Protein dispensability and rate of evolution

Re-examining Correlations Between Synonymous Codon Usage and Protein Bond Angles in Escherichia coli

Rosenberg AA, Marx A, Bronstein AM (Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon. Nat Commun. 2022:13:2815) recently found a surprising correlation between synonymous codon usage and the dihedral bond angles of the resulting amino acid. However, their analysis did not account for the strongest known correlate of codon usage: gene expression. We re-examined the relationship between bond angles and codon usage by applying the approach of Rosenberg et al. to simulated protein-coding sequences that (i) have random codon usage, (ii) codon usage determined by mutation biases, and (iii) maintain the general relationship between codon usage and gene expression via the assumption of selection-mutation-drift equilibrium. We observed correlations between dihedral bond angle and codon usage when codon usage is entirely random, indicating possible conflation of noise with differences in bond angle distributions between synonymous codons. More relevant to the general analysis of codon usage patterns, we found surprisingly good agreement between the analysis of the real sequences and the analysis of sequences simulated assuming selection-mutation-drift equilibrium, with 91% of significant synonymous codon pairs detected in the former were also detected in the latter. We believe the correlation between codon usage and dihedral bond angles resulted from the variation in codon usage across genes due to the interplay between mutation bias, natural selection for translation efficiency, and gene expression, further underscoring these factors must be controlled for when looking for novel patterns related to codon usage.

RFEM: A framework for essential microRNA identification in mice based on rotation forest and multiple feature fusion

With the increasing number of microRNAs (miRNAs), identifying essential miRNAs has become an important task that needs to be solved urgently. However, there are few computational methods for essential miRNA identification. Here, we proposed a novel framework called Rotation Forest for Essential MicroRNA identification (RFEM) to predict the essentiality of miRNAs in mice. We first constructed 1,264 miRNA features of all miRNA samples by fusing 38 miRNA features obtained from the PESM paper and 1,226 miRNA functional features calculated based on miRNA-target gene interactions. Then, we employed 182 training samples with 1,264 features to train the rotation forest model, which was applied to compute the essentiality scores of the candidate samples. The main innovations of RFEM were as follows: 1) miRNA functional features were introduced to enrich the diversity of miRNA features; 2) the rotation forest model used decision tree as the base classifier and could increase the difference among base classifiers through feature transformation to achieve better ensemble results. Experimental results show that RFEM significantly outperformed two previous models with the AUC (AUPR) of 0.942 (0.944) in three comparison experiments under 5-fold cross validation, which proved the model's reliable performance. Moreover, ablation study was further conducted to demonstrate the effectiveness of the novel miRNA functional features. Additionally, in the case studies of assessing the essentiality of unlabeled miRNAs, experimental literature confirmed that 7 of the top 10 predicted miRNAs have crucial biological functions in mice. Therefore, RFEM would be a reliable tool for identifying essential miRNAs.

Mitogenomic Characterization and Phylogenetic Placement of African Hind, Cephalopholis taeniops: Shedding Light on the Evolution of Groupers (Serranidae: Epinephelinae)

The global exploration of evolutionary trends in groupers, based on mitogenomes, is currently underway. This research extensively investigates the structure of and variations in Cephalopholis species mitogenomes, along with their phylogenetic relationships, focusing specifically on Cephalopholis taeniops from the Eastern Atlantic Ocean. The generated mitogenome spans 16,572 base pairs and exhibits a gene order analogous to that of the ancestral teleost's, featuring 13 protein-coding genes (PCGs), two ribosomal RNA genes (rRNAs), 22 transfer RNA genes (tRNAs), and an AT-rich control region. The mitogenome of C. taeniops displays an AT bias (54.99%), aligning with related species. The majority of PCGs in the mitogenome initiate with the start codon ATG, with the exceptions being COI (GTG) and atp6 (TTG). The relative synonymous codon usage analysis revealed the maximum abundance of leucine, proline, serine, and threonine. The nonsynonymous/synonymous ratios were <1, which indicates a strong negative selection among all PCGs of the Cephalopholis species. In C. taeniops, the prevalent transfer RNAs display conventional cloverleaf secondary structures, except for tRNA-serine (GCT), which lacks a dihydrouracil (DHU) stem. A comparative examination of conserved domains and sequence blocks across various Cephalopholis species indicates noteworthy variations in length and nucleotide diversity. Maximum likelihood, neighbor-joining, and Bayesian phylogenetic analyses, employing the concatenated PCGs and a combination of PCGs + rRNAs, distinctly separate all Cephalopholis species, including C. taeniops. Overall, these findings deepen our understanding of evolutionary relationships among serranid groupers, emphasizing the significance of structural considerations in mitogenomic analyses.

Resolving network clusters disparity based on dissimilarity measurements with nonmetric analysis of variance

Classic ANOVA (cA) tests the explanatory power of a partitioning on a set of objects. More fit for clusters proximity analysis, nonparametric ANOVA (npA) extends to a case where instead of the object values themselves, their mutual distances are available. However, extending the cA applicability, the metric conditions in npA are limiting. Based on the central limit theorem (CLT), here we introduce nonmetric ANOVA (nmA) that by relaxing the metric properties between objects, allows an ANOVA-like statistical testing of a network clusters disparity. We present a parametric test statistic which under the null hypothesis of no differences between the competing clusters means, follows an exact F-distribution. We apply our method on three diverse biological examples, discuss its parallel performance, and note the specific use of each method tailored by the inherent data properties. The R code is provided at github.com/AmiryousefiLab/nmANOVA.

Balanophora genomes display massively convergent evolution with other extreme holoparasites and provide novel insights into parasite-host interactions

Parasitic plants have evolved to be subtly or severely dependent on host plants to complete their life cycle. To provide new insights into the biology of parasitic plants in general, we assembled genomes for members of the sandalwood order Santalales, including a stem hemiparasite (Scurrula) and two highly modified root holoparasites (Balanophora) that possess chimaeric host-parasite tubers. Comprehensive genome comparisons reveal that hemiparasitic Scurrula has experienced a relatively minor degree of gene loss compared with autotrophic plants, consistent with its moderate degree of parasitism. Nonetheless, patterns of gene loss appear to be substantially divergent across distantly related lineages of hemiparasites. In contrast, Balanophora has experienced substantial gene loss for the same sets of genes as an independently evolved holoparasite lineage, the endoparasitic Sapria (Malpighiales), and the two holoparasite lineages experienced convergent contraction of large gene families through loss of paralogues. This unprecedented convergence supports the idea that despite their extreme and strikingly divergent life histories and morphology, the evolution of these and other holoparasitic lineages can be shaped by highly predictable modes of genome reduction. We observe substantial evidence of relaxed selection in retained genes for both hemi- and holoparasitic species. Transcriptome data also document unusual and novel interactions between Balanophora and host plants at the host-parasite tuber interface tissues, with evidence of mRNA exchange, substantial and active hormone exchange and immune responses in parasite and host.

Predicting the effect of mutations to investigate recent events of selection across 60,472 Escherichia coli strains

Microbial genomics studies focusing on the dynamics of selection have often used a small number of distant genomes. As a result, they could only analyze mutations that had become fixed during the divergence between species. However, thousands of genomes of some species are now available in public databases, thanks to high-throughput sequencing. These data provide a more complete picture of the polymorphisms segregating within a species, offering a unique insight into the processes that shape the recent evolution of a species. In this study, we present GLASS (Gene-Level Amino-acid Score Shift), a selection test that is based on the predicted effects of amino acid changes. By comparing the distribution of effects of mutations observed in a gene to the expectation in the absence of selection, GLASS can quantify the intensity of selection. We applied GLASS to a dataset of 60,472 Escherichia coli strains and used this to reexamine the longstanding debate about the role of essentiality versus expression level in the rate of protein evolution. We found that selection has contrasting short-term and long-term dynamics, with essential genes being subject to strong purifying selection in the short term, while expression level determines the rate of gene evolution in the long term. GLASS also found an overrepresentation of inactivating mutations in specific transcription factors, such as efflux pump repressors, which is consistent with selection for antibiotic resistance. These gene-inactivating polymorphisms do not reach fixation, suggesting another contrast between short-term fitness gains and long-term counterselection.

The impact of local genomic properties on the evolutionary fate of genes

Functionally indispensable genes are likely to be retained and otherwise to be lost during evolution. This evolutionary fate of a gene can also be affected by factors independent of gene dispensability, including the mutability of genomic positions, but such features have not been examined well. To uncover the genomic features associated with gene loss, we investigated the characteristics of genomic regions where genes have been independently lost in multiple lineages. With a comprehensive scan of gene phylogenies of vertebrates with a careful inspection of evolutionary gene losses, we identified 813 human genes whose orthologs were lost in multiple mammalian lineages: designated 'elusive genes.' These elusive genes were located in genomic regions with rapid nucleotide substitution, high GC content, and high gene density. A comparison of the orthologous regions of such elusive genes across vertebrates revealed that these features had been established before the radiation of the extant vertebrates approximately 500 million years ago. The association of human elusive genes with transcriptomic and epigenomic characteristics illuminated that the genomic regions containing such genes were subject to repressive transcriptional regulation. Thus, the heterogeneous genomic features driving gene fates toward loss have been in place and may sometimes have relaxed the functional indispensability of such genes. This study sheds light on the complex interplay between gene function and local genomic properties in shaping gene evolution that has persisted since the vertebrate ancestor.

Complexity and self-organization in the evolution of cell polarization

Cellular life exhibits order and complexity, which typically increase over the course of evolution. Cell polarization is a well-studied example of an ordering process that breaks the internal symmetry of a cell by establishing a preferential axis. Like many cellular processes, polarization is driven by self-organization, meaning that the macroscopic pattern emerges as a consequence of microscopic molecular interactions at the biophysical level. However, the role of self-organization in the evolution of complex protein networks remains obscure. In this Review, we provide an overview of the evolution of polarization as a self-organizing process, focusing on the model species Saccharomyces cerevisiae and its fungal relatives. Moreover, we use this model system to discuss how self-organization might relate to evolutionary change, offering a shift in perspective on evolution at the microscopic scale.

Complete genome sequence of the Pogostemon cablin bacterial wilt pathogen Ralstonia solanacearum strain SY1

BACKGROUND

Ralstonia solanacearum causes bacterial wilt of Pogostemon cablin which is an important aromatic herb and also the main materials of COVID-19 therapeutic traditional drugs. However, we are lacking the information on the genomic sequences of R. solanacearum isolated from P. cablin.

OBJECTIVE

The acquisition and analysis of this whole-genome sequence of the P. cablin bacterial wilt pathogen.

METHODS

An R. solanacearum strain, named SY1, was isolated from infected P. cablin plants, and the complete genome sequence was sequenced and analyzed.

RESULTS

The SY1 strain contains a 3.70-Mb chromosome and a 2.18-Mb megaplasmid, with GC contents of 67.57% and 67.41%, respectively. A total of 3308 predicted genes were located on the chromosome and 1657 genes were located in the megaplasmid. SY1 strain has 273 unique genes compared with five representative R. solanacearum strains, and these genes were enriched in the plant-pathogen interaction pathway. SY1 possessed a higher syntenic relationship with phylotype I strains, and the arsenal of type III effectors predicted in SY1 were also more closely related to those of phylotype I strains. SY1 contained 14 and 5 genomic islands in its chromosome and megaplasmid, respectively, and two prophage sequences in its chromosome. In addition, 215 and 130 genes were annotated as carbohydrate-active enzymes and antibiotic resistance genes, respectively.

CONCLUSION

This is the first genome-scale assembly and annotation for R. solanacearum which isolated from infected P. cablin plants. The arsenal of virulence and antibiotic resistance may as the determinants in SY1 for infection of P. cablin plants.

Defect-buffering cellular plasticity increases robustness of metazoan embryogenesis

Developmental processes are intrinsically robust so as to preserve a normal-like state in response to genetic and environmental fluctuations. However, the robustness and potential phenotypic plasticity of individual developing cells under genetic perturbations remain to be systematically evaluated. Using large-scale gene perturbation, live imaging, lineage tracing, and single-cell phenomics, we quantified the phenotypic landscape of C. elegans embryogenesis in >2,000 embryos following individual knockdown of over 750 conserved genes. We observed that cellular genetic systems are not sufficiently robust to single-gene perturbations across all cells; rather, gene knockdowns frequently induced cellular defects. Dynamic phenotypic analyses revealed many cellular defects to be transient, with cells exhibiting phenotypic plasticity that serves to alleviate, correct, and accommodate the defects. Moreover, potential developmentally related cell modules may buffer the phenotypic effects of individual cell position changes. Our findings reveal non-negligible contributions of cellular plasticity and multicellularity as compensatory strategies to increase developmental robustness.

High quality genome annotation and expression visualisation of a mupirocin-producing bacterium

Pseudomonas strain NCIMB10586, in the P. fluorescens subgroup, produces the polyketide antibiotic mupirocin, and has potential as a host for industrial production of a range of valuable products. To underpin further studies on its genetics and physiology, we have used a combination of standard and atypical approaches to achieve a quality of the genome sequence and annotation, above current standards for automated pathways. Assembly of Illumina reads to a PacBio genome sequence created a retrospectively hybrid assembly, identifying and fixing 415 sequencing errors which would otherwise affect almost 5% of annotated coding regions. Our annotation pipeline combined automation based on related well-annotated genomes and stringent, partially manual, tests for functional features. The strain was close to P. synxantha and P. libaniensis and was found to be highly similar to a strain being developed as a weed-pest control agent in Canada. Since mupirocin is a secondary metabolite whose production is switched on late in exponential phase, we carried out RNAseq analysis over an 18 h growth period and have developed a method to normalise RNAseq samples as a group, rather than pair-wise. To review such data we have developed an easily interpreted way to present the expression profiles across a region, or the whole genome at a glance. At the 2-hour granularity of our time-course, the mupirocin cluster increases in expression as an essentially uniform bloc, although the mupirocin resistance gene stands out as being expressed at all the time points.

Are transient protein-protein interactions more dispensable?

Protein-protein interactions (PPIs) are key drivers of cell function and evolution. While it is widely assumed that most permanent PPIs are important for cellular function, it remains unclear whether transient PPIs are equally important. Here, we estimate and compare dispensable content among transient PPIs and permanent PPIs in human. Starting with a human reference interactome mapped by experiments, we construct a human structural interactome by building three-dimensional structural models for PPIs, and then distinguish transient PPIs from permanent PPIs using several structural and biophysical properties. We map common mutations from healthy individuals and disease-causing mutations onto the structural interactome, and perform structure-based calculations of the probabilities for common mutations (assumed to be neutral) and disease mutations (assumed to be mildly deleterious) to disrupt transient PPIs and permanent PPIs. Using Bayes' theorem we estimate that a similarly small fraction (<~20%) of both transient and permanent PPIs are completely dispensable, i.e., effectively neutral upon disruption. Hence, transient and permanent interactions are subject to similarly strong selective constraints in the human interactome.

Complete Genome Sequence Analysis of Ralstonia solanacearum Strain PeaFJ1 Provides Insights Into Its Strong Virulence in Peanut Plants

The bacterial wilt of peanut (Arachis hypogaea L.) caused by Ralstonia solanacearum is a devastating soil-borne disease that seriously restricted the world peanut production. However, the molecular mechanism of R. solanacearum–peanut interaction remains largely unknown. We found that R. solanacearum HA4-1 and PeaFJ1 isolated from peanut plants showed different pathogenicity by inoculating more than 110 cultivated peanuts. Phylogenetic tree analysis demonstrated that HA4-1 and PeaFJ1 both belonged to phylotype I and sequevar 14M, which indicates a high degree of genomic homology between them. Genomic sequencing and comparative genomic analysis of PeaFJ1 revealed 153 strain-specific genes compared with HA4-1. The PeaFJ1 strain-specific genes consisted of diverse virulence-related genes including LysR-type transcriptional regulators, two-component system-related genes, and genes contributing to motility and adhesion. In addition, the repertoire of the type III effectors of PeaFJ1 was bioinformatically compared with that of HA4-1 to find the candidate effectors responsible for their different virulences. There are 79 effectors in the PeaFJ1 genome, only 4 of which are different effectors compared with HA4-1, including RipS4, RipBB, RipBS, and RS_T3E_Hyp6. Based on the virulence profiles of the two strains against peanuts, we speculated that RipS4 and RipBB are candidate virulence effectors in PeaFJ1 while RipBS and RS_T3E_Hyp6 are avirulence effectors in HA4-1. In general, our research greatly reduced the scope of virulence-related genes and made it easier to find out the candidates that caused the difference in pathogenicity between the two strains. These results will help to reveal the molecular mechanism of peanut–R. solanacearum interaction and develop targeted control strategies in the future.

Complete genome sequence of the kiwifruit bacterial canker pathogen Pseudomonas savastanoi strain MHT1

Background

Pseudomonas savastanoi is an important plant pathogen that infects and causes symptoms in a variety of economically important crops, causing considerable loss of yield and quality. Because there has been no research reported to date on bacterial canker of kiwifruit (Actinidia chinensis) plants caused by P. savastanoi and, in particular, no in-depth studies of the complete genome sequence or pathogenic mechanism, long-lasting and environmentally friendly control measures against this pathogen in kiwifruit are lacking. This study therefore has both theoretical value and practical significance.

Results

We report the complete genome sequence of P. savastanoi strain MHT1, which was first reported as the pathogen causing bacterial canker in kiwifruit plants. The genome consists of a 6.00-Mb chromosome with 58.5% GC content and 5008 predicted genes. Comparative genome analysis of four sequenced genomes of representative P. savastanoi strains revealed that 230 genes are unique to the MHT1 strain and that these genes are enriched in antibiotic metabolic processes and metabolic pathways, which may be associated with the drug resistance and host range observed in this strain. MHT1 showed high syntenic relationships with different P. savastanoi strains. Furthermore, MHT1 has eight conserved effectors that are highly homologous to effectors from P. syringae, Pseudomonas amygdali, and Ralstonia solanacearum strains. The MHT1 genome contains six genomic islands and two prophage sequences. In addition, 380 genes were annotated as antibiotic resistance genes and another 734 as encoding carbohydrate-active enzymes.

Conclusion

The whole-genome sequence of this kiwifruit bacterial canker pathogen extends our knowledge of the P. savastanoi genome, sets the stage for further studies of the interaction between kiwifruit and P. savastanoi, and provides an important theoretical foundation for the prevention and control of bacterial canker.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-022-02459-4.

Complete mitogenome of the endangered and endemic Nicobar treeshrew (Tupaia nicobarica) and comparison with other Scandentians

The Nicobar treeshrew (Tupaia nicobarica) is an endangered small mammal endemic to the Nicobar Island of the Andaman Sea, India regarded as an alternative experimental animal model in biomedical research. The present study aimed to assemble the first mitochondrial genome of T. nicobarica to elucidate its phylogenetic position with respect to other Scandentians. The structure and variation of the novel mitochondrial genome were analyzed and compared with other Scandentians. The complete mitogenome (17,164 bp) encodes 37 genes, including 13 protein-coding genes (PCGs), 22 transfer RNA (tRNAs), two ribosomal RNA (rRNAs), and one control region (CR). Most of the genes were encoded on majority strand, except nad6 and eight tRNAs. The nonsynonymous/synonymous ratio in all PCGs indicates strong negative selection among all Tupaiidae species. The comparative study of CRs revealed the occurrence of tandem repeats (CGTACA) found in T. nicobarica. The phylogenetic analyses (Maximum Likelihood and Bayesian Inference) showed distinct clustering of T. nicobarica with high branch supports and depict a substantial divergence time (12–19 MYA) from the ancestor lineage of Tupaiidae. The 16S rRNA dataset corroborates the taxonomic rank of two subspecies of T. nicobarica from the Great and Little Nicobar Islands. In the future, whole nuclear genome sequencing is necessary to further improve our understanding of evolutionary relationships among treeshrews, and will have implications for biomedical research.

Evolutionary mode for the functional preservation of fast-evolving Drosophila telomere capping proteins

DNA end protection is fundamental for the long-term preservation of the genome. In vertebrates the Shelterin protein complex protects telomeric DNA ends, thereby contributing to the maintenance of genome integrity. In the Drosophila genus, this function is thought to be performed by the Terminin complex, an assembly of fast-evolving subunits. Considering that DNA end protection is fundamental for successful genome replication, the accelerated evolution of Terminin subunits is counterintuitive, as conservation is supposed to maintain the assembly and concerted function of the interacting partners. This problem extends over Drosophila telomere biology and provides insight into the evolution of protein assemblies. In order to learn more about the mechanistic details of this phenomenon we have investigated the intra- and interspecies assemblies of Verrocchio and Modigliani, two Terminin subunits using in vitro assays. Based on our results and on homology-based three-dimensional models for Ver and Moi, we conclude that both proteins contain Ob-fold and contribute to the ssDNA binding of the Terminin complex. We propose that the preservation of Ver function is achieved by conservation of specific amino acids responsible for folding or localized in interacting surfaces. We also provide here the first evidence on Moi DNA binding.

Harnessing model organism genomics to underpin the machine learning-based prediction of essential genes in eukaryotes - Biotechnological implications

The availability of high-quality genomes and advances in functional genomics have enabled large-scale studies of essential genes in model eukaryotes, including the 'elegant worm' (Caenorhabditis elegans; Nematoda) and the 'vinegar fly' (Drosophila melanogaster; Arthropoda). However, this is not the case for other, much less-studied organisms, such as socioeconomically important parasites, for which functional genomic platforms usually do not exist. Thus, there is a need to develop innovative techniques or approaches for the prediction, identification and investigation of essential genes. A key approach that could enable the prediction of such genes is machine learning (ML). Here, we undertake an historical review of experimental and computational approaches employed for the characterisation of essential genes in eukaryotes, with a particular focus on model ecdysozoans (C. elegans and D. melanogaster), and discuss the possible applicability of ML-approaches to organisms such as socioeconomically important parasites. We highlight some recent results showing that high-performance ML, combined with feature engineering, allows a reliable prediction of essential genes from extensive, publicly available 'omic data sets, with major potential to prioritise such genes (with statistical confidence) for subsequent functional genomic validation. These findings could 'open the door' to fundamental and applied research areas. Evidence of some commonality in the essential gene-complement between these two organisms indicates that an ML-engineering approach could find broader applicability to ecdysozoans such as parasitic nematodes or arthropods, provided that suitably large and informative data sets become/are available for proper feature engineering, and for the robust training and validation of algorithms. This area warrants detailed exploration to, for example, facilitate the identification and characterisation of essential molecules as novel targets for drugs and vaccines against parasitic diseases. This focus is particularly important, given the substantial impact that such diseases have worldwide, and the current challenges associated with their prevention and control and with drug resistance in parasite populations.

Comparative Genomics of Eight Fusarium graminearum Strains with Contrasting Aggressiveness Reveals an Expanded Open Pangenome and Extended Effector Content Signatures

Fusarium graminearum, the primary cause of Fusarium head blight (FHB) in small-grain cereals, demonstrates remarkably variable levels of aggressiveness in its host, producing different infection dynamics and contrasted symptom severity. While the secreted proteins, including effectors, are thought to be one of the essential components of aggressiveness, our knowledge of the intra-species genomic diversity of F. graminearum is still limited. In this work, we sequenced eight European F. graminearum strains of contrasting aggressiveness to characterize their respective genome structure, their gene content and to delineate their specificities. By combining the available sequences of 12 other F. graminearum strains, we outlined a reference pangenome that expands the repertoire of the known genes in the reference PH-1 genome by 32%, including nearly 21,000 non-redundant sequences and gathering a common base of 9250 conserved core-genes. More than 1000 genes with high non-synonymous mutation rates may be under diverse selection, especially regarding the trichothecene biosynthesis gene cluster. About 900 secreted protein clusters (SPCs) have been described. Mostly localized in the fast sub-genome of F. graminearum supposed to evolve rapidly to promote adaptation and rapid responses to the host's infection, these SPCs gather a range of putative proteinaceous effectors systematically found in the core secretome, with the chloroplast and the plant nucleus as the main predicted targets in the host cell. This work describes new knowledge on the intra-species diversity in F. graminearum and emphasizes putative determinants of aggressiveness, providing a wealth of new candidate genes potentially involved in the Fusarium head blight disease.

Improve it or lose it: Evolvability cost of competition for expression

Expression level is known to be a strong determinant of a protein's rate of evolution. But the converse can also be true: evolutionary dynamics can affect expression levels of proteins. Having implications in both directions fosters the possibility of an "improve it or lose it" feedback loop, where higher expressed systems are more likely to improve and be expressed even higher, while those that are expressed less are eventually lost to drift. Using a minimal model to study this in the context of a changing environment, we demonstrate that one unexpected consequence of such a feedback loop is that a slow switch to a new environment can allow genotypes to reach higher fitness sooner than a direct exposure to it.

Abundance Imparts Evolutionary Constraints of Similar Magnitude on the Buried, Surface, and Disordered Regions of Proteins

An understanding of the forces shaping protein conservation is key, both for the fundamental knowledge it represents and to allow for optimal use of evolutionary information in practical applications. Sequence conservation is typically examined at one of two levels. The first is a residue-level, where intra-protein differences are analyzed and the second is a protein-level, where inter-protein differences are studied. At a residue level, we know that solvent-accessibility is a prime determinant of conservation. By inverting this logic, we inferred that disordered regions are slightly more solvent-accessible on average than the most exposed surface residues in domains. By integrating abundance information with evolutionary data within and across proteins, we confirmed a previously reported strong surface-core association in the evolution of structured regions, but we found a comparatively weak association between disordered and structured regions. The facts that disordered and structured regions experience different structural constraints and evolve independently provide a unique setup to examine an outstanding question: why is a protein’s abundance the main determinant of its sequence conservation? Indeed, any structural or biophysical property linked to the abundance-conservation relationship should increase the relative conservation of regions concerned with that property (e.g., disordered residues with mis-interactions, domain residues with misfolding). Surprisingly, however, we found the conservation of disordered and structured regions to increase in equal proportion with abundance. This observation implies that either abundance-related constraints are structure-independent, or multiple constraints apply to different regions and perfectly balance each other.

Comparative genomics analysis of two banana Fusarium wilt biocontrol endophytes Bacillus subtilis R31 and TR21 provides insights into their differences on phytobeneficial trait

Fusarium wilt of banana is considered one of the most destructive plant diseases. Bacillus subtilis R31 and TR21, isolated from Dendrobium sp. leaves, exhibit different phytobeneficial effects on banana Fusarium wilt bio-controlling. Here, we performed genome sequencing and comparative genomics analysis of R31 and TR21 to enhance our understanding of the different phytobeneficial traits. These results revealed that the strain-specific genes of R31 involved in sporulation, quorum sensing, and antibiotic synthesis allow R31 to present a better capacity of sporulation, rhizosphere adaptation, and quorum sensing than TR21. Selective pressure analysis indicated that the glycosylase and endo-alpha-(1- > 5)-L-arabinanase genes were strong positive selected, which may contribute to the TR21 to colonize well in banana's vascular bundles. Altogether, our findings presented here should advance further agricultural application of R31 and TR21 as two promising resources of plant growth promotion and biological control via genetic engineering.

The Relationship between the Misfolding Avoidance Hypothesis and Protein Evolutionary Rates in the Light of Empirical Evidence

For more than a decade, the misfolding avoidance hypothesis (MAH) and related theories have dominated evolutionary discussions aimed at explaining the variance of the molecular clock across cellular proteins. In this study, we use various experimental data to further investigate the consistency of the MAH predictions with empirical evidence. We also critically discuss experimental results that motivated the MAH development and that are often viewed as evidence of its major contribution to the variability of protein evolutionary rates. We demonstrate, in Escherichia coli and Homo sapiens, the lack of a substantial negative correlation between protein evolutionary rates and Gibbs free energies of unfolding, a direct measure of protein stability. We then analyze multiple new genome-scale data sets characterizing protein aggregation and interaction propensities, the properties that are likely optimized in evolution to alleviate deleterious effects associated with toxic protein misfolding and misinteractions. Our results demonstrate that the propensity of proteins to aggregate, the fraction of charged amino acids, and protein stickiness do correlate with protein abundances. Nevertheless, across multiple organisms and various data sets we do not observe substantial correlations between proteins’ aggregation- and stability-related properties and evolutionary rates. Therefore, diverse empirical data support the conclusion that the MAH and similar hypotheses do not play a major role in mediating a strong negative correlation between protein expression and the molecular clock, and thus in explaining the variability of evolutionary rates across cellular proteins.

Genome plasticity in Paramecium bursaria revealed by population genomics

Background

Ciliates are an ancient and diverse eukaryotic group found in various environments. A unique feature of ciliates is their nuclear dimorphism, by which two types of nuclei, the diploid germline micronucleus (MIC) and polyploidy somatic macronucleus (MAC), are present in the same cytoplasm and serve different functions. During each sexual cycle, ciliates develop a new macronucleus in which newly fused genomes are extensively rearranged to generate functional minichromosomes. Interestingly, each ciliate species seems to have its way of processing genomes, providing a diversity of resources for studying genome plasticity and its regulation. Here, we sequenced and analyzed the macronuclear genome of different strains of Paramecium bursaria, a highly divergent species of the genus Paramecium which can stably establish endosymbioses with green algae.

Results

We assembled a high-quality macronuclear genome of P. bursaria and further refined genome annotation by comparing population genomic data. We identified several species-specific expansions in protein families and gene lineages that are potentially associated with endosymbiosis. Moreover, we observed an intensive chromosome breakage pattern that occurred during or shortly after sexual reproduction and contributed to highly variable gene dosage throughout the genome. However, patterns of copy number variation were highly correlated among genetically divergent strains, suggesting that copy number is adjusted by some regulatory mechanisms or natural selection. Further analysis showed that genes with low copy number variation among populations tended to function in basic cellular pathways, whereas highly variable genes were enriched in environmental response pathways.

Conclusions

We report programmed DNA rearrangements in the P. bursaria macronuclear genome that allow cells to adjust gene copy number globally according to individual gene functions. Our results suggest that large-scale gene copy number variation may represent an ancient mechanism for cells to adapt to different environments.

Supplementary information

The online version contains supplementary material available at 10.1186/s12915-020-00912-2.

Towards reconstructing the dipteran demise of an ancient essential gene: E3 ubiquitin ligase Murine double minute

Genome studies have uncovered many examples of essential gene loss, raising the question of how ancient genes transition from essentiality to dispensability. We explored this process for the deeply conserved E3 ubiquitin ligase Murine double minute (Mdm), which is lacking in Drosophila despite the conservation of its main regulatory target, the cellular stress response gene p53. Conducting gene expression and knockdown experiments in the red flour beetle Tribolium castaneum, we found evidence that Mdm has remained essential in insects where it is present. Using bioinformatics approaches, we confirm the absence of the Mdm gene family in Drosophila, mapping its loss to the stem lineage of schizophoran Diptera and Pipunculidae (big-headed flies), about 95-85 million years ago. Intriguingly, this gene loss event was preceded by the de novo origin of the gene Companion of reaper (Corp), a novel p53 regulatory factor that is characterized by functional similarities to vertebrate Mdm2 despite lacking E3 ubiquitin ligase protein domains. Speaking against a 1:1 compensatory gene gain/loss scenario, however, we found that hoverflies (Syrphidae) and pointed-wing flies (Lonchopteridae) possess both Mdm and Corp. This implies that the two p53 regulators have been coexisting for ~ 150 million years in select dipteran clades and for at least 50 million years in the lineage to Schizophora and Pipunculidae. Given these extensive time spans of Mdm/Corp coexistence, we speculate that the loss of Mdm in the lineage to Drosophila involved further acquisitions of compensatory gene activities besides the emergence of Corp. Combined with the previously noted reduction of an ancestral P53 contact domain in the Mdm homologs of crustaceans and insects, we conclude that the loss of the ancient Mdm gene family in flies was the outcome of incremental functional regression over long macroevolutionary time scales.

Detection, characterization and evolutionary aspects of S54LP of SP (SAP54 Like Protein of Sesame Phyllody): a phytoplasma effector molecule associated with phyllody development in sesame (Sesamum indicum L.)

SAP54, an effector protein secreted by phytoplasmas has been reported to induce phyllody. S54LP of SP (SAP54 Like Protein of Sesame Phyllody), a SAP54 ortholog from phyllody and witches' broom affected sesame (Sesamum indicum L.) was amplified, cloned and sequenced. Comparative sequence and phylogenetic analysis of diverse phytoplasma strains was carried out to delineate the evolution of S54LP of SP. The degree of polymorphism across SAP54 orthologs and the evolutionary forces acting on this effector protein were ascertained. Site-specific selection across SAP54 orthologs was estimated using Fixed Effects Likelihood (FEL) approach. Nonsynonymous substitutions were detected in the SAP54 orthologs' sequences from phytoplasmas belonging to same (sub) group. Phylogenetic analysis based on S54LP of SP grouped phytoplasmas belonging to same 16SrDNA (sub) groups into different clusters. Analysis of selection forces acting on SAP54 orthologs from nine different phytoplasma (sub)groups, affecting plant species belonging to twelve different families across ten countries showed the orthologs to be under purifying (negative) selection. One amino acid residue was found to be under pervasive diversifying (positive) selection and a total of three amino acid sites were found to be under pervasive purifying (negative) selection. The location of these amino acids in the signal peptide and mature protein was studied with an aim to understand their role in protein-protein interaction. Asparagine residues (at positions 68 and 84) were found to be under pervasive purifying selection suggesting their functional importance in the effector protein. Our study suggests lack of coevolution between SAP54 and 16SrDNA. Signal peptide appears to evolve at a rate slightly higher than the mature protein. Overall, SAP54 and its orthologs are evolving under purifying selection confirming their functional importance in phytoplasma virulence.

Whole genome sequencing and comparative genomic analysis of oleaginous red yeast Sporobolomyces pararoseus NGR identifies candidate genes for biotechnological potential and ballistospores-shooting

BACKGROUND

Sporobolomyces pararoseus is regarded as an oleaginous red yeast, which synthesizes numerous valuable compounds with wide industrial usages. This species hold biotechnological interests in biodiesel, food and cosmetics industries. Moreover, the ballistospores-shooting promotes the colonizing of S. pararoseus in most terrestrial and marine ecosystems. However, very little is known about the basic genomic features of S. pararoseus. To assess the biotechnological potential and ballistospores-shooting mechanism of S. pararoseus on genome-scale, the whole genome sequencing was performed by next-generation sequencing technology.

RESULTS

Here, we used Illumina Hiseq platform to firstly assemble S. pararoseus genome into 20.9 Mb containing 54 scaffolds and 5963 predicted genes with a N50 length of 2,038,020 bp and GC content of 47.59%. Genome completeness (BUSCO alignment: 95.4%) and RNA-seq analysis (expressed genes: 98.68%) indicated the high-quality features of the current genome. Through the annotation information of the genome, we screened many key genes involved in carotenoids, lipids, carbohydrate metabolism and signal transduction pathways. A phylogenetic assessment suggested that the evolutionary trajectory of the order Sporidiobolales species was evolved from genus Sporobolomyces to Rhodotorula through the mediator Rhodosporidiobolus. Compared to the lacking ballistospores Rhodotorula toruloides and Saccharomyces cerevisiae, we found genes enriched for spore germination and sugar metabolism. These genes might be responsible for the ballistospores-shooting in S. pararoseus NGR.

CONCLUSION

These results greatly advance our understanding of S. pararoseus NGR in biotechnological potential and ballistospores-shooting, which help further research of genetic manipulation, metabolic engineering as well as its evolutionary direction.

The evolutionary plasticity of chromosome metabolism allows adaptation to constitutive DNA replication stress

Many biological features are conserved and thus considered to be resistant to evolutionary change. While rapid genetic adaptation following the removal of conserved genes has been observed, we often lack a mechanistic understanding of how adaptation happens. We used the budding yeast, Saccharomyces cerevisiae, to investigate the evolutionary plasticity of chromosome metabolism, a network of evolutionary conserved modules. We experimentally evolved cells constitutively experiencing DNA replication stress caused by the absence of Ctf4, a protein that coordinates the enzymatic activities at replication forks. Parallel populations adapted to replication stress, over 1000 generations, by acquiring multiple, concerted mutations. These mutations altered conserved features of two chromosome metabolism modules, DNA replication and sister chromatid cohesion, and inactivated a third, the DNA damage checkpoint. The selected mutations define a functionally reproducible evolutionary trajectory. We suggest that the evolutionary plasticity of chromosome metabolism has implications for genome evolution in natural populations and cancer.

Distributed phenomics with the unPAK project reveals the effects of mutations

Determining how genes are associated with traits in plants and other organisms is a major challenge in modern biology. The unPAK project - undergraduates phenotyping Arabidopsis knockouts - has generated phenotype data for thousands of non-lethal insertion mutation lines within a single Arabidopsis thaliana genomic background. The focal phenotypes examined by unPAK are complex macroscopic fitness-related traits, which have ecological, evolutionary and agricultural importance. These phenotypes are placed in the context of the wild-type and also natural accessions (phytometers), and standardized for environmental differences between assays. Data from the unPAK project are used to describe broad patterns in the phenotypic consequences of insertion mutation, and to identify individual mutant lines with distinct phenotypes as candidates for further study. Inclusion of undergraduate researchers is at the core of unPAK activities, and an important broader impact of the project is providing students an opportunity to obtain research experience.

The first complete mitochondrial genome of the Indian Tent Turtle, Pangshura tentoria (Testudines: Geoemydidae): Characterization and comparative analysis

The characterization of a complete mitogenome is widely used in genomics studies for systematics and evolutionary research. However, the sequences and structural motifs contained within the mitogenome of Testudines taxa have rarely been examined. The present study decodes the first complete mitochondrial genome of the Indian Tent Turtle, Pangshura tentoria (16,657 bp) by using next-generation sequencing. This denovo assembly encodes 37 genes: 13 protein-coding genes (PCGs), 22 transfer RNA (tRNAs), two ribosomal RNA, and one control region (CR). Most of the genes were encoded on majority strand, except for one PCG (NADH dehydrogenase subunit 6) and eight tRNAs. Most of the PCGs were started with an ATG initiation codon, except for Cytochrome oxidase subunit 1 with "GTG" and NADH dehydrogenase subunit 5 with "ATA." The termination codons, "TAA" and "AGA" were observed in two subunits of NADH dehydrogenase gene. The relative synonymous codon usage analysis revealed the maximum abundance of alanine, isoleucine, leucine, and threonine. The nonsynonymous/synonymous ratios were <1 in all PCGs, which indicates strong negative selection among all Geoemydid species. The study also found the typical cloverleaf secondary structure in most of the tRNA genes, except for serine with the lack of the conventional DHU arm. The comparative study of Geoemydid mitogenomes revealed the occurrence of tandem repeats was frequent in the 3' end of CR. Further, two copies of a unique tandem repeat "TTCTCTTT" were identified in P. tentoria. The Bayesian and maximum-likelihood phylogenetic trees using concatenation of 13 PCGs revealed the close relationships of P. tentoria with Batagur trivittata in the studied dataset. All the Geoemydid species showed distinct clustering with high bootstrap support congruent with previous evolutionary hypotheses. We suggest that the generations of more mitogenomes of Geoemydid species are required, to improve our understanding of their in-depth phylogenetic and evolutionary relationships.

The Evolutionary Traceability of a Protein

Orthologs document the evolution of genes and metabolic capacities encoded in extant and ancient genomes. However, the similarity between orthologs decays with time, and ultimately it becomes insufficient to infer common ancestry. This leaves ancient gene set reconstructions incomplete and distorted to an unknown extent. Here we introduce the “evolutionary traceability” as a measure that quantifies, for each protein, the evolutionary distance beyond which the sensitivity of the ortholog search becomes limiting. Using yeast, we show that genes that were thought to date back to the last universal common ancestor are of high traceability. Their functions mostly involve catalysis, ion transport, and ribonucleoprotein complex assembly. In turn, the fraction of yeast genes whose traceability is not sufficient to infer their presence in last universal common ancestor is enriched for regulatory functions. Computing the traceabilities of genes that have been experimentally characterized as being essential for a self-replicating cell reveals that many of the genes that lack orthologs outside bacteria have low traceability. This leaves open whether their orthologs in the eukaryotic and archaeal domains have been overlooked. Looking at the example of REC8, a protein essential for chromosome cohesion, we demonstrate how a traceability-informed adjustment of the search sensitivity identifies hitherto missed orthologs in the fast-evolving microsporidia. Taken together, the evolutionary traceability helps to differentiate between true absence and nondetection of orthologs, and thus improves our understanding about the evolutionary conservation of functional protein networks. “protTrace,” a software tool for computing evolutionary traceability, is freely available at https://github.com/BIONF/protTrace.git; last accessed February 10, 2019.

Rapid turnover of life-cycle-related genes in the brown algae

BACKGROUND

Sexual life cycles in eukaryotes involve a cyclic alternation between haploid and diploid phases. While most animals possess a diploid life cycle, many plants and algae alternate between multicellular haploid (gametophyte) and diploid (sporophyte) generations. In many algae, gametophytes and sporophytes are independent and free-living and may present dramatic phenotypic differences. The same shared genome can therefore be subject to different, even conflicting, selection pressures during each of the life cycle generations. Here, we analyze the nature and extent of genome-wide, generation-biased gene expression in four species of brown algae with contrasting levels of dimorphism between life cycle generations.

RESULTS

We show that the proportion of the transcriptome that is generation-specific is broadly associated with the level of phenotypic dimorphism between the life cycle stages. Importantly, our data reveals a remarkably high turnover rate for life-cycle-related gene sets across the brown algae and highlights the importance not only of co-option of regulatory programs from one generation to the other but also of a role for newly emerged, lineage-specific gene expression patterns in the evolution of the gametophyte and sporophyte developmental programs in this major eukaryotic group. Moreover, we show that generation-biased genes display distinct evolutionary modes, with gametophyte-biased genes evolving rapidly at the coding sequence level whereas sporophyte-biased genes tend to exhibit changes in their patterns of expression.

CONCLUSION

Our analysis uncovers the characteristics, expression patterns, and evolution of generation-biased genes and underlines the selective forces that shape this previously underappreciated source of phenotypic diversity.

Complete mitochondrial genome of Black Soft-shell Turtle (Nilssonia nigricans) and comparative analysis with other Trionychidae

The characterization of mitochondrial genome has been evidenced as an efficient field of study for phylogenetic and evolutionary analysis in vertebrates including turtles. The aim of this study was to distinguish the structure and variability of the Trionychidae species mitogenomes through comparative analysis. The complete mitogenome (16796 bp) of an endangered freshwater turtle, Nilssonia nigricans was sequenced and annotated. The mitogenome encoded for 37 genes and a major non-coding control region (CR). The mitogenome was A + T biased (62.16%) and included six overlapping and 19 intergenic spacer regions. The Relative synonymous codon usage (RSCU) value was consistent among all the Trionychidae species; with the exception of significant reduction of Serine (TCG) frequency in N. nigricans, N. formosa, and R. swinhoei. In N. nigricans, most of the transfer RNAs (tRNAs) were folded into classic clover-leaf secondary structures with Watson-Crick base pairing except for trnS1 (GCT). The comparative analysis revealed that most of the tRNAs were structurally different, except for trnE (TTC), trnQ (TTG), and trnM (CAT). The structural features of tRNAs resulted ≥ 10 mismatched or wobble base pairings in 12 tRNAs, which reflects the nucleotide composition in both H- and L-strands. The mitogenome of N. nigricans also revealed two unique tandem repeats (ATTAT)8, and (TATTA)20 in the CR. Further, the conserved motif 5'-GACATA-3' and stable stem-loop structure was detected in the CRs of all Trionychidae species, which play an significant role in regulating transcription and replication in the mitochondrial genome. Further, the comparative analysis of Ka/Ks indicated negative selection in most of the protein coding genes (PCGs). The constructed Maximum Likelihood (ML) phylogeny using all PCGs showed clustering of N. nigricans with N. formosa. The resulting phylogeny illustrated the similar topology as described previously and consistent with the taxonomic classification. However, more sampling from different taxonomic groups of Testudines and studies on their mitogenomics are desirable for better understanding of the phylogenetic and evolutionary relationships.

Reduced intrinsic DNA curvature leads to increased mutation rate

BACKGROUND

Mutation rates vary across the genome. Many trans factors that influence mutation rates have been identified, as have specific sequence motifs at the 1-7-bp scale, but cis elements remain poorly characterized. The lack of understanding regarding why different sequences have different mutation rates hampers our ability to identify positive selection in evolution and to identify driver mutations in tumorigenesis.

RESULTS

Here, we use a combination of synthetic genes and sequences of thousands of isolated yeast colonies to show that intrinsic DNA curvature is a major cis determinant of mutation rate. Mutation rate negatively correlates with DNA curvature within genes, and a 10% decrease in curvature results in a 70% increase in mutation rate. Consistently, both yeast and humans accumulate mutations in regions with small curvature. We further show that this effect is due to differences in the intrinsic mutation rate, likely due to differences in mutagen sensitivity and not due to differences in the local activity of DNA repair.

CONCLUSIONS

Our study establishes a framework for understanding the cis properties of DNA sequence in modulating the local mutation rate and identifies a novel causal source of non-uniform mutation rates across the genome.

Integrating genetic and protein-protein interaction networks maps a functional wiring diagram of a cell

Systematic experimental approaches have led to construction of comprehensive genetic and protein-protein interaction networks for the budding yeast, Saccharomyces cerevisiae. Genetic interactions capture functional relationships between genes using phenotypic readouts, while protein-protein interactions identify physical connections between gene products. These complementary, and largely non-overlapping, networks provide a global view of the functional architecture of a cell, revealing general organizing principles, many of which appear to be evolutionarily conserved. Here, we focus on insights derived from the integration of large-scale genetic and protein-protein interaction networks, highlighting principles that apply to both unicellular and more complex systems, including human cells. Network integration reveals fundamental connections involving key functional modules of eukaryotic cells, defining a core network of cellular function, which could be elaborated to explore cell-type specificity in metazoans.

Effect of genetic drift on determinants of protein evolution

A number of previous studies reported that gene expression, tissue specificity, gene essentiality and the number of protein-protein interactions influence the rate of protein evolution. Here we investigated the influence of effective population size (N_e) on these determinants of protein evolution. For this purpose, we compared the ratio of non-synonymous-to-synonymous diversities (π_N/π_S) estimated for protein-coding genes of Mus musculus castaneus and Mus musculus musculus: populations with high and low N_e respectively. Our results revealed that the difference between π_N/π_S estimated for genes with high and low expression levels was significantly smaller for M. m. musculus compared to that observed for M. m. castaneus The difference between the π_N/π_S of broadly expressed and tissue specific genes was much higher for M. m. castaneus compared to that of M. m. musculus. Furthermore, the difference between the π_N/π_S computed for essential and non-essential genes was much smaller for M. m. musculus than M. m. castaneus A similar pattern was observed for genes involved in many protein-protein interactions versus those involved in one. These results suggest that the effects of the determinants on protein evolution were much reduced for the population with small N_e due to increased genetic drift.

Patterns of Conservation and Diversification in the Fungal Polarization Network

The combined actions of proteins in networks underlie all fundamental cellular functions. Deeper insights into the dynamics of network composition across species and their functional consequences are crucial to fully understand protein network evolution. Large-scale comparative studies with high phylogenetic resolution are now feasible through the recent rise in available genomic data sets of both model and nonmodel species. Here, we focus on the polarity network, which is universally essential for cell proliferation and studied in great detail in the model organism, Saccharomyces cerevisiae. We examine 42 proteins, directly related to cell polarization, across 298 fungal strains/species to determine the composition of the network and patterns of conservation and diversification. We observe strong protein conservation for a group of 23 core proteins: >95% of all examined strains/species possess at least 14 of these core proteins, albeit in varying compositions, and non of the individual core proteins is 100% conserved. We find high levels of variation in prevalence and sequence identity in the remaining 19 proteins, resulting in distinct lineage-specific compositions of the network in the majority of strains/species. We show that the observed diversification in network composition correlates with lineage, lifestyle, and genetic distance. Yeast, filamentous and basal unicellular fungi, form distinctive groups based on these analyses, with substantial differences to their polarization network. Our study shows that the fungal polarization network is highly dynamic, even between closely related species, and that functional conservation appears to be achieved by varying the specific components of the fungal polarization repertoire.

Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers

BACKGROUND

The development of new ortholog detection algorithms and the improvement of existing ones are of major importance in functional genomics. We have previously introduced a successful supervised pairwise ortholog classification approach implemented in a big data platform that considered several pairwise protein features and the low ortholog pair ratios found between two annotated proteomes (Galpert, D et al., BioMed Research International, 2015). The supervised models were built and tested using a Saccharomycete yeast benchmark dataset proposed by Salichos and Rokas (2011). Despite several pairwise protein features being combined in a supervised big data approach; they all, to some extent were alignment-based features and the proposed algorithms were evaluated on a unique test set. Here, we aim to evaluate the impact of alignment-free features on the performance of supervised models implemented in the Spark big data platform for pairwise ortholog detection in several related yeast proteomes.

RESULTS

The Spark Random Forest and Decision Trees with oversampling and undersampling techniques, and built with only alignment-based similarity measures or combined with several alignment-free pairwise protein features showed the highest classification performance for ortholog detection in three yeast proteome pairs. Although such supervised approaches outperformed traditional methods, there were no significant differences between the exclusive use of alignment-based similarity measures and their combination with alignment-free features, even within the twilight zone of the studied proteomes. Just when alignment-based and alignment-free features were combined in Spark Decision Trees with imbalance management, a higher success rate (98.71%) within the twilight zone could be achieved for a yeast proteome pair that underwent a whole genome duplication. The feature selection study showed that alignment-based features were top-ranked for the best classifiers while the runners-up were alignment-free features related to amino acid composition.

CONCLUSIONS

The incorporation of alignment-free features in supervised big data models did not significantly improve ortholog detection in yeast proteomes regarding the classification qualities achieved with just alignment-based similarity measures. However, the similarity of their classification performance to that of traditional ortholog detection methods encourages the evaluation of other alignment-free protein pair descriptors in future research.

Position Matters: Network Centrality Considerably Impacts Rates of Protein Evolution in the Human Protein-Protein Interaction Network

The proteins of any organism evolve at disparate rates. A long list of factors affecting rates of protein evolution have been identified. However, the relative importance of each factor in determining rates of protein evolution remains unresolved. The prevailing view is that evolutionary rates are dominantly determined by gene expression, and that other factors such as network centrality have only a marginal effect, if any. However, this view is largely based on analyses in yeasts, and accurately measuring the importance of the determinants of rates of protein evolution is complicated by the fact that the different factors are often correlated with each other, and by the relatively poor quality of available functional genomics data sets. Here, we use correlation, partial correlation and principal component regression analyses to measure the contributions of several factors to the variability of the rates of evolution of human proteins. For this purpose, we analyzed the entire human protein–protein interaction data set and the human signal transduction network—a network data set of exceptionally high quality, obtained by manual curation, which is expected to be virtually free from false positives. In contrast with the prevailing view, we observe that network centrality (measured as the number of physical and nonphysical interactions, betweenness, and closeness) has a considerable impact on rates of protein evolution. Surprisingly, the impact of centrality on rates of protein evolution seems to be comparable, or even superior according to some analyses, to that of gene expression. Our observations seem to be independent of potentially confounding factors and from the limitations (biases and errors) of interactomic data sets.

Evolutionary Proteomics Uncovers Ancient Associations of Cilia with Signaling Pathways

Cilia are organelles specialized for movement and signaling. To infer when during evolution signaling pathways became associated with cilia, we characterized the proteomes of cilia from sea urchins, sea anemones, and choanoflagellates. We identified 437 high-confidence ciliary candidate proteins conserved in mammals and discovered that Hedgehog and G-protein-coupled receptor pathways were linked to cilia before the origin of bilateria and transient receptor potential (TRP) channels before the origin of animals. We demonstrated that candidates not previously implicated in ciliary biology localized to cilia and further investigated ENKUR, a TRP channel-interacting protein identified in the cilia of all three organisms. ENKUR localizes to motile cilia and is required for patterning the left-right axis in vertebrates. Moreover, mutation of ENKUR causes situs inversus in humans. Thus, proteomic profiling of cilia from diverse eukaryotes defines a conserved ciliary proteome, reveals ancient connections to signaling, and uncovers a ciliary protein that underlies development and human disease.

The Evolution of Gene-Specific Transcriptional Noise Is Driven by Selection at the Pathway Level

Biochemical reactions within individual cells result from the interactions of molecules, typically in small numbers. Consequently, the inherent stochasticity of binding and diffusion processes generates noise along the cascade that leads to the synthesis of a protein from its encoding gene. As a result, isogenic cell populations display phenotypic variability even in homogeneous environments. The extent and consequences of this stochastic gene expression have only recently been assessed on a genome-wide scale, owing, in particular, to the advent of single-cell transcriptomics. However, the evolutionary forces shaping this stochasticity have yet to be unraveled. Here, we take advantage of two recently published data sets for the single-cell transcriptome of the domestic mouse Mus musculus to characterize the effect of natural selection on gene-specific transcriptional stochasticity. We show that noise levels in the mRNA distributions (also known as transcriptional noise) significantly correlate with three-dimensional nuclear domain organization, evolutionary constraints on the encoded protein, and gene age. However, the position of the encoded protein in a biological pathway is the main factor that explains observed levels of transcriptional noise, in agreement with models of noise propagation within gene networks. Because transcriptional noise is under widespread selection, we argue that it constitutes an important component of the phenotype and that variance of expression is a potential target of adaptation. Stochastic gene expression should therefore be considered together with the mean expression level in functional and evolutionary studies of gene expression.

A High-Resolution Genome-Wide CRISPR/Cas9 Viability Screen Reveals Structural Features and Contextual Diversity of the Human Cell-Essential Proteome

To interrogate genes essential for cell growth, proliferation and survival in human cells, we carried out a genome-wide clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 screen in a B-cell lymphoma line using a custom extended-knockout (EKO) library of 278,754 single-guide RNAs (sgRNAs) that targeted 19,084 RefSeq genes, 20,852 alternatively spliced exons, and 3,872 hypothetical genes. A new statistical analysis tool called robust analytics and normalization for knockout screens (RANKS) identified 2,280 essential genes, 234 of which were unique. Individual essential genes were validated experimentally and linked to ribosome biogenesis and stress responses. Essential genes exhibited a bimodal distribution across 10 different cell lines, consistent with a continuous variation in essentiality as a function of cell type. Genes essential in more lines had more severe fitness defects and encoded the evolutionarily conserved structural cores of protein complexes, whereas genes essential in fewer lines formed context-specific modules and encoded subunits at the periphery of essential complexes. The essentiality of individual protein residues across the proteome correlated with evolutionary conservation, structural burial, modular domains, and protein interaction interfaces. Many alternatively spliced exons in essential genes were dispensable and were enriched for disordered regions. Fitness defects were observed for 44 newly evolved hypothetical reading frames. These results illuminate the contextual nature and evolution of essential gene functions in human cells.

Systematic Analyses and Prediction of Human Drug Side Effect Associated Proteins from the Perspective of Protein Evolution

Identification of various factors involved in adverse drug reactions in target proteins to develop therapeutic drugs with minimal/no side effect is very important. In this context, we have performed a comparative evolutionary rate analyses between the genes exhibiting drug side-effect(s) (SET) and genes showing no side effect (NSET) with an aim to increase the prediction accuracy of SET/NSET proteins using evolutionary rate determinants. We found that SET proteins are more conserved than the NSET proteins. The rates of evolution between SET and NSET protein primarily depend upon their noncomplex (protein complex association number = 0) forming nature, phylogenetic age, multifunctionality, membrane localization, and transmembrane helix content irrespective of their essentiality, total druggability (total number of drugs/target), m-RNA expression level, and tissue expression breadth. We also introduced two novel terms—killer druggability (number of drugs with killing side effect(s)/target), essential druggability (number of drugs targeting essential proteins/target) to explain the evolutionary rate variation between SET and NSET proteins. Interestingly, we noticed that SET proteins are younger than NSET proteins and multifunctional younger SET proteins are candidates of acquiring killing side effects. We provide evidence that higher killer druggability, multifunctionality, and transmembrane helices support the conservation of SET proteins over NSET proteins in spite of their recent origin. By employing all these entities, our Support Vector Machine model predicts human SET/NSET proteins to a high degree of accuracy (∼86%).

Emerging and evolving concepts in gene essentiality

Gene essentiality is a founding concept of genetics with important implications in both fundamental and applied research. Multiple screens have been performed over the years in bacteria, yeasts, animals and more recently in human cells to identify essential genes. A mounting body of evidence suggests that gene essentiality, rather than being a static and binary property, is both context dependent and evolvable in all kingdoms of life. This concept of a non-absolute nature of gene essentiality changes our fundamental understanding of essential biological processes and could directly affect future treatment strategies for cancer and infectious diseases.

Genome-wide characterization and expression analyses of superoxide dismutase (SOD) genes in Gossypium hirsutum

BACKGROUND

Superoxide dismutases (SODs) are a key antioxidant enzyme family, which have been implicated in protecting plants against the toxic effects of reactive oxygen species. Despite current studies have shown that the gene family are involved in plant growth and developmental processes and biotic and abiotic stress responses, little is known about its functional role in upland cotton.

RESULTS

In the present study, we comprehensively analyzed the characteristics of the SOD gene family in upland cotton (Gossypium hirsutum). Based on their conserved motifs, 18 GhSOD genes were identified and phylogenetically classified into five subgroups which corroborated their classifications based on gene-structure patterns and subcellular localizations. The GhSOD sequences were distributed at different densities across 12 of the 26 chromosomes. The conserved domains, gene family evolution cis-acting elements of promoter regions and miRNA-mediated posttranscriptional regulation were predicted and analyzed. In addition, the expression pattern of 18 GhSOD genes were tested in different tissues/organs and developmental stages, and different abiotic stresses and abscisic acid, which indicated that the SOD gene family possessed temporal and spatial specificity expression specificity and may play important roles in reactive oxygen species scavenging caused by various stresses in upland cotton.

CONCLUSIONS

This study describes the first genome-wide analysis of the upland cotton SOD gene family, and the results will help establish a foundation for the further cloning and functional verification of the GhSOD gene family during stress responses, leading to crop improvement.

Increased rates of protein evolution and asymmetric deceleration after the whole-genome duplication in yeasts

Background

Whole-genome duplication (WGD) events have shaped the genomes of eukaryotic organisms. Relaxed selection after duplication along with inherent functional constraints are thought to determine the fate of the paralogs and, ultimately, the evolution of gene function. Here, we investigated the rate of protein evolution (as measured by dN/dS ratios) before and after the WGD in the hemiascomycete yeasts, and the way in which changes in such rates relate to molecular and biological function.

Results

For most groups of orthologous genes (81%) we observed a change in the rates of evolution after genome duplication. Genes with atypically-low dN/dS ratio before the WGD were prone to increase their rates of evolution after duplication. Importantly, the paralogs were often different in their rates of evolution after the WGD (50% cases), however, this was more consistent with an asymmetric deceleration in the protein-evolution rates, rather than an asymmetric increase of the initial rates. Functional-category analysis showed that regulatory proteins such as protein kinases and transcription factors were enriched in genes that increase their rates of evolution after the WGD. While changes in the rate of protein-sequence evolution were associated to protein abundance, content of disordered regions, and contribution to fitness, these features were an attribute of specific functional classes.

Conclusions

Our results indicate that strong purifying selection in ancestral pre-duplication sequences is a strong predictor of increased rates after the duplication in yeasts and that asymmetry in evolution rate is established during the deceleration phase. In addition, changes in the rates at which paralogous sequences evolve before and after WGD are different for specific protein functions; increased rates of protein evolution after duplication occur preferentially in specific protein functions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-017-0895-1) contains supplementary material, which is available to authorized users.

Upon Accounting for the Impact of Isoenzyme Loss, Gene Deletion Costs Anticorrelate with Their Evolutionary Rates

System-level metabolic network models enable the computation of growth and metabolic phenotypes from an organism's genome. In particular, flux balance approaches have been used to estimate the contribution of individual metabolic genes to organismal fitness, offering the opportunity to test whether such contributions carry information about the evolutionary pressure on the corresponding genes. Previous failure to identify the expected negative correlation between such computed gene-loss cost and sequence-derived evolutionary rates in Saccharomyces cerevisiae has been ascribed to a real biological gap between a gene's fitness contribution to an organism "here and now" and the same gene's historical importance as evidenced by its accumulated mutations over millions of years of evolution. Here we show that this negative correlation does exist, and can be exposed by revisiting a broadly employed assumption of flux balance models. In particular, we introduce a new metric that we call "function-loss cost", which estimates the cost of a gene loss event as the total potential functional impairment caused by that loss. This new metric displays significant negative correlation with evolutionary rate, across several thousand minimal environments. We demonstrate that the improvement gained using function-loss cost over gene-loss cost is explained by replacing the base assumption that isoenzymes provide unlimited capacity for backup with the assumption that isoenzymes are completely non-redundant. We further show that this change of the assumption regarding isoenzymes increases the recall of epistatic interactions predicted by the flux balance model at the cost of a reduction in the precision of the predictions. In addition to suggesting that the gene-to-reaction mapping in genome-scale flux balance models should be used with caution, our analysis provides new evidence that evolutionary gene importance captures much more than strict essentiality.

Lateralization of gene expression in the honeybee brain during olfactory learning

In the last decade, it has been demonstrated that brain functional asymmetry occurs not only in vertebrates but also in invertebrates. However, the mechanisms underlying functional asymmetry remain unclear. In the present study, we trained honeybees of the same parentage and age, on the proboscis extension reflex (PER) paradigm with only one antenna in use. The comparisons of gene expression between the left and right hemispheres were carried out using high throughput sequencing. Our research revealed that gene expression in the honeybee brain is also asymmetric, with more genes having higher expression in the right hemisphere than the left hemisphere. Our studies show that during olfactory learning, the left hemisphere is more responsible for long term memory and the right hemisphere is more responsible for the learning and short term memory.

Essentiality Is a Strong Determinant of Protein Rates of Evolution during Mutation Accumulation Experiments in Escherichia coli

The Neutral Theory of Molecular Evolution is considered the most powerful theory to understand the evolutionary behavior of proteins. One of the main predictions of this theory is that essential proteins should evolve slower than dispensable ones owing to increased selective constraints. Comparison of genomes of different species, however, has revealed only small differences between the rates of evolution of essential and nonessential proteins. In some analyses, these differences vanish once confounding factors are controlled for, whereas in other cases essentiality seems to have an independent, albeit small, effect. It has been argued that comparing relatively distant genomes may entail a number of limitations. For instance, many of the genes that are dispensable in controlled lab conditions may be essential in some of the conditions faced in nature. Moreover, essentiality can change during evolution, and rates of protein evolution are simultaneously shaped by a variety of factors, whose individual effects are difficult to isolate. Here, we conducted two parallel mutation accumulation experiments in Escherichia coli, during 5,500–5,750 generations, and compared the genomes at different points of the experiments. Our approach (a short-term experiment, under highly controlled conditions) enabled us to overcome many of the limitations of previous studies. We observed that essential proteins evolved substantially slower than nonessential ones during our experiments. Strikingly, rates of protein evolution were only moderately affected by expression level and protein length.