Biology subjects

van Dam, T. J. P.

Publications and source records attributed to van Dam, T. J. P..

5 recordsLinked to original sources

bioRxiv2021

Phylogenetic profiling in eukaryotes: The effect of species, orthologous group, and interactome selection on protein interaction prediction

Phylogenetic profiling in eukaryotes is of continued interest to study and predict the functional relationships between proteins. This interest is likely driven by the increased number of available diverse genomes and computational methods to infer orthologies. The evaluation of phylogenetic profiles has mainly focussed on reference genome selection in prokaryotes. However, it has been proven to be challenging to obtain high prediction accuracies in eukaryotes. As part of our recent comparison of orthology inference methods for eukaryotic genomes, we observed a surprisingly high performance for predicting interacting orthologous groups. This high performance, in turn, prompted the question of what factors influence the success of phylogenetic profiling when applied to eukaryotic genomes. Here we analyse the effect of species, orthologous group and interactome selection on protein interaction prediction using phylogenetic profiles. We select species based on the diversity and quality of the genomes and compare this supervised selection with randomly generated genome subsets. We also analyse the effect on the performance of orthologous groups defined to be in the last eukaryotic common ancestor of eukaryotes to that of orthologous groups that are not. Finally, we consider the effects of reference interactome set filtering and reference interactome species. In agreement with other studies, we find an effect of genome selection based on quality, less of an effect based on genome diversity, but a more notable effect based on the amount of information contained within the genomes. Most importantly, we find it is not merely selecting the correct genomes that is important for high prediction performance. Other choices in meta parameters such as orthologous group selection, the reference species of the interaction set, and the quality of the interaction set have a much larger impact on the performance when predicting protein interactions using phylogenetic profiles. These findings shed light on the differences in reported performance amongst phylogenetic profiles approaches, and reveal on a more fundamental level for which types of protein interactions this method has most promise when applied to eukaryotes.

bioinformatics↗

bioRxiv2020

Comparing orthology methods and their performance by recapitulating patterns of eukaryotic genome evolution.

Insights into the evolution of ancestral complexes and pathways are generally achieved through careful and time-intensive manual analysis often using phylogenetic profiles of the constituent proteins. This manual analysis limits the possibility of including more protein-complex components, repeating the analyses for updated genome sets, or expanding the analyses to larger scales. Automated orthology inference should allow such large scale analyses, but substantial differences between orthologous groups generated by different approaches are observed. We evaluate orthology methods for their ability to recapitulate a number of observations that have been made with regards to genome evolution in eukaryotes. Specifically, we investigate phylogenetic profile similarity (co-occurrence of complexes), the Last Eukaryotic Common Ancestors gene content, pervasiveness of gene loss, and the overlap with manually determined orthologous groups. Moreover, we compare the inferred orthologies to each other. We find that most orthology methods reconstruct a large Last Eukaryotic Common Ancestor, with substantial gene loss, and can predict interacting proteins reasonably well when applying phylogenetic co-occurrence. At the same time derived orthologous groups show imperfect overlap with manually curated orthologous groups. There is no strong indication of which orthology method performs better than another on individual or all of these aspects. Counterintuitively, despite the orthology methods behaving similarly regarding large scale evaluation, the obtained orthologous groups differ vastly from one another. Availability and implementationThe data and code underlying this article are available in github and/or upon reasonable request to the corresponding author: https://github.com/ESDeutekom/ComparingOrthologies. SummaryO_LIWe compared multiple orthology inference methods by looking at how well they perform in recapitulating multiple observations made in eukaryotic genome evolution. C_LIO_LICo-occurrence of proteins is predicted fairly well by most methods and all show similar behaviour when looking at loss numbers and dynamics. C_LIO_LIAll the methods show imperfect overlap when compared to manually curated orthologous groups and when compared to orthologous groups of the other methods. C_LIO_LIDifferences are compared between methods by looking at how the inferred orthologies represent a high-quality set of manually curated orthologous groups. C_LIO_LIWe conclude that all methods behave similar when describing general patterns in eukaryotic genome evolution. However, there are large differences within the orthologies themselves, arising from how a method can differentiate between distant homology, recent duplications, or classifying orthologous groups. C_LI

bioinformatics↗

bioRxiv2019

TMEM70 is an assembly factor of mitochondrial complexes I and V

Protein complexes from the oxidative phosphorylation (OXPHOS) system are assembled with the help of proteins called assembly factors. We here delineate the function of the inner mitochondrial membrane protein TMEM70, in which mutations have been linked to OXPHOS deficiencies, using a combination of BioID, complexome profiling and coevolution analyses. TMEM70 interacts with complex I and V and for both complexes the loss of TMEM70 results in the accumulation of an assembly intermediate followed by a reduction of the next assembly intermediate in the pathway. This indicates that TMEM70 has a role in the stability of membrane-bound subassemblies or in the membrane recruitment of subunits into the forming complex. Independent evidence for a role of TMEM70 in OXPHOS assembly comes from evolutionary analyses. The TMEM70/TMEM186/TMEM223 protein family, of which we show that TMEM186 and TMEM223 are mitochondrial in human as well, only occurs in species with OXPHOS complexes. Our results validate the use of combining complexomics with BioID and evolutionary analyses in elucidating congenital defects in protein complex assembly.

cell biology↗

bioRxiv2017

Genome-scale detection of positive selection in 9 primates predicts human-virus evolutionary conflicts

Hotspots of rapid genome evolution hold clues about human adaptation. Here, we present a comparative analysis of nine whole-genome sequenced primates to identify high-confidence targets of positive selection. We find strong statistical evidence for positive selection acting on 331 protein-coding genes (3%), pinpointing 934 adaptively evolving codons (0.014%). Our stringent procedure and quality control of alignments and evolutionary inferences reveal substantial artefacts (20% of initial predictions) that have inflated previous estimates of positive selection, the large majority relating to transcript definitions (61%) or gene models (38%). Our final set of 331 positively selected genes (PSG) are strongly enriched for innate and adaptive immune functions, secreted and cell membrane proteins (e.g. pattern recognition, complement, cytokine pathways, defensins, immune receptors, MHC, Siglecs). We also find evidence for positive selection in reproduction, chromosome segregation and meiosis (e.g. centromere-associated CENPO, CENPT), apolipoproteins, smell/taste receptors, and proteins interacting with mitochondrial-encoded molecules. Focusing on the virus-host interaction, we retrieve most evolutionary conflicts known to influence antiviral activity (e.g. TRIM5, MAVS, SAMHD1, tetherin) and predict 70 novel cases through integration with virus-host interaction data (virus-human PPIs, immune cell expression, infection screens). Protein structure analysis identifies positive selection in the interaction interfaces between viruses and their human cellular receptors (CD4 - HIV; CD46 [MCP] - measles, adenoviruses; CD55 [DAF] - picornaviruses). Finally, the primate PSG consistently show high sequence variation in human exomes, suggesting ongoing evolution. Our curated dataset of positively selected genes and positions, available at http://www.cmbi.umcn.nl/[~]rvdlee/positive_selection/, is a rich source for studying the genetics underlying human (antiviral) phenotypes.

evolutionary biology↗

bioRxiv2017

CiliaCarta: An Integrated And Validated Compendium Of Ciliary Genes

The cilium is an essential organelle at the surface of most mammalian cells whose dysfunction causes a wide range of genetic diseases collectively called ciliopathies. The current rate at which new ciliopathy genes are identified suggests that many ciliary components remain undiscovered. We generated and rigorously analyzed genomic, proteomic, transcriptomic and evolutionary data and systematically integrated these using Bayesian statistics into a predictive score for ciliary function. This resulted in 285 candidate ciliary genes. We found experimental evidence of ciliary associations for 24 out of 36 analyzed candidate proteins. In addition, we show that OSCP1, which has previously been implicated in two distinct non-ciliary functions, causes a cilium dysfunction phenotype when depleted in zebrafish. The candidate list forms the basis of CiliaCarta, a comprehensive ciliary compendium covering 836 genes. The resource can be used to objectively prioritize candidate genes in whole exome or genome sequencing of ciliopathy patients and can be accessed at http://bioinformatics.bio.uu.nl/john/syscilia/ciliacarta/.

bioinformatics↗