1. The Wellcome Trust Sanger Institute
Assembly Scaffolding using String Graphs and In Silico Chromosome Assignment
Zemin Ning
The Wellcome Trust Sanger Institute 1

2. Phusion2 Assembly Pipeline
Illumina
Reads
Assembly
2x75 or 2x100bp
Flow-sorting Reads
Map Markers
AGPcontig
Data
Process
Mate Pair Reads
BAC Ends
Supercontig
Base
Correction
Contigs
Reads
Group
Consensus
Generation

3. Spinner – a scaffolding tool
Spinner uses mate pair data to scaffold contigs. Contigs, and pairs of contigs connected by pairs, define a bi-directional graph:
Using expected insert size, a estimate of the gap size can be given for each contig.

4. Spinner – removing bad pairs
Spinner seeks to delete spurious connections where possible. Pairs screened for (a) PCR duplication, (b) cross-biotin and (c) chimeric pairs, etc. 
Max insert length
If placement of reads implies a large negative distance between the contigs, pair is discarded. 
Max insert length
After merging two contigs…
this check is repeated to find more spurious pairs.

5. Spinner – deciding when to merge
Connection to X with smallest gap size is merged -- as long as neither of these “conflicts” occur: A X B
(1) According to the gap distance estimates and contig length, some alternative B overlaps A. X A B
(2) Some alternative B is NOT connected to A.
Must ALSO check the reverse: that there is nothing closer to A than X (and no conflicts with X from A).
Conflicts may be resolved by a “strength comparison”.

6. Spinner – still to do These techniques alone produces useful results.
Further stages will be used to resolve repeats pairs that “jump over” repeats, and graph flow concepts.

7. Remove Heterozygosity Contigs

8. Pipeline of Contig Gap Closure

9. Scaffold Comparisons SPINNER vs SSPACE
SSPACE SPINNER
Genome_Size N Average N Average
Assemblathon Mb 608Kb 86.8Kb 10Mb 450Kb
Bamboo Gb 322Kb Kb 7689
Parrot Gb 906Kb Mb 6969

10. Tasmanian tiger
Tasmanian devil
Australian
Tasmanian

11. Tasmanian devil facial tumour disease (DFTD)
Transmissible cancer characterised by the growth of large tumours on the face, neck and mouth of Tasmanian devils
Transmitted by biting
Commonly metastasises
First observed in 1996
Primarily affects adults >1yr
Death in 4 – 6 months

12. Tasmanian devil
Tasmanian devil
Opossum
Wallaby

13. 1 2 3 4 5 6 7 8 X 2a 3a 2b 3b
Devil – Opossum Homology Map Based on Hybridisation Results of Devil Paints onto Opossum Chromosomes
Opossum
Devil
Opossum chromosome images were taken from Duke et a. 2007, Chromosome Res 15:

14. 3431 3319 2926 Genome size Opossum Devil Chr Seq FC 1 748 611 571 2
Flow cytometry analysis of chromosomal mixture of devil and opossum
Genome size
Opossum
Devil
Chr
Seq FC 1
748
611
571 2
541
484
610 3
526
483
556 4
430
423
450 5
309
321
341 6
245
296
277 7
263
264 8
308 X 61
116
121
Total
3431
3319
2926 3 2 1 1
Tasmanian devil 4 2 3 5 4 6
5+8 6 7
Opossum X X

15. Read mapping coefficient: e = Size_of_Chr/Num_reads_in_lane
Table 1 Run ID, Template names, Number of reads and Chromosome size
4972_1 chr1 IL20_4972:
4967_1 chr2 IL21_4967:
4971_1 chr3 IL30_4971:
4964_1 chr4 IL14_4964:
4969_1 chr5 IL17_4969:
4969_2 chr6 IL17_4969:
4969_ chrx IL17_4969:
Read mapping coefficient:
e = Size_of_Chr/Num_reads_in_lane

16. Perfect - Reads from the same library were mapped to the contig

17. Acceptable - Majority of the reads were from the same library, but there were reads from other libraries

18. Bad – mis-assembly error
Majority of the reads in one region were from one library. But there is a transition from which we see a new library, i.e. switch to another chromosome.

19. Unassigned contigs were placed by supercontigs using mate pairs

20. Scaffolds Assigned to Chromosomes using Flow-sorting Data
Chr_ID Chr_size Scaffolds_assigned Bases_assigned Mb
Chr
Chr
Chr
Chr
Chr
Chr
Chrx
Unassigned

21. Genome Assembly Normal – T. Devil
Solexa reads:
Number of read pairs: Million; Estimated genome size: GB;
Read length: 2x100bp;
Estimated read coverage: ~40X;
Insert size: / bp;
Mate pair data: 2k,4k,5k,6k,8k,10k
Number of reads clustered: 591 Million
Assembly features: - stats
Contigs Supercontigs Total number of contigs: ,711 26,954
Total bases of contigs: Gb 3.08 Gb
N50 contig size: ,921 2,244,460
Largest contig: 214,456 6,014,846
Averaged contig size: , ,451
Contig coverage on genome: ~94% >99%
Ratio of placed PE reads: ~92% ?

22. Devil Tumour Genome Assemblies
Solexa reads: Tumour_87T Tumour_53T
Number of read pairs: Million 669 M; Finished genome size: GB 3.2 GB;
Read length: 2x x100;
Estimated read coverage: ~46X ~40X;
Insert size: bp 300bp;
Number of reads clustered: 635 Million 603 M
Assembly features: - stats
Tumour_87T Tumour_53T Total number of contigs: , ,288
Total bases of contigs: Gb 3.14 Gb
N50 contig size: ,908 14,632
Largest contig: 109, ,831
Averaged contig size: ,882 5,567
Contig coverage on genome: ~95% ~95%
Ratio of placed PE reads: ~92% ~92%

23. DFTD1 K I F1 F G/H D F2 E F M1 A J M2? M3 1 der1 der2 3 4 5 der5 6X X 5 6 2 5 6 2 5 X? X 2 2

24. DFTD2 L K3 M J K1/K2 I J H D F G B M3 M1 M2 der6 der5 der1 1 2 3 4 5 6Xp Xq 5 1 6 2 2 1 X 2 X X 2 2

25. Acknowledgements: Joe Henson Elizabeth Murchuson David McBride Yong Gu
Fengtang Yang
Mike Stratton
Ole Schulz-Trieglaff
Dirk Evers
David Bentley