Rittschof, Clare C

Rittschof Lab Introduction

The Rittschof lab studies honey bee behavior through an integrative lens, examining the influences of gene expression, social experience, and environmental factors on the individual as well as the colony. Projects include the effects of the developmental environment and past life experiences on future behavior and physiological state of an individual, decision making and communication in foraging and robbing behaviors in different contexts, and examining how the brain and peripheral tissues such as the fat body interact to influence complex behaviors. The lab also works with wild bee populations and measuring their abundance, as well as wild bee responses to pesticides and agriculture. We also have connections with local beekeepers for projects such as studying honey bee viral infections, as well as outreach opportunities.

Analysis of changes in spatial gene expression patterns in high aggression verses low aggression bees  

This project will use a previously published data set from Rittschof et al. (2019) [BioProject PRJNA562696], which consists of Illumina RNASeq reads from the brains, midguts, and fatbodies of either low or high aggression bees. This project will analyze this data in two ways to determine what spatial patterns and relationships are changed or lost with differences in aggression. First we will do pairwise analyses between the three tissue types and look for the non-overlapping DEG’s between the two conditions. We will also analyze this data as if it were a time series, by clustering this “spatial series” across the three tissues and determining what genes change clusters between the two conditions.

Personnel:

PI - Dr. Clare Rittschof

Student:

Anastasia Weger, Graduate

Software:

Available through the MCC singularity – HISAT2, samtools, stringtie

Available through Bioconductor – DESeq2

Available in Browser – g:profiler, REVIGO

Comparison of tau gene expression between conditions that can impact learning and memory

This project will focus on the microtubule-associated protein tau, which has been implicated in Alzheimer’s disease, and has been linked to memory and learning behaviors. We will find and use previously published RNASeq data sets available on NCBI for honey bee brain tissue that have conditions that could also affect memory and learning, such as pesticide exposure (Tsetkov and Zayed, 2021) or disease/parasite presence (Doublet et al., 2016), and compare tau expression with control data sets.

Personnel:

PI: Dr. Clare Rittschof

Student:

Anastasia Weger, Graduate

Abdallah Sher, Undergraduate

Software:

Available through the MCC singularity – HISAT2, samtools, stringtie

Available through Bioconductor – DESeq2

Determining the predictors of gene expression profiles associated with aggressive behavior

This project is investigating how predictive adult fatbody content and brain DNA methylation pattern are of aggressive behavior, gene expression profiles, and response to new information. For this, we will need to analyze RNASeq data to characterize brain gene expression for honey bees of different caste and age mixes, as well as bisulfite sequencing data to analyze DNA methylation pattern. We will use the RNA and bisulfite sequencing data to create a GLMM, as well as find DEG’s between different bee types and time points.

Personnel:

PI: Dr. Clare Rittschof

Student:

Anastasia Weger, Graduate

Software:

Available through the MCC singularity – HISAT2, samtools, stringtie, Bismark

Available for download – bicycle (https://www.sing-group.org/bicycle/download.html)

Available through Bioconductor – DESeq2, glmmSeq

DNA Metabarcoding of Pollen Samples

This project seeks to use DNA metabarcoding to identify and quantify pollen present in mixed pollen samples collected from honey bee hives. Pollen present in each sample will be identified to the lowest taxonomic level, and used to determine the major sources of pollen collected by honey bee colonies located in areas that differ in floral abundance.  We will be using a pipeline adapted from Richardson et al., 2015.

Personnel:

PI: Dr. Clare Rittschof

Students:

Chelsea V Pretz, Postdoc, Added on the MCC cluster 04/17/2023 

Collaborator:

Dr. Rodney Richardson (University of Maryland, Assistant Professor of Molecular Ecology)

Software:

Available through the MCC singularity – Fastx-toolkit, blast

Available for download – PEAR (https://cme.h-its.org/exelixis/web/software/pear/), MEGAN (https://www.wsi.uni-tuebingen.de/lehrstuehle/algorithms-in-bioinformatics/software/megan6/)

Publications:

Doublet V, Paxton RJ, McDonnell CM, Dubois E, Nidelet S, Moritz RF, Alaux C, Le Conte Y. Brain transcriptomes of honey bees (Apis mellifera) experimentally infected by two pathogens: Black queen cell virus and Nosema ceranae. Genom Data. 2016 Sep 28;10:79-82. doi: 10.1016/j.gdata.2016.09.010. PMID: 27747157; PMCID: PMC5054260.

Richardson, R.T., Lin, C., Sponsler, D.B., Quijia, J.O., Goodell, K., Johnson, R.M. Application of ITS2 metabarcoding to determine the provenance of pollen collected by honey bees in an agroecosystem. Applications in Plant Sciences. 2015, Jan 3;1:1400066. https://doi.org/10.3732/apps.1400066

Tsvetkov N, Zayed A. Searching beyond the streetlight: Neonicotinoid exposure alters the neurogenomic state of worker honey bees. Ecol Evol. 2021 Dec 20;11(24):18733-18742. doi: 10.1002/ece3.8480. PMID: 35003705; PMCID: PMC8717355.