Human_Microbiome_Project_MockB_Shotgun

Instrument:  PacBio RS II
Chemistry:  C2 & C3
Enzyme: P4 & P5
P4-C2 and P5-C3 both collected as indicated below.

Just as the de novo assembly of individual genomes is dramatically improved by applying the long read lengths of SMRT® Sequencing, the assembly of metagenomes should also benefit from these advances with significant improvements to delineate between members of the community. As a proof of concept to study this hypothesis, Pacific Biosciences has sequenced a mock community from the Human Microbiome Project and assembled the data using the same algorithm used to assemble single microbial genomes, HGAP.

Posted here is shotgun sequencing data from the Mock Community B sample from the Human Microbiome Project. These files contain the sequencing read data only, not an assembly. The data has been broken into several sets to keep the file size somewhat reasonable. Some preliminary example results of the assembly are also shown at the bottom of the page.

The mock community was obtained through BEI Resources, NIAID, NIH as part of the Human Microbiome Project: Genomic DNA from Microbial Mock Community B (Even, High Concentration), v5.1H, for Whole Genome Shotgun Sequencing, HM-276D. http://www.beiresources.org/Catalog/otherProducts/HM-276D.aspx

Data files:

• Set 1 (7 SMRT Cells using P4-C2) (43 Gb tar.gz)
• Set 2 (7 SMRT Cells using P4-C2) (30 Gb tar.gz)
• Set 3 (7 SMRT Cells using P4-C2) (28 Gb tar.gz)
• Set 4 (6 SMRT Cells using P4-C2) (25 Gb tar.gz)
• Set 5 (8 SMRT Cells using P5-C3) (35 Gb tar.gz)
• Set 6 (7 SMRT Cells using P5-C3) (29 Gb tar.gz)
• Set 7 (7 SMRT Cells using P5-C3) (20 Gb tar.gz)

SMRT Cell summary statistics:

Data file	Sample Name	Binding Tube	Polymerase	Chemistry	Acq Time	Post-Filter # Subreads	Post-Filter # Bases
hmp_set1	BEI high even metagenomic_50 pM	BEI high even metagenomic_bt_1	P4	C2	180	86148	379137670
hmp_set1	BEI high even metagenomic_50 pM	BEI high even metagenomic_bt_1	P4	C2	180	81868	360470933
hmp_set1	BEI high even metagenomic_50 pM	BEI high even metagenomic_bt_1	P4	C2	180	74202	325257630
hmp_set1	BEI high even metagenomic_50 pM	BEI high even metagenomic_bt_1	P4	C2	180	56766	239910920
hmp_set1	BEI high even metagenomic_75 pM	BEI high even metagenomic_bt_1	P4	C2	180	77952	334252160
hmp_set1	BEI high even metagenomic_75 pM	BEI high even metagenomic_bt_1	P4	C2	180	84656	403816210
hmp_set1	BEI high even metagenomic_75 pM	BEI high even metagenomic_bt_1	P4	C2	180	96587	478724129
hmp_set2	BEI high even metagenomic_75 pM	BEI high even metagenomic_bt_1	P4	C2	180	88561	426776736
hmp_set2	BEI high even metagenomic_25 pM	BEI high even metagenomic_bt_1	P4	C2	180	60997	277183852
hmp_set2	BEI high even metagenomic_25 pM	BEI high even metagenomic_bt_1	P4	C2	180	53994	236239138
hmp_set2	BEI high even metagenomic_25 pM	BEI high even metagenomic_bt_1	P4	C2	180	37144	153559945
hmp_set2	BEI high even metagenomic_25 pM	BEI high even metagenomic_bt_1	P4	C2	180	16972	71041660
hmp_set2	BEI high even metagenomic_50nM	BEI high even metagenomic_bt_1	P4	C2	180	82662	330381041
hmp_set2	BEI high even metagenomic_50nM	BEI high even metagenomic_bt_1	P4	C2	180	68918	252186962
hpm_set3	BEI high even metagenomic_50nM	BEI high even metagenomic_bt_1	P4	C2	180	72172	263299931
hmp_set3	BEI high even metagenomic_50nM	BEI high even metagenomic_bt_1	P4	C2	180	82525	326780667
hmp_set3	BEI high even metagenomic_50nM	BEI high even metagenomic_bt_1	P4	C2	180	71059	268035345
hmp_set3	BEI high even metagenomic_50nM	BEI high even metagenomic_bt_1	P4	C2	180	64942	261233340
hmp_set3	BEI high even metagenomic_50nM	BEI high even metagenomic_bt_1	P4	C2	180	45375	176070055
hmp_set3	BEI high even metagenomic_50 pM	BEI high even metagenomic_bt_1	P4	C2	120	57429	197140754
hmp_set3	BEI high even metagenomic_50 pM	BEI high even metagenomic_bt_1	P4	C2	120	36045	124101501
hmp_set4	BEI high even metagenomic_50 pM	BEI high even metagenomic_bt_1	P4	C2	120	54251	216380686
hmp_set4	BEI high even metagenomic_50 pM	BEI high even metagenomic_bt_1	P4	C2	120	79171	308755441
hmp_set4	BEI high even metagenomic_50 pM	BEI high even metagenomic_bt_1	P4	C2	120	60845	237953531
hmp_set4	BEI high even metagenomic_50 pM	BEI high even metagenomic_bt_1	P4	C2	120	82003	317202529
hmp_set4	BEI high even metagenomic_50 pM	BEI high even metagenomic_bt_1	P4	C2	120	79972	316034059
hmp_set4	BEI high even metagenomic_50 pM	BEI high even metagenomic_bt_1	P4	C2	120	72257	274021988
hmp_set5	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	71388	383313431
hmp_set5	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	71115	373244879
hmp_set5	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	70456	366785650
hmp_set5	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	69065	357261288
hmp_set5	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	66999	346936491
hmp_set5	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	70243	349011680
hmp_set5	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	68937	337872541
hmp_set5	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	65010	320675096
hmp_set6	BEI high even metagenomic_50pM	BEI high even metagenomic_bt_2	P5	C3	150	80562	381691078
hmp_set6	BEI high even metagenomic_50pM	BEI high even metagenomic_bt_2	P5	C3	150	66540	324761102
hmp_set6	BEI high even metagenomic_50pM	BEI high even metagenomic_bt_2	P5	C3	150	78035	371404939
hmp_set6	BEI high even metagenomic_50pM	BEI high even metagenomic_bt_2	P5	C3	150	73278	349280176
hmp_set6	BEI high even metagenomic_50pM	BEI high even metagenomic_bt_2	P5	C3	150	61150	289192246
hmp_set6	BEI high even metagenomic_50pM	BEI high even metagenomic_bt_2	P5	C3	150	66913	314699834
hmp_set6	BEI high even metagenomic_50pM	BEI high even metagenomic_bt_2	P5	C3	150	63319	291515819
hmp_set7	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	58617	262376178
hmp_set7	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	59557	266423085
hmp_set7	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	43703	196536274
hmp_set7	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	49685	224514646
hmp_set7	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	44409	209207825
hmp_set7	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	40569	181415565
hmp_set7	BEI high even metagenomic_	BEI high even metagenomic_bt_2	P5	C3	150	35858	162613189

The preliminary results of this analysis are promising, and the assemblies produced generally display improved contiguity as compared to publicly available, short-read data sets and assemblies. Additionally, the use of epigenetic information to make associations between contigs may make it possible to further improve the shotgun metagenome assembly. This approach would serve as a novel validation method provided only with PacBio sequencing, which can detect epigenetic modifications during single-molecule sequencing. We expect that using methylation data to make associations between contigs will prove more reliable than other strategies, such as binning by GC content, since the methylation profiles of different species within the community should follow a fundamental biological principle to be consistent across the genome. .

Some example results of the shotgun metagenome assembly are represented in the figures below, comparing PacBio preliminary results to MetaVelvet assemblies using Illumina® data. (Illumina benchmark from Treangen and Koren et al. MetAMOS: a modular and open source metagenomic assembly and analysis pipeline. MetaVelvet used for comparison because it produced the fewest contigs for the example genomes shown below -- i.e., the best short-read assemblies are used as a comparison below.)