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Inherited and De Novo Variation in Lithuanian Genomes: Introduction to the Analysis of the Generational Shift

Most genetic variants are rare and specific to the population, highlighting the importance of characterizing local population genetic diversity. Many countries have initiated population-based whole-genome sequencing (WGS) studies. Genomic variation within Lithuanian families are not available in the...

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Autores principales: Urnikyte, Alina, Pranckeniene, Laura, Domarkiene, Ingrida, Dauengauer-Kirliene, Svetlana, Molyte, Alma, Matuleviciene, Ausra, Pilypiene, Ingrida, Kučinskas, Vaidutis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9028680/
https://www.ncbi.nlm.nih.gov/pubmed/35456375
http://dx.doi.org/10.3390/genes13040569
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author Urnikyte, Alina
Pranckeniene, Laura
Domarkiene, Ingrida
Dauengauer-Kirliene, Svetlana
Molyte, Alma
Matuleviciene, Ausra
Pilypiene, Ingrida
Kučinskas, Vaidutis
author_facet Urnikyte, Alina
Pranckeniene, Laura
Domarkiene, Ingrida
Dauengauer-Kirliene, Svetlana
Molyte, Alma
Matuleviciene, Ausra
Pilypiene, Ingrida
Kučinskas, Vaidutis
author_sort Urnikyte, Alina
collection PubMed
description Most genetic variants are rare and specific to the population, highlighting the importance of characterizing local population genetic diversity. Many countries have initiated population-based whole-genome sequencing (WGS) studies. Genomic variation within Lithuanian families are not available in the public databases. Here, we describe initial findings of a high-coverage (an average of 36.27×) whole genome sequencing for 25 trios of the Lithuanian population. Each genome on average carried approximately 4,701,473 (±28,255) variants, where 80.6% (3,787,626) were single nucleotide polymorphisms (SNPs), and the rest 19.4% were indels. An average of 12.45% was novel according to dbSNP (build 150). The WGS structural variation (SV) analysis identified on average 9133 (±85.10) SVs, of which 95.85% were novel. De novo single nucleotide variation (SNV) analysis identified 4417 variants, where 1.1% de novo SNVs were exonic, 43.9% intronic, 51.9% intergenic, and the rest 3.13% in UTR or downstream sequence. Three potential pathogenic de novo variants in the ZSWIM8, CDC42EP1, and RELA genes were identified. Our findings provide useful information on local human population genomic variation, especially for de novo variants, and will be a valuable resource for further genetic studies, and medical implications.
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spelling pubmed-90286802022-04-23 Inherited and De Novo Variation in Lithuanian Genomes: Introduction to the Analysis of the Generational Shift Urnikyte, Alina Pranckeniene, Laura Domarkiene, Ingrida Dauengauer-Kirliene, Svetlana Molyte, Alma Matuleviciene, Ausra Pilypiene, Ingrida Kučinskas, Vaidutis Genes (Basel) Article Most genetic variants are rare and specific to the population, highlighting the importance of characterizing local population genetic diversity. Many countries have initiated population-based whole-genome sequencing (WGS) studies. Genomic variation within Lithuanian families are not available in the public databases. Here, we describe initial findings of a high-coverage (an average of 36.27×) whole genome sequencing for 25 trios of the Lithuanian population. Each genome on average carried approximately 4,701,473 (±28,255) variants, where 80.6% (3,787,626) were single nucleotide polymorphisms (SNPs), and the rest 19.4% were indels. An average of 12.45% was novel according to dbSNP (build 150). The WGS structural variation (SV) analysis identified on average 9133 (±85.10) SVs, of which 95.85% were novel. De novo single nucleotide variation (SNV) analysis identified 4417 variants, where 1.1% de novo SNVs were exonic, 43.9% intronic, 51.9% intergenic, and the rest 3.13% in UTR or downstream sequence. Three potential pathogenic de novo variants in the ZSWIM8, CDC42EP1, and RELA genes were identified. Our findings provide useful information on local human population genomic variation, especially for de novo variants, and will be a valuable resource for further genetic studies, and medical implications. MDPI 2022-03-23 /pmc/articles/PMC9028680/ /pubmed/35456375 http://dx.doi.org/10.3390/genes13040569 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Urnikyte, Alina
Pranckeniene, Laura
Domarkiene, Ingrida
Dauengauer-Kirliene, Svetlana
Molyte, Alma
Matuleviciene, Ausra
Pilypiene, Ingrida
Kučinskas, Vaidutis
Inherited and De Novo Variation in Lithuanian Genomes: Introduction to the Analysis of the Generational Shift
title Inherited and De Novo Variation in Lithuanian Genomes: Introduction to the Analysis of the Generational Shift
title_full Inherited and De Novo Variation in Lithuanian Genomes: Introduction to the Analysis of the Generational Shift
title_fullStr Inherited and De Novo Variation in Lithuanian Genomes: Introduction to the Analysis of the Generational Shift
title_full_unstemmed Inherited and De Novo Variation in Lithuanian Genomes: Introduction to the Analysis of the Generational Shift
title_short Inherited and De Novo Variation in Lithuanian Genomes: Introduction to the Analysis of the Generational Shift
title_sort inherited and de novo variation in lithuanian genomes: introduction to the analysis of the generational shift
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9028680/
https://www.ncbi.nlm.nih.gov/pubmed/35456375
http://dx.doi.org/10.3390/genes13040569
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