Show simple item record

dc.creatorBelaarouch, Oussamaen_US
dc.date2018-10-26en_US
dc.date.accessioned2019-08-04T13:46:06Z
dc.date.available2019-08-04T13:46:06Z
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/813a2cfa17b3ecae3cc3bc6a39ce439een_US
dc.identifier.citationOussama Belaarouch. (26/10/2018). Meta-analysis of QTL and ontology-based candidate gene prioritization for key agronomic agronomic traits in cereals.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/10142
dc.description.abstractQTL mapping remains an unavoidable technique to decipher the genetic components of quantitative traits variation in plants and especially in cereals given its economic importance. However the efficiency of statistical methods and the advance made in conducting such experiments, There still exist some bottlenecks mainly represented in the lack of heterogeneity between different studies, lack of results validation, and also imprecise statistical QTL detection leads to huge confidence intervals which increases candidate gene mining complexity. However, data integration methods such as meta-analysis can provide an efficient framework to detect “real” QTL and narrow down their confidence intervals for better control of candidate gene mining. Therefore, the objective of the first part of this work is to provide an overview of current advances in QTL analysis and meta-analysis highlighting different statistical methods and computational tools employed. In the second part, a meta-analysis approach has been applied on published QTL associated with Fusarium head blight resistance in barley. And in last part, a meta-analysis of QTL associated with four flowering time related traits in maize was performed using public QTL datasets associated with flowering-time related traits in maize, also an ontology-based candidate gene prioritization approach has been executed on genes flaking detected metaQTL confidence intervals in order to detect GO terms that are most over-represented in these regions.en_US
dc.formatDOCen_US
dc.languageenen_US
dc.rightsCC-BY-NC-4.0en_US
dc.subjectmeta-analysisen_US
dc.subjectcandidate geneen_US
dc.subjectqtl analysisen_US
dc.subjectmasen_US
dc.subjectgene ontologyen_US
dc.subjectflowering-timeen_US
dc.subjectfhben_US
dc.subjectgseaen_US
dc.titleMeta-analysis of QTL and ontology-based candidate gene prioritization for key agronomic agronomic traits in cerealsen_US
dc.typeThesisen_US
cg.subject.agrovoccerealsen_US
cg.subject.agrovocprioritizationen_US
cg.contributor.centerMohammed V University at Agdal**en_US
cg.contributor.crpCGIAR Research Program for Managing and Sustaining Crop Collections - Genebanksen_US
cg.contributor.funderFood and Agriculture Organization of the United Nations - FAOen_US
cg.contributor.projectIn vitro culture and genomics-assisted fast track improvement of local landraces of wheat and barley in Morocco, Tunisia and Algeria for enhancing food security and adaptation to climate changeen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.regionGlobalen_US
cg.contactbelaarouch.95@gmail.comen_US
dc.identifier.statusOpen accessen_US
mel.project.openhttp://www.google.comen_US


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record


DSpace software copyright © 2002-2016  DuraSpace
Disclaimer:
MELSpace content providers and partners accept no liability to any consequence resulting from use of the content or data made available in this repository. Users of this content assume full responsibility for compliance with all relevant national or international regulations and legislation.
Theme by 
Atmire NV