Theor Appl Genet (2009) 119:1193–1204

DOI 10.1007/s00122-009-1120-4

ORIGINAL PAPER

Exploiting rice–sorghum synteny for targeted development of EST-SSRs to enrich the sorghum genetic linkage map

P. Ramu · B. Kassahun · S. Senthilvel · C. Ashok Kumar · B. Jayashree · R. T. Folkertsma · L. Ananda Reddy · M. S. Kuruvinashetti · B. I. G. Haussmann · C. T. Hash

Received: 6 March 2009 / Accepted: 20 July 2009 / Published online: 8 August 2009© Springer-Verlag 2009

Abstract The sequencing and detailed comparative func-tional analysis of genomes of a number of select botanicalmodels open new doors into comparative genomics amongthe angiosperms, with potential beneWts for improvement ofmany orphan crops that feed large populations. In thisstudy, a set of simple sequence repeat (SSR) markers wasdeveloped by mining the expressed sequence tag (EST)database of sorghum. Among the SSR-containingsequences, only those sharing considerable homology withrice genomic sequences across the lengths of the 12 ricechromosomes were selected. Thus, 600 SSR-containingsorghum EST sequences (50 homologous sequences on

each of the 12 rice chromosomes) were selected, with theintention of providing coverage for corresponding homolo-gous regions of the sorghum genome. Primer pairs weredesigned and polymorphism detection ability was assessedusing parental pairs of two existing sorghum mappingpopulations. About 28% of these new markers detected poly-morphism in this 4-entry panel. A subset of 55 polymorphicEST-derived SSR markers were mapped onto the existingskeleton map of a recombinant inbred population derivedfrom cross N13 £ E 36-1, which is segregating for Strigaresistance and the stay-green component of terminaldrought tolerance. These new EST-derived SSR markersmapped across all 10 sorghum linkage groups, mostly toregions expected based on prior knowledge of rice–sorghum synteny. The ESTs from which these markers werederived were then mapped in silico onto the alignedsorghum genome sequence, and 88% of the best hitscorresponded to linkage-based positions. This study

Communicated by T. Sasaki.

P. Ramu and B. Kassahun contributed equally to this work.

Electronic supplementary material The online version of this article (doi:10.1007/s00122-009-1120-4) contains supplementary material, which is available to authorized users.

P. Ramu · B. Kassahun · S. Senthilvel · C. Ashok Kumar · B. Jayashree · R. T. Folkertsma · C. T. Hash (&)M. S. Swaminathan Applied Genomics Laboratory, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), ICRISAT-Patancheru PO, Hyderabad, Andhra Pradesh 502 324, Indiae-mail: c.hash@cgiar.org

P. Ramu · L. A. ReddyDepartment of Genetics, Osmania University, Hyderabad, Andhra Pradesh 500 007, India

B. Kassahun · M. S. KuruvinashettiUniversity of Agricultural Sciences, Dharwad, Karnataka 580 005, India

B. KassahunCollege of Agriculture and Veterinary Medicine, Jimma University, P.O. Box 307, Jimma, Ethiopia

Present Address:C. Ashok KumarDepartment of Plant Pathology & Crop Physiology, Louisiana State University, Baton Rouge, LA 70803, USA

R. T. FolkertsmaDepartment of Phytopathology, De Ruiter Seeds, Leeuwenhoekweg 52, 2661 CZ, Bergschenhoek, The Netherlands

B. I. G. HaussmannInternational Crops Research Institute for the Semi-Arid Tropics (ICRISAT), BP 12404, Niamey, Niger

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demonstrates the utility of comparative genomic informa-tion in targeted development of markers to Wll gaps in link-age maps of related crop species for which suYcientgenomic tools are not available.

Introduction

Sorghum [Sorghum bicolor (L.) Moench, 2n = 20] is one ofthe most important cereal crops and well adapted to harshenvironments characterized by drought and high tempera-tures. In addition to being an important source of caloriesfor millions of poor people living in the semi-arid tropics ofAfrica and Asia, and an essential livestock feed there andelsewhere, sorghum has been identiWed as a potentialsource of bio-fuel (Antonopoulou et al. 2008). Sorghum isa model organism for tropical grasses having the ‘C4’ pho-tosynthetic pathway and is a logical complement to the ‘C3’grass Oryza sativa (Kresovich et al. 2005), which was theWrst monocot with a completely sequenced genome (GoVet al. 2002; Yu et al. 2002; International Rice GenomeSequencing Project 2005). Sorghum has a relatively smallgenome (»760 Mb; Arumuganathan and Earle 1991) that isless complex than those of other major C4 crops like maize(Zea mays L.) and sugarcane (Saccharum oYcinarum).Genome sequencing of sorghum was initiated at the end of2005 through the ‘Community sequencing program ofDepartment of Energy-Joint Genome Institute, USA’ andduring the course of this study the complete alignedgenome sequence (8£) information for this species wasmade available to public use (Paterson et al. 2009; http://www.jgi.doe.gov/sorghum). This has provided an opportu-nity to better understand genome organization in sorghum,its wild relatives including Johnson grass (Sorghum hale-pense), and even maize.

Sorghum is the Wrst species in the crop improvementmandate of the International Crops Research Institute forthe Semi-Arid Tropics (ICRISAT) for which a reasonableamount of genomic tools are available that can be exploitedfor applied crop improvement. Construction of molecularmarker-based linkage maps in sorghum started during the1990s with restriction fragment length polymorphism(RFLP) markers (Hulbert et al. 1990; Pereira et al. 1994;Chittenden et al. 1994; Ragab et al. 1994; Xu et al. 1994;Dufour et al. 1997; Tao et al. 1998a; Peng et al. 1999) fol-lowed by maps adding other marker systems like ampliWedfragment length polymorphism (AFLP), simple sequencerepeat (SSR), and recently diversity array technology(DArT) markers (Boivin et al. 1999; Kong et al. 2000;Bhattramakki et al. 2000; Klein et al. 2000; Subudhi andNguyen 2000; Haussmann et al. 2002a; Menz et al. 2002;Bowers et al. 2003; Mace et al. 2008). Several genomicregions associated with important agronomic traits including

a range of abiotic stress tolerances [primarily mid-seasonand terminal drought tolerance (Tuinstra et al. 1996, 1997;Crasta et al. 1999; Subudhi et al. 2000; Tao et al. 2000; Xuet al. 2000; Kebede et al. 2001; Haussmann et al. 2002b;Sanchez et al. 2002; Harris et al. 2007) and aluminumtolerance (Magalhaes et al. 2004)], host plant resistances tohemi-parasitic weeds [Striga spp. (Haussmann et al.2004)], insect pests [aphids (Agrama et al. 2002; Katsaret al. 2002; Nagaraj et al. 2005; Wu et al. 2007), midge(Tao et al. 2003), and shoot Xy (Folkertsma et al. 2003)],and diseases [of both foliage (Oh et al. 1996; Tao et al.1998b; Nagy et al. 2007) and panicles (Klein et al. 2001)],and a range of traits related to grain quality (Lijavetskyet al. 2000), crop phenology [height and maturity (Lin et al.1995; Pereira and Lee 1995; Klein et al. 2001; Feltus et al.2006a)], and yield components (Hart et al. 2002; Hickset al. 2002) have been mapped. Now high-density geneticmaps are available for sorghum (Klein et al. 2000; Bowerset al. 2003). However, these maps have some signiWcantgaps and many genomic regions are covered by only AFLPand RFLP markers. At the onset of this study there werecirca 300 publicly available primer pair sequences formapped sorghum SSR loci (Brown et al. 1996; Taraminoet al. 1997; Kong et al. 2000; Bhattramakki et al. 2000;Menz et al. 2002; Schloss et al. 2002).

SSR markers have clear advantages over RFLP andAFLP markers in terms of technical simplicity, throughputlevel and automation (Varshney et al. 2005). SSRs are thepreferred marker system for many breeding applications.Hence, enriching the existing sorghum linkage map withmore SSR markers is a valuable objective for the sorghumbreeding community globally. Conventional SSR markerdevelopment is a costly and time-consuming process.Thanks to the availability of genomic or expressedsequence tag (EST) sequences in public databases and therecent advent of bioinformatics tools, SSR marker develop-ment has become easier and more cost-eVective (e.g.,Jayashree et al. 2006). In the past, SSR markers have beensuccessfully developed by mining EST databases in severalcrops (reviewed in Varshney et al. 2005). EST-SSRs are ahighly valued marker system as they are developed fromtranscribed portions of the genome and often target func-tional diversity. They are also superior in terms of cross-species transferability, and thus are well suited for applica-tion in phylogenetic analysis and comparative genomemapping. The transfer rate of EST-SSR markers from sor-ghum to paspalum (Paspalum spp.) and to maize was 68and 61%, respectively (Wang et al. 2005).

The rice genome exhibits substantial collinearity withthe genomes of other grasses, such as sorghum, maize,wheat (Triticum aestivum L.), and barley (Hordeum vulg-are L.) (Ahn et al. 1993; Chen et al. 2002; Devos and Gale1997; Tarchini et al. 2000). A direct comparison of the

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genetic linkage maps of sorghum and rice has been per-formed by Ventelon et al. (2001) using the mapping infor-mation of a common set of RFLP probes. Klein et al.(2003) indicated that the overall architecture of sorghumchromosome 3 and rice chromosome 1 has remainedlargely intact with the exception of one major rearrange-ment. The sorghum genome has now been reasonablyaligned with that of rice through comparative genetic, cyto-genetic, and physical mapping approaches (Draye et al.2001; Bowers et al. 2005, Kim et al. 2005a, Paterson et al.2009). In this study, we attempted to develop a set of EST-SSR markers that are expected to provide coverage forgene-rich regions of the entire nuclear genome using com-parative genomic information from rice as the sorghumgenome sequence information was not available when thestudy was initiated.

Materials and methods

Data mining of sorghum ESTs

Sorghum EST sequences were downloaded in FASTA for-mat from the J. Craig Venter Institute [formerly, The Insti-tute for Genome Research (TIGR)] database (http://www.tigr.org) as of May 2004. The identiWcation of micro-satellites from these EST sequences was carried out usingSSRIT (www.gramene.org/db/searches/ssrtool), and simplescripts (written in Visual Basic) to parse SSRIT output intothe relational database. CAP3 (Huang and Madan 1999)was used to identify the non-redundant EST sequences.Non-redundant sorghum EST sequences containing SSRswere then obtained from this local database and used in thisstudy.

Selection of candidate ESTs and primer design

Non-redundant sorghum EST sequences containing micro-satellites were BLAST searched against the rice genomesequence available in the GRAMENE database (http://www.gramene.org/db/searches/blast) as of May 2004. Eachrice chromosome was divided into Wve arbitrary regionsviz., ‘top’, ‘middle, ‘bottom’, ‘between top and middle’,and ‘between middle and bottom’. The ten top-scoring sor-ghum EST sequences for each region of the rice chromo-some were picked. Thus, a total of 600 SSR-containingEST sequences of sorghum (10 each for each region of the12 rice chromosomes) having sequence homology with ricesequences were identiWed. These 600 candidate EST-SSRsequences were expected to sparsely cover the entirenuclear genome of rice, and thereby the corresponding sor-ghum genomic regions. Primer pairs were designed fromthe selected 600 non-redundant sorghum EST-SSR

sequences using Primer3 (http://biotools.umassmed.edu/bioapps/primer3_www.cgi) after masking the repeat units.The primer pairs were designed with the following condi-tions: primer length (min-18nt, opt-22nt, max-24nt), Tm(min-54°C, opt-57°C, max-60°C), and GC content (min-45,opt-50, max-60%).

Primer optimization and polymorphism assessment

PCR conditions for the EST-SSR primer pairs were opti-mized using template DNA of genetically diverse parentalpairs of two sorghum mapping populations available atICRISAT, Patancheru viz., N13 £ E 36-1 and BTx623 £IS 18551. N13 is Striga resistant while E 36-1 is stay-green, drought tolerant, and Striga susceptible. BTx623 isan elite hybrid parental line chosen for genome sequencing(Paterson et al. 2009). It is susceptible to shoot Xy andbeing used as the recurrent parent for ICRISAT’s explor-atory shoot Xy resistance marker-assisted backcrossing pro-gram. IS 18551 is a shoot Xy resistant donor parent beingused by ICRISAT for shoot Xy resistance QTL mappingand marker-assisted backcrossing. DNA of parental lineswas isolated using a high-throughput DNA extractionprotocol as reported by Mace et al. (2003) and normalizedto a working concentration of 5 ng/�l.

PCR was performed in 5 �l reaction volume with Wnalconcentrations of 2.5 ng DNA, 2 mM MgCl2, 0.1 mM ofdNTPs, 1£ PCR buVer, 0.4 pM of each primer, and 0.1 Uof Taq DNA polymerase (AmpliTaq Gold®, Applied Bio-systems, USA) in a GeneAmp® PCR System 9700 thermalcycler (Applied Biosystems, USA) with the followingcyclic conditions: initial denaturation at 94°C for 15 min(to activate Taq DNA polymerase) then 10 cycles of dena-turation at 94°C for 15 s, annealing at 61°C for 20 s (tem-perature reduced by 1°C for each cycle), and extension at72°C for 30 s. This was followed by 34 cycles of denatur-ation at 94°C for 10 s, annealing at 54°C for 20 s, andextension at 72°C for 30 s with the Wnal extension of20 min at 72°C. AmpliWed PCR products were resolved on6% native polyacrylamide gels coupled with silver stainingas described by Tegelstrom (1992).

Mapping of EST-SSRs

The polymorphic markers were subsequently mapped usingrecombinant inbred lines (RILs) of N13 £ E 36-1 (Hauss-mann et al. 2004). The markers polymorphic between N13and E 36-1 were surveyed on a subset of 94 F3-derived F5

RILs. The segregation data were used to place the newmarkers on to the existing skeleton map with 164 previ-ously mapped RFLP, AFLP, RAPD, and SSR markers(Haussmann et al. 2002a, 2004) at LOD score of 3.0 usingMapmaker 3.0v (Lander et al. 1987). The Haldane mapping

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1196 Theor Appl Genet (2009) 119:1193–1204

function (Haldane 1919) was used to convert recombina-tion frequency into linkage map distance. The linkagegroups were oriented and designated following Kim et al.(2005b).

In silico mapping of ESTs

Aligned sorghum genome sequence information (Sbi 1.4)for elite sorghum inbred BTx623 was made available forpublic use (http://www.jgi.doe.gov/sorghum) during thecourse of this study (Paterson et al. 2009). This aligned sor-ghum genome sequence information was downloaded andformatted into a database. All mapped SSR-containing ESTsequences (55 markers) were searched against this databaseusing Paracel BLAST (Altschul et al. 1990) on a ParacelHigh Performance Computing system. These sequenceswere then aligned on to the sequence-based physical mapaccording to their hit location on each linkage group.

Results

Data mining of sorghum ESTs

In the TIGR database, about 187,282 sorghum ESTsequences were available when this study was initiated. WeidentiWed 39,106 EST sequences with SSRs using theSSRIT tool. These sequences were clustered using theCAP3 program to identify 10,044 non-redundant ESTsequences containing microsatellites.

A set of 1,486 non-redundant sorghum EST sequencescontaining microsatellites were BLAST searched against therice genome in the GRAMENE database. From the sequencesimilarity search, 150 sorghum EST sequences had no hitson rice genome sequence; 180 sequences had homology withsequences on rice chromosome 1; 130 on chromosome 2,243 on chromosome 3, 98 on chromosome 4, 115 on chro-mosome 5, 77 on chromosome 6, 67 on chromosome 7, 66each on chromosomes 8 and 9, 71 on chromosome 10, 144on chromosome 11, and 79 on chromosome 12. On eachchromosome, 50 sorghum SSR-containing EST sequenceswith highest BLAST search score that provided coverageacross the entire length of each rice chromosome were iden-tiWed. Thus, 1,486 non-redundant EST sequences wereBLAST searched against the rice genome to identify 600sequences (50 per rice chromosome). Primer pairs Xankingthe SSR motifs were designed using Primer3. These primerpairs were designated as ‘ICRISAT Sorghum EST Primers(ISEP)’ (listed as electronic supplementary information S1).Among the selected 600 SSR-containing sorghum ESTsequences, 470 (78%) sequences have putative annotations.The majority of these are classiWed as transcription factors orDNA binding proteins.

Out of the 600 sorghum EST-SSR markers developed,63 were di-nucleotide repeats (10.5%); 425 were tri-nucleo-tide repeats (70.8%); 78 were tetra-nucleotide repeats(13.0%); and 34 were penta-nucleotide repeats (5.6%). Themost abundant repeats among the selected EST sequenceswere AG and CCG. A total of 79 SSR motifs (13%) were ofClass I type of SSRs (¸20 nucleotides in length) and 496SSR motifs were Class II type of SSRs (>12 but <20 nucle-otides in length), and remaining 25 SSR motifs were 10nucleotides in length. Further details on SSR frequency anddistribution in the set of EST sequences used here havebeen published by Jayashree et al. (2006).

Primer optimization and polymorphism assessment

PCR conditions for the 600 primer pairs were optimizedusing template DNA from the four inbred parental lines ofthe two mapping populations, and parental polymorphismwas simultaneously scored. Out of 600 primer pairs, 457(76.1%) ampliWed the template and 386 (84.5%) producedsimple and easy to score ampliWcation products, whereasthe remaining 15.5% of template-amplifying primer pairsproduced multiple fragments that were diYcult to score.Most of the primer pairs that produced no ampliWcation orgave non-speciWc ampliWcation were targeting tri-nucleo-tide repeats. Of the 386 primer pairs that produced goodampliWcation proWles, 133 primer pairs (34.5%) detectedpolymorphism between N13 and E 36-1 and 140 primerpairs detected polymorphism between BTx623 andIS 18551 (listed as electronic supplementary informationS1). In both crosses, di-nucleotide repeats were found mostpolymorphic (30–38%), followed by tetra-nucleotiderepeats in the N13 £ E 36-1 cross, and penta-nucleotiderepeats in the BTx623 £ IS 18551 cross.

Mapping of EST-SSRs

The polymorphic markers were surveyed on 94 RILsderived from the cross N13 £ E 36-1 and the segregationdata were scored. A total of 55 EST-SSR markers wereadded (Table 1) to the existing skeleton map of this map-ping population. These markers mapped to all 10 sorghumlinkage groups and were well-distributed within each link-age group except in the case of SBI-06 for which the newlymapped markers clustered along the bottom of the linkagegroup in a region corresponding to the long arm of the sor-ghum chromosome. Among these 55 newly mapped EST-SSR markers, 9 mapped to SBI-09, 8 markers each mappedto SBI-02 and SBI-03, 7 mapped to SBI-01, 6 markers eachmapped on SBI-04 and SBI-07, 3 markers each mapped onSBI-05, SBI-06, and SBI-10, and 2 markers mapped onSBI-08, with an average of 5.5 EST-SSR markers per link-age group. The linkage map augmented with these 55

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Theor Appl Genet (2009) 119:1193–1204 1197

Tab

le1

Det

ails

of

55 g

enet

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ly m

appe

d so

rghu

m E

ST-S

SR

mar

kers

and

thei

r co

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pond

ing

phys

ical

map

loca

tions

on

the

alig

ned

sorg

hum

gen

ome

sequ

ence

Mar

ker

Sor

ghum

ES

T

sequ

ence

ID

Rep

eat

mot

ifF

orw

ard

prim

er s

eque

nce

(5�–

3�)

Rev

erse

pri

mer

seq

uenc

e (5

�–3�

)A

ppro

x.

ampl

icon

si

ze in

B

Tx6

23 (

bp)

Ali

gnm

ent p

osit

ion

on r

ice

geno

me

sequ

ence

BL

AST

sc

ore

Lin

kage

gr

oup

Phy

sica

l m

ap

posi

tion

Xis

ep01

01A

W67

9887

TG

(9)

CA

GA

TC

TC

CG

GT

TG

AA

GA

GC

TG

AG

CC

GA

GC

TC

AA

CA

TA

CA

205

chr1

: 193

1190

-128

4781

013

50S

BI-

03S

BI-

03

Xis

ep01

02A

W56

5338

AA

G(4

)C

GC

TG

GA

GT

AC

CA

GA

GG

AA

GA

AC

AA

AA

TC

CG

AG

CC

TG

TT

G68

0ch

r1: 4

1937

5-22

7804

7896

8S

BI-

03S

BI-

03

Xis

ep01

07A

W74

4864

TG

G(4

)G

CC

GT

AA

CA

GA

GA

AG

GA

TG

GT

TT

CC

GC

TA

CC

TC

AA

AA

AC

C20

5ch

r1: 4

9463

97-4

9468

6271

1S

BI-

03S

BI-

03

Xis

ep01

10B

E36

0507

CG

(6)

GA

GG

GG

AA

GC

TG

GA

GA

CC

TC

AA

GT

GT

AC

AA

CG

CA

TC

CA

G48

0ch

r1:

8105

89-3

1327

180

1821

SBI-

09SB

I-03

Xis

ep01

38A

W92

3239

TA

(6)

GA

GA

TC

GA

GA

GG

CA

CT

TT

GG

CA

GC

GA

CA

AG

CC

AA

TA

CC

A21

0ch

r1: 4

0999

721-

4128

3498

1349

SB

I-03

SB

I-03

Xis

ep02

02A

W67

9616

TG

A(7

)C

AA

CC

TG

TG

AT

TG

AC

CC

AT

TT

AA

AC

AT

GT

CC

AG

AT

TC

AT

CA

AG

G19

5ch

r2: 3

9576

94-3

9583

7612

35S

BI-

04S

BI-

04

Xis

ep02

24A

W56

3693

CT

G(4

)A

CT

GG

GG

TT

CC

TT

TT

CC

TG

TT

CC

CT

GA

TT

TC

CC

CT

CT

TT

T20

0ch

r2: 1

3206

311-

2603

7486

824

SB

I-04

SB

I-04

Xis

ep02

28B

E35

6910

GA

GG

(3)

GA

CA

TG

GC

CA

GC

TA

AG

AG

GA

CC

AT

GC

AG

TG

AT

CG

TT

GT

GT

220

chr2

: 763

5368

-305

6099

474

6S

BI-

04S

BI-

04

Xis

ep03

10A

W28

6133

CC

AA

T(4

)T

GC

CT

TG

TG

CC

TT

GT

TT

AT

CT

GG

AT

CG

AT

GC

CT

AT

CT

CG

TC

200

chr3

: 104

7959

7-10

4800

1771

1S

BI-

02S

BI-

02

Xis

ep03

14B

E35

8851

GC

C(4

)G

TT

CG

AC

GA

CG

AC

GA

CC

TG

TC

CT

CG

AA

CC

CG

AC

CT

T40

5ch

r3:

1696

130-

2881

2187

730

SBI-

10SB

I-01

Xis

ep03

27A

W68

0959

GT

T(4

)C

TG

TT

TG

TG

CT

TG

CA

AC

TC

CT

CA

TC

GA

TG

CA

GA

AC

TC

AC

C20

0/21

0ch

r3: 1

6826

707-

3071

4737

730

SB

I-01

SB

I-01

Xis

ep03

28B

E35

9052

AA

G(4

)C

AT

CT

TC

CT

CC

GT

CA

AC

CA

TA

TC

CT

GC

GA

CC

CT

TC

TC

AC

300

chr3

: 207

5686

8-33

4796

0114

19S

BI-

07S

BI-

07

Xis

ep04

22A

W28

5124

GC

AT

(3)

TG

CC

CG

TA

AT

TA

AG

CC

CA

TA

CC

CA

CT

GC

TC

CA

GG

TA

AG

AA

300

chr4

: 281

0717

-300

5033

541

0S

BI-

06S

BI-

06

Xis

ep04

39A

W74

5664

GA

C(4

)T

AG

TC

GA

AG

CA

GC

AG

TC

GT

GG

TG

TT

CA

AG

TT

CG

AC

GA

GC

A62

0ch

r4: 3

1792

724-

3183

2792

863

SB

I-07

SB

I-07

Xis

ep04

43B

E35

5584

GC

A(7

)T

CA

TG

TA

CA

GA

GG

CG

AC

AC

GA

GG

TC

GC

AA

CA

GA

CA

CC

TT

C19

0ch

r4: 2

9104

052-

2912

2456

734

SB

I-06

SB

I-06

Xis

ep04

49B

E35

7875

TC

A(7

)C

CG

CT

CA

TC

AG

TC

AT

CA

CA

TA

CA

AA

AT

CC

AT

CC

CA

CA

AC

G20

0ch

r4: 3

6595

7-34

7436

4618

08S

BI-

06S

BI-

06

Xis

ep05

06A

W92

2528

AA

CG

(3)

CG

TG

CA

AG

TT

TG

GA

AT

TT

GT

CC

GG

GC

AG

GT

AT

AA

GG

TG

TT

G22

5/43

0ch

r5: 2

0763

88-4

4028

6669

7S

BI-

09S

BI-

09

Xis

ep05

13A

W74

5388

GG

C(5

)G

AG

GG

AA

GA

AG

AA

AA

CC

CA

GA

AG

CC

TC

TC

CT

CC

TC

CT

CC

T30

0ch

r5: 8

0303

4-17

0974

8710

53S

BI-

09S

BI-

09

Xis

ep05

22B

E36

1646

CA

G(8

)T

CA

TG

GA

CC

GT

GT

CA

TC

GG

CG

TA

CT

TG

CT

CC

AC

CT

CT

C33

0ch

r5:

1594

3072

-221

6622

611

10SB

I-04

SBI-

02

Xis

ep05

23B

E35

8885

TG

C(4

)A

CG

AC

AT

GG

AC

GA

CA

TC

AG

AA

AC

AA

AA

AC

AC

AC

GG

GA

AG

G22

0/30

5ch

r5: 1

7631

682-

1763

2292

911

SB

I-09

SB

I-09

Xis

ep05

50A

W74

6901

GA

(11)

GC

GG

CG

AG

AG

AG

AG

AG

TT

CC

GA

GC

TT

GA

TC

TT

CT

CG

TT

GA

185

chr5

: 303

9650

-253

3801

867

0S

BI-

09S

BI-

09

Xis

ep06

07A

W92

3923

AG

A(4

)C

AC

GA

GG

AT

TT

CA

CC

AA

AC

CT

GC

AC

GT

GT

TC

GA

AA

TA

GG

A19

5ch

r6: 2

2385

20-2

2406

3154

3S

BI-

10S

BI-

10

Xis

ep06

08B

E35

5471

AG

A(4

)T

TT

CA

CC

AA

AC

CA

AG

CT

AA

GG

GT

AG

AG

GC

AG

CC

CT

TC

TC

CT

205

chr6

: 22

3852

0-22

4063

154

3SB

I-04

SBI-

10

Xis

ep06

32B

E35

5933

CA

TG

(4)

AG

AG

AG

GA

GG

TC

CC

AA

AT

GC

TT

AA

GG

CC

CA

AA

CA

AA

CT

GG

195

chr6

: 890

8340

-281

2850

372

9S

BI-

08S

BI-

08

Xis

ep06

39B

E35

7831

TC

T(6

)T

CG

GA

CG

GA

GT

CA

TC

AG

AT

AG

CC

TT

CG

TG

TC

TT

CT

GT

CC

T20

0ch

r6: 2

6216

943-

2646

0093

628

SB

I-10

SB

I-10

Xis

ep07

01B

E36

0023

TT

CT

T(3

)C

GG

TG

GG

AG

AG

AC

AG

AG

AG

AC

CA

AT

CA

AT

AC

CA

CT

CC

TG

TG

A20

0ch

r7: 4

0610

86-4

0614

4712

28S

BI-

02S

BI-

02

Xis

ep07

04A

W68

0310

GT

(5)

CA

AG

TC

CG

TC

GT

GC

TA

GA

GG

CC

CT

TT

AA

TT

AG

CC

CC

AA

AC

A20

0ch

r7: 5

2476

30-5

2479

4390

8S

BI-

07S

BI-

07

Xis

ep07

33B

E35

7808

TG

TA

A(5

)G

TG

AT

GC

AT

CT

CA

CG

GA

CA

GG

CA

GC

TA

CT

GC

AT

GC

TT

GT

C40

0ch

r7: 2

2294

109-

2698

5575

1443

SB

I-02

SB

I-02

Xis

ep07

47B

E35

7135

TC

C(5

)A

GG

CA

GC

CT

GC

TT

AT

CA

CA

AA

CA

AG

CT

CA

GG

TG

GG

TG

GT

210

chr7

: 372

151-

2672

6597

897

SB

I-02

SB

I-02

Xis

ep08

09A

W74

7322

TA

TG

(4)

GG

AA

AC

TC

TT

GT

GG

GT

TG

GA

TT

GA

CC

TC

TC

TA

CA

AA

TG

AT

CC

AC

200

chr8

: 102

2442

-102

2570

221

SB

I-08

SB

I-08

Xis

ep08

24A

W56

4458

CC

G(4

)T

CC

TG

AA

AG

AA

AC

GC

AC

AC

AG

AG

GA

GG

GT

GT

GG

AG

GT

GT

A20

0ch

r8: 1

3585

814-

1358

6034

428

SB

I-03

SB

I-03

Xis

ep08

29B

E12

5697

AG

(6)

CG

CT

GC

CA

AA

AT

CT

AA

GC

TC

CA

CG

GT

GG

TC

AC

AT

CA

GA

AG

205/

243

chr8

: 277

3824

4-27

7385

5412

25S

BI-

07S

BI-

07

Xis

ep08

31B

E36

0943

AA

AA

G(3

)T

CC

AT

GA

CC

TT

GA

GG

AG

GA

GT

TG

AA

GC

AG

GA

CA

AC

AC

AC

C20

0ch

r8: 2

4781

619-

2478

1723

943

SB

I-07

SB

I-07

Xis

ep08

39B

E35

7549

AT

TA

C(4

)T

AC

GC

AT

AG

CG

CC

TT

TC

AA

TA

TT

TC

AT

TA

TG

CC

GG

TC

TC

G20

0ch

r8: 2

7711

931-

2771

2047

378

SB

I-01

SB

I-01

Xis

ep08

41B

E35

8373

GC

A(1

0)T

AG

GA

AT

GA

CG

AC

AC

CA

CC

AC

AA

AG

GC

AA

GG

GT

TT

TG

CT

A21

0ch

r8: 2

4665

284-

2466

5519

299

SB

I-02

SB

I-02

123

1198 Theor Appl Genet (2009) 119:1193–1204

Tab

le1

cont

inue

d

Mar

kers

conX

ictin

g in

phy

sica

l and

link

age

map

pos

itio

ns a

re h

ighl

ight

ed in

bol

d

Mar

ker

Sor

ghum

EST

se

quen

ce I

DR

epea

t m

otif

For

war

d pr

imer

seq

uenc

e (5

�–3�

)R

ever

se p

rim

er s

eque

nce

(5�–

3�)

App

rox.

am

plic

on

size

in

BT

x623

(bp

)

Ali

gnm

ent p

osit

ion

on r

ice

geno

me

sequ

ence

BL

AS

T

scor

eL

inka

ge

grou

pPh

ysic

al

map

po

siti

on

Xis

ep08

43B

E35

7146

AG

CT

G(3

)C

CC

AA

AC

AT

TC

CC

AC

GT

AA

CG

TG

AA

CA

GA

GG

AG

GC

AG

AG

G20

0ch

r8: 2

9918

52-2

4982

703

993

SB

I-03

SBI-

03

Xis

ep08

44B

E35

6742

CG

T(4

)G

TG

TT

CA

AG

TT

CG

AC

GA

GC

AT

AG

TC

GA

AG

CA

GC

AG

TC

GT

G60

0ch

r8: 1

6414

13-2

5156

453

941

SB

I-07

SBI-

07

Xis

ep09

38A

W74

7241

TG

GG

T(6

)T

GC

TG

TT

CT

TG

AA

CG

TG

TT

TG

TT

TT

GC

AC

AA

AG

TT

GC

GT

GT

225

chr9

: 172

1048

6-17

2109

4477

9S

BI-

02SB

I-02

Xis

ep09

48B

E35

8472

TA

(5)

AG

GC

CG

AA

TC

AC

AA

TA

AT

GG

AG

TG

CA

TG

AA

CA

GG

GC

AT

C20

5ch

r9: 2

0568

536-

2056

8726

297

SB

I-04

SBI-

04

Xis

ep09

49A

W56

4537

GC

A(5

)C

AG

TG

CC

AA

TA

AG

CT

CG

TC

TC

CA

TC

GA

TC

TC

TG

CT

TC

TG

CT

T10

0ch

r9: 1

9365

772-

1936

5933

271

SB

I-01

SBI-

01

Xis

ep10

08A

W28

5562

CA

G(7

)G

AT

GC

GC

AA

GC

AG

AA

CA

AG

CA

GC

AA

TG

GA

AA

TA

GC

TC

AG

G34

0ch

r10:

249

1921

-130

6650

463

2SB

I-09

SBI-

01

Xis

ep10

13B

E36

0610

CG

G(7

)C

GG

TT

AC

GG

CG

GA

TT

AT

TA

CA

TG

GT

GG

CG

AT

GC

AG

AC

TA

220

chr1

0: 4

4143

94-1

6362

660

402

SB

I-02

SBI-

02

Xis

ep10

14A

W28

3055

GT

(5)

AC

CG

CC

GA

CG

TC

AT

AG

TA

AG

GG

CA

GT

AA

CA

TA

GC

AT

CC

AT

CA

240

chr1

0: 1

3864

191-

1386

4421

391

SB

I-09

SBI-

09

Xis

ep10

25A

W67

2031

GC

G(5

)A

CC

TT

CT

CG

TC

CT

CG

TC

CT

CA

GA

AC

AT

GA

CC

GG

AT

CG

AA

G49

0ch

r10:

852

6382

-218

1396

593

1SB

I-02

SBI-

01

Xis

ep10

28A

W74

7772

GC

A(4

)C

AG

CG

AC

CA

TG

AG

GA

TG

AC

TG

GC

AT

GC

AT

CA

AA

CA

AG

AT

200

chr1

0: 1

1501

109-

2094

1969

638

SB

I-01

SBI-

01

Xis

ep10

31B

E35

5884

CG

G(6

)T

GC

TC

CT

GC

CT

CG

TT

CT

CT

AG

TC

CT

CG

GT

CG

AC

TC

CA

T69

0ch

r10:

555

4237

-217

6595

432

6S

BI-

03SB

I-03

Xis

ep10

32B

E35

6267

TT

CA

G(3

)G

CA

AG

CT

CT

AC

GG

GA

TC

TT

CG

CA

GC

TG

GA

AA

AT

AA

TC

GA

AA

200

chr1

0: 1

4058

773-

2160

9683

1532

SB

I-01

SBI-

01

Xis

ep10

39A

W28

7556

CC

TG

(5)

GT

GG

AT

TC

AA

AT

CC

GC

TG

AC

GG

CA

AT

TT

GG

CA

AG

CA

AT

200

chr1

0: 1

3165

407-

1773

0031

492

SB

I-01

SBI-

01

Xis

ep10

47A

W28

5966

TG

CG

T(4

)T

CT

TT

GC

CC

TC

CC

GC

TA

TT

CC

AT

GA

AA

TG

AG

CA

AA

CG

A16

0ch

r10:

189

0192

3-18

9021

7423

5S

BI-

03SB

I-03

Xis

ep11

07B

E12

5211

GC

A(6

)G

GA

TA

AT

CT

GC

AG

GC

GA

CT

TC

CA

TC

TG

CT

GC

TC

TG

AC

TT

G21

0ch

r11:

534

1585

-536

2168

830

SB

I-05

SBI-

05

Xis

ep11

11A

W28

6876

CG

AG

(3)

CC

TC

CT

CT

CC

TC

AT

CC

CT

CT

AT

GG

GT

AG

CG

GG

TT

TC

TT

G22

0ch

r11:

139

2730

-139

3672

711

SB

I-05

SBI-

05

Xis

ep11

28A

W56

5976

AT

(6)

GG

CG

GG

AA

AA

AG

TT

CC

TT

TA

CG

CA

CA

CC

CA

TT

TC

AA

TT

C22

0ch

r11:

142

4987

4-23

8498

8179

3SB

I-09

SBI-

05

Xis

ep11

33A

W56

4774

CC

A(5

)C

GA

TG

CA

GC

TC

CA

AC

TC

AT

AG

TG

TA

TG

TC

GC

CG

AA

GT

GG

220

chr1

1: 2

9439

34-2

1608

323

350

SB

I-05

SBI-

05

Xis

ep12

13B

E35

8492

GA

A(5

)A

GG

TC

AG

CG

TC

TT

GC

AA

TC

TA

CA

AA

TT

GA

AA

GG

GC

GA

GA

G20

2ch

r12:

165

8936

-210

4613

931

5S

BI-

01SB

I-01

Xis

ep12

41B

E36

0849

AG

CT

G(5

)G

AG

GG

CG

AG

AC

AG

AG

GA

GA

TC

TA

CC

TT

TG

AG

CC

CA

CC

GT

A19

0ch

r12:

248

1225

2-24

8125

2328

8S

BI-

09SB

I-09

123

Theor Appl Genet (2009) 119:1193–1204 1199

newly mapped loci spanned 2,838 cM (Fig. 1). Markerssuch as Xisep0841, Xisep0733, and Xisep0938 on SBI-02,and Xisep0138, Xisep0824, and Xisep0843 on SBI-03,mapped to the vicinity of previously reported stay-greenQTLs (Haussmann et al. 2002b) whereas Xisep0747,Xisep0701, and Xisep1013 on SBI-02 mapped in the vicin-ity of previously reported Striga resistance QTLs (Hauss-mann et al. 2004).

In silico mapping of SSR containing ESTs

All genetically mapped SSR-containing ESTs were thenmapped physically by BLAST search against the alignedsorghum genome sequence. These markers were thenaligned on to the sorghum physical map (Fig. 1). Physicalmap positions were essentially as expected from the genetic

linkage analysis of these markers, except in case ofXisep0110, Xisep0314, Xisep0522, Xisep0608, Xisep1008,Xisep1025, and Xisep1128. Physical and linkage map posi-tions for all 55 mapped markers are listed in Table 1.

Discussion

The nature and frequency of SSRs in sorghum EST collec-tion has been comprehensively discussed in Jayashree et al.(2006). Generally, EST-derived SSR markers are found tobe less polymorphic than genomic SSRs. In this study, only28% of the EST-SSR markers developed were polymorphicamong the four sorghum genotypes initially screened. Asimilar percentage of polymorphism (25%) was reportedfor EST-SSRs in durum wheat (Eujayl et al. 2002), whereas

Fig. 1 Distribution of EST-SSR markers across sorghum linkage groups. Linkage group nomenclature follows Kim et al. (2005b). Newly addedmarkers are highlighted in bold font. Striga resistance QTL and stay-green QTL

Xisep1039Xisep1008

73.8 Mb

SBI-01

Xisep0327

Xisep0839Xisep0949

Xisep1028

Xisep1032

Xisep1213

10

20

30

40

50

60

70

Linkage map Physical map

Xisep1025

Xisep0314

Xisep08390.0Xisep094919.0Xtxp208_A40.8Xisep032750.2Xumc107_HindIII_A64.9E33_M50_F-561-P280.9E13_M61_F-188-P2109.6E11_M48_F-177-P2121.4E14_M60_F-151-P2122.9E14_M50_F-218-P2135.6Xisep1032140.8Xisep1213143.1Xisep1039149.0E12_M47_F-238-P1154.8E12_M47_F-274-P2159.3E11_M49_F-326_P1162.6E11_M60_F-132-P2164.6E11_M60_F-89-P2169.1E11_M48_F-156-P1177.6Xtxp43_A181.6Xtxp88_A183.0Xisep1028205.7Xtxp37_A235.1Xisp324_A245.9Xisp203_A274.7Xbnl05.0_HindIII_A287.8Xtxp61_A298.1Xtxp340_A319.2Xtxp248_A330.1

Xtxp96_B0.0Xtxp197_B16.2Xisep074722.2XSbAGH0429.5E14_M60_F-141-P136.8Xisep070147.0Xtxp50_B54.0Xisep1013102.0Xtxp201_B133.1E14_M61_F-385-P1142.7E33_M50-F-155-P1145.1Xisp366153.6XSbAGB03_B175.0Xumc136_HindIII_B192.7Xumc098_HindIII_B195.1E14_M61-F-115-P2205.2Xisp336212.4Xisep0938224.3Xtxp100_kaf_B239.8Xisep0841248.3Xisep0733251.5E14_M48-F-462-P1253.3Xtxp296_B258.6E11_M49-F-485-P1263.1Xisep1025268.7E14_M48-F-181-P2274.2Xtxp8_B279.4E14_M50-F-192-P2290.8Xisep0310299.6

77.9 Mb

SBI-02Xisep0747

Xisep0701

Xisep1013

Xisep0938

Xisep0733

Xisep0841Xisep0310

Xisep0522

Linkage map Physical map

74.4 Mb

SBI-03Xisep0110Xisep0107Xisep0101

Xisep1047Xisep1031

Xisep0102

Xisep0138Xisep0843

Xisep0824

Linkage map Physical map

Xisep01010.0

Xisp33152.6Xisep010780.1Xisp282_C105.8Xtxp228_C137.3E14-M48-F-209-P2162.8Xisep1047169.7E14_M48-F-173-P2177.3Xisep1031190.5E14_m48-F-88-P1193.1E14_M50-F-512-P1214.3Xtxp33_C236.9E11_M60-F-172-P1246.8Xisep0102252.7E14_M50-F-72-P1257.3Xumc063_EcoRI_C269.7Xisp307_C285.2Xtxp114_C311.4

E11-M60-F-459-P2362.2Xtxp38_I_C384.0Xisp361403.6Xbnl05.37_HindIII_C421.7Xisep0843438.3Xisep0824445.3E12_M47-F-174-P1454.9Xisp323_C466.7

Xisep0138499.0

Xisep09480.0Xisep02249.2Xisep020236.4E14_M61-F-49-P143.9E14_M60-F-438-P244.1E12_M47-F-199-P155.8Xisep022888.5E12_M47-F-226-P1106.2Xisep0522113.0Xisep0608119.7E14_M48-F-130-P2119.8Xtxp343_D123.3Xgap10_D136.6Xbnl05.71_EcoRV_D141.8E14_M61-F-365-P1144.4E14_M50-F-345-P1160.1Xtxp41_D175.9Xtxp327_D180.5Xisp229_D206.7Xtxp27_D239.2

SBI-04Xisep0224

Xisep0948Xisep0202Xisep0228

68 Mb

Linkage map Physical map

Xisp215_J0.0Xisep111130.6Xisp258_J39.2Xumc133_EcoRl_J52.4E13_M61-F-158-P254.0E14_M48-F-186-P276.6E11_M60-F-341-P283.2Xtxp303_J99.8E11_M49-F-67-P2130.1Xisep1107132.6E11_M49-F-270-P2137.4Xisep1133150.2E14_M50-F-382-P2155.7E11_M49-F-584-P2160.5E14_M61-F-142-P1163.8E14_M50-F-157-P1174.4E13_M61-F-71-P1190.4E14_M50-F-137-P1205.7Xtxp123_Kaf2_J217.1

62.3 Mb

SBI-05

Xisep1111

Xisep1107

Xisep1133

Xisep1128

Linkage map Physical map

123

1200 Theor Appl Genet (2009) 119:1193–1204

Thiel et al. (2003) reported 8–54% polymorphism on threediVerent mapping population parental line pairs in barley.Di-nucleotide repeats were more polymorphic (listed aselectronic supplementary information S1) than other repeatclasses, as reported by Thiel et al. (2003) in barley. In ourstudy, a total of 169 EST-SSR markers (28%) detectedpolymorphism between parental lines of two mapping pop-ulations. Among these, 104 EST-SSR markers were poly-morphic in both populations whereas 36 and 29 detectedpolymorphism speciWc to the shoot Xy and the Striga resis-tance mapping populations, respectively.

Sequence-based alignment studies accelerate the Wllingof gaps on linkage maps of related species and can be eVec-tively used for comparative genome mapping across spe-cies (Klein et al. 2003). When searching the homology of1,486 non-redundant sorghum SSR-containing ESTsequences against the rice genome, the highest alignmentscores were obtained for those aligning to the long arms ofrice linkage groups (listed as electronic supplementaryinformation S1). Rice chromosome 3 had the highest num-ber of hits followed by chromosomes 1 and 11. In the

sequence similarity search, 150 of these sorghum ESTsequences did not have any hit on the rice genome. Kleinet al. (2003) also found that 10% of the sorghum ESTsstudied have no homologs in the rice genome. Interestingly,this agrees well with the observation that 7% of the pre-dicted genes from the aligned 8£ shotgun sequence of sor-ghum inbred BTx623 have no apparent homologs inArabidposis, rice or poplar (Paterson et al. 2009).

After incorporating the new markers, the total map dis-tance for the 94-entry (N13 £ E 36-1)-based RIL popula-tion was 2,838 cM, which is similar to that reported by Taoet al. (2000) using 152 RILs and 306 markers. However,the present map is longer than sorghum linkage maps previ-ously reported by several authors (Haussmann et al. 2002a;Pereira et al. 1994; Chittenden et al. 1994). The variation inmap length of diVerent mapping populations is generallyattributed to diVerences in population size, the type of pop-ulation, and the genetic distance between the parents, whichstrongly aVect observed recombination rates, and thus,genetic distances (Menz et al. 2002). A comparison of thepresent map with that of Haussmann et al. (2002a), which

Fig. 1 continued

Xtxp6_I0.0E33_M50-F-354-P25.5E11_M48-F-212-P215.9E11_M48-F-381-P219.2E12_M47-F-101-P239.1E33_M50-F-279-P178.1E14_M60-F-149-P279.2E13_M61-F-257-P182.4E13_M61-F-185-P293.0Xumc044_EcoRl_I108.3Xtxp176_I118.3Xtxp57_I125.5Xisep0422133.2E13_M61-F-367-P1138.1Xisep0449142.1Xisp347_I149.8Xisep0443163.4Xisp225_I180.9

62.2 Mb

SBI-06

Xisep0443

Xisep0422Xisep0449

Linkage map Physical map

Xtxp40_E0.0

Xisp362_E36.7Xumc085_Hindlll_E62.8E11_M60-F-202-P174.1Xtxp312_E88.4Xisep0328122.0E13_M61-F-86-P2153.3E12_M47-F-186-P1162.9E14_M60-F-234-P2163.7E14_M61-F-120-P2172.6

XSbAGF06_E224.6

Xisep0829263.8Xisp344_E278.8Xisep0439289.3Xisep0844296.8Xisu074_Hindlll_E311.5Xisep0831326.3Xisep0704345.6

64.3 Mb

SBI-07

Xisep0328

Xisep0829Xisep0831Xisep0844Xisep0439Xisep0704

Linkage map Physical map

Xisep06320.0Xtxp273_H20.3Xtxp47_H41.5Xcsu030_Hindlll_H79.7E11_M60-F-134-P199.7E11_M60-F-139-P2113.4E14_M60-F-162-P2114.6E11_M60-F-198-P2116.5E14_M48-F-400-P1116.8E11_M49-F-212-P2121.6Xisp198138.3Xisp279163.9E14_M50-F-244-P2178.6E11_M48-F-301-P2194.1Xtxp18_H196.2Xtxp105_H214.4E14_M60-F-250-P1233.9Xisep0809241.0

55.5 Mb

Xisep0632

Xisep0809

SBI-08

Linkage map Physical map

59.6 Mb

Xisep1014Xisep0506

Xisep0513Xisep0550Xisep1214

Xisep0523

Linkage map Physical map

Xisep01100.0E14_M16-F-219-P217.9Xtxp289_F27.6E14_M61-F-182-P239.5E14_M48-F-59-P146.5Xisep101455.6Xisep055073.7Xisep050689.0Xisep051396.3E14_M48-F-110-P1102.8E14_M50-F-213-P2110.8E14_M47-F-257-P1114.7Xisep1008116.3Xisep1241125.3E11_M60-F-189-P2137.6Xisep0523146.2E12_M47-F-157-P1151.6Xbnl05.47_EcoRI_F169.5E14_M48-F-143-P1174.0E14_M48-F-123-P2181.3Xgap32_F215.4E13_M61-F-583-P1273.3Xisep1128290.8

SBI-09

Xisep06070.0E14_M61-F-89-P110.5Xisu136_EcoRV_G23.6Xumc113_EcoRl_G29.7E14_M60-F-116-P245.5Xisep031458.3Xisp359_G78.3Xtxp217_G97.7Xisp263_G116.6E14_M61-F-322-P2145.5E14_M61-F-320-P1149.1Xisep0639158.4Xtxp141_G185.9E14_M60-F-509-P1199.3

60.9 Mb

Xisep0639

Xisep0607

Xisep0608

SBI-10

Linkage map Physical map

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was based on a larger sample of progenies from the samemapping population, revealed that 94 out of 113 (83%)common markers had the same linear order in both maps.Some possible rearrangements were detected, which mostlyinvolved alternative orders for closely linked loci. Suchrearrangements are likely due to the use of a sub-sample of94 lines from this mapping population in the current study.The only major change observed in the order of markerswas in the upper part of linkage group SBI-04, inverting theorder of two markers separated by 9 cM. These EST-SSRmarkers, however, Wlled gaps or marker-rare regions in theexisting linkage map of sorghum targeted based on rice–sorghum sequence similarity.

The newly developed EST-SSR markers have shownpractical signiWcance by virtue of their positions. For exam-ple, Xisep0138, Xisep0843, and Xisep0824, which weremapped to SBI-03, are located in the vicinity of a stay-green QTL reported by Haussmann et al. (2002b) (Fig. 1).Three of the markers mapped to SBI-05 (Xisep1111,Xisep1107, and Xisep1133) are located in close proximityto Striga resistance QTLs (Haussmann et al. 2004). Thesemarkers are currently being used by ICRISAT and ournational program partners in the introgression of stay-greenand Striga resistance QTLs into a wide range of farmer-pre-ferred sorghum genotypes through marker-assisted back-crossing. Two markers [Xisep0107 (SBI-03) and Xisep0310(SBI-02)] were selected based on their linkage map posi-tions and used by the Generation Challenge Programme(GCP) in large-scale SSR-based diversity analysis of over3,000 sorghum accessions in a global composite germplasmcollection. Across this very broad range of wild and culti-vated sorghums, a total of nine alleles were noted forXisep0310 and six alleles for Xisep0107 (data not shown).Such small allele numbers with EST-SSRs in such a largeand diverse set of germplasm, as compared to genomicSSRs agrees with expectations that EST-SSRs are lesspolymorphic than genomic SSRs, as the former are derivedfrom conserved and expressed regions of the genome.Although this makes EST-SSRs less useful than genomicSSRs for Wngerprinting purposes, this lower level of vari-ability is helpful in diversity analysis, in which relation-ships between accessions are much more diYcult to assesswhen there are large numbers of rare alleles. Hence, theseEST-SSRs have potential for use in assessing functionaldiversity among diVerent genotypes, as well as use as Xank-ing markers for foreground selection in marker-assistedbreeding programs.

In silico mapping of the ESTs (from which these newSSRs were developed) on the aligned sorghum genomesequence (Paterson et al. 2009) gave very similar positionsas the conventional linkage analysis, both in terms of chro-mosome arm location and order. The order of these EST-SSRs from the in silico mapping agrees with the linkage

map for all ten sorghum linkage groups provided that thelatter are oriented with the short chromosome arm at thetop, as per the suggestion of Kim et al. (2005a). Only seven(12.7%) out of 55 mapped EST-SSR markers added to theN13 £ E 36-1-based skeleton map were mapped in silico tosorghum chromosomes other than those expected. Some ofthese diVerences are likely because the ESTs have beendrawn of multi-gene families with members distributed onmore than one chromosome as a result of ancestral genomeduplication events or transposition. For example,Xisep1025 mapped in silico to SBI-01 where as it ismapped to SBI-02 based on linkage analysis. However, thesorghum EST sequence (which had a best hit on rice chro-mosome 1) from which the primer pair for Xisep1025 wasderived also has a low e-value hit on SBI-02. This may bedue to presence of duplicate loci on SBI-01 and SBI-02.Recently, 5,012 genomic SSRs were mapped in silico on tothe aligned sorghum genome sequence assembly (Yone-maru et al. 2009).

The sorghum genome sequencing project has revealedthat predicted gene density in sorghum is much higher atthe ends of each chromosome and that heterochromaticregions near the centromere are essentially devoid of pre-dicted genes (Paterson et al. 2009). In silico positions forall mapped EST-SSRs are located at the ends of sorghumchromosome arms, away from the centromeric regions, inagreement with the predicted genomic distribution of sor-ghum genes. The in silico-predicted physical map positionsof candidate markers (including EST-SSRs that have notyet been mapped) can help to choose markers to Wll gapsand better saturate linkage maps. Thus the availability ofgenome sequences and other marker information can helpin selecting or developing markers for targeted mapping notonly in a given crop but also in related crops for whichsuYcient genomic tools are not yet available in the publicdomain.

On-going and future sequencing projects will contributemany more genomic and genic sequences to publicly avail-able databases, facilitating development of diVerent typesof markers at lower cost. As economically importantgrasses have more conserved regions across taxa thanfound in other crop lineages, EST-SSRs should become anextremely powerful tool for better understanding of rela-tionships between the grass species and for genetic map-ping. Our initial attempt to develop EST-SSRs based onsorghum–rice synteny was successful in Wlling importantgaps in the existing sorghum linkage map. We propose toinvestigate further the large number of SSR-containing sor-ghum EST sequences to develop a dense linkage map basedon these functional markers. The newly developed markersin hand, which are tightly linked to genomic regions con-trolling Striga resistance and the stay-green componentof terminal drought tolerance, can be used in functional

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analysis of these traits. These markers are being used byICRISAT, along with the newly reported CISP markers(Feltus et al. 2006b), for mapping of sorghum resistance toshoot Xy, stem borers, and grain mold. Through this study,we have demonstrated the value of a comparative sequencesimilarity approach for targeted development of PCR-com-patible molecular markers for practical applications in cropgenetics and breeding. It has previously been reported thatmore than half (57%) of EST-SSR markers developed fromsorghum ESTs show cross-species transferability (Wanget al. 2005), hence these markers can also be successfullyused in other related grass species for which insuYcientnumbers of PCR-compatible markers are available. Primerpairs for non-redundant sorghum EST-SSRs are availablefrom our database (http://intranet.icrisat.org/gt1/ssr/ssrdat-abase.html).

Acknowledgments The research fellowship provided to PR by theCouncil of ScientiWc and Industrial Research (CSIR), New Delhi, Indiais greatly acknowledged. KB acknowledges the Wnancial support pro-vided by the Ethiopian Government and ICRISAT. Work reported herewas partially funded by the CGIAR Generation Challenge Program(GCP).

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