Search bioRxivSearch

Biology subjects

Emms, D.

Publications and source records attributed to Emms, D..

2 recordsLinked to original sources

Gene duplication accelerates the pace of protein gain and loss from plant organelles.

Introductory paragraphA hallmark of eukaryotic cells is the compartmentalisation of intracellular processes into specialised membrane-bound compartments known as organelles. Plant cells contain several such organelles including the nucleus, chloroplast, mitochondrion, peroxisome, golgi, endoplasmic reticulum and vacuole. Organelle biogenesis and function is dependent on the concerted action of numerous nuclear-encoded proteins which must be imported from the cytosol (or endoplasmic reticulum) where they are made. Using phylogenomic approaches coupled to ancestral state estimation we show that the rate of change in plant organellar proteome content is proportional to the rate of molecular sequence evolution such that the proteomes of chloroplasts and mitochondria lose or gain ~3.2 proteins per million years. We show that these changes in protein targeting have predominantly occurred in genes with regulatory rather than metabolic functions, and thus altered regulatory capacity rather than metabolic function has been the major theme of plant organellar evolution. Finally we show gain and loss of protein targeting occurs at a higher rate following gene duplication events, revealing that gene and genome duplication are a key facilitator of organelle evolution.

evolutionary biology

STAG: Species Tree Inference from All Genes

Species tree inference is fundamental to our understanding of the evolution of life on earth. However, species tree inference from molecular sequence data is complicated by gene duplication events that limit the availably of suitable data for phylogenetic reconstruction. Here we propose a novel method for species tree inference called STAG that is specifically designed to leverage data from multi-copy gene families. By application to 12 real species datasets sampled from across the eukaryotic domain we demonstrate that species trees inferred from multi-copy gene families are comparable in accuracy to species trees inferred from single-copy orthologues. We further show that the ability to utilise data from multi-copy gene families increases the amount of data available for species tree inference by an average of 8 fold. We reveal that on real species datasets STAG has higher accuracy than other leading methods for species tree inference; including concatenated alignments of protein sequences, ASTRAL & NJst. Finally we show that STAG is fast, memory efficient and scalable and thus suitable for analysis of large multispecies datasets.

evolutionary biology