Towards utilization of genome sequence information for

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Towards utilization of genome sequence
information for pigeonpea improvement
By ICAR institutes, SAUs and
ICRISAT
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Pigeonpea (Cajanus cajan L. Millsp)

• Belongs to family Leguminosae with chromosome
  no. 2n22 and genome size of 833 Mbp

• A major source of protein to about 20 of the
  world population (Thu et al., 2003)
• An abundant source of minerals and vitamins
  (Saxena et al., 2002)
• Most versatile food legume with diversified uses
  such as food, feed, fodder and fuel
• It is hardy, widely adaptable crop with better
  tolerance to drought and high temperature

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Climate change!
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Pigeonpea production trends (last five decades)
Unfortunately, no increase has been witnessed in
its productivity (yield kg ha-1), which in the
past five decades has remained stagnant at around
700 kg ha-1
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Some constraints in pigeonpea production
Fusarium wilt (FW)
Sterility mosaic disease (SMD)
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A route developed and taken by breeders From
germplasm to variety/hybrid
Germplasm
Superior variety
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Genomics-assisted breeding Predicting the
phenotype
Genotype
EST Sequencing Genome Sequencing Map-based Cloning
Genetic Mapping Physical Mapping
Gene(s)
Genetic Resources
Improved germplasm
Trait/QTL
Transcriptomics Proteomics Metabolomics TILLING Ec
oTILLING
Genetic Mapping Association Mapping QTL
Mapping Trait Correlations
Phenotype
Trends Pl Science 2005 Trends Biotech 2006
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A variety of approaches (cars)

• MAS MARKER-ASSISTED SELECTION
• - Plants are selected for one or more (up to
  8-10) alleles
• MABC MARKER-ASSISTED BACKCROSSING
• One or more (up to 6-8) donor alleles are
  transferred to an
  elite line
• MARS MARKER-ASSISTED RECURRENT SELECTION
• Selection for several (up to 20-30) mapped QTLs
  relies on index (genetic)
  values computed for each individual
  based on its haplotype at target QTLs
• GWS GENOME-WIDE SELECTION
• Selection of genome-wide several loci that confer
  
• tolerance/resistance/ superiority to traits of
  interest using GEBVs
  based on genome-wide marker profiling

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Example of development of a submergence tolerant
version of Swarna, a widely grown variety, in 2½
years
X
Swarna Non-tolerant
IR49830-7 tolerant
Marker-assisted backcrossing

• Target gene selection
• Recombinant selection
• Background selection

Sub1
BC2 or BC3
Swarna-Sub1
Courtesy of David Mackill, IRRI
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New Sub1 lines (in yellow) and recurrent parents
(in white) after 17 days submergence in field at
IRRI, 2007DS
Courtesy of David Mackill, IRRI
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Swarna-Sub1 in U.P. (Faizabad area)
Courtesy of David Mackill, IRRI, The Philippines
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Challenges in genomics- assisted crop improvement

• Narrow genetic base in the primary gene pool
• Very few molecular (SSR) markers
• Non-availability of appropriate germplasm such as
  mapping populations
• Intraspecific genetic map with low marker density
• Non-availability of trait-associated markers in
  breeding
• Issues of costs and expertise in molecular
  breeding

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Developing infrastructures and sign posts for
providing directions (Indo-US AKI, CGIAR-GCP,
US-NSF)
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Gene/transcriptomic/ SNP resources
Resource Pigeonpea
SSRs 29,000
SNPs 35,000
GoldenGate 768 SNPs
KASPar assays 1,616 SNPs
DArT arrays 15,360
Sanger ESTs 20,000
454 /FLX reads 496,705
TUSs 21,432
Illumina reads (million reads) gt160 (14 parents)
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CMS and mt genome sequencing of pigeonpea

• ICPA 2039, ICPB 2039, ICPH 2433 ICPW 29
  sequenced using 454 technology

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From Orphan crop- genomic resources rich crop
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Phylogenetic analysis of Cajanus spp. using
KASPar assays
Cluster-I
Cluster-II
Cluster-III
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How to use this genome information
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Objectives

• Molecular mapping of resistance to biotic and
  abiotic stresses
• - Mapping populations available
• - Genotyping and phenotyping
• - Marker trait association for resistance to
  FW, SMD and Rf
• Enhancing the genetic base of pigeonpea genepool
  by developing multi-parents populations
• - MAGIC population (2000 lines) developed using
  8 parents
• - NAM population (50 crosses-1000 lines) with
  50 parents
• - High density genotyping or genotyping by
  sequencing of 3000 lines
• - Phenotyping of MAGIC and NAM populations
  (each population at least in 3 environments)
• - Marker trait association analysis for traits
  of interest

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• Genome wide association studies based on
  re-sequencing and phenotyping of germplasm set
• - Germplasm set of 300-500 lines assembled
• - Genotyping-by-sequencing of the germplasm
  set
• - Precise phenotyping of the germplasm set by
  different partners
• - Fine mapping of traits of interest for
  breeders
• Bioinformatics analysis to improve the quality
  of
• draft genome
• - Two genome assemblies need to be merged
• - Defining a consensus genes set
• - Breeders-friendly genome databases

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• Validation and characterization of 1213 disease
  resistance genes
• - Genetic mapping of disease resistance genes
• - Association of genes with disease
  resistance traits
• - Functional validation of selected set of
  candidate genes
• - Mining of superior allleles/haplotypes for
  disease resistance
• Validation and characterization of ca. 200
  abiotic stress tolerance genes
• - Genetic mapping of abiotic stress tolerance
  genes
• - Association of genes with abiotic stress
  tolerance traits
• - Functional validation of selected set of
  candidate genes
• - Mining of superior allleles/haplotypes for
  abiotic stress tolerance genes

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Possible outcomes

• Superior breeding lines for traits of interest
  with enhanced genetic diversity
• Molecular markers associated with resistance to
• biotic stresses and tolerance to abiotic
  stresses
• Alleles and haplotype information available on
  germplasm set so that breeders can use
  informative lines
• Set of well characterized disease resistance and
• abiotic stress tolerance genes
• Breeder-friendly genome database of pigeonpea

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Possible partners
NRCPB, New Delhi NBPGR, New Delhi
IIPR, Kanpur IARI, New Delhi Uni Agril
Sciences- Bangalore Banaras Hindu
University ANGRAU- Hyderabad