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1,023 results for “Copy Number”
Chemical composition, soil water content and 16S rRNA and ITS gene copy numbers of soil aggregates and bulk soil samples
<p>This repository contains all data to reproduce the analyses presented in "Distinct microbial communities are linked to organic matter properties in millimetre-sized soil aggregates", Simon et al 2024, <em>The ISME Journal </em>(DOI: 10.1093/ismejo/wrae156).</p>
Raw read counts and phased SNP counts for every single cell in the sequencing datasets of the breast cancer patient S1 from "Characterizing allele- and haplotype-specific copy numbers in single cells with CHISEL"
<p>This dataset contains the raw read counts and phased SNP counts for every single cell in the sequencing datasets of breast cancer patient S1 from “Characterizing allele- and haplotype-specific copy numbers in single cells with CHISEL” [Zaccaria & Raphael, 2020]. These data enable the full reproduction of all the results in the related manuscript for breast cancer patient S1. Specifically, the data are provided in two files for every dataset <em>DAT</em> of patient S1 with the following format:</p> <ol> <li><em>DAT.raw</em>_<em>read</em>_<em>counts.bed.gz </em>is a multi-cell BED file containing the raw read counts in the following fields: <ul> <li>CHROMOSOME: the name of a human chromosome</li> <li>START: the starting genomic position of a genomic bin in the chromosome</li> <li>END: the ending genomic position of the genomic bin in the chromosome</li> <li>CELL: the cell barcode that uniquely identifies a cell</li> <li>NORMAL: the raw read count for the specified bin from a matched-normal sample</li> <li>COUNT: the raw read count for the specified bin in the specified cell</li> <li>RDR: the estimated read-depth ratio for the specified bin in the specified cell</li> </ul> </li> <li><em>DAT.phased</em>_<em>snps</em>_<em>counts.pos.gz </em>is a multi-cell POS file containing the phased SNP counts in the following fields: <ul> <li>CHROMOSOME: the name of a human chromosome</li> <li>POS: the genomic position in the chromosome of a germline SNP</li> <li>CELL: the cell barcode that uniquely identifies a cell</li> <li>COUNT_HAPLOTYPE_A: the count of reads that cover the SNP and that belong to haplotype A in the specified cell</li> <li>COUNT_HAPLOTYPE_B: the count of reads that cover the SNP and that belong to haplotype B in the specified cell</li> </ul> </li> </ol> <p>All the files have been compressed using standard <em>gzip</em>.</p>
Raw read counts and phased SNP counts for every single cell in the sequencing datasets of the breast cancer patient S0 from "Characterizing allele- and haplotype-specific copy numbers in single cells with CHISEL"
<p>This dataset contains the raw read counts and phased SNP counts for every single cell in the sequencing datasets of breast cancer patient S0 from “Characterizing allele- and haplotype-specific copy numbers in single cells with CHISEL” [Zaccaria & Raphael, 2020]. These data enable the full reproduction of all the results in the related manuscript for breast cancer patient S0. Specifically, the data are provided in two files for every dataset <em>DAT</em> of patient S0 with the following format:</p> <ol> <li><em>DAT.raw</em>_<em>read</em>_<em>counts.bed.gz </em>is a multi-cell BED file containing the raw read counts in the following fields: <ul> <li>CHROMOSOME: the name of a human chromosome</li> <li>START: the starting genomic position of a genomic bin in the chromosome</li> <li>END: the ending genomic position of the genomic bin in the chromosome</li> <li>CELL: the cell barcode that uniquely identifies a cell</li> <li>NORMAL: the raw read count for the specified bin from a matched-normal sample</li> <li>COUNT: the raw read count for the specified bin in the specified cell</li> <li>RDR: the estimated read-depth ratio for the specified bin in the specified cell</li> </ul> </li> <li><em>DAT.phased</em>_<em>snps</em>_<em>counts.pos.gz </em>is a multi-cell POS file containing the phased SNP counts in the following fields: <ul> <li>CHROMOSOME: the name of a human chromosome</li> <li>POS: the genomic position in the chromosome of a germline SNP</li> <li>CELL: the cell barcode that uniquely identifies a cell</li> <li>COUNT_HAPLOTYPE_A: the count of reads that cover the SNP and that belong to haplotype A in the specified cell</li> <li>COUNT_HAPLOTYPE_B: the count of reads that cover the SNP and that belong to haplotype B in the specified cell</li> </ul> </li> </ol> <p>All the files have been compressed using standard <em>gzip</em>.</p>
Soil Bacteria Community-Weighted rrn Operon Copy Number Estimation
<p>Datasets and R-Scripts for estimating community-weighted rrn operon copy number for soil bacteria communities collected from the Yukon-Kuskokwim River Delta, AK, USA, and from La Selva Biological Station, Costa Rica. File descriptions follow:</p> <p>"rrnDB_copy_number_database.csv": The Ribosomal RNA Database downloaded from <a href="rrndb.umms.med.umich.edu.">rrndb.umms.med.umich.edu.</a> Citation: </p> <ul> <li>Stoddard S.F, Smith B.J., Hein R., Roller B.R.K. and Schmidt T.M. (2015) <em>rrn</em>DB: improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development. <em>Nucleic Acids Research</em> 2014; doi: 10.1093/nar/gku1201 [<a href="http://www.ncbi.nlm.nih.gov/pubmed/25414355">PMID:25414355</a></li> </ul> <p>"AK_16S_Genus_Abundance.csv": Count of ASVs by taxon (assigned to genus level) present in each soil sample collected in the Yukon_Kuskokwim River Delta, AK, USA.</p> <p>"Costa_Rica_16S_OTU_Abundance": Count of OTUs by taxon present in each soil sample collected in La Selva Biological Station, Costa Rica.</p> <p>"Alaska_rrn_copy_number_estimation_script.R": an R script for processing Alaska ASV count table and estimating community-weighted rrn operon copy numbers for each soil sample.</p> <p>"CostaRica_rrn_copy_number_estimation_script.R": an R script for processing Costa Rica OTU count table and estimating community-weighted rrn operon copy numbers for each soil sample.</p>
High MHC gene copy number maintains diversity despite homozygosity in a Critically Endangered single-island endemic bird, but no evidence of MHC-based mate choice
<p>Raw sequence data from two amplicon libraries of MHC class I exon 3 of Raso Lark <em>Alauda razae</em>, sequenced on an Illumina Miseq. The two different libraries (two different Illumina runs) are collected in separat tar archive (.tar). Within each of those are individual sequence reads as gzipped fastq files (.fastq.gz). Each sample has two files, one for read 1 (R1) and one for read 2 (R2), with file names structured as follows. Delimited by underscore (_) are:</p> <ol> <li>sample name as referred to in the data and paper (“RingNo” in the Supporting data table);</li> <li>formal ID (also referred to in data table, often corresponding to full ring number);</li> <li>Illumina sample number (i.e. based on the order that samples are listed in the sample sheet);</li> <li>Illumina lane number (static as L001, as Miseq instruments have a single lane on their flow cells);</li> <li>read number (R1 [forward] or R2 [reverse]);</li> <li>static identifier from Illumina (001).</li> </ol> <p>Thus, the file 83304_TJ83304_S163_L001_R2_001.fastq.gz is the reverse (read 2) MHC class I exon 3 sequence of individual 83304 (ring number TJ83304).</p>
Analysis of copy number variation in dogs implicates genomic structural variation in the development of anterior cruciate ligament rupture
<p>Anterior cruciate ligament (ACL) rupture is an important condition of the human knee. Second ruptures are common and societal costs are substantial. Canine cranial cruciate ligament (CCL) rupture closely models the human disease. CCL rupture is common in the Labrador Retriever (5.79% prevalence), ~100-fold more prevalent than in humans. Labrador Retriever CCL rupture is a polygenic complex disease, based on genome-wide association study (GWAS) of single nucleotide polymorphism (SNP) markers. Dissection of genetic variation in complex traits can be enhanced by studying structural variation, including copy number variants (CNVs). Dogs are an ideal model for CNV research because of reduced genetic variability within breeds and extensive phenotypic diversity across breeds. We studied the genetic etiology of CCL rupture by association analysis of CNV regions (CNVRs) using 110 case and 164 control Labrador Retrievers. CNVs were called from SNPs using three different programs (PennCNV, CNVPartition, and QuantiSNP). After quality control, CNV calls were combined to create CNVRs using ParseCNV and an association analysis was performed. We found no strong effect CNVRs but found 46 small effect (max(T) permutation P<0.05) CCL rupture associated CNVRs in 22 autosomes; 25 were deletions and 21 were duplications. Of the 46 CCL rupture associated CNVRs, we identified 39 unique regions. Thirty four were identified by a single calling algorithm, 3 were identified by two calling algorithms, and 2 were identified by all three algorithms. For 42 of the associated CNVRs, frequency in the population was <10% while 4 occurred at a frequency in the population ranging from 10-25%. Average CNVR length was 198,872bp and CNVRs covered 0.11 to 0.15% of the genome. All CNVRs were associated with case status. CNVRs did not overlap previous canine CCL rupture risk loci identified by GWAS. Associated CNVRs contained 152 annotated genes; 12 CNVRs did not have genes mapped to CanFam3.1. Using pathway analysis, a cluster of 19 homeobox domain transcript regulator genes was associated with CCL rupture (P=6.6E-13). This gene cluster influences cranial-caudal body pattern formation during embryonic limb development. Clustered genes were found in 3 CNVRs on chromosome 14 (HoxA), 28 (NKX6-2), and 36 (HoxD). When analysis was limited to deletion CNVRs, the association was strengthened (P=8.7E-16). This study suggests a component of the polygenic risk of CCL rupture in Labrador Retrievers is associated with small effect CNVs and may include aspects of stifle morphology regulated by homeobox domain transcript regulator genes.</p>
CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data
<p>To date, ancient genome analyses have been largely confined to the study of single nucleotide polymorphisms (SNPs). Copy number variants (CNVs) are a major contributor of disease and of evolutionary adaptation, but identifying CNVs in ancient shotgun-sequenced genomes is hampered by (i) most published genomes being <1x coverage, (ii) ancient DNA fragments being typically <80 bps. These characteristics preclude state-of-the-art CNV detection software to be effectively applied to ancient genomes. Here we present CONGA, an algorithm tailored for genotyping deletion and duplication events in genomes with low depths of coverage. Simulations and down-sampling experiments show that CONGA can genotype deletions >1 kbps with F-scores >0.75 at >=1x, and distinguish between heterozygous and homozygous states. Using CONGA, we analyse deletion events at 10,018 loci in 56 ancient human genomes spanning the last 50,000 years, with coverages 0.4x-26x. We show that inter-individual genetic diversity measured using deletions and SNPs are highly correlated, as in modern-day genomes, confirming that deletion frequencies broadly reflect demographic history. We also identify signatures of strong purifying selection on deletions in ancient-genomes, such as an excess of singletons compared to those in SNPs. CONGA paves the way for systematic studies of drift, mutation load, and adaptation in ancient and modern-day gene pools through the lens of CNVs.</p>
Bacterial Community Weighted rrn Operon Copy Numbers and Enzyme Activity in Costa Rica and Alaska Soils.
<p>Datasets of bacterial community weighted rrn operon copy number and enzyme activity in Alaska and Costa Rica soils. The Alaska soils were collected from across four elevational terraces in a tidal wetland on the western coast. The Costa Rica soils were collected from plots subjected to precipitation manipulation treatments in La Selva Biological Research Station. </p> <p>The variable descriptions for the Alaska dataset are as follows: simple_id: an identifier variable. id: an identifier variable that includes terrace identity. transect_id: a variable that identifies collection transect location. BG_umol_g_h: the activity rate of beta-glucosiadase in micromoles per gram soil per hour. NAG_umol_g_h: the activity rate of N-acetyl-glucosaminidase in micromoles per gram soil per hour. LAP_umol_g_h: activity rate of leucine-aminopeptidase in micromoles per grams soil per hour. AP_umol_g_h: the activity rate of acid phosphatase in micromoles per gram soil per hour. BG_g_C: the activity rate of beta-glucosiadase in micromoles per gram soil carbon per hour. NAG-g_N: activity rate of N-acetyl-glucosaminidase in micromoles per gram soil nitrogen per hour. LAP_g_N: activity rate of leucine-aminopeptidase in micromoles per gram soil nitrogen per hour. AP_mg_P: activity rate of acid-phosphatase in micromoles per gram soil phosphorus per hour. P_mg_kg: soil phosphorus concentration in milligrams phosphorus per kilogram soil. K_mg_kg: soil potassium concentration in milligrams potassium per kilogram soil. C_pct: soil carbon concentration in percent. N_pct: soil nitrogen concentration in percent. pH: soil pH. cn_ratio: the carbon-to-nitrogen ratio of soil. cp_ratio: the carbon-to-phosphorus ratio of soil. np_ratio: the nitrogen to phosphorus ratio of soil. weighted_copy_number: the bacterial community weighted rrn operon copy number.</p> <p>The variable descriptions for the Costa Rica dataset are as follows: ID: a variable that identifies the soil core collected. Plot: a variable that identifies the experimental plot from which soils were collected. Precip: a variable that describes the precipitation manipulation treatment applied. Core: a variable that identifies whether soil cores were enclosed in mesh or not. Moisture: the soil moisture of the collected core in grams water per grams dry soil. weighted copy_number: the bacterial community weighted rrn operon copy number. AP: activity rate of acid-phosphatase in micromoles per gram soil per hour. BG: the activity rate of beta-glucosiadase in micromoles per gram soil per hour.</p> <p>Also included are files of the code used to analyze the data in the R Statistical Computing Environment.</p>
Rare Genomic Copy Number Variants Implicate New Candidate Genes for Bicuspid Aortic Valve
<p>Whole genome genotyping data in dbGAP format and copy number variant calls in dbVar format.</p> <p>dbVar data includes CNV calls from cases with early onset bicuspid aortic valve disease (EBAV), cases from the International BAV Consortium (BAVCon), and controls from the dbGAP Wisconsin Longitudinal Study on Aging dataset (WLS).</p> <p>dbGAP files are divided into 12 batches of genotypes from EBAV subjects (EBAV1-12):</p> <p>1) PLINK output files (.map and .ped)</p> <p>2) GenomeStudio Final Report files</p> <p>3) One master pedigree file</p> <p>4) dbGAP subject mapping files</p> <p> </p>
Supporting data for RCANE: A Deep Learning Algorithm for Whole-genome Pan-Cancer Somatic Copy Number Aberration Prediction using RNA-seq Data.
<p>This is the data repository for <em>RCANE: A Deep Learning Algorithm for Whole-genome Pan-Cancer Somatic Copy Number Aberration Prediction using RNA-seq Data</em>. To use this dataset, please refer to <a href="https://github.com/HowardGech/RCANE" target="_blank" rel="noopener">https://github.com/HowardGech/RCANE</a>.</p>
Dataset for: Ace and ace-like genes of invasive redlegged earth mite: Copy number variation, target-site mutations, and their associations with organophosphate insensitivity
<p class="MsoNormal">This repository contains the scripts and data required to replicate the analyses in Thia et al.'s, "Evolution of an acetylcholinesterase<em> </em>gene complex and its contribution toward organophosphate insensitivity in an invasive mite pest", submitted to <em>Pest Management Science</em>.</p> <p class="MsoNormal">In this work, Thia et al. use a combination of experimental selection and pool-seq genomic analyses to understand the genetic mechanisms underpinning organophosphate insensitivity in the redlegged earth mite, <em>Halotydeus destructor</em>. There is a special emphasis on disentangling the roles of copy number variation and target-site mutations in the acetylcholinesterase genes, <em>ace,</em> and radiated <em>ace</em>-like genes<span>.</span></p> <p class="MsoNormal">There are three major analyses: (1) an F<sub>ST</sub> genome scan to identify outlier loci between alive (insensitive) and dead (sensitive) mites; (2) an analysis of <em>ace </em>copy number variation between alive and dead mites; and (3) an analysis of candidate target-site mutations in the <em>ace</em> gene.</p>
CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples
<p>This folder includes simulated and real data used in validating CNETML, a new maximum likelihood method designed to reconstruct the evolutionary history of multiple samples of a single patient which may be taken at different locations and/or times, which can take as input (relative) total integer copy numbers called from shallow whole genome sequencing data.</p>
Copy number variations and their effect on the plasma proteome | Associations
<p>Results and supplementary data from a GWAS investigation the relationship of CNVs and blood protein measurements.</p>
Dataset for: Ace and ace-like genes of invasive redlegged earth mite: Copy number variation, target-site mutations, and their associations with organophosphate insensitivity
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Analysis of copy number variation in dogs implicates genomic structural variation in the development of anterior cruciate ligament rupture
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Prickly postglacial pioneers: freshwater plankton community composition influences fatty acid desaturase (FADS2) copy number in Southern Greenland threespine sticklebacks
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Copy number variants outperform SNPs to reveal genotype-temperature association in a marine species
<p>Copy number variants (CNVs) are a major component of genotypic and phenotypic variation in genomes. To date, our knowledge of genotypic variation and evolution has largely been acquired by means of single nucleotide polymorphism (SNPs) analyses. Until recently, the adaptive role of structural variants (SVs) and particularly that of CNVs has been overlooked in wild populations, partly due to their challenging identification. Here, we document the usefulness of Rapture, a derived reduced‐representation shotgun sequencing approach, to detect and investigate copy number variants (CNVs) alongside SNPs in American lobster (<i>Homarus americanus</i>) populations. We conducted a comparative study to examine the potential role of SNPs and CNVs in local adaptation by sequencing 1,141 lobsters from 21 sampling sites within the southern Gulf of St. Lawrence, which experiences the highest yearly thermal variance of the Canadian marine coastal waters. Our results demonstrated that CNVs account for higher genetic differentiation than SNP markers. Contrary to SNPs, for which no significant genetic–environment association was found, 48 CNV candidates were significantly associated with the annual variance of sea surface temperature, leading to the genetic clustering of sampling locations despite their geographic separation. Altogether, we provide a strong empirical case that CNVs putatively contribute to local adaptation in marine species and unveil stronger spatial signal of population structure than SNPs. Our study provides the means to study CNVs in nonmodel species and highlights the importance of considering structural variants alongside SNPs to enhance our understanding of ecological and evolutionary processes shaping adaptive population structure.</p>
Adaptation by copy number variation increases insecticide resistance in the fall armyworm (vcf files)
<p>Here, I deposite vcf files used for a paper, entitled 'Adaptation by copy number variation increases insecticide resistance in the fall armyworm'.</p> <p>genotype.vcf and SNP.filtered.vcf.gz have the information of CNVs and SNPs, respectively. </p>
Data from: Extreme copy number variation at a tRNA ligase gene affecting phenology and fitness in yellow monkeyflowers
Copy number variation (CNV) is a major part of the genetic diversity segregating within populations, but remains poorly understood relative to single nucleotide variation. Here, we report on a tRNA ligase gene (RLG1a) exhibiting unprecedented, and fitness-relevant, CNV within an annual population of the yellow monkeyflower Mimulus guttatus. Variation at RLG1a was associated with multiple traits in pooled population resequencing (PoolSeq) scans of phenotypic and phenological cohorts. Five of 35 (14%) of resequenced inbred lines carried three-copy variants of RLG1a (trip+), and trip+ lines exhibited elevated RLG1a expression. trip+ carriers, in addition to being over-represented in late-flowering and large-flowered PoolSeq populations, flowered later under stressful conditions in a greenhouse experiment (P < 0.05). In early-flowering wild cohorts, we discovered an additional rare variant (high+) that carries 250-300 copies of RLG1a totaling ~5.7Mb, equivalent to 20-40% of a chromosome. Mendelian segregation of diagnostic alleles and qPCR-based copy counts In the progeny of a high+ carrier, indicate that high+ is a single tandem array unlinked from the single copy RLG1a locus in the reference genome. In the wild, high+ carriers had highest fitness in two dry and/or hot years (2015 and 2017; both P < 0.01), while single copy individuals were twice as fecund as either CNV genotype in a lush year (2016: p < 0.005). Our results demonstrate fluctuating selection on CNVs affecting phenological traits in a wild population, suggest that plant tRNA ligases mediate stress-responsive life-history traits, and introduce a novel system for investigating the molecular mechanisms of gene amplification.
Somatic copy number and structural variation in RPE-1 cells with induced chromosomal instability
<p><span><span><span><span><span><span><span><span><span><span><span>The chromosome breakage-fusion-bridge (BFB) cycle is a mutational process that produces gene amplification and genome instability. Signatures of BFB cycles can be observed in cancer genomes alongside chromothripsis, another catastrophic mutational phenomenon. Here, we explain this association by elucidating a mutational cascade, downstream of <a>th</a></span></span></span></span></span></span></span></span></span></span></span><span><span><span><span><span><span><span><span><span><span><span>e single cell division error of chromosome bridge formation, that rapidly generates extreme genomic complexity. We show that actomyosin forces are required for initial bridge breakage and mutagenesis, following which chromothripsis accumulates with aberrant interphase replication of bridge DNA. This is then followed by an unexpected burst of DNA replication in the next mitosis, generating extensive DNA damage. During this second cell division, broken bridge chromosomes frequently mis-segregate and form micronuclei, promoting additional chromothripsis. We <a>fu</a></span></span></span></span></span></span></span></span></span></span></span><span><span><span><span><span><span><span><span><span><span><span>rther show that this mutational cascade generates the continuing evolution and sub-clonal heterogeneity characteristic of many human cancers.</span></span></span></span></span></span></span></span></span></span></span></p>
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