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Assessment of genetic diversity among wild and captive-bred Labeo rohita through microsatellite markers and mitochondrial DNA

  • Muhammad Noorullah (Fisheries & Aquaculture Program, Department of Zoology, Faculty of Biological Sciences, Quaid-i-Azam University Islamabad) ;
  • Amina Zuberi (Fisheries & Aquaculture Program, Department of Zoology, Faculty of Biological Sciences, Quaid-i-Azam University Islamabad) ;
  • Muhib Zaman (Fisheries & Aquaculture Program, Department of Zoology, Faculty of Biological Sciences, Quaid-i-Azam University Islamabad) ;
  • Waqar Younas (Fisheries & Aquaculture Program, Department of Zoology, Faculty of Biological Sciences, Quaid-i-Azam University Islamabad) ;
  • Sadam Hussain (Carp Hatchery and Training Center) ;
  • Muhammad Kamran (Aquaculture Laboratory, Department of Zoology, University of Sialkot)
  • Received : 2023.04.06
  • Accepted : 2023.10.17
  • Published : 2023.12.31

Abstract

Genetic diversity serves as the basis for selecting and genetically enhancing any culturable species in aquaculture. Here, two different strains of wild (River Ravi and River Kabul) and six captive-bred strains of Labeo rohita from various provinces were se- lected, and genetic diversity among them was evaluated using three different microsatellite markers, i.e., Lr-28, Lr-29, and Lr-37, and one mitochondrial CO1 (Cytochrome c oxidase subunit 1) gene. Different strains of L. rohita were collected, and part of their caudal fin was cut and preserved in ethanol for DNA extraction and determination of genetic diversity among them. Results in- dicated that selected markers were polymorphic with polymorphic information content (PIC) content values above 0.5 with the highest in Lr-28 followed by Lr-29 and then Lr-37. The observed heterozygosity (Ho) of all strains was higher (Avg: 0.731) but less than the expected heterozygosity (He). Moreover, TMs and WRs showed the highest He, while TKs showed the lowest, He. Over- all, inbreeding coefficient (FIS) values observed for all strains with selected markers were positive. The DNA barcoding with the CO1 gene revealed genetic variation among various strains, as demonstrated by the clades in the phylogenetic tree separating the strains into two distinct clusters that then divided into sub-clusters. In conclusion, TMs showed the highest heterozygosity as compared to other strains. Overall results provide the baseline data for the initiation of the genetic improvement program.

Keywords

Acknowledgement

The staff at various hatcheries and training centers have contributed significantly to this study, and the authors would like to acknowledge their efforts. These include the Tawakkal hatchery in district Muzaffargarh, Mianchannu fish hatchery in district Khanewal, Punjab; the Upper Sindh hatchery in the Fisheries Department of the Government of Sindh; Carp hatchery and training center in Peshawar, Tanda fish hatchery in Kohat, and Charbanda fish hatchery in Mardan, KPK.

References

  1. Ahammad AKS, Hasan NA, Bashar A, Haque MM, Abualreesh MH, Islam MM, et al. Diallel cross application and histomolecular characterization: an attempt to develop reference stock of Labeo ariza. Biology. 2022;11:691.
  2. Ahmad M, Zuberi A, Ali M, Sherzada S, Noorullah M. Identification and determination of phylogenetic relationship among Labeo rohita, Labeo catla and their reciprocal hybrids by traditional and molecular tools. Aquac Res. 2022;53:2686-96. https://doi.org/10.1111/are.15784
  3. Alam MS, Jahan M, Hossain MM, Islam MS. Population genetic structure of three major river populations of rohu, Labeo rohita (Cyprinidae: Cypriniformes) using microsatellite DNA markers. Genes Genom. 2009;31:43-51. https://doi.org/10.1007/BF03191137
  4. Allendorf FW, Utter FM. Population genetics. Fish Physiol. 1979;8:407-54. https://doi.org/10.1016/S1546-5098(08)60031-X
  5. Chauhan T, Rajiv K. Molecular markers and their applications in fisheries and aquaculture. Adv Biosci Biotechnol. 2010;1:281-91. https://doi.org/10.4236/abb.2010.14037
  6. Costa-Urrutia P, Abud C, Secchi ER, Lessa EP. Population genetic structure and social kin associations of Franciscana dolphin, Pontoporia blainvillei. J Hered. 2012;103:92-102. https://doi.org/10.1093/jhered/esr103
  7. Figueras A, Robledo D, Corvelo A, Hermida M, Pereiro P, Rubiolo JA, et al. Whole genome sequencing of turbot (Scophthalmus maximus; Pleuronectiformes): a fish adapted to demersal life. DNA Res. 2016;23:181-92. https://doi.org/10.1093/dnares/dsw007
  8. Gandra M, Assis J, Martins MR, Abecasis D. Reduced global genetic differentiation of exploited marine fish species. Mol Biol Evol. 2021;38:1402-12. https://doi.org/10.1093/molbev/msaa299
  9. Gariboldi MC, Tunez JI, Failla M, Hevia M, Panebianco MV, Paso Viola MN, et al. Patterns of population structure at microsatellite and mitochondrial DNA markers in the franciscana dolphin (Pontoporia blainvillei). Ecol Evol. 2016;6:8764-76. https://doi.org/10.1002/ece3.2596
  10. Goudet J. FSTAT (version 1.2): a computer program to calculate F-statistics. J Hered. 1995;86:485-6. https://doi.org/10.1093/oxfordjournals.jhered.a111627
  11. Habib A. Possible economic impact on coastal fish stock resources in Bangladesh in the case of climate change [M.S. thesis]. Norway: University of Tromso; 2010.
  12. Hebert PD, Stoeckle MY, Zemlak TS, Francis CM. Identification of birds through DNA barcodes. PLoS Biol. 2004;2:e312.
  13. Hussain M, Naqqash T, Yaseen G, Amin Q, Shabir G, Babar M. Genetic diversity of rohu, Labeo rohita (Hamilton, 1822) from Chenab river and its reservoirs. J Biotechnol Res. 2021;12:177-85.
  14. Islam MS, Alam MS. Randomly amplified polymorphic DNA analysis of four different populations of the Indian major carp, Labeo rohita (Hamilton). J Appl Ichthyol. 2004;20:407-12. https://doi.org/10.1111/j.1439-0426.2004.00588.x
  15. Kamran M, Razzaq H, Noorullah M, Ahmad M, Zuberi A. Comparative analysis of genetic diversity, growth performance, disease resistance and expression of growth and immune related genes among five different stocks of Labeo rohita (Hamilton, 1822). Aquaculture. 2023;567:739277.
  16. Kamran M, Yaqub A, Malkani N, Anjum KM, Awan MN, Paknejad H. Identification and phylogenetic analysis of Channa species from riverine system of Pakistan using COI gene as a DNA barcoding marker. J Bioresour Manag. 2020;7:10.
  17. Kumar NP, Rajavel AR, Natarajan R, Jambulingam P. DNA barcodes can distinguish species of Indian mosquitoes (Diptera: Culicidae). J Med Entomol. 2007;44:1-7. https://doi.org/10.1093/jmedent/41.5.01
  18. Lie HC, Simmons LW, Rhodes G. Genetic dissimilarity, genetic diversity, and mate preferences in humans. Evol Hum Behav. 2010;31:48-58. https://doi.org/10.1016/j.evolhumbehav.2009.07.001
  19. Lu YF, Goldstein DB, Angrist M, Cavalleri G. Personalized medicine and human genetic diversity. Cold Spring Harb Perspect Med. 2014;4:a008581.
  20. Luhariya RK, Lal KK, Singh RK, Mohindra V, Punia P, Chauhan UK, et al. Genetic divergence in wild population of Labeo rohita (Hamilton, 1822) from nine Indian rivers, analyzed through MtDNA cytochrome b region. Mol Biol Rep. 2012;39:3659-65. https://doi.org/10.1007/s11033-011-1140-4
  21. Mandal A, Mohindra V, Singh RK, Punia P, Singh AK, Lal KK. Mitochondrial DNA variation in natural populations of endangered Indian Feather-Back fish, Chitala chitala. Mol Biol Rep. 2012;39:1765-75. https://doi.org/10.1007/s11033-011-0917-9
  22. Nabeela F, Azizullah A, Bibi R, Uzma S, Murad W, Shakir SK, et al. Microbial contamination of drinking water in Pakistan-a review. Environ Sci. 2014;21:13929-42. https://doi.org/10.1007/s11356-014-3348-z
  23. Nash JHE. DNAfrag, program version 3.03. Ottawa: Institute for Biological Sciences, National Research Council of Canada; 1991.
  24. Nei M. Genetic distance between populations. Am Nat. 1972;106:283-92. https://doi.org/10.1086/282771
  25. Okumus I, Ciftci Y. Fish population genetics and molecular markers: II-molecular markers and their applications in fisheries and aquaculture. Turk J Fish Aquat Sci. 2003;3:51-79.
  26. Patel A, Das P, Barat A, Meher PK, Jayasankar P. Utility of cross-species amplification of 34 rohu microsatellite loci in Labeo bata, and their transferability in six other species of the cyprinidae family. Aquac Res. 2010;41:590-3. https://doi.org/10.1111/j.1365-2109.2009.02335.x
  27. Qadeer I, Abbas K. Microsatellite markers based genetic structure of rohu (Labeo rohita) in selected riverine populations of Punjab, Pakistan. Pak J Agric Sci. 2017;54:865-72.
  28. Rahman MA, Mazid MA, Rahman MR, Khan MN, Hossain MA, Hussain MG. Effect of stocking density on survival and growth of critically endangered mahseer, Tor putitora (Hamilton), in nursery ponds. Aquaculture. 2005;249:275-84. https://doi.org/10.1016/j.aquaculture.2005.04.040
  29. Riaz R, Junaid M, Rehman MYA, Iqbal T, Khan JA, Dong Y, et al. Spatial distribution, compositional profile, sources, ecological and human health risks of legacy and emerging per- and polyfluoroalkyl substances (PFASs) in freshwater reservoirs of Punjab, Pakistan. Sci Total Environ. 2023;856:159144.
  30. Rousset F. Genepop'007: a complete re-implementation of the GENEPOP software for Windows and Linux. Mol Ecol Resour. 2008;8:103-6.  https://doi.org/10.1111/j.1471-8286.2007.01931.x
  31. Sah U, Mukhiya Y, Wagle SK. Comparative evaluation of genetically improved and farmed rohu (Labeo rohita) on growth and yield at initial stage of rearing. Int J Fish Aquat Stud. 2018;6:47-50.
  32. Serrote CML, Reiniger LRS, Silva KB, dos Santos Rabaiolli SM, Stefanel CM. Determining the polymorphism information content of a molecular marker. Gene. 2020;726:144175.
  33. Shah MS. Management improvement of hatchery and brood stocks of Indian major carps, rohu (Labeo rohita), mrigal (Cirrhinus cirrhosus) and catla (Catla catla). Bangladesh: University Grant Commission; 2004.
  34. Sharma P, Tang S, Mayer GD, Patino R. Effects of thyroid endocrine manipulation on sex-related gene expression and population sex ratios in Zebrafish. Gen Comp Endocrinol. 2016;235:38-47. https://doi.org/10.1016/j.ygcen.2016.05.028
  35. Sultana F, Abbas K, Xiaoyun Z, Abdullah S, Qadeer I, Hussnain R. Microsatellite markers reveal genetic degradation in hatchery stocks of Labeo rohita. Pak J Agric Sci. 2015;52:775-81.
  36. Thompson KG, Bergersen EP, Nehring RB, Bowden DC. Longterm effects of electrofishing on growth and body condition of brown trout and rainbow trout. N Am J Fish Manag. 1997;17:154-9. https://doi.org/10.1577/1548-8675(1997)017<0154:LTEOEO>2.3.CO;2
  37. Ullah A, Basak A, Islam MN, Alam MS. Population genetic characterization and family reconstruction in brood bank collections of the Indian major carp Labeo rohita (Cyprinidae: Cypriniformes). Springerplus. 2015;4:774.
  38. Ward RD, Zemlak TS, Innes BH, Last PR, Hebert PDN. DNA barcoding Australia's fish species. Philos Trans R Soc B Biol Sci. 2005;360:1847-57. https://doi.org/10.1098/rstb.2005.1716
  39. Wattanadilokchatkun P, Panthum T, Jaisamut K, Ahmad SF, Dokkaew S, Muangmai N, et al. Characterization of microsatellite distribution in siamese fighting fish genome to promote conservation and genetic diversity. Fishes. 2022;7:251.
  40. Yaqub A, Kamran M, Malkani N, Anjum KM, Faheem M, Iqbal M, et al. Mitochondrial COI gene based molecular identification and phylogenetic analysis in exotic fish (Oreochromis mossambicus) of Pakistan. J Anim Plant Sci. 2019;29:1501-8.
  41. Yilmaz A, Boydak E. The effects of cobalt-60 applications on yield and yield components of cotton (Gossypium barbadense L.). Pak J Biol Sci. 2006;9:2761-9. https://doi.org/10.3923/pjbs.2006.2761.2769
  42. Zhang DX, Hewitt GM. Nuclear DNA analyses in genetic studies of populations: practice, problems and prospects. Mol Ecol. 2003;12:563-84.