Project description:Technological advances are progressively increasing the application of genomics to a wider array of economically and ecologically important species. High-density maps enriched for transcribed genes facilitate the discovery of connections between genes and phenotypes. We report the construction of a high-density linkage map of expressed genes for the heterozygous genome of Eucalyptus using Single Feature Polymorphism (SFP) markers. SFP discovery and mapping was achieved using pseudo-testcross screening and selective mapping to simultaneously optimize linkage mapping and microarray costs. SFP genotyping was carried out by hybridizing complementary RNA prepared from 4.5 year-old trees xylem to an SFP array containing 103,000 25-mer oligonucleotide probes representing 20,726 unigenes derived from a modest size expressed sequence tags collection. An SFP-mapping microarray with 43,777 selected candidate SFP probes representing 15,698 genes was subsequently designed and used to genotype SFPs in a larger subset of the segregating population drawn by selective mapping. A total of 1,845 genes were mapped, with 884 of them ordered with high likelihood support on a framework map anchored to 180 microsatellites with average density of 1.2 cM. Using more probes per unigene increased by two-fold the likelihood of detecting segregating SFPs eventually resulting in more genes mapped. In silico validation showed that 87% of the SFPs map to the expected location on the 4.5X draft sequence of the Eucalyptus grandis genome. The Eucalyptus 1,845 gene map is the most highly enriched map for transcriptional information for any forest tree species to date. It represents a major improvement on the number of genes previously positioned on Eucalyptus maps and provides an initial glimpse at the gene space for this global tree genome. A general protocol is proposed to build high-density transcript linkage maps in less characterized plant species by SFP genotyping with a concurrent objective of reducing microarray costs. HIgh-density gene-rich maps represent a powerful resource to assist gene discovery endeavors when used in combination with QTL and association mapping and should be especially valuable to assist the assembly of reference genome sequences soon to come for several plant and animal species.

Project description:Advances in genomic technologies are rapidly filling the gap in genomic information available from non-model species that are economically and ecologically important. Reduction in costs and higher throughput of data acquisition will progressively increase the application of genomics in population and quantitative genetics. In molecular breeding, the ability to rapidly develop large numbers of genetic markers and generate high-density genetic maps at low cost is critical because they provide the framework for identification of elements that regulate trait variation, connecting genetics and genomics to phenotype. To generate the first high-density, gene-based genetic map for Eucalyptus, we genotyped a hybrid segregating population with microarray-based markers. The genus Eucalyptus includes the most economically important species used for bioenergy pulp and paper production worldwide. A custom 25-mers oligonucleotide array was designed based on 20,726 expressed sequence tags consensus, and RNA from 28 biologically-replicated individuals allowed clear-cut detection of putative single feature polymorphisms (SFPs) segregating 1:1 and 3:1. A genotyping array confirmed the segregation in a larger portion of the family and a genetic map with 1064 gene-related markers is made available with an average of one marker every 1.2 cM. Interestingly, reanalyzing the data from the 28 genotypes using a mixed-model approach resulted in most of the mapped genes among the significant probesets. We also demonstrate that designing more probes per gene increases the chance of mapping those genes. Finally, in silico validatation shows that 87% of the markers map to expected location on the draft genome, an important characteristic of SFP markers. Simultaneously detecting and genotyping SFP markers in a subset of the mapping population instead of only the genitors was more efficient for mapping genes in outcrossing species than previously reported approaches. Mapping SFP markers require low genomic resources and can be done at relatively low cost. We demonstrate the possibility of mapping hundreds to thousands of genes that can ultimately be used in generating further genomic resources, such as genome assembly, or for more direct applications, such as QTL analysis. Two biological replication of 28 genotypes were hybridized to the custom microarray, labeled with Cy3 and Cy5. Genotypes are fullsib progenies of the cross E. urophylla X E. grandis. A loop design was employed for the hybridization using xylem tissue. In total the microarray comprised 103,000 probes representing 20,726 unigenes with an average of five probes per unigene. Twenty-six negative control probes were also included in the microarray.

Project description:Advances in genomic technologies are rapidly filling the gap in genomic information available from non-model species that are economically and ecologically important. Reduction in costs and higher throughput of data acquisition will progressively increase the application of genomics in population and quantitative genetics. In molecular breeding, the ability to rapidly develop large numbers of genetic markers and generate high-density genetic maps at low cost is critical because they provide the framework for identification of elements that regulate trait variation, connecting genetics and genomics to phenotype. To generate the first high-density, gene-based genetic map for Eucalyptus, we genotyped a hybrid segregating population with microarray-based markers. The genus Eucalyptus includes the most economically important species used for bioenergy pulp and paper production worldwide. A custom 25-mers oligonucleotide array was designed based on 20,726 expressed sequence tags consensus, and RNA from 28 biologically-replicated individuals allowed clear-cut detection of putative single feature polymorphisms (SFPs) segregating 1:1 and 3:1. A genotyping array confirmed the segregation in a larger portion of the family and a genetic map with 1064 gene-related markers is made available with an average of one marker every 1.2 cM. Interestingly, reanalyzing the data from the 28 genotypes using a mixed-model approach resulted in most of the mapped genes among the significant probesets. We also demonstrate that designing more probes per gene increases the chance of mapping those genes. Finally, in silico validatation shows that 87% of the markers map to expected location on the draft genome, an important characteristic of SFP markers. Simultaneously detecting and genotyping SFP markers in a subset of the mapping population instead of only the genitors was more efficient for mapping genes in outcrossing species than previously reported approaches. Mapping SFP markers require low genomic resources and can be done at relatively low cost. We demonstrate the possibility of mapping hundreds to thousands of genes that can ultimately be used in generating further genomic resources, such as genome assembly, or for more direct applications, such as QTL analysis. Two technical replication of 68 individuals were hybridized to the custom microarray, labeled with Cy3 and Cy5. Individuals are fullsib progenies of the cross E. urophylla X E. grandis. A loop design was employed for the hybridization using xylem tissue. In total the microarray comprised 43,803 probes representing 15,698 unigenes. These probes were pre-selected in a screening array based on their mendelian segregation and bimodal signal separation. Twenty-six negative control probes were also included in the microarray.

Project description:Background:; Cowpea (Vigna unguiculata L. Walp) is an important food and fodder legume of the semiarid tropics and subtropics worldwide, especially in sub-Saharan Africa. High density genetic linkage maps are needed for marker assisted breeding but are not available for cowpea. A single feature polymorphism (SFP) is a microarray-based marker which can be used for high throughput genotyping and high density mapping. Results:; Here we report detection and validation of SFPs in cowpea using a readily available soybean (Glycine max) genome array. Robustified projection pursuit (RPP) was used for statistical analysis using RNA as a surrogate for DNA. Using a 15% outlying score cut-off, 1058 potential SFPs were enumerated between two parents of a recombinant inbred line (RIL) population segregating for several important traits including drought tolerance, Fusarium and brown blotch resistance, grain size and photoperiod sensitivity. Sequencing of 25 putative polymorphism-containing amplicons yielded a SFP probe set validation rate of 68%. Conclusions:; We conclude that the Affymetrix soybean genome array is a satisfactory platform for identification of some 1000âs of SFPs for cowpea. This study provides an example of extension of genomic resources from a well supported species to an orphan crop. Presumably, other legume systems are similarly tractable to SFP marker development using existing legume array resources. SUBMITTER_CITATION: Detection and validation of single feature polymorphisms in cowpea (Vigna unguiculata L. Walp) using a soybean genome array Sayan Das, Prasanna R. Bhat, Chinta Sudhakar, Jeffrey D. Ehlers, Steve Wanamaker, Philip A. Roberts, Xinping Cui, Timothy J. Close BMC Genomics 2008, 9:107 Experiment Overall Design: Expression data were generated by hybridizing cowpea cRNA to the soybean genome array. A statistical method called robustified projection pursuit (RPP) was used for Single Feature Polymorphism(SFP) analysis. Only the values from the PM probes were utilized. The use of RNA as a surrogate for genomic DNA eliminated interference from highly repetitive DNA as a technical impediment to SFP detection. An important aspect of the RPP method is that it first utilizes a probe set level analysis to identify SFP-containing probe sets and then chooses individual probes from within each SFP-containing probe set. The net result is the identification of probes that directly overlay polymorphic sequences. Experiment Overall Design: Separate comparisons were made between two genotypes (with two replicates each) for unstressed and drought stressed treatments, resulting in two SFP lists. In the context of SFPs, there is no necessity to have separate stress and control lists; in fact it would be simpler and less costly to have only one SFP list from highly complex RNA made by blending stressed and unstressed RNA. In our case, two separate lists were available as a consequence of another study not described here which compared gene expression patterns in stressed and control plants (data not shown). At 15% outlying score cut-off, we detected 488 SFP probes in stressed and 661 SFP probes in unstressed treatments. The union of these two lists contained 1058 SFP probes and the intersection contained 91. A total of 37 primer pairs targeting 37 putative SFP probe sets were initially tested, of which 25 yielded single amplicons of the expected sizes from both parents. These 25 amplicons targeted 14 probe sets selected from the intersection of the two SFP probe set lists and 11 from the remaining SFP probe sets. 9 of the 14 SFP probe sets (64%) from the intersection list were validated at the DNA sequence level and 8 of the other 11 (73%) were validated.

Project description:Background: Genome-wide detection of single feature polymorphisms (SFP) in swine using transcriptome profiling of day 25 placental RNA by contrasting probe intensities from either Meishan or an occidental composite breed with Affymetrix porcine microarrays is presented. A linear mixed model analysis was used to identify significant breed-by-probe interactions. Results: Gene specific linear mixed models were fit to each of the log2 transformed probe intensities on these arrays, using fixed effects for breed, probe, breed-by-probe interaction, and a random effect for array. After surveying the day 25 placental transcriptome, 789 probes with a q-value ≤ 0.05 and |fold change| ≥ 2 for the breed-by-probe interaction were identified as candidates containing SFP. To address the quality of the bioinformatics approach, universal pyrosequencing assays were designed from Affymetrix exemplar sequences to independently assess polymorphisms within a subset of probes. Of those probes sampled from high-, medium-, and low-ranking categories, 20 of 27 were confirmed by pyrosequencing to contain SFPs. In most cases, the 25-mer probe sequence printed on the microarray diverged from Meishan, not occidental crosses. This analysis was used to define a set of highly reliable predicted SFPs according to their probability scores. Conclusions: By this method we detected transition and transversion single nucleotide polymorphisms, as well as insertions/deletions. These results demonstrate that this approach can identify polymorphisms between two breeds and/or lines of any species for which a short oligonucleotide array is available, and can be used to rapidly develop markers for genetic mapping and association analysis in species where high density genotyping platforms are otherwise unavailable. SNPs and INDELS discovered by this approach have been publicly deposited in NCBI’s SNP repository dbSNP. This method is an attractive bioinformatics tool for uncovering breed-by-probe interactions, for rapidly identifying expressed SNPs, for investigating potential functional correlations between gene expression and breed polymorphisms, and is robust enough to be used on any Affymetrix gene expression platform. Keywords: Transcriptional profiling of Day 25 porcine placentas

Project description:Background: Genome-wide detection of single feature polymorphisms (SFP) in swine using transcriptome profiling of day 25 placental RNA by contrasting probe intensities from either Meishan or an occidental composite breed with Affymetrix porcine microarrays is presented. A linear mixed model analysis was used to identify significant breed-by-probe interactions. Results: Gene specific linear mixed models were fit to each of the log2 transformed probe intensities on these arrays, using fixed effects for breed, probe, breed-by-probe interaction, and a random effect for array. After surveying the day 25 placental transcriptome, 789 probes with a q-value ≤ 0.05 and |fold change| ≥ 2 for the breed-by-probe interaction were identified as candidates containing SFP. To address the quality of the bioinformatics approach, universal pyrosequencing assays were designed from Affymetrix exemplar sequences to independently assess polymorphisms within a subset of probes. Of those probes sampled from high-, medium-, and low-ranking categories, 20 of 27 were confirmed by pyrosequencing to contain SFPs. In most cases, the 25-mer probe sequence printed on the microarray diverged from Meishan, not occidental crosses. This analysis was used to define a set of highly reliable predicted SFPs according to their probability scores. Conclusions: By this method we detected transition and transversion single nucleotide polymorphisms, as well as insertions/deletions. These results demonstrate that this approach can identify polymorphisms between two breeds and/or lines of any species for which a short oligonucleotide array is available, and can be used to rapidly develop markers for genetic mapping and association analysis in species where high density genotyping platforms are otherwise unavailable. SNPs and INDELS discovered by this approach have been publicly deposited in NCBI’s SNP repository dbSNP. This method is an attractive bioinformatics tool for uncovering breed-by-probe interactions, for rapidly identifying expressed SNPs, for investigating potential functional correlations between gene expression and breed polymorphisms, and is robust enough to be used on any Affymetrix gene expression platform. Keywords: Transcriptional profiling of Day 25 porcine placentas 30 samples: Breed (Meishan, Occidental) Placental Tissue, Days (25, 45, 65, 85, 105)

Project description:Background: Genome-wide detection of single feature polymorphisms (SFP) in swine using transcriptome profiling of day 25 placental RNA by contrasting probe intensities from either Meishan or an occidental composite breed with Affymetrix porcine microarrays is presented. A linear mixed model analysis was used to identify significant breed-by-probe interactions. Results: Gene specific linear mixed models were fit to each of the log2 transformed probe intensities on these arrays, using fixed effects for breed, probe, breed-by-probe interaction, and a random effect for array. After surveying the day 25 placental transcriptome, 789 probes with a q-value â¤ 0.05 and |fold change| â¥ 2 for the breed-by-probe interaction were identified as candidates containing SFP. To address the quality of the bioinformatics approach, universal pyrosequencing assays were designed from Affymetrix exemplar sequences to independently assess polymorphisms within a subset of probes. Of those probes sampled from high-, medium-, and low-ranking categories, 20 of 27 were confirmed by pyrosequencing to contain SFPs. In most cases, the 25-mer probe sequence printed on the microarray diverged from Meishan, not occidental crosses. This analysis was used to define a set of highly reliable predicted SFPs according to their probability scores. Conclusions: By this method we detected transition and transversion single nucleotide polymorphisms, as well as insertions/deletions. These results demonstrate that this approach can identify polymorphisms between two breeds and/or lines of any species for which a short oligonucleotide array is available, and can be used to rapidly develop markers for genetic mapping and association analysis in species where high density genotyping platforms are otherwise unavailable. SNPs and INDELS discovered by this approach have been publicly deposited in NCBIâs SNP repository dbSNP. This method is an attractive bioinformatics tool for uncovering breed-by-probe interactions, for rapidly identifying expressed SNPs, for investigating potential functional correlations between gene expression and breed polymorphisms, and is robust enough to be used on any Affymetrix gene expression platform. Keywords: Transcriptional profiling of Day 25 porcine placentas 6 samples: Breed (Meishan, Occidental) Placental Tissue, Day 25

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Gene expression in xylem tissue on an Eucalyptus pseudo-testcross population: discovery array probes

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