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Optimizing transcriptomics to study the evolutionary effect of FOXP2
Optimizing transcriptomics to study the evolutionary effect of FOXP2
The field of genomics was established with the sequencing of the human genome, a pivotal achievement that has allowed us to address various questions in biology from a unique perspective. One question in particular, that of the evolution of human speech, has gripped philosophers, evolutionary biologists, and now genomicists. However, little is known of the genetic basis that allowed humans to evolve the ability to speak. Of the few genes implicated in human speech, one of the most studied is FOXP2, which encodes for the transcription factor Forkhead box protein P2 (FOXP2). FOXP2 is essential for proper speech development and two mutations in the human lineage are believed to have contributed to the evolution of human speech. To address the effect of FOXP2 and investigate its evolutionary contribution to human speech, one can utilize the power of genomics, more specifically gene expression analysis via ribonucleic acid sequencing (RNA-seq). To this end, I first contributed in developing mcSCRB-seq, a highly sensitive, powerful, and efficient single cell RNA-seq (scRNA-seq) protocol. Previously having emerged as a central method for studying cellular heterogeneity and identifying cellular processes, scRNA-seq was a powerful genomic tool but lacked the sensitivity and cost-efficiency of more established protocols. By systematically evaluating each step of the process, I helped find that the addition of polyethylene glycol increased sensitivity by enhancing the cDNA synthesis reaction. This, along with other optimizations resulted in developing a sensitive and flexible protocol that is cost-efficient and ideal in many research settings. A primary motivation driving the extensive optimizations surrounding single cell transcriptomics has been the generation of cellular atlases, which aim to identify and characterize all of the cells in an organism. As such efforts are carried out in a variety of research groups using a number of different RNA-seq protocols, I contributed in an effort to benchmark and standardize scRNA-seq methods. This not only identified methods which may be ideal for the purpose of cell atlas creation, but also highlighted optimizations that could be integrated into existing protocols. Using mcSCRB-seq as a foundation as well as the findings from the scRNA-seq benchmarking, I helped develop prime-seq, a sensitive, robust, and most importantly, affordable bulk RNA-seq protocol. Bulk RNA-seq was frequently overlooked during the efforts to optimize and establish single-cell techniques, even though the method is still extensively used in analyzing gene expression. Introducing early barcoding and reducing library generation costs kept prime-seq cost-efficient, but basing it off of single-cell methods ensured that it would be a sensitive and powerful technique. I helped verify this by benchmarking it against TruSeq generated data and then helped test the robustness by generating prime-seq libraries from over seventeen species. These optimizations resulted in a final protocol that is well suited for investigating gene expression in comprehensive and high-throughput studies. Finally, I utilized prime-seq in order to develop a comprehensive gene expression atlas to study the function of FOXP2 and its role in speech evolution. I used previously generated mouse models: a knockout model containing one non-functional Foxp2 allele and a humanized model, which has a variant Foxp2 allele with two human-specific mutations. To study the effect globally across the mouse, I helped harvest eighteen tissues which were previously identified to express FOXP2. By then comparing the mouse models to wild-type mice, I helped highlight the importance of FOXP2 within lung development and the importance of the human variant allele in the brain. Both mcSCRB-seq and prime-seq have already been used and published in numerous studies to address a variety of biological and biomedical questions. Additionally, my work on FOXP2 not only provides a thorough expression atlas, but also provides a detailed and cost-efficient plan for undertaking a similar study on other genes of interest. Lastly, the studies on FOXP2 done within this work, lay the foundation for future studies investigating the role of FOXP2 in modulating learning behavior, and thereby affecting human speech.
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Janjic, Aleksandar
2022
English
Universitätsbibliothek der Ludwig-Maximilians-Universität München
Janjic, Aleksandar (2022): Optimizing transcriptomics to study the evolutionary effect of FOXP2. Dissertation, LMU München: Graduate School of Systemic Neurosciences (GSN)
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Abstract

The field of genomics was established with the sequencing of the human genome, a pivotal achievement that has allowed us to address various questions in biology from a unique perspective. One question in particular, that of the evolution of human speech, has gripped philosophers, evolutionary biologists, and now genomicists. However, little is known of the genetic basis that allowed humans to evolve the ability to speak. Of the few genes implicated in human speech, one of the most studied is FOXP2, which encodes for the transcription factor Forkhead box protein P2 (FOXP2). FOXP2 is essential for proper speech development and two mutations in the human lineage are believed to have contributed to the evolution of human speech. To address the effect of FOXP2 and investigate its evolutionary contribution to human speech, one can utilize the power of genomics, more specifically gene expression analysis via ribonucleic acid sequencing (RNA-seq). To this end, I first contributed in developing mcSCRB-seq, a highly sensitive, powerful, and efficient single cell RNA-seq (scRNA-seq) protocol. Previously having emerged as a central method for studying cellular heterogeneity and identifying cellular processes, scRNA-seq was a powerful genomic tool but lacked the sensitivity and cost-efficiency of more established protocols. By systematically evaluating each step of the process, I helped find that the addition of polyethylene glycol increased sensitivity by enhancing the cDNA synthesis reaction. This, along with other optimizations resulted in developing a sensitive and flexible protocol that is cost-efficient and ideal in many research settings. A primary motivation driving the extensive optimizations surrounding single cell transcriptomics has been the generation of cellular atlases, which aim to identify and characterize all of the cells in an organism. As such efforts are carried out in a variety of research groups using a number of different RNA-seq protocols, I contributed in an effort to benchmark and standardize scRNA-seq methods. This not only identified methods which may be ideal for the purpose of cell atlas creation, but also highlighted optimizations that could be integrated into existing protocols. Using mcSCRB-seq as a foundation as well as the findings from the scRNA-seq benchmarking, I helped develop prime-seq, a sensitive, robust, and most importantly, affordable bulk RNA-seq protocol. Bulk RNA-seq was frequently overlooked during the efforts to optimize and establish single-cell techniques, even though the method is still extensively used in analyzing gene expression. Introducing early barcoding and reducing library generation costs kept prime-seq cost-efficient, but basing it off of single-cell methods ensured that it would be a sensitive and powerful technique. I helped verify this by benchmarking it against TruSeq generated data and then helped test the robustness by generating prime-seq libraries from over seventeen species. These optimizations resulted in a final protocol that is well suited for investigating gene expression in comprehensive and high-throughput studies. Finally, I utilized prime-seq in order to develop a comprehensive gene expression atlas to study the function of FOXP2 and its role in speech evolution. I used previously generated mouse models: a knockout model containing one non-functional Foxp2 allele and a humanized model, which has a variant Foxp2 allele with two human-specific mutations. To study the effect globally across the mouse, I helped harvest eighteen tissues which were previously identified to express FOXP2. By then comparing the mouse models to wild-type mice, I helped highlight the importance of FOXP2 within lung development and the importance of the human variant allele in the brain. Both mcSCRB-seq and prime-seq have already been used and published in numerous studies to address a variety of biological and biomedical questions. Additionally, my work on FOXP2 not only provides a thorough expression atlas, but also provides a detailed and cost-efficient plan for undertaking a similar study on other genes of interest. Lastly, the studies on FOXP2 done within this work, lay the foundation for future studies investigating the role of FOXP2 in modulating learning behavior, and thereby affecting human speech.