Computer-aided identification of polymorphism sets diagnostic for groups of bacterial and viral genetic variants

Price, Erin P.; Inman-Bamber, John; Thiruvenkataswamy, Venugopal; Huygens, Flavia; Giffard, Philip M.

doi:10.1186/1471-2105-8-278

Cited by 24 publications

(28 citation statements)

References 47 publications

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“…The problem to be addressed searching for minimal sets of SNPs with an optimal pairwise differentiation among OTUs is often called “feature selection” (e.g., [30]) and is used to address similar questions, e.g., to find tag SNPs for capturing haplotype patterns used in studies on disease association and drug design (e.g., [31,32]; see [33] and references therein), or for computer-aided identification of polymorphism sets for bacteria and viruses [34]). However, none of these were designed for our exact purpose.…”

Section: Resultsmentioning

confidence: 99%

Developing diagnostic SNP panels for the identification of true fruit flies (Diptera: Tephritidae) within the limits of COI-based species delimitation

et al. 2013

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BackgroundRapid and reliable identification of quarantine pests is essential for plant inspection services to prevent introduction of invasive species. For insects, this may be a serious problem when dealing with morphologically similar cryptic species complexes and early developmental stages that lack distinctive characters useful for taxonomic identification. DNA based barcoding could solve many of these problems. The standard barcode fragment, an approx. 650 base pairs long sequence of the 5′end of the mitochondrial cytochrome oxidase I (COI), enables differentiation of a very wide range of arthropods. However, problems remain in some taxa, such as Tephritidae, where recent genetic differentiation among some of the described species hinders accurate molecular discrimination.ResultsIn order to explore the full species discrimination potential of COI, we sequenced the barcoding region of the COI gene of a range of economically important Tephritid species and complemented these data with all GenBank and BOLD entries for the systematic group available as of January 2012. We explored the limits of species delimitation of this barcode fragment among 193 putative Tephritid species and established operational taxonomic units (OTUs), between which discrimination is reliably possible. Furthermore, to enable future development of rapid diagnostic assays based on this sequence information, we characterized all single nucleotide polymorphisms (SNPs) and established “near-minimal” sets of SNPs that differentiate among all included OTUs with at least three and four SNPs, respectively.ConclusionsWe found that although several species cannot be differentiated based on the genetic diversity observed in COI and hence form composite OTUs, 85% of all OTUs correspond to described species. Because our SNP panels are developed based on all currently available sequence information and rely on a minimal pairwise difference of three SNPs, they are highly reliable and hence represent an important resource for developing taxon-specific diagnostic assays. For selected cases, possible explanations that may cause composite OTUs are discussed.

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Section: Resultsmentioning

confidence: 99%

Developing diagnostic SNP panels for the identification of true fruit flies (Diptera: Tephritidae) within the limits of COI-based species delimitation

et al. 2013

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“…We used the program ‘Minimum SNPs’, with incorporated Not-N algorithm [28], to find population-specific SNPs from both Structure and BAPS defined populations. Using STs with ≥95% population assignment from Structure , we identified a set of 25 SNPs that were needed to discriminate STs from Population 2 from all other STs, albeit with a confidence of only 92.5%.…”

Section: Resultsmentioning

confidence: 99%

Epidemiological Tracking and Population Assignment of the Non-Clonal Bacterium, Burkholderia pseudomallei

et al. 2011

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Rapid assignment of bacterial pathogens into predefined populations is an important first step for epidemiological tracking. For clonal species, a single allele can theoretically define a population. For non-clonal species such as Burkholderia pseudomallei, however, shared allelic states between distantly related isolates make it more difficult to identify population defining characteristics. Two distinct B. pseudomallei populations have been previously identified using multilocus sequence typing (MLST). These populations correlate with the major foci of endemicity (Australia and Southeast Asia). Here, we use multiple Bayesian approaches to evaluate the compositional robustness of these populations, and provide assignment results for MLST sequence types (STs). Our goal was to provide a reference for assigning STs to an established population without the need for further computational analyses. We also provide allele frequency results for each population to enable estimation of population assignment even when novel STs are discovered. The ability for humans and potentially contaminated goods to move rapidly across the globe complicates the task of identifying the source of an infection or outbreak. Population genetic dynamics of B. pseudomallei are particularly complicated relative to other bacterial pathogens, but the work here provides the ability for broad scale population assignment. As there is currently no independent empirical measure of successful population assignment, we provide comprehensive analytical details of our comparisons to enable the reader to evaluate the robustness of population designations and assignments as they pertain to individual research questions. Finer scale subdivision and verification of current population compositions will likely be possible with genotyping data that more comprehensively samples the genome. The approach used here may be valuable for other non-clonal pathogens that lack simple group-defining genetic characteristics and provides a rapid reference for epidemiologists wishing to track the origin of infection without the need to compile population data and learn population assignment algorithms.

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“…[27] and would be useful to assess the discriminatory power of combinations of candidate targets for typing systems for other pathogens. It can be used for a wide range of data types, but for interrogation of informative SNPs, we recommend Minimum SNPs, which has been designed specifically for this purpose [6,7]. Minimum SNPs should be used to examine input data in the form of multiple sequence alignments.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, alternative approaches are required. Software has been developed to interrogate informative single nucleotide polymorphisms (SNPs) in sequence based data (Minimum SNPs) but it is not designed to handle other forms of typing data [6,7]. Furthermore, while it can be used to identify SNPs, which are most predictive of a user-nominated sequence type, it does not consider overall measures of concordance between typing systems.…”

Section: Introductionmentioning

confidence: 99%

Software for selecting the most informative sets of genomic loci for multi-target microbial typing

2013

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BackgroundHigh-throughput sequencing can identify numerous potential genomic targets for microbial strain typing, but identification of the most informative combinations requires the use of computational screening tools. This paper describes novel software – Automated Selection of Typing Target Subsets (AuSeTTS) - that allows intelligent selection of optimal targets for pathogen strain typing. The objective of this software is to maximise both discriminatory power, using Simpson’s index of diversity (D), and concordance with existing typing methods, using the adjusted Wallace coefficient (AW). The program interrogates molecular typing results for panels of isolates, based on large target sets, and iteratively examines each target, one-by-one, to determine the most informative subset.ResultsAuSeTTS was evaluated using three target sets: 51 binary targets (13 toxin genes, 16 phage-related loci and 22 SCCmec elements), used for multilocus typing of 153 methicillin-resistant Staphylococcus aureus (MRSA) isolates; 17 MLVA loci in 502 Streptococcus pneumoniae isolates from the MLVA database (http://www.mlva.eu) and 12 MLST loci for 98 Cryptococcus spp. isolates.The maximum D for MRSA, 0.984, was achieved with a subset of 20 targets and a D value of 0.954 with 7 targets. Twelve targets predicted MLST with a maximum AW of 0.9994. All 17 S. pneumoniae MLVA targets were required to achieve maximum D of 0.997, but 4 targets reached D of 0.990. Twelve targets predicted pneumococcal serotype with a maximum AW of 0.899 and 9 predicted MLST with maximum AW of 0.963. Eight of the 12 MLST loci were sufficient to achieve the maximum D of 0.963 for Cryptococcus spp.ConclusionsComputerised analysis with AuSeTTS allows rapid selection of the most discriminatory targets for incorporation into typing schemes. Output of the program is presented in both tabular and graphical formats and the software is available for free download from http://www.cidmpublichealth.org/pages/ausetts.html.

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Computer-aided identification of polymorphism sets diagnostic for groups of bacterial and viral genetic variants

Cited by 24 publications

References 47 publications

Developing diagnostic SNP panels for the identification of true fruit flies (Diptera: Tephritidae) within the limits of COI-based species delimitation

Developing diagnostic SNP panels for the identification of true fruit flies (Diptera: Tephritidae) within the limits of COI-based species delimitation

Epidemiological Tracking and Population Assignment of the Non-Clonal Bacterium, Burkholderia pseudomallei

Software for selecting the most informative sets of genomic loci for multi-target microbial typing

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