Exploring structural variants in environmentally sensitive gene families.

Environmentally sensitive plant gene families like NBS-LRRs, receptor kinases, defensins and others, are known to be highly variable. However, most existing strategies for discovering and describing structural variation in complex gene families provide incomplete and imperfect results. The move to de novo genome assemblies for multiple accessions or individuals within a species is enabling more comprehensive and accurate insights about gene family variation. Earlier array-based genome hybridization and sequence-based read mapping methods were limited by their reliance on a reference genome and by misplacement of paralogous sequences. Variant discovery based on de novo genome assemblies overcome the problems arising from a reference genome and reduce sequence misplacement. As de novo genome sequencing moves to the use of longer reads, artifacts will be minimized, intact tandem gene clusters will be constructed accurately, and insights into rapid evolution will become feasible.

Detecting small plant peptides using SPADA (Small Peptide Alignment Discovery Application).

BACKGROUND: Small peptides encoded as one- or two-exon genes in plants have recently been shown to affect multiple aspects of plant development, reproduction and defense responses. However, popular similarity search tools and gene prediction techniques generally fail to identify most members belonging to this class of genes. This is largely due to the high sequence divergence among family members and the limited availability of experimentally verified small peptides to use as training sets for homology search and ab initio prediction. Consequently, there is an urgent need for both experimental and computational studies in order to further advance the accurate prediction of small peptides. RESULTS: We present here a homology-based gene prediction program to accurately predict small peptides at the genome level. Given a high-quality profile alignment, SPADA identifies and annotates nearly all family members in tested genomes with better performance than all general-purpose gene prediction programs surveyed. We find numerous mis-annotations in the current Arabidopsis thaliana and Medicago truncatula genome databases using SPADA, most of which have RNA-Seq expression support. We also show that SPADA works well on other classes of small secreted peptides in plants (e.g., self-incompatibility protein homologues) as well as non-secreted peptides outside the plant kingdom (e.g., the alpha-amanitin toxin gene family in the mushroom, Amanita bisporigera). CONCLUSIONS: SPADA is a free software tool that accurately identifies and predicts the gene structure for short peptides with one or two exons. SPADA is able to incorporate information from profile alignments into the model prediction process and makes use of it to score different candidate models. SPADA achieves high sensitivity and specificity in predicting small plant peptides such as the cysteine-rich peptide families. A systematic application of SPADA to other classes of small peptides by research communities will greatly improve the genome annotation of different protein families in public genome databases.

Large-scale integrative network-based analysis identifies common pathways disrupted by copy number alterations across cancers.

BACKGROUND: Many large-scale studies analyzed high-throughput genomic data to identify altered pathways essential to the development and progression of specific types of cancer. However, no previous study has been extended to provide a comprehensive analysis of pathways disrupted by copy number alterations across different human cancers. Towards this goal, we propose a network-based method to integrate copy number alteration data with human protein-protein interaction networks and pathway databases to identify pathways that are commonly disrupted in many different types of cancer. RESULTS: We applied our approach to a data set of 2,172 cancer patients across 16 different types of cancers, and discovered a set of commonly disrupted pathways, which are likely essential for tumor formation in majority of the cancers. We also identified pathways that are only disrupted in specific cancer types, providing molecular markers for different human cancers. Analysis with independent microarray gene expression datasets confirms that the commonly disrupted pathways can be used to identify patient subgroups with significantly different survival outcomes. We also provide a network view of disrupted pathways to explain how copy number alterations affect pathways that regulate cell growth, cycle, and differentiation for tumorigenesis. CONCLUSIONS: In this work, we demonstrated that the network-based integrative analysis can help to identify pathways disrupted by copy number alterations across 16 types of human cancers, which are not readily identifiable by conventional overrepresentation-based and other pathway-based methods. All the results and source code are available at http://compbio.cs.umn.edu/NetPathID/.

Spatio-temporal expression patterns of Arabidopsis thaliana and Medicago truncatula defensin-like genes.

Plant genomes contain several hundred defensin-like (DEFL) genes that encode short cysteine-rich proteins resembling defensins, which are well known antimicrobial polypeptides. Little is known about the expression patterns or functions of many DEFLs because most were discovered recently and hence are not well represented on standard microarrays. We designed a custom Affymetrix chip consisting of probe sets for 317 and 684 DEFLs from Arabidopsis thaliana and Medicago truncatula, respectively for cataloging DEFL expression in a variety of plant organs at different developmental stages and during symbiotic and pathogenic associations. The microarray analysis provided evidence for the transcription of 71% and 90% of the DEFLs identified in Arabidopsis and Medicago, respectively, including many of the recently annotated DEFL genes that previously lacked expression information. Both model plants contain a subset of DEFLs specifically expressed in seeds or fruits. A few DEFLs, including some plant defensins, were significantly up-regulated in Arabidopsis leaves inoculated with Alternaria brassicicola or Pseudomonas syringae pathogens. Among these, some were dependent on jasmonic acid signaling or were associated with specific types of immune responses. There were notable differences in DEFL gene expression patterns between Arabidopsis and Medicago, as the majority of Arabidopsis DEFLs were expressed in inflorescences, while only a few exhibited root-enhanced expression. By contrast, Medicago DEFLs were most prominently expressed in nitrogen-fixing root nodules. Thus, our data document salient differences in DEFL temporal and spatial expression between Arabidopsis and Medicago, suggesting distinct signaling routes and distinct roles for these proteins in the two plant species.

Case-parent analysis of variation in pubertal hormone genes and pediatric osteosarcoma: a Children's Oncology Group (COG) study.

Osteosarcoma (OS) is a rare malignant bone tumor with an overall incidence rate of 4.6 cases per million children aged 0-19 years in the United States. While the etiology of OS is largely unknown, its distinctive age-incidence pattern suggests that growth and development is crucial in genesis. Prior studies have suggested that variants in genes in the estrogen metabolism (ESTR) and insulin-like growth factor/growth hormone (IGF/GH) pathways are associated with OS. We examined 798 single nucleotide polymorphisms (SNPs) in 42 genes from these pathways in a case-parent study (229 complete triads and 56 dyads) using buccal cell samples. Relative risks (RR) and 95% confidence intervals (CI) associated with transmitting one or two copies of the variant were estimated using log-linear models. After Bonferroni correction, 1 SNP within the ESTR pathway (rs1415270: RR = 0.50 and 8.37 for 1 and 2 vs. 0 copies, respectively; p = 0.010), and two SNPs in the IGF/GH pathway (rs1003737: RR = 0.91 and 0.0001 for 1 and 2 vs. 0 copies, respectively; p <0.0001 and rs2575352: RR = 2.62 and 0.22 for 1 and 2 vs. 0 copies; p < 0.0001) were significantly associated with OS incidence. These results confirm previous findings that variation in the estrogen metabolism and bone growth pathways influence OS risk and further support a biologically and epidemiologically plausible role in OS development.

Phosphorylated and sumoylation-deficient progesterone receptors drive proliferative gene signatures during breast cancer progression.

INTRODUCTION: Progesterone receptors (PR) are emerging as important breast cancer drivers. Phosphorylation events common to breast cancer cells impact PR transcriptional activity, in part by direct phosphorylation. PR-B but not PR-A isoforms are phosphorylated on Ser294 by mitogen activated protein kinase (MAPK) and cyclin dependent kinase 2 (CDK2). Phospho-Ser294 PRs are resistant to ligand-dependent Lys388 SUMOylation (that is, a repressive modification). Antagonism of PR small ubiquitin-like modifier (SUMO)ylation by mitogenic protein kinases suggests a mechanism for derepression (that is, transcriptional activation) of target genes. As a broad range of PR protein expression is observed clinically, a PR gene signature would provide a valuable marker of PR contribution to early breast cancer progression. METHODS: Global gene expression patterns were measured in T47D and MCF-7 breast cancer cells expressing either wild-type (SUMOylation-capable) or K388R (SUMOylation-deficient) PRs and subjected to pathway analysis. Gene sets were validated by RT-qPCR. Recruitment of coregulators and histone methylation levels were determined by chromatin immunoprecipitation. Changes in cell proliferation and survival were determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays and western blotting. Finally, human breast tumor cohort datasets were probed to identify PR-associated gene signatures; metagene analysis was employed to define survival rates in patients whose tumors express a PR gene signature. RESULTS: 'SUMO-sensitive' PR target genes primarily include genes required for proliferative and pro-survival signaling. DeSUMOylated K388R receptors are preferentially recruited to enhancer regions of derepressed genes (that is, MSX2, RGS2, MAP1A, and PDK4) with the steroid receptor coactivator, CREB-(cAMP-response element-binding protein)-binding protein (CBP), and mixed lineage leukemia 2 (MLL2), a histone methyltransferase mediator of nucleosome remodeling. PR SUMOylation blocks these events, suggesting that SUMO modification of PR prevents interactions with mediators of early chromatin remodeling at 'closed' enhancer regions. SUMO-deficient (phospho-Ser294) PR gene signatures are significantly associated with human epidermal growth factor 2 (ERBB2)-positive luminal breast tumors and predictive of early metastasis and shortened survival. Treatment with antiprogestin or MEK inhibitor abrogated expression of SUMO-sensitive PR target-genes and inhibited proliferation in BT-474 (estrogen receptor (ER)+/PR+/ERBB2+) breast cancer cells. CONCLUSIONS: We conclude that reversible PR SUMOylation/deSUMOylation profoundly alters target gene selection in breast cancer cells. Phosphorylation-induced PR deSUMOylation favors a permissive chromatin environment via recruitment of CBP and MLL2. Patients whose ER+/PR+ tumors are driven by hyperactive (that is, derepressed) phospho-PRs may benefit from endocrine (antiestrogen) therapies that contain an antiprogestin.