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Research Article

Legume Research, volume 45 issue 7 (july 2022) : 804-814

Identification of Highly Polymorphic Molecular Markers and Potential Genotypes for Harnessing Chickpea Breeding Strategies

Ashwani Kumar1,2,3, Ashwani Yadav1,3, Renu Yadav1,4, J.P. Misra1,3, R.S. Yadav2, H.D. Upadhyaya5, Rajendra Kumar6,*
1Department of Biotechnology, Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut-250 110, Uttar Pardesh, India.
2Department of Botany, DAV College, Muzaffarnagar- 251 001, Uttar Pardesh, India.
3UP Council of Agricultural Research, Lucknow-226 010, Uttar Pardesh, India.
4Amity University, Noida-201 313, Uttar Pardesh, India.
5International Crops Research Institute for the Semi-Arid Tropics, Patancheru-502 324, Hyderabad, Telangana, India.
6Division of Genetics, ICAR-Indian Agricultural Research Institute, Pusa, New Delhi-110 012, India.

  • Submitted26-03-2020|

  • Accepted14-08-2020|

  • First Online 09-11-2020|

  • doi 10.18805/LR-4379

Cite article:- Kumar Ashwani, Yadav Ashwani, Yadav Renu, Misra J.P., Yadav R.S., Upadhyaya H.D., Kumar Rajendra (2022). Identification of Highly Polymorphic Molecular Markers and Potential Genotypes for Harnessing Chickpea Breeding Strategies . Legume Research. 45(7): 804-814. doi: 10.18805/LR-4379.

ABSTRACT

Background: STMS markers and morphological traits were used to investigate the genetic relationship and allelic diversity in chickpea. In this study, we focused on the selection and more efficient utilization of core germplasm in breeding programs for chickpea crop improvement using STMS and quantitative / morphological traits. 

Methods: Seeds of elite accessions of chickpea were obtained from ICRISAT, Patancheru, Andhra Pradesh, India. 50 STMS markers and 11 quantitative traits were used for exploring the genetic variability and relationship in 35 chickpea accessions. 

Result: A total of 97 alleles were produced out of the 32 polymorphic STMS loci with an average of 3.03 alleles per locus ranging between 2-6 alleles per primer. The PIC value ranged from 0.029 to 0.768 with an average of 0.502. PIC value showed a highly positive correlation (r = 0.718) with number of alleles at the STMS loci. In both molecular and morphological markers / traits-based clustering, out of 35 chickpea accessions only one accession ICC-13892 was isolated at the end of clustering. The results indicated that highly polymorphic microsatellite markers NCPGR 68, NCPGR 50, NCPGR 81, NCPGR 48 and NCPGR 77 along with the accessions ICC-13892 having distant associations with ICC-13816, ICC-15697, ICC-15610, ICC-15868, ICC-15888, ICC-15996 with novel findings should be useful resources for strategies of allele mining, association genetics, mapping and cloning of gene(s) and in applied breeding to broaden the genetic base of chickpea.

INTRODUCTION

Chickpea (Cicer arietinum L.) is an annual, self-pollinating, diploid (2n = 2x = 16) food legume that ranks second in world legume production (Gaur et al., 2012). It is primarily cultivated in arid and semi-arid areas of the world. Chickpea is valued for its nutritious seeds, which contain 20-30% protein, ~ 40% carbohydrate and only 3-6% oil (Gil et al., 1996). Chickpea is often grown as a disease break in rotation with other crops and contributes to the maintenance of soil fertility through the fixation of atmospheric nitrogen. Hence, chickpea does not only serve as a good source of nutrition to the people but also improves the fertility of the soil.
       
Quantitative traits provide an estimate of genetic diversity and cluster analyses have been successfully used to classify and measure the pattern of genetic diversity in germplasm, as in chickpea (Naghavi and Jahansouz, 2005), black gram (Ghafoor et al., 2001), pea (Amurrio et al., 1995), soybean (Perry and McIntosh, 1991), alfa-alfa (Smith et al., 1995), lentil (Sultana et al., 2006) and cowpea (Nkoana et al., 2019). Among numerous techniques available for assessing the genetic variability and relatedness among crop germplasm, DNA-based markers provide very effective and reliable tools for measuring genetic diversity in crop germplasm and studying evolutionary relationships (Iruela et al., 2002). Molecular techniques using DNA polymorphism have been increasingly used to characterize and identify a novel germplasm for uses in the crop breeding process (O’Neill et al., 2003).
               
Among various types of DNA marker, microsatellite markers [simple sequence repeats (SSRs) or sequence-tagged microsatellite site (STMS)] have been used extensively in genetic diversity analysis and DNA typing in recent years (Choumane et al., 2000; Abe et al., 2003; He et al., 2003). Microsatellite markers have also been developed for C. arietinum (Hüttel et al., 1999; Muehlbauer and Kahl, 1999; Winter et al., 1999; Sethy et al., 2003; Lichtenzveig et al., 2005; Bhardwaj et al., 2014). Microsatellites consist of tandemly repeated units, each between one and 10 base-pairs in length, such as (TG)n or (AAT)n (Bruford and Wayne, 1993). They are widely dispersed through eukaryotic genomes and are often highly polymorphic. The aim of the present study was to assess the genetic diversity and relationship amongst 35 chickpea accessions to facilitate the selection and more efficient utilization of this germplasm in breeding programmes using STMS markers and morphological traits.

MATERIALS AND METHODS

Seed material, field experiment and genomic DNA extraction

Seeds of elite accessions of chickpea were obtained from ICRISAT (International Crop Research Institute for the Semi-Arid Tropics), Patancheru,  Andhra Pradesh, India representing different geographical areas of the world (Table 1). The experiments were conceptualized, standardized and conducted at Crop Research Centre (CRC), Sardar Vallabhbhai Patel University of Agriculture and Technology, Modipuram, Meerut, Amity University during the period 2009-15. Healthy seeds of 35 chickpea accessions were sown in the experimental field in augmented block design (Federer, 1956) with three replications under all suitable agronomic practices. Eleven morphological traits including plant height (cm), internode length (cm), days to 50% flowering, number of primary branches per plant, number of secondary branches per plant, number of pods per plant, number of seeds per plant, number of seeds per pod, days to plant maturity, 100-seed weight (g), seed yield per plant (g) were recorded on 10 competitive plants basis in the middle of each row for each accessions. For extraction of DNA young and fresh leaves of each chickpea accessions were collected and total genomic DNA was extracted using CTAB procedure as described by Doyle and Doyle (1990) with minor modifications. The quantity and quality of DNA were determined by biophotometeric analysis and agarose gel electrophoresis, respectively. All DNA samples were stored at -20°C for use in PCR amplification.
 

Table 1: List of chickpea accessions used in the present investigation.


 
PCR amplification and gel electrophoresis
 
A total of 50 STMS primers were used (Sethy et al., 2006, Table 2) to assess the polymorphism in 35 chickpea accessions. The PCR amplification was carried out in 10 µl reaction volumes that contained 1X PCR buffer, 50 µM Mgcl2, 10 µM of each primer, 2.5 mM of dNTPs and 1 U Red Taq DNA polymerase (Bangalore GeNei, India). The PCR amplification was carried out in Master cycler gradient PCR (Eppendorf, Germany) with following profile: 2-minute initial denaturation at 95°C followed by 35 cycles of 95°C for 20 second, 53-62°C (primer specific annealing) for 50 second, 72°C for 50 second and final extension at 72°C for 7 minute. The amplified PCR products were resolved at 1.5% Agarose gel in 1X TBE buffer by horizontal gel electrophoresis for 2 hrs at 50 Voltage.
 

Table 2: List of chickpea STMS primers used in DNA fingerprinting of chickpea.


 
STMS amplification, data scoring and statistical analysis
 
The gel was scored both manually and with the help of the gel doc system. Allele size was determined on the basis of bands position. Alleles were numbered as ‘a1’, ‘a2’, ‘a3’ etc. sequentially from the largest to the smallest sized band. The allelic band for all the chickpea accessions were scored in a binary matrix on the basis of presence (1) or absence (0) of bands. The binary matrix was used to estimate DNA polymorphisms and genetic relatedness of chickpea accessions.     

Polymorphic information content (PIC) was determined as per Senior et al. (1998) for each STMS primer pair. The PIC, as a measure of the allele diversity at a locus, was determined as equal to 1-åPij2, where Pij is the frequency of the jth allele for ith locus summed across all alleles in the locus. The 0-1 data matrix was further used to calculate genetic similarity (GS) between pairs of accessions using SIMQUAL module of NTSYS-pc software ver.2.2 (Exeter software, New York) (Rohlf, 1993). The similarity matrix was then used to generate a dendrogram depicting clustering pattern of accessions using unweighted pair group method with arithmetic averages (UPGMA) methods under sequential agglomerative hierarchical nested clustering (SAHN) module of NTSYS.

RESULTS AND DISCUSSION

Allelic analysis and polymorphism of STMS markers
 
Out of 50 STMS primer pairs were used for the fingerprinting of 35 chickpea accessions, 18 primer pairs namely NCPGR 40, NCPGR 41, NCPGR 42, NCPGR 43, NCPGR 44, NCPGR 51, NCPGR 52, NCPGR 53, NCPGR 54, NCPGR 55, NCPGR 56, NCPGR 58, NCPGR 60, NCPGR 62, NCPGR 63, NCPGR 64, NCPGR 79 and NCPGR 84 were found to be monomorphic and the rest 32 primer pairs as polymorphic. The detailed statistical parameters of these 32 polymorphic STMS primers are presented in Table 3. The STMS markers used in the present investigation exhibited a high degree of polymorphism producing a total of 97 alleles with an average of 3.03 alleles per locus. Most of the 15 marker loci produced 2 alleles, followed by 9 primers produced 3 alleles, 4 primers produced 5 alleles, 2 primers produced 4 alleles and 2 primers produced 6 alleles. The range of alleles observed in our study is comparatively less than the previous reports (Sethy et al., 2006; Chaudhary et al., 2012) where they have reported allele range 2 to 11 with an average of 6.4 alleles / loci in chickpea. However, our report is comparable to several other reports (2011; Ghaffari et al., 2014; Katoch et al., 2016; Kumar et al., 2017; Rashmi et al., 2012; Rizvi et al., 2014; Singh et al., 2011, 2012, 2013; Soi et al., 2014).
 

Table 3: List of 32 polymorphic STMS markers with number of alleles and PIC value.


       
Out of 97 alleles detected, 8 were considered as rare alleles due to their low frequency (<0.03), 23 as common (0.04-0.20) and rest 66 as frequent alleles (>0.21) (Table 3). The average polymorphic information content (PIC) value was found to be 0.502 with a range of 0.029 (NCPGR 37) and 0.768 (NCPGR 68) (Table 3). The PIC value reveals the informativeness level and accordingly is defined into high (PIC>0.5), moderate (0.5>PIC>0.25) and low (PIC<0.25) categories (Botstein et al., 1980). In the present investigation, the STMS markers exhibited moderate to high level of informativeness with average PIC value of 0.502 and most of the STMS (53.0%) had PIC value more than 0.50.
       
A positive correlation was obtained (r = 0.718) between PIC and number of alleles at the STMS locus, which confirms that STMS markers used in this study were highly informative. The positive association of PIC value and allele number was also reported earlier by Saini et al., (2004). The PIC value obtained in the present study was lower than reported by several others (Singh et al., 2008; Ghaffari et al., 2014) but it was comparable to as reported by href="#chaudhary_2012">Chaudhary et al., (2012). In reference to PIC value the STMS markers namely NCPGR 68, NCPGR 50, NCPGR 81, NCPGR 48 and NCPGR 77 were considered as very good markers. However, NCPGR 37 and NCPGR 49 were considered as very poor markers and the rest of the markers as moderate.
 
Diversity analysis on the basis of STMS markers
 
The genotypic data of the polymorphic STMS primers was used to study the genetic relationship among the chickpea accessions. The pairwise genetic similarity coefficients ranged from 0.22 to 0.91. The highest similarity occurred between ICC-15868 vs ICC-15888 and ICC-16269 vs ICC-16487 with a coefficient value of 91% and the lowest similarity occurred between ICC-13892 vs ICC-15610 with a coefficient value of 22%.
       
The dendrogram based on UPGMA clustering clearly revealed 7 distinct clusters namely A, B, C, D, E, F and G (Fig 1). Cluster A comprised 6 accessions, which were further divided into two sub-clusters viz. A-1 and A-2. Sub-cluster A-1 consisted of three accessions ICC-13816, ICC-15697 and ICC-15610. Sub-cluster A-2 consisted of three accessions ICC-15868, ICC-15888 and ICC-15996. Cluster B consisted of only two accessions ICC-15333 and ICC-15406. Cluster C comprised 7 accessions, which were further divided into two sub-clusters viz. C-1 and C-2. Sub-cluster C-1 consisted of three accessions ICC-13863, ICC-14098 and ICC-14199. Sub-cluster C-2 consisted of 4 accessions ICC-14077, ICC-15264, ICC-14595 and ICC-14778. Cluster D consisted of 4 accessions ICC-15510, ICC-15518, ICC-16903 and ICC-15294. Cluster E comprised 8 accessions, which were further subdivided into two sub-clusters viz. E-1 and E-2. Sub-cluster E-1 consisted of three accessions ICC-14831, ICC-16207 and ICC-16261. Sub-cluster E-2 consisted of 4 accessions ICC-16269, ICC-16487, ICC-16524 and ICC-16915. Accession ICC-14799 was isolated at the end of cluster E. Cluster F consisted of only two accessions ICC-14815 and ICC-15606. Cluster G consisted of 6 accessions namely ICC-14402, ICC-14669, ICC-15567, ICC-15802, ICC-15612 and ICC-13892. At the end of clustering, out of 35 chickpea accessions only one accession ICC-13892 was isolated.
 

Fig 1: Dendrogram based on STMS markers.


       
However, the accessions, ICC-13892, ICC-15612, ICC-15802, ICC-15567 expressed distant association with ICC-13816, ICC-15697, ICC-15610, ICC-15868, ICC-15888 and ICC-15996 revealing very high diversity in their genotypic structure. Similar results have also been reported in chickpea by Monika et al., 2018 and Vishnu et al., 2020. These accessions could be potentially utilized in various hybridization programmes for further genetic improvement of chickpea.
 
Diversity analysis based on quantitative traits
 
The pooled quantitative trait data (Table 4) partially published (Kumar et al., 2013, 2014) across the seasons were used to generate a dendrogram with the help of computer software NTSYS-pc. The genetic dissimilarity coefficients for the 35 chickpea accessions based on 11 quantitative traits ranged from 0.01 to 0.578. The highest dissimilarity coefficient value (57.8%) occurred between two chickpea accessions, ICC-7272 vs ICC-15697 and the lowest dissimilarity coefficient values (1.0%.) occurred between ICC-11944 vs ICC-14799 and ICC-14595 vs ICC-14669.

Table 4: Two years pooled morphological data for 35 chickpea accessions.



The resulting dendrogram classified the 35 chickpea accessions into 7 distinct clusters namely A, B, C, D, E, F and G (Fig 2). Cluster A comprised 6 accessions, which were further subdivided into two sub-clusters viz. A-1 and A-2. Sub-cluster A-1 consisted of three accessions ICC-13816, ICC-15697 and ICC-15610. Sub-cluster A-2 consisted of three accessions ICC-15868, ICC-15888 and ICC-15996. Cluster B consisted of only two accessions ICC-15333 and ICC-15406. Cluster C comprised 7 accessions, which were further subdivided into two sub-clusters viz. C-1 and C-2. Sub-cluster C-1 consisted of three accessions ICC-13863, ICC-14098 and ICC-14199. Sub-cluster C-2 consisted of 4 accessions ICC-14077, ICC-15264, ICC-14595 and ICC-14778. Cluster D consisted of 5 accessions ICC-15510, ICC-15518, ICC-16903, ICC-15294 and ICC-14799. Cluster E consisted of 4 accessions ICC-14669, ICC-15567, ICC-15802 and ICC-15612. Cluster F consisted of 8 accessions, which were further subdivided into two sub-clusters viz. F-1 and F-2. Sub-cluster F-1 consisted of three accessions ICC-14831, ICC-16207 and ICC-16261. Sub-cluster F-2 consisted of 4 accessions ICC-16269, ICC-16487, ICC-16524 and ICC-16915. Accession ICC-14402 was isolated from the cluster F. Cluster G consisted of three accessions ICC-14815, ICC-15606 and ICC-13892. At the end of clustering, out of 35 chickpea accessions only one accession ICC-13892 was isolated.
 

Fig 2: Dendrogram based on morphological data.


       
The maximum similarity coefficient value occurred between chickpea accessions, ICC-15868 vs ICC-15888 and ICC-16269 vs ICC-16487 in the tune of molecular data-based similarity index values. However, the accessions ICC-13892, ICC-14815, ICC-15606, ICC-16915 expressed distant association with ICC-13816, ICC-15697, ICC-15610, ICC-15868, ICC-15888, ICC-15996 revealing high degree of diversity in phenotypic expressions.

CONCLUSION

Crop improvement depends on the existence of genetic diversity. We report that STMS markers NCPGR 68, NCPGR 50, NCPGR 81, NCPGR 48 and NCPGR 77 are highly efficient polymorphic markers and should be utilized to assess chickpea genetic and allelic diversity. The morphological as well as molecular data-based dissimilarity values confirm the distant association of accession ICC-13892 with accessions ICC-13816, ICC-15697, ICC-15610, ICC-15868, ICC-15888, ICC-15996 as a novel finding and should be utilized in various hybridization programmes for further genetic broadening and chickpea improvement. Thus, identified polymorphic STMS markers along with distantly related accessions will be useful resources for future strategies of allele mining, association genetics, mapping and cloning of gene(s) and in applied breeding to broaden the genetic base of chickpeas.

ACKNOWLEDGEMENT

The authors gratefully acknowledge the financial support from the National Fund for Basic and Strategic Research (NFBSRA) of Indian Council of Agricultural Research (ICAR), New Delhi.

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