Genotype network intersections promote evolutionary innovation
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB30802 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR3063150.fastq.gz | Fastqsanger.gz | |||
| ERR3063151.fastq.gz | Fastqsanger.gz | |||
| ERR3063143.fastq.gz | Fastqsanger.gz | |||
| ERR3063144.fastq.gz | Fastqsanger.gz | |||
| ERR3063145.fastq.gz | Fastqsanger.gz |
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Project description:Evolutionary innovations are qualitatively novel traits that emerge through evolution and increase biodiversity. The genetic mechanisms of innovation remain poorly understood. A systems view of innovation requires the analysis of genotype networks-the vast networks of genetic variants that produce the same phenotype. Innovations can occur at the intersection of two different genotype networks. However, the experimental characterization of genotype networks has been hindered by the vast number of genetic variants that need to be functionally analyzed. Here, we use high-throughput sequencing to study the fitness landscape at the intersection of the genotype networks of two catalytic RNA molecules (ribozymes). We determined the ability of numerous neighboring RNA sequences to catalyze two different chemical reactions, and we use these data as a proxy for a genotype to fitness map where two functions come in close proximity. We find extensive functional overlap, and numerous genotypes can catalyze both functions. We demonstrate through evolutionary simulations that these numerous points of intersection facilitate the discovery of a new function. However, the rate of adaptation of the new function depends upon the local ruggedness around the starting location in the genotype network. As a consequence, one direction of adaptation is more rapid than the other. We find that periods of neutral evolution increase rates of adaptation to the new function by allowing populations to spread out in their genotype network. Our study reveals the properties of a fitness landscape where genotype networks intersect and the consequences for evolutionary innovations. Our results suggest that historic innovations in natural systems may have been facilitated by overlapping genotype networks.
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Project description:Conservation and innovation in the DUX4-family gene network
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Project description:Despite being essential for fertility, genome defence pathway genes often evolve rapidly. However, little is known about the molecular basis of this adaptation. Here, we characterize the evolution of a protein interaction network within the PIWI-interacting small RNA (piRNA) genome defence pathway in Drosophila at unprecedented scale and evolutionary resolution. We uncover pervasive rapid evolution of a protein interaction network anchored at the Heterochromatin Protein 1 (HP1) paralog Rhino. Using complementary phylogenetic analysis, high-throughput yeast-two-hybrid matrix screening, and in vivo interaction analyses in cross-species transgenic flies, we characterized at least three distinct evolutionary protein interaction trajectories across ~40 million years of Drosophila evolution. The comprehensive cross-species interaction data set covering 11 piRNA pathway proteins of five Drosophila species revealed several protein interactions that are fully conserved, indicating functional conservation despite overall rapid amino acid sequence change. Other interactions are preserved through co-evolution and were detected only between proteins in closely related and within species. We also identified sets of species-restricted protein interactions which, through rewiring of a Rhino-anchored transcription factor network, may preserve critical roles in enabling and adapting piRNA production from heterochromatic loci. In sum, our analyses dissected principles of interaction evolution in an adaptively evolving protein-protein interaction network uncovering evolutionary and functional insight into germline piRNA production across Drosophila species. Our work provides key experimental evidence in support of a fundamental model proposing that intermolecular interaction innovation is a major molecular mechanism of evolutionary adaptation in protein-coding genes.
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Project description:The survival of a population during environmental shifts depends on whether the rate of phenotypic adaptation keeps up with the rate of changing conditions. A common way to achieve this is via change to gene regulatory network (GRN) connections – known as rewiring – that facilitate novel interactions and innovation of transcription factors. To understand the success of rapidly adapting organisms, we therefore need to determine the rules that create and constrain opportunities for GRN rewiring. Here, using an experimental microbial model system based on the soil bacterium Pseudomonas fluorescens, we reveal a hierarchy among transcription factors that are rewired to rescue lost function, with alternative rewiring pathways only unmasked after the preferred pathway is eliminated. We identify three key properties - high activation, high expression, and pre-existing low-level affinity for novel target genes – that facilitate transcription factor innovation. Ease of acquiring these properties is constrained by pre-existing GRN architecture, which was overcome in our experimental system by both targeted and global network alterations. This work reveals the key properties that determine transcription factor evolvability, and as such, the evolution of GRNs.
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Project description:Understanding and predicting the relationships between genotype and phenotype is often challenging, largely due to the complex nature of eukaryotic gene regulation. A step towards this goal is to map how phenotypic variation evolves through genomic changes that modify gene regulatory interactions. Using the Prairie Rattlesnake (Crotalus viridis) and related species, we integrate mRNA-seq, proteomic, ATAC-seq and whole genome resequencing data to understand how specific evolutionary modifications to gene regulatory network components produce variation in venom gene expression. Through comparisons within and between species, we find a remarkably high degree of gene expression and regulatory network variation across even a shallow level of evolutionary divergence. We use these data to test hypotheses about the roles of specific trans-factors and cis-regulatory elements, how these roles may vary across venom genes and gene families, and how variation in regulatory systems drive variation in venom phenotypes. Our results illustrate that variation in chromatin and genotype at regulatory elements plays major roles in modulating expression. However, we also find that enhancer deletions, variation in transcription-factor expression, and variation in activity of the insulator protein CTCF also impact downstream venom phenotypes. Our findings provide insight into the diversity and gene-specificity of gene regulatory features and highlight the value of comparative studies to link gene regulatory network variation to phenotypic variation.
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