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Chromosomes

Chromosomes are the thread-like structures located within the nucleus of cells that carry the genetic information in the form of genes.
They are composed of DNA and protein, and come in pairs, with one chromosome from each parent.
Chromosomes play a crucial role in cell division, heredity, and genetic disorders.
Understanding the structure and function of chromosomes is essential for advancing research in fields such as genetics, genomics, and molecular biology.
With PubCompare.ai's AI-driven platform, you can easily locate and compare protocols related to chromosomes, streamlining your research workflow and enhancing reproducibility.

Most cited protocols related to «Chromosomes»

BWA supports paired-end mapping. It first finds the positions of all the good hits, sorts them according to the chromosomal coordinates and then does a linear scan through all the potential hits to pair the two ends. Calculating all the chromosomal coordinates requires to look up the suffix array frequently. This pairing process is time consuming as generating the full suffix array on the fly with the method described above is expensive. To accelerate pairing, we cache large intervals. This strategy halves the time spent on pairing.
In pairing, BWA processes 256K read pairs in a batch. In each batch, BWA loads the full BWA index into memory, generates the chromosomal coordinate for each occurrence, estimates the insert size distribution from read pairs with both ends mapped with mapping quality higher than 20, and then pairs them. After that, BWA clears the BWT index from the memory, loads the 2 bit encoded reference sequence and performs Smith–Waterman alignment for unmapped reads whose mates can be reliably aligned. Smith–Waterman alignment rescues some reads with excessive differences.
Publication 2009
Chromosomes Memory Radionuclide Imaging
To support the multiresolution data model described earlier, we developed a corresponding file format. The ‘tiled data format’, or TDF, stores the pyramidal data tile structure and provides fast access to individual tiles. TDF files can be created using the auxiliary package ‘igvtools’. We note however that IGV does not require conversion to TDF before data can be loaded. In fact, IGV supports a variety of genomic file formats, which can be divided into three categories: (i) nonindexed, (ii) indexed and (iii) multiresolution formats:

Nonindexed formats include flat file formats such as GFF [11 ], BED [12 ] and WIG [13 ]. Files in these formats must be read in their entirety and are only suitable for relatively small data sets.

Indexed formats include BAM and Goby [14 ] for sequence alignments. Additionally, many tab-delimited feature formats can be converted to an indexed file using Tabix [15 (link)] or ‘igvtools’. Indexed formats provide rapid and efficient access to subsets of the data for display, but only when zoomed in to a sufficiently small genomic region. Zooming out requires ever-larger portions of the file to be loaded. Thus, indexed formats can efficiently support views only for a limited range of resolution scales. This range depends on the genomic density of the underlying data and can span tens of kilobases for NGS alignments, hundreds of megabases for typical variant (SNP) files, or whole chromosomes for sparse feature files. IGV uses heuristics to determine a suitable upper limit on the genomic range that can be loaded quickly with a reasonable memory footprint. If zoomed out beyond this limit, the data are not loaded.

Multiresolution formats, such as our TDF described earlier and the bigWig and bigBed formats [16 (link)], include both an index for the raw data, and precomputed indexed summary data for lower resolution (zoomed out) scales. Multiresolution formats can efficiently support views at any resolution scale.

Publication 2012
Chromosomes Genome Memory Sequence Alignment Toxic Epidermal Necrolysis
MACS is implemented in Python and freely available with an open source Artistic License at [16 ]. It runs from the command line and takes the following parameters: -t for treatment file (ChIP tags, this is the ONLY required parameter for MACS) and -c for control file containing mapped tags; --format for input file format in BED or ELAND (output) format (default BED); --name for name of the run (for example, FoxA1, default NA); --gsize for mappable genome size to calculate λBG from tag count (default 2.7G bp, approximately the mappable human genome size); --tsize for tag size (default 25); --bw for bandwidth, which is half of the estimated sonication size (default 300); --pvalue for p-value cutoff to call peaks (default 1e-5); --mfold for high-confidence fold-enrichment to find model peaks for MACS modeling (default 32); --diag for generating the table to evaluate sequence saturation (default off).
In addition, the user has the option to shift tags by an arbitrary number (--shiftsize) without the MACS model (--nomodel), to use a global lambda (--nolambda) to call peaks, and to show debugging and warning messages (--verbose). If a user has replicate files for ChIP or control, it is recommended to concatenate all replicates into one input file. The output includes one BED file containing the peak chromosome coordinates, and one xls file containing the genome coordinates, summit, p-value, fold_enrichment and FDR (if control is available) of each peak. For FoxA1 ChIP-Seq in MCF7 cells with 3.9 million and 5.2 million ChIP and control tags, respectively, it takes MACS 15 seconds to model the ChIP-DNA size distribution and less than 3 minutes to detect peaks on a 2 GHz CPU Linux computer with 2 GB of RAM. Figure S6 in Additional data file 1 illustrates the whole process with a flow chart.
Publication 2008
Chromatin Immunoprecipitation Sequencing Chromosomes DNA Chips FOXA1 protein, human Genome Homo sapiens MCF-7 Cells Neoplasm Metastasis Python
Like BLAST, both BLAT and SSAHA2 report all significant alignments or typically tens of top-scoring alignments, but this is not the most desired output in read mapping. We are typically more interested in the best alignment or best few alignments, covering each region of the query sequence. For example, suppose a 1000 bp query sequence consists of a 900 bp segment from one chromosome and a 100 bp segment from another chromosome; 400 bp out of the 900 bp segment is a highly repetitive sequence. For BLAST, to know this is a chimeric read we would need to ask it to report all the alignments of the 400 bp repeat, which is costly and wasteful because in general we are not interested in alignments of short repetitive sequences contained in a longer unique sequence. On this example, a useful output would be to report one alignment each for the 900 bp and the 100 bp segment, and to indicate if the two segments have good suboptimal alignments that may render the best alignment unreliable. Such output simplifies downstream analyses and saves time on reconstructing the detailed alignments of the repetitive sequence.
In BWA-SW, we say two alignments are distinct if the length of the overlapping region on the query is less than half of the length of the shorter query segment. We aim to find a set of distinct alignments which maximizes the sum of scores of each alignment in the set. This problem can be solved by dynamic programming, but as in our case a read is usually aligned entirely, a greedy approximation would work well. In the practical implementation, we sort the local alignments based on their alignment scores, scan the sorted list from the best one and keep an alignment if it is distinct from all the kept alignments with larger scores; if alignment a2 is rejected because it is not distinctive from a1, we regard a2 to be a suboptimal alignment to a1 and use this information to approximate the mapping quality (Section 2.7).
Because we only retain alignments largely non-overlapping on the query sequence, we might as well discard seeds that do not contribute to the final alignments. Detecting such seeds can be done with another heuristic before the Smith–Waterman extension and time spent on unnecessary extension can thus be saved. To identify these seeds, we chain seeds that are contained in a band (default band width 50 bp). If on the query sequence a short chain is fully contained in a long chain and the number of seeds in the short chain is below one-tenth of the number of seeds in the long chain, we discard all the seeds in the short chain, based on the observation that the short chain can rarely lead to a better alignment than the long chain in this case. Unlike the Z-best strategy, this heuristic does not have a noticeable effect on alignment accuracy. On 1000 10 kb simulated data, it halves the running time with no reduction in accuracy.
Publication 2010
BP 100 BP 400 Chimera Chromosomes Plant Embryos Radionuclide Imaging Repetitive Region Sequence Alignment Toxic Epidermal Necrolysis
A SAM/BAM file can be unsorted, but sorting by coordinate is used to streamline data processing and to avoid loading extra alignments into memory. A position-sorted BAM file can be indexed. We combine the UCSC binning scheme (Kent et al., 2002 (link)) and simple linear indexing to achieve fast random retrieval of alignments overlapping a specified chromosomal region. In most cases, only one seek call is needed to retrieve alignments in a region.
Publication 2009
Chromosomes Memory

Most recents protocols related to «Chromosomes»

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Example 2

A 30× genome coverage of both Xi19 and Robigus was generated. Bio-informatic mapping of the gDNA reads to the IWGSCWGAV02_2BS_scaffold14096, IWGSCWGAV02_2BS_scaffold11627 and the BAC sequence confirmed large structural differences in the region, which explain the observed lack of recombination. Essentially, there were no gDNA-seq reads from Xi19 that mapped onto the BAC sequence of Renan (FIG. 3). Similarly, none of the gDNA-seq reads from Robigus mapped onto scaffold11627 portion located in the interval. This indicates that the gene content of the corresponding genomic regions in susceptible and resistant plants is very divergent and this was probably caused by a local chromosomal rearrangement. Similar structural rearrangements between the Chinese Spring reference genome sequence and the region containing the Fusarium head blight resistance gene (Fhb1) have recently been published (Schweiger et al, 2016).

Patent 2024
Chinese Chromosomes Fusarium Gene Rearrangement Genes Genome Head Plants Recombination, Genetic

Example 1

This example describes the generation of a marker-free B. subtilis strain expressing allulose epimerase. Briefly, in a first step, a B. subtilis strain was transformed with a cassette encoding the BMCGD1 epimerase and including an antibiotic resistance marker. This cassette recombined into the Bacillus chromosome and knocked out 8 kb of DNA, including a large sporulation gene cluster and the lysine biosynthesis gene lysA. In a second step, a second cassette was recombined into the B. subtilis chromosome, restoring the lysA gene and removing DNA encoding the antibiotic resistance. E. coli strain 39 A10 from the Keio collection was used to passage plasmid DNA prior to transformation of B. subtilis. The relevant phenotype is a deficiency in the DNA methylase HsdM in an otherwise wild-type K-12 strain of E. coli.

In detail, a cassette of 5120 bp (SEQ ID NO:1; synthetic DNA from IDT, Coralville, Iowa) was synthesized and cloned into a standard ampicillin resistant pIDT vector. The synthetic piece encoded 700 bp upstream of lysA on the B. subtilis chromosome, the antibiotic marker cat (651 bp), the DNA-binding protein lad (1083 bp), and the allulose epimerase (894 bp), and included 700 bp of homology in dacF. This vector was transformed into E. coli strain 39 A10 (Baba et al., 2006), and plasmid DNA was prepared and transformed into B. subtilis strains 1A751 and 1A976.

Transformants were selected on LB supplemented with chloramphenicol. The replicon for pIDT is functional in E. coli but does not work in Gram positive bacteria such as B. subtilis. The colonies that arose therefore represented an integration event into the chromosome. In strain 1A751, the colony morphology on the plates was used to distinguish between single and double recombination events. The double recombination event would knock out genes required for sporulation, whereas the single recombination would not. After three days on LB plates, colonies capable of sporulation were brown and opaque; sporulation-deficient colonies were more translucent.

B. subtilis strain 1A976 with the allulose epimerase cassette is auxotrophic for histidine and lysine and can achieve very high transformation efficiency upon xylose induction. A 1925 bp synthetic DNA (SEQ ID NO:2) was amplified by primers (SEQ ID NO:3, SEQ ID NO:4) and Taq polymerase (Promega). This PCR product encoded the lysA gene that was deleted by the dropping in the epimerase cassette and 500 bp of homology to lad. A successful double recombination event of this DNA should result in colonies that are prototrophic for lysine and sensitive to chloramphenicol; i.e., the entire cat gene should be lost.

Transformants were selected on Davis minimal media supplemented with histidine. Colonies that arose were characterized by PCR and streaking onto LB with and without chloramphenicol. Strains that amplified the introduced DNA and that were chloramphenicol sensitive were further characterized, and their chromosomal DNA was extracted.

Strain 1A751 containing the chloramphenicol resistant allulose was transformed with this chromosomal DNA and selected on Davis minimal media supplemented with histidine. Transformants were streaked onto LB with and without chloramphenicol and characterized enzymatically as described below.

Patent 2024
Ampicillin Anabolism Antibiotic Resistance, Microbial Antibiotics Bacillus Bacillus subtilis Chloramphenicol Chromosomes Cloning Vectors DNA, A-Form DNA-Binding Proteins Epimerases Escherichia coli Gene Clusters Gene Knockout Techniques Genes Gram-Positive Bacteria Histidine Lysine Methyltransferase Oligonucleotide Primers Phenotype Plasmids psicose Recombination, Genetic Replicon Strains Taq Polymerase Xylose

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.

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

Example 1

To generate an attenuated strain of P. aeruginosa for production of alginate, the following virulence factor genes were sequentially deleted from the chromosome of the wild-type strain PAO1: toxA, plcH, phzM, wapR, and aroA. toxA encodes the secreted toxin Exotoxin A, which inhibits protein synthesis in the host by deactivating elongation factor 2 (EF-2). plcH encodes the secreted toxin hemolytic phospholipase C, which acts as a surfactant and damages host cell membranes. phzM encodes phenazine-specific methyltransferase, an enzyme required for the production of the redox active, pro-inflammatory, blue-green secreted pigment, pyocyanin. wapR encodes a rhamnosyltransferase involved in synthesizing O-antigen, a component of lipopolysaccharide (LPS) of the outer membrane of the organism. aroA encodes 3-phosphoshikimate 1-carboxyvinyltransferase, which is required intracellularly for aromatic amino acid synthesis. Deletion of aroA from the P. aeruginosa genome has previously been shown to attenuate the pathogen. Each gene was successfully deleted using a homologous recombination strategy with the pEX100T-Not1 plasmid. The in-frame, marker-less deletion of these five gene sequences was verified by Sanger sequencing and by whole genome resequencing (FIG. 1 and FIG. 8). This engineered strain was designated as PGN5. The whole genome sequence of PGN5 has been deposited to NCBI Genbank with an accession number of CP032541. All five in-frame gene deletions were detected and validated to be the deletion as designed using PCR (FIG. 7).

To verify gene deletion and attenuation of the PGN5 strain, the presence of the products of the deleted genes was measured and was either undetectable, or significantly reduced in the PGN5 strain. To test for the toxA gene deletion in PGN5, a Western blot analysis was performed for the presence of Exotoxin A in the culture medium. Exotoxin A secretion was detected in wild-type PAO1 control, but not in the PGN5 strain (FIG. 2A). To confirm the loss of plcH, hemolysis was assessed on blood agar. The hemolytic assay was carried out by streaking PAO1, PGN5, P. aeruginosa mucoid strain VE2, and a negative control, Escherichia coli strain BL21 on blood agar plates. A clear zone was observed surrounding PAO1 and VE2 cell growth, indicating complete (β-) hemolysis (FIG. 2B). In contrast, the blood agar remained red and opaque surrounding PGN5 and BL21 growth, indicating negligible or no hemolytic activity in these strains (FIG. 2B). To assess for deletion of phzM, the amount of pyocyanin secreted by PAO1 and PGN5 was extracted and measured. The amount of pyocyanin detected was significantly reduced in PGN5 (FIG. 2C). In fact, the difference in pigment production between PAO1 and PGN5 was immediately apparent on agar plates (FIG. 3A-3B). To test for wapR gene deletion, an LPS extraction was performed, followed by silver-stained SDS-PAGE and Western blot on the following strains: PAO1, PGN4 (PGN5 without aroA deletion), VE2, and PAO1wbpL, which serves as a negative control due to a deletion in the O-antigen ligase gene, and thus produces no O-antigen. The presence of O-antigen was detected in PGN4, but the level of LPS banding was significantly reduced compared to the LPS banding profile observed in PAO1 and VE2 (FIG. 2D). Lastly, to test for aroA deletion, ELISA was performed to detect the presence of 3-phosphoshikimate 1-carboxyvinyltransferase in cell lysates prepared from PAO1 and PGN5. The ELISA results showed that the amount of 3-phosphoshikimate 1-carboxyvinyltransferase was significantly reduced in PGN5, compared to that in PAO1 (FIG. 2E). Additionally, the deletion of aroA resulted in slower growth in the PGN5 strain, a growth defect that was restored with the addition of 1 mg/mL of aromatic amino acids (W, Y, F) to the culture medium (data not shown).

Patent 2024
1-Carboxyvinyltransferase, 3-Phosphoshikimate Agar Alginate Anabolism Aromatic Amino Acids Biological Assay BLOOD Cardiac Arrest Chromosomes Culture Media Deletion Mutation Enzyme-Linked Immunosorbent Assay Enzymes Escherichia coli Exotoxins Gene Deletion Genes Genetic Markers Genome Hemolysis Homologous Recombination Inflammation Ligase Lipopolysaccharides Methyltransferase O Antigens Oxidation-Reduction Pathogenicity Peptide Elongation Factor 2 Phenazines Phospholipase C Pigmentation Plasma Membrane Plasmids Protein Biosynthesis Pseudomonas aeruginosa Pyocyanine Reading Frames SDS-PAGE secretion SERPINA3 protein, human Silver Strains Surface-Active Agents Tissue, Membrane Toxins, Biological Virulence Factors Western Blot Western Blotting

Example 4

Since no mortality was observed in mice injected with PGN5+mucE, it was determined whether cells of this strain might localize differently than VE2 cells within the mice post-injection. To test this, the luxCDABEG operon was used to tag each strain with bioluminescence. VE2 and PGN5+mucE both carry gentamicin resistance genes, while the plasmids used for labeling with bioluminescence required gentamicin sensitivity. Thus, the luxCDABEG operon was incorporated into the chromosome of PAO1 and PGN5, and then the pUCP20-pGm-mucE plasmid was introduced into each strain to induce alginate production and mucoidy. Intraperitoneal injection of C57BL/6 mice with bioluminescent PAO1+mucE showed either localization at the injection site or dissemination through the body, and lethality resulted in all mice injected (FIGS. 5A-5B). Conversely, localization at the injection site but no dissemination was observed with bioluminescent PGN5+mucE, and no mortality was observed in injected mice (FIGS. 5C-5D).

Patent 2024
Alginate Cells Chromosomes Cultured Cells Figs Genes Gentamicin Human Body Hypersensitivity Injections, Intraperitoneal Mice, Inbred C57BL Mus Operon Plasmids Strains

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More about "Chromosomes"

Chromosomes are the fundamental units of genetic information within the cell nucleus.
These thread-like structures, composed of DNA and proteins, come in pairs and carry the genes that determine our inherited traits.
Understanding chromosomes is crucial for advancing research in fields like genetics, genomics, and molecular biology.
Chromosomes play a vital role in cell division, heredity, and genetic disorders.
During cell division, chromosomes undergo complex processes such as replication, segregation, and condensation.
Aberrations in chromosome structure or number can lead to genetic disorders like Down syndrome, Turner syndrome, and Klinefelter syndrome.
Researchers often use specialized techniques and tools to study chromosomes.
Colcemid, a microtubule-disrupting agent, is commonly used to arrest cells in metaphase, allowing for better visualization and analysis of chromosomes.
DNA extraction kits like the QIAamp DNA Mini Kit and the DNeasy Blood & Tissue Kit are used to isolate high-quality genomic DNA, which can then be analyzed using advanced sequencing technologies like the HiSeq 2500 and HiSeq 2000.
Microscopy techniques, such as those utilizing the Vectashield mounting medium, enable the visualization and study of chromosome structure and organization.
Additionally, the Wizard Genomic DNA Purification Kit and the CytoScan HD array provide tools for chromosome analysis and detection of chromosomal abnormalities.
By leveraging these cutting-edge tools and techniques, researchers can deepen their understanding of chromosome structure, function, and their role in genetic processes, ultimately leading to advancements in fields like disease diagnosis, personalized medicine, and evolutionary biology.