Four classic "de novo" genes all have plausible homologs and likely evolved from retro-duplicated or pseudogenic sequences.

Despite being previously regarded as extremely unlikely, the idea that entirely novel protein-coding genes can emerge from non-coding sequences has gradually become accepted over the past two decades. Examples of "de novo origination", resulting in lineage-specific "orphan" genes, lacking coding orthologs, are now produced every year. However, many are likely cases of duplicates that are difficult to recognize. Here, I re-examine the claims and show that four very well-known examples of genes alleged to have emerged completely "from scratch"- FLJ33706 in humans, Goddard in fruit flies, BSC4 in baker's yeast and AFGP2 in codfish-may have plausible evolutionary ancestors in pre-existing genes. The first two are likely highly diverged retrogenes coding for regulatory proteins that have been misidentified as orphans. The antifreeze glycoprotein, moreover, may not have evolved from repetitive non-genic sequences but, as in several other related cases, from an apolipoprotein that could have become pseudogenized before later being reactivated. These findings detract from various claims made about de novo gene birth and show there has been a tendency not to invest the necessary effort in searching for homologs outside of a very limited syntenic or phylostratigraphic methodology. A robust approach is used for improving detection that draws upon similarities, not just in terms of statistical sequence analysis, but also relating to biochemistry and function, to obviate notable failures to identify homologs.

Quantifying protein sequences with reference to the genetic code.

Although the analysis of protein molecules is extensive, their primary sequences have yet to be quantified like their mass or size. The composition and particular arrangement of amino acids in proteins confers the distinct biochemical functionality, but it remains unclear why only a tiny proportion of possible character combinations are potentially functional. Here, I offer a simple but effective technique, utilizing the assignment of codons in the genetic code, that permits the quantification of polypeptide sequences and establishes statistical parameters through which they can now be numerically compared. Two main tests were conducted, one analyzing the composition and the other the specific order of the amino acids within the primary sequence. The results confirm that natural proteins are significantly different to random heteropolymers of equivalent size, although this is much more marginal in the case of the arrangement than it is for the composition. Moreover, they reveal that there are key patterns that have hitherto not been identified, relevant to the the study of the evolution of proteins, and which raise doubts about the plausibility of some purported cases of the de novo origination of protein-coding genes from intergenic DNA. Despite the fact that the applicability of quantification to the design of novel proteins is probably limited, it nonetheless provides a useful guideline that could complement much more precise methods.