Positive Selection in Gene Regulatory Factors Suggests Adaptive Pleiotropic Changes During Human Evolution

Gene regulatory factors (GRFs), such as transcription factors, co-factors and histone-modifying enzymes, play many important roles in modifying gene expression in biological processes. They have also been proposed to underlie speciation and adaptation. To investigate potential contributions of GRFs to primate evolution, we analyzed GRF genes in 27 publicly available primate genomes. Genes coding for zinc finger (ZNF) proteins, especially ZNFs with a Krüppel-associated box (KRAB) domain were the most abundant TFs in all genomes. Gene numbers per TF family differed between all species. To detect signs of positive selection in GRF genes we investigated more than 3,000 human GRFs with their more than 70,000 orthologs in 26 non-human primates. We implemented two independent tests for positive selection, the branch-site-model of the PAML suite and aBSREL of the HyPhy suite, focusing on the human and great ape branch. Our workflow included rigorous procedures to reduce the number of false positives: excluding distantly similar orthologs, manual corrections of alignments, and considering only genes and sites detected by both tests for positive selection. Furthermore, we verified the candidate sites for selection by investigating their variation within human and non-human great ape population data. In order to approximately assign a date to positively selected sites in the human lineage, we analyzed archaic human genomes. Our work revealed with high confidence five GRFs that have been positively selected on the human lineage and one GRF that has been positively selected on the great ape lineage. These GRFs are scattered on different chromosomes and have been previously linked to diverse functions. For some of them a role in speciation and/or adaptation can be proposed based on the expression pattern or association with human diseases, but it seems that they all contributed independently to human evolution. Four of the positively selected GRFs are KRAB-ZNF proteins, that induce changes in target genes co-expression and/or through arms race with transposable elements. Since each positively selected GRF contains several sites with evidence for positive selection, we suggest that these GRFs participated pleiotropically to phenotypic adaptations in humans.

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A Phenotype–Genotype Codon Model for Detecting Adaptive Evolution

Systematic Biology ◽

10.1093/sysbio/syz075 ◽

2019 ◽

Vol 69 (4) ◽

pp. 722-738 ◽

Cited By ~ 2

Author(s):

Christopher T Jones ◽

Noor Youssef ◽

Edward Susko ◽

Joseph P Bielawski

Keyword(s):

Positive Selection ◽

Adaptive Evolution ◽

Evolutionary History ◽

Life History Trait ◽

Molecular Adaptation ◽

Simulation Studies ◽

Site Model ◽

Branch Site ◽

A Site ◽

Post Hoc

Abstract A central objective in biology is to link adaptive evolution in a gene to structural and/or functional phenotypic novelties. Yet most analytic methods make inferences mainly from either phenotypic data or genetic data alone. A small number of models have been developed to infer correlations between the rate of molecular evolution and changes in a discrete or continuous life history trait. But such correlations are not necessarily evidence of adaptation. Here, we present a novel approach called the phenotype–genotype branch-site model (PG-BSM) designed to detect evidence of adaptive codon evolution associated with discrete-state phenotype evolution. An episode of adaptation is inferred under standard codon substitution models when there is evidence of positive selection in the form of an elevation in the nonsynonymous-to-synonymous rate ratio $\omega$ to a value $\omega > 1$. As it is becoming increasingly clear that $\omega > 1$ can occur without adaptation, the PG-BSM was formulated to infer an instance of adaptive evolution without appealing to evidence of positive selection. The null model makes use of a covarion-like component to account for general heterotachy (i.e., random changes in the evolutionary rate at a site over time). The alternative model employs samples of the phenotypic evolutionary history to test for phenomenological patterns of heterotachy consistent with specific mechanisms of molecular adaptation. These include 1) a persistent increase/decrease in $\omega$ at a site following a change in phenotype (the pattern) consistent with an increase/decrease in the functional importance of the site (the mechanism); and 2) a transient increase in $\omega$ at a site along a branch over which the phenotype changed (the pattern) consistent with a change in the site’s optimal amino acid (the mechanism). Rejection of the null is followed by post hoc analyses to identify sites with strongest evidence for adaptation in association with changes in the phenotype as well as the most likely evolutionary history of the phenotype. Simulation studies based on a novel method for generating mechanistically realistic signatures of molecular adaptation show that the PG-BSM has good statistical properties. Analyses of real alignments show that site patterns identified post hoc are consistent with the specific mechanisms of adaptation included in the alternate model. Further simulation studies show that the covarion-like component of the PG-BSM plays a crucial role in mitigating recently discovered statistical pathologies associated with confounding by accounting for heterotachy-by-any-cause. [Adaptive evolution; branch-site model; confounding; mutation-selection; phenotype–genotype.]

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On the interpretation of results returned by branch-site models

10.7287/peerj.preprints.944 ◽

2015 ◽

Author(s):

Stephane Guindon

Keyword(s):

Positive Selection ◽

Negative Selection ◽

Molecular Level ◽

Site Model ◽

Branch Site ◽

Codon Evolution ◽

Interpretation Of Results

In a recent study, Murrell et al. (2015) compared the performance of several branch-site models of codon evolution. Their interpretation of results published by Lu & Guindon (2014) suggests that the stochastic branch-site model implemented in the software fitmodel is anti-conservative altogether, i.e., positive selection is detected more often than expected when analyzing sequences evolving under a mixture of neutrality and negative selection. I argue here that this presentation of the performance of fitmodel is misleading and should not deter evolutionary biologists from using this approach in exploratory analyses of selection patterns at the molecular level.

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On the interpretation of results returned by branch-site models

10.7287/peerj.preprints.944v1 ◽

2015 ◽

Author(s):

Stephane Guindon

Keyword(s):

Positive Selection ◽

Negative Selection ◽

Molecular Level ◽

Site Model ◽

Branch Site ◽

Codon Evolution ◽

Interpretation Of Results

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Dietary Diversification and Specialisation in New World Bats Facilitated by Early Molecular Evolution

Molecular Biology and Evolution ◽

10.1093/molbev/msab028 ◽

2021 ◽

Author(s):

Joshua H T Potter ◽

Kalina T J Davies ◽

Laurel R Yohe ◽

Miluska K R Sanchez ◽

Edgardo M Rengifo ◽

...

Keyword(s):

Positive Selection ◽

Food Sources ◽

Published Data ◽

Protein Coding ◽

Ecological Diversification ◽

Site Model ◽

Branch Site ◽

Complex Picture ◽

Dietary Diversification ◽

Dietary Shifts

Abstract Dietary adaptation is a major feature of phenotypic and ecological diversification, yet the genetic basis of dietary shifts is poorly understood. Among mammals, Neotropical leaf-nosed bats (family Phyllostomidae) show unmatched diversity in diet; from a putative insectivorous ancestor, phyllostomids have radiated to specialize on diverse food sources, including blood, nectar, and fruit. To assess whether dietary diversification in this group was accompanied by molecular adaptations for changing metabolic demands, we sequenced 89 transcriptomes across 58 species, and combined these with published data to compare ∼13,000 protein coding genes across 66 species. We tested for positive selection on focal lineages, including those inferred to have undergone dietary shifts. Unexpectedly, we found a broad signature of positive selection in the ancestral phyllostomid branch, spanning genes implicated in the metabolism of all major macronutrients, yet few positively selected genes at the inferred switch to plantivory. Branches corresponding to blood- and nectar-based diets showed selection in loci underpinning nitrogenous waste excretion and glycolysis, respectively. Intriguingly, patterns of selection in metabolism genes were mirrored by those in loci implicated in craniofacial remodelling, a trait previously linked to phyllostomid dietary specialisation. Finally, using simulations, we show that the widely-used branch-site model is likely to be misspecified, with the implication that it is too conservative and probably under-reports true cases of positive selection. Our findings point to a complex picture of adaptive radiation, in which the evolution of new dietary specialisations has been facilitated by early adaptations combined with the generation of new genetic variation.

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Genetic Variation in Human Gene Regulatory Factors Uncovers Regulatory Roles in Local Adaptation and Disease

Genome Biology and Evolution ◽

10.1093/gbe/evz131 ◽

2019 ◽

Vol 11 (8) ◽

pp. 2178-2193 ◽

Cited By ~ 3

Author(s):

Álvaro Perdomo-Sabogal ◽

Katja Nowick

Keyword(s):

Genetic Variation ◽

Local Adaptation ◽

Target Genes ◽

Gene Clusters ◽

Regulatory Elements ◽

Nucleotide Polymorphisms ◽

Extended Haplotype ◽

Regulatory Factors ◽

Gene Regulatory ◽

Candidate Regions

Abstract Differences in gene regulation have been suggested to play essential roles in the evolution of phenotypic changes. Although DNA changes in cis-regulatory elements affect only the regulation of its corresponding gene, variations in gene regulatory factors (trans) can have a broader effect, because the expression of many target genes might be affected. Aiming to better understand how natural selection may have shaped the diversity of gene regulatory factors in human, we assembled a catalog of all proteins involved in controlling gene expression. We found that at least five DNA-binding transcription factor classes are enriched among genes located in candidate regions for selection, suggesting that they might be relevant for understanding regulatory mechanisms involved in human local adaptation. The class of KRAB-ZNFs, zinc-finger (ZNF) genes with a Krüppel-associated box, stands out by first, having the most genes located on candidate regions for positive selection. Second, displaying most nonsynonymous single nucleotide polymorphisms (SNPs) with high genetic differentiation between populations within these regions. Third, having 27 KRAB-ZNF gene clusters with high extended haplotype homozygosity. Our further characterization of nonsynonymous SNPs in ZNF genes located within candidate regions for selection, suggests regulatory modifications that might influence the expression of target genes at population level. Our detailed investigation of three candidate regions revealed possible explanations for how SNPs may influence the prevalence of schizophrenia, eye development, and fertility in humans, among other phenotypes. The genetic variation we characterized here may be responsible for subtle to rough regulatory changes that could be important for understanding human adaptation.

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Insight into the Phylogenetic Relationships among Three Subfamilies within Heptageniidae (Insecta: Ephemeroptera) along with Low-Temperature Selection Pressure Analyses Using Mitogenomes

Insects ◽

10.3390/insects12070656 ◽

2021 ◽

Vol 12 (7) ◽

pp. 656

Author(s):

Xiao-Dong Xu ◽

Jia-Yin Guan ◽

Zi-Yi Zhang ◽

Yu-Rou Cao ◽

Yin-Yin Cai ◽

...

Keyword(s):

Low Temperature ◽

Positive Selection ◽

Temperature Stress ◽

Selection Pressure ◽

Gene Rearrangement ◽

Phylogenetic Analyses ◽

Low Temperature Stress ◽

Protein Coding ◽

Site Model ◽

Branch Site

We determined 15 complete and two nearly complete mitogenomes of Heptageniidae belonging to three subfamilies (Heptageniinae, Rhithrogeninae, and Ecdyonurinae) and six genera (Afronurus, Epeorus, Leucrocuta, Maccaffertium, Stenacron, and Stenonema). Species of Rhithrogeninae and Ecdyonurinae had the same gene rearrangement of CR-I-M-Q-M-ND2, whereas a novel gene rearrangement of CR-I-M-Q-NCR-ND2 was found in Heptageniinae. Non-coding regions (NCRs) of 25–47 bp located between trnA and trnR were observed in all mayflies of Heptageniidae, which may be a synapomorphy for Heptageniidae. Both the BI and ML phylogenetic analyses supported the monophyly of Heptageniidae and its subfamilies (Heptageniinae, Rhithrogeninae, and Ecdyonurinae). The phylogenetic results combined with gene rearrangements and NCR locations confirmed the relationship of the subfamilies as (Heptageniinae + (Rhithrogeninae + Ecdyonurinae)). To assess the effects of low-temperature stress on Heptageniidae species from Ottawa, Canada, we found 27 positive selection sites in eight protein-coding genes (PCGs) using the branch-site model. The selection pressure analyses suggested that mitochondrial PCGs underwent positive selection to meet the energy requirements under low-temperature stress.

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Deciphering the genetic links between NAFLD and co-occurring conditions using a liver gene regulatory network

10.1101/2021.12.08.471841 ◽

2021 ◽

Author(s):

Sreemol Gokuladhas ◽

William Schierding ◽

Roan Eltigani Zaied ◽

Tayaza Fadason ◽

Murim Choi ◽

...

Keyword(s):

Gene Regulatory Network ◽

Regulatory Network ◽

Complex Traits ◽

Target Genes ◽

Specific Gene ◽

Fat Percentage ◽

Alcoholic Fatty Liver ◽

Regulatory Interactions ◽

Hepatic Diseases ◽

Gene Regulatory

Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is a multi-system metabolic disease that co-occurs with various hepatic and extra-hepatic diseases. The phenotypic manifestation of NAFLD is primarily observed in the liver. Therefore, identifying liver-specific gene regulatory interactions between variants associated with NAFLD and multimorbid conditions may help to improve our understanding of underlying shared aetiology. Methods: Here, we constructed a liver-specific gene regulatory network (LGRN) consisting of genome-wide spatially constrained expression quantitative trait loci (eQTLs) and their target genes. The LGRN was used to identify regulatory interactions involving NAFLD-associated genetic modifiers and their inter-relationships to other complex traits. Results and Conclusions: We demonstrate that MBOAT7 and IL32, which are associated with NAFLD progression, are regulated by spatially constrained eQTLs that are enriched for an association with liver enzyme levels. MBOAT7 transcript levels are also linked to eQTLs associated with cirrhosis, and other traits that commonly co-occur with NAFLD. In addition, genes that encode interacting partners of NAFLD-candidate genes within the liver-specific protein-protein interaction network were affected by eQTLs enriched for phenotypes relevant to NAFLD (e.g. IgG glycosylation patterns, OSA). Furthermore, we identified distinct gene regulatory networks formed by the NAFLD-associated eQTLs in normal versus diseased liver, consistent with the context-specificity of the eQTLs effects. Interestingly, genes targeted by NAFLD-associated eQTLs within the LGRN were also affected by eQTLs associated with NAFLD-related traits (e.g. obesity and body fat percentage). Overall, the genetic links identified between these traits expand our understanding of shared regulatory mechanisms underlying NAFLD multimorbidities.

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Functional effects of variation in transcription factor binding highlight long-range gene regulation by epromoters

10.1101/620062 ◽

2019 ◽

Author(s):

Joanna Mitchelmore ◽

Nastasiya Grinberg ◽

Chris Wallace ◽

Mikhail Spivakov

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Statistical Power ◽

Target Genes ◽

Allelic Variation ◽

Regulatory Function ◽

Regulatory Sequences ◽

Distal Enhancer ◽

Association Testing ◽

Gene Regulatory

AbstractIdentifying DNA cis-regulatory modules (CRMs) that control the expression of specific genes is crucial for deciphering the logic of transcriptional control. Natural genetic variation can point to the possible gene regulatory function of specific sequences through their allelic associations with gene expression. However, comprehensive identification of causal regulatory sequences in brute-force association testing without incorporating prior knowledge is challenging due to limited statistical power and effects of linkage disequilibrium. Sequence variants affecting transcription factor (TF) binding at CRMs have a strong potential to influence gene regulatory function, which provides a motivation for prioritising such variants in association testing. Here, we generate an atlas of CRMs showing predicted allelic variation in TF binding affinity in human lymphoblastoid cell lines (LCLs) and test their association with the expression of their putative target genes inferred from Promoter Capture Hi-C and immediate linear proximity. We reveal over 1300 CRM TF-binding variants associated with target gene expression, the majority of them undetected with standard association testing. A large proportion of CRMs showing associations with the expression of genes they contact in 3D localise to the promoter regions of other genes, supporting the notion of ‘epromoters’: dual-action CRMs with promoter and distal enhancer activity.

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Evolution of gene regulatory networks by means of selection and random genetic drift

10.1101/449645 ◽

2018 ◽

Author(s):

Antonios Kioukis ◽

Pavlos Pavlidis

Keyword(s):

Natural Selection ◽

Positive Selection ◽

Genetic Drift ◽

Regulatory Networks ◽

Fitness Landscape ◽

Random Genetic Drift ◽

Maturation Period ◽

Evolutionary Forces ◽

Gene Regulatory

The evolution of a population by means of genetic drift and natural selection operating on a gene regulatory network (GRN) of an individual has not been scrutinized in depth. Thus, the relative importance of various evolutionary forces and processes on shaping genetic variability in GRNs is understudied. Furthermore, it is not known if existing tools that identify recent and strong positive selection from genomic sequences, in simple models of evolution, can detect recent positive selection when it operates on GRNs. Here, we propose a simulation framework, called EvoNET, that simulates forward-in-time the evolution of GRNs in a population. Since the population size is finite, random genetic drift is explicitly applied. The fitness of a mutation is not constant, but we evaluate the fitness of each individual by measuring its genetic distance from an optimal genotype. Mutations and recombination may take place from generation to generation, modifying the genotypic composition of the population. Each individual goes through a maturation period, where its GRN reaches equilibrium. At the next step, individuals compete to produce the next generation. As time progresses, the beneficial genotypes push the population higher in the fitness landscape. We examine properties of the GRN evolution such as robustness against the deleterious effect of mutations and the role of genetic drift. We confirm classical results from Andreas Wagner’s work that GRNs show robustness against mutations and we provide new results regarding the interplay between random genetic drift and natural selection.

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Evolutionary analysis of vision genes identifies potential drivers of visual differences between giraffe and okapi

PeerJ ◽

10.7717/peerj.3145 ◽

2017 ◽

Vol 5 ◽

pp. e3145 ◽

Cited By ~ 2

Author(s):

Edson Ishengoma ◽

Morris Agaba ◽

Douglas R. Cavener

Keyword(s):

Positive Selection ◽

Visual Signal ◽

Evolutionary Analysis ◽

Long Distance ◽

Phenotypic Differences ◽

Multiple Strategies ◽

Branch Site ◽

Signature Of Selection ◽

Evolutionary Success ◽

Signatures Of Selection

BackgroundThe capacity of visually oriented species to perceive and respond to visual signal is integral to their evolutionary success. Giraffes are closely related to okapi, but the two species have broad range of phenotypic differences including their visual capacities. Vision studies rank giraffe’s visual acuity higher than all other artiodactyls despite sharing similar vision ecological determinants with many of them. The extent to which the giraffe’s unique visual capacity and its difference with okapi is reflected by changes in their vision genes is not understood.MethodsThe recent availability of giraffe and okapi genomes provided opportunity to identify giraffe and okapi vision genes. Multiple strategies were employed to identify thirty-six candidate mammalian vision genes in giraffe and okapi genomes. Quantification of selection pressure was performed by a combination of branch-site tests of positive selection and clade models of selection divergence through comparing giraffe and okapi vision genes and orthologous sequences from other mammals.ResultsSignatures of selection were identified in key genes that could potentially underlie giraffe and okapi visual adaptations. Importantly, some genes that contribute to optical transparency of the eye and those that are critical in light signaling pathway were found to show signatures of adaptive evolution or selection divergence. Comparison between giraffe and other ruminants identifies significant selection divergence inCRYAAandOPN1LW. Significant selection divergence was identified inSAGwhile positive selection was detected inLUMwhen okapi is compared with ruminants and other mammals. Sequence analysis ofOPN1LWshowed that at least one of the sites known to affect spectral sensitivity of the red pigment is uniquely divergent between giraffe and other ruminants.DiscussionBy taking a systemic approach to gene function in vision, the results provide the first molecular clues associated with giraffe and okapi vision adaptations. At least some of the genes that exhibit signature of selection may reflect adaptive response to differences in giraffe and okapi habitat. We hypothesize that requirement for long distance vision associated with predation and communication with conspecifics likely played an important role in the adaptive pressure on giraffe vision genes.

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