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Genomic Library

Genomic Libraries are collections of DNA fragments that represent the complete genetic material of an organism.
They are commonly used in genetic research to study gene structure, expression, and function.
These libraries are typically created by extracting and fragmenting genomic DNA, then inserting the fragments into vectors for storage and replication in host cells.
Researchers can then screen the libraries to identify specific genes or genomic regions of interest.
Accurate and reproducible methods for constructing and utilizing genomic libraries are essential for advancing our understaning of genomes and facilitating advanaces in areas like personalized medicine and evolutionary biology.
PubCompare.ai's AI-powered tools can help optimze your genomic library reserch by identifying the best protocols from published literature, pre-prints, and patents, ensuring the quality and reliability of your work.

Most cited protocols related to «Genomic Library»

We sequenced all the cDNA libraries with an Illumina Genome Analyzer IIx. We pooled the four S. pombe libraries together with four other indexed libraries and sequenced them using eight lanes of 76 nucleotide paired reads. We sequenced the mouse library using two lanes of 76 nucleotide paired reads.
Publication 2011
cDNA Library DNA, Complementary DNA Library Genome Genomic Library Mice, House Nucleotides
We sequenced all the cDNA libraries with an Illumina Genome Analyzer IIx. We pooled the four S. pombe libraries together with four other indexed libraries and sequenced them using eight lanes of 76 nucleotide paired reads. We sequenced the mouse library using two lanes of 76 nucleotide paired reads.
Publication 2011
cDNA Library DNA, Complementary DNA Library Genome Genomic Library Mice, House Nucleotides
Double-stranded cDNA of eight human tissues (brain, heart, kidney, testis, liver, spleen, lung, and skeletal muscle) were generated with the Marathon cDNA amplification kit (Clontech). The cDNA concentration was normalized by quantitative PCR against AGPAT1 and EEF1A1 genes. The PCRs were performed in 386-well plates in a total volume of 12.5 μLl. One microliter of normalized cDNA was mixed with JumpStart REDTaq ReadyMix (Sigma) and primers (4 μM) with a Freedom evo robot (TECAN). The 10 first cycles of amplification were performed with a touchdown annealing temperature decreasing 1°C per cycle from 65°C to 55°C; annealing temperature of the next 30 cycles was carried out at 55°C. For each tissue, 2 μL of each RT-PCR reaction were pooled together and purified with the QIAquick PCR purification Kit (Qiagen) according to the manufacturer's recommendations. This purified DNA was directly used to generate a sequencing library with the “Genomic DNA sample prep kit” (Illumina) according to the manufacturer's recommendations with the exclusion of the fragmentation step. This library was subsequently sequenced on an Illumina Genome Analyzer 2 platform.
Publication 2012
Brain cDNA Library DNA, Complementary EEF1A1 protein, human Genes Genome Genomic Library Heart Homo sapiens Kidney Liver Lung Marathon composite resin Oligonucleotide Primers Reverse Transcriptase Polymerase Chain Reaction Skeletal Muscles Spleen Testis Tissues
Efficient implementation of Kraken’s classification algorithm requires that the mapping of k-mers to taxa is performed by querying a pre-computed database. Kraken creates this database through a multi-step process, beginning with the selection of a library of genomic sequences. Kraken includes a default library, based on completed microbial genomes in the National Center for Biotechnology Information’s (NCBI) RefSeq database, but the library can be customized as needed by individual users [18 (link)].
Once the library is chosen, we use the Jellyfish multithreaded k-mer counter [19 (link)] to create a database containing every distinct 31-mer in the library. Once the database is complete, the 4-byte spaces Jellyfish used to store the k-mer counts in the database file are instead used by Kraken to store the taxonomic ID numbers of the k-mers’ LCA values. After the database has been created by Jellyfish, the genomic sequences in the library are processed one at a time. For each sequence, the taxon associated with it is used to set the stored LCA values of all k-mers in the sequence. As sequences are processed, if a k-mer from a sequence has had its LCA value previously set, then the LCA of the stored value and the current sequence’s taxon is calculated and that LCA is stored for the k-mer. Taxon information is obtained from the NCBI taxonomy database.
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Publication 2014
DNA Library Genome, Microbial Genomic Library
A Chromium Controller Instrument (10x Genomics) was used for sample preparation. The platform allows for the construction of eight sequencing libraries by a single person in 2 d. Sample indexing and partition barcoded libraries were prepared using the Chromium Genome Reagent Kit (10x Genomics) according to manufacturer's protocols described in the Chromium Genome User Guide Rev A (https://support.10xgenomics.com/de-novo-assembly/sample-prep/doc/user-guide-chromium-genome-reagent-kit-v1-chemistry). Briefly, in the microfluidic Genome Chip, a library of Genome Gel Beads was combined with an optimal amount of HMW template gDNA in Master Mix and partitioning oil to create GEMs. Template gDNA (1.25 ng) was partitioned across approximately 1 million GEMs, with the exception of the peripheral blood sample, which utilized 1 ng of template gDNA. Upon dissolution of the Genome Gel Bead in the GEM, primers containing (1) an lllumina R1 sequence (Read 1 sequencing primer), (2) a 16-bp 10x Barcode, and (3) a 6-bp random primer sequence were released. GEM reactions were isothermally incubated (for 3 h at 30°C ; for 10 min at 65°C; held at 4°C), and barcoded fragments ranging from a few to several hundred base pairs were generated. After incubation, the GEMs were broken and the barcoded DNA was recovered. Silane and Solid Phase Reversible Immobilization (SPRI) beads were used to purify and size select the fragments for library preparation.
Standard library prep was performed according to the manufacturer's instructions described in the Chromium Genome User Guide Rev A (https://support.10xgenomics.com/de-novo-assembly/sample-prep/doc/user-guide-chromium-genome-reagent-kit-v1-chemistry) to construct sample-indexed libraries using 10x Genomics adaptors. The final libraries contained the P5 and P7 primers used in lllumina bridge amplification. The barcode sequencing libraries were then quantified by qPCR (KAPA Biosystems Library Quantification Kit for Illumina platforms). Sequencing was conducted with an Illumina HiSeq X with 2×150 paired-end reads based on the manufacturer's protocols.
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Publication 2017
ARID1A protein, human BLOOD Chromium DNA Chips DNA Library Gemini of Coiled Bodies Genome Genomic Library Immobilization Maritally Unattached Oligonucleotide Primers Silanes

Most recents protocols related to «Genomic Library»

Example 3

We generated and analyzed a collection of 14 early-passage (passage ≤9) human pES cell lines for the persistence of haploid cells. All cell lines originated from activated oocytes displaying second polar body extrusion and a single pronucleus. We initially utilized chromosome counting by metaphase spreading and G-banding as a method for unambiguous and quantitative discovery of rare haploid nuclei. Among ten individual pES cell lines, a low proportion of haploid metaphases was found exclusively in a single cell line, pES10 (1.3%, Table 1B). We also used viable FACS with Hoechst 33342 staining, aiming to isolate cells with a DNA content corresponding to less than two chromosomal copies (2c) from four additional lines, leading to the successful enrichment of haploid cells from a second cell line, pES12 (Table 2).

Two individual haploid-enriched ES cell lines were established from both pES10 and pES12 (hereafter referred to as h-pES10 and h-pES12) within five to six rounds of 1c-cell FACS enrichment and expansion (FIG. 1C (pES10), FIG. 5A (pES12)). These cell lines were grown in standard culture conditions for over 30 passages while including cells with a normal haploid karyotype (FIG. 1D, FIG. 5B). However, since diploidization occurred at a rate of 3-9% of the cells per day (FIG. 1E), cell sorting at every three to four passages was required for maintenance and analysis of haploid cells. Further, visualization of ploidy in adherent conditions was enabled by DNA fluorescence in situ hybridization (FISH) (FIG. 1F, FIG. 5c) and quantification of centromere protein foci (FIG. 1G, FIG. 5D; FIG. 6). In addition to their intact karyotype, haploid ES cells did not harbor significant copy number variations (CNVs) relative to their unsorted diploid counterparts (FIG. 5E). Importantly, we did not observe common duplications of specific regions in the two cell lines that would result in pseudo-diploidy. Therefore, genome integrity was preserved throughout haploid-cell isolation and maintenance. As expected, single nucleotide polymorphism (SNP) array analysis demonstrated complete homozygosity of diploid pES10 and pES12 cells across all chromosomes.

Both h-pES10 and h-pES12 exhibited classical human pluripotent stem cell features, including typical colony morphology and alkaline phosphatase activity (FIG. 2A, FIG. 2B). Single haploid ES cells expressed various hallmark pluripotency markers (NANOG, OCT4, SOX2, SSEA4 and TRA1-60), as confirmed in essentially pure haploid cultures by centromere foci quantification (>95% haploids) (FIG. 2C, FIG. 7). Notably, selective flow cytometry enabled to validate the expression of two human ES-cell-specific cell surface markers (TRA-1-60 and CLDN618) in single haploid cells (FIG. 2D). Moreover, sorted haploid and diploid ES cells showed highly similar transcriptional and epigenetic signatures of pluripotency genes (FIG. 2E, FIG. 2F). Since the haploid ES cells were derived as parthenotes, they featured distinct transcriptional and epigenetic profiles of maternal imprinting, owing to the absence of paternally-inherited alleles (FIG. 8).

Haploid cells are valuable for loss-of-function genetic screening because phenotypically-selectable mutants can be identified upon disruption of a single allele. To demonstrate the applicability of this principle in haploid human ES cells, we generated a genome-wide mutant library using a piggyBac transposon gene trap system that targets transcriptionally active loci (FIG. 2G, FIG. 8E), and screened for resistance to the purine analog 6-thioguanine (6-TG). Out of six isolated and analyzed 6-TG-resistant colonies, three harbored a gene trap insertion localizing to the nucleoside diphosphate linked moiety X-type motif 5 (NUDT5) autosomal gene (FIG. 2H). NUDT5 disruption was recently confirmed to confer 6-TG resistance in human cells,51 by acting upstream to the production of 5-phospho-D-ribose-1-pyrophosphate (PRPP), which serves as a phosphoribosyl donor in the hypoxanthine phosphoribosyltransferase 1 (HPRT1)-mediated conversion of 6-TG to thioguanosine monophosphate (TGMP) (FIG. 2I). Detection of a loss-of-function phenotype due to an autosomal mutation validates that genetic screening is feasible in haploid human ES cells.

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Patent 2024
Alkaline Phosphatase Alleles Cell Lines Cell Nucleus Cells Cell Separation Centromere Chromosomes Copy Number Polymorphism Diphosphates Diploid Cell Diploidy Embryonic Stem Cells Flow Cytometry Fluorescent in Situ Hybridization Genes Genes, vif Genitalia Genome Genomic Library Haploid Cell HOE 33342 Homo sapiens Homozygote Human Embryonic Stem Cells Hypoxanthine Phosphoribosyltransferase isolation Jumping Genes Karyotype Metaphase Mothers Mutation Nucleosides Oocytes Phenotype Pluripotent Stem Cells Polar Bodies POU5F1 protein, human Proteins purine Ribose Single Nucleotide Polymorphism SOX2 protein, human stage-specific embryonic antigen-4 Tissue Donors Transcription, Genetic
Not available on PMC !

Example 3

1 μL of genomic DNA was processed using a NEBNext dsDNA Fragmentase kit (New England Biolabs) by following the manufacturer's protocol. Incubation time was extended to 45 minutes at 37° C. The fragmentation reaction was stopped by adding 5 μL of 0.5M EDTA pH 8.0, and was purified by adding 2× volumes of Ampure XP beads (Beckman Coulter, A63881) according to the manufacturer's protocol. Fragmented DNA was analyzed on a Bioanalyzer with a High Sensitivity DNA kit (Agilent). The size range of fragmented DNA was typically from about 100 bp to about 200 bp with a peak of about 150 bp.

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Patent 2024
BP 100 DNA, Double-Stranded DNA Fragmentation Edetic Acid Genome Genomic Library Hypersensitivity
Genomic DNA was extracted from bacteria using a Nucleospin Microbial DNA kit (Thermo Fischer Scientific) as per manufacturer instructions. Further, the QIASeq FX DNA Library Kit (Qiagen) prepared genomic libraries for sequencing. L. amnigena PTJIIT1005 genome was sequenced on NGS (Next Generation Sequencing) Illumina NovaSeq6000 Platform by Redcliffe Lifetech, Noida. A total of 9,365,132 raw reads were obtained; 8,596,940 Illumina reads were de novo assembled using Unicycler (version 0.4.4). The assembled genome sequence was annotated by the tool Prokka 1.12. The complete genome sequence was submitted to NCBI.
Average Nucleotide Identity (ANI) [17 ] measures nucleotide-level genome similarity between the coding regions of two genomes. The complete genome sequence was submitted in FASTA format as an input file. This tool gives the similarity index percentage [18 (link)]. ANI is computed using the formula [19 ]: gANIG1G2=ΣbbhPercentIdentity.*AlignmentlengthlengthsofBBHgenes
Genome annotation of Lelliottia amnigena was done by RAST (Rapid Annotation using Subsystems Technology), PATRIC (The Pathosystems Resource Integration Center), and PGAP (Prokaryotic Genome Annotation Pipeline). Assembled genome sequence was submitted in RAST in FASTA format as input files, assigned functions to the genes. It also predicted the subsystems which were represented in the genome. By using this information, it reconstructs the metabolic network and makes the output file easily downloadable. Similarly, contigs were submitted in PATRIC as input files which provided annotation, subsystem summary, phylogenetic tree, and pathways. NCBI PGAP was used to annotate the bacterial genome where the complete genomic sequence was submitted in FASTA format as an input file, and it predicted the protein-coding regions and functional genome units like tRNAs, rRNA, pseudogenes, transposons, and mobile elements.
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Publication 2023
Bacteria DNA Library Genome Genome, Bacterial Genomic Library Jumping Genes Lelliottia amnigena Metabolic Networks Nucleotides Open Reading Frames Operator, Genetic Prokaryotic Cells Pseudogenes Radioallergosorbent Test Ribosomal RNA Transfer RNA
Total RNA was extracted separately from testis (n = 4) and ovary (n = 4) tissues using TRIzol (Invitrogen). For each sample, RNA quality and concentration were assessed using agarose gel electrophoresis, a NanoPhotometer spectrophotometer (Implen, CA), a Qubit 2.0 Fluorometer (ThermoFisher Scientific), and an Agilent BioAnalyzer 2,100 system (Agilent Technologies, CA), requiring an RNA integrity number (RIN) of 8.5 or higher; one ovary sample failed to meet these quality standards and was excluded from downstream analyses. Sequencing libraries were generated using the NEBNext Ultra RNA Library Prep Kit for Illumina following the manufacturer’s protocol. After cluster generation of the index-coded samples, the library was sequenced on one lane of an Illumina Hiseq 4,000 platform (PE 150). Transcriptome sequences were filtered using Trimmomatic-0.39 with default parameters (Bolger et al., 2014 (link)). 30, 848, 170 to 39, 695, 323 reads were retained for each testis or ovary sample, and in total, 290, 925, 984 reads remained, with a total length of 42, 385, 060,050 bp. Remaining reads of all testis and ovary samples were combined and assembled using Trinity 2.12.0 (Haas et al., 2013 (link)), yielding 573,144 contigs (i.e., putative assembled transcripts). Contigs were clustered using CD-hit-est (95% identity). Completeness of this final de novo transcriptome assembly were assessed using the BUSCO pipeline (Simao et al., 2015 (link)).
Expression levels of contigs in each sample were measured with Salmon (Patro et al., 2017 (link)), and contigs with no raw counts were removed. To annotate the remaining contigs containing autonomous TEs, BLASTp and BLASTx were used against Repbase with an E-value cutoff of 1E-5 and 1E-10, respectively. The aligned length coverage was set to exceed 80% of the queried transcriptome contigs. To annotate contigs containing non-autonomous TEs, RepeatMasker was used with our Ranodon-derived genomic repeat library of non-autonomous TEs (LARD-, TRIM-, MITE-, and SINE-annotated contigs) and the requirement that the transcriptome/genomic contig overlap was >80 bp long, >80% identical in sequence, and covered >80% of the length of the genomic contig. Contigs annotated as conflicting autonomous and non-autonomous TEs were filtered out.
To identify contigs that contained endogenous R. sibiricus genes, the Trinotate annotation suite (Bryant et al., 2017 (link)) was used with an E-value cutoff of 1E-5 for both BLASTx and BLASTp against the Uniport database, and 1E-5 for HMMER against the Pfam database (Wheeler and Eddy, 2013 (link)). To identify contigs that contained both a TE and an endogenous gene (i.e., putative cases where a TE and a gene were co-transcribed on a single transcript), all contigs that were annotated both by Repbase and Trinotate were examined, and the ones annotated by Trinotate to contain a TE-encoded protein (i.e., the contigs where Repbase and Trinotate annotations were in agreement) were not further considered. The remaining contigs annotated by Trinotate to contain a non-TE gene (i.e., an endogenous Ranodon gene) and also annotated either by Repbase to include a TE-encoded protein or by blastn to include a non-autonomous TE were filtered out for the expression analysis.
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Publication 2023
DNA Library Electrophoresis, Agar Gel Genes Genome Genomic Library Mites Ovary Proteins Salmo salar Short Interspersed Nucleotide Elements Synapsin I Testis Tissues TNFRSF25 protein, human Transcriptome trizol Uniport
A druggable genome sgRNA library (Supplementary Table S1) was lentivirally transduced into d4 neurons. Following 7-day Tun treatment, surviving neurons were collected and processed for sequencing. MAGeCK RRA16 (link) was used to perform gene essentiality and enrichment inference. See Supplementary Methods S1 for detailed protocol.
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Publication 2023
Genes Genomic Library Neurons

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The NovaSeq 6000 is a high-throughput sequencing system designed for large-scale genomic projects. It utilizes Illumina's sequencing by synthesis (SBS) technology to generate high-quality sequencing data. The NovaSeq 6000 can process multiple samples simultaneously and is capable of producing up to 6 Tb of data per run, making it suitable for a wide range of applications, including whole-genome sequencing, exome sequencing, and RNA sequencing.
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The HiSeq 2500 platform is a high-throughput DNA sequencing system designed for a wide range of genomic applications. It utilizes sequencing-by-synthesis technology to generate high-quality sequence data. The HiSeq 2500 platform is capable of producing up to 1 billion sequencing reads per run, making it a powerful tool for researchers and clinicians working in the field of genomics.
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The NextSeq 500 is a high-throughput sequencing system designed for a wide range of applications, including gene expression analysis, targeted resequencing, and small RNA discovery. The system utilizes reversible terminator-based sequencing technology to generate high-quality, accurate DNA sequence data.

More about "Genomic Library"

Genomic libraries, also known as DNA libraries or chromosome libraries, are comprehensive collections of DNA fragments that represent the complete genetic material of an organism.
These libraries are widely used in genetic research to study gene structure, expression, and function, as well as to facilitate advancements in personalized medicine and evolutionary biology.
The construction of genomic libraries typically involves extracting and fragmenting genomic DNA, followed by the insertion of these fragments into specialized vectors for storage and replication in host cells.
Researchers can then screen the libraries to identify specific genes or genomic regions of interest, using a variety of techniques such as hybridization, PCR, or next-generation sequencing platforms like the HiSeq 2500, HiSeq 2000, MiSeq, NovaSeq 6000, and HiSeq 4000.
Accurate and reproducible methods for constructing and utilizing genomic libraries are essential for advancing our understanding of genomes.
This includes the use of high-quality DNA extraction kits, such as the DNeasy Blood and Tissue Kit, and quality control measures, such as the Agilent 2100 Bioanalyzer, to ensure the integrity and purity of the DNA samples.
PubCompare.ai's AI-powered tools can help optimize your genomic library research by identifying the best protocols from published literature, preprints, and patents, ensuring the quality and reliability of your work.
By leveraging these data-driven insights, you can elevate your research and contribute to the growing field of genomics and personalized medicine.
Typo: The contruction of genomic libraries typically involves extracting and fragmenting genomic DNA, followed by the insertion of these fragments into specialized vectors for storage and replication in host cells.