edna and plant pathogen metabarcoding · edna metabarcoding applications •specific organisms...

eDNA and Plant Pathogen Metabarcoding

Use of Technology in the Natural Environment

SNH Sharing Good Practice day – June 7 2017

David Cooke Leighton Pritchard & Peter Thorpe Sarah Green

Tree Health and Plant Biosecurity initiative

Terminology

eDNA • Total DNA extracted from organisms in an

environmental sample

• skin, water, soil, air, gut contents, pollen sac, etc....

• Contemporary samples, permafrost, sediments

NGS/HTS • Next Gen sequencing/ High throughput sequencing

• Technology - Illumina, Ion Torrent, Nanopore, SMRT

Metagenomics

• Sequencing all DNA in eDNA sample

By Abizar at English Wikipedia, CC BY-SA 3.0

What is metabarcoding?

• Barcoding is a means of discriminating organisms

based on short DNA sequence differences

Species 1 CCACACTGAGCTAAGGCCTTTAA

Species 2 CCACACAGAGGTAAGGCCATTAA

• Metabarcoding - massive increase in

throughput due to advancing sequencing

technology and reduced prices per base pair

Oxford Nanopore Technologies

eDNA metabarcoding applications

• Specific organisms

• Great crested newt surveys

• Biosecurity – search for quarantine organisms

• Biodiversity inventory - conservation monitoring

• Surveys of fish, fungi, YFO etc

• Research projects

• How does a specific treatment affect biodiversity

Metabarcoding – some pros and cons

• High throughput

• Massively parallel – indexing

• Identifies most species (barcode resolution)

• Identifies organisms that cannot be cultured

• Can share DNA samples – synergy between projects

Some challenges

• Need good sampling and replication

• Will not identify hybrid species

• Error rates and contamination risks – false positive and false

negatives

• Blind acceptance is risky – validation needed

• Data storage and computational biology resources are critical

Method Tool

DNA extraction/ PCR

DNAseq

QC, Trim, Chimera detection

Assemble reads

Error correction Bayes Hammer

Nested PCR

Illumina overlapping reads

Fastqc, Trimmomatic, Vsearch

Flash / PEAR

Convert FQ, FA & Trim primers

Cluster

Seqcrumbs, Biopython

Swarm CD-HIT Vsearch Bowtie

Blastclust

Python: sklearn

Compare clustering

Graphics

Summarise species Python

Identify species found by all methods,

Or what was unique to each method

Leighton Pritchard & Peter Thorpe

Reference database (any)

Coded in Python - will be released on GitHub

Computational biology pipeline

Case Study - Phytophthora

• 167 species – destructive plant pathogens • 16 species on UK plant health risk register

Dave Rizzo Youtube.com California Oak Mortality Task Force

Phytophthora zoospore detection

Sampling water

• Irrigation water

• Water flooded through roots of pot-grown plants

• Rivers

Filtration

• Cellulose acetate filters

• DNA extraction

• PCR - Phytophthora genus specific primers

• Sequencing (high or low throughput)

• Invergowrie Burn (IGB) sampled 56 times (every 2 weeks) over 2 years at a single sample point

• Filter DNA extracted and PCR with Phytophthora specific primers

• Run on Illumina MiSeq with v2 chemistry (896K 250bp reads)

• 30 known and 31 unknown Phytophthora species detected

Past success…

Some species abundant all year

Quantitative when considering frequency of occurrence between samples

Winter months

P. xcambivora lower frequency all year

Winter months

Unknown clade 4 species – summer only

Winter months

Herbaceous downy mildew (nettle) summer only

Mycorrhizal Fungi in Montane Heaths

Dr Andy Taylor – James Hutton Institute, Aberdeen

Arctostaphylos alpinus

Salix herbecea

Arctostaphylos uva-ursi

Betula nana

Ectomycorrhizal Host species

36 new records for Scotland (28 UK)

23 taxa are undescribed - new to science

257 ECM taxa recorded

80 taxa appear restricted to the habitat

Alpine Ectomycorrhizal Fungi

Highly diverse, but poorly recorded

communities, restricted to a rapidly

declining habitat in Scotland.

Emily Carroll

Current Projects at Hutton

• Tree Health and Plant Biosecurity III

• UK Nursery testing

• Environmental diversity

• Baseline testing natural ecosystems

• Aids interception decisions

• Watershed sampling (WP1.3)

• Targeted sampling of catchment

WP1.3.3 Monitoring ECN sites

Environmental monitoring

THAPBI II nursery sampling

• 3 sites at 5-6 locations covering a range of habitats

• Additional key sites with help of Jenny Park (SNH)

Example 1

Hänfling et al., 2016 Environmental DNA metabarcoding of lake fish communities reflects long-term data from established survey methods. Molecular Ecology 25 3101-3119

• eDNA (14 species) better

than conventional gill-

netting (4 species)

• Interpretation challenges