Recent/Ongoing Projects

We are a molecular/computational lab facility located in the Life Sciences North (LSN) Building 209 of SDSU's main campus in San Diego, CA. Our work is graciously supported by NSF CAREER: 2042516 to PI Sethuraman, NIH 1R15GM143700-01 to PI Sethuraman, NSF-ABI: 1564659 to PI Sethuraman and co-PI Jody Hey (Temple University), USDA-REEU: 2017-06423 to PI Vourlitis and co-PI Sethuraman, NSF-REU: 1852189  to PI Betsy Read and co-PI Sethuraman, USDA-NIFA: 0224776 to PI John Obrycki (University of Kentucky), as well as various intra-mural grants.

We are always interested in recruiting motivated young researchers. If you are an undergraduate/potential graduate student who is interested in working with us, here is a sample of some recent/ongoing projects in the lab. Do write to Dr. Sethuraman with your statement of interest, and CV. 

Diversity of Dinocampus coccinellae

Dinocampus coccinellae are a fascinating species of parasitoid wasps that affect more than 40 species of coccinellid lady beetles. We are interested in the morphological and genomic diversity of these tiny wasps from across the United States, and in delineating their evolutionary history. This work is currently ongoing, with gracious support from a CSUSM's Office of Graduate Studies and Research seed grant, in collaboration with Dr. John Obrycki at UKY, and Dr. Diego Sustaita at CSUSM. ​ We have now sequenced the first high-quality genome of D. coccinellae, analyzed morphological diversity in the species, and strive to understand the heritability of plastic morphology, and its evolution through comparative genomics.

PPP - Pop-Gen Pipeline Platform


​This NSF-funded project in collaboration with Jody Hey and colleagues at Temple University is currently developing a unified bioinformatics platform for end-to-end population genomics analyses using large-scale sequencing data. Additionally, a Galaxy Project based implementation of PPP will be developed to enhance user experience and ease of analyses. ​


Ghost Populations

Unsampled 'ghost' populations have been known to contribute extensively to extant genomic variation across species. These populations may be unsampled due to logistics, or extinction. We are currently systematically quantifying the effects of ghost population admixture on a variety of population genomics analyses.​ Read our recent preprint on this (to be updated soon).

Telomere Length variation in humans

Telomeric repeats have been implicated in numerous processes of cellular senescence, apoptosis, and cancer. We are quantifying the variation in telomere lengths across human populations using data from the 1000 Genome Project.

MigSelect

Differentially introgressing loci are often implicated to be under some form of natural selection, and hypothesized to contain adaptively evolving regions, called "genomic islands". Previously, the inference of these islands has been contentious, with most researchers using summary statistics like Fst in genome-scans. In collaboration with Vitor Sousa, and Jody Hey, I am developing a parallel program for the inference of differential migration (across loci), under the Isolation with Migration (IM) model. We have now analyzed genome-wide patterns of differential migration in several species, including Anopheles gambiae subtypes, Heliconius melpomene wing-pattern morphs, and great apes (P.t. troglodytes versus P.t.verus) Watch this space for updates on this new software! This work is funded by an NIH-R01 grant to Jody Hey. Click the link below to watch my presentation at Evolution 2016 on the new IMSelect program. Also see the preprint.

IMa2p - Parallel MCMC

I developed a parallel framework for ancestral demography inference under a Bayesian Markov Chain Monte Carlo (MCMC) framework. IMa2p has now been released, which distributes chains across multiple processors to efficiently compute divergence times, migration rates, and effective population sizes under the IM model. IMa2p can handle larger haplotypic data-sets (more individuals, more loci, more populations), and is efficient, with nearly linear improvements in computation time with number of processors used. As part of an ongoing collaboration with Sarah Tishkoff at the University of Pennsylvania, I am also currently analyzing the ancestral population demography of African Hunter-Gatherers. See our recent publication here, and download the source code, and instructions on how to install and run IMa2p at my Git page here. This work was funded by an NIH-R01 grant to Jody Hey, and continues to be funded by an NIH-R15 grant to PI Sethuraman.

Population genomics in biocontrol

The predatory convergent ladybird beetle, Hippodemia convergens has been utilized as an insect parasitoid and populations of beetles have been artificially introduced into locations across the Americas. This study focuses on analysis of genetic admixture and patterns of migration of these beetles (either naturally or artificially) supplanted from a potential source population in California, and is currently being undertaken in collaboration with John Obrycki at the University of Kentucky, and several undergraduate students in the Janzen lab. See our recent publication in Biological Control here. Furthermore, we are interested in studying the effects of (a) pervasive inbreeding, (b) cessation of admixture from source populations, and (c) resource competition with other hetero-specific beetles - Harmonia axyridis, and Coccinella septempunctata.This work was funded by a USDA-NIFA grant to John Obrycki, and an Entomological Society of America travel grant to me.

Conservation Genomics

Our lab is interested in broad conservation questions - ranging from large-scale meta analyses of population genomic datasets to understand the relationship between population genomic parameters and the IUCN (conservation) status of animals, to developing predictive models of conservation status from extant genomic and environmental variables. We also collaborate on numerous conservation genomics projects in amphibians, reptiles, and plant species.

Missing Data Problems in Population Genomics

Data is either considered to be
missing if genomic data are absent due to (1) sequencing or genotyping errors, or (2) systematic bias in
the generation of genotyping libraries (e.g. from techniques such as Restriction site Associated DNA
sequencing (RADseq), or (3) the absence of genomic data from unsampled, perhaps extinct “ghost”
populations. Our lab is working on a series of programmatic developments to address all three missing data
problems by accounting for missing data as an unobserved variable in statistical models developed
for the estimation of population genetic parameters and evolutionary history from genomic data.

Genomics of domestication in hops

 With two regional
hop farmers and USDA-ARS, we are (1) cataloging genomic diversity of local hops to assess
their origin, (2) understanding metagenomics of hop farm soil microbiomes to assess microbial community
diversity to identify microbial pathogens, (3) assessing effectiveness of insects in hop integrated
pest management, and (4) understanding hop-virus interactions by assessing the epidemiology,
population genomics of viral infection.