Like all forms of life, bacteria undergo evolution. However, unlike many other organisms, bacterial evolution is not one of strict vertical descent. Horizontal (or lateral) gene transfer (HGT), a process by which genetic material is transferred among distantly related species, is ubiquitous in the prokaryotic branch of the Tree of Life. In the presence of HGT, the evolutionary history of a set of organisms is not treelike;rather, it is reticulate. HGT plays a major role in microbial genome diversification, and is claimed to be rampant among various groups of genes in bacteria. Further, it is a major mechanism by which bacteria develop resistance to antibiotics. Two major challenges that face studies of bacterial genomes involve estimating the extent of horizontally transferred genes in them, and reconstructing their evolutionary history. The former bears great significance on understanding the evolutionary role HGT plays and making predictions about its occurrence, and the latter amounts to detecting the donors and recipients of horizontally transferred genes, helping to understand how bacteria acquire antibiotic resistance and how to develop more effective ones. Attempts at addressing the first challenge have led to conflicting results, whereas attempts at the second challenge have been limited. Estimates as to the extent of HGT in bacteria range from one extreme (HGT is so rampant, rendering a bacterial phylogenetic tree useless) to another (HGT is mere background noise overridden by the lineal descent signal). As for the challenge of reconstructing reticulate evolutionary histories, the progress is even less satisfactory, mainly due to the lack of accurate and efficient methods for reconstructing phylogenetic networks. Our objective is to develop computational tools for high-throughput genome-wide evolutionary analysis of bacterial genomes, with focus on the detection and reconstruction of HGT. To achieve this objective, we will develop: (1) Protocols for micro-level analyses of bacterial genomes, to estimate HGT rates. (2) A stochastic framework that combined population genetics and phylogenetics theories for medium-level analyses. (3) Algorithmic techniques for phylogenetic (macro-level) analyses of genomes for detecting HGT. (4) Software tools that implement the protocols and methodologies and make them available to the research community.

National Institute of Health (NIH)
National Library of Medicine (NLM)
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Biomedical Library and Informatics Review Committee (BLR)
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Ye, Jane
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Rice University
Biostatistics & Other Math Sci
Schools of Engineering
United States
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Wen, Dingqiao; Yu, Yun; Zhu, Jiafan et al. (2018) Inferring Phylogenetic Networks Using PhyloNet. Syst Biol 67:735-740
Liu, Kevin J; Steinberg, Ethan; Yozzo, Alexander et al. (2015) Interspecific introgressive origin of genomic diversity in the house mouse. Proc Natl Acad Sci U S A 112:196-201
Liu, Kevin J; Dai, Jingxuan; Truong, Kathy et al. (2014) An HMM-based comparative genomic framework for detecting introgression in eukaryotes. PLoS Comput Biol 10:e1003649
Yu, Yun; Dong, Jianrong; Liu, Kevin J et al. (2014) Maximum likelihood inference of reticulate evolutionary histories. Proc Natl Acad Sci U S A 111:16448-53
Yu, Yun; Ristic, Nikola; Nakhleh, Luay (2013) Fast algorithms and heuristics for phylogenomics under ILS and hybridization. BMC Bioinformatics 14 Suppl 15:S6
Nakhleh, Luay (2013) Computational approaches to species phylogeny inference and gene tree reconciliation. Trends Ecol Evol 28:719-28
Yu, Yun; Barnett, R Matthew; Nakhleh, Luay (2013) Parsimonious inference of hybridization in the presence of incomplete lineage sorting. Syst Biol 62:738-51
Park, Hyun Jung; Nakhleh, Luay (2012) Inference of reticulate evolutionary histories by maximum likelihood: the performance of information criteria. BMC Bioinformatics 13 Suppl 19:S12
Yu, Yun; Degnan, James H; Nakhleh, Luay (2012) The probability of a gene tree topology within a phylogenetic network with applications to hybridization detection. PLoS Genet 8:e1002660
Yu, Yun; Warnow, Tandy; Nakhleh, Luay (2011) Algorithms for MDC-based multi-locus phylogeny inference: beyond rooted binary gene trees on single alleles. J Comput Biol 18:1543-59

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