Introduction to the SNP/ND concept - Phylogeny on WGS data

Transcription

1 Introduction to the SNP/ND concept - Phylogeny on WGS data Johanne Ahrenfeldt PhD student

2 Overview What is Phylogeny and what can it be used for Single Nucleotide Polymorphism (SNP) methods CSI Phylogeny Nucleotide Differences NDtree Controlled Evolution study What services for which data

3 What is phylogeny? Early phylogeny Classification Based on phenotypes Current phylogeny Based on genotypes DNA mutations as basis for evolution

4 Classification Classification by Carl Linnaeus Hierarchical system Kingdom Phylum Class Order Family Genus Species

5 Classification depicted as a tree

6 Classification depicted as a tree Species Genus Family Order Class

7 DNA mutations as basis for evolution

8 What are phylogenetic trees Phylogenetic trees are a visual representation of the genetic relationship between species Think of them as family trees Phylogeny can also be represented by distance matrices

9 What are phylogenetic trees Trees were traditionally made using aligned sequences of single genes or proteins Whole genome data can be used to create trees based on SNP calling K-mer overlap

10 What is a SNP A Single Nucleotide Polymorphism (SNP) is a DNA sequence variation occurring commonly* within a population (e.g. 1%) in which a Single Nucleotide A, T, C or G in the genome (or other shared sequence) differs between members of a biological species or paired chromosomes.

11 How does it work Strain A Strain B Strain C Strain D ATTCAGTA ATGCAGTC ATGCAATC ATTCAGTC

12 Construct distance matrix Strain A Strain B Strain C Strain D ATTCAGTA ATGCAGTC ATGCAATC ATTCAGTC A B C D AA B C D

13 Make Tree Strain A Strain B Strain C Strain D ATTCAGTA ATGCAGTC ATGCAATC ATTCAGTC A B C D A B C D Strain A Strain B Strain C Strain D

14 What is phylogeny used for Classify taxonomy The classic use Outbreak detection Increasing with WGS data

15 What is phylogeny used for Cholera outbreak in Haiti 2010 Listeria outbreak 2014 Whole-genome Sequencing Used to Investigate a Nationwide Outbreak of Listeriosis Caused by Ready-to-eat Delicatessen Meat, Denmark, Kvistholm Jensen et al. Clin Infect Dis. (2016) 63 (1): doi: /cid/ciw192

16 Case story Vibrio Cholerae outbreak in Haiti followed the 2010 earthquake Rumors said that the outbreak may have come from Nepal, travelling along with UN soldiers from Nepal No proof had been given of this until the Hendriksen et al. paper in 2011 Popula1on Gene1cs of Vibrio cholerae from Nepal in 2010: Evidence on the Origin of the Hai1an Outbreak. Hendriksen et al. 23 August 2011 mbio vol. 2 no. 4 e doi: /mBio

17 Case story Data 24 recent V. cholerae strains from Nepal 10 previously sequenced V. cholerae isolates, including 3 from the Haitian outbreak Analysis Antimicrobial susceptibility testing PFGE (pulsed-field gel electrophoresis) to analyze for genetic relatedness Whole genome sequencing, snp identification and phylogenetic analysis

18 Case story - Results Resistance profile Suscep5ble Decreased suscep5bility Nepalese strains Hendriksen et al Resistant Tetracycline Ciprofloxacin Trimethoprim, Sulfamethoxazole Nalidixic Hai1an outbreak strains Centers for Disease Control and Preven1on, 2010 Tetracycline Ciprofloxacin Trimethoprim, Sulfamethoxazole Nalidixic

19 Case story - Results PFGE Nepalese isolates divided in 4 clusters

20 Case story - Results

21 snptree First online webserver for constructing phylogenetic trees based on whole genome sequencing snptree- - a web- server to iden1fy and construct SNP trees from whole genome sequence data. Leekitcharoenphon P, Kaas RS, Thomsen MC, Friis C, Rasmussen S, Aarestrup FM. BMC Genomics. 2012;13 Suppl 7:S6.

22 snptree flow

23 CSI Phylogeny SNP identification same as snptree Strict sorting of SNPs Depth Relative depth Distance between SNPs SNP quality Read mapping quality Rolf S. Kaas, Pimlapas Leekitcharoenphon, Frank M. Aarestrup, Ole Lund. Solving the Problem of Comparing Whole Bacterial Genomes across Different Sequencing Pla`orms. PLoS ONE 2014; 9(8): e

24 CSI Phylogeny Requires all SNPs to be significant Z-score higher than 1.96 for all SNPs Z = X Y X+Y X is the number of reads, with the most common nucleotide at that position, and Y the number of reads with any other nucleotide.

25 CSI Phylogeny Output Tree build by FastTree algorithm, in Newick format Branch lengths is substitutions per site at the variable sites Matrix of SNP pair counts in text (.txt) format Diagonal SNP matrix

26 CSI Phylogeny

27 NDtree Nucleotide calling A different approach where the main distinction is not between if a SNP should be called or not, but between whether or not there is solid evidence for the nucleotide at the given position. Real- Time Whole- Genome Sequencing for Rou1ne Typing, Surveillance, and Outbreak Detec1on of Verotoxigenic Escherichia coli. Joensen KG, Scheutz F, Lund O, Hasman H, Kaas RS, Nielsen EM, Aarestrup FM. J Clin Microbiol May;52(5):

28 NDtree Simple mapping approach Cuts all reads into K-mers Maps all K-mers to reference genome Makes an ungapped consensus sequences of equal lengths

29 NDtree Nucleotide calling When all reads have been mapped the significance of the base call at each position was evaluated by calculating the number of reads X having the most common nucleotide at that position, and the number of reads Y supporting other nucleotides. A Z-score threshold was calculated as: Z = X Y X+Y > 1.96 (or 3.29) >90% of reads supporting the same base

30 NDtree Count nucleotide differences Method 1: Each pair of sequences was compared and the number of nucleotide differences in positions called in all sequences was counted. More accurate (Z=1.96 is used as threshold) Method 2: Each pair of sequences was compared and the number of nucleotide differences in positions called in both sequences was counted. More robust (Z=3.29 is used as threshold)

31 NDtree Uses two different algorithms to make two different trees UPGMA Neighbor Joining Both algorithms are part of the PHYLIP Neighbor program package and make trees from distance matrices

32 UPGMA vs. Neighbor Joining UPGMA works when samples have been taken the same time Neighbor Joining is better when samples have been taken at different times

33 NDtree Output distance.txt: Distance matrix - tab separated dist.mat: Distance matrix - PHYLIP format tree.nj.newick: Neighbor Joining tree - Newick format Branch lengths is number of Nucleotide Differences tree.upgma.newick: UPGMA tree Newick format Branch lengths is number of Nucleotide Differences

34 Johanne Ahrenfeldt, Master thesis. Controlled Evolution study

35 Naming the descendants

36 Mutations

37 Phylogenetic tree using NDtree (UPGMA)

38 Phylogenetic tree using NDtree (Neighbor Joining)

39 UPGMA vs. Neighbor Joining UPGMA works when samples have been taken the same time Neighbor Joining is better when samples have been taken at different times

40 CSI Phylogeny Default settings 1_1_1_1 1_1_1_2 1_1_1 1_1_2_1 1_1_2_2 1_1_2 1_1 1_2_1 1_2_2_1 1_2_2_2 1_2_2 1_2 1 c_1_1_1_2_1 e_1_1_2_1_1 f_1_1_2_1_2 f_2_1_1 g_1_1_2_2_1 h_1_1_2_2_2 m_1_2_2_1_1 n_1_2_2_1_2 o_1_2_2_2_1 d_1_1_1_2_2 b_1_1_1_1_2 1_2_1_1 i_1_2_1_1_1 1_2_1_2 k_1_2_1_2_1 l_1_2_1_2_2 a_1_1_1_1_1 j_1_2_1_1_2 b_1_2_2 0.2

41 CSI Phylogeny Pruning disabled 1 1_2 1_1 1_1_1 1_2_2 1_2_2_2 o_1_2_2_2_1 1_2_2_1 m_1_2_2_1_1 n_1_2_2_1_2 l_1_2_1_2_2 1_2_1_2 k_1_2_1_2_1 i_1_2_1_1_1 1_2_1_1 j_1_2_1_1_2 1_2_1 1_1_1_2 1_1_2_2 g_1_1_2_2_1 h_1_1_2_2_2 1_1_2 e_1_1_2_1_1 1_1_2_1 f_1_1_2_1_2 c_1_1_1_2_1 1_1_1_1 a_1_1_1_1_1 d_1_1_1_2_2 b_1_1_1_1_2 b_1_2_2 f_2_1_1 0.2

42 So What should I use when? CSI Phylogeny has very good statistics and a good graphical overview. It is advantageous to use when you expect the differences between the isolates to be larger than 5-10 mutations. NDtree is able to find these small differences. But it does not take recombination into consideration.

43 Choosing a reference genome For comparison of very closely related isolates, a better level of detail is given by using a closely related reference genome.

44 Questions? Thank you for listening