Transcript-Specific Expression Profiles Derived from Sequence-Based Analysis of Standard Microarrays

Background: Alternative mRNA processing mechanisms lead to multiple transcripts (i.e. splice isoforms) of a given gene which may have distinct biological functions. Microarrays like Affymetrix GeneChips measure mRNA expression of genes using sets of nucleotide probes. Until recently probe sets were not designed for transcript specificity. Nevertheless, the reanalysis of established microarray data using newly defined transcript-specific probe sets may provide information about expression levels of specific transcripts. Methodology/Principal Findings: In the present study alignment of probe sequences of the Affymetrix microarray HGU133A with Ensembl transcript sequences was performed to define transcript-specific probe sets. Out of a total of 247,965 perfect match probes, 95,008 were designated ‘‘transcript-specific’’, i.e. showing complete sequence alignment, no crosshybridization, and transcript-, not only gene-specificity. These probes were grouped into 7,941 transcript-specific probe sets and 15,619 gene-specific probe sets, respectively. The former were used to differentiate 445 alternative transcripts of 215 genes. For selected transcripts, predicted by this analysis to be differentially expressed in the human kidney, confirmatory real-time RT-PCR experiments were performed. First, the expression of two specific transcripts of the genes PPM1A (PP2CA_HUMAN and P35813) and PLG (PLMN_HUMAN and Q5TEH5) in human kidneys was determined by the transcriptspecific array analysis and confirmed by real-time RT-PCR. Secondly, disease-specific differential expression of single transcripts of PLG and ABCA1 (ABCA1_HUMAN and Q5VYS0_HUMAN) was computed from the available array data sets and confirmed by transcript-specific real-time RT-PCR. Conclusions: Transcript-specific analysis of microarray experiments can be employed to study gene-regulation on the transcript level using conventional microarray data. In this study, predictions based on sufficient probe set size and foldchange are confirmed by independent mean

Determining Signalling Nodes for Apoptosis by a Genetic High-Throughput Screen

With the ever-increasing information emerging from the various sequencing and gene annotation projects, there is an urgent need to elucidate the cellular functions of the newly discovered genes. The genetically regulated cell suicide of apoptosis is especially suitable for such endeavours as it is governed by a vast number of factors.We have set up a high-throughput screen in 96-well microtiter plates for genes that induce apoptosis upon their individual transfection into human cells. Upon screening approximately 100,000 cDNA clones we determined 74 genes that initiate this cellular suicide programme. A thorough bioinformatics analysis of these genes revealed that 91% are novel apoptosis regulators. Careful sequence analysis and functional annotation showed that the apoptosis factors exhibit a distinct functional distribution that distinguishes the cell death process from other signalling pathways. While only a minority of classic signal transducers were determined, a substantial number of the genes fall into the transporter- and enzyme-category. The apoptosis factors are distributed throughout all cellular organelles and many signalling circuits, but one distinct signalling pathway connects at least some of the isolated genes. Comparisons with microarray data suggest that several genes are dysregulated in specific types of cancers and degenerative diseases.Many unknown genes for cell death were revealed through our screen, supporting the enormous complexity of cell death regulation. Our results will serve as a repository for other researchers working with genomics data related to apoptosis or for those seeking to reveal novel signalling pathways for cell suicide

Exploring the Switchgrass Transcriptome Using Second-Generation Sequencing Technology

Background: Switchgrass (Panicum virgatum L.) is a C4 perennial grass and widely popular as an important bioenergy crop. To accelerate the pace of developing high yielding switchgrass cultivars adapted to diverse environmental niches, the generation of genomic resources for this plant is necessary. The large genome size and polyploid nature of switchgrass makes whole genome sequencing a daunting task even with current technologies. Exploring the transcriptional landscape using next generation sequencing technologies provides a viable alternative to whole genome sequencing in switchgrass. Principal Findings: Switchgrass cDNA libraries from germinating seedlings, emerging tillers, flowers, and dormant seeds were sequenced using Roche 454 GS-FLX Titanium technology, generating 980,000 reads with an average read length of 367 bp. De novo assembly generated 243,600 contigs with an average length of 535 bp. Using the foxtail millet genome as a reference greatly improved the assembly and annotation of switchgrass ESTs. Comparative analysis of the 454-derived switchgrass EST reads with other sequenced monocots including Brachypodium, sorghum, rice and maize indicated a 70– 80 % overlap. RPKM analysis demonstrated unique transcriptional signatures of the four tissues analyzed in this study. More than 24,000 ESTs were identified in the dormant seed library. In silico analysis indicated that there are more than 2000 EST-SSRs in this collection. Expression of several orphan ESTs was confirmed by RT-PCR. Significance: We estimate that about 90 % of the switchgrass gene space has been covered in this analysis. This study nearl

Tracking the metabolic pulse of plant lipid production with isotopic labeling and flux analyses: Past, present and future

Metabolism is comprised of networks of chemical transformations, organized into integrated biochemical pathways that are the basis of cellular operation, and function to sustain life. Metabolism, and thus life, is not static. The rate of metabolites transitioning through biochemical pathways (i.e., flux) determines cellular phenotypes, and is constantly changing in response to genetic or environmental perturbations. Each change evokes a response in metabolic pathway flow, and the quantification of fluxes under varied conditions helps to elucidate major and minor routes, and regulatory aspects of metabolism. To measure fluxes requires experimental methods that assess the movements and transformations of metabolites without creating artifacts. Isotopic labeling fills this role and is a long-standing experimental approach to identify pathways and quantify their metabolic relevance in different tissues or under different conditions. The application of labeling techniques to plant science is however far from reaching it potential. In light of advances in genetics and molecular biology that provide a means to alter metabolism, and given recent improvements in instrumentation, computational tools and available isotopes, the use of isotopic labeling to probe metabolism is becoming more and more powerful. We review the principal analytical methods for isotopic labeling with a focus on seminal studies of pathways and fluxes in lipid metabolism and carbon partitioning through central metabolism. Central carbon metabolic steps are directly linked to lipid production by serving to generate the precursors for fatty acid biosynthesis and lipid assembly. Additionally some of the ideas for labeling techniques that may be most applicable for lipid metabolism in the future were originally developed to investigate other aspects of central metabolism. We conclude by describing recent advances that will play an important future role in quantifying flux and metabolic operation in plant tissues

A genome-wide association study identifies susceptibility loci for nonsyndromic sagittal craniosynostosis near BMP2 and within BBS9

Sagittal craniosynostosis is the most common form of craniosynostosis, affecting approximately one in 5,000 newborns. We conducted, to our knowledge, the first genome-wide association study for nonsyndromic sagittal craniosynostosis (sNSC) using 130 non-Hispanic case-parent trios of European ancestry (NHW). We found robust associations in a 120-kb region downstream of BMP2 flanked by rs1884302 (P = 1.13 × 10-14, odds ratio (OR) = 4.58) and rs6140226 (P = 3.40 × 10-11, OR = 0.24) and within a 167-kb region of BBS9 between rs10262453 (P = 1.61 × 10-10, OR = 0.19) and rs17724206 (P = 1.50 × 10-8, OR = 0.22). We replicated the associations to both loci (rs1884302, P = 4.39 × 10-31 and rs10262453, P = 3.50 × 10-14) in an independent NHW population of 172 unrelated probands with sNSC and 548 controls. Both BMP2 and BBS9 are genes with roles in skeletal development that warrant functional studies to further understand the etiology of sNSC. © 2012 Nature America, Inc. All rights reserved

Storage Reserve Accumulation in Arabidopsis: Metabolic and Developmental Control of Seed Filling

In the life cycle of higher plants, seed development is a key process connecting two distinct sporophytic generations. Seed development can be divided into embryo morphogenesis and seed maturation. An essential metabolic function of maturing seeds is the deposition of storage compounds that are mobilised to fuel post-germinative seedling growth. Given the importance of seeds for food and animal feed and considering the tremendous interest in using seed storage products as sustainable industrial feedstocks to replace diminishing fossil reserves, understanding the metabolic and developmental control of seed filling constitutes a major focus of plant research. Arabidopsis thaliana is an oilseed species closely related to the agronomically important Brassica oilseed crops. The main storage compounds accumulated in seeds of A. thaliana consist of oil stored as triacylglycerols (TAGs) and seed storage proteins (SSPs). Extensive tools developed for the molecular dissection of A. thaliana development and metabolism together with analytical and cytological procedures adapted for very small seeds have led to a good description of the biochemical pathways producing storage compounds. In recent years, studies using these tools have shed new light on the intricate regulatory network controlling the seed maturation process. This network involves sugar and hormone signalling together with a set of developmentally regulated transcription factors. Although much remains to be elucidated, the framework of the regulatory system controlling seed filling is coming into focus