[All-postdocs] Biology Seminar next week: JP students Arianna Krinos and Ciara Willis

[Margot McKlveen]

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*Biology Department Virtual Seminar*

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Thursday, May 27 at Noon

Zoom link: 
https://whoi-edu.zoom.us/j/93395960738?pwd=Y0VtaFh5SG9vcU1uSWJVOU1xZFEyQT09 
<https://whoi-edu.zoom.us/j/93395960738?pwd=Y0VtaFh5SG9vcU1uSWJVOU1xZFEyQT09>


MIT-WHOI Joint Program students

Arianna Krinos: “Eukrhythmic: leveraging the metatranscriptomic 
landscape to reproducibly detect and describe marine protistan communities”

Ciara Willis: “Comparing estimates of larval dispersal in a coral reef 
fish derived from a coupled biophysical model and DNA parentage analyses”


Arianna Krinos - Eukrhythmic: leveraging the metatranscriptomic 
landscape to reproducibly detect and describe marine protistan communities

Metatranscriptome analysis, the processing and interpretation of 
transcribed sequences from a biological community, has emerged as a 
promising approach to answer questions about natural microbial 
communities without prior knowledge or bias. Metatranscriptomes are an 
accessible means to characterize a more complete suite of expressed 
genes. Despite the potential of this technology, processing methods are 
relatively new, and often focused on RNAseq data from single-organism 
transcriptomes or prokaryotic communities, not mixed eukaryotic systems. 
As more metatranscriptomes are collected in oceanographic surveys, it is 
crucial to generate metatranscriptome-specific tools to improve study 
reproducibility and comparability. Here, we introduce eukrhythmic, a 
Snakemake-based metatranscriptome processing pipeline designed to 
address common problems in analyzing marine or other environmental 
samples. Using multiple assembly methods and tandem sample processing, 
eukrhythmic minimizes assembly bias, and enables rapid collation of 
samples from multiple sites. The pipeline enables functional and 
taxonomic annotation with special consideration of microbial eukaryotes, 
and provides a curated assembly that can be integrated with 
metaproteomic data. In particular, we show how the pipeline can be 
applied to understand a diel metatranscriptomic time series from the 
Western Antarctic Peninsula, and emphasize how metatranscriptomics can 
provide deep insight into the diversity and ecology of these samples.


Ciara Willis - Comparing estimates of larval dispersal in a coral reef 
fish derived from a coupled biophysical model and DNA parentage analyses

The dispersal of pelagic larvae is a defining feature of the life 
histories of many marine species, including coral reef fishes. Resolving 
the dispersal of these larvae and the resulting connectivity of reef 
fish populations is a major focus in ocean ecology and is of critical 
importance to the effective design and implementation of marine reserve 
networks. Larval surveys, population genetics, hydrodynamic modelling, 
and tagging have all been used to infer population connectivity among 
reefs, with varying degrees of success. Development of DNA parentage 
analyses has produced direct estimates of population connectivity in 
reef fishes but with considerable logistical investment in field and lab 
work. Coupled biophysical modelling can potentially be used to track 
virtual larvae of any reef fish species but requires a number of 
assumptions that remain to be tested. Here, I leverage an existing DNA 
parentage dataset to test the skill of a coupled biophysical model to 
estimate larval dispersal of the vagabond butterflyfish (Chaetodon 
vagabundus) in Kimbe Bay, PNG. I used an embedded particle tracking 
module in the Finite Volume Coastal Ocean Model (FVCOM) system to 
estimate dispersal of virtual butterflyfish larvae with simplistic 
behaviour and spatially invariant mortality. The rare opportunity to 
test biophysical model results against empirical data is of value not 
just to future work in Kimbe Bay, but also for future use in sites where 
field sampling is cost-prohibitive or logistically difficult.


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*

-- 
Margot McKlveen | she/her
Senior Administrative Assistant
Woods Hole Oceanographic Institution
Redfield Building Room 305 | MS 32
266 Woods Hole Rd.
Woods Hole, MA 02543
508-289-2334
mmcklveen at whoi.edu

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