosome could indicate a role in host interaction. All four lineages were present in the South American Andes region, which is concluded to be the center of origin of this species. Only members of lineage II have been found outside South America since the 1990s, indicating it as the current pandemic population. As a seed-borne pathogen, <em>C. lupini</em> has mainly spread through infected but symptomless seeds, stressing the importance of phytosanitary measures to prevent future outbreaks of strains that are yet confined to South America.</p>
Clonal heterogeneity of endocrine therapy resistance in breast cancer
<p>We barcoded endocrine therapy sensitive cell lines (MCF7 and T47D) and rendered them resistant to commonly applied first line endocrine therapeutics (Tamoxifen and estrogen deprivation). Next, we isolated single cell clones of endocrine therapy resistant populations and subjected clonal cell lines to RNA-Seq and Phosphoproteomics profiling.</p>
Single-Cell Profiling of CD8+ T Cells in Acute Myeloid Leukemia Reveals a Continuous Spectrum of Differentiation and Clonal Hyperexpansion
<p>Data for the publication <strong>Single-Cell Profiling of CD8<sup>+</sup> T Cells in Acute Myeloid Leukemia Reveals a Continuous Spectrum of Differentiation and Clonal Hyperexpansion</strong></p>
Spatial transcriptomics of B and T cell receptors uncovers lymphocyte clonal dynamics.
<p>This dataset contains a single zipped folder containing:</p> <ul> <li> <p>data</p> </li> <li> <p>scripts</p> </li> </ul> <p>needed to reproduce the manuscript entitled "Spatial transcriptomics of B and T cell receptors uncovers lymphocyte clonal dynamics". Each folder is organized by tissue type, methodology, and analysis. A readme file accompanies each folder with details on the files/scripts within that folder. Alongside the paper and supplementary materials, it should be possible to reproduce all the figures in the manuscript.</p>
Exploring the genetic consequences of clonality in haplodiplontic taxa
<p>Partially clonality is an incredibly common reproductive mode found across all the major eukaryotic lineages. Yet, population genetic theory is based on exclusive sexuality or exclusive asexuality and partial clonality is often ignored. This is particularly true in haplodiplontic eukaryotes, including algae, ferns, mosses, and fungi, where somatic development occurs in both the haploid and diploid stages. Haplodiplontic life cycles are predicted to be correlated with asexuality, but tests of this prediction are rare. Moreover, there are unique consequences of having long-lived haploid and diploid stages in the same life cycle. For example, clonal processes uncouple the life cycle such that the repetition of the diploid stage via clonality leads to the loss of the haploid stage. Here, we surveyed the literature to find studies that had genotyped both haploid and diploid stages and re-calculated population genetic summary metrics for seven red algae, one green alga, three brown algae, and three mosses. We compared these data to recent simulations that explicitly addressed the population genetic consequences of partial clonality in haplodiplontic life cycles. Not only was partial clonality found to act as a homogenizing force, but the combined effects of proportion of haploids, rate of clonality, and the relative strength of mutation versus genetic drift impacts the distributions of population genetic indices. We found remarkably similar patterns across commonly used population genetic metrics between our empirical and recent theoretical expectations. To facilitate future studies, we provide some recommendations for sampling and analyzing population genetic parameters for haplodiplontic taxa.</p>
Immune repertoire profiling reveals that clonally expanded B and T cells infiltrating diseased human kidneys can also be tracked in the blood
<p>Recent advances in high-throughput sequencing allow for the competitive analysis of the human B and T cell immune repertoire. In this study we compared Immunoglobulin and T cell receptor repertoires of lymphocytes found in kidney and blood samples of 10 patients with various renal diseases based on next-generation sequencing data.</p>
Processed data to accompany "Clonally heritable gene expression imparts a layer of diversity within cell types"
<p>This is the processed data underlying the paper "Clonally heritable gene expression imparts a layer of diversity within cell types" by Mold, Weissman, et al. Data has been gone through preprocessing steps, using the Python Notebooks found at <a href="https://github.com/MartyWeissman/ClonalOmics/tree/main/Data">https://github.com/MartyWeissman/ClonalOmics/tree/main/Data</a>. </p> <p>Smaller files are provided in .csv (comma-separated-value) format and larger files such as expression matrices are provided in .loom format (<a href="https://anndata.readthedocs.io/en/latest/">using the AnnData package</a>).</p> <p> </p> <p> </p>
Unraveling clonal trait space: Beyond aboveground and fine-root traits
<p>Plant trait variation is constrained by mechanical and energetic tradeoffs as attested by the global spectrum of plant form and function and the fine-root economics space for above- and belowground traits. However, traits that are key for fitness maintenance in some plant groups, such as clonal and bud bank traits, have not yet been integrated within the frameworks provided by the aboveground and the fine-root economics space.</p> <p>By using an extensive dataset encompassing aboveground, fine-root, clonal, and bud bank traits of 2000 species of Central European herbs, we asked whether clonal and bud bank traits correspond to the placement of species in the aboveground or fine-root trait spaces.</p> <p>Perennial clonal and non-clonal herbs show indistinct positioning within the aboveground and fine-root trait spaces. This extends and reinforces previous fragmentary evidence of weak correlations between clonal and bud bank traits and aboveground trait dimensions. Additionally, we identify for the first time a limited correlation between clonal and fine-root traits as well. This disconnection suggests that clonal traits operate independently from other trait spectra. For this reason, we introduce the concept of a "clonal trait space" for clonal herbs. The first dimension of this space is defined by bud bank size and the persistence of clonal connection, reflecting a gradient of species specialisation for on-spot persistence and tolerance to disturbance (persistence dimension). The second dimension, defined by multiplication rate and lateral spread, reflects a specialisation axis for clonal multiplication and horizontal size dimension (clonal multiplication dimension). Clonal trait dimensions add non-redundant information to the aboveground or fine-roots trait space.</p> <p><strong>Synthesis:</strong> We champion the integration of the persistence and clonal multiplication dimensions from the "clonal trait space" into the frameworks provided by the aboveground trait and the fine-root economics spaces, thereby enhancing our comprehension of the multifaceted trait strategies exhibited by plants.</p>
Clonally resolved spatial transcriptomics data of mouse spleen
<p>The BGI Stereo-seq strategy was applied to a mouse spleen sample containing SPLINTR barcoded AML cells.</p> <p>Data generated with <a href="https://github.com/DaneVass/bartools_manuscript_code/blob/main/spatial-analysis/data_preprocessing_m4_paper.py" target="_blank" rel="noopener">https://github.com/DaneVass/bartools_manuscript_code/blob/main/spatial-analysis/data_preprocessing_m4_paper.py</a>.</p> <p>mouse4_bin*_bc_counts.tsv:<br>Binned barcode counts across whole slide.<br>Can be merged with AnnData file by `cell_id`.<br>Contains all barcodes detected in a bin (`barcode`) and UMI counts summed by bin (`count_binned`).<br>`isin_adata` marks whether the bin is on the manually segmented tissue section.</p> <p>mouse4_bin*_bc_counts_top1.tsv:<br>Binned barcode counts on tissue section, barcode with most UMI per bin is selected. </p> <p>mouse4_bin*_bc.h5ad:<br>Binned stereo-seq data with barcode information.</p> <p>mouse4_bin*_bc_clustered.h5ad:<br>Filtered, log1p transformed, scaled, clustered stereo-seq data.<br>Data is not zero centered for bin10 for memory efficiency.</p>
Data from: Inter-clonal competition over queen succession imposes a cost of parthenogenesis on termite colonies
<p>In social insect colonies, selfish behaviour due to intracolonial conflict among members can result in colony-level costs despite close relatedness. In certain termite species, queens use asexual reproduction for within-colony queen succession but rely on sexual reproduction for worker and alate production, resulting in multiple half-clones of a single primary queen competing for personal reproduction. Our study demonstrates that competition over asexual queen succession among different clone types leads to the overproduction of parthenogenetic offspring, resulting in the production of dysfunctional parthenogenetic alates. By genotyping the queens of 23 field colonies of <em>Reticulitermes speratus</em>, we found that clone variation in the queen population reduces as colonies develop. Field sampling of alates and primary reproductives of incipient colonies showed that overproduced parthenogenetic offspring develop into alates that have significantly smaller body sizes and much lower survivorship than sexually-produced alates. Our results indicate that while the production of earlier and more parthenogenetic eggs is advantageous for winning the competition for personal reproduction, it comes at a great cost to the colony. Thus, this study highlights the evolutionary interplay between individual-level and colony-level selection on parthenogenesis by queens.</p>
Erythropoietin directly remodels the clonal composition of murine hematopoietic multipotent progenitor cells
<p>## In version 1 of the repository the scRNAseq data was corrupted -- in version 2 this has been corrected and the bam files of both scRNAseq runs have been uploaded ##</p> <p>This dataset consists of the raw sequencing files of 9 independent barcoding experiments and of one 10X Genomics scRNAseq experiment. These are the source files for the main figures of the associated publication.</p> <p>HSPCs (C-Kit+ Sca1+ CD150+ Flt3-) or MPP2 (C-Kit+ Sca1+ Flt3- CD150+ CD48+) were isolated form mouse bone marrow through flushing, MACS-enrichment and sorting. The cells were barcoded by spin infection for 6h, and cultured in StemSpanMedium SFEM with 50 ng/ml mSCF (STEMCELL Technologies) for 16h with or without human recombinant EPO (Eprex, erythropoietin alpha, Janssen) at 1000 ng/ml or 160 ng/ml. At this stage scRNAseq was perfromed on the 10X Chromium platfom (10X Genomics), or cells were transplanted by tail vein injection into 6Gy irradiated recipient mice. When appropirate an additional injection of EPO 133ug/kg was given at the moment of transplantation. Different mature hematopoietic cells were isolated form the transplanted mice after 4 weeks or 16 weeks.</p> <p>For barcoding experiments, a three-step PCR was performed to amplify barcode sequences, to add Read1 and Read2 Illumina sequencing adapters, P5 and P3 flow cell attachment sites as well as plate and sample indices. Libraries were sequenced on an Illumina HiSeq SR65 with 10% of PhiX spike-in. For scRNAseq experiment, libraries were made using the Chromium SIngle Cell 3' v2 kit and sequencing was performed on a HiSeq PE26-98.</p> <p>The repository encompasses the following datasets:</p> <ul> <li>A1006.tar.gz -- AE05Low -- HSPCs EPO 160 ng/ml + injection 4 weeks -- main figure 2</li> <li>A1007.tar.gz -- AE05High -- HSPCs EPO 1000 ng/ml + injection 4 weeks -- main figure 2</li> <li>A984.tar.gz -- AE03Low -- HSPCs EPO 160 ng/ml 4 weeks -- main figure 2 and HSPC part of main figure 4</li> <li>A1008.tar.gz -- AE03High -- HSPCs EPO 1000 ng/ml 4 weeks -- main figure 1, 2 and DC part of main figure 3</li> <li>A1012.tar.gz -- AE04Low -- HSPCs EPO 160 ng/ml 4 months -- main figure 8</li> <li>A1013.tar.gz -- AE04High -- HSPCs EPO 1000 ng/ml 4 months -- main figure 8</li> <li>A1105.tar.gz -- AE07part1 -- HSPCs EPO 1000 ng/ml 4 weeks part 1 -- MkP part of main figure 3</li> <li>A1107.tar.gz -- AE07part2 -- HSPCs EPO 1000 ng/ml 4 weeks part 2 -- MkP part of main figure 3</li> <li>A1166.tar.gz -- AE13part1 -- HSPCs EPO 1000 ng/ml 4 weeks part 1 -- HSPC part of main figure 4</li> <li>A1166.tar.gz -- AE13part2 -- HSPCs EPO 1000 ng/ml 4 weeks part 2 -- HSPC part of main figure 4</li> <li>D757_3697.tar.gz -- LP26MPP2 -- MPP2 EPO 1000 ng/ml 4 weeks -- main figure 7</li> </ul> <p>In version two of the repository the scRNAseq data is changed into:</p> <ul> <li>possorted_genome_bam_T1.bam -- 10X of EPO exposed (T1) HSPCs -- main figure 5 and 6</li> <li>possorted_genome_bam_T2.bam -- 10X of control (T2) HSPCs -- main figure 5 and 6</li> </ul> <p>The folder for each barcode experiment encompasses fastq files for each sample index used in the experiment. These have to be further de-multiplexed by plate index and barcode reads have to be called. These, and all subsequent processing steps till the making of the main figures are described in the github folder accompanying the associated publication.</p> <p> </p> <p> </p> <p> </p> <p> </p>
Variation in the location and timing of experimental severing demonstrates that the persistent rhizome serves multiple functions in a clonal forest understory herb
<p>1. In clonal plants, persistent rhizomes can serve multiple purposes, including resource storage, modulation of heterogenous resource distributions, maintenance of bud banks and promotion of recovery from disturbance. Clonal plants are commonly long-lived and, in temperate zones, often exhibit organ preformation. Thus, investigations of how the timing of disturbance to the rhizome affects plant performance must occur over multiple growing seasons, but these types of studies are rare.</p> <p>2. We conducted a field experiment to examine how the persistent rhizome supports the existing shoot, new ramet production, and recovery from damage using mayapple (<i>Podophyllum peltatum</i>; Berberidaceae), a common herbaceous perennial of low-light forest understories in Eastern North America. Mayapple maintains a long-lived rhizome and exhibits a developmentally-programmed seasonal pattern of resource transport and new ramet initiation. We varied both the position and timing of rhizome severing in rhizome systems with terminal sexual or vegetative shoots, and tracked plants for two years following severing.</p> <p>3. The location and timing of severing affected both plant persistence (production of new shoots) and performance (leaf area), with effects differing for new shoots at the front vs. the back of the rhizome system. Across years, severing location and past years' shoot size influenced plant persistence and performance, while the effect of timing of severing diminished; initial sexual status had little effect on rhizome system response that was not accounted for by initial leaf area. Severing generally led to the establishment of two independent rhizome systems. Relative to unmanipulated control systems, these two systems had more total leaf area, but less average leaf area per system.</p> <p>4. Synthesis. Our results point to the rhizome as a resource integrator that affects plant responses to disturbance immediately following damage and in subsequent growing seasons. Rhizome bud age and/or subtending rhizome size, and developmental program influence responses to disturbance. While the effects of experimental disturbance on plant performance decreased two years after disturbance, further long-term investigation is needed to fully understand the demographic consequences of damage to persistent rhizomes. </p>
DNA methylation in clonal Duckweed lineages (Lemna minor L.) reflects current and historical environmental exposures.
<p>The following depository contains raw phenotypic data and intermediate DNA methylation data presented in the article <strong>"DNA methylation in clonal Duckweed lineages (<em>Lemna minor </em>L.) reflects current and historical environmental exposures.</strong>" :</p> <p><strong>1) Raw phenotypic data</strong></p> <p>- Frond_area_Phase1_Phase2 -> Frond area measured at different time points (week 1, 6, 7 and 8) during the experiment.</p> <p>- Frond_number_Phase1_Phase2 -> Frond number measured at different time points (week 1, 6, 7 and 8) during the experiment.</p> <p><strong>2) Intermediate files obtained from running the epiGBS2 pipeline. The following files are available:</strong></p> <p>- consensus_cluster.renamed.fa -> epiGBS <em>de novo </em>loci. This file consists of the <em>de novo </em>epiGBS reference sequence file obtained during the <em>de novo </em>reference creation.</p> <p>- methylation.filtMETH -> The filtered DNA methylation data. This data was obtained after filtering the raw DNA methylation data. Cytosines which had a 10X coverage or higher and which were present in 80% of all samples were kept for further analysis.</p> <p>Demultiplexed and raw data were deposited at NCBI: BioProject: <strong>PRJNA883550</strong></p>
Genetic structure in patchy populations of a candidate foundation plant: a case study of Leymus chinensis using genetic and clonal diversity
<p><strong>PREMISE</strong>: The distribution of genetic diversity on the landscape has critical ecological and evolutionary implications. This may be especially the case on a local scale for foundation plant species since they create and define ecological communities, contributing disproportionately to ecosystem function.</p> <p><strong>METHODS</strong>: We examined the distribution of genetic diversity and clones, which we defined first as unique multilocus genotypes (MLG), and then by grouping similar MLGs into multilocus lineages (MLL). We used 186 markers from inter-simple sequence repeats (ISSR) across 358 ramets from 13 patches of the foundation grass <em>Leymus chinensis</em>. We examined the relationship between genetic and clonal diversities, their variation with patch-size, and the effect of the number of markers used to evaluate genetic diversity and structure in this species.</p> <p><strong>RESULTS</strong>: Every ramet had a unique MLG. Almost all patches consisted of individuals belonging to a single MLL. We confirmed this with a clustering algorithm to group related genotypes. The predominance of a single lineage within each patch could be the result of the accumulation of somatic mutations, limited dispersal, some sexual reproduction with partners mainly restricted to the same patch, or a combination of all three.</p> <p><strong>CONCLUSIONS</strong>: We found strong genetic structure among patches of <em>L. chinensis</em>. Consistent with previous work on the species, the clustering of similar genotypes within patches suggests that clonal reproduction combined with somatic mutation, limited dispersal, and some degree of sexual reproduction among neighbors causes individuals within a patch to be more closely related than among patches.</p>
Fig. 4 in Clonal Diversity Of Otiorhynchus Ligustici And O. Raucus (Coleoptera, Curculionidae) In Central Ukraine
Fig. 4. The polyclonal structure of two species genus Otiorhynchus samples from Kyiv vicinities: L1–L9 — O. ligustici clones; R1–R7 — O. raucus clones.
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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.