The Sethuraman Lab recently joined the Evolutionary Biology group at SDSU - special thanks to Dr. Kevin Burns and his partner for hosting a welcome party at their place. We look forward to years of fun science and collaboration with  the team!

We are actively recruiting TWO PhD students via the Joint Doctoral Program in Evolutionary Biology at SDSU (collaboratively offered with University of California Riverside), and TWO Masters students via the Biological and Medical Informatics Graduate Program at SDSU, both starting Fall 2022.
 
Dr. Sethuraman will work with all graduate students to develop their project(s) which can broadly span the fields of genomics, bioinformatics, and evolutionary biology.
 
Please write to Dr. Sethuraman (asethuraman@sdsu.edu) with a copy of your CV/Resume, a brief statement of interest, and let’s chat more.
 
We are committed to recruiting a diverse group of scientists to join my lab group – so we highly encourage folks who identify as a part of historically underrepresented groups to apply. This includes (non-exhaustively) people of color, international students, Veterans of armed forces, student-parents/caregivers, first-generation degree holders, the LGBTQIA+ family, and folks with medical conditions and disabilities.
 
                                                                     Description of Doctoral positions
 
Start Date: Fall 2022
 
Application Deadline: December 15, 2021
 
Requirements/Qualifications:
 
A Bachelors or Masters degree in Biology/Bioinformatics/Genetics/Computer Science/Statistics, or a related field. Knowledge and experience in scientific programming using C/C++/Python is highly encouraged, but not necessary.
As of 2020, the GRE is no longer required for admissions to the program, but international students are required to submit scores from the TOEFL. More information about admission requirements and procedures can be found at: http://www.bio.sdsu.edu/eb/jdapplications.html
 
Position 1: Funded by NSF CAREER #2042516 to PI Sethuraman
 
We currently have an opening for a PhD student (with research funding for ~5 years) to work on projects developing new statistical methods, software, and pipelines for estimation of population structure, relatedness, and evolutionary history from large scale population genomic data while accounting for missingness. Specifically, we will address missingness due to (1) genotyping/variant calling errors, (2) allele dropout in genotyping by sequencing methods – e.g. RADseq, and (3) gene flow from unsampled “ghost” populations.
 
Position 2: Funded by NIH R15 #1R15GM143700-01 to PI Sethuraman
 
This PhD student (with research funding for ~5 years) will work on projects in human population genomics, focused on developing new statistical methods, software, and pipelines for analyses of large scale human genomic data to (1) accurately estimate population structure in the presence of archaic gene flow, (2) analyze large human genomic datasets to quantify archaic variation, and (3) understanding patterns of natural selection and adaptation at introgressed archaic variants and haplotypes across humans.
 
                                                                         Description of Masters positions
 
Start Date: Fall 2022, and subsequent Fall terms
 
Application Deadline: March 1, 2022
 
Requirements/Qualifications:
A Bachelors degree in Biology/Bioinformatics/Genetics/Computer Science/Statistics, or a related field. As of 2020, the GRE is no longer required for admissions to the BMI program. More information about admission requirements and procedures can be found at: https://informatics.sdsu.edu/admissions/.
 
We are looking to recruit TWO enthusiastic Masters students to work on various population genomics projects.
 
Current “Wet” Lab Projects

1. Population genomics of invasive lady beetles (Coleoptera: Coccinellidae)
2. Evolutionary history of domestication of hops (Humulus lupulus)
 
Current “Dry” Lab Projects (Data Analyses)

3. Annotation, phylogenomic history using the genome of the convergent lady beetle (Hippodamia convergens)
4. Population genomics of a parthenogenetic parasitoid wasp, Dinocampus coccinellae using Ultra Conserved Elements
5. Population genomics of several other species of lady beetles (Coleoptera: Coccinellidae), including Hippodamia convergens, Harmonia axyridis, Propylea quatrodecimpunctata, and Hippodamia variegata
6. Identifying and understanding the evolutionary history in regions of modern human genomes that are of “archaic” (e.g. Neanderthal) ancestry
 
Current “Dry” Lab Projects (Software Development/Testing)

7. Testing of PPP – the Pop-Gen Pipeline Platform, developing Jupyter Notebooks on publicly available RADseq datasets (Python)
8. Development, deployment, testing of a PPP GUI via The Galaxy Project (usegalaxy.org) (Python/XML)
9. Testing p-MULTICLUST, a parallelized method for estimating population structure (C, Python)
10. Developing a new software for estimating genetic relatedness (C/C++/Python)
 
 Come join us!

Andrew recently presented his Summer research describing the assembly and annotation of the convergent lady beetle (Hippodamia convergens) genome, and phylogenomic history of Coleoptera at the CSUSM Summer Research Symposium. Congrats, Andrew! We are so proud of his accomplishments in such a small period of time, and wish him the best as he heads back to IU Bloomington!

Alicia successfully defended her Masters thesis titled "How far does the apple fall from the tree? Evolutionary genetics and the heritability of body size morphology in the parasitoid wasp Dinocampus coccinellae"! One of her chapters is already in review, and we're working on getting her other chapter submitted in the coming weeks. We are so proud of Alicia and her accomplishments, and wish her the best in her bright future!

The Sethuraman Lab will move to the Department of Biology at San Diego State University in Fall 2021! Dr. Sethuraman will be affiliated with the Evolutionary Biology group, and the Interdisciplinary Graduate Program in Biological and Medical Informatics. We will be hiring several PhD and Masters students soon - stay tuned for job announcements in coming months! 

Dr. Sethuraman recently received an NIH R15 Award titled "The Architecture of Missing Variation in Human Population Genomic Data"! The grant will fund the development of methods to (1) estimate archaic population structure, (2) evolutionary history which includes gene flow from archaic "ghost" genomes, as well as (3) quantifying the architecture of archaic ancestry in modern human populations across the world.  More exciting times! 

Hearty congratulations to all Sethuraman Lab graduates - Michelle, Gwen, Alicia, Theresa, and Ben - here are some photos from commencement! We wish you all the brightest futures ahead!

Dr. Sethuraman was just awarded the prestigious NSF CAREER Award which will fund the next five years of computational research in our lab! This grant will focus on the development of novel computational methods to deal with three types of missing data - (1) data missing at random due to genotyping or sequencing errors, (2) data missing due to reduced representation sequencing techniques and allele dropout (e.g. RADseq), and (3) data missing due to extinction (e.g. "ghost" variants from extinct lineages into extant sampled lineages). Exciting times! His award was also recently featured by CSUSM news.

Our new study on the demographic composition and gaps in Diversity, Equity, and Inclusion efforts in three evolution societies (SSE, ASN and SSB) has now been published in Evolution. Read the published article here, and do let us know your thoughts and recommendations for bridging these gaps in the future.

Our long awaited PPP release manuscript has now been accepted for publication in Molecular Biology and Evolution! This paper describes our first release of a comprehensive pipeline for all things population genomics - starting from a VCF file, to performing numerous population genomics analyses. Congratulations to all Sethuraman and Hey Lab folks that have contributed to this project over the years - Andrew Webb, Jared Knoblauch, Apeksha Sukesh Kallur, Nitesh Sabankar, Jonathan Tedjo. You can read the preprint here, and also check out PPP's first release here. This work was funded by NSF ABI 1564659 to Arun Sethuraman and Jody Hey.