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Abstract

The escalating biodiversity crisis necessitates innovative and effective conservation strategies. Conservation genomics, the application of genomic tools and analyses to conservation challenges, provides a powerful framework for understanding and managing biodiversity. This review synthesizes current approaches in conservation genomics, examining the application of genomic data in assessing genetic diversity, understanding adaptation, managing populations, monitoring species, and informing conservation policy. We explore the strengths and limitations of various genomic technologies, including whole-genome sequencing and environmental DNA analysis, and discuss the challenges and future directions of this rapidly evolving field. Ultimately, conservation genomics offers a crucial pathway for safeguarding global biodiversity in the face of unprecedented environmental change.

Keywords

Conservation genomics, understanding adaptation, managing populations, monitoring species

Introduction

The Earth's biodiversity, a tapestry of life intricately woven over millions of years, is facing an unprecedented crisis. The relentless expansion of human activities, coupled with the accelerating impacts of climate change, has triggered a cascade of species extinctions and ecosystem degradation, threatening the very foundations of our planet's ecological stability. This biodiversity loss, characterized by the rapid decline in genetic, species, and ecosystem diversity, not only diminishes the intrinsic value of life but also undermines the essential services that ecosystems provide, including clean water, food security, and climate regulation. The urgency to address this crisis has never been more critical, demanding innovative and effective conservation strategies that can safeguard the planet's irreplaceable biological heritage [1-6,9,11].

Traditional conservation approaches, while vital, often fall short in addressing the complexities of modern environmental challenges. These methods, relying primarily on ecological observations and demographic data, struggle to capture the intricate genetic underpinnings of species resilience and adaptability. In the face of rapid environmental change, understanding the genetic diversity and evolutionary potential of populations becomes paramount for effective conservation planning [7,8].This is where conservation genomics emerges as a revolutionary field, offering a powerful toolkit to illuminate the genetic dimensions of biodiversity and inform targeted conservation interventions[11-13].

Conservation genomics, at its core, represents the application of genomic tools and analyses to address pressing conservation challenges. It transcends the limitations of traditional conservation genetics by delving into the comprehensive analysis of entire genomes, revealing the intricate patterns of genetic variation, adaptation, and evolutionary history. This holistic approach empowers researchers to move beyond simply counting species to understanding the fundamental genetic mechanisms that underpin their survival and adaptability. By harnessing the power of next-generation sequencing, bioinformatics, and computational biology, conservation genomics provides unprecedented insights into the genetic architecture of populations, allowing for a more nuanced understanding of their vulnerability and resilience [14-16].

The scope of conservation genomics is vast, encompassing a wide array of applications that directly contribute to effective conservation strategies. One of the primary applications is the assessment of genetic diversity, a cornerstone of population viability. By quantifying genetic variation within and among populations, conservation genomics helps identify those with low genetic diversity, which are often more susceptible to environmental stressors and genetic bottlenecks. Conversely, it pinpoints areas of high genetic diversity, highlighting crucial regions for conservation prioritization. Furthermore, understanding the adaptive potential of populations is vital in the face of rapid environmental change. Conservation genomics facilitates the identification of genes under selection, revealing the genetic basis of adaptation and allowing for the assessment of a population's capacity to respond to changing conditions, such as climate change [13,17-19].

Beyond assessing genetic diversity and adaptation, conservation genomics plays a crucial role in population management and restoration. By determining genetic relationships between populations, genomics informs decisions about translocations and reintroductions, ensuring the genetic health and viability of managed populations. It also helps detect and manage hybridization and introgression, which can have significant genetic consequences for threatened species. Moreover, genomics has revolutionized species monitoring and identification. Environmental DNA (eDNA) analysis, for example, enables the detection of species from environmental samples, providing a non-invasive and efficient way to monitor rare and elusive species [7,20]. Metagenomics offers insights into the composition and function of microbial communities, which are essential for ecosystem health. And in the fight against illegal wildlife trade, genomics provides powerful forensic tools to identify species and geographic origins of seized wildlife products [21,22].

The rapid advancements in genomic technologies and bioinformatics have been instrumental in driving the progress of conservation genomics. Whole-genome sequencing (WGS) provides comprehensive genetic information, enabling the analysis of genome-wide patterns of variation and adaptation. Reduced representation sequencing techniques, such as RAD-seq and GBS, offer cost-effective alternatives for many applications. Bioinformatics tools and databases are essential for managing and analyzing the vast amounts of genomic data generated. These advancements have not only expanded the scope of conservation genomics but also made it more accessible to researchers and conservation practitioners[23-30].

However, despite its immense potential, conservation genomics faces several challenges. The sheer volume of genomic data necessitates robust data management and analysis infrastructure. Ethical considerations surrounding the use of genetic information, particularly regarding data privacy and potential misuse, must be carefully addressed. Perhaps most importantly, the integration of genomic research into practical conservation policy remains a significant hurdle. Effective communication and collaboration between scientists, policymakers, and conservation practitioners are crucial for translating genomic insights into actionable conservation strategies [31-34].

This review aims to provide a comprehensive overview of current approaches in conservation genomics, examining the application of genomic data in various conservation contexts. We will evaluate the strengths and limitations of different genomic technologies, discuss the challenges and future directions of this rapidly evolving field, and ultimately, demonstrate how conservation genomics can contribute to safeguarding global biodiversity [35,36]. By bridging the gap between genomic research and conservation practice, we can harness the power of genomics to inform targeted and effective strategies that will ensure the long-term survival of Earth's diverse life forms. The imperative to integrate genomic data into conservation practice is not merely a scientific pursuit, but a moral obligation to protect the planet's irreplaceable biological heritage for future generations[38,40,42].

II..Understanding Adaptation and Evolution:Conservation genomics has emerged as a critical tool for understanding the intricate mechanisms by which species adapt to environmental change and evolve under selective pressures. By delving into the genetic makeup of populations, researchers gain unprecedented insights into the processes driving adaptation and the potential for species to persist in a rapidly changing world[37,39,41].

2.1The Power of Genomics in Evolutionary Studies:Traditional evolutionary studies relied heavily on phenotypic observations and ecological data. While valuable, these approaches often lacked the resolution to pinpoint the underlying genetic basis of adaptation. Genomics provides a direct window into the genetic variation that fuels evolutionary change, allowing researchers to:[43-45].

  • Identify Adaptive Genes: By analyzing patterns of genetic variation, researchers can identify genes that have been under selection, revealing the genetic basis of traits that enhance survival and reproduction in specific environments [46].
  • Track Evolutionary History: Genomic data can reconstruct the evolutionary history of populations and species, revealing patterns of gene flow, population divergence, and adaptation to past environmental changes [47].
  • Predict Evolutionary Trajectories: By understanding the genetic basis of adaptation, researchers can develop models to predict how populations might respond to future environmental changes, such as climate change or habitat loss [48].

2.2. Applications in Conservation:The insights gained from conservation genomics have direct applications in conservation management[3].

  • Assessing Adaptive Potential: By measuring genetic diversity and identifying adaptive genes, researchers can assess the potential for populations to adapt to future environmental challenges. This information can be used to prioritize conservation efforts for populations with high adaptive potential [44].
  • Guiding Assisted Migration: In cases where populations are unlikely to adapt in situ, assisted migration (translocation) may be considered. Genomics can help identify suitable source populations and recipient habitats, maximizing the chances of successful translocation [45].
  • Monitoring Evolutionary Responses: Genomics can be used to monitor evolutionary responses to conservation interventions, such as habitat restoration or captive breeding programs. This allows researchers to assess the effectiveness of these interventions and make adjustments as needed [41].
  • Understanding Local Adaptation: Many species exhibit local adaptation, meaning that populations are adapted to the specific environmental conditions of their habitat. Genomics can help to understand the genetic basis of local adaptation, ensuring that conservation efforts do not disrupt these adaptations [38].

2.3. Examples of Genomic Insights:

  • Studies of fish populations have revealed genes associated with tolerance to temperature changes, providing insights into how these species might respond to climate change.
  • Research on plant populations has identified genes involved in drought tolerance, which is crucial for understanding how these species might adapt to increasing aridity.
  • Genomic analyses of endangered species have revealed patterns of genetic bottlenecking and inbreeding, highlighting the need for conservation interventions to maintain genetic diversity[48-51].

III. Population Management and Restoration: Leveraging Genomic Insights

Genomic data has become an indispensable tool in the realm of conservation, particularly in the critical areas of population management and ecosystem restoration. The ability to delve into the genetic makeup of species and ecosystems provides a level of detail previously unattainable, enabling more informed and effective conservation strategies[55].

A. Population Management: Precision Conservation Through Genomics

Effective population management hinges on understanding the genetic health and structure of a species. Genomic data offers several key advantages[56].

  • Genetic Diversity Assessment:
    • Genomics allows for the precise quantification of genetic diversity within and between populations. This is crucial for identifying populations with low genetic diversity, which are more susceptible to inbreeding depression, reduced adaptive potential, and increased vulnerability to diseases.
    • By identifying genetically diverse populations, conservationists can prioritize them for protection and management, ensuring the long-term viability of the species[55,57].
  • Population Connectivity and Gene Flow:
    • Genomic data reveals patterns of gene flow and connectivity among populations. This information is vital for understanding how populations are linked and identifying important dispersal corridors.
    • Understanding connectivity is essential for designing effective conservation strategies, such as establishing wildlife corridors and managing habitat fragmentation[56].
  • Defining Management Units:
    • Genomics helps delineate distinct management units within species, ensuring that conservation efforts are tailored to the specific genetic characteristics of different populations.
    • This is particularly important for species with wide distributions or complex population structures, where local adaptations may be crucial for survival[58].
  • Monitoring Population Health and Inbreeding:
    • Genomic data can be used to monitor the genetic health of populations, including the detection of genetic markers associated with disease susceptibility or resistance.
    • It also allows for the assessment of inbreeding levels, which can have detrimental effects on population viability.
    • Long term monitoring of genetic diversity is now possible[55-56,59].
  • Guiding Captive Breeding Programs:
    • For endangered species, captive breeding programs play a crucial role in conservation. Genomics guides these programs by maximizing genetic diversity and minimizing inbreeding.
    • It helps select individuals for breeding that are genetically representative of the wild population, ensuring that captive-bred individuals are well-adapted for reintroduction[60].

B. Ecosystem Restoration: Rebuilding Biodiversity with Genomic Precision: Ecosystem restoration aims to reverse the degradation of ecosystems and restore their ecological functions. Genomics provides valuable insights for achieving this goal [61].

Source Population Selection for Restoration:

    • Genomics helps identify suitable source populations for restoration projects, ensuring that reintroduced individuals are genetically adapted to the target environment[62].
    • This increases the success of restoration efforts by maximizing the survival and reproduction of reintroduced individuals [63].
  • Monitoring Restoration Success and Biodiversity Return:
    • Genomics can monitor the genetic diversity and adaptive potential of restored populations over time, allowing for the assessment of restoration success.
    • Environmental DNA (eDNA) allows for the monitoring of the return of key species, and the return of a healthy level of biodiversity to a restored site[64].
  • Restoring Soil Microbiome Health:
    • Metagenomics allows for the assessment of soil microbial diversity and function, which are essential for plant growth and ecosystem health.
    • This information can be used to develop strategies for restoring degraded soil ecosystems, such as inoculating soils with beneficial microbes[65].
  • Understanding Ecosystem Resilience:
    • Genomics helps reveal the genetic basis of ecosystem resilience to environmental stressors, such as climate change and pollution.
    • This information can inform restoration efforts aimed at creating ecosystems that are more resistant to disturbances.[66-69,72]
  • eDNA monitoring:
    • eDNA sampling allows for the monitoring of species presence, and biodiversity in both terrestrial and aquatic systems. It is a noninvasive way to monitor the success of restoration efforts [70,71]

IV. Monitoring and Species Identification

(Table no.1 Monitoring and Species Identification) [73-76]

Application

Description

Example

Species Identification

Distinguishing between closely related species that are morphologically similar.

Identifying cryptic species of butterflies or fish.

Population Genetics

Studying genetic variation within and between populations of a species.

Tracking the spread of invasive species or understanding the genetic diversity of endangered species.

Conservation Genetics

Applying genetic information to conservation efforts.

Identifying genetically distinct populations for conservation, monitoring inbreeding, and assessing the impact of human activities on genetic diversity.

Disease Surveillance

Tracking the spread of infectious diseases and identifying their origins.

Monitoring the emergence and spread of new strains of viruses or bacteria.

Forensic Applications

Using genetic information for legal purposes, such as identifying individuals or species involved in crimes.

Wildlife forensics, such as identifying the source of illegally traded wildlife products.

V. Genomic Technologies and Bioinformatics: Fueling the Conservation Genomics Revolution

The explosive growth of genomic technologies and bioinformatics has fundamentally transformed the landscape of conservation genomics. These advancements have drastically increased the speed, efficiency, and scale of genetic data collection and analysis, enabling researchers to address critical conservation questions with unprecedented precision.[72].

Genomic Technologies: Unlocking the Secrets of the Genome

The development of high-throughput sequencing technologies, such as next-generation sequencing (NGS), has been a game-changer.1 These technologies allow for the rapid and cost-effective sequencing of entire genomes or specific genomic regions, generating vast amounts of data that were previously unattainable.2 Key technological advancements include[77].

  • Next-Generation Sequencing (NGS): NGS platforms, like Illumina and PacBio, have revolutionized sequencing by allowing for the simultaneous sequencing of millions of DNA fragments.3 This has drastically reduced the cost and time required for genome sequencing, making it feasible to study a wider range of species[76]
  • Environmental DNA (eDNA) Sequencing: eDNA sequencing allows for the detection and identification of species from environmental samples, such as water, soil, or air. This non-invasive approach is particularly valuable for monitoring elusive or endangered species and assessing biodiversity in challenging environments[77].
  • Genotyping-by-Sequencing (GBS): GBS is a cost-effective method for genotyping large numbers of individuals, making it ideal for population genetics studies.7 It involves sequencing a subset of the genome, providing sufficient information to assess genetic diversity and population structure[78].
  • Long-Read Sequencing: Technologies like PacBio and Oxford Nanopore enable the sequencing of long DNA fragments, which is crucial for assembling complex genomes and resolving repetitive regions. This improves the accuracy and completeness of genome assemblies [79].
  • Portable Sequencing: Handheld sequencing devices, like the Oxford Nanopore MinION, are enabling field-based genomics, allowing researchers to collect and analyze genetic data in real-time.10 This is particularly valuable for rapid response to disease outbreaks or other conservation emergencies [80].

Bioinformatics: Transforming Data into Knowledge

The vast amounts of data generated by genomic technologies require sophisticated bioinformatics tools and expertise for analysis and interpretation.11 Key bioinformatics advancements include[17-21].

  • Genome Assembly and Annotation: Bioinformatics tools are used to assemble short DNA fragments into complete genome sequences and to identify genes and other functional elements within the genome.
  • Population Genetics Analysis: Software packages are available for analyzing population genetic data, such as calculating genetic diversity, estimating gene flow, and identifying population structure.
  • Phylogenomics: Phylogenomics uses genomic data to reconstruct evolutionary relationships among species, providing insights into the history of diversification and adaptation.
  • Metagenomics Analysis: Metagenomics involves the analysis of DNA from complex microbial communities, revealing the diversity and function of these communities in ecosystems
  • Machine Learning and Artificial Intelligence: Machine learning algorithms are being increasingly used to analyze complex genomic datasets, identify patterns, and predict evolutionary responses to environmental change.
  • Cloud Computing and Data Storage: Cloud-based platforms provide the computational resources and storage capacity needed to handle the vast amounts of genomic data.
  • Development of Databases: Public databases like GenBank, and specialized databases for specific organisms, allow for the storage and sharing of genetic data.[29-35,81-85]

Impact on Conservation Genomics:

These advancements have had a profound impact on conservation genomics, enabling researchers to

  • Assess genetic diversity and population structure with greater precision.
  • Identify adaptive genes and predict evolutionary responses to environmental change.
  • Monitor biodiversity and ecosystem health using eDNA.
  • Develop more effective conservation strategies based on genetic information.
  • Rapidly respond to conservation emergencies.
  • Gain a deeper understanding of the evolutionary processes that shape biodiversity.

The continued development of genomic technologies and bioinformatics will further enhance our ability to conserve biodiversity in a rapidly changing world. By harnessing the power of genomics, we can gain a deeper understanding of the genetic basis of adaptation, resilience, and evolution, and develop more effective strategies for protecting the planet's biodiversity[7,15,88]

  • A. Whole Genome Sequencing (WGS):
    • WGS provides comprehensive genetic information, enabling the analysis of genome-wide patterns of variation and adaptation.
  • B. Reduced Representation Sequencing:
    • Techniques like RAD-seq and GBS offer cost-effective alternatives to WGS, providing sufficient resolution for many conservation applications.
  • C. Bioinformatics Tools & Databases:
    • Bioinformatics tools and databases are essential for managing and analyzing large genomic datasets. Advancements in computational power and algorithm development have greatly enhanced the efficiency of genomic data analysis.[9-13,86,87]

VI. Challenges and Future Directions:Conservation genomics, with its capacity to illuminate genetic diversity and evolutionary processes, holds immense promise for safeguarding biodiversity.1 However, realizing this potential necessitates navigating a complex landscape of challenges.[89]

(Table no.2 Challenges Directions)[90-93]

Challenge

Description

Impact on Conservation

Data Analysis and Interpretation

The sheer volume and complexity of genomic data demand sophisticated bioinformatics tools and expertise. Translating raw data into actionable conservation strategies is often difficult.

Slows down decision-making, hinders the identification of critical genetic markers, and can lead to misinterpretations.

Cost and Accessibility

High-throughput sequencing   and advanced computational resources can be prohibitively expensive, limiting the application of genomics in resource-constrained regions and for non-model organisms.

Creates disparities in conservation efforts, favoring well-funded projects and

limiting the scope of studies to a few select species.

Reference Genome Availability

Comprehensive reference genomes are lacking for many non-model organisms,

hindering comparative

analyses and limiting the ability to identify functional genetic variants.

Restricts the application of genomics to a small subset of species, leaving many vulnerable organisms

without the benefits of genomic insights.

Ethical Considerations

The use of genetic information raises ethical concerns, including data privacy, potential misuse, and the implications of genetic manipulation. The potential for genetic discrimination against certain populations is also a concern.

Undermines public trust in conservation genomics, creates potential for misuse of genetic information, and raises complex ethical dilemmas regarding intervention.

Linking Genotype to Phenotype

Understanding how genetic variation translates to observable traits (phenotypes)

is crucial for predicting how species will respond to environmental change.

This link is often complex and difficult to establish, particularly in natural populations.

Limits the ability to predict adaptive potential and hinders the development

of effective conservation

strategies based on genetic information.

Integrating Genomics with Other Disciplines

Effective conservation requires integrating genomic data with ecological, demographic, and socioeconomic information.

This integration can be challenging due to differences in data types,

methodologies, and expertise.

Leads to fragmented approaches to conservation,

limiting the ability to address complex ecological and social challenges.

Future Directions:

To overcome these challenges, the field of conservation genomics is moving in several crucial directions.

  • Technological Advancements: Continued improvements in sequencing technologies, bioinformatics tools, and computational power will reduce costs, increase efficiency, and enable the analysis of larger datasets. Field-based genomics, allowing for real-time monitoring, will also be increasingly valuable.
  • Increased Data Sharing and Collaboration: Open-access databases, standardized protocols, and collaborative networks will facilitate data sharing and accelerate research. This will allow researchers to leverage existing data and expertise, reducing redundancy and promoting efficiency.
  • Functional Genomics: A greater focus on functional genomics will help to elucidate the roles of specific genes and genetic variants in adaptation and resilience. This will enable researchers to predict how species will respond to environmental change and prioritize conservation efforts accordingly.
  • Integrating Genomics into Conservation Planning: Developing frameworks for incorporating genomic data into conservation decision-making will be essential. This will involve working closely with policymakers, conservation practitioners, and local communities to ensure that genomic insights are translated into effective conservation actions.
  • Establishing Ethical Frameworks: Robust ethical guidelines and best practices are needed to ensure the responsible use of genomic data in conservation.2 This will involve addressing concerns about data privacy, potential misuse, and the implications of genetic manipulation.
  • Metagenomics and Environmental DNA (eDNA): The use of metagenomics and eDNA to monitor biodiversity and ecosystem health will become increasingly important. These techniques offer a powerful way to assess species presence, abundance, and genetic diversity in a non-invasive manner.
  • Epigenetics: Increased focus on epigenetic studies will reveal how environmental factors influence gene expression and impact species' responses to change. This will help us understand how organisms adapt to rapid environmental shifts.[6,18-25,88,90,93]

VII. Conclusion:Conservation genomics has emerged as a powerful tool for safeguarding biodiversity. By providing detailed insights into genetic variation, adaptation, and evolutionary processes, genomics enhances our ability to manage populations, restore ecosystems, and monitor species. The ongoing development of genomic technologies and bioinformatics tools will continue to expand the scope and impact of conservation genomics. However, addressing the challenges of data management, ethical considerations, and policy integration is crucial for realizing the full potential of this field. As we face an unprecedented biodiversity crisis, conservation genomics offers a vital pathway for ensuring the long-term survival of Earth's diverse life forms. The integration of genomic data into conservation practice is no longer a luxury, but a necessity.

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  60. Avise, J. C. (2000). Phylogeography: the history and formation of species. Harvard University Press.
  61. Beaumont, M. A. (2010). Approximate Bayesian computation in evolution and ecology. Annual Review of Ecology, Evolution, and Systematics, 41, 379-406.1
  62. Bernatchez, L., & Olsen, J. B. (2004). Is it really adaptive radiation? Journal of Evolutionary Biology, 17(6), 1413-1418.
  63. Bruford, M. W., & Wayne, R. K. (1993). Microsatellite and minisatellite variation in the bottlenose dolphin (Tursiops truncatus): geographical, social and individual-specific variation. Genetics, 134(4), 1279-1290.
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  65. DeSalle, R., & Amato, G. (2004). The expansion of conservation genetics. Nature Reviews Genetics, 5(9), 702-711.
  66. Edwards, S. V., & Beerli, P. (2000). Perspective: gene divergence, population divergence, and phylogeography. Evolution, 54(6), 1839-1854.
  67. Excoffier, L., Smouse, P. E., & Quattro, J. M. (1992). Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human2 mitochondrial DNA restriction data. Genetics, 131(2),3 479-491.
  68. Frankham, R. (1995). Conservation genetics of inbred populations. Conservation Biology, 9(6), 1279-1283.
  69. Freeland, J. R. (2005). Molecular ecology. John Wiley & Sons.
  70. Gaggiotti, O. E. (2003). Genetic threats to population persistence and recovery. Conservation Biology, 17(1), 5-10.
  71. Hedrick, P. W., & Kalinowski, S. T. (2000). Inbreeding depression in conservation biology. Annual Review of Ecology and Systematics, 31(1),4 139-162.
  72. Hughes, A. R., Inouye, B. D., Johnson, S. L., Underwood, N., & Vellend, M. (2008). Ecological consequences of genetic diversity. Ecology Letters, 11(6), 609-623.
  73. Keller, L. F., & Waller, D. M. (2002). Inbreeding effects in wild plant populations. Journal of Heredity, 93(2), 87-98.
  74. Kimura, M. (1983). The neutral theory of molecular evolution. Cambridge University Press.
  75. Lande, R. (1988). Genetics and demography in biological conservation. Science, 241(4872), 1455-1460.
  76. Lynch, M. (1996). A quantitative-genetic perspective on conservation issues. Conservation Biology, 10(3), 627-638.
  77. Manel, S., Schwartz, M. K., Luikart, G., & Taberlet, P. (2003). Landscape genetics: combining landscape ecology and population genetics. Trends in5 Ecology & Evolution, 18(4),6 189-197.
  78. Meffe, G. K., & Carroll, C. R. (1997). Principles of conservation biology. Sinauer Associates.
  79. Nei, M. (1987). Molecular evolutionary genetics. Columbia University Press.
  80. O'Brien, S. J., & Evermann, J. F. (1988). Interactive influence of infectious disease and genetic diversity in natural populations. Trends in Ecology7 & Evolution, 3(9), 254-262.
  81. Peakall, R., & Smouse, P. E. (2006). GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes, 6(1),8 288-295.
  82. Petit, R. J., & Hampe, A. (2006). Some evolutionary consequences of being a tree. Annual Review of Ecology, Evolution, and Systematics, 37, 187-214.9
  83. Reed, D. H., & Frankham, R. (2003). Correlation between fitness and genetic diversity. Conservation Biology, 17(1), 230-237.
  84. Ryman, N., & Utter, F. (1987). Population genetics and fishery management. University of Washington Press.
  85. Schlötterer, C. (2004). The evolution of molecular markers and their applicability in ecological and evolutionary studies. Journal of Ecology, 92(6), 1025-1042.
  86. Templeton, A. R. (2006). Statistical phylogeography: methods of evaluating and minimizing inference errors. Molecular Ecology, 15(13), 3079-3091.
  87. Vandergast, A. G., Bohonak, A. J., & Weiss, M. R. (2008). Contrasting patterns of population structure in two species of gall-inducing sawflies (Hymenoptera: Tenthredinidae). Molecular Ecology, 17(11), 2736-2751.
  88. Vellend, M. (2005). The landscape genetics of rapid range expansion in an introduced plant. Molecular Ecology, 14(12), 3409-3421.
  89. Vilà, C., Leonard, J. A., Götherström, A., Marklund, S., Sandberg, K., Lindqvist, C., ... & Ellegren, H. (1999). Widespread origins of domestic horse lineages. Science, 283(5403), 848-851.
  90. Wang, J. (2005). Estimation of effective population sizes from genetic samples. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1459), 1395-1409.
  91. Wright, S. (1931). Evolution in Mendelian populations. Genetics, 16(2), 97.
  92. Wright, S. (1969). Evolution and the genetics of populations. Vol. 2: The theory of gene frequencies. University of Chicago Press.
  93. Young, A. G., & Clarke, G. M. (Eds.). (2000). Genetics, demography and viability of fragmented populations. Cambridge University Press.

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  90. Wang, J. (2005). Estimation of effective population sizes from genetic samples. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1459), 1395-1409.
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  92. Wright, S. (1969). Evolution and the genetics of populations. Vol. 2: The theory of gene frequencies. University of Chicago Press.
  93. Young, A. G., & Clarke, G. M. (Eds.). (2000). Genetics, demography and viability of fragmented populations. Cambridge University Press.

Photo
Monika Kharat
Corresponding author

Women's College of Pharmacy, Peth - Vadgoan

Photo
Tejaswini Khot
Co-author

Women's College of Pharmacy, Peth - Vadgoan

Photo
Kalyani Bavade
Co-author

Women's College of Pharmacy, Peth - Vadgoan

Monika Kharat*, Tejaswini Khot, Kalyani Bavade, Conservation Genomics: Harnessing Genomic Data to Inform Conservation Strategies: A Comprehensive Review of Current Approaches, Int. J. of Pharm. Sci., 2025, Vol 3, Issue 3, 417-429. https://doi.org/10.5281/zenodo.14989950

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