Getting the most out of your fungal microarray data: two cost- and time-effective methods.

Advances in genome sequencing technologies have facilitated production of a wealth of fungal data; within the last 5 years, experimental costs and labor have diminished, shifting the production bottleneck from genomic data generation to data analysis. Genome sequences and microarrays now exist for many fungi, and transcriptional profiling has been shown to be an efficient way to examine how the entire genome changes in response to many different environments or treatments. Multiple platforms, programs, and protocols exist for analyzing such data, making this task daunting for the bench-based scientist. Furthermore, many existing programs are expensive and require license renewals on a yearly basis for each user in the laboratory. Costs may be prohibitively high for bench-based scientists in academia. Our combined experiences with this kind of analysis have favored two programs, depending upon whether the scientist is working with single- or dual-channel hybridization data. Our protocols are aimed toward helping the bench-based PI get the most possible information from their data, without the need for expensive software or an experienced bioinformaticist.

Deep sequencing reveals the complex and coordinated transcriptional regulation of genes related to grain quality in rice cultivars.

BACKGROUND: Milling yield and eating quality are two important grain quality traits in rice. To identify the genes involved in these two traits, we performed a deep transcriptional analysis of developing seeds using both massively parallel signature sequencing (MPSS) and sequencing-by-synthesis (SBS). Five MPSS and five SBS libraries were constructed from 6-day-old developing seeds of Cypress (high milling yield), LaGrue (low milling yield), Ilpumbyeo (high eating quality), YR15965 (low eating quality), and Nipponbare (control). RESULTS: The transcriptomes revealed by MPSS and SBS had a high correlation co-efficient (0.81 to 0.90), and about 70% of the transcripts were commonly identified in both types of the libraries. SBS, however, identified 30% more transcripts than MPSS. Among the highly expressed genes in Cypress and Ilpumbyeo, over 100 conserved cis regulatory elements were identified. Numerous specifically expressed transcription factor (TF) genes were identified in Cypress (282), LaGrue (312), Ilpumbyeo (363), YR15965 (260), and Nipponbare (357). Many key grain quality-related genes (i.e., genes involved in starch metabolism, aspartate amino acid metabolism, storage and allergenic protein synthesis, and seed maturation) that were expressed at high levels underwent alternative splicing and produced antisense transcripts either in Cypress or Ilpumbyeo. Further, a time course RT-PCR analysis confirmed a higher expression level of genes involved in starch metabolism such as those encoding ADP glucose pyrophosphorylase (AGPase) and granule bound starch synthase I (GBSS I) in Cypress than that in LaGrue during early seed development. CONCLUSION: This study represents the most comprehensive analysis of the developing seed transcriptome of rice available to date. Using two high throughput sequencing methods, we identified many differentially expressed genes that may affect milling yield or eating quality in rice. Many of the identified genes are involved in the biosynthesis of starch, aspartate family amino acids, and storage proteins. Some of the differentially expressed genes could be useful for the development of molecular markers if they are located in a known QTL region for milling yield or eating quality in the rice genome. Therefore, our comprehensive and deep survey of the developing seed transcriptome in five rice cultivars has provided a rich genomic resource for further elucidating the molecular basis of grain quality in rice.

Transcriptome profiling of the rice blast fungus during invasive plant infection and in vitro stresses.

BACKGROUND: Rice blast is the most threatening disease to cultivated rice. Magnaporthe oryzae, its causal agent, is likely to encounter environmental challenges during invasive growth in its host plants that require shifts in gene expression to establish a compatible interaction. Here, we tested the hypothesis that gene expression patterns during in planta invasive growth are similar to in vitro stress conditions, such as nutrient limitation, temperature up shift and oxidative stress, and determined which condition most closely mimicked that of in planta invasive growth. Gene expression data were collected from these in vitro experiments and compared to fungal gene expression during the invasive growth phase at 72 hours post-inoculation in compatible interactions on two grass hosts, rice and barley. RESULTS: We identified 4,973 genes that were differentially expressed in at least one of the in planta and in vitro stress conditions when compared to fungal mycelia grown in complete medium, which was used as reference. From those genes, 1,909 showed similar expression patterns between at least one of the in vitro stresses and rice and/or barley. Hierarchical clustering of these 1,909 genes showed three major clusters in which in planta conditions closely grouped with the nutrient starvation conditions. Out of these 1,909 genes, 55 genes and 129 genes were induced and repressed in all treatments, respectively. Functional categorization of the 55 induced genes revealed that most were either related to carbon metabolism, membrane proteins, or were involved in oxidoreduction reactions. The 129 repressed genes showed putative roles in vesicle trafficking, signal transduction, nitrogen metabolism, or molecular transport. CONCLUSIONS: These findings suggest that M. oryzae is likely primarily coping with nutrient-limited environments at the invasive growth stage 72 hours post-inoculation, and not with oxidative or temperature stresses.

Allelic genome structural variations in maize detected by array comparative genome hybridization.

DNA polymorphisms such as insertion/deletions and duplications affecting genome segments larger than 1 kb are known as copy-number variations (CNVs) or structural variations (SVs). They have been recently studied in animals and humans by using array-comparative genome hybridization (aCGH), and have been associated with several human diseases. Their presence and phenotypic effects in plants have not been investigated on a genomic scale, although individual structural variations affecting traits have been described. We used aCGH to investigate the presence of CNVs in maize by comparing the genome of 13 maize inbred lines to B73. Analysis of hybridization signal ratios of 60,472 60-mer oligonucleotide probes between inbreds in relation to their location in the reference genome (B73) allowed us to identify clusters of probes that deviated from the ratio expected for equal copy-numbers. We found CNVs distributed along the maize genome in all chromosome arms. They occur with appreciable frequency in different germplasm subgroups, suggesting ancient origin. Validation of several CNV regions showed both insertion/deletions and copy-number differences. The nature of CNVs detected suggests CNVs might have a considerable impact on plant phenotypes, including disease response and heterosis.

Whole genome scan detects an allelic variant of fad2 associated with increased oleic acid levels in maize.

We used whole genome scan association mapping to identify loci with major effect on oleic acid content in maize kernels. Single nucleotide polymorphism haplotypes at 8,590 loci were tested for association with oleic acid content in 553 maize inbreds. A single locus with major effect on oleic acid was mapped between 380 and 384 cM in the IBM2 neighbors genetic map on chromosome 4 and confirmed in a biparental population. A fatty acid desaturase, fad2, identified approximately 2 kb from the associated genetic marker, is the most likely candidate gene responsible for the differences in the phenotype. The fad2 alleles with high- and low-oleic acid content were sequenced and allelic differences in fad2 RNA level in developing embryos was investigated. We propose that a non-conservative amino acid polymorphism near the active site of fad2 contributes to the effect on oleic acid content. This is the first report of the use of a high resolution whole genome scan association mapping where a putative gene responsible for a quantitative trait was identified in plants.

A set of multiplex panels of microsatellite markers for rapid molecular characterization of rice accessions.

BACKGROUND: This study aimed to analyze the efficiency of three new microsatellite multiplex panels, which were designed to evaluate a total of 16 loci of the rice genome, based on single PCR reactions of each panel. A sample of 548 accessions of traditional upland rice landraces collected in Brazil in the last 25 years was genotyped, a database of allelic frequencies was established, estimates of genetic parameters were performed and analysis of genetic structure of the collection was developed. RESULTS: The three panels yielded a combined matching probability of 6.4 x 10-21, polymorphism information content (PIC) of 0.637, and a combined power of exclusion greater than 99.99%. A few samples presented a genetic background of indica rice. The 16 SSR loci produced a total of 229 alleles. Gene diversity values averaged 0.667, and PIC values averaged 0.637. Genetic structure analysis of the collection using a Bayesian approach detected three possible major clusters, with an overall FST value of 0.177. Important inputs on the knowledge about upland rice germplasm differentiations which happened in Brazil in the last few centuries were also achieved and are discussed. CONCLUSION: The three multiplex panels described here represent a powerful tool for rice genetic analysis, offering a rapid and efficient option for rice germplasm characterization. The data gathered demonstrates the feasibility of genotyping extensive germplasm collections using panels of multiplexed microsatellite markers. It contributes to the advancement of research on large scale characterization and management of germplasm banks, as well as identification, protection and assessments of genetic relationship of rice germplasm.

An expression atlas of rice mRNAs and small RNAs.

Identification of all expressed transcripts in a sequenced genome is essential both for genome analysis and for realization of the goals of systems biology. We used the transcriptional profiling technology called 'massively parallel signature sequencing' to develop a comprehensive expression atlas of rice (Oryza sativa cv Nipponbare). We sequenced 46,971,553 mRNA transcripts from 22 libraries, and 2,953,855 small RNAs from 3 libraries. The data demonstrate widespread transcription throughout the genome, including sense expression of at least 25,500 annotated genes and antisense expression of nearly 9,000 annotated genes. An additional set of approximately 15,000 mRNA signatures mapped to unannotated genomic regions. The majority of the small RNA data represented lower abundance short interfering RNAs that match repetitive sequences, intergenic regions and genes. Among these, numerous clusters of highly regulated small RNAs were readily observed. We developed a genome browser (http://mpss.udel.edu/rice) for public access to the transcriptional profiling data for this important crop.