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QTL Mapping of Cotton Verticillium Wilt Resistance
Presented By..
Ripon Kumar Sikder, PhD Fellow
Institute of Cotton Research, CAAS
Abstract
 Cotton (Gossypium spp. L.) is considered as the foremost natural fiber with an
estimated production and utilization of∼115 million bales.
 From sowing to harvest, cotton may suffer from more than 40 types of diseases,
which lead to economic losses of approximately 15% in China.
 The most serious of these diseases is Verticillium wilt, which is caused by fungal
pathogen called Verticillium dahliae, a serious soil-borne disease with international
consequences for cotton production (Ren et al., 2014).
 To date, the most effective and feasible way to control wilt disease has been to
develop new cotton varieties resistant to Verticillium wilt.
 Therefore, the present study seeks to identify major QTL associated with Cotton
Verticillium Wilt Resistance.
 Cotton (Gossypium spp. L.) - most important cash crops around the world because of
the significant economic value of its textile
 fiber, feed, food stuff
 oil and biofuel products (Chen et al., 2007)
 50 species with 45 diploid and 5 allotetraploid species in the Gossypium genus.
 Two cultivated tetraploid cotton species, G. hirsutum accounts for 90% of cotton
production in the world while G. barbadense contributes about 9% (USDA-NASS2013).
 Genetic variation is extremely limited in polyploid species such as G. hirsutum,
especially among elite cultivated types (Mei et al., 2004).
Introduction
 Gossypium barbadense L. is highly resistant to Verticillium Wilt compared to G. hirsutum L.
 At least 60 different Verticillium wilt resistance QTLs have been reported on 10
chromosomes or linkage groups of cotton (Zhao et al., 2013).
 The QTLs were mapped in four different biparental populations and poorly co-localized, thus
markers linked to these QTLs are not directly used in cotton breeding.
 Genetic mapping and validation of QTL for Verticillium Wilt resistance in cotton is the most
important factor for cotton breeding (Li et al., 2014)
 Mapping QTLs involving Verticillium Wilt resistance in cotton is necessary for the genetic
basis of Verticillium Wilt resistance (Luo et al., 2014).
Introduction
The present project comprises-
 Identification of QTL for Verticillium Wilt resistance that is stable across
multiple generations and environments.
 Construction of a linkage map.
 Identification of QTLs through MAS.
Objectives
Materials & Methods
Plant Materials:
Individuals that were generated from the cross
between Zhong 36 and Hai 1.
Phenotyping
Data Collection
DNA Extraction
PCR Primers and Assays
Marker Data Acquisition & Linkage Map
Construction
Chromosome Assignments
QTL Analysis
Methods:
The annual work plan could be categorized as follows
Population screening
Field data collection and validation in
greenhouse, SSR genotyping
Data analysis
Construction of genetic map
QTL analysis
Result preparation and submit final
paper
Annual Work Plan
SN Budget head Proposed Amount (RMB)
1 Travelling allowance 5000
2 Phenotyping work 15000
3 Genotyping work 30000
4 Stationary & Printing 2000
5 Publications 5000
6 Miscellaneous 6000
Total 63000
Budget Estimation
QTL Mapping of Cotton Verticillium Wilt Resistance

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QTL Mapping of Cotton Verticillium Wilt Resistance

  • 1. QTL Mapping of Cotton Verticillium Wilt Resistance Presented By.. Ripon Kumar Sikder, PhD Fellow Institute of Cotton Research, CAAS
  • 2. Abstract  Cotton (Gossypium spp. L.) is considered as the foremost natural fiber with an estimated production and utilization of∼115 million bales.  From sowing to harvest, cotton may suffer from more than 40 types of diseases, which lead to economic losses of approximately 15% in China.  The most serious of these diseases is Verticillium wilt, which is caused by fungal pathogen called Verticillium dahliae, a serious soil-borne disease with international consequences for cotton production (Ren et al., 2014).  To date, the most effective and feasible way to control wilt disease has been to develop new cotton varieties resistant to Verticillium wilt.  Therefore, the present study seeks to identify major QTL associated with Cotton Verticillium Wilt Resistance.
  • 3.  Cotton (Gossypium spp. L.) - most important cash crops around the world because of the significant economic value of its textile  fiber, feed, food stuff  oil and biofuel products (Chen et al., 2007)  50 species with 45 diploid and 5 allotetraploid species in the Gossypium genus.  Two cultivated tetraploid cotton species, G. hirsutum accounts for 90% of cotton production in the world while G. barbadense contributes about 9% (USDA-NASS2013).  Genetic variation is extremely limited in polyploid species such as G. hirsutum, especially among elite cultivated types (Mei et al., 2004). Introduction
  • 4.  Gossypium barbadense L. is highly resistant to Verticillium Wilt compared to G. hirsutum L.  At least 60 different Verticillium wilt resistance QTLs have been reported on 10 chromosomes or linkage groups of cotton (Zhao et al., 2013).  The QTLs were mapped in four different biparental populations and poorly co-localized, thus markers linked to these QTLs are not directly used in cotton breeding.  Genetic mapping and validation of QTL for Verticillium Wilt resistance in cotton is the most important factor for cotton breeding (Li et al., 2014)  Mapping QTLs involving Verticillium Wilt resistance in cotton is necessary for the genetic basis of Verticillium Wilt resistance (Luo et al., 2014). Introduction
  • 5. The present project comprises-  Identification of QTL for Verticillium Wilt resistance that is stable across multiple generations and environments.  Construction of a linkage map.  Identification of QTLs through MAS. Objectives
  • 6. Materials & Methods Plant Materials: Individuals that were generated from the cross between Zhong 36 and Hai 1. Phenotyping Data Collection DNA Extraction PCR Primers and Assays Marker Data Acquisition & Linkage Map Construction Chromosome Assignments QTL Analysis Methods:
  • 7. The annual work plan could be categorized as follows Population screening Field data collection and validation in greenhouse, SSR genotyping Data analysis Construction of genetic map QTL analysis Result preparation and submit final paper Annual Work Plan
  • 8. SN Budget head Proposed Amount (RMB) 1 Travelling allowance 5000 2 Phenotyping work 15000 3 Genotyping work 30000 4 Stationary & Printing 2000 5 Publications 5000 6 Miscellaneous 6000 Total 63000 Budget Estimation