1. Jan Pačes Institute of Molecular Genetics AS CR
hard assembly
Jan Pačes
Institute of Molecular Genetics AS CR

2. problems genomes high GC content
repetitions (short - low informational content, long)
polymorphic
"unreadable" sequences, "weird" structures
technologies
nonrandom libraries
wrong sizes
erroneous or chimeric reads

3. sequencing technologies
ABI (sanger)
454 (pyrosequencing)
solexa (reversible terminator)
SOLiD (2base ligation)
PacBio (SMRT)

4. example of errors in one technology

5. high GC regions are underrepresented
Aird et al. Genome Biology 2011

6. protocol optimization for high GC content
Aird et al. Genome Biology 2011

7. repetitions
scaffold
repetition

8. repetitions

9. repetitions recognition
Repeatmasker
RepeatModeller (RECON and RepeatScout)
position aware assemblers
MIRA
MaSuRCA
SPAdes

10. k-mer distribution

11. k-mer analysis JELLYFISH - Fast, Parallel k-mer Counting for DNA
Quake is a package to correct substitution sequencing errors in experiments with deep coverage
KHMER Trim off likely erroneous k-mers

12. repetitions
repetition
scaffold

13. filling gaps GapCloser (part of SOAPdenovo)
GapFiller (part of SSPACE)
GapFiller

14. 454 multiplicates

15. contig coverage by large libraries

16. illumina pe and mate-pairs libraries
1616
illumina pe and mate-pairs libraries

17. highly polymorphic genomes
two copies of polymorphic contigs
scaffold

18. polymorphic assembly workflow
normal assembly
condensing alternative contigs
mapping to identify SNPs
"repair" reads
second "polymorpic" assembly

20. G-quadruplex

21. Chicken p53 – coverage from RNAseq data
AGCGACCCCCCCCCACCACCGCCACCACCACCTCTGCCATTGGCCGCCGCCGCCCCCCCCCCATTAAACCCCCCCACCCCCCCCCGCGCTGCCCCCTCCCCGGTGG
Coverage > 13,000X

22. Chicken erythropoietin (EPO)– coverage from RNAseq data
CCCGCCCACCCCCACCCCCACCCGCACCCCCCACTCTCCCACCCCCACCCCCTTTTCTCCCACCCCCTCTTCTCCCACCCCCTTTTCCCCCCCTTCCTCCCCCCACTCCG
CCCCCCCCCCGCCCCCTCCCCCCCCCCAGGTGAGGACCCT
Coverage > 500X from RNAseq
(*EPO locus not completed even from 1000X coverage genomic Illumina data!)

23. chicken missing genes

24. that’s it, thank you many thanks also to: Daniel Elleder Tomáš Hron
Michal Kolář
Hynek Strnad