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Resolving the full spectrum of human genome variation using Linked-Reads
Large-scale population analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. To date, this diversity has largely been uncovered using short-read whole-genome sequencing. However, these short-read approaches fail to give a comple...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6442396/ https://www.ncbi.nlm.nih.gov/pubmed/30894395 http://dx.doi.org/10.1101/gr.234443.118 |
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author | Marks, Patrick Garcia, Sarah Barrio, Alvaro Martinez Belhocine, Kamila Bernate, Jorge Bharadwaj, Rajiv Bjornson, Keith Catalanotti, Claudia Delaney, Josh Fehr, Adrian Fiddes, Ian T. Galvin, Brendan Heaton, Haynes Herschleb, Jill Hindson, Christopher Holt, Esty Jabara, Cassandra B. Jett, Susanna Keivanfar, Nikka Kyriazopoulou-Panagiotopoulou, Sofia Lek, Monkol Lin, Bill Lowe, Adam Mahamdallie, Shazia Maheshwari, Shamoni Makarewicz, Tony Marshall, Jamie Meschi, Francesca O'Keefe, Christopher J. Ordonez, Heather Patel, Pranav Price, Andrew Royall, Ariel Ruark, Elise Seal, Sheila Schnall-Levin, Michael Shah, Preyas Stafford, David Williams, Stephen Wu, Indira Xu, Andrew Wei Rahman, Nazneen MacArthur, Daniel Church, Deanna M. |
author_facet | Marks, Patrick Garcia, Sarah Barrio, Alvaro Martinez Belhocine, Kamila Bernate, Jorge Bharadwaj, Rajiv Bjornson, Keith Catalanotti, Claudia Delaney, Josh Fehr, Adrian Fiddes, Ian T. Galvin, Brendan Heaton, Haynes Herschleb, Jill Hindson, Christopher Holt, Esty Jabara, Cassandra B. Jett, Susanna Keivanfar, Nikka Kyriazopoulou-Panagiotopoulou, Sofia Lek, Monkol Lin, Bill Lowe, Adam Mahamdallie, Shazia Maheshwari, Shamoni Makarewicz, Tony Marshall, Jamie Meschi, Francesca O'Keefe, Christopher J. Ordonez, Heather Patel, Pranav Price, Andrew Royall, Ariel Ruark, Elise Seal, Sheila Schnall-Levin, Michael Shah, Preyas Stafford, David Williams, Stephen Wu, Indira Xu, Andrew Wei Rahman, Nazneen MacArthur, Daniel Church, Deanna M. |
author_sort | Marks, Patrick |
collection | PubMed |
description | Large-scale population analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. To date, this diversity has largely been uncovered using short-read whole-genome sequencing. However, these short-read approaches fail to give a complete picture of a genome. They struggle to identify structural events, cannot access repetitive regions, and fail to resolve the human genome into haplotypes. Here, we describe an approach that retains long range information while maintaining the advantages of short reads. Starting from ∼1 ng of high molecular weight DNA, we produce barcoded short-read libraries. Novel informatic approaches allow for the barcoded short reads to be associated with their original long molecules producing a novel data type known as “Linked-Reads”. This approach allows for simultaneous detection of small and large variants from a single library. In this manuscript, we show the advantages of Linked-Reads over standard short-read approaches for reference-based analysis. Linked-Reads allow mapping to 38 Mb of sequence not accessible to short reads, adding sequence in 423 difficult-to-sequence genes including disease-relevant genes STRC, SMN1, and SMN2. Both Linked-Read whole-genome and whole-exome sequencing identify complex structural variations, including balanced events and single exon deletions and duplications. Further, Linked-Reads extend the region of high-confidence calls by 68.9 Mb. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone. |
format | Online Article Text |
id | pubmed-6442396 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Cold Spring Harbor Laboratory Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-64423962019-04-17 Resolving the full spectrum of human genome variation using Linked-Reads Marks, Patrick Garcia, Sarah Barrio, Alvaro Martinez Belhocine, Kamila Bernate, Jorge Bharadwaj, Rajiv Bjornson, Keith Catalanotti, Claudia Delaney, Josh Fehr, Adrian Fiddes, Ian T. Galvin, Brendan Heaton, Haynes Herschleb, Jill Hindson, Christopher Holt, Esty Jabara, Cassandra B. Jett, Susanna Keivanfar, Nikka Kyriazopoulou-Panagiotopoulou, Sofia Lek, Monkol Lin, Bill Lowe, Adam Mahamdallie, Shazia Maheshwari, Shamoni Makarewicz, Tony Marshall, Jamie Meschi, Francesca O'Keefe, Christopher J. Ordonez, Heather Patel, Pranav Price, Andrew Royall, Ariel Ruark, Elise Seal, Sheila Schnall-Levin, Michael Shah, Preyas Stafford, David Williams, Stephen Wu, Indira Xu, Andrew Wei Rahman, Nazneen MacArthur, Daniel Church, Deanna M. Genome Res Method Large-scale population analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. To date, this diversity has largely been uncovered using short-read whole-genome sequencing. However, these short-read approaches fail to give a complete picture of a genome. They struggle to identify structural events, cannot access repetitive regions, and fail to resolve the human genome into haplotypes. Here, we describe an approach that retains long range information while maintaining the advantages of short reads. Starting from ∼1 ng of high molecular weight DNA, we produce barcoded short-read libraries. Novel informatic approaches allow for the barcoded short reads to be associated with their original long molecules producing a novel data type known as “Linked-Reads”. This approach allows for simultaneous detection of small and large variants from a single library. In this manuscript, we show the advantages of Linked-Reads over standard short-read approaches for reference-based analysis. Linked-Reads allow mapping to 38 Mb of sequence not accessible to short reads, adding sequence in 423 difficult-to-sequence genes including disease-relevant genes STRC, SMN1, and SMN2. Both Linked-Read whole-genome and whole-exome sequencing identify complex structural variations, including balanced events and single exon deletions and duplications. Further, Linked-Reads extend the region of high-confidence calls by 68.9 Mb. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone. Cold Spring Harbor Laboratory Press 2019-04 /pmc/articles/PMC6442396/ /pubmed/30894395 http://dx.doi.org/10.1101/gr.234443.118 Text en © 2019 Marks et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by/4.0/ This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Method Marks, Patrick Garcia, Sarah Barrio, Alvaro Martinez Belhocine, Kamila Bernate, Jorge Bharadwaj, Rajiv Bjornson, Keith Catalanotti, Claudia Delaney, Josh Fehr, Adrian Fiddes, Ian T. Galvin, Brendan Heaton, Haynes Herschleb, Jill Hindson, Christopher Holt, Esty Jabara, Cassandra B. Jett, Susanna Keivanfar, Nikka Kyriazopoulou-Panagiotopoulou, Sofia Lek, Monkol Lin, Bill Lowe, Adam Mahamdallie, Shazia Maheshwari, Shamoni Makarewicz, Tony Marshall, Jamie Meschi, Francesca O'Keefe, Christopher J. Ordonez, Heather Patel, Pranav Price, Andrew Royall, Ariel Ruark, Elise Seal, Sheila Schnall-Levin, Michael Shah, Preyas Stafford, David Williams, Stephen Wu, Indira Xu, Andrew Wei Rahman, Nazneen MacArthur, Daniel Church, Deanna M. Resolving the full spectrum of human genome variation using Linked-Reads |
title | Resolving the full spectrum of human genome variation using Linked-Reads |
title_full | Resolving the full spectrum of human genome variation using Linked-Reads |
title_fullStr | Resolving the full spectrum of human genome variation using Linked-Reads |
title_full_unstemmed | Resolving the full spectrum of human genome variation using Linked-Reads |
title_short | Resolving the full spectrum of human genome variation using Linked-Reads |
title_sort | resolving the full spectrum of human genome variation using linked-reads |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6442396/ https://www.ncbi.nlm.nih.gov/pubmed/30894395 http://dx.doi.org/10.1101/gr.234443.118 |
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