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Gene acquisition in eukaryotes
C L Bishop
Genome Biology , 2003, DOI: 10.1186/gb-spotlight-20030528-01
Abstract: In the early edition of Proceedings of the National Academy of Sciences, John Archibald and colleagues from The Canadian Institute for Advanced Research describe phylogenetic analysis of several plastid-targeted proteins from a chlorarachniophytes. They show that a significant number of genes have been acquired through lateral gene transfer from numerous sources, but that the genes of the chlorophyte Chlamydomonas reinhardtii show no evidence of lateral gene transfer (PNAS, DOI:10.1073/pnas.1230951100).Archibald et al. screened nearly 4,000 ESTs (expressed sequence tags) from the chlorarachniophyte Bigelowiella natans and identified 78 cDNAs encoding putative plastid-targeted proteins. By means of alignment and phylogenetic analysis, they established that the majority were derived from a chlorophyte of green algal origin. But 21% of the proteins had phylogenetic affinities that indicated they were from a source other than the endosymbiont. These genes had been acquired by lateral gene transfer from a variety of sources, including streptophyte algae, red algae, algae with red algal endosymbionts and even bacteria. Similar analysis of the chlorophyte Chlamydomonas reinhardtii showed no evidence of lateral gene transfer."There is no obvious reason to assume that the acquisition of foreign genes by chlorarachniophytes is limited to those involved in plastid function. Whether lateral transfer will prove to be as important in eukaryotes as in prokaryotes remains to be seen... At present, it seems that lateral gene transfer has been a factor in the evolution of eukaryotic genomes, but that its impact may very from lineage to lineage," conclude the authors.
An HMM-Based Comparative Genomic Framework for Detecting Introgression in Eukaryotes  [PDF]
Kevin J. Liu ,Jingxuan Dai,Kathy Truong,Ying Song,Michael H. Kohn,Luay Nakhleh
PLOS Computational Biology , 2014, DOI: doi/10.1371/journal.pcbi.1003649
Abstract: One outcome of interspecific hybridization and subsequent effects of evolutionary forces is introgression, which is the integration of genetic material from one species into the genome of an individual in another species. The evolution of several groups of eukaryotic species has involved hybridization, and cases of adaptation through introgression have been already established. In this work, we report on PhyloNet-HMM—a new comparative genomic framework for detecting introgression in genomes. PhyloNet-HMM combines phylogenetic networks with hidden Markov models (HMMs) to simultaneously capture the (potentially reticulate) evolutionary history of the genomes and dependencies within genomes. A novel aspect of our work is that it also accounts for incomplete lineage sorting and dependence across loci. Application of our model to variation data from chromosome 7 in the mouse (Mus musculus domesticus) genome detected a recently reported adaptive introgression event involving the rodent poison resistance gene Vkorc1, in addition to other newly detected introgressed genomic regions. Based on our analysis, it is estimated that about 9% of all sites within chromosome 7 are of introgressive origin (these cover about 13 Mbp of chromosome 7, and over 300 genes). Further, our model detected no introgression in a negative control data set. We also found that our model accurately detected introgression and other evolutionary processes from synthetic data sets simulated under the coalescent model with recombination, isolation, and migration. Our work provides a powerful framework for systematic analysis of introgression while simultaneously accounting for dependence across sites, point mutations, recombination, and ancestral polymorphism.
An HMM-based Comparative Genomic Framework for Detecting Introgression in Eukaryotes  [PDF]
Kevin J. Liu,Jingxuan Dai,Kathy Truong,Ying Song,Michael H. Kohn,Luay Nakhleh
Quantitative Biology , 2013, DOI: 10.1371/journal.pcbi.1003649
Abstract: One outcome of interspecific hybridization and subsequent effects of evolutionary forces is introgression, which is the integration of genetic material from one species into the genome of an individual in another species. The evolution of several groups of eukaryotic species has involved hybridization, and cases of adaptation through introgression have been already established. In this work, we report on a new comparative genomic framework for detecting introgression in genomes, called PhyloNet-HMM, which combines phylogenetic networks, that capture reticulate evolutionary relationships among genomes, with hidden Markov models (HMMs), that capture dependencies within genomes. A novel aspect of our work is that it also accounts for incomplete lineage sorting and dependence across loci. Application of our model to variation data from chromosome 7 in the mouse (Mus musculus domesticus) genome detects a recently reported adaptive introgression event involving the rodent poison resistance gene Vkorc1, in addition to other newly detected introgression regions. Based on our analysis, it is estimated that about 12% of all sites withinchromosome 7 are of introgressive origin (these cover about 18 Mbp of chromosome 7, and over 300 genes). Further, our model detects no introgression in two negative control data sets. Our work provides a powerful framework for systematic analysis of introgression while simultaneously accounting for dependence across sites, point mutations, recombination, and ancestral polymorphism.
Identification of Divergent Protein Domains by Combining HMM-HMM Comparisons and Co-Occurrence Detection  [PDF]
Amel Ghouila, Isabelle Florent, Fatma Zahra Guerfali, Nicolas Terrapon, Dhafer Laouini, Sadok Ben Yahia, Olivier Gascuel, Laurent Bréhélin
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0095275
Abstract: Identification of protein domains is a key step for understanding protein function. Hidden Markov Models (HMMs) have proved to be a powerful tool for this task. The Pfam database notably provides a large collection of HMMs which are widely used for the annotation of proteins in sequenced organisms. This is done via sequence/HMM comparisons. However, this approach may lack sensitivity when searching for domains in divergent species. Recently, methods for HMM/HMM comparisons have been proposed and proved to be more sensitive than sequence/HMM approaches in certain cases. However, these approaches are usually not used for protein domain discovery at a genome scale, and the benefit that could be expected from their utilization for this problem has not been investigated. Using proteins of P. falciparum and L. major as examples, we investigate the extent to which HMM/HMM comparisons can identify new domain occurrences not already identified by sequence/HMM approaches. We show that although HMM/HMM comparisons are much more sensitive than sequence/HMM comparisons, they are not sufficiently accurate to be used as a standalone complement of sequence/HMM approaches at the genome scale. Hence, we propose to use domain co-occurrence — the general domain tendency to preferentially appear along with some favorite domains in the proteins — to improve the accuracy of the approach. We show that the combination of HMM/HMM comparisons and co-occurrence domain detection boosts protein annotations. At an estimated False Discovery Rate of 5%, it revealed 901 and 1098 new domains in Plasmodium and Leishmania proteins, respectively. Manual inspection of part of these predictions shows that it contains several domain families that were missing in the two organisms. All new domain occurrences have been integrated in the EuPathDomains database, along with the GO annotations that can be deduced.
Distinct Gene Number-Genome Size Relationships for Eukaryotes and Non-Eukaryotes: Gene Content Estimation for Dinoflagellate Genomes  [PDF]
Yubo Hou, Senjie Lin
PLOS ONE , 2009, DOI: 10.1371/journal.pone.0006978
Abstract: The ability to predict gene content is highly desirable for characterization of not-yet sequenced genomes like those of dinoflagellates. Using data from completely sequenced and annotated genomes from phylogenetically diverse lineages, we investigated the relationship between gene content and genome size using regression analyses. Distinct relationships between log10-transformed protein-coding gene number (Y′) versus log10-transformed genome size (X′, genome size in kbp) were found for eukaryotes and non-eukaryotes. Eukaryotes best fit a logarithmic model, Y′ = ln(-46.200+22.678X′, whereas non-eukaryotes a linear model, Y′ = 0.045+0.977X′, both with high significance (p<0.001, R2>0.91). Total gene number shows similar trends in both groups to their respective protein coding regressions. The distinct correlations reflect lower and decreasing gene-coding percentages as genome size increases in eukaryotes (82%–1%) compared to higher and relatively stable percentages in prokaryotes and viruses (97%–47%). The eukaryotic regression models project that the smallest dinoflagellate genome (3×106 kbp) contains 38,188 protein-coding (40,086 total) genes and the largest (245×106 kbp) 87,688 protein-coding (92,013 total) genes, corresponding to 1.8% and 0.05% gene-coding percentages. These estimates do not likely represent extraordinarily high functional diversity of the encoded proteome but rather highly redundant genomes as evidenced by high gene copy numbers documented for various dinoflagellate species.
Massive expansion of the calpain gene family in unicellular eukaryotes  [cached]
Zhao Sen,Liang Zhe,Demko Viktor,Wilson Robert
BMC Evolutionary Biology , 2012, DOI: 10.1186/1471-2148-12-193
Abstract: Background Calpains are Ca2+-dependent cysteine proteases that participate in a range of crucial cellular processes. Dysfunction of these enzymes may cause, for instance, life-threatening diseases in humans, the loss of sex determination in nematodes and embryo lethality in plants. Although the calpain family is well characterized in animal and plant model organisms, there is a great lack of knowledge about these genes in unicellular eukaryote species (i.e. protists). Here, we study the distribution and evolution of calpain genes in a wide range of eukaryote genomes from major branches in the tree of life. Results Our investigations reveal 24 types of protein domains that are combined with the calpain-specific catalytic domain CysPc. In total we identify 41 different calpain domain architectures, 28 of these domain combinations have not been previously described. Based on our phylogenetic inferences, we propose that at least four calpain variants were established in the early evolution of eukaryotes, most likely before the radiation of all the major supergroups of eukaryotes. Many domains associated with eukaryotic calpain genes can be found among eubacteria or archaebacteria but never in combination with the CysPc domain. Conclusions The analyses presented here show that ancient modules present in prokaryotes, and a few de novo eukaryote domains, have been assembled into many novel domain combinations along the evolutionary history of eukaryotes. Some of the new calpain genes show a narrow distribution in a few branches in the tree of life, likely representing lineage-specific innovations. Hence, the functionally important classical calpain genes found among humans and vertebrates make up only a tiny fraction of the calpain family. In fact, a massive expansion of the calpain family occurred by domain shuffling among unicellular eukaryotes and contributed to a wealth of functionally different genes.
Analysis of Gene Order Conservation in Eukaryotes Identifies Transcriptionally and Functionally Linked Genes  [PDF]
Marcela Dávila López,Juan José Martínez Guerra,Tore Samuelsson
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0010654
Abstract: The order of genes in eukaryotes is not entirely random. Studies of gene order conservation are important to understand genome evolution and to reveal mechanisms why certain neighboring genes are more difficult to separate during evolution. Here, genome-wide gene order information was compiled for 64 species, representing a wide variety of eukaryotic phyla. This information is presented in a browser where gene order may be displayed and compared between species. Factors related to non-random gene order in eukaryotes were examined by considering pairs of neighboring genes. The evolutionary conservation of gene pairs was studied with respect to relative transcriptional direction, intergenic distance and functional relationship as inferred by gene ontology. The results show that among gene pairs that are conserved the divergently and co-directionally transcribed genes are much more common than those that are convergently transcribed. Furthermore, highly conserved pairs, in particular those of fungi, are characterized by a short intergenic distance. Finally, gene pairs of metazoa and fungi that are evolutionary conserved and that are divergently transcribed are much more likely to be related by function as compared to poorly conserved gene pairs. One example is the ribosomal protein gene pair L13/S16, which is unusual as it occurs both in fungi and alveolates. A specific functional relationship between these two proteins is also suggested by the fact that they are part of the same operon in both eubacteria and archaea. In conclusion, factors associated with non-random gene order in eukaryotes include relative gene orientation, intergenic distance and functional relationships. It seems likely that certain pairs of genes are conserved because the genes involved have a transcriptional and/or functional relationship. The results also indicate that studies of gene order conservation aid in identifying genes that are related in terms of transcriptional control.
The metastate approach to thermodynamic chaos  [PDF]
C. M. Newman,D. L. Stein
Physics , 1996, DOI: 10.1103/PhysRevE.55.5194
Abstract: In realistic disordered systems, such as the Edwards-Anderson (EA) spin glass, no order parameter, such as the Parisi overlap distribution, can be both translation-invariant and non-self-averaging. The standard mean-field picture of the EA spin glass phase can therefore not be valid in any dimension and at any temperature. Further analysis shows that, in general, when systems have many competing (pure) thermodynamic states, a single state which is a mixture of many of them (as in the standard mean-field picture) contains insufficient information to reveal the full thermodynamic structure. We propose a different approach, in which an appropriate thermodynamic description of such a system is instead based on a metastate, which is an ensemble of (possibly mixed) thermodynamic states. This approach, modelled on chaotic dynamical systems, is needed when chaotic size dependence (of finite volume correlations) is present. Here replicas arise in a natural way, when a metastate is specified by its (meta)correlations. The metastate approach explains, connects, and unifies such concepts as replica symmetry breaking, chaotic size dependence and replica non-independence. Furthermore, it replaces the older idea of non-self-averaging as dependence on the bulk couplings with the concept of dependence on the state within the metastate at fixed coupling realization. We use these ideas to classify possible metastates for the EA model, and discuss two scenarios introduced by us earlier --- a nonstandard mean-field picture and a picture intermediate between that and the usual scaling/droplet picture.
Rapid gene-based SNP and haplotype marker development in non-model eukaryotes using 3'UTR sequencing
Tyson Koepke, Scott Schaeffer, Vandhana Krishnan, Derick Jiwan, Artemus Harper, Matthew Whiting, Nnadozie Oraguzie, Amit Dhingra
BMC Genomics , 2012, DOI: 10.1186/1471-2164-13-18
Abstract: RNA-seq was performed on two sweet cherry cultivars, Bing and Rainier using a 3' untranslated region (UTR) sequencing method yielding 43,396 assembled contigs. In order to test our approach of rapid identification of SNPs without any reference genome information, over 25% (10,100) of the contigs were screened for the SNPs. A total of 207 contigs from this set were identified to contain high quality SNPs. A set of 223 primer pairs were designed to amplify SNP containing regions from these contigs and high resolution melting (HRM) analysis was performed with eight important parental sweet cherry cultivars. Six of the parent cultivars were distantly related to Bing and Rainier, the cultivars used for initial SNP discovery. Further, HRM analysis was also performed on 13 seedlings derived from a cross between two of the parents. Our analysis resulted in the identification of 84 (38.7%) primer sets that demonstrated variation among the tested germplasm. Reassembly of the raw 3'UTR sequences using upgraded transcriptome assembly software yielded 34,620 contigs containing 2243 putative SNPs in 887 contigs after stringent filtering. Contigs with multiple SNPs were visually parsed to identify 685 putative haplotypes at 335 loci in 301 contigs.This approach, which leverages the advantages of RNA-seq approaches, enabled rapid generation of gene-linked SNP and haplotype markers. The general approach presented in this study can be easily applied to other non-model eukaryotes irrespective of the ploidy level to identify gene-linked polymorphisms that are expected to facilitate efficient Gene Assisted Breeding (GAB), genotyping and population genetics studies. The identified SNP haplotypes reveal some of the allelic differences in the two sweet cherry cultivars analyzed. The identification of these SNP and haplotype markers is expected to significantly improve the genomic resources for sweet cherry and facilitate efficient GAB in this non-model crop.Sweet cherry (Prunus avium L.),
Gene flow and biological conflict systems in the origin and evolution of eukaryotes  [PDF]
L. Aravind
Frontiers in Cellular and Infection Microbiology , 2012, DOI: 10.3389/fcimb.2012.00089
Abstract: The endosymbiotic origin of eukaryotes brought together two disparate genomes in the cell. Additionally, eukaryotic natural history has included other endosymbiotic events, phagotrophic consumption of organisms, and intimate interactions with viruses and endoparasites. These phenomena facilitated large-scale lateral gene transfer and biological conflicts. We synthesize information from nearly two decades of genomics to illustrate how the interplay between lateral gene transfer and biological conflicts has impacted the emergence of new adaptations in eukaryotes. Using apicomplexans as example, we illustrate how lateral transfer from animals has contributed to unique parasite-host interfaces comprised of adhesion- and O-linked glycosylation-related domains. Adaptations, emerging due to intense selection for diversity in the molecular participants in organismal and genomic conflicts, being dispersed by lateral transfer, were subsequently exapted for eukaryote-specific innovations. We illustrate this using examples relating to eukaryotic chromatin, RNAi and RNA-processing systems, signaling pathways, apoptosis and immunity. We highlight the major contributions from catalytic domains of bacterial toxin systems to the origin of signaling enzymes (e.g., ADP-ribosylation and small molecule messenger synthesis), mutagenic enzymes for immune receptor diversification and RNA-processing. Similarly, we discuss contributions of bacterial antibiotic/siderophore synthesis systems and intra-genomic and intra-cellular selfish elements (e.g., restriction-modification, mobile elements and lysogenic phages) in the emergence of chromatin remodeling/modifying enzymes and RNA-based regulation. We develop the concept that biological conflict systems served as evolutionary “nurseries” for innovations in the protein world, which were delivered to eukaryotes via lateral gene flow to spur key evolutionary innovations all the way from nucleogenesis to lineage-specific adaptations.
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