Mahjani Laboratory

Madison Caballero, PhD

Bioinformatician III
Email: madison.caballero@mssm.edu

Madison is a bioinformatician III at Dr. Mahjani lab with a primary focus on investigating the role of ultra-rare genetic variation in psychiatric disorders. With a background in genetics, she specializes in analyzing large-scale genomics data using innovative computational approaches. Outside of research, Madison enjoys theater and spending time with her cat.

Madison earned her PhD in Genetics from Cornell University in 2022, where her research delved into the epigenetic phenomenon of DNA replication timing and its relationship to mutation rate. Additionally, she received a BSc in Cellular and Molecular Biology from the University of Connecticut, where she led plant genomics research, software development for protein annotation, and the successful design of a genotyping array for pines.

 

Select publications:

  • Caballero, M. The Interplay Between DNA Replication Timing and Mutations. Cornell University (2022). [doctoral dissertation]
  • Caballero, M. & Koren, A. The landscape of somatic mutations in lymphoblastoid cell lines. Cell Genomics 100305 (2023).
  • Caballero, M., Boos, D. & Koren, A. Cell-type specificity of the human mutation landscape with respect to DNA replication dynamics. Cell Genom 3, 100315 (2023).
  • Caballero, M. et al. Comprehensive analysis of DNA replication timing across 184 cell lines suggests a role for MCM10 in replication timing regulation. Hum Mol Genet ddac082 (2022).
  • Caballero, M. et al. Toward genomic selection in Pinus taeda: Integrating resources to support array design in a complex conifer genome. Applications in Plant Sciences 9, e11439 (2021).
  • Caballero, M. et al. Crossover interference and sex-specific genetic maps shape identical by descent sharing in close relatives. PLOS Genetics 15, e1007979 (2019).
  • Caballero, M. & Wegrzyn, J. gFACs: Gene Filtering, Analysis, and Conversion to Unify Genome Annotations Across Alignment and Gene Prediction Frameworks. Genomics, Proteomics & Bioinformatics 17, 305–310 (2019).

 

Education:

  • PhD, 2022, Genetics, University of Cornell University
  • BSc, 2018, Molecular and Cellular Biology, University of Connecticut

 

 

Research Projects – Computational Genetics

Genetic Architecture of Autism Spectrum Disorder

Our efforts encompass a range of projects aimed at unraveling the genetic risk architecture of autism spectrum disorder, encompassing both common and rare variation: 

  1. Investigating genetic variants with a moderate effect size in ASD.
  2. Exploring tandem repeat expansions in the context of ASD.
  3. Analyzing differential gene mutations associated with ASD.
  4. Examining the interplay between gene-environment interactions and the heterogeneity of ASD.
  5. Assessing how ancestral differences contribute to the heterogeneity of ASD.
  6. Uncovering the impact of common genetic variations on ASD risk, particularly through the autoimmunity pathway.
Model Development: Variant effect prediction using deep learning

We are in the process of developing an innovative model utilizing deep learning methods to effectively differentiate between deleterious and non-deleterious mutations, including non-coding variants.