International Journal of Molecular Ecology and Conservation 2024, Vol.14, No.1, 18-26 http://ecoevopublisher.com/index.php/ijmec 24 5.2 The significance of genetic adaptation strategies for human future survival and health The genetic adaptability of humans to environmental changes is not only the result of evolutionary processes, but also of great significance for our future survival and health. Understanding human genetic adaptation strategies can help us predict potential health challenges in the context of global climate change. For example, as global temperatures rise, some diseases that originally only appeared in tropical regions may spread to temperate regions. Understanding human genetic adaptability to these new environmental pressures will provide guidance for public health strategies. Moreover, research on genetic adaptability can help us design more effective medical interventions. By understanding the mechanisms of human genetic variation under specific environmental pressures, we can develop targeted drugs and treatment methods to address health issues caused by environmental changes. It is worth mentioning that research on human genetic adaptability to environmental changes emphasizes the importance of protecting genetic diversity. Genetic diversity is a key resource for humans to adapt to environmental changes. Only by maintaining a high level of genetic diversity can humans effectively cope with future environmental challenges. 6 Challenges and Opportunities GWAS has become an important means of analyzing human genetic adaptability, but in practical applications, researchers still face many challenges, including the complexity of data and the difficulty of statistical analysis. GWAS involves a vast amount of data, with each participant’s genome potentially containing millions of single nucleotide polymorphisms (SNPs), making the processing and analysis of this data extremely complex. Moreover, research on human genetic adaptability also requires consideration of the interaction between environmental and genetic factors, which increases the difficulty of data analysis (Welter et al., 2013). Meanwhile, GWAS requires the use of complex statistical methods to identify genetic variations associated with specific traits. Due to the large number of hypotheses tested, false positive results are prone to occur. Therefore, how to design a reasonable statistical model and how to correct the impact of multiple comparisons have become challenges in research. At present, the development of high-throughput sequencing technology has greatly improved the efficiency and accuracy of GWAS, making it possible to sequence more samples in a shorter time and at a lower cost (Schmidt and Hildebrandt, 2017). This not only speeds up the discovery of genetic variations, but also makes diversity research, including smaller populations, feasible. In addition, the application of artificial intelligence and machine learning technology, especially in data processing and statistical analysis, provides powerful tools for processing complex data in GWAS. These technologies can help researchers identify meaningful patterns and associations from large datasets while reducing the occurrence of false positive results. With the intensification of global climate change, understanding how humans can adapt to environmental changes through genetic adaptation has become particularly important. Genetic adaptability research can not only help us predict the potential impact of future climate change on humans, but also provide scientific basis for formulating long-term strategies to adapt to climate change. Although GWAS research on human adaptability faces many challenges, technological progress is continuously driving the development of this field, providing us with new opportunities to deepen our understanding of human genetic adaptability. Applying these research findings to public health and strategies to address climate change is expected to make significant contributions to protecting human health and promoting sustainable social development. Acknowledgments The author thanks the two anonymous peer reviewers for their thorough review of this study and for their valuable suggestions for improvement. Conflict of Interest Disclosure The author affirms that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.
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