Polydactyly is a genetic condition characterized by the presence of additional fingers or toes on at least one limb [1]. Polydactyly encompasses a broad range of phenotypes, varying in number of digits as well as level of development [1, 2, 3]. The additional digits range in functionality from small and entirely undeveloped to fully-functional [2]. Polydactyly arises from genetic errors in early embryonic development [3]. One of the genes associated with polydactyly is GLI3, a transcription factor that uses five zinc-finger peptide domains to bind to DNA. It is involved in the Hedgehog signaling pathway, a biological pathway essential to embryonic organ development in vertebrates [4]. GLI3, lacking Hedgehog signaling, is post-transcriptionally modified into GLI3R, a repressor that blocks the transcription of genes involved in organ development [4]. When GLI3 receives Hedgehog signaling, it is converted into GLI3A, an activated form that promotes target gene expression [4]. The ratio of GLI3R/GLI3A is crucial to proper organ development, including the development of the proper number of digits [4].The biological mechanism determining digit number and placement is currently unknown.
My objective is to determine GLI3’s role in the mechanism controlling digit count and placement. Mus musculus will be utilized as a model organism, as its GLI3 homolog is well-conserved and there already exists a broad body of literature to draw from concerning polydactyly phenotypes in mice [5]. I hypothesize that the disruption of different regions of GLI3’s five C2H2 zinc finger domains will cause distinct polydactyly phenotypes due to an inability to bind properly to DNA, reducing its effectiveness as a transcription factor during embryogenesis [3, 6]. My long-term goal is to understand the biological mechanism that determines digit number and placement during embryogenesis.
Aim 1: Disrupt GLI3 peptide domains to link polydactyly phenotypes to the disruption of particular loci
Rationale: To begin to identify how errors in GLI3 lead to particular polydactyly phenotypes, it will be useful to disrupt major conserved peptide sequences and observe the phenotypes that arise. This will begin to help us understand GLI3’s function in the mechanism determining digit number and placement.
Approach: Utilize PFAM and SMART to determine well-conserved and identified peptide sequences within GLI3 (as well as the Mus musculus homolog). Next, use CRISPR/Cas9 to induce mutations disrupting the sequence of each notable peptide sequence in mouse models. In addition to the single-disruption lines, create lines where more than one peptide sequence is disrupted. Observe the phenotypes that develop from the models for each mutation to determine the peptide sequences’ relevancy to digit development.
Hypothesis: I predict that disruption of each of the five well-conserved C2H2 zinc fingers will cause polydactyl phenotypes, the severity of which will increase with the number of disrupted peptide sequences in that mouse lineage.
Aim 2: Find correlations in gene expression changes in GLI3-mutant specimens during embryogenesis
Rationale: In order to determine GLI3’s role in the digit-determination mechanism, we will need to determine what relevant genes’ expressions are controlled by GLI3.
Approach: Extract tissue from the anterior and posterior portions of the limb nubs from wild-type and GLI3-mutant mouse embryos at successive periods of embryonic development. Next, use RNA-seq technology to detect discrepancies between gene expression patterns in wild-type and mutant specimens.
Hypothesis: I predict that in GLI3-mutant specimens, we will see higher expression levels of genes involved in skeletal development, as the mutant GLI3 cannot function as a repressor.
Aim 3: Identify novel protein interactions in wild-type and mutant GLI3 specimens
Rationale: As GLI3 is a transcription factor, GLI3 mutations likely affect the expression of many other genes. It is also possible that GLI3 possesses a heretofore-unknown functionality beyond that of transcription factor. Discovering what proteins’ interactions are altered by GLI3 mutations will be key to finding the next step in the digit-determining mechanism.
Approach: GLI3 proteins will be isolated and purified from wild-type mouse embryos as well as mutant mouse embryos generated from the lineages designed in Aim 1 using TAP-tags and mass spectrometry. Next, Gene ontology tools will be utilized to discover novel GLI3 protein interactors, and examine differences between the protein interaction networks generated from wild-type and mutant specimens.
Hypothesis: I predict that GLI3 mutant specimens will display altered or diminished gene interaction networks between GLI3 and proteins involved in skeletal formation.
My objective is to determine GLI3’s role in the mechanism controlling digit count and placement. Mus musculus will be utilized as a model organism, as its GLI3 homolog is well-conserved and there already exists a broad body of literature to draw from concerning polydactyly phenotypes in mice [5]. I hypothesize that the disruption of different regions of GLI3’s five C2H2 zinc finger domains will cause distinct polydactyly phenotypes due to an inability to bind properly to DNA, reducing its effectiveness as a transcription factor during embryogenesis [3, 6]. My long-term goal is to understand the biological mechanism that determines digit number and placement during embryogenesis.
Aim 1: Disrupt GLI3 peptide domains to link polydactyly phenotypes to the disruption of particular loci
Rationale: To begin to identify how errors in GLI3 lead to particular polydactyly phenotypes, it will be useful to disrupt major conserved peptide sequences and observe the phenotypes that arise. This will begin to help us understand GLI3’s function in the mechanism determining digit number and placement.
Approach: Utilize PFAM and SMART to determine well-conserved and identified peptide sequences within GLI3 (as well as the Mus musculus homolog). Next, use CRISPR/Cas9 to induce mutations disrupting the sequence of each notable peptide sequence in mouse models. In addition to the single-disruption lines, create lines where more than one peptide sequence is disrupted. Observe the phenotypes that develop from the models for each mutation to determine the peptide sequences’ relevancy to digit development.
Hypothesis: I predict that disruption of each of the five well-conserved C2H2 zinc fingers will cause polydactyl phenotypes, the severity of which will increase with the number of disrupted peptide sequences in that mouse lineage.
Aim 2: Find correlations in gene expression changes in GLI3-mutant specimens during embryogenesis
Rationale: In order to determine GLI3’s role in the digit-determination mechanism, we will need to determine what relevant genes’ expressions are controlled by GLI3.
Approach: Extract tissue from the anterior and posterior portions of the limb nubs from wild-type and GLI3-mutant mouse embryos at successive periods of embryonic development. Next, use RNA-seq technology to detect discrepancies between gene expression patterns in wild-type and mutant specimens.
Hypothesis: I predict that in GLI3-mutant specimens, we will see higher expression levels of genes involved in skeletal development, as the mutant GLI3 cannot function as a repressor.
Aim 3: Identify novel protein interactions in wild-type and mutant GLI3 specimens
Rationale: As GLI3 is a transcription factor, GLI3 mutations likely affect the expression of many other genes. It is also possible that GLI3 possesses a heretofore-unknown functionality beyond that of transcription factor. Discovering what proteins’ interactions are altered by GLI3 mutations will be key to finding the next step in the digit-determining mechanism.
Approach: GLI3 proteins will be isolated and purified from wild-type mouse embryos as well as mutant mouse embryos generated from the lineages designed in Aim 1 using TAP-tags and mass spectrometry. Next, Gene ontology tools will be utilized to discover novel GLI3 protein interactors, and examine differences between the protein interaction networks generated from wild-type and mutant specimens.
Hypothesis: I predict that GLI3 mutant specimens will display altered or diminished gene interaction networks between GLI3 and proteins involved in skeletal formation.
Drafts
zochert_3-3-20_specific_aims_draft1.docx | |
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zochert_4-17-20_specificaims_draft2.docx | |
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zochert_5-4-20_specificaims_finaldraft.docx | |
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File Type: | docx |
References
- Patel, R., Singh, C. B., Bhattacharya, V., Singh, S. K., & Ali, A. (2016). GLI3 mutations in syndromic and non-syndromic polydactyly in two Indian families. Congenital Anomalies, 56(2), 94-97. doi:10.1111/cga.12139
- Cheng, F., Ke, X., Lv, M., Zhang, F., Li, C., Zhang, X., . . . Li, S. (2011). A novel frame-shift mutation of GLI3 causes non-syndromic and complex digital anomalies in a Chinese family. 412(11), 1012-1017.
- Crapster, J. A., Hudgins, L., Chen, J. K., & Gomez-Ospina, N. (2017). A novel missense variant in the GLI3 zinc finger domain in a family with digital anomalies. American Journal of Medical Genetics Part A, 173(12), 3221-3225. doi:10.1002/ajmg.a.38415
- Carballo, G. B., Honorato, J. R., de Lopes, G. P. F., & Spohr, T. C. L. d. S. e. (2018). A highlight on Sonic hedgehog pathway. Cell Communication and Signaling, 16(1), 11. doi:10.1186/s12964-018-0220-7
- Büscher, D., Bosse, B., Heymer, J., & Rüther, U. (1997). Evidence for genetic control of Sonic hedgehog by Gli3 in mouse limb development. 62(2), 175-182.
- Fedotova, A. A., Bonchuk, A. N., Mogila, V. A., & Georgiev, P. G. (2017). C2H2 Zinc Finger Proteins: The Largest but Poorly Explored Family of Higher Eukaryotic Transcription Factors. Acta naturae, 9(2), 47-58.
Images
Header: https://www.researchgate.net/figure/Antroposterior-radiograph-of-the-right-hand-with-thumb-polydactyly-demonstrates-that_fig2_303539642
This web page was produced as an assignment for Genetics 564, an undergraduate capstone course at UW-Madison.