| Affiliations: | Genetics & Genomics Research Leadership |
| Project Leader: | Andrew Harris ajharris@cvm.tamu.edu Veterinary Integrative Biosciences |
| Faculty Mentor: | Bill Murphy, Ph.D. |
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Meeting Times:
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TBA |
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Team Size:
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5
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| Open Spots: | 0 |
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Special Opportunities:
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Candidates selected for our team will gain knowledge and experience with important bioinformatic skills including obtaining high-throughput sequence data from remote databases, high-throughput sequence quality control, mapping of sequence data to high quality reference genome assemblies, multiple-sequence alignment generation, and whole-genome phylogenomic analyses. The skills acquired by candidates can be applied to diverse research fields that employ genomic data and thus represent a charismatic environment to explore the rapidly growing field of phylogenomics. In addition to gaining core bioinformatic skills, candidates will also have the opportunity to contribute to scientific publications and present their findings at scientific workshops |
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Team Needs:
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We are looking for students interested in the world of cat phylogenomics who are self-motivated, determined, and willing to take the initiative to help our team progress as a unit. Prior bioinformatic knowledge and experience using the TAMU HPRC cluster Grace is preferred but not required |
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Description:
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The field of phylogenomics is rapidly advancing, and the ability to assess species-level relationships at a genome-wide scale is becoming readily available. Recent discoveries in phylogenomics have shown how hybridization between closely related species confounds standard phylogenetic approaches. To identify the true species relationship, one must evaluate both phylogenetic and genomic data types at a genome-wide scale. Our project focuses on conducting whole-genome phylogenomic analyses on each of the eight major cat lineages to understand better the distribution of evolutionary histories that have been woven throughout the genomes of the various cat species through rampant hybridization over the past 9 million years. Using state-of-the-art software and novel techniques, we will also identify true species relationships by comparing phylogenetic and genomic data types in addition to identifying genes under selection for specific traits/phenotypes. |