Development of an Environmental Metagenetics Approach for

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Transcript Development of an Environmental Metagenetics Approach for

Nathan Evans, Mark Renshaw, Cameron Turner, Brett Olds, Yiyuan Li, Christopher Jerde, Gary Lamberti, Michael Pfrender, and David Lodge University of Notre Dame

Develop a novel and practical method for monitoring aquatic species richness using molecular genetic tools, that:

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has better detection limits than traditional tools does not require handling of organisms produces results rapidly provides input into statistical models that can produce rigorous estimates of species richness

1 Collect water sample 2 Filter water sample 3 Extract all DNA 4 Amplify target DNA

Amplicon Lengths Cytb #1 ~413 bp 12s #1 #2 16s #1 #2 #3 ~241 bp ~385 bp ~202 bp ~310 bp ~330 bp

Cytb 12s 16s

Suite of 6 Markers

1 Collect water sample 2 Filter water sample 3 Extract all DNA 4 Amplify target DNA 5 Sequence amplicons & Screen for species

Data Prep Step

Raw reads from Miseq Cytb #1 16s #1 12s #1 16s #2 12s #2 16s #3 Filtering of reads

Data Prep Step

Raw reads from Miseq Cytb #1 16s #1 12s #1 16s #2 12s #2 16s #3 Filtering of reads Known species Map to reference Unmapped reads

Analysis Step

Data Prep Step

Raw reads from Miseq Cytb #1 16s #1 12s #1 16s #2 12s #2 16s #3 Filtering of reads Known species Map to reference Unmapped reads

Analysis Step

Unknown species Create OTUs Compare to Genbank Report of species

• • •

Testing Scenarios Mesocosm communities Well censused natural communities

Stream ecosystem

Pond ecosystem Natural communities with unknown species assemblages

Objective: Determine if our metagenetic approach can be used to accurately measure species richness in mesocosms with differing assemblage structures

Treatment Population Densities

Even Abundance

50 40 30 20 10 0 FHM BLG GAM KOI BFT

Species

CKC CSR BST WSK Even-High Even-Low

Skewed Abundance

50 40 30 20 10 0 FHM BLG GAM KOI BFT

Species

CKC CSR BST WSK Skewed-High Skewed-Low All nine species were detected!

Fathead Minnow (FHM) Bluegill Sunfish (BLG) Eastern Mosquitofish (GAM) Common Carp (KOI) White Sucker (WSK) Creek Chub (CKC) Central Stoneroller (CSR) Blackstripe Topminnow (BST) Bullfrog Tadpole (BFT)

Objective: Determine if our metagenetic approach can accurately describe the fish species richness of a highly censused natural stream ecosystem

Number of years (out of 17) each species was sampled during annual electrofishing collections Species # of years

Creek chub (

Semotilus atromaculatus

) Mottled sculpin (

Cottus bairdii

) Johnny darter (

Etheostoma nigrum

) Blacknose dace (

Rhinichthys atratulus

) White sucker (

Catostomus commersonii

) Green sunfish (

Lepomis cyanellus

) Rainbow trout (

Oncorhynchus mykiss

) Brown trout (

Salmo trutta

) Rock bass (

Ambloplites rupestris

) Smallmouth bass (

Micropterus dolomieu

) Bluegill sunfish (

Lepomis macrochirus

) Largemouth bass (

Micropterus salmoides

) Hybrid sunfish (

L. macrochirus

X

L. cyanellus

) Pumpkinseed sunfish (

Lepomis gibbosus

) Yellow perch (

Perca flavescens

) Central mudminnow (

Umbra limi

) Rainbow darter (

Etheostoma caeruleum

) Warmouth (

Lepomis gulosus

) Hybrid sunfish (

L. gibbosus

X

L. cyanellus

) Golden shiner (

Notemigonus crysoleucas

) 17 17 17 17 17 17 15 13 11 11 10 6 5 4 3 2 2 1 1 1

• Four 60-m reaches with block nets Triple-pass backpack electrofishing

Flow

Blacknose dace Creek chub Johnny darter Rainbow darter Mottled sculpin Bluegill sunfish Green sunfish Rock bass Smallmouth bass Brown trout Rainbow trout White sucker

Additional eDNA

Largemouth bass Yellow bullhead Common carp

 All 12 species detected by electrofishing were detected by metagenetic sequencing. 3 species were detected only by eDNA.

Species richness (S) is the number of unique species found in a defined area. We are using the bias-corrected Chao II estimator for incidence data: 𝑛 − 1 𝑆 𝐶ℎ𝑎𝑜2 = 𝑆 𝑜𝑏𝑠 + 𝑛 + 𝑞 1 (𝑞 1 2(𝑞 2 + 1) + 1) Estimated species richness Correction for small sampling effort Observed species richness Estimated number of unobserved species from rare occurrences q 1 = Number of species found in only one sample q 2 = Number of species found in only two samples

Electrofishing eDNA eDNA (15) Electrofishing (12)

Objective: Determine if our metagenetic approach can accurately describe the fish and amphibian species richness of a thoroughly sampled natural pond within a military property

Common Name Black crappie Blackchin shiner Blacknose shiner Bluegill sunfish Bluntnose minnow Bowfin Brown bullhead Central mudminnow Common carp Golden shiner Grass pickerel Green sunfish Iowa darter Lake chubsucker Largemouth bass Northern Pike Northern redbelly dace Pugnose shiner Pumpkinseed sunfish Redear sunfish Sand shiner Tadpole madtom Warmouth White sucker Yellow bullhead Yellow perch Scientific Name

Pomoxis nigromaculatus Notropis heterodon Notropis heterolepis Lepomis macrochirus Pimephales notatus Amia calva Ameiurus nebulosus Umbra limi Cyprinus carpio Notemigonus crysoleucas Esox americanus vermiculatus Lepomis cyanellus Etheostoma exile Erimyzon sucetta Micropterus salmoides Esox lucius Phoxinus eos Notropis anogenus Lepomis gibbosus Lepomis microlophus Notropis stramineus Noturus gyrinus Lepomis gulosus Catostomus commersonii Ameiurus natalis Perca flavescens

Lawler Pond eDNA Samples

Pumpkinseed sunfish Bluegill sunfish Blackchin shiner Yellow bullhead Largemouth bass Grass pickerel White Sucker Common carp

Traditional eDNA Additional eDNA

Green sunfish Warmouth Central mudminnow Brook stickleback Creek chub Golden shiner Fathead minnow

• We have identified additional locations at Ft. Custer and Camp Pendleton to serve as our first application of the metagenetic approach in natural ecosystems with unknown species richness. eDNA sampling is planned for 2015.

• We hope to refine our approach to provide the DoD with an accurate and cost-effective tool for monitoring aquatic biodiversity at military sites across the nation.

Field and lab assistance: Crysta Gantz, Matt Dougherty, Mary Hupka, and Karen Uy

Contact Information:

Nathan Evans University of Notre Dame [email protected]