Rafael Guerrero
Bio
PhD Biology University of Texas at Austin 2013
Area(s) of Expertise
Computational Evolutionary Genetics
Publications
- CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods , GENOME BIOLOGY (2024)
- Evolutionary druggability for low-dimensional fitness landscapes toward new metrics for antimicrobial applications , eLife (2024)
- Genetic polymorphisms associated with adverse pregnancy outcomes in nulliparas , SCIENTIFIC REPORTS (2024)
- Mixed outcomes in recombination rates after domestication: Revisiting theory and data , (2024)
- Epistasis and pleiotropy shape biophysical protein subspaces associated with drug resistance , PHYSICAL REVIEW E (2023)
- Epistasis meets pleiotropy in shaping biophysical protein subspaces associated with antimicrobial resistance , (2023)
- Evolutionary druggability for low-dimensional fitness landscapes toward new metrics for antimicrobial applications , ELIFE (2023)
- Evolutionary druggability: leveraging low-dimensional fitness landscapes towards new metrics for antimicrobial applications , (2023)
- Genetic Associations with Placental Proteins in Maternal Serum Identify Biomarkers for Hypertension in Pregnancy , (2023)
- Polygenic prediction of preeclampsia and gestational hypertension , NATURE MEDICINE (2023)
Grants
Understanding the forces that drive structural changes in the genome remains a key challenge in genetics and evolutionary biology. Since the earliest days of genetics, scientists have understood the vast implications that structural variation has on phenotypes. Chromosomal variation is ubiquitous across nature. It has been shown to play a role in several biological processes and is associated with multiple traits, including number of offspring, disease states, and the regulation of gene expression. Yet, despite this ubiquity and importance, several longstanding questions about the evolution of structural variation remain unanswered. Over the next five years, my lab will advance two parallel and complementary research lines that focus on two major features of the genomic landscape: chromosome inversions and sex chromosomes. First, my group will investigate the evolutionary forces maintaining inversions and the specific mutations within inversions that underlie important phenotypes. To this end, I will create and deploy a full-featured open-source software package that simulates whole chromosomes that carry polymorphic inversions and use it to quantify evolutionary forces acting on inversions in the malaria mosquito Anopheles gambiae. This proposed computational infrastructure will deepen our understanding of the biology of inversions and their role in processes like adaptation and speciation, and will motivate further work by allowing the rapid simulation of genome-scale data with chromosomal variation. A second research line uses comparative and population genomics to test theoretical predictions on the evolution of sex chromosomes, perhaps the most dynamically evolving region of the genome. I will focus on two independently evolved sex-chromosome systems in Solanum (a speciose plant genus of agricultural importance and considerable genomic resources), to study the mode and tempo of sex chromosome divergence. I will produce chromosome-level genome assemblies for two dioecious species (i.e., those with separate male and female individuals), characterize their sex chromosomes, and use a comparative approach to test for gene movement on and off the sex chromosomes. Further, I will search for two key features of the sex-linked regions predicted by theoretical models: an enrichment of sex-biased gene expression and an accumulation of sexually antagonistic polymorphism. My research will leverage the benefits of working with evolutionarily recent sex-chromosome systems, gaining a unique perspective on the origin of sex and the dynamics of sex-linked genomic regions, and learning about the conditions that affect the evolution of recombination suppression, subsequent sex-chromosome divergence, and potential degeneration. By developing computational tools necessary for genomic analysis and by testing core hypotheses of the evolution of large genomic features, this research program will make important strides in our understanding of how and why the structure of the genome evolves.