Meta-analysis of QTLs Associated with Pest and disease resistance genes in Cassava
By: Reshma Parveen J.
Contributor(s): Sreekumar, J.(Guide).
Material type:
BookPublisher: Vellayani Department of Plant Biotechnology, College of Agriculture, 2019Description: 101p.Subject(s): Plant BiotechnologyDDC classification: 660.6 Online resources: Click here to access online Dissertation note: B.Sc.-M.Sc. Int. Abstract: Plant disease resistance is a complex trait which is controlled by quantitative trait loci (QTLs). Several QTLs have been found for cassava disease resistance. Meta-analysis provides a simple, reliable, and economical method for integrating information from multiple QTL studies across various environmental and genetic backgrounds, detecting consistent QTLs powerfully and estimating their genetic positions precisely.
The study entitled "META-ANALYSIS OF QTLs ASSOCIATED WITH PEST AND DISEASE RESISTANCE GENES IN CASSAVA" was conducted at the ICAR-CTCRI, Sreekaryam, Thiruvanathapuram during October 2018 to August 2019. The objectives of this study was to combine the results of QTL detection studies conducted on Cassava Mosaic Disease (CMD) resistance genes in cassava, to integrate this data with genomic information of cassava and to validate the results obtained using resistant and susceptible varieties.
61 QTLs from 6 different published QTL mapping studies related to Cassava Mosaic Disease (CMD) and Cassava Brown Streak Disease (CBSD) were selected. A consensus map was constructed by integrating individual linkage maps of these QTLs with a reference map (Cassava genetic linkage map). 58 QTLs from the initial 61 QTLs were then projected to this consensus map.
Using Biomercator V.4 software meta-analysis of these projected QTLs were carried out. Meta-analysis of CMD and CBSD-RN resistance QTLs were done separately. 11 MQTLs for CMD resistance and 10 MQTLs for CBSD-RN resistance were obtained. For mining candidate genes and for identifying their functional information the QTLs within the MQTLs with confidence interval less than 2cM and physical length less than1Mb were selected.
A total of 38 candidate genes associated with CMD resistance and 30 genes associated with CBSD-RN resistance were annotated. Defence related
civ
104
protein and transcription factors were found to be associated with these genes. Validation of the identified QTLs was done by using real time PCR and the genes were found to be expressed in resistant variety of cassava.
The MQTLs found in this study that have small physical and genetic intervals are useful for marker-assisted selection for developing disease resistance varieties of cassava.
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Theses
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KAU Central Library, Thrissur Theses | Reference Book | 660.6 RES/ME PG (Browse shelf) | Not For Loan | 174780 |
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B.Sc.-M.Sc. Int.
Plant disease resistance is a complex trait which is controlled by quantitative trait loci (QTLs). Several QTLs have been found for cassava disease resistance. Meta-analysis provides a simple, reliable, and economical method for integrating information from multiple QTL studies across various environmental and genetic backgrounds, detecting consistent QTLs powerfully and estimating their genetic positions precisely.
The study entitled "META-ANALYSIS OF QTLs ASSOCIATED WITH PEST AND DISEASE RESISTANCE GENES IN CASSAVA" was conducted at the ICAR-CTCRI, Sreekaryam, Thiruvanathapuram during October 2018 to August 2019. The objectives of this study was to combine the results of QTL detection studies conducted on Cassava Mosaic Disease (CMD) resistance genes in cassava, to integrate this data with genomic information of cassava and to validate the results obtained using resistant and susceptible varieties.
61 QTLs from 6 different published QTL mapping studies related to Cassava Mosaic Disease (CMD) and Cassava Brown Streak Disease (CBSD) were selected. A consensus map was constructed by integrating individual linkage maps of these QTLs with a reference map (Cassava genetic linkage map). 58 QTLs from the initial 61 QTLs were then projected to this consensus map.
Using Biomercator V.4 software meta-analysis of these projected QTLs were carried out. Meta-analysis of CMD and CBSD-RN resistance QTLs were done separately. 11 MQTLs for CMD resistance and 10 MQTLs for CBSD-RN resistance were obtained. For mining candidate genes and for identifying their functional information the QTLs within the MQTLs with confidence interval less than 2cM and physical length less than1Mb were selected.
A total of 38 candidate genes associated with CMD resistance and 30 genes associated with CBSD-RN resistance were annotated. Defence related
civ
104
protein and transcription factors were found to be associated with these genes. Validation of the identified QTLs was done by using real time PCR and the genes were found to be expressed in resistant variety of cassava.
The MQTLs found in this study that have small physical and genetic intervals are useful for marker-assisted selection for developing disease resistance varieties of cassava.
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