A preliminary genetic analysis of fibre traits and the use of new genomic SSRs for genetic diversity...

A preliminary genetic analysis of fibre traits and the useof new genomic SSRs for genetic diversity in jute

Reyazul R. Mir Æ Sachin Rustgi Æ Shailendra Sharma Æ Ravinder Singh ÆAakash Goyal Æ Jitendra Kumar Æ Anupama Gaur Æ Akhilesh K. Tyagi ÆHaseena Khan Æ Mohit K. Sinha Æ Harindra S. Balyan Æ Pushpendra Kumar Gupta

Received: 3 April 2006 / Accepted: 8 October 2007 / Published online: 30 October 2007

� Springer Science+Business Media B.V. 2007

Abstract Jute is one of the most important fibre

crops, which is second only to cotton in providing

environment-friendly (biodegradable and renewable)

ligno-cellulose fibre. In order to improve this largely

neglected crop, we conducted a preliminary study

involving the following: (i) analysis of nature and

extent of the genetic variability for fibre yield and

four other related traits in a set of 81 genotypes

belonging to two commercially cultivated Corchorus

species (45 genotypes of C. olitorius + 36 genotypes

of C. capsularis), (ii) development and analysis of a

set of simple sequence repeat (SSR) markers from

C. olitorius, and (iii) use of a sub-set of SSRs for

assessment of genetic diversity in the above set of 81

genotypes. The results suggested quantitative nature

of fibre yield and other related traits, with a

preponderance of dominance component in genetic

variance. A sub-set of 45 SSRs derived from

C. olitorius, when used for a study of DNA poly-

morphism and genetic diversity, showed high

transferability of these C. olitorius SSRs to C. caps-

ularis. The average number of alleles for individual

SSRs was surprisingly low (3.04 for both species,

2.02 for C. capsularis and 2.51 for C. olitorius), and

so was the average polymorphic information content

(PIC; 0.23 and 0.24 in two species). In the dendro-

gram obtained using a similarity matrix, the 81

genotypes were grouped into three clusters, which

largely corresponded to the two species, Cluster I

belonging mainly to C. capsularis and the other two

closely related clusters (clusters II and III) belonging

to C. olitorius. It was also shown that a minimum of

15 SSRs could give the same information as 41 SSRs,

thus making many SSRs redundant. The SSR markers

developed during the present study and to be

developed in future will prove useful not only for

evaluation of genetic diversity, but also for molecular

mapping/QTL analysis, and for comparative genome

analysis of the two Corchorus species.

Keywords Jute � Corchorus � Genetic analysis �Simple sequence repeats � Genetic diversity

Electronic supplementary material The online version ofthis article (doi:10.1007/s10681-007-9597-x) contains supple-mentary material, which is available to authorized users.

R. R. Mir � S. Rustgi � S. Sharma � R. Singh �A. Goyal � J. Kumar � H. S. Balyan � P. K. Gupta (&)

Molecular Biology Laboratory, Department of Genetics

and Plant Breeding, Ch. Charan Singh University, Meerut

250 004, Uttar Pradesh, India

e-mail: [email protected]

A. Gaur � A. K. Tyagi

Department of Plant Molecular Biology, University of

Delhi South Campus, New Delhi 110 021, India

H. Khan

Department of Biochemistry and Molecular Biology,

University of Dhaka, Dhaka 1000, Bangladesh

M. K. Sinha

Division of Crop Improvement, Central Research Institute

for Jute and Allied Fibres, Barrackpore 743 101, West

Bengal, India

123

Euphytica (2008) 161:413–427

DOI 10.1007/s10681-007-9597-x

http://dx.doi.org/10.1007/s10681-007-9597-x

Introduction

Jute is one of the most important fibre crops of the

Indian subcontinent, and stands second only to

cotton, in providing an environment-friendly, biode-

gradable and renewable ligno-cellulose fibre. The jute

fibre is used, as a raw material, for several products

like hessians, sacs, and carpet backings. The two

species of the genus Corchorus (family Tiliaceae),

which are cultivated as jute crop include C. capsu-

laris (the white jute) and C. olitorius (the tossa jute),

each with 2n = 14 (genome size, *1,250 Mb),

although 50–60 species are widely known and 170

names are described under the genus Corchorus in

Index Kewensis (Palve et al. 2003; Edmonds 1990).

In India, eight species of the genus Corchorus,

including the above two cultivated species, are

known to occur in diverse ecological conditions and

habitats.

In recent years, the productivity of jute in India

has only marginally increased from 19 9 102 Kg/ha

in 1993 to 21 9 102 Kg/ha in 2003–2004 (Sinha

et al. 2004a). This is largely due to lack of adequate

efforts towards breeding new superior varieties based

on sound knowledge of genetics. Consequently, only

12 improved varieties of white jute (C. capsularis)

and 10 improved varieties of tossa jute (C. olitorius)

have been developed in India so far (see Roy et al.

2006). There is a need, therefore, to develop new

varieties of jute with improved fibre yield and fibre

quality to meet the expanding demand of jute fibre.

This would require a knowledge of not only the

extent and nature of available genetic variability, but

also that of the genetic architecture of fibre yield and

quality traits. An accurate assessment of genetic

diversity within the available germplasm is also

necessary for exploitation of this germplasm in

breeding programme.

In the past, only few studies on genetics of fibre

yield traits have been conducted in jute, and only

classical methods of genetic analysis were used in

these studies (Singh 1973, 1975; Sinha et al. 1989;

Sengupta et al. 2005). The genetic diversity in jute

has also been studied in the past but mainly using

only morpho-physiological traits such as plant height,

harvest index, cambial activity and fibre strength

(Palit et al. 1996). However, such traits are limited in

number and are often influenced by the environment,

thus making them unsuitable for correct assessment

of the genetic diversity. This limitation can be largely

overcome by the use of molecular markers, which are

unlimited in number and are not influenced by the

environment. Therefore, in recent years, considerable

emphasis has been placed on the development and

use of molecular markers in all major crops (Liu

et al. 1996; Roder et al. 1998; McCouch et al. 1997;

Sharopova et al. 2002; Hirata et al. 2006; Odeny

et al. 2007). In some recent studies in jute also,

molecular markers like RAPDs, chloroplast-SSRs,

STMSs, ISSRs, and AFLPs have been used to assess

genetic diversity (Qi et al. 2003a, b; Hossain et al.

2002, 2003; Basu et al. 2004; Roy et al. 2006).

Among these DNA markers, simple sequence repeats

have become the markers of choice due to their

several desirable attributes including their abundance,

multiallelic and codominant nature, high level of

reproducibility, cross-species transferability, etc.

(Gupta et al. 1996; Gupta and Varshney 2000).

In view of the above, we have initiated a

programme for developing a large repertoire of SSR

and AFLP markers in jute for the purpose of

germplasm characterization, gene tagging, construc-

tion of molecular maps and QTL analysis. In this

communication, we first present the results of our

preliminary study on an analysis of the extent and

nature of genetic variability in jute germplasm, and

then present in a relatively greater detail the results of

our study involving development and use of SSRs for

assessment of genetic diversity in jute germplasm

comprising genotypes of both tossa jute (C. olitorius)

and white jute (C. capsularis).

Materials and methods

Plant material

Two sets of jute genotypes were used in the present

study. The first set belonging to tossa jute (C. olito-

rius) included 55 F1 hybrids (produced through

diallel mating) and 11 parental genotypes (JRO524,

KEN/DS/060, TAN/SM/040C, TAN/NY/018C,

TAN/X/112C, THA/YA/064C, KEN/SM/024, KEN/

DS/053C, NPL/YPY/026C, JRO3670 and JRO3352),

which were used for combining ability analysis. The

second set comprised 81 jute genotypes including 45

genotypes belonging to tossa jute (C. olitorius) and

36 genotypes belonging to white jute (C. capsularis)

414 Euphytica (2008) 161:413–427

123

(Table 1). This second set was used for genetic

diversity analysis.

Raising of material, recording of data and

statistical analyses

The two sets of material listed above were evaluated

each in an experiment based on randomized block

design with three replications at Central Research

Institute for Jute and Allied Fibres (CRIJAF),

Barrackpore, Kolkata, India. Phenotypic data were

recorded on 10 random plants of each genotype in

each of the three replications, involving the following

five traits: plant height (m), basal diameter (cm),

number of nodes per plant, fibre weight per plant (g)

and stick weight per plant (g). The data from the first

set of 66 genotypes (55 F1s + 11 parental genotypes)

were used for combining ability analysis following

method 2 and model 1 of Griffing (1956), and the

data on the second set of 81 genotypes were used for

calculation of range, mean, coefficient of variation

(CV) and correlations using online statistics software

(Wessa 2007).

DNA extraction

DNA of each of the 81 genotypes listed in Table 1

was extracted from leaves of 1-month-old plants

grown at the Research Farm of the Department of

Genetics and Plant Breeding, Ch. Charan Singh

University, Meerut following modified CTAB

method (Saghai-Maroof et al. 1984). The DNA was

purified by RNaseA treatment and phenol: chloro-

form: isoamyl alcohol precipitation following

Sambrook et al. (1989). The quality and concentra-

tion of DNA were checked on agarose gel, using

digested k Hind III DNA as marker.

Construction of genomic library and enrichment

of SSRs

The genomic DNA of tossa jute, C. olitorius cv. O-4,

was sheared using a sonication device (Soniprep 150,

MSE, UK) and DNA fragments ranging in size from

0.5 kb to 1.5 kb, were cloned in pUC18 following

standard protocol (Sambrook et al. 1989). As many as

*20,000 recombinant clones were probed with

sheared total genomic DNA of tossa jute labelled with

a-P32 dATP to eliminate clones carrying repetitive

DNA. The selected clones were further screened using

wheat ribosomal DNA probe pTA71 labelled with

a-P32 dATP, to eliminate clones with ribosomal DNA.

No effort was made to eliminate chloroplast SSRs.

The bacterial colonies selected above were hybrid-

ized with pools of following end-labelled (c-P32dATP)

synthetic oligonucleotides {(A)30, (G)30; (GA)15,

(CT)15, (AT)15; (CAA)10, (AAG)10, (CTT)10, (ACC)10,

(TAT)10, (CAG)10; (ATTA)10, (TTCT)10, (AATA)10,

(AAAT)10, (AAGA)10, (CATT)10, (TTTA)10; (TA-

AAT)6, (TTTTC)6, (TCCTT)6; (CCTCCG)5 and

(CAGCCT)5}. The colonies giving strong hybridization

signals were selected for sequencing of clones.

Plasmid isolation, sequencing, designing

of primers for SSRs

Plasmid DNA was isolated from each of the selected

colonies using QIAprep1 Spin Miniprep kit (QIA-

GEN GmbH; Hilden, Germany), and the cloned

inserts were sequenced on contract by MACROGEN,

Seoul, South Korea. Sequences were screened for

SSRs that were C12 nucleotides long, using a Macro

that was kindly provided by Dr. N. D. Young

(University of Minnesota, St. Paul, Minn), and

modified by us. Primers for SSRs were designed

using web based PRIMER3 software (http://www-

genome.wi.mit.edu/cgi-bin/primer/primer3_www.cgi)

and were synthesized on contract by Illumina, Inc., San

Diego, USA. Details of primer sequences are presented

in Table 2.

Polymerase chain reaction (PCR)

DNA amplification was carried out in 25 ll reaction

mixtures, each carrying 50 ng template DNA, 0.2 lM

SSR primers, 200 lM dNTPs, 1.5 mM MgCl2, 19

PCR buffer and 0.5 U Taq DNA polymerase (Life

Technologies, New York, USA) using the following

PCR profile in a DNA Mastercycler (Eppendorf,

Hamburg, Germany): initial denaturation at 95�C for

5 min followed by 35 cycles at 95�C for 1 min,

52–64�C for 1 min (according to primer’s annealing

temperature), 72�C for 1 min, with a ramp at the rate

Euphytica (2008) 161:413–427 415

123

http://www-genome.wi.mit.edu/cgi-bin/primer/primer3_www.cgi

http://www-genome.wi.mit.edu/cgi-bin/primer/primer3_www.cgi

Table 1 A list of genotypes of C. capsularis and C. olitorius used in the study of genetic variability/diversity

S. No. C. capsularisa Country/Origin S. No. C. olitoriusa Country/Origin

1 CIJ-003 (BRANCA) Brazil 37 OIJ-102 Tanzania

2 CIJ-004 (LISA) Brazil 38 OIJ-103 Tanzania

3 CIJ-005 (ROXA) Brazil 39 OIJ-104 Tanzania

4 CIJ-006 (SOLIMOS) Brazil 40 OIJ-105 Tanzania

5 CIJ-007 Thailand 41 OIJ-106 Tanzania










15 CIJ-056 Nepal 51 OIJ-138 Tanzania

16 CIJ-060 Nepal 52 OIJ-140 Tanzania

17 CIJ-064 Nepal 53 OIJ-153 Thailand







24 CIJ-081 (PARC/2448) Pakistan 60 OIJ-162 Thailand

25 CIJ-082 China 61 OIJ-167 Indonesia






31 JRC-321 India 67 OIJ-174 Indonesia

32 LISA (CIJ-005) Brazil 68 OIJ-175 Indonesia

33 SOLIMOS (CIJ-007) Brazil 69 OIJ-176 Indonesia

34 BZ-1-3 (CIJ-001) Brazil 70 OIJ-204 Nepal

35 CMU-010 (soft stem) Mutant 71 OIJ-206 Nepal

36 JRC-212 India 72 OIJ-207 Nepal

73 OIJ-208 Nepal

74 OIJ-209 Nepal

75 OIJ-210 Nepal

76 O-4 Bangla Desh

77 JRO-524 India

78 TANGANYKA-1 (OEX-002) Tanzania

79 NPL/YPY/026C (OIJ-245) Nepal

80 SALYOUT (OEX-001) Nepal

81 S-19 (JRO – 620 9 Sudan Green) India

a Popular names, wherever available, are given in parenthesis

416 Euphytica (2008) 161:413–427

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) 76

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) 45

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40

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(AA

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) 55

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45

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AT

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(TT

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) 55

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70

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Euphytica (2008) 161:413–427 419

123

of 0.5�C per second and a final extension at 72�C for

10 min. The amplification products were resolved on

10% polyacrylamide denaturing gels (PAGE) fol-

lowed by silver staining (Tegelstrom 1992). Hundred

base pair ladder was used as a marker (New England

BioLabs, Inc., Beverly, USA).

Polymorphic information content (PIC) and

genetic diversity

For each SSR locus, PIC was calculated using the

following formula: PIC = 1-P

(Pi)2, where Pi is

the proportion of genotypes carrying the ith allele

(Botstein et al. 1980). Dissimilarity Analysis and

Representation for WINdows (DARwin) version 5.0

was used for assessing genetic diversity leading to

the preparation of a dendrogram (Perrier et al. 2003).

For this purpose, null alleles were scored as zero (0)

and other microsatellite alleles (length variants) were

each scored in the form of a single band of expected

size, which was later converted into number of

repeat units as allele codes. Data files prepared thus

were used to compute pair-wise genetic distances,

and the dissimilarity matrix thus obtained was

subjected to cluster analysis using the unweighted

neighbour-joining (UNJ) method (Gascuel 1997),

followed by bootstrap analysis with 1,000

permutations.

In order to workout a minimum set of SSR

markers, which can potentially characterize 81 jute

genotypes, we successively excluded each marker

from the datasheet and looked for the patterns

detected by remaining markers. If the remaining

markers could still characterize 81 jute genotypes, the

excluded marker was considered redundant. This

process was repeated in an iterative manner till a

minimum set of SSRs became available.

Open reading frame (ORF) and their annotation

ORF finder available at NCBI website (http://

www.ncbi.nlm.nih.gov/gorf/gorf.html) was used for

detection of ORFs and prediction of functions of

corresponding sequences; BLASTX (score C100; E

value Be-50; http://blast.genome.jp) similarity sear-

ches against nr-aa database were used for this

purpose.

Results and discussion

Phenotypic variability and interrelationship

among fibre yield and related traits

The mean values for fibre yield and four other traits

in each of the two species of jute, C. olitorious and

C. capsularis, showed continuous distribution. How-

ever, a good fit to normal distribution was observed

only for plant height, number of nodes per plant and

fibre weight per plant in C. olitorius and for basal

stem diameter, number of nodes per plant and fibre

weight per plant in C. capsularis (data not shown).

For the remaining traits in the two species, the

distributions of means of genotypes were asymmet-

ric, suggesting abundance of particular specific

alleles at loci controlling these traits, possibly as a

result of specific selection efforts made in the past.

The above results, taken together, confirmed quanti-

tative nature and polygenic control of each of the five

traits in the two jute species, as also reported in the

past (Ali 1994).

The data on mean, range and coefficient of

variation (CV) for the five quantitative traits are

presented in Table 3. Higher mean and higher upper

range values (except for stick weight per plant) for all

the five traits in tossa jute (C. olitorious) indicated its

superiority over white jute (C. capsularis) and con-

firmed results of an earlier study (Ali et al. 2002).

The relative variability for the five traits also differed,

with highest variability (CV) for stick weight per

plant followed by fibre weight per plant in both the

species. The variability for the remaining three traits

was relatively low. Among these three traits, since

plant height is an important component of fibre yield,

it may be desirable to look for germplasm with

greater plant height, and use it for improvement of

plant height. It is also known that tossa jute

(C. olitorious) is relatively more tolerant to diseases

and pests with low resistance to floods and drought,

while the white jute (C. capsularis) has higher level

of resistance to floods and droughts associated with

susceptibility to diseases and pests (see Roy et al.

2006). Therefore interspecific genetic variability

needs to be exploited for developing genotypes with

desirable attributes of both the species. Successful

efforts to obtain interspecific hybrids between these

two apparently cross-incompatible species have been

made in the past, suggesting the feasibility of this

420 Euphytica (2008) 161:413–427

123

http://www.ncbi.nlm.nih.gov/gorf/gorf.html

http://www.ncbi.nlm.nih.gov/gorf/gorf.html

http://blast.genome.jp

approach (Islam and Rashid 1960; Swaminathan

et al. 1961; Islam 1964; Sinha et al. 2004b).

The above five quantitative traits also showed

varying levels of positive and significant associations

(Table 4). Of particular interest are the positive and

significant associations of fibre weight per plant with

plant height, basal stem diameter, number of nodes

per plant and stick weight per plant. Significant

positive associations of fibre yield with plant height

and basal diameter were also reported in the past,

suggesting an importance of these traits in breeding

for high fibre yield (Shaikh et al. 1980; Ali 1984,

1993, 1994).

Genetic analysis of fibre yield traits

Estimates of general and specific combining ability

variances (r2g, r2

s ) for fibre yield and other related

traits were significant for all the traits except for

the basal stem diameter. This indicates presence of

both additive and non-additive components of

genetic variance for fibre yield and other related

traits, although the ratio r2g=r

2s suggested a prepon-

derance of the dominance component (Table 5).

Thus, the results of the present study support an

earlier study (Sengupta et al. 2005), where prepon-

derance of non-additive genetic variance was

recorded for all the traits studied except basal

diameter, which exhibited predominant additive

variance. Another earlier study involving a triallel

cross also indicated significance of epistatic inter-

actions (additive 9 additive, additive 9 dominance,

dominance 9 dominance) in controlling genetic

variation for fibre yield (Sinha et al. 1989). In this

background, future studies on marker-trait associa-

tions would certainly help in developing suitable

strategy for fibre yield improvement. It is thus

obvious that the SSR markers developed during the

present study and the additional SSR and AFLP

markers being currently developed by us will be

helpful in future studies, which would involve

Table 3 A summary of

data on range, mean and

coefficient of variation

(CV) for fibre yield and four

other related traits based on

81 genotypes of two

Corchorus species

(C. olitorius and

C. capsularis)

Statistic Plant

height (m)

Basal stem

diameter (cm)

Number of

nodes per plant

Fibre weight

per plant (g)

Stick weight

per plant (g)

Range

C. olitorius 2.0–3.7 1.0–2.8 43–101 3.9–17.8 14.4–84.9

C. capsularis 1.51–3.49 1.0–2.0 46–82 2.3–14 7.8–91.5

Mean

C. olitorius 2.93 1.75 72.04 10.73 47.53

C. capsularis 2.61 1.63 64.30 8.28 26.49

CV (%)

C. olitorius 16.72 25.55 19.03 29.19 42.18

C. capsularis 17.55 12.26 15.13 31.95 49.59

Table 4 Simple

correlation coefficients

among fibre yield and

related traits in two

Corchorus species

The figures in upper rows

belong to C. olitorius and

those in the lower rows

belong to C. capsularis

*P \ 0.05; **P \ 0.01 and

***P \ 0.001

Trait Basal stem

diameter (cm)

Number of

nodes per

plant

Fibre weight

per plant (g)

Stick weight

per plant (g)

Plant height (m) 0.17 0.70*** 0.73*** 0.26

0.33* 0.39* 0.67*** 0.47***

Basal diameter of stem (cm) 0.10 0.51*** 0.84***

0.27 0.79*** 0.45**

Number of nodes per plant 0.58*** 0.35*

0.40** 0.18

Fibre weight per plant (g) 0.58***

0.52***

Euphytica (2008) 161:413–427 421

123

preparation and use of molecular maps for quanti-

tative trait loci (QTL) analysis.

SSRs in C. olitorius cv. O-4

The results of an analysis of SSRs in 194 selected

low-copy sequences are presented in Table 6 and

Fig. 1. The trinucleotide repeats were most abundant,

and among the different repeats, (T)n and (AAG)n

were the most frequent, a feature that is in agreement

with earlier studies (Gupta et al. 1996; Cardle et al.

2000; Gupta and Varshney 2000; Kumpatla and

Mukhopadhyay 2005). The abundance of (T)n could

be partly due to the presence of chloroplast DNA that

is often rich in (A)n and (T)n. The abundance of

trinucleotide repeats was not unexpected, because the

library was enriched for low copy sequences, which

are known to tolerate trinucleotide repeats in view of

the triplet nature of the genetic code (Cardle et al.

2000; Scott et al. 2000; Gupta et al. 2003), although

dinucleotide repeats are often most frequent in

random genome sequences (Akkaya et al. 1992; Bell

and Ecker 1994; Gupta et al. 1996; Cardle et al.

2000; Kumpatla and Mukhopadhyay 2005). More-

over, functions could be assigned to 68 (35.05%) of

the 194 low-copy clones (see ESM Fig. 1), suggest-

ing that a good proportion of the above sequences

actually belonged to the transcribed fraction (low

copy sequences) of the jute genome.

Polymorphism of SSRs

Each of the 45 SSR primers gave an amplification

product of expected size in both the species, albeit

only in 2,931 (80.41%) of the 3,645 possible

primer 9 genotype combinations. These represented

SSR length polymorphisms. Sequencing of amplified

products in five representative primer 9 genotype

combinations confirmed that length polymorphism

was due to variation in the number of repeat units in

an individual SSR. The remaining 714 (19.59%)

cases exhibited +/- polymorphism due to null alleles,

which were more frequent in C. capsularis than in

C. olitorius. These cases of null alleles may be

attributed either to sequence divergence in the primer

binding sites or to an absence of specific SSR loci in

C. capsularis. Similar high frequency of null alleles

was also reported in bread wheat (Stachel et al. 2000)

and barley (Hamza et al. 2004).

Table 5 A comparison of

the results of combining

ability analysis conducted

during the present study

with the results of an earlier

study

Ratios of general and

specific combining

ability variances

Fibre

weight per

plant (g)

Plant

height

(m)

Basal stem

diameter

(cm)

Number of

nodes per

plant

Stick

weight per

plant (g)

Reference

r2g=r

2s 0.378 0.194 0.088 0.226 0.266 Present

study

r2g=r

2s 0.367 0.190 -0.085 0.225 0.260 Sengupta

et al.

(2005)

Table 6 A summary of SSRs detected in gDNA clones

derived from C. olitorius cv. O-4

Description of clones/SSRs Value Density

(kb/SSR)

Total number of clones

sequenced

194 –


with SSRs

44 –


with single SSR

27 –


with two SSRs each

11 –


with three SSRs each

6 –

Total number of SSRs

identified

67 1.7

Simple SSR 60 (89.6%) 1.9

Mononucleotide 13 (21.6%) 8.7

Dinucleotide 9 (15.0%) 12.7

Trinucleotide 25 (41.7%) 4.5

Tetranucleotide 8 (13.3%) 14.2

Pentanucleotide 3 (5.0%) 37.8

Hexanucleotide 2 (3.3%) 56.7

Compound SSR 7 (10.4%) 16.2

422 Euphytica (2008) 161:413–427

123

Forty-one of the 45 SSRs (91.11%) detected

polymorphism either due to variation in length of

SSRs (27 SSRs) or due to the null alleles (14 SSRs)

(Fig. 2a, b). Five SSRs exhibited intraspecific poly-

morphism only in tossa jute (C. olitorius), 1 SSRs

exhibited intraspecific polymorphism only in white

jute (C. capsularis), and the remaining 35 exhibited

both intraspecific and interspecific polymorphisms.

Thus, the frequency of polymorphic SSRs for

C. capsularis (87.80%) was relatively lower than

that for the source species, C. olitorius (97.56%). In

the present study, the percentage (91.11%) of

polymorphic SSRs in jute was close to the polymor-

phic SSRs (100%) reported in a recent study on jute

(Roy et al. 2006). However, the percentage of

polymorphic SSRs recorded during the present study

was relatively higher than the percentage of poly-

morphic SSRs reported earlier for other dicotyledons

like Cicer arietinum (33%), other Cicer species

(79%) and Pisum sativum (72%) (Sethy et al. 2006;

Burstin et al. 2001; Huttel et al. 1999), but was

comparable to the percentage (90.45%) of polymor-

phic SSRs observed in bread wheat (Stachel et al.

2000).

Fig. 2 Representative PCR amplification patterns showing

length polymorphism of SSRs noticed in different jute

genotypes (a) Polymorphism (interspecific) due to length

variation for SSR marker (J-7) in seven genotypes of

C. capsularis (lanes: 1, CIJ-003; 2, CIJ-004; 3, CIJ-005; 4,

CIJ-006; 5, CIJ-007; 6, CIJ-008; 7, CIJ-009) and eight

genotypes of C. olitorius (lanes: 8, OIJ-102; 9, OIJ-103; 10,

OIJ-104; 11, OIJ-105; 12, OIJ-106; 13, OIJ-107; 14, OIJ-108;

15, OIJ-109). (b) Polymorphism (intraspecific) due to length

variation for SSR marker (J- 121) in 15 genotypes of

C. olitorius (lanes: 1, OIJ-101; 2, OIJ-102; 3, OIJ-103; 4,

OIJ-106; 5, OIJ-107; 6, OIJ-108; 7, OIJ-110; 8, OIJ-132; 9,

OIJ-134; 10, OIJ-109; 11, OIJ-133; 12, OIJ-135; 13, OIJ-137;

14, OIJ-140; 15, OIJ-153). The arrows indicate the expected

product size

Fig. 1 A histogram

depicting frequencies of

SSRs with different classes

of repeat motifs (mono- to

hexa-nucleotide) in 60

SSRs, derived from a

genomic library of

C. olitorius cv. O-4

Euphytica (2008) 161:413–427 423

123

Transferability of SSR primers

The SSR primers derived from C. olitorius in the

present study showed good transferability to C. caps-

ularis, since expected amplified products were

available in 1141 (70.43%) primer 9 genotype com-

binations in C. capsularis, as against 1,790 (88.40%)

primer 9 genotype combinations in C. olitorius. The

level of transferability may be further improved, if

ESTs are developed and, EST-SSRs are used, since

these SSRs will belong exclusively to the transcribed

region of the genome. In the present study, although

the genomic library was enriched for low copy

sequences, a small proportion of clones in this

enriched library would still belong to the non-

transcribed fraction of the genome. The level of

transferability reported in earlier studies falls within

the range of 5% in Zostera to 100% in Caryocar

(Rossetto 2001; Sharma et al. 2002; Decroocq et al.

2003; Martinez-Gomez et al. 2003; Bandopadhyay

et al. 2004). The transferable SSRs may be used in

studies on comparative genome analysis in jute.

Evaluation of genetic diversity

The average number of alleles per SSR locus

involving both the species was 3.04 (range 1–6); in

C. capsularis, it was 2.02 (range 1–4), which was

lower than a mean number of 2.51 alleles per locus

(range 1–4) in C. olitorius. But the average PIC for

individual SSRs did not differ: 0.23 (range 0.00–0.63)

in C. capsularis and 0.24 (range 0.00–0.61) in

C. olitorius. A relatively higher average number of

alleles in C. olitorius suggested higher level of

genetic diversity among C. olitorius genotypes than

in C. capsularis genotypes. This feature is also

reflected in the dendrogram (Fig. 3), where the

genotypes of C. olitorius are grouped in two related

clusters and those of C. capsularis are grouped in a

Fig. 3 A dendrogram showing clustering pattern of 81 jute genotypes based on genetic distances estimated from SSR polymorphism.

Bootstrap values ([40) are indicated at different nodes

424 Euphytica (2008) 161:413–427

123

single distant cluster. The results of the present study

are in agreement with the results of recent studies in

jute conducted using chloroplast-SSRs and a few

genomic-SSR, ISSR and RAPD markers; in these

studies also, higher level of allelic diversity was

noted in C. olitorius than in C. capsularis (Basu

et al. 2004; Roy et al. 2006). This could be attributed

to higher level of natural outcrossing in C. olitorius

(up to 15%) relative to that of C. capsularis (only up

to 3%).

However, the intraspecific genetic distances (GDs)

among the genotypes of white jute (C. capsularis;

range = 0.04–0.55, mean = 0.23) or among those of

tossa jute (C. olitorius; range = 0.04–0.49, mean =

0.24) were only half that of the interspecific GD

values (range = 0.04–0.82, mean = 0.55). This

again suggested the need for exploitation of inter-

specific genetic diversity for jute improvement.

The clustering pattern of genotypes belonging to

C. olitorius and C. capsularis obtained during the

present study did not differ from those obtained

earlier using other marker systems like chloroplast-

SSR, genomic-SSR, ISSR, AFLP and RAPD (Hoss-

ain et al. 2002; Basu et al. 2004; Roy et al. 2006).

Clustering of two C. olitorius genotypes (OIJ-102

and OIJ-103) with 46 genotypes of C. capsularis in

the present study was, however, unusual and may be

attributed to the horizontal transfer of alleles or to the

admixture between two species. One of these two

genotypes carried C. capsularis alleles at eight SSR

loci and the other carried C. capsularis alleles at 13

SSR loci. These observations also suggested a

possibility of natural crossing between their ancestral

species during the course of their evolution.

The results of the present study were also exam-

ined with a view to select diverse genotypes to be

used as parents of crosses that are designed for

breeding improved jute cultivars and for producing

mapping populations for QTL analysis. It can be

noticed that within C. capsularis, genotype CIJ-003

(BRANCA) from Brazil (in sub-cluster Ia) and

genotype JRC-212 from India (in the same sub-

cluster) were most divergent. Similarly within C.

olitorius, genotype OIJ-107 from Tanzania (in sub-

cluster IIa) and genotype OIJ-207 from Nepal (in sub-

cluster IIIb) were most divergent. These two pairs of

divergent genotypes in each of the two species may

be involved in intraspecific crosses for getting

improved cultivars of white and tossa jute. At the

interspecific level, however, the most diverse pair of

genotypes involved genotype BZ-1-3 (CIJ-001) from

Brazil (in sub-cluster Ia) belonging to C. capsularis

and the genotype S-19 (JRO-620 9 Sudan Green)

from India (in sub-cluster IIa), belonging to C. oli-

torius. Interspecific crosses between these two

diverse genotypes may help combining desirable

attributes from the two species, since interspecific

hybridization has been successfully attempted and

utilized in the past (Islam and Rashid 1960; Swami-

nathan et al. 1961; Islam 1964; Sinha et al. 2004b).

Minimum number of SSRs required for

assessment of the diversity of 81 genotypes

While analyzing the patterns of 41 polymorphic SSRs

in all the 81genotypes, we noticed that all the above

genotypes could be discriminated from each other on

the basis of these 41 SSRs. It was also noticed that the

above 81 genotypes could also be discriminated by

using as few as 15 SSRs. Furthermore, taking the

number of alleles for each SSR marker into consid-

eration, these 15 markers could theoretically give as

many as 74,64,96,000 patterns. Therefore, the num-

ber of SSRs markers used in the present study was not

only adequate, but was rather redundant, since the

same information could be derived with a much

smaller number of markers. However, relatively

fewer alleles at each SSR locus could be specific to

this crop and may prove to be a disadvantage. In an

earlier study in bread wheat conducted by us, we

noticed that 12 of the 20 markers were adequate to

discriminate a maximum of 48 of the 55 genotypes

examined, but the number of alleles per locus ranged

from 1 to 13 (Prasad et al. 2000).

Conclusion

The present study reports the results of analysis of

genetic variability for fibre yield and four other traits

in a set of 81 jute genotypes. This is also the first

effort to develop genomic-SSRs in jute. The utility of

these SSRs for selecting diverse genotypes for future

hybridization programmes has been suggested in this

study. These SSRs along with additional SSR

(including EST-SSR) and AFLP markers that are

likely to be developed in future will be utilized for

Euphytica (2008) 161:413–427 425

123

construction of a framework linkage map, which

would be utilized for QTL interval mapping to detect

marker-trait associations. This information will then

be useful for developing strategies for marker-aided

selection (MAS) involving fibre yield and some

difficult quality traits like reduced lignin content and

fibre fineness/strength, leading to improvement in

jute productivity and quality.

Acknowledgements Financial support from the International

Centre for Genetic Engineering and Biotechnology (ICGEB) to

carry out this study and the award of JRF/SRF/RA to RRM,

SR, SS, RS, AG, and JK by CSIR, DBT, and DAE-BRNS are

gratefully acknowledged. Support of DBT to AKT, and the

award of a position of INSA-Senior Scientist by INSA to PKG

are also acknowledged. Funds provided under FIST

Programme by DST for equipments used to carry out this

study are also acknowledged.

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