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Genetic relatedness among indigenous rice varieties in the Eastern Himalayan region based on nucleotide sequences of the Waxy gene
© Choudhury et al.; licensee BioMed Central. 2014
Received: 2 June 2013
Accepted: 17 December 2014
Published: 29 December 2014
Indigenous rice varieties in the Eastern Himalayan region of Northeast India are traditionally classified into sali, boro and jum ecotypes based on geographical locality and the season of cultivation. In this study, we used DNA sequence data from the Waxy (Wx) gene to infer the genetic relatedness among indigenous rice varieties in Northeast India and to assess the genetic distinctiveness of ecotypes.
The results of all three analyses (Bayesian, Maximum Parsimony and Neighbor Joining) were congruent and revealed two genetically distinct clusters of rice varieties in the region. The large group comprised several varieties of sali and boro ecotypes, and all agronomically improved varieties. The small group consisted of only traditionally cultivated indigenous rice varieties, which included one boro, few sali and all jum varieties. The fixation index analysis revealed a very low level of differentiation between sali and boro (FST = 0.005), moderate differentiation between sali and jum (FST = 0.108) and high differentiation between jum and boro (FST = 0.230) ecotypes.
The genetic relatedness analyses revealed that sali, boro and jum ecotypes are genetically heterogeneous, and the current classification based on cultivation type is not congruent with the genetic background of rice varieties. Indigenous rice varieties chosen from genetically distinct clusters could be used in breeding programs to improve genetic gain through heterosis, while maintaining high genetic diversity.
The indigenous rice varieties in NE India show remarkable diversity in morphological and agronomic traits including high variability in size, shape, aroma and nutritional properties of grains , disease resistance  and abiotic stress tolerance . A recent study revealed high levels of genetic diversity in these rice varieties with the highest genetic diversity in the varieties of the sali ecotype, followed by the jum and boro ecotypes . These rice varieties with exceptional phenotypic and genetic diversity can serve as an important source of germplasm for the genetic improvement of cultivated rice. A thorough understanding of genetic relatedness among these rice varieties is crucial for designing breeding programs for the genetic improvement of rice, allowing us to capitalize on genetic gain through heterosis while maintaining high genetic diversity.
The objective of the present study is to infer the genetic relatedness among indigenous rice varieties of sali, boro and jum ecotypes cultivated in NE India using the nucleotide sequences of the Wx gene. As a single copy nuclear gene with high polymorphism, the nucleotide sequences of the Wx gene is an ideal genomic tool to assess the genetic relatedness of rice varieties. The Wx gene, which encodes granule-bound starch synthase [8, 9], determines the amylose content in the endosperm and influences the glutinous nature of the rice grain. The nucleotide sequences of three Wx genes (Wx-A1, Wx-B1 and Wx- D1) reported from wheat  have been used successfully to infer genetic relatedness among wheat cultivars , highlighting the Wx gene’s suitability for determining genetic relatedness in crop plants.
The variety name, cultivation type and collection sites of traditionally cultivated indigenous and agronomically improved rice varieties in Northeast India (AP, Arunachal Pradesh; AS, Assam; ML, Meghalaya; MZ, Mizoram)
N. Lakhimpur, (AS)
N. Lakhimpur, (AS)
N. Lakhimpur, (AS)
N. Lakhimpur, (AS)
Garo Hills (ML)
West Siang (AP)
PCR amplification and sequencing
Oligonucleotide primer sequences used for amplification of the Wx gene
The DNA sequences were analyzed using the computer program Geneious version 5.4.6 (http://www.geneious.com/). The resulting consensus sequences were aligned using the software program ClustalW v2 . We used Bayesian, maximum-parsimony (MP) and neighbor-joining (NJ) methods to infer genetic relatedness of rice varieties. The Bayesian analysis infers the phylogenetic relationships based on posterior probability distribution using evolutionary models , whereas the MP analysis infers the evolutionary tree(s) with the minimum number of nucleotide changes . The NJ method uses a pairwise distance matrix to infer the genetic relatedness among taxa . Thus, the use of a variety of approaches that differ in underlying assumptions provided a means to assess the robustness of resulting phylogenetic trees.
The best model of nucleotide substitution obtained through Modeltest analy ses based on Akaike Information Criterion (AIC)
HKY + I + G
A = 0.275
C = 0.239
G = 0.213
T = 0.273
Ti/Tv ratio = 3.489
Among-site rate variation
Proportion of invariable sites (I) = 0.937
Variable sites (G)
Gamma distribution shape parameter = 0.148
Using mixed χ2 distribution
P-value = < 0.00001
The phylogenetic trees based on NJ and MP methods were inferred using the PAUP*  software. Kimura 2-parameter distances  were used in the NJ analysis following Saitou and Nei . The MP analyses were performed with full heuristic search with tree bisection-reconnection branch swapping and random order of taxon addition option. The robustness of tree topologies was tested with 1000 bootstrap replicates. Nodes with greater than 50% bootstrap support were retained in the tree.
Genetic relatedness among rice varieties was further analyzed through haplotype networks. In this analysis, a series of nested clades based on haplotypic or allelic networks were reconstructed. The haplotype network analysis infers evolutionary relationships among intraspecific populations and closely related species . The median-joining algorithm  as implemented in the software package NETWORK 4.5.1 (Fluxus Technology) was used in this analysis. The level of differentiation between the ecotypes was estimated by calculating FST values between pairs of populations using the DnaSP software .
The MP analysis resulted in 141 equally parsimonious trees with total length of 140 steps, and the consensus tree topology was similar to the tree based on the Bayesian analysis. Most varieties of the sali ecotype clustered within Group-I along with the varieties of boro and jum ecotypes (Additional file 1: Figure S2). The other clade (Group-II) comprised only indigenous rice varieties. The varieties clustered within Group-III were identical to the group that clustered together in the Bayesian analysis. The sole difference between the Bayesian and MP-based trees was the placement of two varieties of the sali ecotype (Harinarayan and Kakiberoin), which occupied a basal position in Group-II in the former analysis and in Group-I in the latter. The NJ analysis also showed similar tree topology, except for the Group-III varieties, which formed a separate cluster and occupied a basal position in Group -I (Additional file 1: Figure S3).
The pairwise differentiation ( F ST ) of ecotypes
Sali and Boro
Sali and Jum
Jum and Boro
In the present study, we investigated genetic relatedness among three different rice ecotypes in the eastern Himalyan region of NE India. The Bayesian, MP and haplotype network analyses resulted in similar tree topologies consisting of two major groups. This clustering pattern was not congruent with three commonly cultivated ecotypes (sali, boro and jum) in NE India, and suggests a polyphyletic nature of rice ecotypes . This could be attributable to two possible reasons. First, exchange of seed material between regions mediated through human migration , often associated with migration of traditional farmers seeking better opportunities , could lead to cultivation of genetically different varieties within a given geographical locality. Second, large scale flooding during monsoon rainy seasons often damages crop plants, and farmers generally seek seeds from other regions leading to seed exchange between different agroclimatic regions. The polyphyletic nature of rice varieties in the region is in agreement with a previous study based on chloroplast DNA, which suggested polyphyletic maternal lineages for O. sativa ssp. indica. Similar results were also reported in other crop species, including sweet sorghum and grain sorghum lines of Sorghum bicolor ssp. bicolor. Based on the nucleotide sequences of the Wx gene, eight to ten genetically distinct indigenous rice varieties within Group-II are discernible. Similarly, rice varieties in the genetically distinct Group III may also contain unique genotypes. Thus, these indigenous rice varieties can serve as a valuable germplasm for genetic improvement of cultivated rice.
Cultivated rice has been subject to human mediated selection for various traits of agronomic and ecological importance. Adaptation to various agroclimatic conditions and human-mediated selection may have contributed to diversification of rice varieties in the NE Indian region . The jum and boro ecotypes showed a high level of population differentiation (FST = 0.230), indicating local adaptation to contrasting habitats leading to high level of population differentiation [35–37]. The cultivation of varieties of the jum ecotype in dry, upland habitats, and the cultivation of varieties of the boro ecotype in low-lying irrigated land during the winter season may have led to the genetic isolation and genetic differentiation of varieties of these two ecotypes. Very low FST value (0.005) between sali and boro ecotypes at the Wx gene reflects high levels of gene flow between rice varieties of these two ecotypes  or the latter ecotype may have originated from the sali ecotype. Since cultivated rice is mostly self-pollinating , gene flow among varieties is minimal. Thus, the observed low differentiation between these two ecotypes could be attributable to the fact that the boro ecotype may have been selected from the sali ecotype to grow in low-lying areas during the winter season.
The present study based on the nucleotide sequence data of the Wx gene revealed a) the polyphyletic nature of sali, boro and jum rice ecotypes and b) two genetically distinct groups of rice varieties in NE India. One group consisted of only traditionally cultivated varieties, while the other group comprised both agronomically improved and traditionally cultivated rice varieties. The occurrence of genetically distinct groups of rice varieties in the region highlights the importance of rice genetic resources in NE India as potential source of germplasm for genetic improvement of cultivated rice to maintain global food security under changing climatic conditions.
Availability of supporting data
The aligned DNA sequences and phylogeny trees were submitted to TreeBASE (Accession number S14972) which can be accessed from the URL http://purl.org/phylo/treebase/phylows/study/TB2:S14972.
The authors thank the farmers of Northeast India and International Rice Research Institute, Philippines for providing samples for the present study. This study was supported by fNSERC Discovery Grant. BIC received MELS merit scholarship from FRQNT and Faculty of Arts and Science Graduate Fellowship from Concordia University. The comments received from anonymous reviewers are gratefully acknowledged.
- Hore DK: Rice diversity collection, conservation and management in Northeastern India. Genet Resour Crop Evol. 2005, 52 (8): 1129-1140. 10.1007/s10722-004-6084-2.View ArticleGoogle Scholar
- Choudhury B, Khan ML, Dayanandan S: Genetic structure and diversity of indigenous rice (Oryza sativa) varieties in the Eastern Himalayan region of Northeast India. Springer Plus. 2013, 2 (1): 1-10. 10.1186/2193-1801-2-1.View ArticleGoogle Scholar
- Roy S, Rathi RS, Misra AK, Bhatt BP, Bhandari DC: Phenotypic characterization of indigenous rice (Oryza sativa L.) germplasm collected from the state of Nagaland, India. Plant Genet Resour. 2013, 1: 9-Google Scholar
- Ramakrishnan PS: Jhum-centered agro-ecosystem analysis. Shifting agriculture and sustainable development of north-eastern India: Tradition in Transition. Edited by: Ramakrishnan PS, Saxena KG, Rao KS. 2006, New Delhi: UNESCO-MAB, Oxford & IBH Publishing Co. Pvt. LtdGoogle Scholar
- Sharma SD, Vellanki JMR, Hakim KL, Singh RK: Primitive and current cultivars of rice in Assam – a rich source of valuable genes. Curr Sci. 1971, 40 (6): 126-128.Google Scholar
- Shastry SVS, Sarma SD, John VT, Krishnaya K: New sources of resistance to pest and diseases in the Asian rice collection. Int Rice Comm Newsl. 1971, 22: 1-6.Google Scholar
- Paroda RS, Malik SS: Rice genetic resources, its conservation and use in India. Oryza. 1990, 27: 361-369.Google Scholar
- Sano Y: Differential regulation of waxy gene expression in rice endosperm. Theor Appl Genet. 1984, 64: 467-473.Google Scholar
- Zhang Z, Li M, Fang Y, Liu F, Lu Y, Meng Q, Peng J, Yi X, Gu M, Yan C: Diversification of the Waxy gene is closely related to variations in rice eating and cooking quality. Plant Mol Biol Rep. 2012, 30 (2): 462-469. 10.1007/s11105-011-0362-x.View ArticleGoogle Scholar
- Yamamori M, Nakamura T, Endo TR, Nagamine T: Waxy protein deficiency and chromosomal location of coding genes in common wheat. Theor Appl Genet. 1994, 89 (2–3): 179-184.PubMedGoogle Scholar
- Guzman C, Caballero L, Martín LM, Alvarez JB: Waxy genes from spelt wheat: new alleles for modern wheat breeding and new phylogenetic inferences about the origin of this species. Ann Bot. 2012, 110 (6): 1161-1171. 10.1093/aob/mcs201.PubMedPubMed CentralView ArticleGoogle Scholar
- Doyle JJ, Doyle JL: A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochemical Bulletin. 1987, 19: 11-15.Google Scholar
- Dayanandan S, Bawa KS, Kesseli RV: Conservation of microsatellites among tropical trees (Leguminosae). Am J Bot. 1997, 84: 1658-1663. 10.2307/2446463.PubMedView ArticleGoogle Scholar
- Olsen KM, Purugganan MD: Molecular evidence on the origin and evolution of glutinous rice. Genetics. 2002, 162 (2): 941-950.PubMedPubMed CentralGoogle Scholar
- Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD, Gibson TJ, Higgins DG: Clustal W and Clustal X version 2.0. Bioinformatics. 2007, 23: 2947-2948. 10.1093/bioinformatics/btm404.PubMedView ArticleGoogle Scholar
- Nylander JA, Ronquist F, Huelsenbeck JP, Nieves-Aldrey J: Bayesian phylogenetic analysis of combined data. Syst Biol. 2004, 53: 47-67. 10.1080/10635150490264699.PubMedView ArticleGoogle Scholar
- Edwards AWF, Cavalli-Sforza LL: The reconstruction of evolution. Heredity. 1963, 18: 553-Google Scholar
- Saitou N, Nei M: The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol. 1987, 4 (4): 406-425.PubMedGoogle Scholar
- Ronquist F, Huelsenbeck JP: MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics. 2003, 19 (12): 1572-1574. 10.1093/bioinformatics/btg180.PubMedView ArticleGoogle Scholar
- Larget B, Simon DL: Markov chain Monte Carlo algorithms for the Bayesian analysis of Phylogenetic trees. Mol Biol Evol. 1999, 16: 750-759. 10.1093/oxfordjournals.molbev.a026160.View ArticleGoogle Scholar
- Posada D, Crandall KA: Modeltest: testing the model of DNA substitution. Bioinformatics. 1998, 14 (9): 817-818. 10.1093/bioinformatics/14.9.817.PubMedView ArticleGoogle Scholar
- Hasegawa M, Kishino H, Yano TA: Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. J Mol Evol. 1985, 22 (2): 160-174. 10.1007/BF02101694.PubMedView ArticleGoogle Scholar
- Rambaut A, Drummond A: FigTree v1. 3.1. Program distributed by the author. 2009, Edinburgh, United Kingdom: Institute of Evolutionary Biology, University of EdinburghGoogle Scholar
- Swofford DL: PAUP* 4.0 - Phylogenetic Analysis Using Parsimony (*and Other Methods). 2001, Sunderland, MA: Sinauer AssocGoogle Scholar
- Kimura M: A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol. 1980, 16: 111-120. 10.1007/BF01731581.PubMedView ArticleGoogle Scholar
- Templeton AR, Routman E, Phillips CA: Separating population structure from population history: a cladistic analysis of the geographical distribution of mitochondrial DNA haplotypes in the tiger salamander Ambystoma tigrinum. Genetics. 1995, 140: 767-782.PubMedPubMed CentralGoogle Scholar
- Bandelt HJ, Forster P, Rohl A: Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol. 1999, 16 (1): 37-48. 10.1093/oxfordjournals.molbev.a026036.PubMedView ArticleGoogle Scholar
- Librado P, Rozas J: DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics. 2009, 25 (11): 1451-1452. 10.1093/bioinformatics/btp187.PubMedView ArticleGoogle Scholar
- Khush GS, Brar DS, Virk PS, Tang SX, Malik SS, Busto GA, Lee YT, McNally R, Trinh LN, Jiang Y, Shata MAM: IRRI Discussion Paper Series No. 46. Classifying rice germplasm by isozyme polymorphism and origin of cultivated rice. 2003, Los Banos (Philippines): International Rice Research Institute, 279-Google Scholar
- Hart JP: Maize, matrilocality, migration, and northern Iroquoian evolution. J Archaeol Method Theory. 2001, 8 (2): 151-182. 10.1023/A:1011301218533.View ArticleGoogle Scholar
- Rajan SI, Korra V, Chyrmang R: Politics of Conflict and Migration. Migration, Identity and Conflict: India Migration Report. Edited by: Rajan SI. 2011, New Delhi: Routledge, 95-101.Google Scholar
- Cheng C, Motohashi R, Tsuchimoto S, Fukuta Y, Ohtsubo H, Ohtsubo E: Polyphyletic origin of cultivated rice: based on the interspersion pattern of SINEs. Mol Biol Evol. 2003, 20 (1): 67-75. 10.1093/molbev/msg004.PubMedView ArticleGoogle Scholar
- Wang ML, Zhu C, Barkley NA, Chen Z, Erpelding JE, Murray SC, Tuinstra MR, Tesso T, Pederson GA, Yu J: Genetic diversity and population structure analysis of accessions in the US historic sweet sorghum collection. Theor Appl Genet. 2009, 120 (1): 13-23. 10.1007/s00122-009-1155-6.PubMedView ArticleGoogle Scholar
- Darwin C: The Variations of Animals and Plants under Domestication. 1850, New York: D. AppletonGoogle Scholar
- Xia H, Camus-Kulandaivelu L, Stephan W, Tellier A, Zhang Z: Nucleotide diversity patterns of local adaptation at drought-related candidate genes in wild tomatoes. Mol Ecol. 2010, 19: 4144-4154. 10.1111/j.1365-294X.2010.04762.x.PubMedView ArticleGoogle Scholar
- Beaumont MA, Balding DJ: Identifying adaptive genetic divergence among populations from genome scans. Mol Ecol. 2004, 13 (4): 969-980. 10.1111/j.1365-294X.2004.02125.x.PubMedView ArticleGoogle Scholar
- Riebler A, Held L, Stephan W: Bayesian variable selection for detecting adaptive genomic differences among populations. Genetics. 2008, 178: 1817-1829. 10.1534/genetics.107.081281.PubMedPubMed CentralView ArticleGoogle Scholar
- Wright S: The interpretation of population structure by F-statistics with special regard to systems of mating. Evolution. 1965, 19 (3): 395-420. 10.2307/2406450.View ArticleGoogle Scholar
- Oka HI: Experimental studies on the origin of cultivated rice. Genetics. 1974, 78 (1): 475-486.PubMedPubMed CentralGoogle Scholar
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