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dc.date.available
2025-02-24T13:05:39Z  
dc.identifier.citation
Abelleyro, Miguel Martin; de Brasi, Carlos Daniel; (2025): Structural Variant genotyping by using short-read massive parallel sequencing of restriction DNA circles. Consejo Nacional de Investigaciones Científicas y Técnicas. (dataset). http://hdl.handle.net/11336/255076  
dc.identifier.uri
http://hdl.handle.net/11336/255076  
dc.description.abstract
Background: Structural variants (SVs) are large DNA rearrangements, typically >50 bp, that may be directly involved in genome evolution and human diseases. SVs can be classified as copy number variants (CNVs), characterized by gain (tandem duplications and insertions) or loss of genetic material (deletions); non-CNVs, large rearrangements non involving gain or loss of DNA (perfect inversions, reciprocal translocations), and complex, combining characteristics. The Human Genome (HG) presents a vast complexity characterized by a high number of long and particularly short interspersed repeated elements (LINEs and SINEs, respectively) as well as low copy number repeats (LCRs) (typically 2-4 copies per haploid genome). Homologous pairing and recombination between non-allelic copies of these repeats may fuel the occurrence of all type of SVs. These SVs mediated by unequal homologous recombination are characterized by being delimited by these repeats and, consequently, the specific breakpoint cannot be determined and will remain undefined and confined to the range of the repeated tract involved in the reciprocal. Massive parallel sequencing (MPS) has greatly improved modern human genetics, so called genomic medicine, by mean of performing a comprehensive and accurate genotyping of small variants including single nucleotide substitutions and indels (SNV). However, SV genotyping by using 2nd generation MPS (e.g., Illumina platform of short read sequencing) and the associated bioinformatics algorithms are still far to reach its potential. 3rd generation MPS has come to address the challenges posed by SV genotyping by producing much longer reads. It is expected that long-read MPS will alleviate numerous computational challenges surrounding genome assembly, transcript reconstruction, and metagenomics among other important areas of modern biology and medicine. Among 2nd generation MPS, pair-end read technologies, is highly accurate for SNV genotyping, but no so efficient for SV calling in the complex HG, in part due to its abundance in repeated sequences such as SINE, LINE and LCR. Certainty, long read sequencing technologies or third generation MPS, have clear advantages for SV genotyping, but its insertion in genomic medicine worldwide is still. Consequently, some recurrent SVs, mediated by large LCRs (e.g., >1 kb), still need characterization by massive sequencing. Aim: The objective of this work is to present the proof-of-concept of a novel approach for SV genotyping characterized by applying second generation Whole Genome Sequencing (WGS) from circularized restriction-fragment DNA and the development of the specifically designed bioinformatic protocol.  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.title
Structural Variant genotyping by using short-read massive parallel sequencing of restriction DNA circles  
dc.type
dataset  
dc.date.updated
2025-02-18T13:17:41Z  
dc.description.fil
Fil: Abelleyro, Miguel Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; Argentina  
dc.description.fil
Fil: de Brasi, Carlos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; Argentina  
dc.datacite.PublicationYear
2025  
dc.datacite.Creator
Abelleyro, Miguel Martin  
dc.datacite.Creator
de Brasi, Carlos Daniel  
dc.datacite.affiliation
Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental  
dc.datacite.affiliation
Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental  
dc.datacite.affiliation
Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck  
dc.datacite.affiliation
Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental  
dc.datacite.affiliation
Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental  
dc.datacite.affiliation
Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Inmunología, Genética y Metabolismo. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Inmunología, Genética y Metabolismo  
dc.datacite.publisher
Consejo Nacional de Investigaciones Científicas y Técnicas  
dc.datacite.subject
Genética Humana  
dc.datacite.subject
Medicina Básica  
dc.datacite.subject
CIENCIAS MÉDICAS Y DE LA SALUD  
dc.datacite.ContributorType
DataCurator  
dc.datacite.ContributorType
RelatedPerson  
dc.datacite.ContributorType
RelatedPerson  
dc.datacite.ContributorType
RelatedPerson  
dc.datacite.ContributorName
Yankilevich, Patricio  
dc.datacite.ContributorName
Rossetti, Liliana Carmen  
dc.datacite.ContributorName
Radic, Claudia Pamela  
dc.datacite.ContributorName
Giliberto, Florencia  
dc.datacite.date
07-2019  
dc.datacite.DateType
Creado  
dc.datacite.language
eng  
dc.datacite.version
1.0  
dc.datacite.description
Detección de variantes estructurales del genoma a partir de secuenciación masiva paralela de 2da generación (lecturas cortas, plataforma Illumina)  
dc.datacite.DescriptionType
Métodos  
dc.datacite.FundingReference
PICT-2019-01651  
dc.datacite.FundingReference
PIP, código: 11220200102067CO01  
dc.datacite.FunderName
Ministerio de Ciencia. Tecnología e Innovación Productiva. Agencia Nacional de Promoción Científica y Tecnológica  
dc.datacite.FunderName
Consejo Nacional de Investigaciones Científicas y Técnicas  
dc.subject.keyword
STRUCTURAL VARIANTS  
dc.subject.keyword
MASSIVE PARALLEL SEQUENCING  
dc.subject.keyword
RESTRICTION CIRCLES  
dc.subject.keyword
BIOINFORMATIC PIPELINE  
dc.datacite.resourceTypeGeneral
dataset  
dc.conicet.datoinvestigacionid
25053  
dc.datacite.awardTitle
Detección Integrada de Variantes Estructurales del Genoma Humano por Secuenciación Masiva Paralela de Círculos de Restricción. Desarrollos experimentales y bioinformáticos con aplicaciones iniciales en Hemofilia  
dc.datacite.awardTitle
Exploración Masiva del Genotipo en Pacientes con variantes patogénicas constitucionales que modifican el fenotipo hemofílico en varones y mujeres  
dc.conicet.justificacion
Los Datos de Investigación refieren a la descripción de una metodología de análisis genómico.  
dc.datacite.formatedDate
2019