A statistical model-building perspective to identification of MS/MS spectra with PeptideProphet.

PeptideProphet is a post-processing algorithm designed to evaluate the confidence in identifications of MS/MS spectra returned by a database search. In this manuscript we describe the "what and how" of PeptideProphet in a manner aimed at statisticians and life scientists who would like to gain a more in-depth understanding of the underlying statistical modeling. The theory and rationale behind the mixture-modeling approach taken by PeptideProphet is discussed from a statistical model-building perspective followed by a description of how a model can be used to express confidence in the identification of individual peptides or sets of peptides. We also demonstrate how to evaluate the quality of model fit and select an appropriate model from several available alternatives. We illustrate the use of PeptideProphet in association with the Trans-Proteomic Pipeline, a free suite of software used for protein identification.

Cross-kingdom comparison of transcriptomic adjustments to low-oxygen stress highlights conserved and plant-specific responses.

High-throughput technology has facilitated genome-scale analyses of transcriptomic adjustments in response to environmental perturbations with an oxygen deprivation component, such as transient hypoxia or anoxia, root waterlogging, or complete submergence. We showed previously that Arabidopsis (Arabidopsis thaliana) seedlings elevate the levels of hundreds of transcripts, including a core group of 49 genes that are prioritized for translation across cell types of both shoots and roots. To recognize low-oxygen responses that are evolutionarily conserved versus species specific, we compared the transcriptomic reconfiguration in 21 organisms from four kingdoms (Plantae, Animalia, Fungi, and Bacteria). Sorting of organism proteomes into clusters of putative orthologs identified broadly conserved responses associated with glycolysis, fermentation, alternative respiration, metabolite transport, reactive oxygen species amelioration, chaperone activity, and ribosome biogenesis. Differentially regulated genes involved in signaling and transcriptional regulation were poorly conserved across kingdoms. Strikingly, nearly half of the induced mRNAs of Arabidopsis seedlings encode proteins of unknown function, of which over 40% had up-regulated orthologs in poplar (Populus trichocarpa), rice (Oryza sativa), or Chlamydomonas reinhardtii. Sixteen HYPOXIA-RESPONSIVE UNKNOWN PROTEIN (HUP) genes, including four that are Arabidopsis specific, were ectopically overexpressed and evaluated for their effect on seedling tolerance to oxygen deprivation. This allowed the identification of HUPs coregulated with genes associated with anaerobic metabolism and other processes that significantly enhance or reduce stress survival when ectopically overexpressed. These findings illuminate both broadly conserved and plant-specific low-oxygen stress responses and confirm that plant-specific HUPs with limited phylogenetic distribution influence low-oxygen stress endurance.