The Pathway Coexpression Network: Revealing pathway relationships.

A goal of genomics is to understand the relationships between biological processes. Pathways contribute to functional interplay within biological processes through complex but poorly understood interactions. However, limited functional references for global pathway relationships exist. Pathways from databases such as KEGG and Reactome provide discrete annotations of biological processes. Their relationships are currently either inferred from gene set enrichment within specific experiments, or by simple overlap, linking pathway annotations that have genes in common. Here, we provide a unifying interpretation of functional interaction between pathways by systematically quantifying coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) to establish the Pathway Coexpression Network (PCxN). We estimated the correlation between canonical pathways valid in a broad context using a curated collection of 3,207 microarrays from 72 normal human tissues. PCxN accounts for shared genes between annotations to estimate significant correlations between pathways with related functions rather than with similar annotations. We demonstrate that PCxN provides novel insight into mechanisms of complex diseases using an Alzheimer's Disease (AD) case study. PCxN retrieved pathways significantly correlated with an expert curated AD gene list. These pathways have known associations with AD and were significantly enriched for genes independently associated with AD. As a further step, we show how PCxN complements the results of gene set enrichment methods by revealing relationships between enriched pathways, and by identifying additional highly correlated pathways. PCxN revealed that correlated pathways from an AD expression profiling study include functional clusters involved in cell adhesion and oxidative stress. PCxN provides expanded connections to pathways from the extracellular matrix. PCxN provides a powerful new framework for interrogation of global pathway relationships. Comprehensive exploration of PCxN can be performed at http://pcxn.org/

Data from: Elucidating biogeographical patterns in Australian native canids using genome wide SNPs

Dingoes play a strong role in Australia’s ecological framework as the apex predator but are under threat from hybridization and agricultural control programs. Government legislation lists the conservation of the dingo as an important aim, yet little is known about the biogeography of this enigmatic canine, making conservation difficult. Mitochondrial and Y chromosome DNA studies show evidence of population structure within the dingo. Here, we present the data from Illumina HD canine chip genotyping for 23 dingoes from five regional populations, and five New Guinea Singing Dogs to further explore patterns of biogeography using genome-wide data. Whole genome single nucleotide polymorphism (SNP) data supported the presence of three distinct dingo populations (or ESUs) subject to geographical subdivision: southeastern (SE), Fraser Island (FI) and northwestern (NW). These ESUs should be managed discretely. The FI dingoes are a known reservoir of pure, genetically distinct dingoes. Elevated inbreeding coefficients identified here suggest this population may be genetically compromised and in need of rescue; current lethal management strategies that do not consider genetic information should be suspended until further data can be gathered. D statistics identify evidence of historical admixture or ancestry sharing between southeastern dingoes and South East Asian village dogs. Conservation efforts on mainland Australia should focus on the SE dingo population that is under pressure from domestic dog hybridization and high levels of lethal control. Further data concerning the genetic health, demographics and prevalence of hybridization in the SE and FI dingo populations is urgently needed to develop evidence based conservation and management strategies

Genotype file for Canine HD array from 24 dingoes (bed)

Illumina CanineHD SNP data from 24 dingoes. In PLINK binary format (.bed, .bim and .fam)