Institute for Systems Biology

About: Institute for Systems Biology is a nonprofit organization based out in Seattle, Washington, United States. It is known for research contribution in the topics: Population & Proteomics. The organization has 1277 authors who have published 2777 publications receiving 353165 citations.

sRNAnalyzer-a flexible and customizable small RNA sequencing data analysis pipeline.

Abstract: Although many tools have been developed to analyze small RNA sequencing (sRNA-Seq) data, it remains challenging to accurately analyze the small RNA population, mainly due to multiple sequence ID assignment caused by short read length. Additional issues in small RNA analysis include low consistency of microRNA (miRNA) measurement results across different platforms, miRNA mapping associated with miRNA sequence variation (isomiR) and RNA editing, and the origin of those unmapped reads after screening against all endogenous reference sequence databases. To address these issues, we built a comprehensive and customizable sRNA-Seq data analysis pipeline-sRNAnalyzer, which enables: (i) comprehensive miRNA profiling strategies to better handle isomiRs and summarization based on each nucleotide position to detect potential SNPs in miRNAs, (ii) different sequence mapping result assignment approaches to simulate results from microarray/qRT-PCR platforms and a local probabilistic model to assign mapping results to the most-likely IDs, (iii) comprehensive ribosomal RNA filtering for accurate mapping of exogenous RNAs and summarization based on taxonomy annotation. We evaluated our pipeline on both artificial samples (including synthetic miRNA and Escherichia coli cultures) and biological samples (human tissue and plasma). sRNAnalyzer is implemented in Perl and available at: http://srnanalyzer.systemsbiology.net/.

Application of affymetrix array and massively parallel signature sequencing for identification of genes involved in prostate cancer progression

Abstract: Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression. Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR. Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the combined transcriptomes identified 66 genes unique to LNCaP cells and 33 genes unique to C4-2 cells. Expression analysis of these genes in prostate cancer specimens showed CA1 to be highly expressed in bone metastasis but not expressed in primary tumor and EPHA7 to be expressed in normal prostate and primary tumor but not bone metastasis. Our data indicates that transcriptome profiling with a single methodology will not fully assess the expression of all genes in a cell line. A combination of transcription profiling technologies such as DNA array and MPSS provides a more robust means to assess the expression profile of an RNA sample. Finally, genes that were differentially expressed in cell lines were also differentially expressed in primary prostate cancer and its metastases.

The role of karyopherins in the regulated sumoylation of septins

Abstract: In the yeast Saccharomyces cerevisiae, several components of the septin ring are sumoylated during anaphase and then abruptly desumoylated at cytokinesis. We show that septin sumoylation is controlled by the interactions of two enzymes of the sumoylation pathway, Siz1p and Ulp1p, with the nuclear transport machinery. The E3 ligase Siz1p is imported into the nucleus by the karyopherin Kap95p during interphase. In M phase, Siz1p is exported from the nucleus by the karyopherin Kap142p/Msn5p and subsequently targeted to the septin ring, where it participates in septin sumoylation. We also show that the accumulation of sumoylated septins during mitosis is dependent on the interactions of the SUMO isopeptidase Ulp1p with Kap121p and Kap95p–Kap60p and the nuclear pore complex (NPC). In addition to sequestering Ulp1 at the NPC, Kap121p is required for targeting Ulp1p to the septin ring during mitosis. We present a model in which Ulp1p is maintained at the NPC during interphase and transiently interacts with the septin ring during mitosis.

Oligonucleotide Arrays for High-Throughput SNPs Detection in the MHC Class I Genes: HLA-B as a Model System

Abstract: A simple and efficient oligonucleotide array was developed to identify single nucleotide polymorphisms (SNPs) encoded within the highly polymorphic human major histocompatibility complex (MHC) using HLA-B as a model system. A total of 137 probes were designed to represent all known polymorphisms encoded in exons 2 and 3. PCR products were amplified from human genomic DNA and allowed to hybridize with the oligonucleotide array. Hybridization was detected by fluorescence scanning, and HLA-B alleles were assigned by quantitative analysis of the hybridization results. Variables known to influence the specificity of hybridization, such as oligonucleotide probe size, spacer length, surface density, hybridization conditions, and array uniformity and stability were studied. The efficiency and specificity of identifying HLA-B SNPs using the oligonucleotide arrays was evaluated by blinded analysis of 100 samples from unrelated individuals representing all HLA-B phenotypes. The oligonucleotide array method described in this paper provides unambiguous detection of complex heterozygous SNP combinations. This methodological approach may be applied to other highly polymorphic gene systems.