Populations and Diseases
With the publication of the Human Genome Project a former target of scientific knowledge was completed and inaugurated a new era in biology and medicine. The next challenge would be, and even today continues to be, to identify all the genetic changes that make us unique and different, all point mutations, all events of gain and loss of genetic material, all segmental duplications and differences in copy number variation distributed in human populations. Thus, the basis of population genomics dedicated to understand the genetic causes that differentially predispose us to diseases are being developing.
After the initial euphoria announcing the end of diseases in the next few years, it has installed a stage with renewed technological changes that gives us insight into the underlying biology of the genetic factors that predispose us to suffer some or other pathologies. This technological renovation has imposed definitely on the life sciences, giving impetus to a new central discipline: bioinformatics, dedicated to the design of programs, databases and viewers that facilitate handling, housing and the accessibility of data. The consequences of this deep change are visible today in biology and medicine. Genomics, bioinformatics, statistics and population biology are gaining a new experimental basis for studying biology, diseases and evolution.
Human Genomics consists in two independent courses offered by the Ecology, Genetics and Evolution Department (EGE) at FCEN-UBA, focusing on the figure’s areas intersection.
Human Population Genomics covers Human Genomics, NGS Technologies, Functional Genomics, Structural Variants, Population Genomics, Human Genome Variability, Ancestral Genomes, Adaptation and Continental Peopling;
Human Genomics and Diseases focuses in Medical Genomics, Mendelian and Complex Diseases, GWAS, Personalized Medical Genomics, Genomic Selection, Ethical, Legal and Social Issues.
Both courses share intensive (60%) hands-on bioinformatics practices (previous computer skills in Linux OS are not required), giving three (3), and two (2) points to the FCEN-UBA Doctorate Program, respectively.
The attendance of biologists and medical doctors to both courses is strongly recommended.
The courses will run from August 2014. Details will be announced in May 2014.
Phylogenetics, Phylogenomics and Adaptation
The reconstruction of the evolutionary history from molecular sequences is a statistical problem. Markov models of DNA and protein’s sequences are useful mathematical tools to estimate accurate parameters characterising the underlying process of evolution of sequence divergence during time. Maximum likelihood and Bayesian statistical analysis are common methods used in the area of computational molecular evolution. Hypothesis of molecular adaptation on genes can be statistically tested using these tools. Moreover, the phylogenetic analysis of thousand of genes of genomes poses new computational and visual challenges in this area.
All this topics are discussed and integrated in “Sistemática Teórica“. I strongly recommend this course for all biologists.
You can download presentations on these topics… here.
RNAseq and Functional Annotation
NGS transcriptome sequencing (RNA- Seq) replaces microarray technology for quantifying and profiling gene expression levels, serving simultaneously to the discovery of alternative splicing variants, rare and novel transcripts and miRNA precursors. The ability to obtain a complete picture of the transcriptome of different tissues and diseases provides a clearer understanding of how genome information becomes functional proteins , allowing the clinical utility of patient classification , diagnosis and individualized treatment. There are a large number of bioinformatics tools and techniques for quality control , pre – processing, alignment, quantitative analysis and differential expression of which pose significant obstacles to many biologists.
During this course we will explore different aspects of RNAseq technology, bioinformatics and statistical analysis of the transcriptome together with the functional annotation of classical and nonclassical sequences.
See details of the course here.