Functionally associated molecular genetic marker map construction in perennial ryegrass (Lolium perenne L.)

A molecular marker-based map of perennial ryegrass (Lolium perenne L.) has been constructed through the use of polymorphisms associated with expressed sequence tags (ESTs). A pair-cross between genotypes from a North African ecotype and the cultivar Aurora was used to generate a two-way pseudo-testcross population. A selection of 157 cDNAs assigned to eight different functional categories associated with agronomically important biological processes was used to detect polymorphic EST–RFLP loci in the F1(NA6 × AU6) population. A comprehensive set of EST–SSR markers was developed from the analysis of 14,767 unigenes, with 310 primer pairs showing efficient amplification and detecting 113 polymorphic loci. Two parental genetic maps were produced: the NA6 genetic map contains 88 EST–RFLP and 71 EST–SSR loci with a total map length of 963 cM, while the AU6 genetic map contains 67 EST–RFLP and 58 EST–SSR loci with a total map length of 757 cM. Bridging loci permitted the alignment of homologous chromosomes between the parental maps, and a sub-set of genomic DNA-derived SSRs was used to relate linkage groups to the perennial ryegrass reference map. Regions of segregation distortion were identified, in some instances in common with other perennial ryegrass maps. The EST-derived marker-based map provides the basis for in silico comparative genetic mapping, as well as the evaluation of co-location between QTLs and functionally associated genetic loci.

A new data source for fisheries resource assessment: genetic estimates of the effective number of spawners. Final Report to the Fisheries Research and Development Corporation.

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.

Characterisation of chicken Campylobacter jejuni isolates using resolution optimised single nucleotide polymorphisms and binary gene markers

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.

The use of genetic correlations to evaluate associations between SNP markers and quantitative traits

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.

New SNPs for population genetic analysis reveal possible cryptic speciation of eastern Australian sea mullet (Mugil cephalus)

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.

Development of single nucleotide polymorphism (SNP) markers from the mango (Mangifera indica) transcriptome for mapping and estimation of genetic diversity

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.