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Research

Statistical Genetics of Chromosomal Dosage and Aneuploidy

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While it is normal for most healthy individuals to contain two copies of our genome within each cell, there can be deviations to this property either due to mutation (copy-number variants) or errors in chromosome segregation. A more recent research direction of mine has been to develop statistical methods for the analysis large-scale changes in chromosomal dosage (e.g. copy-number variation, or whole-chromosome aneuploidy). Much of my research has been focused on pre-implantation genetic testing (PGT) data from in-vitro fertilization (IVF) embryos, to infer properties of aneuploidy and meiotic recombination related to fertility.

Some active topics of research in this area:

  • Inferring crossover rates in embryo PGT datasets and their genetic architecture
  • Refining dosage constraint estimates of genes from segmental aneuploidies
  • Evolution of dosage constraint/relaxation across somatic tissue evolution

Representative Publications

  • Sara A. Carioscia* , Arjun Biddanda* , Margaret R. Starostik, Xiaona Tang, Eva R. Hoffmann, Zachary P. Demko, Rajiv C. McCoy. Common variation in meiosis genes shapes human recombination phenotypes and aneuploidy risk. Nature | Full Text

Human Statistical and Population Genetics

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Much of my current work is centered on human population genetics -with a goal to understand human evolutionary history and improve experimental design for studies of human disease. A subset of my research has been developing methods for using inferred ancestral recombination graphs (ARGs) for both statistical genetics of complex traits or inference of population history. Some recent topics of interest include:

  • Leveraging ARGs for population genetic inference and association testing for complex variants (e.g., CNVs)
  • Statistical considerations for meta-analysis of complex traits across multiple ancestries
  • Characterizing population demographic history of Indian populations

Representative Publications

  • Yulin Zhang* ‡, Arjun Biddanda* ‡ , Sarah A. Johnson, Colm O'Dushlaine, Priya Moorjani‡. Recovering signatures of archaic introgression using ancestral recombination graphs bioRxiv | Full Text | Software
  • Brian C Zhang, Arjun Biddanda, Árni F Gunnarsson, Fergus Cooper, Pier Francesco Palamara. (2023) Biobank-scale inference of ancestral recombination graphs enables genealogy-based mixed model association of complex traits. Nature Genetics | Full Text | Software
  • Arjun Biddanda* , Esha Bandyopadhyay* , Constanza de la Fuente Castro* , David Witonsky, ... , Niraj Rai, Maanasa Raghavan. (2024) Distinct positions of genetic and oral histories - Perspectives from India. HGG Advances | Full Text

Theoretical Population Genetics

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Much of my applied work draws on results from population genetic theory, and I enjoy working on problems that involve more mathematical rigor. Typically, these are oriented towards understanding how theory can be used to intuit or improve statistical population genetic inference. Some active topics of research in this domain are:

  • Two-locus genealogies with spatial and temporal structure
  • Evolution of recombination rates and meiosis-related traits
  • Genealogical models for intra-cellular/somatic evolutionary inference

Representative Publications

  • Arjun Biddanda, Matthias Steinrücken, John Novembre. (2022) Properties of Two-Locus Genealogies and Linkage Disequilibrium in Temporally Structured Samples. Genetics | Full Text | Software