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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-9028680 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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