Genetic least squares for system identification

The recursive least-squares algorithm with a forgetting factor has been extensively applied and studied for the on-line parameter estimation of linear dynamic systems. This paper explores the use of genetic algorithms to improve the performance of the recursive least-squares algorithm in the parameter estimation of time-varying systems. Simulation results show that the hybrid recursive algorithm (GARLS), combining recursive least-squares with genetic algorithms, can achieve better results than the standard recursive least-squares algorithm using only a forgetting factor.

Identification of genetic and phenotypic differences associated with prevalent and non-prevalent Salmonella Enteritidis phage types: analysis of variation in amino acid transport

In this study, differences at the genetic level of 37 Salmonella Enteritidis strains from five phage types (PTs) were compared using comparative genomic hybridization (CGH) to assess differences between PTs. There were approximately 400 genes that differentiated prevalent (4, 6, 8 and 13a) and sporadic (11) PTs, of which 35 were unique to prevalent PTs, including six plasmid-borne genes, pefA, B, C, D, srgC and rck, and four chromosomal genes encoding putative amino acid transporters. Phenotype array studies also demonstrated that strains from prevalent PTs were less susceptible to urea stress and utilized L-histidine, L-glutamine, L-proline, L-aspartic acid, gly-asn and gly-gln more efficiently than PT11 strains. Complementation of a PT11 strain with the transporter genes from PT4 resulted in a significant increase in utilization of the amino acids and reduced susceptibility to urea stress. In epithelial cell association assays, PT11 strains were less invasive than other prevalent PTs. Most strains from prevalent PTs were better biofilm formers at 37 degrees C than at 28 degrees C, whilst the converse was true for PT11 strains. Collectively, the results indicate that genetic and corresponding phenotypic differences exist between strains of the prevalent PTs 4, 6, 8 and 13a and non-prevalent PT11 strains that are likely to provide a selective advantage for strains from the former PTs and could help them to enter the food chain and cause salmonellosis.

Genetic diversity among Escherichia coli O157 : H7 isolates and identification of genes linked to human infections

An Escherichia coli oligonucleotide microarray based on three sequenced genomes was validated for comparative genomic microarray hybridization and used to study the diversity of E. coli O157 isolates from human infections and food and animal sources. Among 26 test strains, 24 (including both Shiga toxin [Stx]-positive and -negative strains) were found to be related to the two sequenced E. coli O157:117 strains, EDL933 and Sakai. However, these strains showed much greater genetic diversity than those reported previously, and most of them could not be categorized as either lineage I or H. Some genes were found more often in isolates from human than from nonhuman sources; e.g., ECs1202 and ECs2976, associated with stx2AB and stx1AB, were in all isolates from human sources but in only 40% of those from nonhuman sources. Some (but not all) lineage I-specific or -dominant genes were also more frequently associated with isolates from human. The results suggested that it might be more effective to concentrate our efforts on finding markers that are directly related to infection rather than those specific to certain lineages. In addition, two Stx-negative O157 cattle isolates (one confirmed to be 117) were significantly different from other Stx-positive and -negative E. coli O157:117 strains and were more similar to MG1655 in their gene content. This work demonstrates that not all E. coli O157:117 strains belong to the same clonal group, and those that were similar to E. coli K-12 might be less virulent.

Statistical methods for examining genetic influences of resistance to anti-epileptic drugs

It is generally accepted that genetics may be an important factor in explaining the variation between patients’ responses to certain drugs. However, identification and confirmation of the responsible genetic variants is proving to be a challenge in many cases. A number of difficulties that maybe encountered in pursuit of these variants, such as non-replication of a true effect, population structure and selection bias, can be mitigated or at least reduced by appropriate statistical methodology. Another major statistical challenge facing pharmacogenetics studies is trying to detect possibly small polygenic effects using large volumes of genetic data, while controlling the number of false positive signals. Here we review statistical design and analysis options available for investigations of genetic resistance to anti-epileptic drugs.

Mapping and controlling molecular processes: The application of control theory and system identification algorithms to ASOPS and other fast pulse spectroscopies

Asynchronous Optical Sampling (ASOPS) [1,2] and frequency comb spectrometry [3] based on dual Ti:saphire resonators operated in a master/slave mode have the potential to improve signal to noise ratio in THz transient and IR sperctrometry. The multimode Brownian oscillator time-domain response function described by state-space models is a mathematically robust framework that can be used to describe the dispersive phenomena governed by Lorentzian, Debye and Drude responses. In addition, the optical properties of an arbitrary medium can be expressed as a linear combination of simple multimode Brownian oscillator functions. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing the recorded THz transients in the time or frequency domain will be outlined [4,5]. Since a femtosecond duration pulse is capable of persistent excitation of the medium within which it propagates, such approach is perfectly justifiable. Several de-noising routines based on system identification will be shown. Furthermore, specifically developed apodization structures will be discussed. These are necessary because due to dispersion issues, the time-domain background and sample interferograms are non-symmetrical [6-8]. These procedures can lead to a more precise estimation of the complex insertion loss function. The algorithms are applicable to femtosecond spectroscopies across the EM spectrum. Finally, a methodology for femtosecond pulse shaping using genetic algorithms aiming to map and control molecular relaxation processes will be mentioned.

Genetic characterization of tick-borne flaviviruses: new insights into evolution, pathogenetic determinants and taxonomy

Here, we analyze the complete coding sequences of all recognized tick-borne flavivirus species, including Gadgets Gully, Royal Farm and Karshi virus, seabird-associated flaviviruses, Kadam virus and previously uncharacterized isolates of Kyasanur Forest disease virus and Omsk hemorrhagic fever virus. Significant taxonomic improvements are proposed, e.g. the identification of three major groups (mammalian, seabird and Kadam tick-borne flavivirus groups), the creation of a new species (Karshi virus) and the assignment of Tick-borne encephalitis and Louping ill viruses to a unique species (Tick-borne encephalitis virus) including four viral types (i.e. Western Tick-borne encephalitis virus, Eastern Tick-borne encephalitis virus, Turkish sheep Tick-borne encephalitis virus and Louping ill Tick-borne encephalitis virus). The analyses also suggest a complex relationship between viruses infecting birds and those infecting mammals. Ticks that feed on both categories of vertebrates may constitute the evolutionary bridge between the three distinct identified lineages.

The genetic basis of resistance to anticoagulants in rodents

Anticoagulant compounds, i.e., derivatives of either 4-hydroxycoumarin (e.g., warfarin, bromadiolone) or indane-1,3-dione (e.g., diphacinone, chlorophacinone), have been in worldwide use as rodenticides for > 50 years. These compounds inhibit blood coagulation by repression of the vitamin K reductase reaction (VKOR). Anticoagulant-resistant rodent populations have been reported from many countries and pose a considerable problem for pest control. Resistance is transmitted as an autosomal dominant trait although, until recently, the basic genetic mutation was unknown. Here, we report on the identification of eight different mutations in the VKORC1 gene in resistant laboratory strains of brown rats and house mice and in wild-caught brown rats from various locations in Europe with five of these mutations affecting only two amino acids (Tyr139Cys, Tyr139Ser, Tyr139Phe and Leu128Gln, Leu128Ser). By recombinant expression of VKORC1 constructs in HEK293 cells we demonstrate that mutations at Tyr139 confer resistance to warlarin at variable degrees while the other mutations, in addition, dramatically reduce VKOR activity. Our data strongly argue for at least seven independent mutation events in brown rats and two in mice. They suggest that mutations in VKORC1 are the genetic basis of anticoagulant resistance in wild populations of rodents, although the mutations alone do not explain all aspects of resistance that have been reported. We hypothesize that these mutations, apart from generating structural changes in the VKORC1 protein, may induce compensatory mechanisms to maintain blood clotting. Our findings provide the basis for a DNA-based field monitoring of anticoagulant resistance in rodents.

Identifying adaptive genetic divergence among populations from genome scans

The identification of signatures of natural selection in genomic surveys has become an area of intense research, stimulated by the increasing ease with which genetic markers can be typed. Loci identified as subject to selection may be functionally important, and hence (weak) candidates for involvement in disease causation. They can also be useful in determining the adaptive differentiation of populations, and exploring hypotheses about speciation. Adaptive differentiation has traditionally been identified from differences in allele frequencies among different populations, summarised by an estimate of F-ST. Low outliers relative to an appropriate neutral population-genetics model indicate loci subject to balancing selection, whereas high outliers suggest adaptive (directional) selection. However, the problem of identifying statistically significant departures from neutrality is complicated by confounding effects on the distribution of F-ST estimates, and current methods have not yet been tested in large-scale simulation experiments. Here, we simulate data from a structured population at many unlinked, diallelic loci that are predominantly neutral but with some loci subject to adaptive or balancing selection. We develop a hierarchical-Bayesian method, implemented via Markov chain Monte Carlo (MCMC), and assess its performance in distinguishing the loci simulated under selection from the neutral loci. We also compare this performance with that of a frequentist method, based on moment-based estimates of F-ST. We find that both methods can identify loci subject to adaptive selection when the selection coefficient is at least five times the migration rate. Neither method could reliably distinguish loci under balancing selection in our simulations, even when the selection coefficient is twenty times the migration rate.

Chromatographic alignment of LC-MS and LC-MS/MS datasets by genetic algorithm feature extraction

Liquid chromatography-mass spectrometry (LC-MS) datasets can be compared or combined following chromatographic alignment. Here we describe a simple solution to the specific problem of aligning one LC-MS dataset and one LC-MS/MS dataset, acquired on separate instruments from an enzymatic digest of a protein mixture, using feature extraction and a genetic algorithm. First, the LC-MS dataset is searched within a few ppm of the calculated theoretical masses of peptides confidently identified by LC-MS/MS. A piecewise linear function is then fitted to these matched peptides using a genetic algorithm with a fitness function that is insensitive to incorrect matches but sufficiently flexible to adapt to the discrete shifts common when comparing LC datasets. We demonstrate the utility of this method by aligning ion trap LC-MS/MS data with accurate LC-MS data from an FTICR mass spectrometer and show how hybrid datasets can improve peptide and protein identification by combining the speed of the ion trap with the mass accuracy of the FTICR, similar to using a hybrid ion trap-FTICR instrument. We also show that the high resolving power of FTICR can improve precision and linear dynamic range in quantitative proteomics. The alignment software, msalign, is freely available as open source.

Implications for DNA identification arising from an analysis of Australian forensic databases

Previous analyses of Australian samples have suggested that populations of the same broad racial group (Caucasian, Asian, Aboriginal) tend to be genetically similar across states. This suggests that a single national Australian database for each such group may be feasible, which would greatly facilitate casework. We have investigated samples drawn from each of these groups in different Australian states, and have quantified the genetic homogeneity across states within each racial group in terms of the "coancestry coefficient" F(ST). In accord with earlier results, we find that F(ST) values, as estimated from these data, are very small for Caucasians and Asians, usually <0.5%. We find that "declared" Aborigines (which includes many with partly Aboriginal genetic heritage) are also genetically similar across states, although they display some differentiation from a "pure" Aboriginal population (almost entirely of Aboriginal genetic heritage).

Modelling niches of arbitrary shape in genetic algorithms using Niche Linkage in the Dynamic Niche Clustering framework

We present some additions to a fuzzy variable radius niche technique called Dynamic Niche Clustering (DNC) (Gan and Warwick, 1999; 2000; 2001) that enable the identification and creation of niches of arbitrary shape through a mechanism called Niche Linkage. We show that by using this mechanism it is possible to attain better feature extraction from the underlying population.

A variable radius niching technique for speciation in genetic algorithms

In this paper, a continuation of a variable radius niche technique called Dynamic Niche Clustering developed by (Gan & Warwick, 1999) is presented. The technique employs a separate dynamic population of overlapping niches that coexists alongside the normal population. An empirical analysis of the updated methodology on a large group of standard optimisation test-bed functions is also given. The technique is shown to perform almost as well as standard fitness sharing with regards to stability and the accuracy of peak identification, but it outperforms standard fitness sharing with regards to time complexity. It is also shown that the technique is capable of forming niches of varying size depending on the characteristics of the underlying peak that the niche is populating.

A genetic linkage map of an apple rootstock progeny anchored to the Malus genome sequence

An apple rootstock progeny raised from the cross between the very dwarfing ‘M.27’ and the more vigorous ‘M.116’ (‘M.M.106’ × ‘M.27’) was used for the construction of a linkage map comprising a total of 324 loci: 252 previously mapped SSRs, 71 newly characterised or previously unmapped SSR loci (including 36 amplified by 33 out of the 35 novel markers reported here), and the self-incompatibility locus. The map spanned the 17 linkage groups (LG) expected for apple covering a genetic distance of 1,229.5 cM, an estimated 91% of the Malus genome. Linkage groups were well populated and, although marker density ranged from 2.3 to 6.2 cM/SSR, just 15 gaps of more than 15 cM were observed. Moreover, only 17.5% of markers displayed segregation distortion and, unsurprisingly in a semi-compatible backcross, distortion was particularly pronounced surrounding the self-incompatibility locus (S) at the bottom of LG17. DNA sequences of 273 SSR markers and the S locus, representing a total of 314 loci in this investigation, were used to anchor to the ‘Golden Delicious’ genome sequence. More than 260 of these loci were located on the expected pseudo-chromosome on the ‘Golden Delicious’ genome or on its homeologous pseudo-chromosome. In total, 282.4 Mbp of sequence from 142 genome sequence scaffolds of the Malus genome were anchored to the ‘M.27’ × ‘M.116’ map, providing an interface between the marker data and the underlying genome sequence. This will be exploited for the identification of genes responsible for traits of agronomic importance such as dwarfing and water use efficiency.

Identification of core and variable components of the Salmonella enterica subspecies I genome by microarray

We have performed microarray hybridization studies on 40 clinical isolates from 12 common serovars within Salmonella enterica subspecies I to identify the conserved chromosomal gene pool. We were able to separate the core invariant portion of the genome by a novel mathematical approach using a decision tree based on genes ranked by increasing variance. All genes within the core component were confirmed using available sequence and microarray information for S. enterica subspecies I strains. The majority of genes within the core component had conserved homologues in Escherichia coli K-12 strain MG1655. However, many genes present in the conserved set which were absent or highly divergent in K-12 had close homologues in pathogenic bacteria such as Shigella flexneri and Pseudomonas aeruginosa. Genes within previously established virulence determinants such as SPI1 to SPI5 were conserved. In addition several genes within SPI6, all of SPI9, and three fimbrial operons (fim, bcf, and stb) were conserved within all S. enterica strains included in this study. Although many phage and insertion sequence elements were missing from the core component, approximately half the pseudogenes present in S. enterica serovar Typhi were conserved. Furthermore, approximately half the genes conserved in the core set encoded hypothetical proteins. Separation of the core and variant gene sets within S. enterica subspecies I has offered fundamental biological insight into the genetic basis of phenotypic similarity and diversity across S. enterica subspecies I and shown how the core genome of these pathogens differs from the closely related E. coli K-12 laboratory strain.

Genetic responses to phosphorus deficiency

Background: Phosphorus (P) is an essential macronutrient for plants. Plants take up P as phosphate (Pi) from the soil solution. Since little Pi is available in most soils, P fertilizers are applied to crops. However, the use of P fertilizers is unsustainable and may cause pollution. Consequently, there is a need to develop more P-use-efficient (PUE) crops and precise methods to monitor crop P-status. Scope: Manipulating the expression of genes to improve the PUE of crops could reduce their P fertilizer requirement. This has stimulated research towards the identification of genes and signalling cascades involved in plant responses to P deficiency. Genes that respond to P deficiency can be grouped into 'early' genes that respond rapidly and often non-specifically to P deficiency, or 'late' genes that impact on the morphology, physiology or metabolism of plants upon Prolonged P deficiency. Summary: The use of micro-array technology has allowed researchers to catalogue the genetic responses of plants to P deficiency. Genes whose expression is altered by P deficiency include various transcription factors, which are thought to coordinate plant responses to P deficiency, and other genes involved in P acquisition and tissue P economy. Several common cis-regulatory elements have been identified in the promoters of these genes, suggesting that their expression might be coordinated. It is suggested that knowledge of the genes whose expression changes in response to P deficiency might allow the development of crops with improved PUE, and could be used in diagnostic techniques to monitor P deficiency in crops either directly using 'smart' indicator plants or indirectly through transcript profiling. The development of crops with improved PUE and the adoption of diagnostic technology could reduce production costs, minimize the use of a non-renewable resource, reduce pollution and enhance biodiversity.