Genetic structure between wild and cultivated populations of Carica papaya in Thailand revealed by microsatellites

Main Article Content

Nidchaya Aketarawong
Siriwan Isasawin
Sujinda Thanaphum

Abstract

Evaluation of genetic variation and population structure between wilds and cultivars is important for understanding their origin and distribution, domestication, and genetic relationship. In this research, sixty-one papayas from eight wild populations and 52 additional samples from three cultivars in Thailand were studied using six polymorphic microsatellite loci. Higher genetic variation was observed in the wilds, especially from the South (mean number of alleles (Na) = 2.333 to 2.833; mean observed heterozygosity (HO) = 0.194 to 0.267; mean expected heterozygosity (HE) = 0.481 to 0.526). This suggests that papayas from the southern part of Thailand could be a potential source population of the other local populations. Conversely, the cultivars have been maintained and selected over a long term. There were low levels of genetic variation (Na = 1.167 to 1.500; HO = 0.081 to 0.167; HE = 0.086 to 0.183) with no private alleles. Cross-fertilisation was indirectly detected in both wilds and cultivars, possibly leading to retaining some polymorphisms. Lastly, genetic clustering of wilds and cultivars (K = 2) was identified; however, approximately 22.95% of wild samples (14 out of 61) were genetically admixed (0.100 ≤ Qwilds ≤ 0.900) and 8.20% (five out of 61) belonged to the cultivar cluster (Qcultivars > 0.900). This suggests that feral papayas could survive in a natural environment.

Article Details

How to Cite
Aketarawong, N. ., Isasawin, S. ., & Thanaphum, S. . (2021). Genetic structure between wild and cultivated populations of Carica papaya in Thailand revealed by microsatellites. Asia-Pacific Journal of Science and Technology, 26(03), APST–26. https://doi.org/10.14456/apst.2021.55
Section
Research Articles

References

[1] Chan Y-K. Breeding papaya (Carica papaya L.). In: Mohan Jain S, Priyadarshan PM, editors. Breeding plantation tree crops: tropical species. New York: Springer; 2009. p. 121-159.
[2] Ratchadaporn J, Sureeporn K, Khumcha U. An analysis on DNA fingerprints of thirty papaya cultivars (Carica papaya L.), grown in Thailand with the use of amplified fragment length polymorphisms technique. Pak J Biol Sci. 2007;10:3072-3078.
[3] Napasintuwong O, Traxler G. Ex-ante impact assessment of GM papaya adoption in Thailand. Ag Bio Forum. 2009;12(2):209-217.
[4] Davidson SN. Power, progress and prevarication. GM Crops & Food. 2012;3(2):104-110.
[5] Gonsalves D, Gonsalves C, Ferreira S, Pitz K, Fitch M, Manshardt R, Slightom JL. Transgenic virus resistant papaya: from hope to reality for controlling papaya ringspot virus in Hawaii. APSnet Features. 2004;Online. doi:10.1094/APSnetFeature-2004-0704
[6] Stokstad E. GM papaya takes on ringspot virus and wins. Science. 2008;320(5875):472.
[7] Pattanapomgthorn J, Sutduean J, Keohavong B. Impact of genetically modified food knowledge, environmental, and food safety concerns on purchase intention of genetically modified food in mediating role of perceived risk: an empirical study in Thailand. World Food Policy. 2020;6:23-41.
[8] Dale PJ, Clarke B, Fontes EMG. Potential for the environmental impact of transgenic crops. Nat Biotechnol. 2002;20:567-574.
[9] Stewart CN Jr, Halfhill MD, Warwick SI. Transgene introgression from genetically modified crops to their wild relatives. Nature Rev Genet. 2003;4:806-817.
[10] Poppy GM. Gene flow from GM plants-towards a more quantitative risk assessment. Trends Biotechnol. 2004;22:436-438.
[11] Warwick SI, Légère A, Simard MJ, James T. Do escaped transgenes persist in nature? The case of an herbicide resistance transgene in a weedy Brassica rapa population. Mol Ecol. 2008;17:1387-1395.
[12] Ellstrand NC, Meirmans P, Rong J, Bartsch D, Ghosh A, de Jong TJ, et al. Introgression of crop alleles into wild or weedy populations. Annu Rev Ecol Evol Syst. 2013;44:325-345.
[13] Cruz-Reyes R, Ávira-Sakar G, Sánchez-Montoya G, Quesada M. Experimental assessment of gene flow between transgenic squash and a wild relative in the center of origin of cucurbits. Ecospere. 2015;6(12): 1-13.
[14] Vaughan DA, Balázs E, Heslop-Harrison JS. From crop domestication to super-domestication. Ann Bot. 2007;100(5):893-901.
[15] Chen YH, Gols R, Benrey B. Crop domestication and its impact on naturally selected trophic interactions. Annu Rev Entomol. 2015;60:35-58.
[16] Govindaraj M, Vetriventhan M, Srinivasan M. Importance of genetic diversity assessment in crop plant and its recent advance: an overview of the analytical perspective. Genet Res Int. 2015;2015:1-14.
[17] Chávez-Pesqueira M, Núñez-Farfán J. Domestication and genetics of papaya: a review. Front Ecol Evol. 2017;5:155.
[18] Kuroda Y, Kaga A, Tomooka N, Vaughan DA. Population genetic structure of Japanese wild soybean (Glycine soja) based on microsatellite variation. Mol Ecol. 2006;15:959-974.
[19] Scarcelli N, Tostain S, Vigouroux Y, Agbangla C, Daïnou O, Pham JL. Farmers’ use of wild relative and sexual reproduction in a vegetatively propagated crop. The case of yam in Benin. Mol Ecol. 2006;15: 2421-2431.
[20] Duputié A, David P, Debain C, Mckey D. Natural hybridization between a clonally propagated crop, cassava (Manihot esculenta Crantz) and a wild relative in French Guiana. Mol Ecol. 2007;16:3025-3038.
[21] Brown JE, Bauman JM, Lawrie JF, Rocha OJ, Moore RC. The Structure of morphological and genetic diversity in natural populations of Carica papaya (Caricaceae) in Costa Rica. Biotropica. 2012;44:179-188.
[22] Aizawa M, Yoshimaru H, Takahashi M, Kawahara T, Sugita H, Saito H, et al. Genetic structure of Sakhalin spruce (Picae glehnii) in northern Japan and adjacent regions revealed by nuclear microsatellites and mitochondrial gene sequences. J Plant Res. 2015;128:91-102.
[23] Pérez JO, Dambier D, Ollitrault P, Deeckenbrugg GP, Brottier P, Froelicher Y, et al. Microsatellite markers in Carica papaya L.: isolation, characterization and transferability to Vasconcellea species. Mol Ecol Notes. 2006;6(1):212-217.
[24] Aketarawong N, Bonizzoni M, Malacrida AR, Gasperi G, Thanaphum S. Seventeen novel microsatellite markers from an enriched library of the pest species Bactrocera dorsalis sensu stricto. Mol Ecol Notes. 2006;6:1138-1140.
[25] Aketarawong N, Isasawin S, Thanaphum S. Evidence of weak genetic structure and recent gene flow between Bactrocera dorsalis s.s. and B. papayae, across Southern Thailand and West Malaysia, supporting a single target pest for SIT applications. BMC Genetics. 2014;15:70.
[26] Antao T, Lopes A, Lopes RJ, Beja-Pereira A, Luikart G. LOSITAN: a workbench to detect molecular adaptation based on a Fst-outlier method. BMC Bioinformatics. 2008;9:323.
[27] Foll M, Gaggiotti O. Agenome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics. 2008;180(2):977-993.
[28] Foll M. BayeScan v2. 1 user manual. Ecology. 2012;20:1450-1462.
[29] Nayfa MG, Zenger KR. Unravelling the effects of gene flow and selection in highly connected populations of the silver-lip pearl oyster (Pinctada maxima). Mar Genomics. 2016;28:99-106.
[30] Paekall R, Smouse PE. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics. 2012;28(19):2537-2539.
[31] Weir BS. Genetic data analysis II: methods for discrete population genetic data. Sunderland: Sinauer Associates, Inc.; 1996.
[32] Brookfield JFY. A simple new method for estimating null allele frequency from heterozygote deficiency. Mol Ecol. 1996;5:453-455.
[33] Rice WR. Analysis tables of statistical tests. Evolution. 1989;43(1):223-225.
[34] Raymond M, Rousset F. Genepop (version 1.2): population genetics software for exact tests and ecumenicism. J Hered. 1995;86:248-249.
[35] Weir BS, Cockerham CC. Estimating F-statistics for the analysis of population structure. Evolution. 1984;38:1358-1370.
[36] Dieringer D, Schlötterer C. MICROSATELLITE ANALYSER (MSA)-a platform independent analysis tool for large microsatellite data sets. Mol Ecol Notes. 2003;3:167-111.
[37] Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotypic data. Genetics. 2000;155:945-959.
[38] Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol. 2005;14:74-75.
[39] Excoffier L, Lischer HE. Arlequin suie ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour. 2010;10(3):564-567.
[40] Piry S, Alapetite A, Cornuet JM, Paetkau D, Baudouin L, Estoup A. GeneClass2: A software for genetic assignment and first-generation migrant detection. J Hered. 2004;95:536-539.
[41] Rannala B, Mountain JL. Detecting immigration by using multilocus genotypes. Proc Natl Acad Sci USA. 1997;94:9197-9221.
[42] Paetkau D, Slade R, Burden M, Estoup A. Genetic assignment methods for the direct, real time estimation of migration rate: a simulation-based exploration of accuracy and power. Mol Ecol. 2004; 13:55-65.
[43] Mutegi E, Snow AA, Rajkumar M, Pasquet R, Ponniah H, Daunay M, et al. Genetic diversity and population structure of wild/weedy eggplant (Solunum insanum, Solananceae) in Southern India: implications for conservation. Am J Bot. 2015;102(1):140-148.
[44] Matos ELS, Oliveira EJ, Jesus ON, Dantas JLL. Microsatellite markers of genetic diversity and population structure of Carica papaya. Ann Appl Biol. 2013;163:298-310.
[45] Niklas KJ, Marler TE. Carica papaya (Caricaceae): a case study into the effects of domestication on plant vegetative growth and reproduction. Am J Bot. 2007;94:999-1002.
[46] Celis C, Scurrah M, Cowgill S, Chumbiauca S, Green J, Franco J. et al. Environmental biosafety and transgenic potato in a center of diversity for this crop. Nature. 2004;432:222-225.