Antonio Augusto Franco Garcia - ESALQ/USP

Antonio Augusto F. Garcia
A Augusto F Garcia has a PhD in Genetics and Plant Breeding (Luiz de Queiroz College of Agriculture - ESALQ, University of São Paulo - USP) and a postdoc in Statistical Genetics (Bioinformatics Research Center, North Carolina State University, USA). He is Associate Professor at Department of Genetics (ESALQ/USP), and leads a Statistical Genetics Laboratory with around 10 students (undergrads, MSC, PhDs and postdocs). He has been working on the development of statistical models to have a better understand of the genetic architecture of quantitative traits and to implement molecular breeding in several crops, including maize, sorghum and (specially) sugarcane. He participates of the National Institute of Science and Technology (INCT) of Bioethanol (FAPESP and CNPq). His research achievements include the development of a software (OneMap, and R package) that is used worldwide for building integrated genetic maps; several statistical methods for QTL mapping (including studies on heterosis and interaction G x E); and also methods for genotyping and mapping polyploids. He is editor of journals Theoretical and Applied Genetics and BMC Genetics.​

Genetic maps: useful tools for breeding and genomic studies

Genetic (or linkage) maps are bi-dimensional representations of distances and order of loci on chromosomes. Although keeping a direct relation with genome sequencing, they are build based on different principles, involving probabilistic distributions, phenomenon such as interference, and the presence of crossing over; all of these are inferred from segregating populations. Even with the recent availability of a large number of sequenced genomes, maps are very useful in a number of situations, once they can be used to understand genetic properties of populations, predict the extension of linkage disequilibrium, help to locate loci controlling the variation of quantitative traits (QTL), and to study the genetic architecture of quantitative traits. In fact, genome assembly and building genetic maps can mutually benefit to each other, once they provide similar information but based on different and complementary information. Also, the majority of plant species do not have sequenced genomes, so genetic maps are good alternatives to sequencing.
In this talk, I will discuss in details the statistical and computational principles involved in building linkage maps, showing the recent advances regarding marker loci based on high-throughput genotyping technologies (including SNPs) and new algorithms to deal with this scenario. I will also cover recent approaches for building maps for o utcrossing and polyploid plant species (such as sugarcane and forage crops).