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Christian D Haudenschild

Publications and source records attributed to Christian D Haudenschild.

7 recordsLinked to original sources

Use of massively parallel signature sequencing to study genes expressed during the plant defense response.

Massively parallel signature sequencing is a sequencing-based method that provides quantitative gene expression data for nearly all transcripts in a particular ribonucleic acid sample. Although the sequencing technology is practiced as a service by a California-based company, we have developed methods for the handling and analysis of these data. This chapter describes the steps involved in obtaining data from massively parallel signature sequencing, aligning the signatures to genomic sequence, identifying novel transcripts, and performing quantitative analyses of genes expressed under conditions such as disease treatments.

Arabidopsis↗

Deep and comparative analysis of the mycelium and appressorium transcriptomes of Magnaporthe grisea using MPSS, RL-SAGE, and oligoarray methods.

BACKGROUND: Rice blast, caused by the fungal pathogen Magnaporthe grisea, is a devastating disease causing tremendous yield loss in rice production. The public availability of the complete genome sequence of M. grisea provides ample opportunities to understand the molecular mechanism of its pathogenesis on rice plants at the transcriptome level. To identify all the expressed genes encoded in the fungal genome, we have analyzed the mycelium and appressorium transcriptomes using massively parallel signature sequencing (MPSS), robust-long serial analysis of gene expression (RL-SAGE) and oligoarray methods. RESULTS: The MPSS analyses identified 12,531 and 12,927 distinct significant tags from mycelia and appressoria, respectively, while the RL-SAGE analysis identified 16,580 distinct significant tags from the mycelial library. When matching these 12,531 mycelial and 12,927 appressorial significant tags to the annotated CDS, 500 bp upstream and 500 bp downstream of CDS, 6,735 unique genes in mycelia and 7,686 unique genes in appressoria were identified. A total of 7,135 mycelium-specific and 7,531 appressorium-specific significant MPSS tags were identified, which correspond to 2,088 and 1,784 annotated genes, respectively, when matching to the same set of reference sequences. Nearly 85% of the significant MPSS tags from mycelia and appressoria and 65% of the significant tags from the RL-SAGE mycelium library matched to the M. grisea genome. MPSS and RL-SAGE methods supported the expression of more than 9,000 genes, representing over 80% of the predicted genes in M. grisea. About 40% of the MPSS tags and 55% of the RL-SAGE tags represent novel transcripts since they had no matches in the existing M. grisea EST collections. Over 19% of the annotated genes were found to produce both sense and antisense tags in the protein-coding region. The oligoarray analysis identified the expression of 3,793 mycelium-specific and 4,652 appressorium-specific genes. A total of 2,430 mycelial genes and 1,886 appressorial genes were identified by both MPSS and oligoarray. CONCLUSION: The comprehensive and deep transcriptome analysis by MPSS and RL-SAGE methods identified many novel sense and antisense transcripts in the M. grisea genome at two important growth stages. The differentially expressed transcripts that were identified, especially those specifically expressed in appressoria, represent a genomic resource useful for gaining a better understanding of the molecular basis of M. grisea pathogenicity. Further analysis of the novel antisense transcripts will provide new insights into the regulation and function of these genes in fungal growth, development and pathogenesis in the host plants.

DNA, Fungal↗

Massively parallel signature sequencing.

Massively parallel signature sequencing is an ultra-high throughput sequencing technology. It can simultaneously sequence millions of sequence tags, and, therefore, is ideal for whole genome analysis. When applied to expression profiling, it reveals almost every transcript in the sample and provides its accurate expression level. This chapter describes the technology and its application in establishing stem cell transcriptome databases.

Cell Culture Techniques↗

Elucidation of the small RNA component of the transcriptome.

Small RNAs play important regulatory roles in most eukaryotes, but only a small proportion of these molecules have been identified. We sequenced more than two million small RNAs from seedlings and the inflorescence of the model plant Arabidopsis thaliana. Known and new microRNAs (miRNAs) were among the most abundant of the nonredundant set of more than 75,000 sequences, whereas more than half represented lower abundance small interfering RNAs (siRNAs) that match repetitive sequences, intergenic regions, and genes. Individual or clusters of highly regulated small RNAs were readily observed. Targets of antisense RNA or miRNA did not appear to be preferentially associated with siRNAs. Many genomic regions previously considered featureless were found to be sites of numerous small RNAs.

Arabidopsis↗

An atlas of human gene expression from massively parallel signature sequencing (MPSS).

We have used massively parallel signature sequencing (MPSS) to sample the transcriptomes of 32 normal human tissues to an unprecedented depth, thus documenting the patterns of expression of almost 20,000 genes with high sensitivity and specificity. The data confirm the widely held belief that differences in gene expression between cell and tissue types are largely determined by transcripts derived from a limited number of tissue-specific genes, rather than by combinations of more promiscuously expressed genes. Expression of a little more than half of all known human genes seems to account for both the common requirements and the specific functions of the tissues sampled. A classification of tissues based on patterns of gene expression largely reproduces classifications based on anatomical and biochemical properties. The unbiased sampling of the human transcriptome achieved by MPSS supports the idea that most human genes have been mapped, if not functionally characterized. This data set should prove useful for the identification of tissue-specific genes, for the study of global changes induced by pathological conditions, and for the definition of a minimal set of genes necessary for basic cell maintenance. The data are available on the Web at http://mpss.licr.org and http://sgb.lynxgen.com.

Algorithms↗

Analysis of the transcriptional complexity of Arabidopsis thaliana by massively parallel signature sequencing.

Large-scale sequencing of short mRNA-derived tags can establish the qualitative and quantitative characteristics of a complex transcriptome. We sequenced 12,304,362 tags from five diverse libraries of Arabidopsis thaliana using massively parallel signature sequencing (MPSS). A total of 48,572 distinct signatures, each representing a different transcript, were expressed at significant levels. These signatures were compared to the annotation of the A. thaliana genomic sequence; in the five libraries, this comparison yielded between 17,353 and 18,361 genes with sense expression, and between 5,487 and 8,729 genes with antisense expression. An additional 6,691 MPSS signatures mapped to unannotated regions of the genome. Expression was demonstrated for 1,168 genes for which expression data were previously unknown. Alternative polyadenylation was observed for more than 25% of A. thaliana genes transcribed in these libraries. The MPSS expression data suggest that the A. thaliana transcriptome is complex and contains many as-yet uncharacterized variants of normal coding transcripts.

Arabidopsis↗

The use of MPSS for whole-genome transcriptional analysis in Arabidopsis.

We have generated 36,991,173 17-base sequence "signatures" representing transcripts from the model plant Arabidopsis. These data were derived by massively parallel signature sequencing (MPSS) from 14 libraries and comprised 268,132 distinct sequences. Comparable data were also obtained with 20-base signatures. We developed a method for handling these data and for comparing these signatures to the annotated Arabidopsis genome. As part of this procedure, 858,019 potential or "genomic" signatures were extracted from the Arabidopsis genome and classified based on the position and orientation of the signatures relative to annotated genes. A comparison of genomic and expressed signatures matched 67,735 signatures predicted to be derived from distinct transcripts and expressed at significant levels. Expressed signatures were derived from the sense strand of at least 19,088 of 29,084 annotated genes. A comparison of the genomic and expression signatures demonstrated that approximately 7.7% of genomic signatures were underrepresented in the expression data. These genomic signatures contained one of 20 four-base words that were consistently associated with reduced MPSS abundances. More than 89% of the sum of the expressed signature abundances matched the Arabidopsis genome, and many of the unmatched signatures found in high abundances were predicted to match to previously uncharacterized transcripts.

Arabidopsis↗