Högskolan i Skövde

his.sePublikationer
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Identification of disease gene variants in two siblings with birth anomalies using whole exome sequencing (WES) and in-silico analysis
Högskolan i Skövde, Institutionen för hälsovetenskaper.
2021 (Engelska)Självständigt arbete på grundnivå (kandidatexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
Abstract [en]

Rare recessive disorders affect 3.5 % - 5.9% of the population worldwide. Most rare disorders are unclassified and are of unknown aetiology. Consanguinity is believed to increase the risk of rare recessive disorders in the offspring. In the current project, two siblings from consanguineous parents were born with severe skeletal and heart defects leading to death. This study aimed to uncover the potential genetic cause involved in the condition using Next Generation Sequencing and In-Silico analyses. First, the Whole Exome Sequencing data of the two affected siblings and their parents was analysed via the Variant-Calling Pipeline. The called gene-variants from the pipeline were filtered based on various In-silico analyses. Variant-dependent methods which included (Allele frequency, conservation, and pathogenicity prediction) and Disease-dependent methods that included (literature review, gene ontology, and pathway analysis) were used to confirm the deleteriousness of the identified rare variants. Three variants in three various genes were identified as candidates in the final list. The variants were then proven for autosomal recessive segregation in the family using homozygosity mapping. All identified variants are assumed to be involved in the observed phenotypes based on previously reported cases and In-Silico analysis.

Ort, förlag, år, upplaga, sidor
2021. , s. 36
Nationell ämneskategori
Biomedicinsk laboratorievetenskap/teknologi
Identifikatorer
URN: urn:nbn:se:his:diva-19832OAI: oai:DiVA.org:his-19832DiVA, id: diva2:1567073
Ämne / kurs
Biomedicin/medicinsk vetenskap
Utbildningsprogram
Biomedicinprogrammet
Handledare
Examinatorer
Tillgänglig från: 2021-06-15 Skapad: 2021-06-15 Senast uppdaterad: 2021-06-15Bibliografiskt granskad

Open Access i DiVA

Fulltext saknas i DiVA

Av organisationen
Institutionen för hälsovetenskaper
Biomedicinsk laboratorievetenskap/teknologi

Sök vidare utanför DiVA

GoogleGoogle Scholar

urn-nbn

Altmetricpoäng

urn-nbn
Totalt: 184 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf