What Insights into Evolution Can Transcriptomics Offer?

Continue reading to learn more about what insights can be gained from applying transcriptomics to evolutionary genetics and biology research.

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Introduction to Transcriptomics in Evolutionary Biology

Transcriptomics in evolutionary biology is a specific field of science that endeavors to understand the transcriptome within an evolutionary framework. Overall, the field aims to understand how gene expression patterns have evolved and how they are responsible for the diversity we see across life forms today.

By analyzing the transcriptome, the entire collection of RNA sequences inside a given cell, we can gain a deeper understanding of how the expression of certain genes changes across species or within populations, allowing researchers to identify genes that are responsible for evolutionary adaptations or traits.1 Transcriptomics leveraged in evolutionary biology can help scientists decipher the mechanisms underlying evolutionary processes, such as the evolution of novel traits, adaptation to new environments, and the development of new species.

Often, the integration of transcriptomics within evolutionary biology also draws on the integration of additional scientific disciplines, such as phylogenetics and comparative genomics. Overall, this interdisciplinary approach greatly contributes to our understanding of the genetic basis of evolution.

Understanding Gene Expression Patterns

Studying gene expression patterns is fundamental to reconstructing genetic and biochemical pathways.2 In doing so, researchers can gain important insights into the function and roles of genes in biological processes, the development and differentiation of an organism, disease mechanisms, and environmental responses. They can also use the knowledge acquired in studying gene expression patterns to help develop safe and effective pharmaceutical compounds to treat a range of diseases.3

Transcriptomics is an essential tool for understanding gene expression patterns. It allows for quantification of the expression levels of multiple genes simultaneously. It also allows scientists to identify genes that have been spliced. In addition, it can be used to reveal novel RNA transcripts that were previously unknown. Finally, it can be used to compare the transcriptomes of individuals across different cohorts or even species, helping researchers to identify genes that contribute to phenotypic differences.

Unraveling Evolutionary Relationships

Understanding evolutionary relationships is important for the taxonomy and classification of species; it provides insight into the functional properties of genes and genomes, helps us better understand how species adapted to their environments over time, informs medical research and allows for the development of personalized medicine, and furthers our knowledge of human evolution and anthropology.

Transcriptomics can be used in a number of ways to help unravel evolutionary relationships. It can be used to identify genes that exist within different species but evolved from a common ancestral gene (orthologous genes).4 This can help researchers unravel evolutionary relationships between species and estimate divergence times. Additionally, transcriptomic data can be used by researchers to produce phylogenetic trees that depict the evolutionary relationships between species based on similarities and differences in their patterns of gene expression.

Studying Adaptive Responses to Environmental Changes

To understand evolutionary processes, it is important to understand how environmental changes can drive adaptive responses within a species. Transcriptomics can be used to help researchers understand this. It can be used to compare gene expression profiles between species or populations to identify genes that are unique to exposure to specific environmental factors. This helps scientists to identify genes that are vital for certain adaptive responses.

Transcriptomics can also be used to discover stress-responsive genes, genes induced under stress and may encode proteins involved in defense mechanisms, stress tolerance, and physiological adjustments.5 This is also highly important for developing our understanding of the underlying mechanisms of certain diseases, such as Alzheimer’s disease, for example.5

3d illustration of a ribonicleic acid chain from which the deoxyribonucleic acid or DNA is composed

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Exploring Regulatory Mechanisms and Genetic Variation

Transcriptomics is used extensively to shed light on regulatory mechanisms and genetic variation. First, transcriptomic data can be leveraged to identify regulatory elements. For example, analysis of transcriptomic data can identify promoters, transcription factor binding sites, and enhancers. By comparing expression patterns with the expression of these regulatory elements, scientists can gain important insight into the regulatory mechanisms that underlie gene expression.

Transcriptomics is also used to detect splicing events and RNA editing events. In doing so, scientists can further understand these events that lead to genetic variation and diversity within a species.6

Finally, transcriptomics is also used to detect and characterize non-coding RNAs, such that they play crucial regulatory roles in gene expression. By studying their patterns of gene expression, researchers can decipher their functions in genetic variation and regulatory mechanisms.

Comparative Transcriptomics Across Species

Comparative transcriptomics across species involves the comparison of patterns of gene expression and regulatory mechanisms across species. Via transcriptomics, scientists can identify genes that are the same across species, as well as those that have undergone divergence. Genes that are concerned are usually responsible for managing essential biological processes that are crucial across species. Those that have diverged tend to be responsible for species-specific adaptations.7

Comparative transcriptomics across species also allows for the detection of lineage-specific gene expression. As a result, lineage-specific genes that are crucial to driving evolutionary divergence and/or phenotypic diversity can be identified.

Finally, comparative transcriptomics can also be used to give insights into human evolution and disease. By comparing gene expression patterns between humans and primates, we can identify conserved genes and divergent relative to the mechanisms underlying human diseases. Doing so helps us better understand the underlying mechanisms of diseases as well as develop more effective treatments for them.

Insights into Evolutionary Processes and Divergence

Finally, transcriptomics offers a way of gaining important insights into evolutionary processes and divergence that are vital to understanding how human and other species have evolved, and what roles our genetics play in basic biological functioning and higher-level, human-specific functioning. Understanding evolutionary processes and divergence also offers us a crucial window into the development and progression of human diseases, both psychical and psychological.

Processes such as comparative gene expression analysis, the detection of lineage-specific gene expression, the detection of evolutionary conservative gene expression programs, and the functional annotation of genes and pathways involved in evolutionary processes are some of the ways that transcriptomics can help gather insights into evolutionary processes and divergence.


  1. Transcriptome Fact Sheet [online]. National Human Genome Research Institute. Available at: www.genome.gov/about-genomics/fact-sheets/Transcriptome-Fact-Sheet
  2. Alberts, B., et al. (2002) Molecular Biology of the Cell. Studying Gene Expression and Function. 4th edition. New York: Garland Science; Available at: https://www.ncbi.nlm.nih.gov/books/NBK26818/
  3. Yang, X. et al. (2020) High-throughput transcriptome profiling in drug and Biomarker Discovery. Frontiers in Genetics, 11. doi.org/10.3389/fgene.2020.00019.
  4. Vercruysse, J., et al. (2019) Comparative transcriptomics enables the identification of functional orthologous genes involved in early leaf growth. Plant Biotechnology Journal, 18(2), pp. 553–567. doi.org/10.1111/pbi.13223.
  5. Navarro, J. F., et al. (2020) Spatial transcriptomics reveals genes associated with dysregulated mitochondrial functions and stress signaling in alzheimer disease. iScience, 23(10), p. 101556. doi.org/10.1016/j.isci.2020.101556.
  6. WANG, Y., et al. (2014) Mechanism of alternative splicing and its regulation. Biomedical Reports, 3(2), pp. 152–158. doi.org/10.3892/br.2014.407.
  7. Ahrens, C.W., et al. (2022) The roles of Divergent and parallel molecular evolution contributing to thermal adaptive strategies in trees. Plant, Cell & Environment, 45(12), pp. 3476–3491. doi.org/10.1111/pce.14449.

Last Updated: Mar 12, 2024

Sarah Moore

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Sarah Moore

After studying Psychology and then Neuroscience, Sarah quickly found her enjoyment for researching and writing research papers; turning to a passion to connect ideas with people through writing.


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