Quantitative Seq-LGS: Genome-Wide Identification of Genetic Drivers of Multiple Phenotypes in Malaria Parasites

Handle URI:
http://hdl.handle.net/10754/625274
Title:
Quantitative Seq-LGS: Genome-Wide Identification of Genetic Drivers of Multiple Phenotypes in Malaria Parasites
Authors:
Abkallo, Hussein M.; Martinelli, Axel; Inoue, Megumi; Ramaprasad, Abhinay ( 0000-0001-9372-5526 ) ; Xangsayarath, Phonepadith; Gitaka, Jesse; Tang, Jianxia; Yahata, Kazuhide; Zoungrana, Augustin; Mitaka, Hayato; Hunt, Paul; Carter, Richard; Kaneko, Osamu; Mustonen, Ville; Illingworth, Christopher J.R.; Pain, Arnab ( 0000-0002-1755-2819 ) ; Culleton, Richard
Abstract:
Identifying the genetic determinants of phenotypes that impact on disease severity is of fundamental importance for the design of new interventions against malaria. Traditionally, such discovery has relied on labor-intensive approaches that require significant investments of time and resources. By combining Linkage Group Selection (LGS), quantitative whole genome population sequencing and a novel mathematical modeling approach (qSeq-LGS), we simultaneously identified multiple genes underlying two distinct phenotypes, identifying novel alleles for growth rate and strain specific immunity (SSI), while removing the need for traditionally required steps such as cloning, individual progeny phenotyping and marker generation. The detection of novel variants, verified by experimental phenotyping methods, demonstrates the remarkable potential of this approach for the identification of genes controlling selectable phenotypes in malaria and other apicomplexan parasites for which experimental genetic crosses are amenable.
KAUST Department:
Biological and Environmental Sciences and Engineering (BESE) Division
Citation:
Abkallo HM, Martinelli A, Inoue M, Ramaprasad A, Xangsayarath P, et al. (2016) Quantitative Seq-LGS: Genome-Wide Identification of Genetic Drivers of Multiple Phenotypes in Malaria Parasites. Available: http://dx.doi.org/10.1101/078451.
Publisher:
Cold Spring Harbor Laboratory Press
Issue Date:
1-Oct-2016
DOI:
10.1101/078451
Type:
Working Paper
Sponsors:
This work was supported by grants from the Naito Foundation (to R.Cu); the JSPS (project numbers Nos. JP25870525, JP24255009 and JP16K21233) (to R.Cu), A Royal Society Bilateral Grant for Co-operative Research (to R.Ca and R.Cu) and a Sasakawa Foundation Butterfield Award (to R.Cu), faculty baseline funding from the King Abdullah University of Science and Technology (KAUST) to AP, and Grants-in-Aids for Scientific Research on Innovative Areas JR23117008, MEXT, Japan (to OK). CJRI was supported by a Sir Henry Dale Fellowship, jointly funded by the Wellcome Trust and the Royal Society (Grant Number 101239/Z/13/Z). This work was conducted in part at the Joint Usage / Research Center on Tropical Disease, Institute of Tropical Medicine, Nagasaki University. We thank Ho Y. Shwen for initial contributions to the project and Andrej Fisher for discussions and for the provision of code used in the jump-diffusion analysis. AM is supported by GI-CoRE funded to the Research Center for Zoonosis Control in Hokkaido University.
Additional Links:
http://www.biorxiv.org/content/early/2017/05/16/078451
Appears in Collections:
Other/General Submission; Biological and Environmental Sciences and Engineering (BESE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorAbkallo, Hussein M.en
dc.contributor.authorMartinelli, Axelen
dc.contributor.authorInoue, Megumien
dc.contributor.authorRamaprasad, Abhinayen
dc.contributor.authorXangsayarath, Phonepadithen
dc.contributor.authorGitaka, Jesseen
dc.contributor.authorTang, Jianxiaen
dc.contributor.authorYahata, Kazuhideen
dc.contributor.authorZoungrana, Augustinen
dc.contributor.authorMitaka, Hayatoen
dc.contributor.authorHunt, Paulen
dc.contributor.authorCarter, Richarden
dc.contributor.authorKaneko, Osamuen
dc.contributor.authorMustonen, Villeen
dc.contributor.authorIllingworth, Christopher J.R.en
dc.contributor.authorPain, Arnaben
dc.contributor.authorCulleton, Richarden
dc.date.accessioned2017-07-27T11:21:47Z-
dc.date.available2017-07-27T11:21:47Z-
dc.date.issued2016-10-01en
dc.identifier.citationAbkallo HM, Martinelli A, Inoue M, Ramaprasad A, Xangsayarath P, et al. (2016) Quantitative Seq-LGS: Genome-Wide Identification of Genetic Drivers of Multiple Phenotypes in Malaria Parasites. Available: http://dx.doi.org/10.1101/078451.en
dc.identifier.doi10.1101/078451en
dc.identifier.urihttp://hdl.handle.net/10754/625274-
dc.description.abstractIdentifying the genetic determinants of phenotypes that impact on disease severity is of fundamental importance for the design of new interventions against malaria. Traditionally, such discovery has relied on labor-intensive approaches that require significant investments of time and resources. By combining Linkage Group Selection (LGS), quantitative whole genome population sequencing and a novel mathematical modeling approach (qSeq-LGS), we simultaneously identified multiple genes underlying two distinct phenotypes, identifying novel alleles for growth rate and strain specific immunity (SSI), while removing the need for traditionally required steps such as cloning, individual progeny phenotyping and marker generation. The detection of novel variants, verified by experimental phenotyping methods, demonstrates the remarkable potential of this approach for the identification of genes controlling selectable phenotypes in malaria and other apicomplexan parasites for which experimental genetic crosses are amenable.en
dc.description.sponsorshipThis work was supported by grants from the Naito Foundation (to R.Cu); the JSPS (project numbers Nos. JP25870525, JP24255009 and JP16K21233) (to R.Cu), A Royal Society Bilateral Grant for Co-operative Research (to R.Ca and R.Cu) and a Sasakawa Foundation Butterfield Award (to R.Cu), faculty baseline funding from the King Abdullah University of Science and Technology (KAUST) to AP, and Grants-in-Aids for Scientific Research on Innovative Areas JR23117008, MEXT, Japan (to OK). CJRI was supported by a Sir Henry Dale Fellowship, jointly funded by the Wellcome Trust and the Royal Society (Grant Number 101239/Z/13/Z). This work was conducted in part at the Joint Usage / Research Center on Tropical Disease, Institute of Tropical Medicine, Nagasaki University. We thank Ho Y. Shwen for initial contributions to the project and Andrej Fisher for discussions and for the provision of code used in the jump-diffusion analysis. AM is supported by GI-CoRE funded to the Research Center for Zoonosis Control in Hokkaido University.en
dc.publisherCold Spring Harbor Laboratory Pressen
dc.relation.urlhttp://www.biorxiv.org/content/early/2017/05/16/078451en
dc.rightsThe copyright holder for this preprint is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.titleQuantitative Seq-LGS: Genome-Wide Identification of Genetic Drivers of Multiple Phenotypes in Malaria Parasitesen
dc.typeWorking Paperen
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Divisionen
dc.eprint.versionPre-printen
dc.contributor.institutionGraduate School of Biomedical Sciences, Nagasaki University, Nagasaki, Japanen
dc.contributor.institutionInstitute of Immunology and Infection Research, School of Biological Sciences, University of Edinburgh, Edinburgh, UKen
dc.contributor.institutionMalaria Unit, Department of Pathology, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japanen
dc.contributor.institutionGlobal Station for Zoonosis Control, Global Institution for Collaborative Research and Education (GI-CoRE), Hokkaido University, Sapporo, Japanen
dc.contributor.institutionNational Institute of Public Health, Vientiane, Lao PDRen
dc.contributor.institutionDepartment of Protozooolgy, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japanen
dc.contributor.institutionCentre for Malaria Elimination, School of Medicine, Mount Kenya University, Thika, Kenyaen
dc.contributor.institutionKey Laboratory of National Health and Family Planning Commission on Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, Jiangsu, Chinaen
dc.contributor.institutionSchool of Medicine, Nagasaki University, Nagasaki, Japanen
dc.contributor.institutionWellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdomen
dc.contributor.institutionDepartment of Genetics, University of Cambridge, Cambridge, UKen
kaust.authorMartinelli, Axelen
kaust.authorRamaprasad, Abhinayen
kaust.authorPain, Arnaben
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