Assessment of AFLP marker based genetic diversity in chilli (Capsicum annuum L. & C. baccatum L.)
S L Krishnamurthy1*, Y Prashanth1, A Mohan Rao1, K Madhavi Reddy2 and R Ramachandra1
1Department of Genetics and Plant Breeding, University of Agricultural Sciences, Bengaluru 560 065, India
2Division of Vegetable, Indian Institute of Horticulture Research, Bengaluru 560 089, India Received 6 September 2013; revised 28 November 2013; accepted 4 January 2014
Chilli (Capsicum annuum L.) is a leading spice cum vegetable crop grown commercially in India. Selection of parents is one of the important steps in hybrid breeding programme. The efficiency of hybrid breeding programme could be increased if the inbred lines per se could be screened for genetic diversity using molecular markers. The present study was conducted to assess the amplified fragment length polymorphism (AFLP) marker based diversity in 59 (3 C. baccatum L. and 56 C.
annuum) chilli genotypes during 2009 at University of Agricultural Sciences (UAS), Bangalore. The 8 AFLP primer combinations generated a total of 414 amplicons, of which 389 were polymorphic with an average of 48.62 bands.
The primer combination, EcoRI+AGC and MseI+GCT was found to amplify a highest number of 81 scorable bands with 97.53 per cent polymorphic bands. The PIC (polymorphic information content) values ranged from 0.84 to 0.97 with a mean of 0.93. All C. baccatum species (PBC 1752, PBC 80 and susceptible baccutum) were grouped in cluster I and other 56 chilli genotypes (C. annuum) were grouped in nine different clusters. The variation range of genetic similarity (GS) coefficients in two groups differed only slightly, where the values varied from 0.19 to 0.85 in Taiwan and from 0.24 to 0.90 in Indian genotypes. This indicates potentially identical diversity in Indian and Taiwan chilli gene pools. Considering the high polymorphism and data frequency revealed by AFLP markers, the technique is recommended for chilli genetic studies and for the identification of chilli genotypes.
Keywords: AFLP, Capsicum annuum, diversity, heterosis
Introduction
Chilli (Capsicum annuum L.) is a leading spice cum vegetable crop grown commercially in India, China, Ethiopia, Hungary, Indonesia, Japan, Spain, Mexico and other countries. India is the largest producer in the world1. In India, it is grown in an area of 9.15 mha with production of 11 lakh tons. India accounts for 26 per cent of global production followed by China. Although, India is the largest producer, productivity is far less (1.1 t ha¯1) compared to global average productivity (4.0 t ha¯1). Selection of parents is one of the important steps in hybrid breeding programme. The efficiency of hybrid breeding programme could be increased if the inbred lines per se could be screened for genetic diversity using molecular markers2. Molecular markers are not influenced by environmental factors and are also fast, efficient and more sensitive compared to field testing to detect large number of distinct differences between genotypes at the DNA level3.
To plan appropriate breeding programme for high yielding cultivars, the plant breeder must possess adequate knowledge on genetic divergence.
Assessment of molecular polymorphism is more meaningful compared to phenotypic divergence as the latter involves data on morphological traits, which are environmental dependent. The study of polymorphism is best done at the level of nucleotide bases in DNA, which is the primary source of all biological information. At this level, even seemingly identical accessions could display enormous differences, if only we could employ appropriate DNA profiling techniques. Molecular markers are used to meet a number of objectives including genetic diversity analysis and prediction of hybrid performances in different crop species. Currently several molecular marker techniques are available serving various purposes in crops. Amplified fragment length polymorphism (AFLP) is one of the well-known molecular marker systems relying on polymerase chain reaction (PCR) technique for DNA amplification. It requires no prior sequence knowledge and can detect large number of genetic
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*Author for correspondence:
krishnagene@gmail.com
loci than restrict fragment length polymorphism (RFLP), random amplified polymorphic DNA (RAPD) and simple sequence repeats (SSR) markers.
It can screen the whole genome of the crop compared to other molecular markers. Hence, the present investigation was carried out to assess the AFLP marker based genetic divergence in chilli.
Material and Methods
Plant Material and DNA Extraction
The plants of 59 chilli genotypes (Table 1) were raised during 2009 at University of Agricultural Sciences (UAS), Bangalore. Genomic DNA was extracted from young and healthy leaves of 40 to 50-d-old chilli genotypes4. Each genotype leaf (2 g) was ground into fine powder in liquid nitrogen and 5 mL of extraction buffer (42% urea; 5 M NaCl; 1 M Tris HCl, pH 7.5; 0.5 M EDTA ; 5% sarkosyl; 5%
phenol) and 20% SDS were added to fine leaf powder in 50 mL tube. After shaking, tube was placed on hot water bath at 65ºC for 30 min with intermittent shake.
Equal volume of 24:1 chloroform:isoamyl alcohol was added and centrifuged at 2000 rpm for 20 min.
The upper aqueous phase was taken to other tube and added with equal volume of 24:1 chloroform:isoamyl alcohol and centrifuged at 2000 rpm for 20 min. The upper aqueous phase was again taken and added with equal volume of ice cold isopropanol to precipitate the nucleic acid. Hooked out nucleic acid was placed into fresh centrifuge tube and centrifuged at 2000 rpm for 3 min. The pellet was rinsed with 500 µL of 70%
ethanol for 5 min. Finally T10E0.1 buffer was added to the pellet and dissolved pellet stored at −20ºC for short term storage.
AFLP Analysis
According to the AFLP protocol, reaction was performed with some modifications5. The genomic DNA was restricted by using the two restriction endonucleases, EcoRI and MseI, and double stranded adopters were ligated to the ends of the fragments, generating templet DNA for subsequent PCR amplifications. The 2.5 µL of NEB 4 buffer, 1.0 µL of EcoRI (10 U/µL) and 1.0 µL of MseI (5 U/µL) were used for the restriction. The 2.5 µL of T4 DNA ligase buffer with 10 mM ATP, 0.5 µL of EcoRI adapter (5 pmol/µL), 0.5 µL of MseI adapter (50 pmol/µL) and 0.5 µL of T4 DNA ligase (1U/µL) were used for ligation. Ligation reaction was done at 37ºC for 1 h.
The digested/ligated AFLP templates were then
Table 1—List of 59 chilli genotypes, species and geographical location
No. Genotypes Species Geographical locations 1 PBC 1752 C. baccatum AVRDC, Taiwan 2 PBC 80 C. baccatum AVRDC, Taiwan 3 Susceptible Baccutum C. baccatum AVRDC, Taiwan
4 CMS 6A C. annuum AVRDC, Taiwan
5 CMS 7A C. annuum AVRDC, Taiwan
6 CMS 1A C. annuum AVRDC, Taiwan
7 CMS 2A C. annuum AVRDC, Taiwan
8 CMS 3A C. annuum AVRDC, Taiwan
9 CMS 5A C. annuum AVRDC, Taiwan
10 CMS 8A C. annuum AVRDC, Taiwan
11 Dae Pong C. annuum AVRDC, Taiwan 12 Lam pong local short C. annuum AVRDC, Taiwan 13 Susan’s Joy C. annuum AVRDC, Taiwan
14 PBC 142 C. annuum AVRDC, Taiwan
15 CA 14 C. annuum AVRDC, Taiwan
16 CA 9 C. annuum AVRDC, Taiwan
17 CA 6 C. annuum AVRDC, Taiwan
18 CA 2 C. annuum AVRDC, Taiwan
19 Byadgi Dabbi C. annuum Karnataka, India 20 Kunchanggi local 2 C. annuum Karnataka, India 21 Kunchanggi local 1 C. annuum Karnataka, India 22 Gwaribidanur local C. annuum Karnataka, India 23 D 379 C. annuum Karnataka, India 24 Chitrchamba C. annuum Karnataka, India 25 Chickballapur local C. annuum Karnataka, India 26 Byadgi kaddi C. annuum Karnataka, India 27 Arka Suphal C. annuum Karnataka, India 28 Devnur C. annuum Karnataka, India 29 Arka Lohith C. annuum Karnataka, India 30 Arka Abhir C. annuum Karnataka, India 31 Vangara C. annuum Andra Pradesh, India 32 LCA 273 C. annuum Andra Pradesh, India 33 LCA 960 C. annuum Andra Pradesh, India 34 LCA 353 C. annuum Andra Pradesh, India 35 LCA 335 C. annuum Andra Pradesh, India 36 LAM 333 C. annuum Andra Pradesh, India 37 LCA 330 C. annuum Andra Pradesh, India 38 LCA 271 C. annuum Andra Pradesh, India 39 LCA 206 C. annuum Andra Pradesh, India 40 Aparna C. annuum Andra Pradesh, India 41 G 4 C. annuum Andra Pradesh, India 42 Paprika C. annuum Kerala, India 43 Shivani C. annuum Kerala, India
44 X 235 C. annuum Kerala, India
45 PMR 23 C. annuum Kerala, India 46 Samrudi C. annuum Kerala, India 47 CO 3 C. annuum Tamil Nadu, India 48 CO 2 C. annuum Tamil Nadu, India 49 CO 1 C. annuum Tamil Nadu, India 50 Pusa Jwala C. annuum New Dehli, India 51 Tiwari C. annuum New Dehli, India 52 Pusa Sadabhar C. annuum New Dehli, India 53 Pant C 1 C. annuum Uttar Pradesh, India 54 Kashi Anmol C. annuum Uttar Pradesh, India 55 Assam local 2 C. annuum Assam, India 56 Assam local 1 C. annuum Assam, India 57 JCA 283 C. annuum Madya Pradesh, India 58 Phule Jyothi C. annuum Maharastra, India 59 Utkal Awa C. annuum Orissa, India
diluted with 100 µL of T10E0.1, pH 8 and stored at
−20ºC.
Pre-amplification is a polymerase chain reaction where each primer combination has a selection of one nucleotide base (EcoRI+A & MseI+G).
Pre-amplification mix involved 2 µL of EcoRI+A (10 pmol/µL), 2 µL of MseI+G (10 pmol/µL), 0.5 µL of 5 mM dNTP mix, 1.2 µL of Taq buffer (10×) and 0.3 µL of Taq polymerase (5U/µL). Pre-amplification was carried out with the following PCR program:
94ºC/30 sec for anneling and 56ºC/1 min, 72ºC/1 min and 10ºC/30 min for 20 cycles. The pre-amplified products were diluted by adding 48 µL of T10E0.1, pH 8.
Re-amplication is a PCR where each primer has 3 nucleotide extensions. Re-amplication reaction mixture contained: 2 µL of EcoRI+A+N+N, 2 µL of MseI+G+N+N, 0.5 µL of dNTP mix (5 mM), 1.2 µL of Taq buffer (10×) and 0.3 µL of Taq polymerase (5 U/µL) (Table 2). Re-amplication was carried out with the following PCR program: 94ºC/30 sec, 65ºC/30 sec reducing by 0.7ºC/cycle to 56ºC and 72ºC/1 min for 11 cycles, and 94ºC/30 secs for anneling, and 56ºC/30 sec, 72ºC/1 min and 10ºC/30 min for 24 cycles. 8 µL of stop loading dye was added to each sample and denaturation was carried out by heating to 94ºC for 5 min and then cooling to 10ºC for 5 min. Finally the product was stored at −20ºC and 4 µL of the mixture was loaded on a polyacrylamide gel. For each primer combination, samples of 59 genotypes were run on the same gel. After electrophoresis, gels were fixed6 and dried.
Scoring and Data Analysis
For the genetic relationship studies, only distinct, reproducible, well-resolved AFLP fragments in the size range of 70-500 bp were scored as present (1) or absent (0), and a binary data matrix was constructed
based on band scores. Different polymorphic fragments produced by each primer were treated as unit and numbered sequentially. Monomorphic fragments and those with low intensity were not taken into account. The information content of each AFLP marker was computed as PICi=1-∑pi2, where pi is the frequency of the ith band. The mean polymorphic information content (PIC) was calculated for AFLP markers across assay units by applying the above formula7. The discrimination power of each AFLP marker was evaluated by the PIC. PIC values range from 0 (monomorphic) to 1 (very highly discriminative), with many alleles in equal frequencies. The PIC is synonymous with the term gene diversity8,9. Genetic diversity estimate related analyses were done using NTSYSpc ver.2.02i10. Genetic similarities (GS) between pairs of accessions were measured by the Jacard similarity coefficient based on the proportion of shared alleles with SIMQUAL module11. Genetic distances between pairs of lines were estimated as GD or D=1-GS. The clustering of accessions was done based on a similarity matrix using an unweighted pair group method with arithmetic average (UPGMA) algorithm following SAHN module. The clustering result was used to construct a dendrogram following TREE module.
Results and Discussion
Level of AFLP Polymorphism
In the present study, AFLP fingerprinting was applied to assess the diversity in chilli. A total of 8 AFLP primer combinations (with 3 selective nucleotides) were used to amplify genomic DNA of 59 chilli genotypes. The 8 AFLP primer combinations generated 414 amplicons, of which 389 were polymorphic with an average of 48.62 bands (Table 2). Among the 8 AFLP primer combinations,
Table 2—Selective primer combinations, number of polymorphic amplicons and polymorphic information content in AFLP analysis of parents in chilli
No. EcoRI primer selective nucleotides
MseI primer selective nucleotides
Total bands obtained
Polymorphic bands obtained
% polymorphic bands
PIC
1 +AAT +GTG 40 35 87.50 0.96
2 +AAT +GCG 43 40 93.02 0.84
3 +AAT +GCT 45 40 88.89 0.88
4 +AAT +GAG 66 64 96.97 0.97
5 +AAT +GCA 32 29 90.63 0.97
6 +AGC +GCC 66 63 95.45 0.97
7 +AGC +GCG 41 39 95.12 0.96
8 +AGC +GCT 81 79 97.53 0.93
Total 414 389 93.96
EcoRI+AGC and MseI+GCT was found to amplify a highest number of 81 scorable bands, followed by EcoRI+AAT and MseI+GAG, EcoRI+AAT and MseI+GCG, and EcoRI+AAT and MseI+GCT, generating maximum of 66, 66 and 45 scorable bands, respectively. Out of the 8 primer combinations tested, two primer combinations EcoRI+AGC and MseI+GCT, and EcoRI+AAT and MseI+GAG produced the highest amplicons with 97.53 and 96.97 per cent polymorphic bands, respectively. The PIC ranged from 0.84 to 0.97, with a mean of 0.93; it provides an estimate of the discriminatory power of a marker by taking into account not only the number of alleles but also their relative frequencies. The distribution of PIC scores was nearly uniform for all 389 polymorphic AFLP markers. Among 8 AFLP primer combinations, EcoRI+AAT and MseI+GAG, EcoRI+AAT and MseI+GCA, and EcoRI+AGC and MseI+GCC explained the highest percentage of PIC (0.97). Hence, these AFLP primers combinations are
very useful for analysis of divergence in chilli. The high number of polymorphic bands and the high level of polymorphism within chilli genotypes suggest that AFLPs are highly discriminatory and powerful markers for classification, fingerprinting and diversity analysis in wild relatives and as well as cultivated genotypes of chillies. The RAPD markers detected 83.17% polymorphism among the chilli accessions12.
Cluster Analysis
The UPGMA based dendogram was obtained from the binary data deduced from the DNA profiles of the samples analyzed from 8 AFLP primer combinations.
Fifty nine chilli genotypes were grouped by Jaccard’s similarity coefficient (19 to 90 per cent) into ten main cluster groups (Fig. 1). All C. baccatum species (PBC 1752, PBC 80 & susceptible baccutum) were grouped in cluster I, while other 56 chilli genotypes (C. annuum) were grouped in nine different clusters (Table 3). The results of the analysis revealed a very
Fig. 1—UPGMA dendogram of 59 chilli genotypes based on AFLP marker data generated from 8 selective primer combinations.
high genetic diversity between cluster I (C. baccatum genotypes) and other clusters (C. annuum genotypes) with a distance of 0.81. All accessions of C. annuum species were grouped in nine different clusters (Cluster II to X), while accessions of C baccatum were grouped in the same cluster (Cluster I). The earlier reports indicate that the chilli accessions are grouped as per the species12.
The UPGMA dendogam releaved that clusters almost corresponded to the geographical origin of the genotypes with few exceptions. The chilli genotypes collected from IVRDC, Taiwan grouped in cluster III, cluster V and cluster VII. These genotypes in respective clusters were from the same geographical origin. In the cluster III, CA 6 and CA 9 genotypes were considerably similar and were not distinguishable from each other (genetic similarity=0.90); these two genotypes were from the same geographical origin. There were no region- specific (diagnostic) markers (present in genotypes from the same geographical origin but absent in others) and no AFLP marker could clearly discriminate Indian from Taiwan chilli genotypes.
The variation range of genetic similarity (GS) coefficients in both the groups differed only slightly, where the values varied from 0.19 to 0.85 (irrespective of GS=0.90 between CA 6 & CA 9) in Taiwan and from 0.24 to 0.90 in Indian genotypes.
This indicates almost similar diversity in Indian and Taiwan chilli gene pools.
The cluster II had the largest number of 21 genotypes; while other clusters III had 2-8 genotypes (Fig 1 & Table 3). All Taiwan chilli genotypes were grouped in a specific cluster, except CMS 6A, CMS 7A, Dae pong, and Lam pong local short, which were grouped in cluster II, Suson’s joy in
cluster IV and PBC 142 in cluster VIII. In these clusters, these Taiwan chilli genotypes were grouped with the genotypes collected from the southern region of India. These six genotypes from Taiwan had higher similarity with Indian genotypes compared with other Taiwan genotypes13. The cluster II had genotypes collected across India. Other than regional boundaries, there may be many other factors also responsible for divergence. Founder effect and cross-fertilization could be the reasons for fall of genotypes those collected from different locations into one group13,14. Except cluster II, almost all the clusters of chilli genotypes conform with the known geographical location. AFLP clustering of the genotypes into different groups are in agreement with their geographical location and species, indicating the effectiveness of AFLP marker for diversity analysis.
The genotypes Shivani (among Indian genotypes) and Susan’s joy (among Taiwan genotypes) expressed the highest genetic distance and may serves as a very good source in chilli breeding programme. These accessions could be used in future genetic, physiological and morphological studies.
Acknowledgment
We thank Sir Edwin Southern, the Chairman, Kirkhouse Trust, UK for support during the present study. We also thank the Indian Council of Agricultural Research, New Delhi for financial support.
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Table 3—Grouping of 59 chilli genotypes based on 8 primer combination of AFLP marker No Clusters No. of genotypes Cluster composition
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