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Microbes make up the majority of the earth's biomass and have evolved for over 3.8 billion years. Knowledge of the enormous range of microbial capacities can have far-reaching implications for health, environment, energy, and industrial applications. With our NGS platforms and bioinformatics experience, BGI Tech provides cost-effective services and fast turnaround time for sequencing microbial genomes. To date, BGI Tech has completed genome research on archaea, fungi, bacteria, protozoa, viruses, as well as micro-ecological systems with more than 21,000 samples. In addition, at least 80 single bacteria-related articles and 10 metagenome-related articles have been published.

High Genome Heterozygosity and Endemic Genetic Recombination in the Wheat Stripe Rust Fungus. Nature communications. doi:10.1038/ncomms3673 (2013).

Here we report a 110-Mb draft sequence of Pst isolate CY32, obtained using a ‘fosmid-to-fosmid’ strategy, to better understand its race evolution and pathogenesis. The Pst genome is highly heterozygous and contains 25,288 protein-coding genes. Compared with non-obligate fungal pathogens, Pst has a more diverse gene composition and more genes encoding secreted proteins. Re-sequencing analysis indicates significant genetic variation among six isolates collected from different continents. Approximately 35% of SNPs are in the coding sequence regions, and half of them are non-synonymous. High genetic diversity in Pst suggests that sexual reproduction has an important role in the origin of different regional races. Our results show the effectiveness of the ‘fosmid-to-fosmid’ strategy for sequencing dikaryotic genomes and the feasibility of genome analysis to understand race evolution in Pst and other obligate pathogens.

Genome Sequencing of 161 Mycobacterium tuberculosis Isolates From China Identifies Genes and Intergenic Regions Associated With Drug Resistance. Nature Genetics. 45, 1255–1260 (2013).

Here we sequenced and analyzed 161 isolates with a range of drug resistance profiles, discovering 72 new genes, 28 intergenic regions (IGRs), 11 nonsynonymous SNPs and 10 IGR SNPs with strong, consistent associations with drug resistance. Our work indicates that the genetic basis of drug resistance is more complex than previously anticipated and provides a strong foundation for elucidating unknown drug resistance mechanisms.

Historical Variations in Mutation Rate in an Epidemic Pathogen, Yersinia pestis. Proc. Natl. Acad. Sci. 110(2):577-82 (2013).

Here we identified 2,326 SNPs from 133 genomes of Y. pestis strains that were isolated in China and elsewhere. These SNPs define the genealogy of Y. pestissince its most recent common ancestor. All but 28 of these SNPs represented mutations that happened only once within the genealogy, and they were distributed essentially at random among individual genes. Only seven genes contained a significant excess of nonsynonymous SNP, suggesting that the fixation of SNPs mainly arises via neutral processes, such as genetic drift, rather than Darwinian selection. However, the rate of fixation varies dramatically over the genealogy: the number of SNPs accumulated by different lineages was highly variable and the genealogy contains multiple polytomies, one of which resulted in four branches near the time of the Black Death. We suggest that demographic changes can affect the speed of evolution in epidemic pathogens even in the absence of natural selection, and hypothesize that neutral SNPs are fixed rapidly during intermittent epidemics and outbreaks.


Bacteria re-sequencing

  1. Filtering out adapters and low quality data
  2. Data production and quality control
  3. Primary assembly of bacteria as well as GC-depth and k-mer analysis
  4. References homology analysis (single base depth and coverage analysis)
  5. SNP and InDel identification
  6. Species evolution analysis (construct phylogenetic tree, Ka/Ks)

Fungal re-sequencing

  1. Filtering out adapters and low quality data
  2. Data production and quality control
  3. Analysis of genomic homology and consensus sequence
  4. SNP and InDel identification
  5. Species evolution analysis (construct phylogenetic tree, Ka/Ks)

Sample Requirements (for the genomic DNA samples):

  1. Purity: OD260/280=1.8-2.0
  2. Concentration: ≥25 ng/μl
  3. DNA amount: single library preparation starts from at least 2.5ug, and the total amount should be determined case by case.