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The Pharma Innovation Journal 2021; 10(8): 784-791
ISSN (E): 2277- 7695
ISSN (P): 2349-8242
NAAS Rating: 5.23
TPI 2021; 10(8): 784-791
© 2021 TPI
www.thepharmajournal.com
Received: 18-06-2021
Accepted: 24-07-2021
Deepa Singh
Department of Genetics and
Plant Breeding, Prof.
Jayashankar Telangana State
Agricultural University,
Rajendranagar, Hyderabad,
Telangana, India
SNCVL Pushpavalli
Assistant Professor, Institute of
Biotechnology, Prof.
Jayashankar Telangana State
Agricultural University,
Rajendranagar, Hyderabad,
Telangana, India
S Vanisri
Department of Genetics and
Plant Breeding, Prof.
Jayashankar Telangana State
Agricultural University,
Rajendranagar, Hyderabad,
Telangana, India
G Anil Kumar
Agricultural Research Station,
PJTSAU, Adilabad, Telangana,
India
Corresponding Author:
SNCVL Pushpavalli
Assistant Professor, Institute of
Biotechnology, Prof.
Jayashankar Telangana State
Agricultural University,
Rajendranagar, Hyderabad,
Telangana, India
Assessment of genetic diversity in chickpea genotypes
(Cicer arietinum L.) using agro-morphological and SSR
markers
Deepa Singh, SNCVL Pushpavalli, S Vanisri and G Anil Kumar
Abstract
The genetic diversity among thirty six chickpea genotypes was assessed by morphological and molecular
studies. The Mahalanobis D
2
statistic grouped 36 genotypes into six clusters with the largest cluster
comprising 20 genotypes. 100 seed weight contributed the most to genetic divergence. Out of 31 SSR
markers used in the study, 28 were found to be polymorphic. A total of 107 alleles were detected across
36 chickpea genotypes with an average of 3.4 alleles per locus. Polymorphic information content ranged
from 0.52 to 0.84. DICE similarity coefficient classified the genotypes into 4 clusters of which cluster I
was the largest with 14 genotypes. The genetic similarity coefficient ranged from 0.03 to 0.78.
Keywords: Chickpea, D
2
analysis, genetic diversity, SSR markers, PIC
Introduction
Chickpea (Cicer arietinum L.) is an important Rabi legume crop. Chickpea was cultivated on
97 lakh hectares in India during 2019-20, with yield and productivity of 11.08 MT and 1142
kg/ha, respectively. (Source: Directorate of Economics and Statistics, DAC&FW 2019-20).
The crop is majorly grown in the states of Madhya Pradesh, Rajasthan, Telangana,
Maharashtra, Karnataka, Uttar Pradesh, and Andhra Pradesh. Chickpea meets its nitrogen
requirements through biological nitrogen fixation and provides a substantial quantity of
residual nitrogen for future crops, improving soil quality, long-term stability, and
sustainability. It plays an important part in meeting the daily nutritional needs of the Indian
populace. Chickpea production may be increased by selecting better genotypes that are directly
related to seed yield and using these genotypes in breeding programs to enhance grain yield.
The most commonly targeted traits for chickpea improvement programs are yield and yield
contributing characters. Yield is a complicated trait that is influenced by a variety of variables
and environment. The primary challenge in plant breeding is the identification and use of
different germplasm. Understanding the patterns of genetic diversity and accurate and
thorough descriptions of breeding materials assists the future breeding programmes.
Mahalonobis D
2
statistic is widely used for analysis of genetic diversity by many researchers
in crop plants (Rao, 1952)
[11]
. Several researchers studied genetic diversity, clustering pattern,
and proportional contribution of various characteristics towards selection effectiveness and
divergence. For successful selection, principal component analysis is performed to identify and
convert a set of correlated variables into a set of smaller variables known as primary
components.
However, it is often assumed that use of molecular markers is more trustworthy and
reproducible than morphological characterization. Various marker systems have been used for
chickpea characterization, including amplified fragment length polymorphism (AFLP),
restriction fragment length polymorphism (RFLP), random amplified polymorphic DNA
(RAPD), and microsatellite markers like simple-sequenced repeats (SSR) or sequenced tagged
microsatellite sites (STMS) (Iruela et al. 2002
[2]
; Nguyen et al. 2004
[9]
; Sachdeva et al. 2018)
[13]
. Because of co-dominance, multiple allelic nature, high polymorphism, locus specificity,
reproducibility, and automation SSRs has been the marker of choice. The present study aims at
assessment of genetic diversity among a set of 36 promising advanced breeding lines which
can be the potential parents for development of high yielding varieties.