Transcriptomes reveal alterations in gravity impact circadian clocks and activate mechanotransduction pathways with adaptation through epigenetic change

Few studies have investigated the impact of alterations in gravity on mammalian transcriptomes. Here, we describe the impact of spaceflight on mammary transcriptome of late pregnant rats and the effect of hypergravity exposure on mammary, liver, and adipose transcriptomes in late pregnancy and at the onset of lactation. RNA was isolated from mammary collected on pregnancy day 20 from rats exposed to spaceflight from days 11 to 20 of gestation. To measure the impact of hypergravity on mammary, liver, and adipose transcriptomes we isolated RNA from tissues collected on P20 and lactation day 1 from rats exposed to hypergravity beginning on pregnancy day 9. Gene expression was measured with Affymetrix GeneChips. Microarray analysis of variance revealed alterations in gravity affected the expression of genes that regulate circadian clocks and activate mechanotransduction pathways. Changes in these systems may explain global gene expression changes in immune response, metabolism, and cell proliferation. Expression of genes that modify chromatin structure and methylation was affected, suggesting adaptation to gravity alterations may proceed through epigenetic change. Altered gravity experiments offer insights into the role of forces omnipresent on Earth that shape genomes in heritable ways. Our study is the first to analyze the impact of alterations in gravity on transcriptomes of pregnant and lactating mammals. Findings provide insight into systems that sense gravity and the way in which they affect phenotype, as well as the possibility of sustaining life beyond Earth's orbit.

Uncovering the expression patterns of chimeric transcripts using surveys of Affymetrix GeneChips

Summary Background: A chimeric transcript is a single RNA sequence which results from the transcription of two adjacent genes. Recent studies estimate that at least 4% of tandem human gene pairs may form chimeric transcripts. Affymetrix GeneChip data are used to study the expression patterns of tens of thousands of genes and the probe sequences used in these microarrays can potentially map to exotic RNA sequences such as chimeras.Results: We have studied human chimeras and investigated their expression patterns using large surveys of Affymetrix microarray data obtained from the Gene Expression Omnibus. We show that for six probe sets, a unique probe mapping to a transcript produced by one of the adjacent genes can be used to identify the expression patterns of readthrough transcripts. Furthermore, unique probes mapping to an intergenic exon present only in the MASK-BP3 chimera can be used directly to study the expression levels of this transcript.Conclusions: We have attempted to implement a new method for identifying tandem chimerism. In this analysis unambiguous probes are needed to measure run-off transcription and probes that map to intergenic exons are particularly valuable for identifying the expression of chimeras.

Using surveys of Affymetrix GeneChips to study antisense expression

SummaryWe have used large surveys of Affymetrix GeneChip HG-U133_Plus_2 data in the public domain to conduct a study of antisense expression across diverse conditions. We derive correlations between groups of probes which map uniquely to the same exon in the antisense direction. When there are no probes assigned to an exon in the sense direction we find that many of the antisense groups fail to detect a coherent block of transcription. We find that only a minority of these groups contain coherent blocks of antisense expression suggesting transcription.We also derive correlations between groups of probes which map uniquely to the same exon in both sense and antisense direction. In some of these cases the locations of sense probes overlap with the antisense probes, and the sense and antisense probe intensities are correlated with each other. This configuration suggests the existence of a Natural Antisense Transcript (NAT) pair. We find the majority of such NAT pairs detected by GeneChips are formed by a transcript of an established gene and either an EST or an mRNA.In order to determine the exact antisense regulatory mechanism indicated by the correlation of sense probes with antisense probes, a further investigation is necessary for every particular case of interest. However, the analysis of microarray data has proved to be a good method to reconfirm known NATs, discover new ones, as well as to notice possible problems in the annotation of antisense transcripts.

Identifying the impact of G-Quadruplexes on Affymetrix 3′ Arrays using Cloud Computing

SummaryA tetramer quadruplex structure is formed by four parallel strands of DNA/ RNA containing runs of guanine. These quadruplexes are able to form because guanine can Hoogsteen hydrogen bond to other guanines, and a tetrad of guanines can form a stable arrangement. Recently we have discovered that probes on Affymetrix GeneChips that contain runs of guanine do not measure gene expression reliably. We associate this finding with the likelihood that quadruplexes are forming on the surface of GeneChips.In order to cope with the rapidly expanding size of GeneChip array datasets in the public domain, we are exploring the use of cloud computing to replicate our experiments on 3′ arrays to look at the effect of the location of G-spots (runs of guanines). Cloud computing is a recently introduced high-performance solution that takes advantage of the computational infrastructure of large organisations such as Amazon and Google.We expect that cloud computing will become widely adopted because it enables bioinformaticians to avoid capital expenditure on expensive computing resources and to only pay a cloud computing provider for what is used. Moreover, as well as financial efficiency, cloud computing is an ecologically-friendly technology, it enables efficient data-sharing and we expect it to be faster for development purposes. Here we propose the advantageous use of cloud computing to perform a large data-mining analysis of public domain 3′ arrays.