Data+Analysis

DNA & Protein Phylogenic Analysis

DNA: I specifically chose to align the LMNA of a large variety of mammalian species in order to see if similarities existed in organisms that one would not expect to be related. Not all collections of species created a tree with bootstrap values over 70 (a measure of statistically significant relation). The most similar sequences of the final tree existed between the two homo sapiens and the common chimpanzee. The farthest branch was between the cattle and crab-eating macaque- I found it interesting that the crab-eating macaque (a primate) was more closely related to the cattle than the other primate (common chimpanzee) or homo sapiens.

Protein: Initially, I tried to align the same species sequences as I did for DNA under the same minimum likelihood setting. However, when I attempted to align with the same species in both minimum and maximum likelihood methods, I did not have high enough bootstrap values to be significant. I was, however, able to incorporate a few different species used frequently in genetic research like the zebrafish, chicken, and african clawed frog.

Both analyses indicate that the LMNA gene is present and very similar, although not identical, in a variety of mammalian species. The existence of the LMNA across such an array of species supports the claim that it is a gene that has been highly conserved throughout evolution, which after understanding its functions within human cells, is no surprise. I found it interesting that in the DNA tree, the pig and homo sapien sequences were one of the least connected species, and in the protein tree they are much more closely related.

Since I was able to obtain DNA and protein tree with high bootstrap values within a high degree of species variety, it is most likely true that the LMNA gene is widespread throughout mammals, which enhances research opportunities and opens up new avenues in the study of LMNA associated diseases.

One potential concern I had was, in both trees, I noticed there were not bootstrap values in all the correct areas. For example, in the DNA tree, the values are present for all species except the cattle and crab-eating macaque. In the protein tree, there were bootstrap values shown between each node indicating the similarities between two species, however only some of the roots of each tree had bootstrap values. For example, there is no value connecting the branch extending from the norwegian rat and the chicken. If given more time, this discrepancy and its meaning would be an interest of further investigation.

Structural Analysis via Cn3D, PDB, and STRING

I used Cn3D and PDB to enhance my understanding of the protein and its mutant forms. They provided a 3-dimensional visual aspect to my gene which helped me conceptualize Lamin A. Although PDB provided me with a 3D image which was useful, once I obtained the id code, I was able to access Lamin A in Cn3D where I could adjust the settings to see every aspect of the protein imaginable from hydrophobicity to polarity to termini and more. It was also an easy to use interactive tool where I could label the termini of the protein and use my mouse to rotate the image of Lamin A in order to see each individual part of the protein.

I found the STRING results very useful in backing up what I read in my primary research. Knowing that researchers found multiple genes with which Lamin A interacts, seeing the thick lines that represented strong associations between them further supported the high degree of interaction that exists between Lamin A and other regulatory proteins. Seeing a visual relationship of this connection made it easier to comprehend.

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