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bioRxiv2018

Catalytic promiscuity potentiated the divergence of new cytochrome P450 enzyme functions in cyanogenic defense metabolism

Cytochrome P450 monooxygenases (P450s) constitute the largest metabolic enzyme family in plants, responsible for synthesizing hundreds of thousands of specialized metabolites with essential roles in chemical defenses against herbivores and pathogens (Banks et al., 2011; Nelson and Werck-Reichhart, 2011; Wurtzel and Kutchan, 2016). Substrate promiscuity has been documented to play a central role in the evolution of plant specialized metabolic enzymes (Weng et al., 2012; Leong and Last, 2017), however most plant P450s are highly substrate-specific (Verpoorte, 2013). Here, we show the rapid inversion of primary and weak secondary (promiscuous) catalytic activities between two distinct yet evolutionarily linked multifunctional P450s, CYP71A12 and CYP71A13, based on intramolecular epistasis of two amino acid residues under positive selection in CYP71A12. Furthermore, we uncover previously undocumented catalytic activity during the inversion as well as naturally occurring amino acid substitution patterns that could have been present in evolutionary intermediates between the two enzymes. Comparative expression profiling and homology modeling reveal that natural selection acted on the promoter of CYP71A13 and the substrate-recognition elements of CYP71A12 to improve the efficiencies of their promiscuous reactions. The rise in catalytic promiscuity potentiated the divergence of new P450 enzyme functions in cyanogenic defense metabolism. Directed evolution of promiscuous reactions is one of the core technologies underpinning the field of synthetic biology. Our results provide a more complete understanding of how natural selection uses promiscuous reactions to generate new enzymes in nature and chemical diversity in pathogen defense, as well as demonstrate a novel strategy for identifying their molecular origins in highly divergent, related enzymes.

evolutionary biology↗

bioRxiv2015

Mitotic chromosome compaction via active loop extrusion

During cell division chromosomes are compacted in length by more than a hundred-fold. A wide range of experiments demonstrated that in their compacted state, mammalian chromosomes form arrays of closely stacked consecutive [~]100Kb loops. The mechanism underlying the active process of chromosome compaction into a stack of loops is unknown. Here we test the hypothesis that chromosomes are compacted by enzymatic machines that actively extrude chromatin loops. When such loop-extruding factors (LEF) bind to chromosomes, they progressively bridge sites that are further away along the chromosome, thus extruding a loop. We demonstrate that collective action of LEFs leads to formation of a dynamic array of consecutive loops. Simulations and an analytically solved model identify two distinct steady states: a sparse state where loops are highly dynamic but provide little compaction, and a dense state with more stable loops and dramatic chromosome compaction. We find that human chromosomes operate at the border of the dense steady state. Our analysis also shows how the macroscopic characteristics of the loop array are determined by the microscopic properties of LEFs and their abundance. When number of LEFs are used that match experimentally based estimates, the model can quantitatively reproduce the average loop length, the degree of compaction, and the general loop-array morphology of compact human chromosomes. Our study demonstrates that efficient chromosome compaction can be achieved solely by an active loop-extrusion process.\n\nSignificance StatementDuring cell division chromosomes are compacted in length more than a hundred-fold and are folded in arrays of loops. The mechanism underlying this essential biological process is unknown. Here we test whether chromosome compaction can be performed by molecular machines that actively extrude chromatin loops. These machines bind to DNA and progressively bridge sites that are further and further away along the chromosome. We demonstrate that the collective action of loop-extruding machines can fold a chromosome into a dynamic array of loops. Simulated chromosome agrees with compact human chromosomes in its degree of compaction, loop size and the general loop-array morphology. Our study demonstrates that efficient chromosome compaction can be achieved solely by such active loop-extrusion process.

Biophysics↗

bioRxiv2016

Repeated divergent selection on pigmentation genes in a rapid finch radiation driven by sexual selection

The search for molecular targets of selection is leading to a better understanding of how evolution shapes biological diversity. Instances of recent and rapid speciation are suitable for associating phenotypes with their causal genotypes, because gene flow may homogenize areas of the genome that are not under divergent selection. Locating differentiated genomic regions among taxa allows us to test associations between the genes in these regions and their contributions to phenotypic diversity. Here we study a rapid radiation of nine sympatric bird species known as southern capuchino seedeaters, which are strikingly differentiated in sexually selected characters of male plumage and song. We sequenced the genomes of 72 individuals representing a diverse set of species and associated phenotypes to search for differentiated genomic regions. We asked what genes are harbored in divergent regions and to what extent has selection on the same targets shaped phenotypic diversity across different lineages. Capuchinos show differences in a small proportion of their genomes, yet selection has acted independently on the same targets during the groups radiation. Many divergence peaks contain genes involved in the melanogenesis pathway, with the strongest signal originating from a regulatory region upstream of the gene coding for the Agouti-signaling protein. Across all divergence peaks, the most differentiated areas are similarly likely regulatory. Our findings are consistent with selection acting on the same genomic regions in different lineages to shape the evolution of cis-regulatory elements, which control how more conserved genes are expressed and thereby generate diversity in sexually selected traits.

Evolutionary Biology↗

bioRxiv2017

Clusterization in head and neck squamous carcinomas based on lncRNA expression: molecular and clinical correlates

BackgroundLong non-coding RNAs (lncRNAs) have emerged as key players in a remarkably variety of biological processes and pathologic conditions, including cancer. Next-generation sequencing technologies and bioinformatics procedures predict the existence of tens of thousands of lncRNAs, from which we know the functions of only a handful of them, and very little is known in cancer types such as head and neck squamous cell carcinomas (HNSCCs).\n\nResultsHere, we use RNA-seq expression data from The Cancer Genome Atlas (TCGA) and various statistic and software tools in order to get insight about the lncRNome in HNSCC. Based on lncRNAs expression across 426 samples, we discover five distinct tumor clusters that we compare with reported clusters based on various genomic/genetic features. Results demonstrate significant associations between lncRNA-based clustering and DNA-methylation, TP53 mutation, and human papillomavirus infection. Using \"guilt by association\" procedures, we infer the possible biological functions of representative lncRNAs of each cluster. Furthermore, we found that lncRNA clustering is correlated with some important clinical and pathologic features, including patient survival after treatment, tumor grade or sub-anatomical location.\n\nConclusionsWe present a landscape of lncRNAs in HNSCC, and provide associations with important genotypic and phenotypic features that may help to understand the disease.

genomics↗

bioRxiv2017

The geometry of heterosis

Heterosis, the superiority of hybrids over their parents for quantitative traits, represents a crucial issue in plant and animal breeding. Heterosis has given rise to countless genetic, genomic and molecular studies, but has rarely been investigated from the point of view of systems biology. We hypothesized that heterosis is an emergent property of living systems resulting from frequent concave relationships between genotypic variables and phenotypes, or between different phenotypic levels. We chose the enzyme-flux relationship as a model of the concave genotype-phenotype (GP) relationship, and showed that heterosis can be easily created in the laboratory. First, we reconstituted in vitro the upper part of glycolysis. We simulated genetic variability of enzyme activity by varying enzyme concentrations in test tubes. Mixing the content of \"parental\" tubes resulted in \"hybrids\", whose fluxes were compared to the parental fluxes. Frequent heterotic fluxes were observed, under conditions that were determined analytically and confirmed by computer simulation. Second, to test this model in a more realistic situation, we modeled the glycolysis/fermentation network in yeast by considering one input flux, glucose, and two output fluxes, glycerol and acetaldehyde. We simulated genetic variability by randomly drawing parental enzyme concentrations under various conditions, and computed the parental and hybrid fluxes using a system of differential equations. Again we found that a majority of hybrids exhibited positive heterosis for metabolic fluxes. Cases of negative heterosis were due to local convexity between certain enzyme concentrations and fluxes. In both approaches, heterosis was maximized when the parents were phenotypically close and when the distributions of parental enzyme concentrations were contrasted and constrained. These conclusions are not restricted to metabolic systems: they only depend on the concavity of the GP relationship, which is commonly observed at various levels of the phenotypic hierarchy, and could account for the pervasiveness of heterosis.

systems biology↗

bioRxiv2017

Reconstruction of developmental landscapes by optimal-transport analysis of single-cell gene expression sheds light on cellular reprogramming.

Understanding the molecular programs that guide cellular differentiation during development is a major goal of modern biology. Here, we introduce an approach, WADDINGTON-OT, based on the mathematics of optimal transport, for inferring developmental landscapes, probabilistic cellular fates and dynamic trajectories from large-scale single-cell RNA-seq (scRNA-seq) data collected along a time course. We demonstrate the power of WADDINGTON-OT by applying the approach to study 65,781 scRNA-seq profiles collected at 10 time points over 16 days during reprogramming of fibroblasts to iPSCs. We construct a high-resolution map of reprogramming that rediscovers known features; uncovers new alternative cell fates including neuraland placental-like cells; predicts the origin and fate of any cell class; highlights senescent-like cells that may support reprogramming through paracrine signaling; and implicates regulatory models in particular trajectories. Of these findings, we highlight Obox6, which we experimentally show enhances reprogramming efficiency. Our approach provides a general framework for investigating cellular differentiation.

bioinformatics↗

bioRxiv2018

Polymer brush bilayers at thermal equilibrium: A theoretical approach

By means of the density functional theory (DFT) framework, the longstanding problem of the polymer brush bilayers at thermal equilibrium is studied. The calculated density profiles reveal that the brushes balance compression and interpenetration when they come into contact. The equation of state of the polymer brush bilayers is obtained and it represents scaling of the pressure with molecular parameters and distance between substrates. The results of this study may shed light in our understanding of some severe Musculoskeletal diseases which degrade the synovium. The significance of this study lays on the fact that the molecular structure is investigated through fundamental physical laws. So, this study bridges between theoretical biological physics and medicine.

biophysics↗

bioRxiv2018

Infectious bronchitis virus attaches to lipid rafts and enters cells via clathrin mediated endocytosis

Due to its economic importance to in poultry industry, the biology and pathogenesis of infectious bronchitis virus (IBV) have been investigated extensively. However, the molecular mechanisms involved in IBV entry are not well characterized. In this study, systematic approaches were used to dissect IBV entry process in various susceptible cells. First, we observed that lipid rafts were involved in IBV attachment. Second, low pH in intracyplasmic vesicles was required for virus entry. By using the specific clathrin mediated endocytosis (CME) inhibitor or knock down of clathrin heavy chain (CHC), we demonstrated that IBV mainly utilized the CME for its entry. Furthermore, GTPase dynamin1 was involved in virus containing vesicle scission and internalization. Surprisingly, CME adaptor Eps15 had no effect on IBV internalization. Third, the penetration of IBV into cells led to active cytoskeleton rearrangement. After internalization, virus particles moved along with the classical endosome/lysosome track, as evidenced by co-localization of R18 labeled IBV with vehicle markers Rab5/Rab7/LAMP1 along with the infection time course. Functional inactivation of Rab5 and Rab7 significantly inhibited IBV infection. VCP, a protein helps early endosome maturation, was involved virus trafficking. Finally, by using the dual R18/DiOC labeled IBV, we observed that membrane fusion with late endosome/lysosome membranes was induced between 2-3 h.p.i.. Taken together, our findings demonstrate that IBV virions attach to lipid rafts and are internalized into cells via CME, move along with early/late endosomes-lysosomes, finally fuse with late endosome-lysosome membranes, release virus genome into cytoplasm. This study provides comprehensive images of IBV attachment-internalization-trafficking-fusion steps.\n\nIMPORTANCEIBV, the avian coronavirus isolated in 1937, infects chicken and causes economic loss in poultry industry. It has been reported that the entry of IBV requires low pH. However, the molecular mechanisms underlying IBV internalization and trafficking remain to be clarified. Therefore, we employed multiple chemical and molecular approaches to dissect the entry mechanisms of IBV in susceptible cells. Our results showed IBV entry was significantly inhibited when clathrin-mediated endocytosis (CME) was blocked by chemical inhibitor or depletion of clathrin protein. Moreover, by using R18-labeled IBV, we found that IBV particles attached to lipid rafts, led to actin rearrangement, and moved along with the entire endosomal system. R18/DiOC labeling method showed that IBV fused with late endosomes or lysosomes. This is the first report to describe the entire entry process of IBV, allowing for a better understanding of the infection process of group III avian coronavirus.

microbiology↗

bioRxiv2018

Template-free detection and classification of heterogeneous membrane-bound complexes in cryo-electron tomograms

With faithful sample preservation and direct imaging of fully hydrated biological material, cryo-electron tomography (cryo-ET) provides an accurate representation of molecular architecture of cells. However, detection and precise localization of macromolecular complexes within cellular environments is aggravated by the presence of many molecular species and molecular crowding. We developed a template-free image processing procedure for accurate tracing of complex networks of densities in cryo-electron tomograms, a comprehensive and automated detection of heterogeneous membrane-bound complexes and an unsupervised classification. Applying this procedure to tomograms of intact cells and isolated endoplasmic reticulum (ER), we detected and classified small protein complexes like the ER protein translocons, which were not detected by other methods before. This classification provided sufficiently homogeneous particle sets and initial references to allow subsequent de novo subtomogram averaging. Therefore the procedure presented allows a comprehensive detection and a structural analysis of complexes in their native state. In addition, we present structural evidence that different ribosome-free translocon species are present at the ER membrane, determine their 3D structure, and show that they have different localization patterns forming nanodomains.

biophysics↗

bioRxiv2017

The Past Sure Is Tense: On Interpreting Phylogenetic Divergence Time Estimates

Divergence time estimation -- the calibration of a phylogeny to geological time -- is a integral first step in modelling the tempo of biological evolution (traits and lineages). However, despite increasingly sophisticated methods to infer divergence times from molecular genetic sequences, the estimated age of many nodes across the tree of life contrast significantly and consistently with timeframes conveyed by the fossil record. This is perhaps best exemplified by crown angiosperms, where molecular clock (Triassic) estimates predate the oldest (Early Cretaceous) undisputed angiosperm fossils by tens of millions of years or more. While the incompleteness of the fossil record is a common concern, issues of data limitation and model inadequacy are viable (if underexplored) alternative explanations. In this vein, Beaulieu et al. (2015) convincingly demonstrated how methods of divergence time inference can be misled by both (i) extreme state-dependent molecular substitution rate heterogeneity and (ii) biased sampling of representative major lineages. While these (essentially model-violation) results are robust (and probably common in empirical data sets), we note a further alternative: that the configuration of the statistical inference problem alone (i.e., the parameters, their relationships, and associated priors) precluded the reconstruction of the paleontological timeframe for the crown age of angiosperms. We demonstrate, through sampling from the joint prior (formed by combining the tree (diversification) prior with the various calibration densities specified for fossil-calibrated nodes), that with no data present at all, an Early Cretaceous crown angiosperms is rejected (i.e., has essentially zero probability). More worrisome, however, is that for the 24 nodes calibrated by fossils, almost all have indistinguishable marginal prior and posterior age distributions, indicating an absence of relevant information in the data. Given that these calibrated nodes are strategically placed in disparate regions of the tree, they essentially anchor the tree scaffold, and so the posterior inference for the tree as a whole is largely determined by the pseudo-data present in the (often arbitrary) calibration densities. We recommend, as for any Bayesian analysis, that marginal prior and posterior distributions be carefully compared, especially for parameters of direct interest. Finally, we note that the results presented here do not refute the biological modelling concerns identified by Beaulieu et al. (2015). Both sets of issues remain apposite to the goals of accurate divergence time estimation, and only by considering them in tandem can we move forward more confidently. [marginal priors; information content; diptych; divergence time estimation; fossil record; BEAST; angiosperms.]

evolutionary biology↗

bioRxiv2018

De novo protein structure prediction using ultra-fast molecular dynamics simulation

Modern genomics sequencing techniques have provided a massive amount of protein sequences, but experimental endeavor in determining protein structures is largely lagging far behind the vast and unexplored sequences. Apparently, computational biology is playing a more important role in protein structure prediction than ever. Here, we present a system of de novo predictor, termed NiDelta, building on a deep convolutional neural network and statistical potential enabling molecular dynamics simulation for modeling protein tertiary structure. Combining with evolutionary-based residue-contacts, the presented predictor can predict the tertiary structures of a number of target proteins with remarkable accuracy. The proposed approach is demonstrated by calculations on a set of eighteen large proteins from different fold classes. The results show that the ultra-fast molecular dynamics simulation could dramatically reduce the gap between the sequence and its structure at atom level, and it could also present high efficiency in protein structure determination if sparse experimental data is available.

bioinformatics↗

bioRxiv2017

Structure Of Allium Lachrymatory Factor Synthase Elucidates Catalysis On Sulfenic Acid Substrate

Natural lachrymatory effects are invoked by small volatile S-oxide compounds. They are produced through alkene sulfenic acids by the action of lachrymatory factor synthase (LFS). Here we present the crystal structures of onion LFS (AcLFS) revealed in solute-free and two solute-stabilized forms. Each structure adopts a single seven-stranded helix-grip fold possessing an internal pocket. Mutagenesis analysis localized the active site to a layer near the bottom of the pocket, which is adjacent to the deduced key residues Arg71, Glu88, and Tyr114. Solute molecules visible on the active site have suggested that AcLFS accepts various small alcohol compounds as well as its natural substrate, and they inhibit this substrate according to their chemistry. Structural homologs have been found in the SRPBCC superfamily, and comparison of the active sites has demonstrated that the electrostatic potential unique to AcLFS could work in capturing the substrate in its specific state. Finally, we propose a rational catalytic mechanism based on intramolecular proton shuttling in which the microenvironment of AcLFS can bypass the canonical [1,4]-sigmatropic rearrangement principle established by microwave studies. Beyond revealing how AcLFS generates the lachrymatory compound, this study provides insights into the molecular machinery dealing with highly labile organosulfur species.\n\nSignificance statementCrushing of onion liberates a volatile compound, syn-propanethial S-oxide (PTSO), which causes lachrymatory effect on humans. We present the crystal structures of onion LFS (AcLFS), the enzyme responsible for natural production of PTSO. AcLFS features a barrel-like fold, and mutagenic and inhibitory analyses revealed that the key residues are present in the central pocket, harboring highly concentrated aromatic residues plus a dyad motif. The architecture of AcLFS is widespread among proteins with various biological functions, such as abscisic acid receptors and polyketide cyclases, and comparisons with these homologs indicate that unique steric and electronic properties maintain the pocket as a reaction compartment. We propose the molecular mechanism behind PTSO generation and shed light on biological decomposition of short-lived sulfur species.

biochemistry↗

bioRxiv2018

A molecular model of the surface-assisted protein aggregation process

The importance of cell surfaces in the self-assembly of proteins is widely accepted. One biologically significant event is the assembly of amyloidogenic proteins into aggregates, which leads to neurodegenerative disorders like Alzheimers and Parkinsons. The interaction of amyloidogenic proteins with cellular membranes appears to dramatically facilitate the aggregation process. Recent findings indicate that, in the presence of surfaces, aggregation occurs at physiologically low concentrations, suggesting interaction with surfaces plays a critical role in the disease-prone aggregation process. However, the molecular mechanisms behind on-surface aggregation remain unclear. Here we provide a theoretical model that offers a molecular explanation. According to this model, monomers transiently immobilized to surfaces increase the local monomer protein concentration and thus work as nuclei to dramatically accelerate the entire aggregation process. This theory was verified by experimental studies, using mica surfaces, to examine the aggregation kinetics of amyloidogenic-synuclein protein (-Syn) and non-amyloidogenic cytosine deaminase APOBEC3G (A3G).

biophysics↗

bioRxiv2018

A Toolbox for Discrete Modelling of Cell Signalling Dynamics

In an age where the volume of data regarding biological systems exceeds our ability to analyse it, many researchers are looking towards systems biology and computational modelling to help unravel the complexities of gene and protein regulatory networks. In particular, the use of discrete modelling allows generation of signalling networks in the absence of full quantitative descriptions of systems, which are necessary for ordinary differential equation (ODE) models. In order to make such techniques more accessible to mainstream researchers, tools such as the BioModelAnalyzer (BMA) have been developed to provide a user-friendly graphical interface for discrete modelling of biological systems. Here we use the BMA to build a library of discrete target functions of known canonical molecular interactions, translated from ordinary differential equations (ODEs). We then show that these BMA target functions can be used to reconstruct complex networks, which can correctly predict many known genetic perturbations. This new library supports the accessibility ethos behind the creation of BMA, providing a toolbox for the construction of complex cell signalling models without the need for extensive experience in computer programming or mathematical modelling, and allows for construction and simulation of complex biological systems with only small amounts of quantitative data.\n\nAUTHOR SUMMARYOrdinary differential equation (ODE) based models are a popular approach for modelling biological networks. A limitation of ODE models is that they require complete networks and detailed kinetic parameterisation. An alternative is the use of discrete, executable models, in which nodes are assigned discrete value ranges, and the relationship between them defined with simple mathematical operations. One tool for constructing such models is the BioModelAnalyzer (BMA), an open source and publicly available (https://www.biomodelanalyzer.org) software, aimed to be fully usable by researchers without extensive computational or mathematical experience. A fundamental question for executable models is whether the high level of abstraction substantially reduces expressivity relative to continuous approaches. Here, we present a canonical library of biological signalling motifs, initially defined by Tyson et al (2003), translated for the first time into the BMA. We show that; 1) these motifs are easily and fully translatable from continuous to discrete models, 2) Combining these motifs in a computationally naive way generates a fully functional and predictive model of the yeast cell cycle.

systems biology↗

bioRxiv2018

A synthetic biology platform for the reconstitution and mechanistic dissection of LINC complex assembly

The linker of nucleoskeleton and cytoskeleton (LINC) is a conserved nuclear envelope-spanning molecular bridge that is responsible for the mechanical integration of the nucleus with the cytoskeleton. LINC complexes are formed by a transluminal interaction between the outer and inner nuclear membrane KASH and SUN proteins, respectively. Despite recent structural insights, our mechanistic understanding of LINC complex assembly remains limited by the lack of an experimental system for its in vitro reconstitution and manipulation. Here, we describe artificial nuclear membranes (ANMs) as a synthetic biology platform based on mammalian cell-free expression for the rapid reconstitution of SUN proteins in supported lipid bilayers. We demonstrate that SUN1 and SUN2 are oriented in ANMs with solvent-exposed C-terminal KASH-binding SUN domains. We also find that SUN2 possesses a single transmembrane domain, while SUN1 possesses three. Finally, SUN protein-containing ANMs bind synthetic KASH peptides, thereby reconstituting the LINC complex core. This work represents the first in vitro reconstitution of KASH-binding SUN proteins in supported lipid bilayers using cell-free expression, which will be invaluable for testing proposed models of LINC complex assembly and its regulation.

synthetic biology↗

bioRxiv2015

Diversity of immune strategies explained by adaptation to pathogen statistics

Biological organisms have evolved a wide range of immune mechanisms to defend themselves against pathogens. Beyond molecular details, these mechanisms differ in how protection is acquired, processed and passed on to subsequent generations - differences that may be essential to long-term survival. Here, we introduce a mathematical framework to compare the long-term adaptation of populations as a function of the pathogen dynamics that they experience and of the immune strategy that they adopt. We find that the two key determinants of an optimal immune strategy are the frequency and the characteristic timescale of the pathogens. Depending on these two parameters, our framework identifies distinct modes of immunity, including adaptive, innate, bet-hedging and CRISPR-like immunities, which recapitulate the diversity of natural immune systems.

Evolutionary Biology↗

bioRxiv2018

Fast and Flexible GPU Accelerated Binding Free Energy Calculations within the AMBER Molecular Dynamics Package

Alchemical free energy calculations (AFE) based on molecular dynamics (MD) simulations are key tools in both improving our understanding of a wide variety of biological processes and accelerating the design and optimization of therapeutics for numerous diseases. Computing power and theory have, however, long been insufficient to enable AFE calculations to be routinely applied in early stage drug discovery. One of the major difficulties in performing AFE calculations is the length of time required for calculations to converge to an ensemble average. CPU implementations of MD based free energy algorithms can effectively only reach tens of nanoseconds per day for systems on the order of 50,000 atoms, even running on massively parallel supercomputers. Therefore, converged free energy calculations on large numbers of potential lead compounds are often untenable, preventing researchers from gaining crucial insight into molecular recognition, potential druggability, and other crucial areas of interest. Graphics Processing Units (GPUs) can help address this. We present here a seamless GPU implementation, within the PMEMD module of the AMBER molecular dynamics package, of thermodynamic integration (TI) capable of reaching speeds of >140 ns/day for a 44,907-atom system, with accuracy equivalent to the existing CPU implementation in AMBER. The implementation described here is currently part of the AMBER 18 beta code and will be an integral part of the upcoming version 18 release of AMBER.

biophysics↗

bioRxiv2014

SINGLE NUCLEOTIDE POLYMORPHISMS SHED LIGHT ON CORRELATIONS BETWEEN ENVIRONMENTAL VARIABLES AND ADAPTIVE GENETIC DIVERGENCE AMONG POPULATIONS IN ONCORHYNCHUS KETA

Identifying the genetic and ecological basis of adaptation is of immense importance in evolutionary biology. In our study, we applied a panel of 58 biallelic single nucleotide polymorphisms (SNPs) for the economically and culturally important salmonid Oncorhynchus keta. Samples included 4164 individuals from 43 populations ranging from Coastal Western Alaska to southern British Colombia and northern Washington. Signatures of natural selection were detected by identifying seven outlier loci using two independent approaches: one based on outlier detection and another based on environmental correlations. Evidence of divergent selection at two candidate SNP loci, Oke_RFC2-168 and Oke_MARCKS-362, indicates significant environmental correlations, particularly with the number of frost-free days (NFFD). Important associations found between environmental variables and outlier loci indicate that those environmental variables could be the major driving forces of allele frequency divergence at the candidate loci. NFFD, in particular, may play an important adaptive role in shaping genetic variation in O. keta. Correlations between divergent selection and local environmental variables will help shed light on processes of natural selection and molecular adaptation to local environmental conditions.

Evolutionary Biology↗