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Transcript
Towards utilization of genome
sequence information for
pigeonpea improvement
By
ICAR institutes, SAUs and ICRISAT
Pigeonpea
(Cajanus cajan L. Millsp)
 Belongs to family Leguminosae
with chromosome no. 2n=22
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
Climate change!
Pigeonpea – production trends
(last five decades)
4.00
3.50
3.00
2.50
Area (M ha)
2.00
Production (M tonnes)
1.50
Productivity (tonnes/ha)
1.00
0.50
0.00
1950-60
1961-70
1971-1980
1981-1990
1991-2000
2001-2007
Years
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
Some constraints in
pigeonpea production
Sterility mosaic disease (SMD)
Fusarium wilt (FW)
A route developed and taken by
breeders: From germplasm to
variety/hybrid
Germplasm
Superior variety
Genomics-assisted breeding:
Predicting the phenotype
Genotype
Genetic Mapping
Physical Mapping
EST Sequencing
Genome Sequencing
Map-based Cloning
Gene(s)
Genetic
Resources
Genetic Mapping
Association Mapping
QTL Mapping
Trait Correlations
Improved
germplasm
Trait/QTL
Transcriptomics
Proteomics
Metabolomics
TILLING
EcoTILLING
Phenotype
Trends Pl Science 2005;
Trends Biotech 2006
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
Example of development of a submergence
tolerant version of Swarna, a widely grown
variety, in 2½ years
X
Swarna:
Non-tolerant
IR49830-7:
Marker-assisted backcrossing tolerant
• Target gene selection
• Recombinant selection
• Background selection
Sub1
Swarna-Sub1
Courtesy of David Mackill, IRRI
BC2
or BC3
New Sub1 lines (in yellow) and recurrent
parents (in white) after 17 days
submergence in field at IRRI, 2007DS
IR64-Sub1
Samba-Sub1
Samba
IR49830 (Sub1)
Samba
IR64
IR42
IR42
IR64
IR49830 (Sub1)
IR49830 (Sub1)
IR64-Sub1
IR64
Samba
Samba-Sub1
IR64-Sub1
IR42
IR49830 (Sub1)
IR42
IR64-Sub1
Samba
Samba-Sub1
IR64
Courtesy of David Mackill, IRRI
IR49830 (Sub1)
Swarna-Sub1 in U.P.
(Faizabad area)
Courtesy of David Mackill, IRRI, The Philippines
Challenges in genomicsassisted 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
Germplasm
Superior variety
Developing infrastructures and
sign posts for providing directions
(Indo-US AKI, CGIAR-GCP, US-NSF)
Gene/transcriptomic/
SNP resources
Resource
SSRs
Pigeonpea
29,000
SNPs
GoldenGate
35,000
768 SNPs
KASPar assays
1,616 SNPs
DArT arrays
15,360
Sanger ESTs
454 /FLX reads
TUSs
~20,000
496,705
21,432
Illumina reads
(million reads)
>160
(14 parents)
CMS and mt genome
sequencing of pigeonpea
Production of
A- line seeds
Production of
hybrid seeds for
commercial crop
Commercial
pigeonpea hybrids
production
ICPA 2039, ICPB 2039, ICPH 2433 & ICPW 29
sequenced using 454 technology
From Orphan crop- genomic resources rich crop
Phylogenetic analysis of Cajanus
spp. using KASPar assays
Cluster-I
Cluster-II
Cluster-III
How to use this genome information…
Objectives
 Molecular mapping of resistance to biotic and
abiotic stresses
- Mapping populations available
and Rf
- Genotyping and phenotyping
- Marker trait association for resistance to FW, SMD
 Enhancing the genetic base of pigeonpea
genepool by developing multi-parents populations
- MAGIC population (2000 lines) developed using 8 parents
lines
at
- NAM population (50 crosses-1000 lines) with 50 parents
- High density genotyping or genotyping by sequencing of 3000
- Phenotyping of MAGIC and NAM populations (each population
least in 3 environments)
 Genome wide association studies based on resequencing and phenotyping of germplasm set
- Germplasm set of 300-500 lines assembled
different
- Genotyping-by-sequencing of the germplasm set
- Precise phenotyping of the germplasm set by
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
 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
resistance
- Mining of superior allleles/haplotypes for disease
 Validation and characterization of ca. 200
abiotic stress tolerance genes
-
traits
Genetic mapping of abiotic stress tolerance genes
- Association of genes with abiotic stress tolerance
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
Possible partners
NRCPB, New Delhi
NBPGR, New Delhi
IIPR, Kanpur
IARI, New Delhi
Uni Agril Sciences- Bangalore
Banaras Hindu University
ANGRAU- Hyderabad