This document discusses utilizing genome sequence information to improve pigeonpea. Pigeonpea is an important crop but productivity has remained stagnant. Challenges include a narrow genetic base and lack of molecular markers. The document outlines developing genetic resources like mapping populations and sequencing ESTs, SNPs, and genomes. It proposes using these resources to map resistance to diseases and abiotic stresses, enhance genetic diversity through multi-parent populations, and conduct genome-wide association studies. Characterizing resistance genes and developing stress-tolerant lines and molecular markers could benefit pigeonpea breeding.

1. Towards utilization of genome
sequence information for
pigeonpea improvement
By
ICAR institutes, SAUs and ICRISAT

2.  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
 Belongs to family Leguminosae
with chromosome no. 2n=22
and genome size of ~833 Mbp
Pigeonpea
(Cajanus cajan L. Millsp)

3. Climate change!

4. Pigeonpea – production trends
(last five decades)
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
1950-60 1961-70 1971-1980 1981-1990 1991-2000 2001-2007
Years
Area (M ha)
Production (M tonnes)
Productivity (tonnes/ha)
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

5. Some constraints in
pigeonpea production
Sterility mosaic disease (SMD)
Fusarium wilt (FW)

6. A route developed and taken by
breeders: From germplasm to
variety/hybrid
Germplasm
Superior variety

7. Genomics-assisted breeding:
Predicting the phenotype
Genotype
Gene(s)
Trait/QTL
Phenotype
Transcriptomics
Proteomics
Metabolomics
TILLING
EcoTILLING
EST Sequencing
Genome Sequencing
Map-based Cloning
Genetic Mapping
Physical Mapping
Genetic Mapping
Association Mapping
QTL Mapping
Trait Correlations
Genetic
Resources
Improved
germplasm
Trends Pl Science 2005;
Trends Biotech 2006

8. 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

9. Example of development of a submergence
tolerant version of Swarna, a widely grown
variety, in 2½ years
Marker-assisted backcrossing
IR49830-7:
tolerant
Swarna-Sub1
Swarna:
Non-tolerant
Sub1• Target gene selection
• Recombinant selection
• Background selection
BC2
or BC3
X
Courtesy of David Mackill, IRRI

10. New Sub1 lines (in yellow) and recurrent
parents (in white) after 17 days
submergence in field at IRRI, 2007DS
Samba
Samba-
Sub1
Samba-Sub1
IR64-Sub1
IR49830 (Sub1)
IR64
IR42
IR64
IR64-Sub1
Samba-Sub1
IR49830 (Sub1)
Samba
IR64
IR64-Sub1 IR49830 (Sub1)
IR42
IR64-Sub1
IR64
IR49830 (Sub1)
IR49830 (Sub1)
IR42
Samba
IR42
Samba
Courtesy of David Mackill, IRRI

11. Swarna-Sub1 in U.P.
(Faizabad area)
Courtesy of David Mackill, IRRI, The Philippines

12. 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

13. Germplasm
Superior variety

14. Developing infrastructures and
sign posts for providing directions
(Indo-US AKI, CGIAR-GCP, US-NSF)

15. 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)
>160
(14 parents)
Gene/transcriptomic/
SNP resources

16. 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

17. From Orphan crop- genomic resources rich crop

21. Phylogenetic analysis of Cajanus
spp. using KASPar assays
Cluster-I
Cluster-II
Cluster-III

22. How to use this genome information…

23. 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)

24.  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

25.  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

26. 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

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