Metabarcoding16S RNA targeted sequencing

Peter TsaiBioinformatics Institute, University of Auckland

What’s metagenomics and metabarcoding? Next generation sequencing and

metabarcoding How NGS changes metagenomics

Analysis approach Taxonomic dependent and independent analysis

Study example NZ vine yeast biogeography by pyrosequencing

Overview

Metagenomics Study of metagenomes, genetic materials directly from

environmental samples. Shotgun metagenomics

◦ Randomly shears DNA, sequence many different species in environment and attempts to reconstruct multiple genomes.

Metabarcoding Subset of metagenomics. Study of one or more marker gene. Gene specific primers to ‘barcode’ that gene, i.e. 16S, ITS or CO1 Aim is often to identify different species and compare different

community

Metagenomics

Accelerated by NGS, predominately 454 sequencing because of the longer read length, now more with Illumina based chemistry.

Organism no longer needs to be cultivated and cloned — Culture independent insight

Direct sequencing from environment as a “community” You can pool multiple samples together

NGS and metagenomics

Not all microbes can be cultured

Analysis approach

Taxonomy independent analysis Reads are group into operational taxonomic units (OTU)

based on a specified sequence variation.

Taxonomy dependent analysis Assignment at the level of domain, phylum, class, order,

family, genus, and species Require a reference database

Analysis approach

Group reads into OTU based on certain imposed similarity threshold In study of bacteria, 97% seems like a good starting point Species dependent, genes dependent, threshold may vary 1 OTU = 1 organism

Extract a OTU representative sequence Most common sequence Sequence that has minimum difference to all other

sequences in the same OTU

Taxonomy independent analysis

Classify sequences BLAST

Simply BLAST what you have

Online RDP classifier (Ribosomal Database Project ) RDP 10.26 (Release 10, Update 26 consists of 1,613,063 aligned and

annotated 16S rRNA sequences Limited by number of reads you can submit

Online Greengenes classifier based on NAST alignment Require pre-aligned dataset Limited by number of reads you can submit

Taxonomy dependent analysis

NZ vine yeast biogeography by pyrosequencing

M. W. Taylor, N. Anfang, A. H. Thrimawithana, P. Tsai, H. Ross and M. R. GoddardSchool of Biological Sciences, University of Auckland

Yeasts are the agents responsible for fermentation of fruits into wine

Yeasts naturally associated with vines and wines are reasonably well characterised

Microbes have an effect on both vine and fruit development (as some are pathogens), as well as the resulting wine quality and style

Investigations into the ecology of these organisms is lacking.

NZ vine yeast biogeography by pyrosequencing

Vitis vinifera

6 distinct vineyards in each of four major and distinct wine-producing regions West Auckland (WA) Hawke’s Bay (HB) Marlborough (MB) Central Otago (CO)

26S RNA gene from DNA directly extracted from microbial communities associated with ripe Chardonnay fruit

NZ vine yeast biogeography by pyrosequencing

Quality checks◦Remove short reads◦Remove reads containing ambiguity◦ Trim off low quality regions

Taxonomy independent analysis◦No well established reference database for eukaryotic 26S◦ Clustering into 98% OTU◦ANOSIM for statistical test between regions◦ Limited classification rely upon NCBI Taxonomy DB

NZ vine yeast biogeography by pyrosequencing

2,000 species were found using deep sequencing across all regions. Culture based analysis recovered 7 species from West Auckland and

Hawke’s Bay Deep sequencing identified ~700 from the same West Auckland and

Hawke’s Bay sample. All 7 species were found in pyrosequencing dataset

The culture-based may miss ~99% of the community

NZ vine yeast biogeography by pyrosequencing

Central Otago

West Auckland

Hawke’s Bay

Marlborough

Central Otago harbours the most distinct community

Different communities associated with Chardonnay vines in different areas of NZ

Community similarity significantly decays with distance and temperature

Different regions harbour different communities, may, in part, contribute to the distinctiveness of wines deriving from that area.

Geographic patterns for yeast communities

Number of reads needed Statistical power

Over estimating due to sequencing error Results in large number of OTUs

Multiple copies of 16S rRNA gene in some species Lead to overrepresentation

Accuracy of taxonomic classification Not all rRNA genes amplify equally well with the same

“universal” primers

Key questions associated with Metagenomics

Basic introduction, basic method, one of many ways of analysing metabarcoded dataset.

Increasingly popular way of extracting the genomes of micro-organisms.

Direct insight into communities without the need of culturing

Culture based and sequencing based method may recover different proportion of organisms

Summary