Professor McInerney is an Irish-born scientist, and former Head of the School of Life Sciences at The University of Nottingham (from Feb 1st, 2018 until Feb 1st, 2022). He holds the Chair in Evolutionary Biology, and is a Principal Investigator in the School of Life Sciences.
In 2020 he was elected President of the Society for Molecular Biology and Evolution, the world’s largest evolutionary biology society, a position he will hold for the duration of 2022. In 2015, Prof. McInerney was elected as a Fellow of the American Academy of Microbiology, and since 2016, he has been an elected Fellow of the Linnean Society.
Before coming to Nottingham, Prof. McInerney was Chair in Evolutionary Biology at The University of Manchester and also the founding Director for the research domain of “Evolution, Systems and Genomics”. For the academic year 2012-2013, Prof. McInerney took a sabbatical at the Center for Communicable Disease Dynamics at Harvard University, USA. In 2013, he was awarded a DSc by the National University of Ireland for a thesis entitled “Studies on the evolution of genes and genomes”.
Professor McInerney’s research group has contributed significantly to the current understanding of horizontal gene transfer, eukaryotic origins and the origin and maintenance of prokaryotic pangenomes. Using a supertree approach that was developed in the research group, the McInerney lab was the first to use genome-wide data to show that the agreement between phylogenetic trees inferred across large numbers of gene families was no better than random, implying that HGT is pervasive among microbes and very likely there is no tree of life that can capture the evolutionary history of most genes. Prof. McInerney has also co-authored work that showed that large amounts of HGT catalysed the origins of halophiles and contributed to the origins of many other Archaeal groups. He has also made several contributions to the understanding of how the first eukaryote cells arose. More recently, in Nature Microbiology, along with Dr. Mary O’Connell and Prof. Alan McNally, Prof. McInerney proposed a comprehensive evolutionary model for how prokaryotic pangenomes originate and are maintained.
Domingo-Sananes, M.R. and McInerney, J.O. (2021) Mechanisms That Shape Microbial Pangenomes. Trends in Microbiology 6 493-503 https://doi.org/10.1016/j.tim.2020.12.004
Whelan, F.J. Rusilowicz, M. and McInerney J.O. (2020) Coinfinder: detecting significant associations and dissociations in pangenomes. Microbial Genomics. 6(3): e000338 DOI 10.1099/mgen.0.000338
McInerney, J.O., McNally, A and O’Connell, M.J. (2017) Why Prokaryotes have Pangenomes. Nature Microbiology 2, 17040. https://www.nature.com/articles/nmicrobiol201740
McInerney, J.O. and O’Connell, M.J. (2017) Minding the gaps in cellular evolution. Nature 541, 297–299 doi:10.1038/nature21113
McInerney, J.O. (2016) Evolution: A four billion year old metabolism. Nature Microbiology. 1, Art. No. 16139. https://www.nature.com/articles/nmicrobiol2016139
Ku, C., Nelson-Sathi, S., Roettger, M., Sousa, F.L., Lockhart, P., Bryant, D., Hazkani-Covo,E., McInerney, J.O., Landan, G., and Martin, W.F. (2015) Endosymbiotic origin and differential loss of eukaryotic genes Nature. 524, 427–432. doi:10.1038/nature14963
Nelson-Sathi, et al., (2015). Origins of major archaeal clades correspond to gene acquisitions from bacteria. Nature doi:10.1038/nature13805. [pdf]
McInerney, J.O. and O’Connell, M.J. (2014) Evolutionary developmental biology: Ghost locus appears. Nature 514, 570–571. doi:10.1038/514570a. [pdf]
McInerney, et al., (2014). The hybrid nature of the Eukaryota and a consilient view of life on Earth. Nature Reviews Microbiology doi:10.1038/nrmicro3271.[pdf]
Liu et al., (2014) Population Genomics Reveal Recent Speciation and Rapid Evolutionary Adaptation in Polar Bears. Cell , 157(4) 785 – 794. doi:10.1016/j.cell.2014.03.054 [pdf]
Alvarez-Ponce, et al., (2013). Gene similarity networks provide new tools for understanding eukaryote origins and evolution.Proceedings of the National Academy of Sciences USA doi: 10.1073/pnas.1211371110.[pdf]
Nelson-Sathi, et al., (2012) Acquisition of 1,000 eubacterial genes physiologically transformed a methanogen at the origin of Haloarchaea. Proceedings of the National Academy of Sciences USA. 109 (50) 20537-20542 doi: 10.1073/pnas.1209119109.[pdf]
Bapteste et al., (2012). Evolutionary analyses of non-genealogical bonds produced by introgressive descent. Proceedings of the National Academy of Sciences, USA. 109:(45) 18266-18272 doi:10.1073/pnas.1206541109.
Cotton, J.A., and McInerney, J.O. (2010) Eukaryotic genes of archaebacterial origin are more important than the more numerous eubacterial genes, irrespective of function. Proceedings of the National Academy of Sciences, USA 107:40 17252-17255. [link]
McInerney, J.O. and Pisani, D (2007) Genetics: Paradigm for Life. Science 318:1390-1391. [link]
Kinsella et al., (2003). Fatty acid biosynthesis in Mycobacterium tuberculosis: Lateral gene transfer, adaptive evolution and gene duplication. Proceedings of the National Academy of Sciences, USA, 100, 10320-10325. [link]
McInerney, J.O. (1998). Replicational and Transcriptional Selection on Codon Usage in Borrelia burgdorferi. Proceedings of the National Academy of Sciences, USA: 95 10698-10703. [link]
You can find more of our publications by clicking the Papers tab at the top of this page.
– Horizontal Gene Transfer
– Eukaryote origins and early evolution
– Network analyses of evolution
– Synonymous Codon Usage
– Phylogenetic Supertrees
– Adaptive evolution
Major Software Projects:
Coinfinder: detecting significant associations and dissociations in pangenomes
TIGER: Tree-Independent Generation of Evolutionary Rates.
TOPD/FMTS: Software to Compare Phylogenetic Trees (Developed by Pere Puigbo, during his stay in the group).
MultiPhyl: Phylogenetic Supercomputer.
Modelgenerator: Selection of Amino Acid Substitution Matrices.
DPRml: Distributed Phylogeny Reconstruction by Maximum Likelihood.
CLANN: Investigating Phylogenetic Information Through Supertree Analysis.
Crann: A Program for Detecting Adaptive Evolution in Protein-Coding DNA Sequences.
GCUA: General Codon Usage Analysis.