De novo creation of protein coding genes involves the formation of short ORFs from noncoding regions; some of these ORFs might then become fixed in the population. These orphan proteins need to, at the bare minimum, not cause serious harm to the organism, meaning that they should for instance not aggregate. Therefore, although the creation of short ORFs could be truly random, the fixation should be subjected to some selective pressure. The selective forces acting on orphan proteins have been elusive, and contradictory results have been reported. In Drosophila young proteins are more disordered than ancient ones, while the opposite trend is present in yeast. To the best of our knowledge no valid explanation for this difference has been proposed. To solve this riddle we studied structural properties and age of proteins in 187 eukaryotic organisms. We find that, with the exception of length, there are only small differences in the properties between proteins of different ages. However, when we take the GC content into account we noted that it could explain the opposite trends observed for orphans in yeast (low GC) and Drosophila (high GC). GC content is correlated with codons coding for disorder promoting amino acids. This leads us to propose that intrinsic disorder is not a strong determining factor for fixation of orphan proteins. Instead these proteins largely resemble random proteins given a particular GC level. During evolution the properties of a protein change faster than the GC level causing the relationship between disorder and GC to gradually weaken.

Intrinsic disorder is more abundant in eukaryotic than prokaryotic proteins. Methods predicting intrinsic disorder are based on the amino acid sequence of a protein. Therefore, there must exist an underlying difference in the sequences between eukaryotic and prokaryotic proteins causing the (predicted) difference in intrinsic disorder. By comparing proteins, from complete eukaryotic and prokaryotic proteomes, we show that the difference in intrinsic disorder emerges from the linker regions connecting Pfam domains. Eukaryotic proteins have more extended linker regions, and in addition, the eukaryotic linkers are significantly more disordered, 38% vs. 12-16% disordered residues. Next, we examined the underlying reason for the increase in disorder in eukaryotic linkers, and we found that the changes in abundance of only three amino acids cause the increase. Eukaryotic proteins contain 8.6% serine; while prokaryotic proteins have 6.5%, eukaryotic proteins also contain 5.4% proline and 5.3% isoleucine compared with 4.0% proline and ≈ 7.5% isoleucine in the prokaryotes. All these three differences contribute to the increased disorder in eukaryotic proteins. It is tempting to speculate that the increase in serine frequencies in eukaryotes is related to regulation by kinases, but direct evidence for this is lacking. The differences are observed in all phyla, protein families, structural regions and type of protein but are most pronounced in disordered and linker regions. The observation that differences in the abundance of three amino acids cause the difference in disorder between eukaryotic and prokaryotic proteins raises the question: Are amino acid frequencies different in eukaryotic linkers because the linkers are more disordered or do the differences cause the increased disorder?

Estrogens exert a key biological role in mammary gland epithelial cells and promote breast carcinogenesis and tumor progression. We recently identified a new large set of estrogen responsive genes from breast cancer (BC) cells by DNA microarray analysis of the gene expression profiles induced by 17beta-estradiol in ZR-75.1 and MCF-7 cells. The purpose of the present study was to test whether the expression pattern of hormone regulated genes from this set identifies estrogen receptor (ERalpha) positive, hormone responsive BC cells. To this aim, we carried out in silico metanalysis of ERalpha positive and ERalpha negative human BC cell line transcriptomes, focusing on two sets of 171 and 218 estrogen responsive genes, respectively. Results show that estrogen dependent gene activity in hormone responsive BC cells is significantly different from that of non-responsive cells and, alone, allows to discriminate these two cellular phenotypes. Indeed, we have identified 61 genes whose expression profile specifically marks ERalpha positive BC cells, suggesting that this gene set may be exploited for phenotypic characterization of breast tumors. This possibility was tested with data obtained by gene expression profiling of BC surgical samples, where the ERalpha positive phenotypes were highlighted by the expression profile of a subset of 27 such hormone responsive genes and four additional BC marker genes, not including ERs. These results provide direct evidence that the expression pattern of a limited number of estrogen responsive genes can be exploited to assess the estrogen signaling status of BC cells both in vitro and ex-vivo.