- Research article
- Open Access
Experimental annotation of the human pathogen Histoplasma capsulatum transcribed regions using high-resolution tiling arrays
© Voorhies et al; licensee BioMed Central Ltd. 2011
- Received: 16 June 2011
- Accepted: 29 September 2011
- Published: 29 September 2011
The fungal pathogen Histoplasma capsulatum is thought to be the most common cause of fungal respiratory infections in immunocompetent humans, yet little is known about its biology. Here we provide the first genome-wide studies to experimentally validate its genome annotation. A functional interrogation of the Histoplasma genome provides critical support for continued investigation into the biology and pathogenesis of H. capsulatum and related fungi.
We employed a three-pronged approach to provide a functional annotation for the H. capsulatum G217B strain. First, we probed high-density tiling arrays with labeled cDNAs from cells grown under diverse conditions. These data defined 6,172 transcriptionally active regions (TARs), providing validation of 6,008 gene predictions. Interestingly, 22% of these predictions showed evidence of anti-sense transcription. Additionally, we detected transcription of 264 novel genes not present in the original gene predictions. To further enrich our analysis, we incorporated expression data from whole-genome oligonucleotide microarrays. These expression data included profiling under growth conditions that were not represented in the tiling experiment, and validated an additional 2,249 gene predictions. Finally, we compared the G217B gene predictions to other available fungal genomes, and observed that an additional 254 gene predictions had an ortholog in a different fungal species, suggesting that they represent genuine coding sequences.
These analyses yielded a high confidence set of validated gene predictions for H. capsulatum. The transcript sets resulting from this study are a valuable resource for further experimental characterization of this ubiquitous fungal pathogen. The data is available for interactive exploration at http://histo.ucsf.edu.
- Gene Prediction
- Antisense Transcript
- Tiling Array
- Tiling Density
- Tiling Data
The elucidation of H. capsulatum pathogenesis and biology has been greatly aided by the genome sequencing of H. capsulatum strains G217B and G186AR at the Genome Sequencing Center (GSC) at Washington University in St. Louis and strains G186AR, WU24, H88, and H143 at the BROAD Institute. These sequenced genomes open up a wealth of possibilities for the H. capsulatum community, enabling or abetting tools such as expression arrays, insertional mutagenesis, and bioinformatic analysis. However, these approaches are limited by the gene annotations associated with the genome assemblies. This limitation is pronounced in H. capsulatum given this eukaryote's sparse gene structure and a limited set of known transcripts with which to train gene prediction algorithms. Accordingly, although the GSC used a variety of tools to generate a set of predicted genes for G217B and G186AR http://genome.wustl.edu/genomes/view/histoplasma_capsulatum/, these predictions are based on limited experimental data.
In other systems where the gene finding problem has presented itself, whole genome tiling has proven a reliable technique for direct observation of the transcriptome[3–6]. To this end, we generated a set of tiling microarrays spanning the non-repetitive regions of the G217B genome and hybridized these arrays with a pool of cDNA derived from yeast-form Histoplasma growing under a diverse set of conditions. The resultant data give an unbiased measure of expression level as a function of genome position, and thus identify the locations and boundaries of expressed genes. The results of this study are available, along with tools for interactive exploration of the data, at http://histo.ucsf.edu.
Whole-genome tiling array expression profiling
Detection of predicted genes
Detection on only the antisense strand may correspond to incorrect predictions coinciding with bona fide transcripts on the opposite strand (e.g., Figure 3b iii, in which there is a spurious prediction antisense to the known 5' UTR of FDH1) or to true genes that are repressed by an antisense transcript in our pooled yeast sample. Due to this ambiguity, genes in this category were not considered "detected". An additional 264 novel transcripts, which were not present in the predicted set, were also detected (Figure 3b iv), as described below. As part of the web database associated with this study, the detected transcript set can be viewed in the context of the raw tiling signal and predicted gene set (as in Figure 3), allowing human estimation of transcript set accuracy on a case by case basis.
Features of transcribed regions in the H. capsulatum genome
The majority of TARs that did not overlap with gene predictions corresponded to unpredicted UTR sequences. For example, 29% of non-overlapping TAR sequence can be interpreted as 5'UTR (immediately upstream of and contiguous with a gene prediction), and 35% as 3'UTR (immediate downstream of and contiguous with a gene prediction). Additionally, 33% of non-overlapping TARs corresponded to the intervening sequence between two predictions (i.e., intergenic sequence incorrectly detected as transcribed due to the resolution limits of the tiling strategy, or long transcripts incorrectly predicted as multiple genes).
Tiling arrays revealed 264 novel genes
One advantage of a tiling strategy is that it can uncover novel TARs that do not correspond to the predicted genes. Our tiling analysis detected 264 such loci that were not represented in the GSC predicted gene set for G217B (e.g., Figure 3b iv). TARs were designated as "novel" if (1) they had no overlap with gene predictions on either strand, (2) they did not fall into the "5'UTR", "3'UTR", or "intervening" classifications described above (i.e., the flanking 5' and 3' base did not coincide with a gene prediction), and (3) they had no overlap with repeat regions.
To determine whether the novel loci correspond to conserved sequences in other genomes and, if so, if these homologous loci have been independently annotated as transcribed (i.e., if they are merely unannotated in G217B), we searched for conserved sequences in other dimorphic fungal pathogens within the order Onygenales (4 strains of H. capsulatum, 2 strains of Blastomyces dermatitidis, 3 strains of Paracoccidioides brasiliensis, and the reference strain of Coccidioides immitis).
Taken together, these results suggest that: 1) the isolated novel sequences are conserved at the sequence level, and, therefore, likely to be transcribed, relative to the other H. capsulatum strains in most cases, and relative to B. dermatitidis for about half of the cases; 2) transcripts with deeply conserved sequence across the Onygenales also tend to be predicted as genes in most of these fungi; and 3) for about half of the isolated novel sequences, a corresponding gene prediction exists in another genome, highlighting differences in the prediction pipelines, while the other half represent truly novel discoveries of this tiling experiment.
Using standard expression profiling and sequence homology to enrich gene validation
Genes that were validated by tiling, gene expression, and sequence homology represented the largest category of predictions (5,379 genes) and accounted for 56% of the non-repeat predicted gene set. The next largest category was 1,404 genes validated by gene-expression and sequence conservation but not by the tiling experiment (15% of the non-repeat predicted gene set), followed by 845 genes (9%) validated only by expression array, and 487 genes (5%) validated by expression and tiling but not sequence conservation. 1,099 gene predictions (11%) were unvalidated by any of the three methods.
In the following discussion, predicted genes are referred to by their common names. Additional file 2, Table S2 gives the corresponding systematic names.
Genes that were missed by tiling array showed enriched expression in the mycelial form
As expected, gene predictions that were not detected by tiling tended to show reduced expression in the yeast phase and enhanced expression in the mycelial form. Examples include TYR1 and ABC4, both previously identified as highly enriched in the mycelial phase ; VELC, a mycelial-enriched paralog of the morphological regulators RYP2 and RYP3 ; and the ortholog of BDBG_03463, which is paralogous to the B. dermatitidis gene BYS1 (BYS1 itself has no ortholog in H. capsulatum)[14, 15].
Other notable categories of genes not detected by tiling include genes in heavily repeat-masked regions of the genome (where the tiling density is, therefore, too low to analyze) and genes with weak expression that did not give significant signal over background on tiling arrays.
Genes that were not detected by homology represented short or interrupted predictions
For genes not detected by homology, there were two related trends: (1) the predicted lengths were short, on the order of those genes not detected by any method (Figure 4); and/or (2) a single TAR was inappropriately split into multiple predicted genes. For example, the copper-repressed gene ELI1, which is known to be expressed as a single mRNA, is split into two predictions. Both predictions are detected by expression and tiling, but only the 3' prediction, which contains the coding sequence, is detected by homology, whereas the 5' prediction, which likely contains 5'UTR, is not. Short predictions are difficult to detect as homologs for two reasons: short runs of sequence similarity are likely to occur by chance, resulting in lower BLASTP p-values for hits to these predictions; and INPARANOID requires 50% reciprocal coverage between orthologs, resulting in rejection of genes where the predicted length is significantly smaller than that of the corresponding homologs. The same issues arise for split predictions, with the additional restriction that INPARANOID will make an ortholog assignment for only one member of a split pair, automatically resulting in rejection of the other member.
In all of these cases, the discrepancy between the experimental and sequence based results is a useful indication that the predicted gene model should be revised. In many cases, comparison of the transcript detected by tiling array to the results of less stringent sequence searches (e.g., BLASTX of the transcribed genomic sequence) is a useful starting point for such revision.
Genes not detected by homology also tend to show enriched expression in conidia, the vegetative spores generated by H. capsulatum filaments. H. capsulatum conidia, or their counterparts in any closely related fungi, have not been extensively studied; thus, the homologs of these genes may be unpredicted or entirely absent in the comparison genomes.
Genes that were validated only by homology have restricted expression profiles
The category of genes with orthologs in other fungi but no direct observation in our experimental data was relatively small (254 predictions representing 3% of the non-repeat gene set) and is predicted to contain genes that are expressed only under very restricted conditions that were not sampled in our expression data. Consistent with this hypothesis, we find STE3, the a-factor receptor whose expression has been observed only in mutants of G217B; the ortholog of N. crassa RID, which is required for the RIP process and therefore expected to be expressed only during meiosis; and the ortholog of T. reesei AXE2, a hemicellulolytic enzyme whose expression is dependent on carbon source.
Empirical redesign of microarray probes
Our tiling arrays and homology predictions can be used to inform future design of microarray probes. Because the expression experiments draw from a more diverse set of samples than the tiling experiments, detection of a predicted gene by homology and tiling but not by expression suggested a platform-specific defect in the 70 mer probe designed to detect that gene on our whole-genome oligonucleotide arrays (rather than a failure of the expression experiments to sample the appropriate condition). Our analyses support this hypothesis. In particular, the 70-mer probes for genes that failed to be detected by expression array tend to lie outside of the transcribed locus detected by tiling (e.g., the nitrositive-stress induced transcript COX12), or span a predicted intron not supported by the tiling data (i.e., due to incorrect gene prediction, the 70 mer probe targets a discontiguous sequence in the true transcript). We are currently augmenting the expression array platform with new 70 mers for these genes, based on the coincidence of tiling transcripts with predicted exons.
Genes that failed to be validated by any method
We were unable to validate 1,099 predictions, or 11% of the non-redundant genes, by any method. This group primarily corresponds to wholly undetected predictions but may also include a small number of correct predictions for which the 5' end is undetected due to the 3' bias of the tiling experiment.
The unvalidated genes are significantly shorter than the detected genes (Figure 4). This observation could be due to false negatives in the tiling data (short transcripts are more difficult to detect because they are difficult to distinguish from background noise) or false gene predictions (there is an increased likelihood of short sequences fitting a gene model by chance). We note that genes validated only by expression (our only validation method that is independent of transcript length) are significantly shorter than genes validated by all methods but significantly longer than the unvalidated genes, lending weight to both explanations.
We probed the transcriptome of H. capsulatum with a large set of tiling arrays, and combined the results with gene-targeted expression profiling and sequence homology, yielding a high confidence set of validated gene predictions for G217B with 7,362 gene predictions being validated by at least two of the three methods. In addition, the unbiased approach of the tiling arrays allowed us to detect 264 novel transcripts that are now being incorporated into our oligo expression arrays, directly extending the sensitivity of that platform. Additionally, the results of this study are available at http://histo.ucsf.edu in an interactive format intended to facilitate expression, insertional mutagenesis, and bioinformatics based studies. Thus, the transcript sets resulting from this study represent an enhancement of the previously available H. capsulatum gene set and a starting point for the experimental and theoretical characterization of the molecular biology of this important intracellular pathogen.
RNA Extraction and cDNA synthesis
To generate a diverse RNA sample for the tiling experiment, we prepared RNA from yeast-form Histoplasma capsulatum strain G217B (ATCC 26032; a kind gift of William Goldman, Washington University, St. Louis, MO) under a variety of conditions (including early, middle, and late logarithmic growth, stationary phase, heat shock (42°C for 30 min), oxidative stress (1 mM menadione for 80 min), sulfhydryl reducing stress (10 mM DTT for 2 hours), and a range of media (HMM, 3M, YPD, and SD complete). Total RNA and polyA RNA were prepared as previously described[8, 9]. Cy5-labeled cDNA was prepared from individual RNA samples as previously described, and an equal mass of cDNA was pooled from each sample and hybridized to individual tiling arrays as described below.
Whole Genome Tiling Array Design
The whole genome tiling arrays were designed based on the GSC Histoplasma capsulatum strain G217B genome assembly as of 11/30/2004. Degenerate sequence and transposable elements were removed from the assembly using RepeatMasker with default parameters and the repeat families determined by the GSC. The remaining sequence was tiled with 50 mer probes at an average frequency of one probe every 60 base pairs. Probe spacing was adjusted to minimize variation in melting temperature, and a subset of probes were truncated to optimize synthesis, in collaboration with CombiMatrix. The number of arrays used to tile a given contig was minimized, and the location of tiling probes was randomized within a given array.
In addition, each array contained a common set of control probes, viz.: quality control (QC) and negative control (NC) probes designed by CombiMatrix (Mukilteo, WA); positive control probes tiling the genomic loci and non-genic flanking sequence of TEF1(P40911), TYR1, and CBP1(AF006209); and probes specific to a spike-in control sequence. The QC, NC, and spike-in probes were not considered in the analysis.
Hybridization of tiling arrays
Fluorescently labeled cDNA was hybridized to CombiMatrix arrays as previously described. In addition to the Cy5-labeled sample described above, a common Cy3-labeled sample was used as a counterpoint reference on each array.
Images of the hybridized arrays were acquired with a GenePix 4000B scanner (Axon Instruments) controlled by the GenePix 4.0 program (Molecular Devices). Each array was scanned three times using the following PMT settings for the 635 nm laser: 400, 450, 540. Images were gridded with GenePix 4.0 and the median foreground intensity for each feature was used as the input for subsequent analysis. Based on the negative control probes, signal/noise was constant for the three scans, so all subsequent analysis was carried out using the lowest PMT scan.
Probe detection on tiling arrays
Background intensity was estimated based on the median intensities of a control set of known antisense and intergenic regions, a method similar to the use of median intensities of known introns in the analysis of rice tiling data. Specifically, the background intensity was estimated as the median intensity of the positive control probes corresponding to the intergenic (untranscribed) regions flanking CBP1 and TYR1 and the antisense (untranscribed) probes for CBP1, TYR1, and TEF1. A tiling probe was considered detected if it had intensity greater than the background intensity estimated for the corresponding array. 58% of the tiling probes were considered detected by this method.
Transcript detection on tiling arrays
In H. capsulatum, introns are small enough to make detection of complete transcripts feasible (in contrast to, e.g., Homo sapiens) but are large and irregular enough to make such detection non-trivial (in contrast to, e.g., Escherichia coli or Saccharomyces cerevisiae). For this study, we traded resolution for improved signal to noise and defined transcripts as genomic loci ≥ 200 bp for which the normalized density of detected probes was greater than 65% of the normalized density of all probes. Smoothed densities were calculated with the density function in R using a bandwidth of 500 bp, and transcripts were truncated such that transcript ends coincided with detected tiles.
In order to avoid regions of the tiling path that were rendered sparse due to repeat masking, transcript detection was restricted to regions spanning at least 10 kb of genome sequence with a minimum tiling density of 1 probe per 250 bp (1/5 th of the target tiling density).
6,172 transcripts were detected. The length distribution (in terms of genomic locus) for detected and predicted transcripts is shown in Figure 4. Known transcripts showed a mild 3' bias, meaning that signal intensity was enriched at the 3' end of the gene, as expected given the method of sample preparation.
94 novel TARs were examined by RT-PCR. Primers were designed using the Primer3 program (with the Primer3plus default parameters) to design up to 5 primer pairs (giving 400-500 bp products) for each transcript. The designed primer pairs were then screened for redundant products using the re-PCR program with the first non-redundant pair being chosen for each target (targets with 5 redundant pairs were rejected).
PolyA RNA corresponding to the cDNA used for tiling arrays was subjected to RT-PCR analysis, with the exception that RNA from early log-phase cells was not included due to limited material. The pooled RNA was DNAse treated and reverse transcribed with AffinityScript (Stratagene). PCR reactions were carried out using AmpliTaq polymerase (Applied Biosystems) for 35 cycles of [94°C 15" → 56°C 15" → 72°C 4'].
Reaction products were visualized on a 1% agarose gel and were considered detected if they occurred at the length predicted by the re-PCR program with no corresponding band in the "no RT" control.
The sequences of the full set of novel TARs are given in Additional file 6, Data S6.
For the purpose of validation, the length of a predicted gene was taken as its full genomic locus (including introns and exons).
RECON-identified repeat-families from the GSC (including the MAGGY transposon) were mapped to the genome with REPEATMASKER using default settings and excluding simple sequence repeats. Predicted genes with greater than 20% of their length covered by REPEATMASKER-annotated repeat sequence were classified as repeats and removed from further analysis.
Non-repeat genes with greater than 50% of their length covered by detected TARs were classified as validated by tiling.
The following two-channel G217B whole-genome oligonucleotide microarray data sets were used for validation by expression profiling: wild type and ryp1 mutant 37°C and RT samples hybridized against a pooled reference (9 arrays), direct hybridizations of yeast, mycelial, and conidial samples (6 arrays, Inglis et al, unpublished), iron depletion time courses hybridized against a pooled reference (8 arrays plus 10 arrays, Hwang et al, unpublished). In keeping with our standard analysis pipeline for this platform, probes were considered detected if they were not manually flagged as bad and the sum of background-subtracted median intensities for the two channels was greater than 500. Non-repeat predicted genes were classified as validated by expression array if they mapped to at least one detected probe in at least 3 of the 33 arrays.
Annotated gene sets from the following genomes were used for validation by homology to other fungi: Blastomyces dermatitidis er-3 and slh14081; Paracoccidioides brasiliensis pb01, pb03, and pb18; Coccidioides immitis rs; Aspergillus nidulans; Aspergillus fumigatus (TIGR); Aspergillus oryzae (DOGAN); Neurospora crassa; Magnaporthe oryzae (formerly Magnaporthe grisea); Fusarium graminearum; Candida albicans (CGD, orfs19 gene set); Saccharomyces cerevisiae (SGD); Cryptococcus neoformans H99; and Ustilago maydis. Except where noted, all gene sets were obtained from the BROAD Institute. Pairwise ortholog/in-paralog mapping to G217B was performed by running INPARANOID with default parameters and no outgroup for each genome. Predicted genes were classified as validated by homology if they were a member of an orthogroup (direct ortholog to a gene in the target genome or in-paralog of a G217B gene with a direct ortholog in the target genome) for at least 3 of the 16 target genomes.
Microarray data have been submitted to the NCBI Gene Expression Omnibus (GEO) under accession number [GEO:GSE31155].
Nucleotide sequence data for the reported novel TARs are available in the Third Party Annotation Section of the DDBJ/EMBL/GenBank databases under the accession numbers TPA: BK008128-BK008391.
This work was supported by the Burroughs Wellcome Fund (Request ID 1006254 to A.S.), U54 AI65359 (to A.S.), 2R01 AI066224-06 (to A.S.), and a Howard Hughes Medical Institute Early Career Scientist Award (to A.S.). We are grateful to Elaine Mardis at the Washington University Genome Sequencing Center for spearheading the sequencing and annotation of the G217B genome, as well as timely sharing of data and resources. We thank the Sil lab for useful discussions and Davina Hocking Murray for assistance with figures.
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