NeoDarwinian Review

Livestock improvement relies on understanding not just the genetic makeup (genome) of animals, but also how genes are regulated - a layer of complexity governed by epigenetics . The research article "53 Establishing a Pan-Epigenome for Cattle and Sheep" tackles this very concept, proposing the creation of a comprehensive reference, a pan-epigenome, for these economically important farm animals. The authors acknowledge the growing field of pangenomics in livestock, which focuses on deciphering genetic variation. However, they highlight a gap – the lack of a similar focus on epigenetics, which can significantly influence traits like meat quality and disease resistance. So, what exactly is a pan-epigenome? It's a comprehensive map of epigenetic modifications across different breeds of a species. These modifications, unlike DNA changes, are reversible and act as a switch, turning genes on or off without altering the underlying code. By studying these variations

The journal article "De novo emergence of adaptive membrane proteins from thymine-rich genomic sequences" by Vakirlis et al. (2020) explores a fascinating concept in evolution: the birth of entirely new protein-coding genes from previously non-coding DNA. This research challenges the traditional neo-Darwinian view where genes arise solely through mutations in existing (exon) ones. The study focuses on budding yeast, a well-studied organism. Recent discoveries suggest that snippets of RNA, normally non-coding , can sometimes be translated into proteins. This "accidental" protein production exposes a vast pool of potential new functionalities. Vakirlis et al. investigate how these "de novo emerging" coding sequences impact the fitness of yeast. Fitness and the Unexpected Advantage of New Genes The researchers disrupted these emerging sequences in the yeast genome. Surprisingly, these disruptions had little effect on the yeast's fitness in la

The journal article "Understanding the causes of errors in eukaryotic protein-coding gene prediction: a case study of primate proteomes" by Meyer et al. (2020) tackles a fundamental challenge in genomics – the accuracy of predicting protein-coding genes in eukaryotes. This process, known as gene prediction, underpins our understanding of how genes translate into functional proteins, the essential machinery that carries out cellular functions. The authors highlight the limitations of current gene prediction methods and delve into the specific causes of errors within the genomes of primates. The Pitfalls of Prediction: These errors can manifest in various ways, including entirely missing gene predictions , predicting genes in incorrect locations, or introducing mistakes in the predicted protein sequence. The authors reference previous research suggesting a high error rate in protein-coding gene prediction for eukaryotes, with estimates reaching up to 50% of sequen