23 resultados para Single Nucleotide

em eResearch Archive - Queensland Department of Agriculture


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The principal objective of this study was to determine if Campylobacter jejuni genotyping methods based upon resolution optimised sets of single nucleotide polymorphisms (SNPs) and binary genetic markers were capable of identifying epidemiologically linked clusters of chicken-derived isolates. Eighty-eight C. jejuni isolates of known flaA RFLP type were included in the study. They encompassed three groups of ten isolates that were obtained at the same time and place and possessed the same flaA type. These were regarded as being epidemiologically linked. Twenty-six unlinked C. jejuni flaA type I isolates were included to test the ability of SNP and binary typing to resolve isolates that were not resolved by flaA RFLP. The remaining isolates were of different flaA types. All isolates were typed by real-time PCR interrogation of the resolution optimised sets of SNPs and binary markers. According to each typing method, the three epidemiologically linked clusters were three different clones that were well resolved from the other isolates. The 26 unlinked C. jejuni flaA type I isolates were resolved into 14 SNP-binary types, indicating that flaA typing can be unreliable for revealing epidemiological linkage. Comparison of the data with data from a fully typed set of isolates associated with human infection revealed that abundant lineages in the chicken isolates that were also found in the human isolates belonged to clonal complex (CC) -21 and CC-353, with the usually rare C-353 member ST-524 being especially abundant in the chicken collection. The chicken isolates selected to be diverse according to flaA were also diverse according to SNP and binary typing. It was observed that CC-48 was absent in the chicken isolates, despite being very common in Australian human infection isolates, indicating that this may be a major cause of human disease that is not chicken associated.

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Using an established genetic map, a single gene conditioning covered smut resistance, Ruh.7H, was mapped to the telomere region of chromosome 7HS in an Alexis/Sloop doubled haploid barley population. The closest marker to Ruh.7H, abg704 was 7.5 cM away. Thirteen loci on the distal end of 7HS with potential to contain single nucleotide polymorphisms (SNPs) were identified by applying a comparative genomics approach using rice sequence data. Of these, one locus produced polymorphic co-dominant bands of different size while two further loci contained SNPs that were identified using the recently developed high resolution melting (HRM) technique. Two of these markers flanked Ruh.7H with the proximal marker located 3.8 cM and the distal marker 2.7 cM away. This is the first report on the application of the HRM technique to SNP detection and to rapid scoring of known cleaved amplified polymorphic sequence (CAPS) markers in plants. This simple, precise post-PCR technique should find widespread use in the fine-mapping of genetic regions of interest in complex cereal and other plant genomes.

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Wood is an important biological resource which contributes to nutrient and hydrology cycles through ecosystems, and provides structural support at the plant level. Thousands of genes are involved in wood development, yet their effects on phenotype are not well understood. We have exploited the low genomic linkage disequilibrium (LD) and abundant phenotypic variation of forest trees to explore allelic diversity underlying wood traits in an association study. Candidate gene allelic diversity was modelled against quantitative variation to identify SNPs influencing wood properties, growth and disease resistance across three populations of Corymbia citriodora subsp. variegata, a forest tree of eastern Australia. Nine single nucleotide polymorphism (SNP) associations from six genes were identified in a discovery population (833 individuals). Associations were subsequently tested in two smaller populations (130160 individuals), validating our findings in three cases for actin 7 (ACT7) and COP1 interacting protein 7 (CIP7). The results imply a functional role for these genes in mediating wood chemical composition and growth, respectively. A flip in the effect of ACT7 on pulp yield between populations suggests gene by environment interactions are at play. Existing evidence of gene function lends strength to the observed associations, and in the case of CIP7 supports a role in cortical photosynthesis.

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Japanese isolates of Candidatus Liberibacter asiaticus have been shown to be clearly differentiated by simple sequence repeat (SSR) profiles at four loci. In this study, 25 SSR loci, including these four loci, were selected from the whole-genome sequence and were used to differentiate non-Japanese samples of Ca. Liberibacter asiaticus (13 Indian, 3 East Timorese, 1 Papuan and 8 Floridian samples). Out of the 25 SSR loci, 13 were polymorphic. Dendrogram analysis using SSR loci showed that the clusters were mostly consistent with the geographical origins of the isolates. When single nucleotide polymorphisms (SNPs) were searched around these 25 loci, only the upstream region of locus 091 exhibited polymorphism. Phylogenetic tree analysis of the SNPs in the upstream region of locus 091 showed that Floridian samples were clustered into one group as shown by dendrogram analysis using SSR loci. The differences in nucleotide sequences were not associated with differences in the citrus hosts (lime, mandarin, lemon and sour orange) from which the isolates were originally derived.

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The development of molecular markers for genomic studies in Mangifera indica (mango) will allow marker-assisted selection and identification of genetically diverse germplasm, greatly aiding mango breeding programs. We report here our identification of thousands of unambiguous molecular markers that can be easily assayed across genotypes of the species. With origin centered in Southeast Asia, mangos are grown throughout the tropics and subtropics as a nutritious fruit that exhibits remarkable intraspecific phenotypic diversity. With the goal of building a high density genetic map, we have undertaken discovery of sequence variation in expressed genes across a broad range of mango cultivars. A transcriptome sequence reference was built de novo from extensive sequencing and assembly of RNA from cultivar 'Tommy Atkins'. Single nucleotide polymorphisms (SNPs) in protein coding transcripts were determined from alignment of RNA reads from 24 mango cultivars of diverse origins: 'Amin Abrahimpur' (India), 'Aroemanis' (Indonesia), 'Burma' (Burma), 'CAC' (Hawaii), 'Duncan' (Florida), 'Edward' (Florida), 'Everbearing' (Florida), 'Gary' (Florida), 'Hodson' (Florida), 'Itamaraca' (Brazil), 'Jakarata' (Florida), 'Long' (Jamaica), 'M. Casturi Purple' (Borneo), 'Malindi' (Kenya), 'Mulgoba' (India), 'Neelum' (India), 'Peach' (unknown), 'Prieto' (Cuba), 'Sandersha' (India), 'Tete Nene' (Puerto Rico), 'Thai Everbearing' (Thailand), 'Toledo' (Cuba), 'Tommy Atkins' (Florida) and 'Turpentine' (West Indies). SNPs in a selected subset of protein coding transcripts are currently being converted into Fluidigm assays for genotyping of mapping populations and germplasm collections. Using an alternate approach, SNPs (144) discovered by sequencing of candidate genes in 'Kensington Pride' have already been converted and used for genotyping.

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The development of innovative methods of stock assessment is a priority for State and Commonwealth fisheries agencies. It is driven by the need to facilitate sustainable exploitation of naturally occurring fisheries resources for the current and future economic, social and environmental well being of Australia. This project was initiated in this context and took advantage of considerable recent achievements in genomics that are shaping our comprehension of the DNA of humans and animals. The basic idea behind this project was that genetic estimates of effective population size, which can be made from empirical measurements of genetic drift, were equivalent to estimates of the successful number of spawners that is an important parameter in process of fisheries stock assessment. The broad objectives of this study were to 1. Critically evaluate a variety of mathematical methods of calculating effective spawner numbers (Ne) by a. conducting comprehensive computer simulations, and by b. analysis of empirical data collected from the Moreton Bay population of tiger prawns (P. esculentus). 2. Lay the groundwork for the application of the technology in the northern prawn fishery (NPF). 3. Produce software for the calculation of Ne, and to make it widely available. The project pulled together a range of mathematical models for estimating current effective population size from diverse sources. Some of them had been recently implemented with the latest statistical methods (eg. Bayesian framework Berthier, Beaumont et al. 2002), while others had lower profiles (eg. Pudovkin, Zaykin et al. 1996; Rousset and Raymond 1995). Computer code and later software with a user-friendly interface (NeEstimator) was produced to implement the methods. This was used as a basis for simulation experiments to evaluate the performance of the methods with an individual-based model of a prawn population. Following the guidelines suggested by computer simulations, the tiger prawn population in Moreton Bay (south-east Queensland) was sampled for genetic analysis with eight microsatellite loci in three successive spring spawning seasons in 2001, 2002 and 2003. As predicted by the simulations, the estimates had non-infinite upper confidence limits, which is a major achievement for the application of the method to a naturally-occurring, short generation, highly fecund invertebrate species. The genetic estimate of the number of successful spawners was around 1000 individuals in two consecutive years. This contrasts with about 500,000 prawns participating in spawning. It is not possible to distinguish successful from non-successful spawners so we suggest a high level of protection for the entire spawning population. We interpret the difference in numbers between successful and non-successful spawners as a large variation in the number of offspring per family that survive – a large number of families have no surviving offspring, while a few have a large number. We explored various ways in which Ne can be useful in fisheries management. It can be a surrogate for spawning population size, assuming the ratio between Ne and spawning population size has been previously calculated for that species. Alternatively, it can be a surrogate for recruitment, again assuming that the ratio between Ne and recruitment has been previously determined. The number of species that can be analysed in this way, however, is likely to be small because of species-specific life history requirements that need to be satisfied for accuracy. The most universal approach would be to integrate Ne with spawning stock-recruitment models, so that these models are more accurate when applied to fisheries populations. A pathway to achieve this was established in this project, which we predict will significantly improve fisheries sustainability in the future. Regardless of the success of integrating Ne into spawning stock-recruitment models, Ne could be used as a fisheries monitoring tool. Declines in spawning stock size or increases in natural or harvest mortality would be reflected by a decline in Ne. This would be good for data-poor fisheries and provides fishery independent information, however, we suggest a species-by-species approach. Some species may be too numerous or experiencing too much migration for the method to work. During the project two important theoretical studies of the simultaneous estimation of effective population size and migration were published (Vitalis and Couvet 2001b; Wang and Whitlock 2003). These methods, combined with collection of preliminary genetic data from the tiger prawn population in southern Gulf of Carpentaria population and a computer simulation study that evaluated the effect of differing reproductive strategies on genetic estimates, suggest that this technology could make an important contribution to the stock assessment process in the northern prawn fishery (NPF). Advances in the genomics world are rapid and already a cheaper, more reliable substitute for microsatellite loci in this technology is available. Digital data from single nucleotide polymorphisms (SNPs) are likely to super cede ‘analogue’ microsatellite data, making it cheaper and easier to apply the method to species with large population sizes.

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Large-scale gene discovery has been performed for the grass fungal endophytes Neotyphodium coenophialum, Neotyphodium lolii, and Epichloë festucae. The resulting sequences have been annotated by comparison with public DNA and protein sequence databases and using intermediate gene ontology annotation tools. Endophyte sequences have also been analysed for the presence of simple sequence repeat and single nucleotide polymorphism molecular genetic markers. Sequences and annotation are maintained within a MySQL database that may be queried using a custom web interface. Two cDNA-based microarrays have been generated from this genome resource. They permit the interrogation of 3806 Neotyphodium genes (NchipTM microarray), and 4195 Neotyphodium and 920 Epichloë genes (EndoChipTM microarray), respectively. These microarrays provide tools for high-throughput transcriptome analysis, including genome-specific gene expression studies, profiling of novel endophyte genes, and investigation of the host grass–symbiont interaction. Comparative transcriptome analysis in Neotyphodium and Epichloë was performed

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Barley (Hordeum vulgare) genotypes were sequenced for polymorphism in the hardness genes, these being the three hordoindoline (hin a, hin b1 and hin b2) genes. The variation in haplotype was determined by sequencing for single nucleotide polymorphisms (SNPs). Polymorphism between each gene was then compared to grain hardness (three methods), malt quality characteristics (hot water extract and friability) and cattle feed quality. Two haplotypes were found in a set of forty barley genotypes. For hin a, two alleles were present, namely hin a1 and hin a2. However, there was no specific hin a allele that was associated with grain hardness, malt and feed quality. Barley has two hin b genes, namely hin b1 and hin b2, and the genotypes tested here had one of two alleles for each gene. However, there were no obvious effects on hardness or quality from either of these hin b alleles. Unlike wheat, where a clear relationship has been demonstrated between a number of SNPs in the wheat hardness genes and quality (soft or hard wheat), there was no such relationship for barley. Despite the wide range in hardness, malt and feed quality, there were only two haplotypes for each of the hin a, hin b1 and hin b2 genes and there was no clear relationship between grain hardness, malt or feed quality. The genotypes used in this study demonstrated that there was a low level of polymorphism in hardness genes in current commercial varieties as well as breeding lines and these polymorphisms had no impact on quality.

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Using DNA markers in plant breeding with marker-assisted selection (MAS) could greatly improve the precision and efficiency of selection, leading to the accelerated development of new crop varieties. The numerous examples of MAS in rice have prompted many breeding institutes to establish molecular breeding labs. The last decade has produced an enormous amount of genomics research in rice, including the identification of thousands of QTLs for agronomically important traits, the generation of large amounts of gene expression data, and cloning and characterization of new genes, including the detection of single nucleotide polymorphisms. The pinnacle of genomics research has been the completion and annotation of genome sequences for indica and japonica rice. This information-coupled with the development of new genotyping methodologies and platforms, and the development of bioinformatics databases and software tools-provides even more exciting opportunities for rice molecular breeding in the 21st century. However, the great challenge for molecular breeders is to apply genomics data in actual breeding programs. Here, we review the current status of MAS in rice, current genomics projects and promising new genotyping methodologies, and evaluate the probable impact of genomics research. We also identify critical research areas to "bridge the application gap" between QTL identification and applied breeding that need to be addressed to realize the full potential of MAS, and propose ideas and guidelines for establishing rice molecular breeding labs in the postgenome sequence era to integrate molecular breeding within the context of overall rice breeding and research programs.

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The highly variable flagellin-encoding flaA gene has long been used for genotyping Campylobacter jejuni and Campylobacter coli. High-resolution melting (HRM) analysis is emerging as an efficient and robust method for discriminating DNA sequence variants. The objective of this study was to apply HRM analysis to flaA-based genotyping. The initial aim was to identify a suitable flaA fragment. It was found that the PCR primers commonly used to amplify the flaA short variable repeat (SVR) yielded a mixed PCR product unsuitable for HRM analysis. However, a PCR primer set composed of the upstream primer used to amplify the fragment used for flaA restriction fragment length polymorphism (RFLP) analysis and the downstream primer used for flaA SVR amplification generated a very pure PCR product, and this primer set was used for the remainder of the study. Eighty-seven C. jejuni and 15 C. coli isolates were analyzed by flaA HRM and also partial flaA sequencing. There were 47 flaA sequence variants, and all were resolved by HRM analysis. The isolates used had previously also been genotyped using single-nucleotide polymorphisms (SNPs), binary markers, CRISPR HRM, and flaA RFLP.flaA HRM analysis provided resolving power multiplicative to the SNPs, binary markers, and CRISPR HRM and largely concordant with the flaA RFLP. It was concluded that HRM analysis is a promising approach to genotyping based on highly variable genes.

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To study the genetic basis of tick burden and milk production and their interrelationship, we collected a sample of 1961 cattle with multiple tick counts from northern Australia of which 973 had dairy production data in the Australian Dairy Herd Information Service database. We calculated heritabilities, genetic and phenotypic correlations for these traits and showed a negative relationship between tick counts and milk and milk component yield. Tests of polymorphisms of four genes associated with milk yield, ABCG2, DGAT1, GHR and PRLR, showed no statistically significant effect on tick burden but highly significant associations to milk component yield in these data and we confirmed separate effects for GHR and PRLR on bovine chromosome 20. To begin to identify some of the molecular genetic bases for these traits, we genotyped a sample of 189 of these cattle for 7397 single nucleotide polymorphisms in a genome-wide association study. Although the allele effects for adjusted milk fat and protein yield were highly correlated (r = 0.66), the correlations of allele effects of these milk component yields and tick burden were small (|r| <= 0.10). These results agree in general with the phenotypic correlations between tick counts and milk component yield and suggest that selection on markers for tick burden or milk component yield may have no undesirable effect on the other trait.

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Age at puberty is an important component of reproductive performance in beef cattle production systems. Brahman cattle are typically late-pubertal relative to Bos taurus cattle and so it is of economic relevance to select for early age at puberty. To assist selection and elucidate the genes underlying puberty, we performed a genome-wide association study (GWAS) using the BovineSNP50 chip (similar to 54 000 polymorphisms) in Brahman bulls (n = 1105) and heifers (n = 843) and where the heifers were previously analysed in a different study. In a new attempt to generate unbiased estimates of single-nucleotide polymorphism (SNP) effects and proportion of variance explained by each SNP, the available data were halved on the basis of year and month of birth into a calibration and validation set. The traits that defined age at puberty were, in heifers, the age at which the first corpus luteum was detected (AGECL, h(2) = 0.56 +/- 0.11) and in bulls, the age at a scrotal circumference of 26 cm (AGE26, h(2) = 0.78 +/- 0.10). At puberty, heifers were on average older (751 +/- 142 days) than bulls (555 +/- 101 days), but AGECL and AGE26 were genetically correlated (r = 0.20 +/- 0.10). There were 134 SNPs associated with AGECL and 146 SNPs associated with AGE26 (P < 0.0001). From these SNPs, 32 (similar to 22%) were associated (P < 0.0001) with both traits. These top 32 SNPs were all located on Chromosome BTA 14, between 21.95 Mb and 28.4 Mb. These results suggest that the genes located in that region of BTA 14 play a role in pubertal development in Brahman cattle. There are many annotated genes underlying this region of BTA 14 and these are the subject of current research. Further, we identified a region on Chromosome X where markers were associated (P < 1.00E-8) with AGE26, but not with AGECL. Information about specific genes and markers add value to our understanding of puberty and potentially contribute to genomic selection. Therefore, identifying these genes contributing to genetic variation in AGECL and AGE26 can assist with the selection for early onset of puberty.

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Open-pollinated progeny of Corymbia citriodora established in replicated field trials were assessed for stem diameter, wood density, and pulp yield prior to genotyping single nucleotide polymorphisms (SNP) and testing the significance of associations between markers and assessment traits. Multiple individuals within each family were genotyped and phenotyped, which facilitated a comparison of standard association testing methods and an alternative method developed to relate markers to additive genetic effects. Narrow-sense heritability estimates indicated there was significant additive genetic variance within this population for assessment traits ( h ˆ 2 =0.28to0.44 ) and genetic correlations between the three traits were negligible to moderate (r G = 0.08 to 0.50). The significance of association tests (p values) were compared for four different analyses based on two different approaches: (1) two software packages were used to fit standard univariate mixed models that include SNP-fixed effects, (2) bivariate and multivariate mixed models including each SNP as an additional selection trait were used. Within either the univariate or multivariate approach, correlations between the tests of significance approached +1; however, correspondence between the two approaches was less strong, although between-approach correlations remained significantly positive. Similar SNP markers would be selected using multivariate analyses and standard marker-trait association methods, where the former facilitates integration into the existing genetic analysis systems of applied breeding programs and may be used with either single markers or indices of markers created with genomic selection processes.

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Spike density in barley is under the control of several major genes, as documented previously by genetic analysis of a number of morphological mutants. One such class of mutants affects the rachis internode length leading to dense or compact spikes and the underlying genes were designated dense spike (dsp). We previously delimited two introgressed genomic segments on chromosome 3H (21 SNP loci, 35.5 cM) and 7H (17 SNP loci, 20.34 cM) in BW265, a BC7F3 nearly isogenic line (NIL) of cv. Bowman as potentially containing the dense spike mutant locus dsp.ar, by genotyping 1,536 single nucleotide polymorphism (SNP) markers in both BW265 and its recurrent parent. Here, the gene was allocated by high-resolution bi-parental mapping to a 0.37 cM interval between markers SC57808 (Hv_SPL14)-CAPSK06413 residing on the short and long arm at the genetic centromere of chromosome 7H, respectively. This region putatively contains more than 800 genes as deduced by comparison with the collinear regions of barley, rice, sorghum and Brachypodium, Classical map-based isolation of the gene dsp.ar thus will be complicated due to the infavorable relationship of genetic to physical distances at the target locus.

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Sustainable management of sea mullet (Mugil cephalus) fisheries needs to account for recent observations of regional-scale differentiation. Population genetic analysis is sought to assess the situation of this ecologically and economically important fish species in eastern Australian waters. Here, we report (i) new population genetic markers [single nucleotide polymorphisms (SNPs) and potential microsatellites], (ii) first estimates of spatial genetic differentiation and (iii) prospective power tests for designing more comprehensive studies. Six DNA samples from three sampling regions (North Queensland, South Queensland and central New South Wales) on the eastern coast of Australia were used to prepare restriction site associated DNA (RAD) tag libraries from genomic DNA digested with EcoRI and MseI. A pooled sample of regional RAD tag libraries was sequenced using the Roche GS-FLX Titanium platform. A total of 172837 raw reads (17.4Mbp) were retrieved, 95500 of which were used to discover 1267 SNPs and 1417 microsatellites. A subset of 161 SNPs was validated based on 63 additional DNA samples genotyped using the Sequenom MassArray (iPLEX Gold chemistry). Altogether 92 SNPs (57%) were confirmed, with 40% of these marking fixed variants between northern and southern sampling regions. Our preliminary findings indicate a multispecies fishery stock of M. cephalus in eastern Australian waters, but suggest that strong genetic differentiation occurs north of major fishing grounds. Low potential differentiation within major fishing grounds (e.g. FST=0.0025) can be resolved with a likely power 67% by using standard sample sizes of 50 and validated subsets of available markers.