Bayesian inference of reassortment networks reveals fitness benefits of reassortment in human influenza viruses
Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this, studying the reassortment process has been constrained by the lack of a coherent, model-based inference framework. Here, we introduce a coalescent...
Gespeichert in:
| Veröffentlicht in: | Proceedings of the National Academy of Sciences - PNAS Jg. 117; H. 29; S. 17104 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
21.07.2020
|
| ISSN: | 1091-6490, 1091-6490 |
| Online-Zugang: | Weitere Angaben |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this, studying the reassortment process has been constrained by the lack of a coherent, model-based inference framework. Here, we introduce a coalescent-based model that allows us to explicitly model the joint coalescent and reassortment process. In order to perform inference under this model, we present an efficient Markov chain Monte Carlo algorithm to sample rooted networks and the embedding of phylogenetic trees within networks. This algorithm provides the means to jointly infer coalescent and reassortment rates with the reassortment network and the embedding of segments in that network from full-genome sequence data. Studying reassortment patterns of different human influenza datasets, we find large differences in reassortment rates across different human influenza viruses. Additionally, we find that reassortment events predominantly occur on selectively fitter parts of reassortment networks showing that on a population level, reassortment positively contributes to the fitness of human influenza viruses.Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this, studying the reassortment process has been constrained by the lack of a coherent, model-based inference framework. Here, we introduce a coalescent-based model that allows us to explicitly model the joint coalescent and reassortment process. In order to perform inference under this model, we present an efficient Markov chain Monte Carlo algorithm to sample rooted networks and the embedding of phylogenetic trees within networks. This algorithm provides the means to jointly infer coalescent and reassortment rates with the reassortment network and the embedding of segments in that network from full-genome sequence data. Studying reassortment patterns of different human influenza datasets, we find large differences in reassortment rates across different human influenza viruses. Additionally, we find that reassortment events predominantly occur on selectively fitter parts of reassortment networks showing that on a population level, reassortment positively contributes to the fitness of human influenza viruses. |
|---|---|
| AbstractList | Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this, studying the reassortment process has been constrained by the lack of a coherent, model-based inference framework. Here, we introduce a coalescent-based model that allows us to explicitly model the joint coalescent and reassortment process. In order to perform inference under this model, we present an efficient Markov chain Monte Carlo algorithm to sample rooted networks and the embedding of phylogenetic trees within networks. This algorithm provides the means to jointly infer coalescent and reassortment rates with the reassortment network and the embedding of segments in that network from full-genome sequence data. Studying reassortment patterns of different human influenza datasets, we find large differences in reassortment rates across different human influenza viruses. Additionally, we find that reassortment events predominantly occur on selectively fitter parts of reassortment networks showing that on a population level, reassortment positively contributes to the fitness of human influenza viruses.Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this, studying the reassortment process has been constrained by the lack of a coherent, model-based inference framework. Here, we introduce a coalescent-based model that allows us to explicitly model the joint coalescent and reassortment process. In order to perform inference under this model, we present an efficient Markov chain Monte Carlo algorithm to sample rooted networks and the embedding of phylogenetic trees within networks. This algorithm provides the means to jointly infer coalescent and reassortment rates with the reassortment network and the embedding of segments in that network from full-genome sequence data. Studying reassortment patterns of different human influenza datasets, we find large differences in reassortment rates across different human influenza viruses. Additionally, we find that reassortment events predominantly occur on selectively fitter parts of reassortment networks showing that on a population level, reassortment positively contributes to the fitness of human influenza viruses. |
| Author | Dudas, Gytis Stolz, Ugnė Müller, Nicola F Stadler, Tanja Vaughan, Timothy G |
| Author_xml | – sequence: 1 givenname: Nicola F surname: Müller fullname: Müller, Nicola F – sequence: 2 givenname: Ugnė surname: Stolz fullname: Stolz, Ugnė – sequence: 3 givenname: Gytis surname: Dudas fullname: Dudas, Gytis – sequence: 4 givenname: Tanja surname: Stadler fullname: Stadler, Tanja – sequence: 5 givenname: Timothy G surname: Vaughan fullname: Vaughan, Timothy G |
| BookMark | eNpljEFLAzEQRoNUsK2eveboZWsmm26SoxatQsGLnks2neDqdlJ3div66y3Ug-Dpe3zw3kSMKBMKcQlqBsqW1zsKPAMPrlQGwJ6IMSgPRWW8Gv3hMzFhflNK-blTY5FvwxdyE0g2lLBDiihzkh0G5tz1W6ReEvafuXvnw7vH0LJMTU_ILGskPDD_MxqSr8P2GG0HpO8g9003MPK5OE2HBF787lS83N89Lx6K1dPycXGzKqLxpi_qqNGmGL2OAZyKVWlrVyKasIES9dxZ7UxtDRo9TxuIunaVTghVrLRxDvVUXB27uy5_DMj9ettwxLYNhHngtTYaQFVeWf0D_r9ixw |
| CitedBy_id | crossref_primary_10_3389_fpubh_2022_994949 crossref_primary_10_1002_jmv_70155 crossref_primary_10_1038_s41579_023_00945_8 crossref_primary_10_1038_s41598_023_30667_z crossref_primary_10_1016_j_virs_2024_02_005 crossref_primary_10_3390_v16010105 crossref_primary_10_1038_s41591_024_03300_3 crossref_primary_10_1038_s41598_025_91026_8 crossref_primary_10_1093_ve_veac005 crossref_primary_10_1093_molbev_msae173 crossref_primary_10_3389_fmicb_2021_793500 crossref_primary_10_1371_journal_pcbi_1013301 crossref_primary_10_1073_pnas_2503565122 crossref_primary_10_1016_j_tree_2021_04_013 crossref_primary_10_1111_irv_70028 crossref_primary_10_1002_evl3_247 crossref_primary_10_1080_03079457_2023_2236568 crossref_primary_10_1093_molbev_msab342 crossref_primary_10_1128_jvi_01056_23 crossref_primary_10_3390_urbansci8020063 crossref_primary_10_1093_molbev_msae078 crossref_primary_10_3390_microorganisms10050900 crossref_primary_10_1073_pnas_2211098120 crossref_primary_10_21105_joss_07773 crossref_primary_10_1038_s41598_024_70023_3 crossref_primary_10_1371_journal_pcbi_1010394 crossref_primary_10_1128_spectrum_01762_23 crossref_primary_10_1038_s41467_022_31749_8 crossref_primary_10_1371_journal_pcbi_1010422 crossref_primary_10_3390_v14050958 crossref_primary_10_1093_sysbio_syad040 crossref_primary_10_1093_molbev_msaf133 crossref_primary_10_3390_v14122764 |
| ContentType | Journal Article |
| Copyright | Copyright © 2020 the Author(s). Published by PNAS. |
| Copyright_xml | – notice: Copyright © 2020 the Author(s). Published by PNAS. |
| DBID | 7X8 |
| DOI | 10.1073/pnas.1918304117 |
| DatabaseName | MEDLINE - Academic |
| DatabaseTitle | MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic |
| Database_xml | – sequence: 1 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database |
| DeliveryMethod | no_fulltext_linktorsrc |
| Discipline | Sciences (General) |
| EISSN | 1091-6490 |
| GroupedDBID | --- -DZ -~X .55 0R~ 123 29P 2AX 2FS 2WC 4.4 53G 5RE 5VS 7X8 85S AACGO AAFWJ AANCE ABBHK ABOCM ABPLY ABPPZ ABTLG ABXSQ ABZEH ACGOD ACHIC ACIWK ACNCT ACPRK ADQXQ AENEX AEUPB AEXZC AFFNX AFRAH ALMA_UNASSIGNED_HOLDINGS AQVQM BKOMP CS3 D0L DCCCD DIK DU5 E3Z EBS F5P FRP GX1 H13 HH5 HYE IPSME JAAYA JBMMH JENOY JHFFW JKQEH JLS JLXEF JPM JSG JST KQ8 L7B LU7 N9A N~3 O9- OK1 PNE PQQKQ R.V RHI RNA RNS RPM RXW SA0 SJN TAE TN5 UKR W8F WH7 WOQ WOW X7M XSW Y6R YBH YKV YSK ZCA ~02 ~KM |
| ID | FETCH-LOGICAL-c494t-bc2e7fcc92ca180c637b83ee4ad13e2587284b74e425fd1c2b862fe16c62488e2 |
| IEDL.DBID | 7X8 |
| ISICitedReferencesCount | 38 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000553294300005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1091-6490 |
| IngestDate | Fri Sep 05 10:42:52 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 29 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c494t-bc2e7fcc92ca180c637b83ee4ad13e2587284b74e425fd1c2b862fe16c62488e2 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| OpenAccessLink | https://www.pnas.org/content/pnas/117/29/17104.full.pdf |
| PQID | 2421106907 |
| PQPubID | 23479 |
| ParticipantIDs | proquest_miscellaneous_2421106907 |
| PublicationCentury | 2000 |
| PublicationDate | 2020-07-21 |
| PublicationDateYYYYMMDD | 2020-07-21 |
| PublicationDate_xml | – month: 07 year: 2020 text: 2020-07-21 day: 21 |
| PublicationDecade | 2020 |
| PublicationTitle | Proceedings of the National Academy of Sciences - PNAS |
| PublicationYear | 2020 |
| SSID | ssj0009580 |
| Score | 2.5228593 |
| Snippet | Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this,... |
| SourceID | proquest |
| SourceType | Aggregation Database |
| StartPage | 17104 |
| Title | Bayesian inference of reassortment networks reveals fitness benefits of reassortment in human influenza viruses |
| URI | https://www.proquest.com/docview/2421106907 |
| Volume | 117 |
| WOSCitedRecordID | wos000553294300005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3NS8MwFA_qPHhR5wd-E8GDHuKaNGvSk6g4PMjwoLDbSNIEemnnsg30r_elS3HgRfDWQvsoL68v7yu_H0JXKXOUCeVIIvKCcMEdUX2pCJPUWF2AlbgGxPVFDIdyNMpfY8HNx7HK1ic2jrqoTaiR90LrkgZYXXE3-SCBNSp0VyOFxjrqpBDKhJEuMZIroLtyiUaQU5LxPGmhfUTam1TK30KuIiGdp5GtbNUTN9vLYOe_H7aLtmNgie-XltBFa7baQ93463p8HfGlb_ZR_aA-bTg7icv2tB-uHQ7T6R6C8VAuxNVyOtzjgPAEFopdOQtOEWsQA9f-1xtlhRu-vyA00J58Kbwop3Nv_QF6Hzy9PT6TyLtADM_5jGjDrHDG5MwoKhOTpULL1FquCppa1pcC9jQtuA0rWVDDNKRFztLMZAz8gWWHaKOqK3uEsIY78KAqcc5CJud0IbkCQRlVzCTCHaPLVqljsOvQrFCVred-_KPWkz88c4q2WEiEE0EYPUMdB5qx52jTLGaln140ZvEN4dnF8A |
| linkProvider | ProQuest |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Bayesian+inference+of+reassortment+networks+reveals+fitness+benefits+of+reassortment+in+human+influenza+viruses&rft.jtitle=Proceedings+of+the+National+Academy+of+Sciences+-+PNAS&rft.au=M%C3%BCller%2C+Nicola+F&rft.au=Stolz%2C+Ugn%C4%97&rft.au=Dudas%2C+Gytis&rft.au=Stadler%2C+Tanja&rft.date=2020-07-21&rft.issn=1091-6490&rft.eissn=1091-6490&rft.volume=117&rft.issue=29&rft.spage=17104&rft_id=info:doi/10.1073%2Fpnas.1918304117&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1091-6490&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1091-6490&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1091-6490&client=summon |