Open access peer-reviewed chapter

Perspective Chapter: Molecular Approach for the Study of Genetic Diversity and Conservation Prioritization of Fish Population

Written By

Shahnawaz Ali and Chinnathangam Siva

Submitted: 11 December 2021 Reviewed: 14 December 2021 Published: 25 August 2022

DOI: 10.5772/intechopen.102018

From the Edited Volume

Population Genetics

Edited by Rafael Trindade Maia and Magnólia Campos de Araújo

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Abstract

Fishes are the most abundant vertebrates in the animal kingdom. They play important biological and ecological roles. Various anthropogenic and climatic factors have led to the decline of natural population and increased the risk of extinction. CBD emphasized the conservation of biodiversity at all levels from genes to ecosystems. However, little attention paid to genetic considerations in restoration efforts. Estimation of genetic diversity and population structure is inevitable for effective implementation of conservation management program. Available DNA markers like mitochondrial and microsatellite markers provide useful insight into understanding the genetic diversity status of fish population in the wild. The present chapter highlights the importance of genetic diversity and its determinants. Utility of mitochondrial and microsatellite markers shown through a case study of a threatened cyprinid species Neolissochilus hexagonolepis known as chocolate mahseer that is widely distributed in the North-eastern part of India. Presence of low genetic diversity confirmed its threatened status and further analysis based on various genetic parameters revealed the status of different stocks as well as the population structure of this species. The results obtained could be helpful in rehabilitation and conservation planning and prioritization for the maintenance of a viable population of this species.

Keywords

  • biodiversity
  • conservation
  • population genetics
  • molecular markers
  • phylogeography

1. Introduction

Fishes are cold-blooded aquatic vertebrates, and over half of the living vertebrates are fishes. The estimated total number of fishes is more than 35,934 species, and it is higher than the combined total of other vertebrates [1]. Among all known fish species, more than 15,000 are found in freshwater, which is less than 0.3% of available global water, while more than 16,000 species are marine, which is 70% of the earth’s surface [2]. The incredible diversity of fishes is astounding that is evident from their morphology, the habitat they occupy, their physiological adaptation, and behavior [3]. They have a long evolutionary history of origin and diversification that began in the Cambrian Period at least 520 million years ago [4]. They occupy all types of the aquatic environment, and to survive and colonize in different habitats, fishes have developed various types of anatomical, physiological, behavioral, and ecological adaptation and plays different types of biological and ecological roles [5]. Fishes are also critically important for the food security and nutrition of ever-increasing human population, and more than 4.5 billion people get at least 15% of their average per capita intake of animal protein from fish. They have unique nutritional properties and are one of the efficient feed converters into high quality food therefore, widely exploited from natural water bodies as well as produced through aquaculture production systems [6].

However, due to various anthropogenic and climatic factors, fish stocks both in marine as well as freshwater are continuously declining and are under severe threats. The unfulfilled demand for resources has resulted in cumulative pressure on the marine ecosystem from a range of human activities. As a result, both marine species and habitat are experiencing detrimental impacts due to different human interference [7, 8]. It is estimated that humans have impacted almost 90% of the global ocean surface [9], and marine fish abundances have declined by 38% in last three decades [10]. Loss of coral habitats, overfishing, dredging activities, and damage caused by bottom trawling all have led to the significant decline of marine fish stocks, its recruitment, and yields, and even after continuous efforts recovery has not yet been achieved [11].

On the other side, freshwater ecosystem has been assessed as the most impacted and endangered ecosystem on the planet [12]. The decline in biodiversity is much greater in freshwater than in terrestrial and marine ecosystems [13, 14]. The major threats to global freshwater biodiversity include overexploitation; water pollution; flow modification; destruction or degradation of habitat; invasion by exotic species; infectious diseases, and the combined and interacting influences of these threats have resulted in population declines and range reduction of freshwater biodiversity worldwide [12, 15, 16]. Therefore, direct and indirect anthropogenic impacts have resulted in global decline of biodiversity [7, 17].

In addition, global climate change also poses many threats to biodiversity and alters the physical, chemical, and biological characteristics of freshwater and marine biodiversity and habitats [18, 19]. According to recent estimates, around 50% of global freshwater fish species are potentially threatened due to climate change [20]. The effects of climate change have been recorded and predicted in terms of changes in species phenology, range, and physiology [21], thus accelerating the risk of extinction [22, 23, 24]. It is increasingly recognized that the scales of different anthropogenic impacts are greater than natural drivers for the earth system and hence coined the name of a new geological epoch, the “Anthropocene” where human-induced changes dominate over natural cycles [25, 26]. The loss of global biodiversity is now comparable to previous global-scale mass extinction events, and we are now witnessing the “sixth mass extinction” event [27, 28]. It is further shown that the sixth mass extinction is more severe than perceived in terms of species extinction [29].

In its assessment, the Convention on Biological Diversity (CBD) has emphasized the conservation of biodiversity at all levels from genes, population, species, and ecosystems [30, 31]. As discussed above, the threat to freshwater biodiversity is far greater than other ecosystems, and the fish species are becoming either vulnerable or endangered, and their numbers are continuously increasing every year (Figure 1), and around 37% of freshwater fishes are threatened with the risk of extinction [20]. The loss of habitat and invasion of non-native species in major riverine systems of the world has reduced not only the species diversity but also caused similarity among species assemblages. This has led to the “taxonomic homogenization” on a regional and global scale [32]. The overall aim of conservation is to protect biological diversity and the underlying processes that sustain it in the face of perturbation caused by human activities. The strategies for conservation need prioritization that maximizes both representation and persistence of diversity [33]. It is known that all organisms are endowed with a genetic blueprint and thus contribute to genetic diversity, which is the foundation of all biological diversity. Earlier works demonstrated that loss of genetic diversity might lead to the collapse of population and even species that are present in the wild [34, 35]. While comparing threatened and non-threatened taxa, it was revealed that the genetic factors such as heterozygosities reduced to a considerable level in the threatened taxa before a species driven to the risk of extinction [36]. Although CBD agreed on the conservation of genetic diversity, little attention has been paid to genetic considerations in restoration efforts, and it remained largely neglected [37]. Therefore, it is necessary to document genetic diversity at the population and species level so that a comprehensive conservation strategy can be implemented for the rehabilitation and restoration of species.

Figure 1.

Changes in numbers of species in the threatened categories (CR: Critical; EN: Endangered; VU: Vulnerable) from 2000 to 2021 (IUCN Red List version 2021–3) for the fish species on the Red List (Accessed on November 17, 2021; https://www.iucnredlist.org/).

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2. Determinants of genetic diversity and its measurement

The vast and varied population of fishes inherit different genetic traits and thus shows remarkable genetic diversity both at spatial and temporal scales [38, 39]. The genetic composition defines the form and functionality of the organism. The presence of genetic variation in the population and species contributes to the ability to respond to environmental changes [40]. The loss of species and their distributional range are detrimental to the genetic diversity, which the species inherited and accumulated over millions of years of evolutionary processes. Thus documenting the genetic variation in populations is important to understand the forces that change their genetic composition over time, and thus their evolutionary relationship is described through the study of population genetics [41]. It is also important to understand that each individual of a species might have a similar phenotype but distinct genetic makeup. These differences arise due to the difference in their nucleotide sequences (e.g. DNA sequences) which is called “polymorphism.” Genetic diversity provides the raw material for the survival, evolution, and natural selection of the organism [42]. One of the important phenomenons, which contribute towards the genetic variation among individuals at species or population level, is “mutation.” In other words, it is a base pair substitution in the DNA sequences (either coding or non-coding region) during the replication, and this is an essential requirement for the evolution [41]. Mutation in non-coding sequences evolves faster than coding sequences since it does not directly affect the gene functions. Thus these genetic variants or “alleles” appear or added at each generation due to random mutation or may disappear due to loss of alleles under the influence of “genetic drift” (i.e., a random change in gene frequencies). The other important evolutionary force responsible for high genetic variation is the “Natural selection” that can change gene frequencies in the population and leads toward the relative fitness in the population. However, for natural selection to affect the allele frequency, the locus must be in the coding region [43]. In contrast to this, “Neutral Theory of Molecular Evolution” proposed by “Kimura” [44] argues that most allelic variations and substitutions in proteins and DNA are neutral. According to this theory, gene frequencies may change by “genetic drift” without the influence of natural selection, and in a large panmictic population (i.e., where species show random mating within a population), and it is inversely proportional to the effective population size [45].

The detection and measurements of genetic diversity and population structure are essentially required for the development of the appropriate strategies for the implementation of conservation programs [46, 47]. Furthermore, molecular phylogenetics and genetic diversity analysis help in ascertaining the taxonomic identity and evolutionary relationship of the wild species. There are certain population genetic parameters that are measured for the evaluation of genetic variability at individual and population levels. These measures are essential for the comprehensive assessment of genetic structure within and among the population. Among such important population genetic parameters are the percentage of polymorphic loci; the number of alleles per locus; the effective number of alleles per locus; observed and expected heterozygosity; estimates of effective population size; and assessment of linkage disequilibrium. Further, for estimating variations between population it is essentially required to measure different types of variances (Fst, GST, RST), genetic distances, and correlation between genetic distance and geographic distance [43, 48]. These population genetic parameters provide important data to draw any plausible conclusion about the status of the stock and its genetic structure.

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3. Application of molecular technology and fisheries genetics

The advent of molecular techniques in the last seven decades has provided significant insights into the population structure and its genetic diversity. Initially, the technique of protein gel electrophoresis to several allozyme loci was applied to measure the genetic variation in the species [49] and assessment of the fish genetic stock. The use of allozyme remained a dominant method until the development of DNA amplification using the PCR (Polymerase Chain Reaction) technique [50]. The arrival of PCR-based techniques revolutionized the field of molecular genetics and led to the emergence of fish genomics by the use of DNA-based markers technology. A genetic or molecular marker is a gene or DNA sequence with a known location on a chromosome and associated with a particular gene or trait. The popular genetic markers widely used for genetic diversity assessment include allozymes, mitochondrial DNA, RFLP, RAPD, AFLP, microsatellite, SNP, and EST markers. Genetic markers have been applied to three areas of fisheries in particular; stock structure analysis, aquaculture, and taxonomy/systematics [51] with varying degrees of success [52].

Among the different available DNA markers, mitochondrial DNA (mtDNA) has been widely and effectively used for the assessment of population structure and phylogenetic study [53, 54]. Mitochondrial DNA (mtDNA), as the name suggests, is contained in the mitochondria of the cell and is generally maternally inherited. The general features of mitochondrial DNA include predominantly female inheritance, lack of recombination, selectively neutral, high rate of evolution, relatively simple structure, and multiple copies in the cell [55, 56]. Therefore, different mtDNA gene sequences have proved to be a good marker for analyzing variation at interspecific and intraspecific levels in fishes. Mitochondrial DNA marker (mtDNA) is widely used to study the gene flow, hybrid zones, population structure, phylogenetics, phylogeography, molecular evolution, and conservation genetics [57]. Another type of marker, which is known as satellite DNA is increasingly used for the investigation of genetic variability and divergence between the species [58]. Microsatellite, also known as Simple Sequence Repeats (SSRs), has widely been utilized for studies in population genetics, evolutionary and conservation biology of species and therefore considered as the most significant genetic marker [59]. A microsatellite is tandem repeated motifs of 1–6 bases found in all prokaryotic and eukaryotic genomes. They are present in both coding and non-coding regions and are usually characterized by a high degree of length polymorphism. Further, microsatellites featured with co-dominant inheritance, inheritance in a mendelian fashion, wide distribution, high stability, and repeatability signify their usage for the assessment of genetic diversity within and between populations and provide significant genetic information [60]. Hence, species-specific microsatellite markers are extensively developed and studied in different fish populations [61, 62].

Recently, with the advent of next-generation sequencing (NGS) platforms, the SSR markers in the non-model organism can be developed rapidly and efficiently compared to the conventional methods [63, 64]. The random sequencing based approach also facilitates the genotyping of a high number of loci at moderate costs [65]. Among the different NGS platforms available, the Illumina sequencing method is a powerful tool for the discovery of SSRs and delivers the highest yield of error-free data for the most sensitive or complex sequencing samples [66].

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4. Conservation prioritization of fish population: a case study

The use of molecular markers based technology has immensely contributed to different aspects of conservation genetics of species, such as resolving the taxonomic ambiguity; designing captive and marker assisted breeding programs; detecting diversity within and among geographical populations; estimating gene flow, and understanding the factors contributing to fitness [67]. Therefore, management of the species must include information on the extent and organization of genetic diversity in populations to suggest sustainable conservation strategies. This becomes more relevant when we are dealing with endangered species [46]. The fundamental aim of the conservation of species is to minimize genetic deterioration of endangered stock and maintain a viable population to avoid the bottleneck and risk of extinction. The parameters such as genetic divergence among populations and gene flow rate are helpful in characterizing populations, species, and subspecies in different conservation units [68]. Here we have briefly discussed the use of mitochondrial and microsatellite markers in conservation prioritization of a threatened cyprinid species Neolissochilus hexagonolepis known as chocolate mahseer that is widely distributed in the north-eastern part of India.

Mahseer is the common name used for three carp genera, viz. Tor, Neolissochilus, and Naziritor (family Cyprinidae). N. hexagonolepis has been widely reported from southeast Asia and is abundantly available in the Brahmaputra river basin of Northeast India [69]. The species is enjoyed as food as well as sports fish and also identified as a candidate species for aquaculture [70]. However, the natural population is rapidly declining due to various anthropogenic reasons such as degradation of natural habitat, hydro development projects, and angling demands of the species and therefore categorized as threatened species by IUCN [71, 72]. For the implementation of any effective conservation program it is inevitable to obtain basic genetic information of this species. Therefore, we used mitochondrial and microsatellite DNA markers to study the genetic structure, population history, and genetic diversity of geographically isolated populations of the N. hexagonolepis from Northeast India. The information provided to identify genetically diverse stocks as well as delineation of conservation units that can be utilized to optimize the conservation of the chocolate mahseer.

In the experimental setup, 200 fish samples were collected from different geographically isolated drainages from Northeast India. First, we evaluated the targeted genetic parameters using three mitochondrial markers, namely ATPase6/8, cytochrome oxidase I (CO-I) and cytochrome b (Cytb). For amplification of these mitochondrial genes, total genomic DNA from fin samples was used and amplified using standard primer pairs designed from the whole mitochondrial genome sequence. Further, PCR products were column purified and sequenced in both directions using an ABI 3130 Genetic Analyzer (Applied Biosystem, Carlsbad, CA) with Big Dye Terminator cycle sequencing kit v.3.1 with the help of the same primers used for amplification of the target genes. Robust statistical analysis was performed using suitable computer programs to estimate the population genetic parameter, mainly polymorphic sites (S), haplotype diversity (Hd), nucleotide diversity (p), and haplotype number. Molecular variance (AMOVA), molecular diversity indices, and genetic differentiation (FST) were also calculated. Moreover, the phylogenetic relationship among individuals of different populations was constructed by implementing the maximum likelihood tree method (MLM) based on the best-predicted model [73]. Mean genetic distances between the populations for all the three genes were also calculated. Geographical distances were simulated with haplotypes to determine the optimal number of population groups (K = 2–8). Possible correlation between pairwise genetic differentiation and geographical distances among nine populations was estimated by applying the Mantel test [74].

The analysis revealed the genetic diversity status of different populations based on their haplotype and nucleotide diversity pattern. In comparison, some populations has undergone a reduction in size or recent colonization events whereas, other populations showed a high level of divergence between haplotypes, indicating a long historical evolutionary pattern [75]. Analysis of molecular variance revealed a high level of genetic structuring among populations. Five major groups and one paraphyletic intermediate group were obtained by phylogenetic analysis. Overall results indicated a positive correlation between geographical distances and genetic divergence [76]. The analysis of different genetic parameters clearly indicated that most of the variation in genetic differentiation is present among population groups, and genetic variations in the chocolate mahseer population might be due to specific habitat conditions that influence population genetic structure. Further, the study also confirmed the threatened status of the population being low in genetic diversity. Thus, information generated by the study would be helpful for developing stock-specific strategies for N. hexagonolepis breeding, conservation, and management.

Further, microsatellite markers were developed, and population genetics, evolutionary, and conservation biology of N. hexagonolepis were studied. Here we used NGS technology (Illumina Miseq) to develop 25 novel SSR markers and further used these markers for assessing the genetic diversity and population structure of this species from Northeast India. Different population genetic parameters such as a number of polymorphic loci, numbers of alleles per locus, observed and expected heterozygosity, and pairwise genetic diversity were estimated using available computer programs. Population structure and bottleneck were estimated as well as migration pattern was studied using appropriate statistical methods.

In N. hexagonolepis we found tetra-nucleotides as the most frequent microsatellite motifs that were opposed to what is observed for other cyprinids where di-nucleotide is the most abundant [77]. All the loci were highly polymorphic and thus used for the analysis. In certain population, observed heterozygosity was lower than expected heterozygosity (He) which indicated the inbreeding effect within the populations [78]. Analysis of molecular variance (AMOVA) and high Fst indicated relatively low gene flow among the population. Migration analysis also revealed that there is no active migration among the studied populations of N. hexagonolepis. The STRUCTURE analysis identified five subgroups that substantiate the result of cluster analysis and factorial correspondence analysis (FCA). Based on the estimation of different genetic parameters through statistical analysis, we could successfully identify the genetic status of different stocks as well as the population structure of this species [79]. The identified major groups can be considered as different conservation units when applying any management measures. Thus both the markers were extremely useful in genetic stock assessment of the species under study and provided critical information regarding conservation prioritization.

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5. Conclusion

Although freshwater ecosystems is under severe threat due to various anthropogenic and climatic factors, little attention and effort have been paid towards its conservation. Identification of fish stock structure and assessment of their genetic diversity should be an important component of any conservation planning. Available molecular tools are quite useful for the estimation of species diversity at individual to population levels. Further, it becomes more important when we deal with species of endangered categories. The present study clearly indicated that the use of mitochondrial and microsatellite markers has provided a great deal of information related to the fish population under study. We could develop novel microsatellite markers, which will be further useful for stock characterization as well as any marker-assisted breeding program in aquaculture. Apart from these, molecular techniques are commonly used as bio-monitoring tools for assessing the genetic diversity status of the species that help in rehabilitation and conservation planning and prioritization for the maintenance of a sustainable ecosystem.

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Acknowledgments

The authors acknowledge the financial assistance provided by Indian Council of Agricultural Research (ICAR) New Delhi, India for carrying out this research work under the project “Fish Genetic Stock—An outreach activity”. The authors express thanks to Director, ICAR-Directorate of Coldwater Fisheries Research, Bhimtal, India for providing all necessary support.

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Conflict of interest

The authors declare no conflict of interest.

References

  1. 1. IUCN. Red List (version 2021-3) for the Fish Species on the Red List. 2021. Available from: https://www.iucnredlist.org/ [Accessed: November 17, 2021]
  2. 2. Levêque C, Oberdorff T, PAUGy D, MLJ S, Tedesco PA. Global diversity of fish (Pisces) in freshwater. Hydrobiologia. 2008;595:545-567. DOI: 10.1007/s10750-007-9034-0
  3. 3. Nelson JS, Grande TC, Wilson MV. Fishes of the World. Hoboken, New Jersey: John Wiley & Sons; 2016
  4. 4. Long J, Choo B, Clement A. The evolution of fishes through geological time. In: Johanson Z, Underwood C, Richter M, editors. Evolution and Development of Fishes. Cambridge: Cambridge University Press; 2019. pp. 3-29. DOI: 10.1017/9781316832172.002
  5. 5. Helfman G, Collette BB, Facey DE, Bowen BW. The Diversity of Fishes: Biology, Evolution, and Ecology. Hoboken, NJ: John Wiley & Sons; 2019. p. 693
  6. 6. Béné C, Barange M, Subasinghe R, Pinstrup-Andersen P, Merino G, Hemre GI, et al. Feeding 9 billion by 2050–Putting fish back on the menu. Food Security. 2015;7(2):261-274. DOI: 10.1007/s12571-015-0427-z
  7. 7. Butchart SH, Walpole M, Collen B, Van Strien A, Scharlemann JP, Almond RE, et al. Global biodiversity: Indicators of recent declines. Science. 2010;328(5982):1164-1168. DOI: 10.1126/science.1187512
  8. 8. Halpern BS, Frazier M, Potapenko J, Casey KS, Koenig K, Longo C, et al. Spatial and temporal changes in cumulative human impacts on the world’s ocean. Nature Communication. 2015;6(1):1-7. DOI: 10.1038/ncomms8615
  9. 9. Jones KR, Klein CJ, Halpern BS, Venter O, Grantham H, Kuempel CD, et al. The location and protection status of Earth’s diminishing marine wilderness. Current Biology. 2018;28(15):2506-2512. DOI: 10.1016/j.cub.2018.06.010
  10. 10. Hutchings JA, Minto C, Ricard D, et al. Trends in the abundance of marine fishes. Canadian Journal of Fisheries and Aquatic Science. 2010;67:1205-1210. DOI: 10.1139/F10-081
  11. 11. Britten GL, Duarte CM, Worm B. Recovery of assessed global fish stocks remains uncertain. Proceedings of the National Academy of Sciences of the United States of America. 2021;118(31):e2108532118. DOI: 10.1073/pnas.2108532118
  12. 12. Dudgeon D, Arthington AH, Gessner MO, Kawabata ZI, Knowler DJ, Leveque C, et al. Freshwater biodiversity: Importance, threats, status and conservation challenges. Biological Review. 2006;81:163-182. DOI: 10.1017/S1464793105006950
  13. 13. Sala OE, Chapin FS, Armesto JJ, Berlow R, Bloomfield J, Dirzo R, et al. Global biodiversity scenarios for the year 2100. Science. 2000;287:1770-1774
  14. 14. Malmqvist B, Rundle S. Threats to the running water ecosystems of the world. Environmental Conservation. 2002;29(2):134-153. DOI: 10.1017/S0376892902000097
  15. 15. Reid AJ, Carlson AK, Creed IF, Eliason EJ, Gell PA, Johnson PT, et al. Emerging threats and persistent conservation challenges for freshwater biodiversity. Biological Reviews. 2019;94(3):849-873. DOI: 10.1111/brv.12480
  16. 16. Barbarossa V, Schmitt RJ, Huijbregts MA, Zarfl C, King H, Schipper AM. Impacts of current and future large dams on the geographic range connectivity of freshwater fish worldwide. Proceedings of the National Academy of Sciences of the United States of America. 2020;117(7):3648-3655. DOI: 10.1073/pnas.1912776117
  17. 17. Su G, Logez M, Xu J, Tao S, Villéger S, Brosse S. Human impacts on global freshwater fish biodiversity. Science. 2021;371(6531):835-838. DOI: 10.1126/science.abd3369
  18. 18. Oberdorff T, Jézéquel C, Campero M, Carvajal-Vallejos F, Cornu JF, Dias MS, et al. Opinion Paper: How vulnerable are Amazonian freshwater fishes to ongoing climate change? Journal of Applied Ichthyology. 2015;31:4-9
  19. 19. Freer JJ, Partridge JC, Tarling GA, Collins MA, Genner MJ. Predicting ecological responses in a changing ocean: The effects of future climate uncertainty. Marine Biology. 2018;165(1):1-18
  20. 20. Darwall WR, Freyhof J. Lost fishes, who is counting? The extent of the threat to freshwater fish biodiversity. In: Closs GP, Krkosek M, Olden JD, editors. Conservation of Freshwater Fishes. Cambridge: Cambridge University Press; 2015. pp. 1-35
  21. 21. Bellard C, Bertelsmeier C, Leadley P, Thuiller W, Courchamp F. Impacts of climate change on the future of biodiversity. Ecology Letters. 2012;15(4):365-377. DOI: 10.1111/j.1461-0248.2011.01736.x
  22. 22. Parmesan C, Yohe G. A globally coherent fingerprint of climate change impacts across natural systems. Nature. 2003;421(6918):37-42. DOI: 10.1038/nature01286
  23. 23. Urban MC. Accelerating extinction risk from climate change. Science. 2015;348(6234):571-573
  24. 24. Wiens JJ. Climate-related local extinctions are already widespread among plant and animal species. PLoS Biology. 2016;14(12):e2001104. DOI: 10.1371/journal.pbio.2001104
  25. 25. Crutzen PJ. Geology of mankind. Nature. 2002;415:23
  26. 26. Luypaert T, Hagan JG, McCarthy ML, Poti M. Status of marine biodiversity in the Anthropocene. In: YOUMARES 9-The Oceans: Our Research, Our Future. Cham: Springer; 2020. pp. 57-82
  27. 27. Barnosky AD, Matzke N, Tomiya S, et al. Has the Earth’s sixth mass extinction already arrived? Nature. 2011;471:51-57. DOI: 10.1038/nature09678
  28. 28. Ceballos G, Ehrlich PR, Barnosky AD, et al. Accelerated modern human-induced species losses: Entering the sixth mass extinction. Sciences Advances. 2015;1:e1400253. DOI: 10.1126/sciadv.1400253
  29. 29. Ceballos G, Ehrlich PR, Dirzo R. Biological annihilation via the ongoing sixth mass extinction signaled by vertebrate population losses and declines. Proceedings of the National Academy of Sciences of the United States of America. 2017;114(30):E6089-E6096. DOI: 10.1073/pnas.1704949114
  30. 30. Convention on Biological Diversity. Framework for monitoring implementation of the achievement of the 2010 target and integration of targets into the thematic programmes of work, COP 8 Decision VIII/15. 2006. Available from: www.cbd.int/decisions
  31. 31. Walpole M, Almond RE, Besançon C, Butchart SH, Campbell-Lendrum D, Carr GM, et al. Tracking progress toward the 2010 biodiversity target and beyond. Science. 2009;325(5947):1503-1504
  32. 32. Villéger S, Blanchet S, Beauchard O, Oberdorff T, Brosse S. Homogenization patterns of the world’s freshwater fish faunas. Proceedings of the National Academy of Sciences of the United States of America. 2011;108(44):18003-18008
  33. 33. Moritz C. Strategies to protect biological diversity and the evolutionary processes that sustain it. Systematic Biology. 2002;51(2):238-254. DOI: 10.1080/10635150252899752
  34. 34. Briskie JV, Mackintosh M. Hatching failure increases with severity of population bottlenecks in birds. Proceedings of the National Academy of Science of the United States of America. 2004;101:558-561
  35. 35. Frankham R. Genetics and extinction. Biological Conservation. 2005;126:131-140
  36. 36. Spielman D, Brook BW, Frankham R. Most species are not driven to extinction before genetic factors impact them. Proceedings of the National Academy of Sciences of the United States of America. 2004;101(42):15261-15264
  37. 37. Laikre L, Allendorf FW, Aroner LC, Baker CS, Gregovich DP, et al. Neglect of genetic diversity in implementation of the convention on biological diversity. Conservation Biology. 2010;24(1):86-88
  38. 38. Riccioni G, Landi M, Ferrara G, Milano I, Cariani A, Zane L, et al. Spatio-temporal population structuring and genetic diversity retention in depleted Atlantic bluefin tuna of the Mediterranean Sea. Proceedings of the National Academy of Sciences of the United States of America. 2010;107(5):2102-2107. DOI: 10.1073/pnas.0908281107
  39. 39. Palstra FP, Ruzzante DE. A temporal perspective on population structure and gene flow in Atlantic salmon (Salmo salar) in Newfoundland, Canada. Canadian Journal of Fisheries and Aquatic Sciences. 2010;67(2):225-242
  40. 40. Hughes AR, Inouye BD, Johnson MT, Underwood N, Vellend M. Ecological consequences of genetic diversity. Ecology Letters. 2008;11(6):609-623. DOI: 10.1111/j.1461-0248.2008.01179.x
  41. 41. Burden CJ. Population genetics. In: Ranganathan S, Gribskov M, Nakai K, Schönbach C, editors. Encyclopedia of Bioinformatics and Computational Biology. Vol. 2. Amsterdam: Elsevier; 2019. pp. 759-788. DOI: 10.1016/B978-0-12-809633-8.90693-9
  42. 42. Fisher RA. The Genetical Theory of Natural Selection. Oxford, United Kingdom: Clarendon Press; 1930. DOI: 10.5962/bhl.title.27468
  43. 43. Gillespie JH. Population Genetics: A Concise Guide. Baltimore and London: The Johns Hopkins University Press; 2004
  44. 44. Kimura M. The Neutral Theory of Molecular Evolution. Cambridge: Cambridge University Press; 1983
  45. 45. Ellegren H, Galtier N. Determinants of genetic diversity. Nature Reviews Genetics. 2016;17(7):422-433
  46. 46. Meffe GK. Conservation genetics and the management of endangered fishes. Fisheries. 1986;11(1):14-23
  47. 47. Milligan BG, Leebens-Mack J, Strand AE. Conservation genetics: Beyond the maintenance of marker diversity. Molecular Ecology. 1994;3:423-435
  48. 48. Höglund J. Evolutionary Conservation Genetics. Oxford: Oxford University Press; 2009
  49. 49. Lewontin RC, Hubby JL. A molecular approach to the study of genetic heterozygosity in natural populations. II. Amount of variation and degree of heterozygosity in natural populations of Drosophila pseudoobscura. Genetics. 1966;54:595-609
  50. 50. Ferguson A, Taggart JB, Prodohl PA, McMeel O, Thompson C, Stone C, et al. The application of molecular markers to the study and conservation of fish populations, with special reference to Salmo. Journal of Fish Biology. 1995;47:103-126
  51. 51. Ward RD, Grewe M. Appraisal of molecular genetic techniques in fisheries. In: Carvalho GR, Pitcher TJ, editors. Molecular Genetics in Fisheries. London: Chapman & hall; 1994. pp. 29-54
  52. 52. Liu ZJ, Cordes JF. DNA marker technologies and their applications in aquaculture genetics. Aquaculture. 2004;238(1-4):1-37
  53. 53. Barat A, Ali S, Sati J, Sivaraman GK. Phylogenetic analysis of fishes of the subfamily Schizothoracinae (Teleostei: Cyprinidae) from Indian Himalayas using cytochrome b gene. Indian Journal of Fish. 2012;59:43-47
  54. 54. Zheng LP, Yang JX. Genetic diversity and population structure of Acrossocheilus yunnanensis (Teleostei, Cyprinidae) inferred from four mitochondrial gene sequences. Mitochondrial DNA Part A. 2018;29(4):606-614
  55. 55. Avise JC. Molecular Markers, Natural History and Evolution. New York: Chapman & Hall; 1994. DOI: 10.1007/978-1-4615-2381-9
  56. 56. Birky CW, Fuerst P, Maruyama T. Organelle gene diversity under migration, mutation, and drift equilibrium expectations, approach to equilibrium, effects of heteroplasmic cells, and comparison to nuclear genes. Genetics. 1989;121:613-627
  57. 57. Rosetti N, Remis MI. Spatial genetic structure and mitochondrial DNA phylogeography of Argentinean populations of the grasshopper Dichroplus elongatus. PLoS ONE. 2012;7(7):e40807
  58. 58. Tautz D. Hypervariability of simple sequences as a general source for polymorphic DNA markers. Nucleic Acids Research. 1989;17:6463-6471
  59. 59. Baillie SM, Muir AM, Scribner K, Bentzen P, Krueger CC. Loss of genetic diversity and reduction of genetic distance among lake trout Salvelinus namaycush ecomorphs, Lake Superior 1959 to 2013. Journal of Great Lakes Research. 2016;42(2):204-216
  60. 60. Chistiakov DA, Hellemans B, Volckaert FAM. Microsatellites and their genomic distribution, evolution, function and applications: A review with special reference to fish genetics. Aquaculture. 2006;255:1-29
  61. 61. Zheng X, Kuang Y, Lü W. Transcriptome-derived EST–SSR markers and their correlations with growth traits in crucian carp Carassius auratus. Fisheries Science. 2014;80(5):977-984
  62. 62. Ariede RB, Freitas MV, Hata ME, Matrochirico-Filho VA, Utsunomia R, Mendonça FF, et al. Development of microsatellite markers using next-generation sequencing for the fish Colossoma macropomum. Molecular Biology Reports. 2018;45(1):9-18
  63. 63. Ekblom R, Galindo J. Applications of next generation sequencing in molecular ecology of non-model organisms. Heredity. 2011;107:1-15. DOI: 10.1038/hdy.2010.152
  64. 64. Heras S, Planella L, Caldarazzo I, Vera M, García-Marín J, Roldán MI. Development and characterization of novel microsatellite markers by Next Generation Sequencing for the blue and red shrimp Aristeus antennatus. Peer J. 2016;4:e2200. DOI: 10.7717/peerj.2200
  65. 65. Guichoux E, Lagache L, Wagner S, Chaumeil P, Léger P, Lepais O, et al. Current trends in microsatellite genotyping. Molecular Ecology Resources. 2011;11:591-611. DOI: 10.1111/j.1755-0998.2011.03014.x
  66. 66. Ergüner B, Ustek D, Sagiroglu MS. Performance comparison of Next Generation sequencing platforms. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Milan, Italy: IEEE; 2015. pp. 6453-6456. DOI: 10.1109/EMBC.2015.7319870
  67. 67. Vrijenhoek RC. Conservation genetics of freshwater fish. Journal of Fish Biology. 1998;1998(53):394-412. DOI: 10.1111/j.1095-8649.1998.tb01039.x
  68. 68. Moritz C. Defining ‘Evolutionarily Significant Units’ for conservation. Trends in Ecology and Evolution. 1994;9:373-375
  69. 69. Laskar BA, Bhattacharjee MJ, Dhar B, Mahadani P, Kundu S, Ghosh SK. The species dilemma of northeast Indian mahseer (Actinopterygii: Cyprinidae): DNA barcoding in clarifying the riddle. PloS One. 2013;8(1):e53704. DOI: 10.1371/journal.pone.0053704
  70. 70. Sarma D, Akhtar MS, Das P, Ganesh G, Ciji A, Mahanta PC. Observations on larval development of chocolate mahseer (Neolissochilus hexagonolepis) (McClelland, 1839). Indian Journal of Fisheries. 2015;62(1):135-138
  71. 71. Mahapatra BK, Vinod K, Mandal BK. Studies on chocolate mahseer, Neolissocheilus hexagonolepis (McClelland) fishery and the cause of its decline in Umiam reservoir, Meghalaya. Journal of Natcon. 2004;16(1):199-205
  72. 72. Abbasi T, Abbasi SA. Small hydro and the environmental implications of its extensive utilization. Renewable and Sustainable Energy Reviews. 2011;15(4):2134-2143
  73. 73. Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0. Molecular Biology and Evolution. 2013;30:2725-2729
  74. 74. Excoffier L, Laval G, Schneider S. Arlequin (version 3.0): An integrated software package for population genetics data analysis. Evolutionary Bioinformatics. 2005;1:47-50
  75. 75. Grant WAS, Bowen BW. Shallow population histories in deep evolutionary lineages of marine fishes: Insights from sardines and anchovies and lessons for conservation. Journal of Heredity. 1998;89(5):415-426. DOI: 10.1093/jhered/89.5.415
  76. 76. Sharma L, Ali S, Barat A, Kumar R, Pande V, Laskar MA, et al. Molecular identification and genetic diversity analysis of Chocolate mahseer (Neolissochilus hexagonolepis) populations of Northeast India, using mitochondrial DNA markers. Mitochondrial DNA Part A. 2019;30(3):397-406. DOI: 10.1080/24701394.2018.1526929
  77. 77. Sahu BP, Sahoo L, Joshi CG, Mohanty P, Sundaray JK, Jayasankar P, et al. Isolation and characterization of polymorphic microsatellite loci in Indian major carp, Catla catla using next generation sequencing platform. Biochemical Systematics and Ecology. 2014;57:357-362
  78. 78. Barat A, Sahoo PK, Kumar R, Mir JI, Ali S, Patiyal RS, et al. Molecular characterization of rainbow trout, Oncorhynchus mykiss (Walbaum, 1792) stocks in India. Journal of Genetics. 2015;94:13-18
  79. 79. Sharma L, Ali S, Siva C, Kumar R, Barat A, Sahoo PK, et al. Genetic diversity and population structure of the threatened chocolate mahseer (Neolissochilus hexagonolepis McClelland 1839) based on SSR markers: implications for conservation management in Northeast India. Molecular Biology Reports. 2019;46(5):5237-5249. DOI: 10.1007/s11033-019-04981-7

Written By

Shahnawaz Ali and Chinnathangam Siva

Submitted: 11 December 2021 Reviewed: 14 December 2021 Published: 25 August 2022