EEB BootCamp 2020

Bioinformatics Boot Camp for Ecology & Evolution: Genomic Epidemiology Thursday, Aug 6, 2020, 2 - 3:30pm Instructors: Dr Weigang Qiu & Ms Saymon Akther Email: weigang@genectr.hunter.cuny.edu Lab Website: http://diverge.hunter.cuny.edu/labwiki/

CoV Genome Tracker	Coronavirus evolutuon	Lyme Disease (Borreliella)
Haplotype network	Spike protein alignment	Gains & losses of host-defense genes among Lyme pathogen genomes (Qiu & Martin 2014)

---

Case studies

• Covid-19 Genome Tracker
• Comparative genomics of worldwide Lyme disease pathogens

1. Is it necessary to mention nextstrain?

• Next Strain

Bioinformatics tools for genomic epidemiology

Required for the tutorial

• bcftools: Reading/writing BCF2/VCF/gVCF files and calling/filtering/summarising SNP and short indel sequence variants Installation link
• vcftools: To work with genetic variation data in the form of VCF files Github link
• Sequence format converter Web tool
• TCS: To infer Haplotype network, TCS.jar file is provided, Required Java. PubMed link
• Web-interactive visualization of Haplotype Network with tcsBU Web tool; Paper

Not required for the tutorial. Recommended

• BpWrapper: command-line tools for manipulation of sequences, alignment, and tree (based on BioPerl). Github Link; Flowchart from publication
• Pairwise genome alignment with MUMMER: Github link
• Samtools: Reading/writing/editing/indexing/viewing SAM/BAM/CRAM format Installation link

CoV genome data set

• N=100 SARS-CoV-2 genomes collected during January, February & March 2020. Data source & acknowledgement GIDAID (Warning: You need to acknowledge GISAID if you reuse the data in any publication)
• Download the folder "bootcamp_august_6th_2020": data file
• unzip the folder

unzip bootcamp_august_6th_2020.zip

• View files

ls -lrt # long list, in reverse timeline

ls cov_data # a folder of 100 CoV2 genomes in FASTA format, pairwise genome alignment sam and indexed sorted bam files generated by bwa (or nucmer) and samtools 

# We skipped bwa (or nucmer) and samtools part of the tutorial for time constrain. The bash script used to generate these files is available on request 

ls cov_data/*sorted.bam | wc # 100 sorted.bam files correspond to 100 sequence files

less ref.fas # NC_045512 as reference sequence, "q" to quit

less metadata_cov.txt # a tsv file that contains collection dates and geographic information of 100 CoV2 genomes
wc metadata_cov.txt

file TCS.jar # Java application

less bcf-snp-call.sh # a file contain all the bash commands required to call SNPs and generate vcf file of 100 CoV2 genomes
less ploidy.txt # to specify the ploidy=1 during vcf SNP call

less rgb.txt #rgb color code to color the phylogenetic network

</syntaxhighlight>

• Additional files

Tutorial

• 2-2:30: Introduction on pathogen phylogenomics
• 2:30-2:45: Demo: sequence manipulation with BpWrapper

bioseq --man
bioseq -i'genbank' ref.gb > ref.fas
bioseq -n Jan-Feb.mafft
bioaln --man
bioaln -n -i'fasta' Jan-Feb.mafft
bioaln -l -i'fasta' Jan-Feb.mafft
bioaln -n -i'phylip' cov-565strains-617snvs.phy
bioaln -l -i'phylip' cov-565strains-617snvs.phy
FastTree -nt cov-565strains-617snvs.phy > cov.dnd
biotree --man
biotree -n cov.dnd
biotree -l cov.dnd

• 2:45-3:10: build haplotype network with TCS

# Data pre-processing
# 1. Download genomes & meta data from GISAID
# 2. Run dnadist against a reference genome
man nucmer
dnadiff -h
dnadiff ref.fas <query FASTA>
mkdir fasta-files
cd fasta-files
for f in *.fas; do dnadiff ref.fas $f; done
<to be added: plot in R seq diff vs collection date>
# 3. Remove mis-assembled and reverse-complemented genomes
bioseq -d'file:'
# 4. Remove genomes with more than 10 non-ATCG bases
bioseq -d'ambig:10'
# 5. Run mafft (not run; takes too long)
# 6. Run snp-sites
snp-sites
java -jar -Xmx1g TCS.jar

• 3:10-3:20: interactive visualization with BuTCS
  • Load graph file
  • Load group file
  • Load haplotype file
• 3:20-3:30: Q & A