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Gene expression plays a crucial role in determining the phenotypes of organisms. The level of gene expression can affect the phenotype of an organism. For example, if a gene that codes for a particular enzyme is expressed at high levels, the organism may produce more of that enzyme and exhibit a particular trait as a result. On the other hand, if the gene is expressed at low levels, the organism may produce less of the enzyme and exhibit a different trait^[1].

Diagram of Extended Central Dogma With Enzymes — The extended central dogma of molecular biology includes all the cellular processes involved in the flow of genetic information

Gene expression is regulated at various levels and thus each level can affect certain phenotypes, including transcriptional and post-transcriptional regulation.

[I would delete the following section and would instead link to the Transcription page:] Transcriptional regulation refers to the control of gene expression at the level of transcription, which is the first step in the process of gene expression. This can involve the binding of regulatory proteins to specific DNA sequences called promoter regions to either enhance or inhibit the transcription of the gene. Post-transcriptional regulation refers to the control of gene expression at the level of RNA processing and translation. This can involve the modification of the RNA molecule, such as splicing or the addition of a poly-A tail, or the regulation of the translation of the RNA molecule into a protein.

The patchy colors of a tortoiseshell cat are the result of different levels of expression of pigmentation genes in different areas of the skin.

Changes in the levels of gene expression can be influenced by a variety of factors, such as environmental conditions, genetic variations, and epigenetic modifications. These modifications can be influenced by environmental factors such as diet, stress, and exposure to toxins, and can have a significant impact on an individual's phenotype. Some phenotypes may be the result of changes in gene expression due to these factors, rather than changes in genotype. An experiment involving Machine learning methods utilizing gene expression measured from RNA sequencing can contain enough signal to separate individuals in the context of phenotype prediction ^[2].

^ Anika Oellrich, Sanger Mouse Genetics Project, Damian Smedley, Linking tissues to phenotypes using gene expression profiles, Database, Volume 2014, 2014, bau017, https://doi.org/10.1093/database/bau017
^ Nussinov, R., Tsai, C.-J., & Jang, H. (2019). Protein ensembles link genotype to phenotype. PLOS Computational Biology, 15(6). https://doi.org/10.1371/journal.pcbi.1006648

[1] Anika Oellrich, Sanger Mouse Genetics Project, Damian Smedley, Linking tissues to phenotypes using gene expression profiles, Database, Volume 2014, 2014, bau017, https://doi.org/10.1093/database/bau017

[2] Nussinov, R., Tsai, C.-J., & Jang, H. (2019). Protein ensembles link genotype to phenotype. PLOS Computational Biology, 15(6). https://doi.org/10.1371/journal.pcbi.1006648

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