Summary Eukaryotic cells make many types of primary and processed RNAs that are found either in specific sub-cellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic sub-cellular localizations are also poorly understood. Since RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell’s regulatory capabilities are focused on its synthesis, processing, transport, modifications and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations taken together prompt to a redefinition of the concept of a gene.

The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome.

Data from the Encyclopedia of DNA Elements (ENCODE) project show over 9640 human genome loci classified as long noncoding RNAs (lncRNAs), yet only~100 have been deeply characterized to determine their role in the cell. To measure the protein-coding output from these RNAs, we jointly analyzed two recent data sets produced in the ENCODE project: tandem mass spectrometry (MS/MS) data mapping expressed peptides to their encoding genomic loci, and RNA-seq data generated by ENCODE in long polyA+ and polyA-fractions in the cell lines K562 and GM12878. We used the machinelearning algorithm RuleFit3 to regress the peptide data against RNA expression data. The most important covariate for predicting translation was, surprisingly, the Cytosol polyA-fraction in both cell lines. LncRNAs are~13-fold less likely to produce detectable peptides than similar mRNAs, indicating that~92% of GENCODE v7 lncRNAs are not translated in these two ENCODE cell lines. Intersecting 9640 lncRNA loci with 79,333 peptides yielded 85 unique peptides matching 69 lncRNAs. Most cases were due to a coding transcript misannotated as lncRNA. Two exceptions were an unprocessed pseudogene and a bona fide lncRNA gene, both with open reading frames (ORFs) compromised by upstream stop codons. All potentially translatable lncRNA ORFs had only a single peptide match, indicating low protein abundance and/or false-positive peptide matches. We conclude that with very few exceptions, ribosomes are able to distinguish coding from noncoding transcripts and, hence, that ectopic translation and cryptic mRNAs are rare in the human lncRNAome.

The simplest approximation of interaction potential between amino-acids in proteins is the contact potential, which defines the effective free energy of a protein conformation by a set of amino acid contacts formed in this conformation. Finding a contact potential capable of predicting free energies of protein states across a variety of protein families will aid protein folding and engineering in silico on a computationally tractable time-scale. We test the ability of contact potentials to accurately and transferably (across various protein families) predict stability changes of proteins upon mutations. We develop a new methodology to determine the contact potentials in proteins from experimental measurements of changes in protein's thermodynamic stabilities ( G) upon mutations. We apply our methodology to derive sets of contact interaction parameters for a hierarchy of interaction models including solvation and multi-body contact parameters. We test how well our models reproduce experimental measurements by statistical tests. We evaluate the maximum accuracy of predictions obtained by using contact potentials and the correlation between parameters derived from different data-sets of experimental G values. We argue that it is impossible to reach experimental accuracy and derive fully transferable contact parameters using the contact models of potentials. However, contact parameters can yield reliable predictions of G for datasets of mutations confined to specific amino-acid positions in the sequence of a single protein.

The identification of proteins by tandem mass spectrometry relies on knowledge of the products produced by collision-induced dissociation of peptide ions. Most previous work has focused on fragmentation statistics for ion trap systems. We analyzed fragmentation in MALDI TOF/TOF mass spectrometry, collecting statistics using a curated set of 2459 MS/MS spectra and applying bootstrap resampling to assess confidence intervals. We calculated the frequency of 18 product ion types, the correlation between both mass and intensity with ion type, the dependence of amide bond breakage on the residues surrounding the cleavage site, and the dependence of product ion detection on residues not adjacent to the cleavage site. The most frequently observed were internal ions, followed by y ions. A strong correlation between ion type and the mass and intensity of its peak was observed, with b and y ions producing the most intense and highest mass peaks. The amino acids P, W, D, and R had a strong effect on amide bond cleavage when situated next to the breakage site, whereas residues including I, K, and H had a strong effect on product ion observation when located in the peptide but not adjacent to the cleavage site, a novel observation.