Project description:Small RNAs are common and effective modulators of gene expression in eukaryotic organisms. To characterize the small RNAs expressed during rice seed development, massively parallel signature sequencing (MPSS) was performed, resulting in the obtainment of 22-nt sequence signatures. Through integrative analysis,novel miRNAs were identified mostly based on the miRNA* accumulation.
Project description:This series represents a very deep survey of all transcripts expressed in a wide range of human tissues and cells by Massively Parallel Signature Sequencing (MPSS). These datasets have been generated and donated to the scientific community by Lynx Therapeutics, Inc in Hayward, CA. The data contained in this submission is described in the following publication: 'C. Victor Jongeneel, Mauro Delorenzi, Christian Iseli, Daixing Zhou, Christian D. Haudenschild, Brian J. Stevenson, Robert L. Strausberg, Andrew J.G. Simpson, and Thomas J. Vasicek.' An atlas of human gene expression from massively parallel signature sequencing (MPSS). Genome Research VolXX 2004 Abstract of the publication: '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 over 20,000 genes with high sensitivity and specificity. The data confirm the widely held belief that differences between cell and tissue types are largely determined by the expression of a limited number of tissue-specific genes, rather than by combinations of more promiscuously expressed genes. Expression of a little over 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 notion that most human genes have been mapped, if not functionally characterised. This dataset 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.' Keywords: other
Project description:Identification of all expressed transcripts in a sequenced complex genome is technically challenging, but essential for systems biology and genome analysis. We used the transcriptional profiling technology called ‘massively parallel signature sequencing’ (MPSS) to develop a comprehensive expression atlas of rice (Oryza sativa cv Nipponbare). A total of 46,971,553 mRNA transcripts from 22 libraries, and 2,953,855 small RNAs from three libraries were sequenced. The data demonstrated widespread transcription throughout the genome, including expression for up to 25,500 annotated genes and antisense expression for nearly 9,000 annotated genes. An additional set of ~15,000 mRNA signatures mapped to unannotated genomic regions. The majority of the small RNA data represented lower abundance small-interfering RNAs (siRNAs) 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 plant. Keywords: MPSS, mRNA, small RNA, transcriptome, rice
Project description:We report the use of MPSS data to compare transcripts expressed in wild-type and sporocyteless mutant ovules All MPSS libraries were performed as described by Meyers et al (Nature Biotechnol. 2004 Aug;22(8):1006-11. Epub 2004 Jul 11.)
Project description:Small RNAs are common and effective modulators of gene expression in eukaryotic organisms. To characterize the small RNAs expressed during rice seed development, massively parallel signature sequencing (MPSS) was performed, resulting in the obtainment of 22-nt sequence signatures. Through integrative analysis,novel miRNAs were identified mostly based on the miRNA* accumulation. Total RNA was isolated separately from rice seeds collected at 3, 6, 9 and 12 days after anthesis (DAA), then mixed into a library and separated on denatured polyacrylamide gel electrophoresis (PAGE). The fraction of 18-26 nt small RNA was recovered by small RNA gel extraction Kit.
Project description: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 technologies like ‘massively parallel signature sequencing (MPSS)’ and ‘Sequencing by Synthesis’ (SBS) to develop a comprehensive expression atlas of rice (Oryza sativa cv Nipponbare). Illumina’s SBS technology can generate large amounts of sequence data in a short time at low cost compared to traditional Sanger sequencing based methods. Using the MPSS technology, we previously analyzed the transcriptomes of 72 rice tissues. To validate the sequencing results from MPSS technology, we employed SBS technology and constructed SBS libraries from 32 rice tissues (47 libraries including replications). For SBS library construction, we used the same mRNA samples and same restriction enzyme (DpnII) that were used for the construction of the MPSS libraries. These libraries include six abiotic-stress libraries, eight pathogen-infected libraries, five insect-damaged libraries, three developing seed libraries, and 10 untreated rice tissue libraries. This study was carried out with the following objectives; a) Identification and quantification of expressed genes in rice at all developmental stages of plant growth, response to biotic and abiotic stresses, and developing seeds; b) Compare SBS signatures with rice genomic sequence to identify novel transcripts; c) To validate the transcriptional data obtained through MPSS technology; and To create query and analysis tools to facilitate public use of and access to rice MPSS and SBS data and to display abundance and chromosomal locations of rice MPSS and SBS signatures. The SBS data will be available at http://mpss.udel.edu/rice_sbs/.
Project description:We performed ChIP-seq for H3K27me3, the Polycomb protein FIE, and two associated transcription factor (AZF1 and BPC1) using epitope tags expressed in germinated seedlings of Arabidopsis thaliana.
Project description:Compared to understanding of biological shape and form, knowledge is sparse regarding what regulates growth and body size of a species. For example, the genetic and physiological causes of heterosis (hybrid vigor) have remained elusive for nearly a century. Here we investigate gene-expression patterns underlying growth heterosis in the Pacific oyster (Crassostrea gigas) in two partially inbred (f=0.375) and two hybrid larval populations produced by a reciprocal cross between the two inbred families. We cloned cDNA and generated 8.6 million sequence tags with massively parallel signature sequencing (MPSSâ). The sequences contain 23,277 distinct signatures that are expressed at statistically non-zero levels and show a highly positively skewed distribution with median and modal counts of 9.25 and 3 transcripts per million, respectively. Approximately 9100 nuclear transcripts are found in all four larval populations, in agreement with the number of genes expressed in sea urchin embryo. For half of the 23,277 signatures, expression level depends on genotype and is predominantly non-additive (hybrids deviate from the inbred average). Statistical contrasts suggest ~350 candidate heterosis genes that exhibit concordant non-additive expression in reciprocal hybrids. Patterns of gene expression, which include dominance for low expression and even underdominance of expression, are more complex than predicted from classical dominant or overdominant explanations of heterosis. Preliminary identification of ribosomal proteins among candidate genes supports the suggestion from previous studies that efficiency of protein metabolism plays a role in heterosis. Keywords: MPSS heterosis larvae expression profiling