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> Anatomy > Cell Component > Karyotype

Karyotype

Karyotype refers to the chromosomal compliment of a cell or organism, typically determined through microscopic analysis.
It provides information about the number, size, and structure of chromosomes, which can be used to identify genetic disorders, chromosomal abnormalities, and other genetic characteristics.
Karyotype analysis is an important tool in clinical genetics, reproductive health, and biological research.
Optimizing karyotype analysis protocols can enhance the reproducibility and efficiency of this critical research process.

Most cited protocols related to «Karyotype»

1
Automated SCNA Profiling in Cancer
In order to facilitate rapid analysis of many cancer samples used in this study, ABSOLUTE was programed to automatically identify copy profiles that cannot be reliably called and to classify them into informative failure categories (Fig. 3a), which were defined by the following criteria. Define m̂ as the sorted vector of posterior genome-wide copy-state allocations (θ̂), so that m̂1 represents the greatest element of θ̂ (the modal copy-state). This vector was constructed with θ0 replaced by 0 if θ0 < 0.01 and b < 0.15, so that germline copy-number variants (CNVs) or regions of inherited homozygosity are not confused with small SCNAs implying very pure samples. The categories are then:

non-aberrant: m̂3 < 0.001, m̂2 < 0.005, σ̂H < 0.02

insufficient purity: m̂3 < 0.001, m̂2 < 0.005, σ̂H ≥ 0.02

polygenomic: θ̂z > 0.2.

These criteria were applied to the top-ranked mode for each sample (combined SCNA-fit and karyotype scores). Several examples of each outcome are shown in Supplementary Fig. 5. The above designations led to reasonably good concordance of automated calls with those obtained after manual review. We note that the use of somatic point-mutation data increases the calling sensitivity within these sample categories.
Carter S.L., Cibulskis K., Helman E., McKenna A., Shen H., Zack T., Laird P.W., Onofrio R.C., Winckler W., Weir B.A., Beroukhim R., Pellman D., Levine D.A., Lander E.S., Meyerson M, & Getz G. (2012). Absolute quantification of somatic DNA alterations in human cancer. Nature biotechnology, 30(5), 413-421.
Publication 2012
Cloning Vectors Copy Number Polymorphism Diploid Cell Genome Germ Line Homozygote Hypersensitivity Karyotype Malignant Neoplasms Point Mutation
2
Automated SCNA Profiling in Cancer
In order to facilitate rapid analysis of many cancer samples used in this study, ABSOLUTE was programed to automatically identify copy profiles that cannot be reliably called and to classify them into informative failure categories (Fig. 3a), which were defined by the following criteria. Define m̂ as the sorted vector of posterior genome-wide copy-state allocations (θ̂), so that m̂1 represents the greatest element of θ̂ (the modal copy-state). This vector was constructed with θ0 replaced by 0 if θ0 < 0.01 and b < 0.15, so that germline copy-number variants (CNVs) or regions of inherited homozygosity are not confused with small SCNAs implying very pure samples. The categories are then:

non-aberrant: m̂3 < 0.001, m̂2 < 0.005, σ̂H < 0.02

insufficient purity: m̂3 < 0.001, m̂2 < 0.005, σ̂H ≥ 0.02

polygenomic: θ̂z > 0.2.

These criteria were applied to the top-ranked mode for each sample (combined SCNA-fit and karyotype scores). Several examples of each outcome are shown in Supplementary Fig. 5. The above designations led to reasonably good concordance of automated calls with those obtained after manual review. We note that the use of somatic point-mutation data increases the calling sensitivity within these sample categories.
Carter S.L., Cibulskis K., Helman E., McKenna A., Shen H., Zack T., Laird P.W., Onofrio R.C., Winckler W., Weir B.A., Beroukhim R., Pellman D., Levine D.A., Lander E.S., Meyerson M, & Getz G. (2012). Absolute quantification of somatic DNA alterations in human cancer. Nature biotechnology, 30(5), 413-421.
Publication 2012
Cloning Vectors Copy Number Polymorphism Diploid Cell Genome Germ Line Homozygote Hypersensitivity Karyotype Malignant Neoplasms Point Mutation
3
Inferring Chromosome Copy Numbers
The inferred copy-number profile was averaged along the genome, providing the DNA content of the corresponding cancer sample.
Chromosome copy numbers were characterized by the status of pericentric regions, defined as the alteration units directly before or after the centromeric part of the chromosome (which has no SNP measurement per se). The definition of pericentric region therefore depends on the SNP chip used for genotyping. Regions less than 10 SNPs were ignored. If the pericentric alteration unit is a small region (less than 100 SNPs), setting the chromosome copy number on the basis of this alteration unit could be erroneous and could therefore interfere with karyotype assessment.
Popova T., Manié E., Stoppa-Lyonnet D., Rigaill G., Barillot E, & Stern M.H. (2009). Genome Alteration Print (GAP): a tool to visualize and mine complex cancer genomic profiles obtained by SNP arrays. Genome Biology, 10(11), R128.
Publication 2009
Centromere Chromosomes Copy Number Polymorphism DNA Chips Genome Karyotype Malignant Neoplasms Single Nucleotide Polymorphism
4
Comprehensive Breast Cancer Genomic Profiling
Breast cancer whole genome profiles were adapted from the R Circos package57 (link). Features depicted in circos plots from outermost rings heading inwards: Karyotypic ideogram outermost. Base substitutions next, plotted as rainfall plots (log10 intermutation distance on radial axis, dot colours: blue=C>A, black=C>G, red=C>T, grey=T>A, green=T>C, pink=T>G). Ring with short green lines = insertions, ring with short red lines = deletions. Major copy number allele (green = gain) ring, minor copy number allele ring (pink=loss), Central lines represent rearrangements (green= tandem duplications, pink=deletions, blue=inversions and gray=interchromosomal events. Top right hand panel displays the number of mutations contributing to each mutation signature extracted using NNMF in individual cancers. Middle right hand panel represents indels. Bottom right corner shows histogram of rearrangements present in this cancer. Bottom left corner shows all curated driver mutations, top and middle left panels show clinical and pathology data respectively.
Nik-Zainal S., Davies H., Staaf J., Ramakrishna M., Glodzik D., Zou X., Martincorena I., Alexandrov L.B., Martin S., Wedge D.C., Van Loo P., Ju Y.S., Smid M., Brinkman A.B., Morganella S., Aure M.R., Lingjærde O.C., Langerød A., Ringnér M., Ahn S.M., Boyault S., Brock J.E., Broeks A., Butler A., Desmedt C., Dirix L., Dronov S., Fatima A., Foekens J.A., Gerstung M., Hooijer G.K., Jang S.J., Jones D.R., Kim H.Y., King T.A., Krishnamurthy S., Lee H.J., Lee J.Y., Li Y., McLaren S., Menzies A., Mustonen V., O’Meara S., Pauporté I., Pivot X., Purdie C.A., Raine K., Ramakrishnan K., Rodríguez-González F.G., Romieu G., Sieuwerts A.M., Simpson P.T., Shepherd R., Stebbings L., Stefansson O.A., Teague J., Tommasi S., Treilleux I., Van den Eynden G.G., Vermeulen P., Vincent-Salomon A., Yates L., Caldas C., van’t Veer L., Tutt A., Knappskog S., Tan B.K., Jonkers J., Borg Å., Ueno N.T., Sotiriou C., Viari A., Futreal P.A., Campbell P.J., Span P.N., Van Laere S., Lakhani S.R., Eyfjord J.E., Thompson A.M., Birney E., Stunnenberg H.G., van de Vijver M.J., Martens J.W., Børresen-Dale A.L., Richardson A.L., Kong G., Thomas G, & Stratton M.R. (2016). Landscape of somatic mutations in 560 breast cancer whole genome sequences. Nature, 534(7605), 47-54.
Publication 2016
Alleles Epistropheus Gene Deletion Gene Rearrangement Genetic Profile INDEL Mutation Insertion Mutation Inversion, Chromosome Karyotype Malignant Neoplasm of Breast Malignant Neoplasms Mutation Venous Catheter, Central
5
Comprehensive Breast Cancer Genomic Profiling
Breast cancer whole genome profiles were adapted from the R Circos package57 (link). Features depicted in circos plots from outermost rings heading inwards: Karyotypic ideogram outermost. Base substitutions next, plotted as rainfall plots (log10 intermutation distance on radial axis, dot colours: blue=C>A, black=C>G, red=C>T, grey=T>A, green=T>C, pink=T>G). Ring with short green lines = insertions, ring with short red lines = deletions. Major copy number allele (green = gain) ring, minor copy number allele ring (pink=loss), Central lines represent rearrangements (green= tandem duplications, pink=deletions, blue=inversions and gray=interchromosomal events. Top right hand panel displays the number of mutations contributing to each mutation signature extracted using NNMF in individual cancers. Middle right hand panel represents indels. Bottom right corner shows histogram of rearrangements present in this cancer. Bottom left corner shows all curated driver mutations, top and middle left panels show clinical and pathology data respectively.
Nik-Zainal S., Davies H., Staaf J., Ramakrishna M., Glodzik D., Zou X., Martincorena I., Alexandrov L.B., Martin S., Wedge D.C., Van Loo P., Ju Y.S., Smid M., Brinkman A.B., Morganella S., Aure M.R., Lingjærde O.C., Langerød A., Ringnér M., Ahn S.M., Boyault S., Brock J.E., Broeks A., Butler A., Desmedt C., Dirix L., Dronov S., Fatima A., Foekens J.A., Gerstung M., Hooijer G.K., Jang S.J., Jones D.R., Kim H.Y., King T.A., Krishnamurthy S., Lee H.J., Lee J.Y., Li Y., McLaren S., Menzies A., Mustonen V., O’Meara S., Pauporté I., Pivot X., Purdie C.A., Raine K., Ramakrishnan K., Rodríguez-González F.G., Romieu G., Sieuwerts A.M., Simpson P.T., Shepherd R., Stebbings L., Stefansson O.A., Teague J., Tommasi S., Treilleux I., Van den Eynden G.G., Vermeulen P., Vincent-Salomon A., Yates L., Caldas C., van’t Veer L., Tutt A., Knappskog S., Tan B.K., Jonkers J., Borg Å., Ueno N.T., Sotiriou C., Viari A., Futreal P.A., Campbell P.J., Span P.N., Van Laere S., Lakhani S.R., Eyfjord J.E., Thompson A.M., Birney E., Stunnenberg H.G., van de Vijver M.J., Martens J.W., Børresen-Dale A.L., Richardson A.L., Kong G., Thomas G, & Stratton M.R. (2016). Landscape of somatic mutations in 560 breast cancer whole genome sequences. Nature, 534(7605), 47-54.
Publication 2016
Alleles Epistropheus Gene Deletion Gene Rearrangement Genetic Profile INDEL Mutation Insertion Mutation Inversion, Chromosome Karyotype Malignant Neoplasm of Breast Malignant Neoplasms Mutation Venous Catheter, Central

Most recents protocols related to «Karyotype»

1
Generation and Maintenance of Haploid Human Embryonic Stem Cells
Not available on PMC !

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.

US11859232B2. Screening for chemotherapy resistance in human haploid cells (2024-01-02). YISSUM RESEARCH DEVELOPMENT COMPANY OF THE HEBREW UNIVERSITY OF JERUSALEM LTD. [IL]. Inventors: Nissim Benvenisty [IL].
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
2
Chromosomal Analysis of Patients
Reverse Heat Giemsa (RHG) banded karyotype was performed on metaphase chromosome preparations obtained from peripheral blood lymphocytes of both patients and parents according to standard protocol (450–550 band level). A minimum of 20 R-banded metaphase chromosomes were analyzed using Cytovision® Karyotyping software version 4.0. Karyotypes were classified according to the International System of Human Cytogenetic Nomenclature (ISCN 2020) [11 ]. Fluorescent in situ Hybridization (FISH) was carried out on metaphase chromosomes of the patients according to the standard protocol, using commercial probes. Array Comparative genomic hybridization (aCGH) 4 × 44 K micro-arrays was performed using the Agilent platform according to the manufacturer’s instructions (Feature Extraction 9.1, CGH Analytics 4.5, Santa Clara, California, United States). An abnormal ratio greater than + 0.58 or lower than − 0.75 was considered as an alteration. An in silico analysis of the unbalanced regions was executed using UCSC Genome Browser (https://genome.ucsc.edu/), the Database of Chromosome Imbalance and Phenotype in Humans using Ensemble Resources (DECIPHER: https://decipher.sanger.ac.uk/), the Database of Genomic Variants (DGV: http://dgv.tcag.ca/dgv/app/home) and the Online Mendelian Inheritance in Man database (OMIM: https://omim.org/).
Rjiba K., Mougou-Zerelli S., Hamida I.H., Saad G., Khadija B., Jelloul A., Slimani W., Hasni Y., Dimassi S., khelifa H.B., Sallem A., Kammoun M., Abdallah H.H., Gribaa M., Bignon-Topalovic J., Chelly S., Khairi H., Bibi M., Kacem M., Saad A., Bashamboo A, & McElreavey K. (2023). Additional evidence for the role of chromosomal imbalances and SOX8, ZNRF3 and HHAT gene variants in early human testis development. Reproductive Biology and Endocrinology : RB&E, 21, 2.
Publication 2023
Array-Based Comparative Genomic Hybridization BLOOD Chromosomes Chromosomes, Human, Pair 20 Fluorescent in Situ Hybridization Genome Homo Homo sapiens Karyotype Lymphocyte Metaphase Outpatients Parent Patients Phenotype Stain, Giemsa
3
Chromosomal Abnormalities in Miscarriage Samples
All fresh miscarriage specimens were rinsed with saline solution for three times. Chorionic villi were separated from maternal decidua according to the standardized technology [9 (link)]. Samples where chorionic villi could not be clearly identified were excluded from this study. Genomic DNA was extracted from chorionic villi with the protocol of QIAamp DNA Mini Kit (Qiagen, Germany). Chromosomal abnormalities of POCs were detected by two CMA platforms in the current study, including CytoScan 750K array (Affymetrix, USA) and HumanCyto12-SNP array (Illumina, USA). SNP array experiments and molecular karyotype analysis for both platforms were performed as previously described [10 (link)]. Quantitative fluorescent polymerase chain reaction (QF-PCR) was subsequently performed to identify the percentage of maternal and foetal DNA if MCC was detected by CMA. Significant MCC referred to the proportion of MCC exceeding 30%. Samples with significant MCC were excluded from our study.
The two platforms could detect CNVs at an effective minimal resolution of 100 kb and regions of allelic homozygosity (ROHs) at a threshold of 5 Mb. Mosaicism for aneuploidies or CNVs ≥ 5 Mb was reported when the detection threshold of 30% was exceeded. CNVs were further classified as partial aneuploidy (CNVs ≥ 10 Mb, large CNVs) and microdeletions/microduplications (CNVs < 10 Mb, submicroscopic CNVs) based on their sizes. Pathogenicity of detected CNVs were evaluated according to the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen) [11 (link)].
Xia Z., Zhou R., Li Y., Meng L., Huang M., Tan J., Qiao F., Zhu H., Hu P., Zhu Q., Xu Z, & Wang Y. (2023). Reproductive outcomes in couples with sporadic miscarriage after embryonic chromosomal microarray analysis. Annals of Medicine, 55(1), 837-848.
Publication 2023
Alleles Aneuploidy Care, Prenatal Chromosome Aberrations Decidua Genome Homozygote Karyotype Mosaicism Pathogenicity Polymerase Chain Reaction Saline Solution Spontaneous Abortion Villi, Chorionic
4
Comparative Genomic Synteny Analysis of Notothenioid Fishes
An analysis of conserved synteny was performed at different stages of the assembly using the Synolog software (Catchen et al. 2009 (link); Small et al. 2016 (link)). Annotated coding sequences from C. esox and C. gunnari primary and secondary assemblies, and other species of interest, were first reciprocally matched using the blastp algorithm from BLAST + v2.4.0. The BLAST results and genome annotation coordinates were fed to Synolog, which (1) establishes reciprocal best BLAST hits to identify orthologous genes, (2) uses the genome coordinates of each best hit to define clusters of conserved synteny between the genomes, (3) refines ortholog assignments using the defined clusters, and (4) defines orthology between chromosomes/scaffolds based on the conserved synteny patterns. In addition to the C. esox and C. gunnari genomes described here, for comparative purposes, we included other high-quality notothenioid assemblies including C. aceratus (Kim et al. 2019 (link)), P. georgianus (Bista et al. 2022 ), Gymnodraco acuticeps (Bista et al. 2022 ), and Trematomus bernacchii (Bista et al. 2022 ; supplementary table S2, Supplementary Material online).
This conserved synteny analysis was initially used to manually curate the assemblies, by identifying discrepancies between primary and secondary assemblies, and/or to identify structural variants located within scaffold boundaries indicating a misassembly. Once the curated chromosome-level sequences were generated, conserved synteny was determined between the genomes of C. esox and C. gunnari against the genome of E. maclovinus, the closest sister species to the Antarctic clade, in order to identify and name orthologous chromosomes. The E. maclovinus assembly (Cheng et al., in preparation) was first compared against the Xiphophorus maculatus reference assembly, which contains the ancestral teleost karyotype number of 24 chromosomes (Amores et al. 2014 (link)). Chromosomes were named accordingly to these patterns of conserved synteny.
Rivera-Colón A.G., Rayamajhi N., Minhas B.F., Madrigal G., Bilyk K.T., Yoon V., Hüne M., Gregory S., Cheng C.H, & Catchen J.M. (2023). Genomics of Secondarily Temperate Adaptation in the Only Non-Antarctic Icefish. Molecular Biology and Evolution, 40(3), msad029.
Publication 2023
Chromosomes Conserved Synteny Esox Exons Genes Genome Karyotype Xiphophorus
5
Family Karyotyping and Genomic Analysis
Venous blood samples were collected from attending family members. Collected blood samples were used for karyotyping and genomic DNA extraction. Blood cells cultured with phytohemagglutinin for 72 hours were used for karyotyping. The cultured cells were disrupted and Giemsa-stained. Twenty metaphases were examined to examine karyotypes of each member. Genomic DNA (gDNA) samples were extracted using QIAamp DNA Kit (QIAGEN, Germany). Extracted gDNA samples were subjected to examine microdeletions at the Y-chromosome (AZFa, AZFb, AZFc, and AZFd), whole exome sequencing (WES), and Sanger Sequencing.
Hwang J.Y., Chai P., Nawaz S., Choi J., Lopez-Giraldez F., Hussain S., Bilguvar K., Mane S., Lifton R.P., Ahmad W., Zhang K, & Chung J.J. (2023). LRRC23 truncation impairs radial spoke 3 head assembly and sperm motility underlying male infertility. bioRxiv.
Publication Preprint 2023
azidofluorescein diacetate BLOOD Blood Cells Cultured Cells Family Member Genome Karyotype Metaphase Phytohemagglutinins Specimen Collection Stain, Giemsa Veins Y chromosome deletions

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More about "Karyotype"

Karyotyping is the process of analyzing the chromosomal complement of a cell or organism, typically through microscopic examination.
This critical research technique provides valuable insights into genetic disorders, chromosomal abnormalities, and other genetic characteristics.
Optimizing karyotype analysis protocols is essential for enhancing the reproducibility and efficiency of this important process.
Karyotype analysis can be performed using a variety of tools and technologies, including the Image-Pro Plus 4.5 imaging software, the BX50 and BX61 epifluorescence microscopes, and specialized media like MTeSR1 and Matrigel.
The QIAamp DNA Mini Kit and QIAamp DNA Blood Mini Kit are also commonly used for DNA extraction and purification in karyotyping studies.
Colcemid, a microtubule-disrupting agent, is often utilized to arrest cells in metaphase, facilitating the visualization and analysis of chromosomes.
Fetal bovine serum (FBS) may also be employed in cell culture protocols to support the growth and division of cells prior to karyotype analysis.
By leveraging the latest advancements in karyotype analysis, researchers can optimize their protocols, enhance reproducibility, and gain deeper insights into the genetic makeup of cells and organisms.
This knowledge is crucial for advancing clinical genetics, reproductive health, and a wide range of biological research applications.