Human Genetics

Courses

Course Requirements

The course requirements listed below are designed to provide a solid, common foundation that is useful in all areas of genomic analysis. These course requirements have been kept to a minimum since all trainees will also have substantial course requirements from their major departments. However, approximately one course per quarter from the requirements listed below will be expected from the trainees until the course requirements are satisfied. In addition, the required ethics course must be taken by the end of the first year as a trainee. Trainees may petition to substitute an equivalent course, that they have already taken or plan to take, for any course listed below by simply showing substantial overlap in the covered material.

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1. Molecular Biology Fundamentals

Trainees are required to take one of the following six courses: Chemistry and Biochemistry 153A or 153B; Ecology and Evolutionary Biology 121; Microbiology, Immunology, and Molecular Genetics 101 or 102; and Molecular, Cell, and Developmental Biology 144.

  • Chemistry and Biochemistry
    • 153A. Biochemistry: Introduction to Structure, Enzymes, and Metabolism. Units: 4. Lecture, four hours; discussion, one hour. Structure of proteins, carbohydrates, and lipids; enzyme catalysis and principles of metabolism, including glycolysis, citric acid cycle, and oxidative phosphorylation. P/NP or letter grading.
    • 153B. Biochemistry: DNA, RNA, and Protein Synthesis. Units: 4. Lecture, three hours; discussion, one hour; tutorial, one hour. Nucleotide metabolism; DNA replication; DNA repair; transcription machinery; regulation of transcription; RNA structure and processing; protein synthesis and processing. P/NP or letter grading.
  • Ecology and Evolutionary Biology
    • 121. Molecular Evolution. Units: 4. Lecture, three hours; discussion, one hour. Molecular biology, with emphasis on evolutionary aspects. DNA replication, RNA transcription, protein synthesis, gene expression, and molecular evolution. Letter grading.
  • Microbiology, Immunology, and Molecular Genetics
    • 101. Introductory Microbiology. Units: 4. Lecture, three hours; discussion, one hour. Historical foundations of microbiology; introduction to bacterial structure, physiology, biochemistry, genetics, and ecology. Letter grading.
    • 102. Introductory Virology. Units: 4. Lecture, three hours; discussion, one hour. Requisites: Life Sciences 3, or 7A, 7B, and 23L with grades of C- or better. Biological properties of bacterial and animal viruses, replication, methods of detection, interactions with host cells and multicellular hosts. Letter grading.
  • Molecular, Cell, and Developmental Biology
    • 144. Molecular Biology. Units: 5. Lecture, three hours; discussion, one hour. Development of sophisticated understanding of DNA, RNA, and protein as well as capability of designing experiments to address fundamental questions in biology and interpreting experimental data. Letter grading.

2. Probability and Statistics Fundamentals

Trainees are required to take one of the following two-quarter sequences.

  • Statistics
    • 100A. Introduction to Probability Theory. Units: 4. Lecture, three hours; discussion, one hour. Probability distributions, random variables, vectors, and expectation. P/NP or letter grading.
    • 100B. Introduction to Mathematical Statistics. Units: 4. Lecture, three hours; discussion, one hour. Survey sampling, estimation, testing, data summary, one- and two-sample problems. P/NP or letter grading.

The above “B” quarter can be substituted with:

    • 236. Units: 4. Lecture, three hours; discussion, one hour. Introduction to statistical inference based on use of Bayes theorem, covering foundational aspects, current applications, and computational issues. Topics include Stein paradox, nonparametric Bayes, and statistical learning. S/U or letter grading.
  • Biostatistics
    • 100A. Introduction to Biostatistics. Units: 4. Lecture, three hours; discussion, one hour; laboratory, one hour. Introduction to methods and concepts of statistical analysis. Sampling situations, with special attention to those occurring in biological sciences. Topics include distributions, tests of hypotheses, estimation, types of error, significance and confidence levels, sample size. P/NP or letter grading.
    • 100B. Introduction to Biostatistics. Units: 4. Lecture, three hours; discussion, one hour; laboratory, one hour. Introduction to analysis of variance, linear regression, and correlation analysis. P/NP or letter grading.
    • 216. Mathematical Methods for Biostatistics. Units: 2. Lecture, two hours. Requisites: Mathematics 31A, 31B, 33A. Designed for incoming first-year MS and PhD students. Review, and in some cases introduction, of specialized topics in linear algebra, multivariable calculus, and scientific computing. Interplay between mathematical methods and scientific computing within R statistical computing environment. Detailed training on numerical algorithms used in linear algebra and probabilistic simulations commonly used by statisticians. S/U or letter grading.

    • 203B. Introduction to Data Science. Units: 4. Lecture, three hours; laboratory, two hours. Requisite: course 203A. Principles of data science. Topics include Health Insurance Portability and Accountability Act (HIPAA) and data ethics, databases and data retrieval, data merging and cleaning, data visualization and web presentation, reproducible research, collaborative research, cluster computing, and cloud computing. S/U or letter grading.

3. Quantitative Genomics Courses

Trainees are required to take Human Genetics 236A. In addition, trainees must take at least two of the following ten courses: Bioinformatics 260A; Biomathematics 207A, 207B, 211; Ecology and Evolutionary Biology 200A, 235; Human Genetics 224, 244, 265; and Statistics 254.

  • Human Genetics
    • 236A. Advanced Human Genetics A: Molecular Aspects. Units: 4. Lecture, three hours. Advanced topics in human genetics related to molecular genetics and relevant technologies. Topics include genomic technologies, human genome, mapping and identification of disease-causing mutations, transcriptomics, proteomics, functional genomics, epigenetics, and stem cells. Letter grading.
    • 224. Computational Genetics. Units: 4. Lecture, four hours; discussion, two hours; outside study, six hours. Introduction to computational analysis of genetic variation and computational interdisciplinary research in genetics. Letter grading.
    • 244. Genomic Technology. Units: 4. Lecture, three hours; discussion, one hour. Survey of key technologies that have led to successful application of genomics to biology, with focus on theory behind specific genome-wide technologies and their current applications. S/U or letter grading.
    • 265. Computational Methods in Genomics. Units: 4. Lecture, two and one half hours; discussion, two and one half hours; outside study, seven hours. Introduction to computational approaches in bioinformatics, genomics, and computational genetics and preparation for computational interdisciplinary research in genetics and genomics. Computational techniques and methods include those from statistics and computer science. Letter grading.
  • Bioinformatics
    • 260A. Introduction to Bioinformatics. Units: 4. Lecture, four hours; discussion, two hours. Introduction to bioinformatics and methodologies, with emphasis on concepts and inventing new computational and statistical techniques to analyze biological data. Focus on sequence analysis and alignment algorithms. S/U or letter grading.
  • Biomathematics
    • 207A. Theoretical Genetic Modeling. Units: 4. Lecture, three hours; discussion, one hour. Mathematical models in statistical genetics. Topics include population genetics, genetic epidemiology, gene mapping, design of genetics experiments, DNA sequence analysis, and molecular phylogeny. S/U or letter grading.
    • 207B. Applied Genetic Modeling. Units: 4. Lecture, three hours; laboratory, one hour. Covers basic genetic concepts. Topics include statistical methodology underlying genetic analysis of both quantitative and qualitative complex traits. Laboratory for hands-on computer analysis of genetic data; laboratory reports required. S/U or letter grading.
    • 211. Mathematical and Statistical Phylogenetics. Units: 4. Lecture, three hours; laboratory, one hour. Theoretical models in molecular evolution, with focus on phylogenetic techniques. Topics include evolutionary tree reconstruction methods, studies of viral evolution, phylogeography, and coalescent approaches. Examples from evolutionary biology and medicine. Laboratory for hands-on computer analysis of sequence data. S/U or letter grading.
  • Ecology and Evolutionary Biology
    • 200A. Units: 4. Lecture, two hours; discussion, two hours. Current concepts and topics in evolutionary biology, including microevolution, speciation and species concepts, analytical biogeography, adaptive radiation, mass extinction, community evolution, molecular evolution, and development of evolutionary thought. S/U or letter grading.
    • 235. Population Genetics. Units: 4. Lecture, three hours; discussion, one hour. Basic principles of genetics of population, dealing with genetic structure of natural populations and mechanisms of evolution. Equilibrium conditions and forces altering gene frequencies, polygenic inheritance, molecular evolution, and methods of quantitative genetics. S/U or letter grading.
  • Microbiology, Immunology, and Molecular Genetics
    • 256. Human Genetics and Genomics. Units: 5. (Same as Molecular, Cell, and Developmental Biology CM256.) Lecture, three hours; discussion, one hour. Requisites: Life Sciences 3, 4, and 23L, or 7A, 7B, and 7C. Application of genetic principles in human populations, with emphasis on genomics, family studies, positional cloning, Mendelian and common diseases, cancer genetics, animal models, cytogenetics, pharmacogenetics, population genetics, and genetic counseling. Lectures and readings in literature, with focus on current questions in fields of medical and human genetics and methodologies appropriate to answer such questions. Concurrently scheduled with course CM156. Independent research project required of graduate students. Letter grading.
  • Statistics
    • 254. Statistical Methods in Computational Biology. Units: 4. Lecture, three hours; discussion, one hour. Introduction to statistical methods developed and widely applied in several branches of computational biology, such as gene expression, sequence alignment, motif discovery, comparative genomics, and biological networks, with emphasis on understanding of basic statistical concepts and use of statistical inference to solve biological problems. Letter grading.

4. Career Development Course

Trainees are required to take one quarter of Human Genetics 282 per year.

  • Human Genetics

282. Topics on Scientific Careers. Units: 2. Lecture, two hours. Covers topics related to scientific careers such as scientific writing and presentation (including to non-scientific audiences), grant writing and reviewing, curricula vitae, hiring process, social media usage, developing short- and long-term goals, and balancing career and non-work life. Exploration of differences between industry, government, teaching-college, and research-college careers. S/U grading.

5. Ethics Course

Trainees are required to take Microbiology, Immunology, and Molecular Genetics 234 or Biomathematics M261 by the end of their first year as a trainee.

  • Microbiology, Immunology, and Molecular Genetics
    • 234. Ethics and Accountability in Biomedical Research. Units: 2. Seminar, two hours. Responsibilities and ethical conduct of investigators in research, data management, mentorship, grant applications, and publications. Responsibilities to peers, sponsoring institutions, and society. Conflicts of interest, disclosure, animal subject welfare, human subject protection, and areas in which investigational goals and certain societal values may conflict. S/U grading.
  • Biomathematics
    • M261. Responsible Conduct of Research Involving Humans. Units: 2. Lecture, two hours; discussion, two hours. Discussion of current issues in responsible conduct of clinical research, including reporting of research, basis for authorship, issues in genetic research, principles and practice of research on humans, conflicts of interest, Institutional Review Board (IRB), and related topics. S/U or letter grading