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Molecular Plant Breeding 2012, Vol.3, No.2, 11
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Figure 6 The map showing 13 countries from where 292 jute
genotypes were collected
3.3 SSR primers
A set of 172 SSR markers were identified by 167
primer pairs. These jute SSRs and their primers
[except 19 HK-primer pairs (Akter et al., 2008)] used
during the present study belonged to a large repertoire
of jute SSRs earlier developed in our laboratory [Mir
et al., 2008b; Mir et al., 2009; Das et al., 2011 (J
Genetics, accepted)]. The details of these SSRs are
given in Supplementary Table 1.
3.4 Genotyping using SSRs
DNA amplification was carried out in 25 µL reaction
mixtures, each carrying 50 ng template DNA, 0.2 µmol/L
SSR primers, 200 µmol/L dNTPs, 1.5 mmol/L MgCl
2
,
1×PCR buffer and 0.5 U
Taq
DNA polymerase (Life
Technologies, New York, USA). Following PCR
profile was used in a DNA Mastercycler (Eppendorf,
Hamburg, Germany): initial denaturation at 95
℃
for
5 min followed by 35 cycles at 95
℃
for 1 min, 52
to 64
℃
for 1 min (according to primer’s annealing
temperature), 72
℃
for 1 min, with a ramp at the rate
of 0.5
℃
per second and a final extension at 72
℃
for
10 min. PCR amplified products were resolved on
10% polyacrylamide denaturing gels (PAGE) in
MEGA-GEL High Throughput Vertical Unit of C.B.S.
Scientific Co. (Wang et al., 2003); amplified fragments
(bands) were visualized by silver staining (Tegelstrom,
1992). A hundred base pair ladder was used as a
marker (New England BioLabs, Inc., Beverly, USA).
The amplified fragments (bands) due to an individual
SSR were scored as SSR alleles in different jute
genotypes.
3.5 Diversity analyses and population differentiation
Genotypic data for a set of 172 SSR loci was used for
the study of genetic diversity and population
differentiation in the whole set of 292 genotypes. For
this purpose, genotypic data of only polymorphic
SSRs were used for each of the two species. Statistics
involving genetic variation for each SSR locus
including total number of alleles (
N
a
), number of
effective alleles (
N
e
) and Shannon’s Information
index (
I
) were calculated using POPGENE version
1.31 (Yeh et al., 1997). Gene diversity (often referred
as expected heterozygosity,
H
e
) and polymorphic
information content (PIC) for each SSR locus were
calculated using the genetic analysis package Power-
Marker version 3.0 (Liu and Muse, 2005).
Dissimilarity matrix was computed using the genotypic
(allelic) data with the help of DARwin version 5.0
(DARwin: Dissimilarity Analysis and Representation
for WINdows; Perrier et al., 2003). The dissimilarity
matrix was then subjected to cluster analysis using the
un-weighted neighbour-joining (UNJ) method (Gascuel,
1997) followed by bootstrap analysis with 1 000
permutations leading to the preparation of dendrograms.
Principal coordinate analysis (PCA) was conducted by
calculating pair-wise genetic distances using genotypic
data (multiple loci and multiple genotypes) for SSRs
following GenAlEx version 6.1 software (Peakall and
Smouse, 2007). The matrix thus generated was used
for preparing PCA plots. GenAlEx was also used for
computing other genetic diversity parameters such as
pair-wise Nei’s unbiased genetic distance and genetic
identity (Nei, 1978), pair-wise
Fst
(Wright, 1951) and
gene flow (Nm).
3.6 Analysis of molecular variance (AMOVA)
Analysis of molecular variance (AMOVA) was
performed using the genetic distance matrices (same
as used for PCA) for hierarchical partitioning of
genetic variation not only among the genotypes of the
two species, but also among the collection of
indigenous and exotic genotypes in each of the two
jute species separately. This was done using the
software GenAlEx following Excoffier et al (1992).
Authors' Contributions
SB planned and conducted experiments, analysed the data and
wrote the first draft of the manuscript. PKG, HSB, MKS and
DS conceived the idea, supervised the work, and helped on a