Real-time assessment of mitochondrial DNA heteroplasmy dynamics at the single-cell level.

Mitochondrial DNA (mtDNA) is present in multiple copies within cells and is required for mitochondrial ATP generation. Even within individual cells, mtDNA copies can differ in their sequence, a state known as heteroplasmy. The principles underlying dynamic changes in the degree of heteroplasmy remain incompletely understood, due to the inability to monitor this phenomenon in real time. Here, we employ mtDNA-based fluorescent markers, microfluidics, and automated cell tracking, to follow mtDNA variants in live heteroplasmic yeast populations at the single-cell level. This approach, in combination with direct mtDNA tracking and data-driven mathematical modeling reveals asymmetric partitioning of mtDNA copies during cell division, as well as limited mitochondrial fusion and fission frequencies, as critical driving forces for mtDNA variant segregation. Given that our approach also facilitates assessment of segregation between intact and mutant mtDNA, we anticipate that it will be instrumental in elucidating the mechanisms underlying the purifying selection of mtDNA.

Evolution of Chromosomal Inversions across an Avian Radiation.

Chromosomal inversions are structural mutations that can play a prominent role in adaptation and speciation. Inversions segregating across species boundaries (trans-species inversions) are often taken as evidence for ancient balancing selection or adaptive introgression, but can also be due to incomplete lineage sorting. Using whole-genome resequencing data from 18 populations of 11 recognized munia species in the genus Lonchura (N = 176 individuals), we identify four large para- and pericentric inversions ranging in size from 4 to 20 Mb. All four inversions cosegregate across multiple species and predate the numerous speciation events associated with the rapid radiation of this clade across the prehistoric Sahul (Australia, New Guinea) and Bismarck Archipelago. Using coalescent theory, we infer that trans-specificity is improbable for neutrally segregating variation despite substantial incomplete lineage sorting characterizing this young radiation. Instead, the maintenance of all three autosomal inversions (chr1, chr5, and chr6) is best explained by selection acting along ecogeographic clines not observed for the collinear parts of the genome. In addition, the sex chromosome inversion largely aligns with species boundaries and shows signatures of repeated positive selection for both alleles. This study provides evidence for trans-species inversion polymorphisms involved in both adaptation and speciation. It further highlights the importance of informing selection inference using a null model of neutral evolution derived from the collinear part of the genome.

German Ixodes inopinatus samples may not actually represent this tick species.

Ticks are important vectors of human and animal pathogens, but many questions remain unanswered regarding their taxonomy. Molecular sequencing methods have allowed research to start understanding the evolutionary history of even closely related tick species. Ixodes inopinatus is considered a sister species and highly similar to Ixodes ricinus, an important vector of many tick-borne pathogens in Europe, but identification between these species remains ambiguous with disagreement on the geographic extent of I. inopinatus. In 2018-2019, 1583 ticks were collected from breeding great tits (Parus major) in southern Germany, of which 45 were later morphologically identified as I. inopinatus. We aimed to confirm morphological identification using molecular tools. Utilizing two genetic markers (16S rRNA, TROSPA) and whole genome sequencing of specific ticks (n = 8), we were able to determine that German samples, morphologically identified as I. inopinatus, genetically represent I. ricinus regardless of previous morphological identification, and most likely are not I. ricinus/I. inopinatus hybrids. Further, our results showed that the entire mitochondrial genome, let alone singular mitochondrial genes (i.e., 16S), is unable to distinguish between I. ricinus and I. inopinatus. Our results suggest that I. inopinatus is geographically isolated as a species (northern Africa and potentially southern Spain and Portugal) and brings into question whether I. inopinatus exists in central Europe. Our results highlight the probable existence of I. inopinatus and the power of utilizing genomic data in answering questions regarding tick taxonomy.

Human disturbance increases coronavirus prevalence in bats.

Human land modification is a known driver of animal-to-human transmission of infectious agents (zoonotic spillover). Infection prevalence in the reservoir is a key predictor of spillover, but landscape-level associations between the intensity of land modification and infection rates in wildlife remain largely untested. Bat-borne coronaviruses have caused three major disease outbreaks in humans: severe acute respiratory syndrome (SARS), Middle East respiratory syndrome, and coronavirus disease 2019 (COVID-19). We statistically link high-resolution land modification data with bat coronavirus surveillance records and show that coronavirus prevalence significantly increases with the intensity of human impact across all climates and levels of background biodiversity. The most significant contributors to the overall human impact are agriculture, deforestation, and mining. Regions of high predicted bat coronavirus prevalence coincide with global disease hotspots, suggesting that infection prevalence in wildlife may be an important factor underlying links between human land modification and zoonotic disease emergence.

Fusion gene detection by RNA-sequencing complements diagnostics of acute myeloid leukemia and identifies recurring NRIP1-MIR99AHG rearrangements.

Identification of fusion genes in clinical routine is mostly based on cytogenetics and targeted molecular genetics, such as metaphase karyotyping, fluorescence in situ hybridization and reverse-transcriptase polymerase chain reaction. However, sequencing technologies are becoming more important in clinical routine as processing time and costs per sample decrease. To evaluate the performance of fusion gene detection by RNAsequencing compared to standard diagnostic techniques, we analyzed 806 RNA-sequencing samples from patients with acute myeloid leukemia using two state-of-the-art software tools, namely Arriba and FusionCatcher. RNA-sequencing detected 90% of fusion events that were reported by routine with high evidence, while samples in which RNA-sequencing failed to detect fusion genes had overall lower and inhomogeneous sequence coverage. Based on properties of known and unknown fusion events, we developed a workflow with integrated filtering strategies for the identification of robust fusion gene candidates by RNA-sequencing. Thereby, we detected known recurrent fusion events in 26 cases that were not reported by routine and found discrepancies in evidence for known fusion events between routine and RNA-sequencing in three cases. Moreover, we identified 157 fusion genes as novel robust candidates and comparison to entries from ChimerDB or Mitelman Database showed novel recurrence of fusion genes in 14 cases. Finally, we detected the novel recurrent fusion gene NRIP1- MIR99AHG resulting from inv(21)(q11.2;q21.1) in nine patients (1.1%) and LTN1-MX1 resulting from inv(21)(q21.3;q22.3) in two patients (0.25%). We demonstrated that NRIP1-MIR99AHG results in overexpression of the 3' region of MIR99AHG and the disruption of the tricistronic miRNA cluster miR-99a/let-7c/miR-125b-2. Interestingly, upregulation of MIR99AHG and deregulation of the miRNA cluster, residing in the MIR99AHG locus, are known mechanisms of leukemogenesis in acute megakaryoblastic leukemia. Our findings demonstrate that RNA-sequencing has a strong potential to improve the systematic detection of fusion genes in clinical applications and provides a valuable tool for fusion discovery.

Assortative mating and epistatic mating-trait architecture induce complex movement of the crow hybrid zone.

Hybrid zones provide a window into the evolutionary processes governing species divergence. Yet, the contribution of mate choice to the temporal and spatial stability of hybrid zones remains poorly explored. Here, we investigate the effects of assortative mating on hybrid-zone dynamics by means of a mathematical model parameterized with phenotype and genotype data from the hybrid zone between all-black carrion and gray-coated hooded crows. In the best-fit model, narrow clines of the two mating-trait loci were maintained by a moderate degree of assortative mating inducing pre- and postzygotic isolation via positive frequency-dependent selection. Epistasis between the two loci induced hybrid-zone movement in favor of alleles conveying dark plumage followed by a shift in the opposite direction favoring gray-coated phenotypes ∼1 200 generations after secondary contact. Unlinked neutral loci diffused near-unimpeded across the zone. These results were generally robust to the choice of matching rule (self-referencing or parental imprinting) and effects of genetic drift. Overall, this study illustrates under which conditions assortative mating can maintain steep clines in mating-trait loci without generalizing to genome-wide reproductive isolation. It further emphasizes the importance of the genetic mating-trait architecture for spatio-temporal hybrid-zone dynamics.

Neoptile feathers contribute to outline concealment of precocial chicks.

Camouflage is a widespread strategy to increase survival. The cryptic plumage colouration of precocial chicks improves camouflage often through disruptive colouration. Here, we examine whether and how fringed neoptile feathers conceal the outline of chicks. We first conducted a digital experiment to test two potential mechanisms for outline concealment through appendages: (1) reduction of edge intensity and (2) luminance transition. Local Edge Intensity Analysis showed that appendages decreased edge intensity whereas a mean luminance comparison revealed that the appendages created an intermediate transition zone to conceal the object's outline. For edge intensity, the outline diffusion was strongest for a vision system with low spatial acuity, which is characteristic of many mammalian chick predators. We then analysed photographs of young snowy plover (Charadrius nivosus) chicks to examine whether feathers increase outline concealment in a natural setting. Consistent with better camouflage, the outline of digitally cropped chicks with protruding feathers showed lower edge intensities than the outline of chicks without those feathers. However, the observed mean luminance changes did not indicate better concealment. Taken together, our results suggest that thin skin appendages such as neoptile feathers improve camouflage. As skin appendages are widespread, this mechanism may apply to many organisms.

Modeling methylation dynamics with simultaneous changes in CpG islands.

BACKGROUND: In vertebrate genomes, CpG sites can be clustered into CpG islands, and the amount of methylation in a CpG island can change due to gene regulation processes. Thus, single regulatory events can simultaneously change the methylation states of many CpG sites within a CpG island. This should be taken into account when quantifying the amount of change in methylation, for example in form of a branch length in a phylogeny of cell types. RESULTS: We propose a probabilistic model (the IWE-SSE model) of methylation dynamics that accounts for simultaneous methylation changes in multiple CpG sites belonging to the same CpG island. We further propose a Markov-chain Monte-Carlo (MCMC) method to fit this model to methylation data from cell type phylogenies and apply this method to available data from murine haematopoietic cells and from human cell lines. Combined with simulation studies, these analyses show that accounting for CpG island wide methylation changes has a strong effect on the inferred branch lengths and leads to a significantly better model fit for the methylation data from murine haematopoietic cells and human cell lines. CONCLUSION: The MCMC based parameter estimation method for the IWE-SSE model in combination with our MCMC based inference method allows to quantify the amount of methylation changes at single CpG sites as well as on entire CpG islands. Accounting for changes affecting entire islands can lead to more accurate branch length estimation in the presence of simultaneous methylation change.

MMARGE: Motif Mutation Analysis for Regulatory Genomic Elements.

Cell-specific patterns of gene expression are determined by combinatorial actions of sequence-specific transcription factors at cis-regulatory elements. Studies indicate that relatively simple combinations of lineage-determining transcription factors (LDTFs) play dominant roles in the selection of enhancers that establish cell identities and functions. LDTFs require collaborative interactions with additional transcription factors to mediate enhancer function, but the identities of these factors are often unknown. We have shown that natural genetic variation between individuals has great utility for discovering collaborative transcription factors. Here, we introduce MMARGE (Motif Mutation Analysis of Regulatory Genomic Elements), the first publicly available suite of software tools that integrates genome-wide genetic variation with epigenetic data to identify collaborative transcription factor pairs. MMARGE is optimized to work with chromatin accessibility assays (such as ATAC-seq or DNase I hypersensitivity), as well as transcription factor binding data collected by ChIP-seq. Herein, we provide investigators with rationale for each step in the MMARGE pipeline and key differences for analysis of datasets with different experimental designs. We demonstrate the utility of MMARGE using mouse peritoneal macrophages, liver cells, and human lymphoblastoid cells. MMARGE provides a powerful tool to identify combinations of cell type-specific transcription factors while simultaneously interpreting functional effects of non-coding genetic variation.

Analysis of Genetically Diverse Macrophages Reveals Local and Domain-wide Mechanisms that Control Transcription Factor Binding and Function.

Non-coding genetic variation is a major driver of phenotypic diversity and allows the investigation of mechanisms that control gene expression. Here, we systematically investigated the effects of >50 million variations from five strains of mice on mRNA, nascent transcription, transcription start sites, and transcription factor binding in resting and activated macrophages. We observed substantial differences associated with distinct molecular pathways. Evaluating genetic variation provided evidence for roles of ∼100 TFs in shaping lineage-determining factor binding. Unexpectedly, a substantial fraction of strain-specific factor binding could not be explained by local mutations. Integration of genomic features with chromatin interaction data provided evidence for hundreds of connected cis-regulatory domains associated with differences in transcription factor binding and gene expression. This system and the >250 datasets establish a substantial new resource for investigation of how genetic variation affects cellular phenotypes.

Genetic Allee effects and their interaction with ecological Allee effects.

It is now widely accepted that genetic processes such as inbreeding depression and loss of genetic variation can increase the extinction risk of small populations. However, it is generally unclear whether extinction risk from genetic causes gradually increases with decreasing population size or whether there is a sharp transition around a specific threshold population size. In the ecological literature, such threshold phenomena are called 'strong Allee effects' and they can arise for example from mate limitation in small populations. In this study, we aim to (i) develop a meaningful notion of a 'strong genetic Allee effect', (ii) explore whether and under what conditions such an effect can arise from inbreeding depression due to recessive deleterious mutations, and (iii) quantify the interaction of potential genetic Allee effects with the well-known mate-finding Allee effect. We define a strong genetic Allee effect as a genetic process that causes a population's survival probability to be a sigmoid function of its initial size. The inflection point of this function defines the critical population size. To characterize survival-probability curves, we develop and analyse simple stochastic models for the ecology and genetics of small populations. Our results indicate that inbreeding depression can indeed cause a strong genetic Allee effect, but only if individuals carry sufficiently many deleterious mutations (lethal equivalents). Populations suffering from a genetic Allee effect often first grow, then decline as inbreeding depression sets in and then potentially recover as deleterious mutations are purged. Critical population sizes of ecological and genetic Allee effects appear to be often additive, but even superadditive interactions are possible. Many published estimates for the number of lethal equivalents in birds and mammals fall in the parameter range where strong genetic Allee effects are expected. Unfortunately, extinction risk due to genetic Allee effects can easily be underestimated as populations with genetic problems often grow initially, but then crash later. Also interactions between ecological and genetic Allee effects can be strong and should not be neglected when assessing the viability of endangered or introduced populations.

Transcriptomic and macroevolutionary evidence for phenotypic uncoupling between frog life history phases.

Anuran amphibians undergo major morphological transitions during development, but the contribution of their markedly different life-history phases to macroevolution has rarely been analysed. Here we generate testable predictions for coupling versus uncoupling of phenotypic evolution of tadpole and adult life-history phases, and for the underlying expression of genes related to morphological feature formation. We test these predictions by combining evidence from gene expression in two distantly related frogs, Xenopus laevis and Mantidactylus betsileanus, with patterns of morphological evolution in the entire radiation of Madagascan mantellid frogs. Genes linked to morphological structure formation are expressed in a highly phase-specific pattern, suggesting uncoupling of phenotypic evolution across life-history phases. This gene expression pattern agrees with uncoupled rates of trait evolution among life-history phases in the mantellids, which we show to have undergone an adaptive radiation. Our results validate a prevalence of uncoupling in the evolution of tadpole and adult phenotypes of frogs.

PERGOLA: fast and deterministic linkage mapping of polyploids.

BACKGROUND: A large share of agriculturally and horticulturally important plant species are polyploid. Linkage maps are used to locate associations between genes and traits by breeders and geneticists. Linkage map creation for polyploid species is not supported by standard tools. We want to overcome this limitation and validate our results with simulation studies. RESULTS: We developed PERGOLA, a deterministic and heuristic method that addresses this problem. We show that it creates correct linkage groups, marker orders and distances for simulated and real datasets. We compare it to existing tools and demonstrate that it overcomes limitations in ploidy and outperforms them in computational time and mapping accuracy. We represent linkage maps as dendrograms and show that this has advantages in the comparison of different maps. CONCLUSIONS: PERGOLA can be used successfully to calculate linkage maps for diploid and polyploid species and outperforms existing tools.

Advantages of continuous genotype values over genotype classes for GWAS in higher polyploids: a comparative study in hexaploid chrysanthemum.

BACKGROUND: Association studies are an essential part of modern plant breeding, but are limited for polyploid crops. The increased number of possible genotype classes complicates the differentiation between them. Available methods are limited with respect to the ploidy level or data producing technologies. While genotype classification is an established noise reduction step in diploids, it gains complexity with increasing ploidy levels. Eventually, the errors produced by misclassifications exceed the benefits of genotype classes. Alternatively, continuous genotype values can be used for association analysis in higher polyploids. We associated continuous genotypes to three different traits and compared the results to the output of the genotype caller SuperMASSA. Linear, Bayesian and partial least squares regression were applied, to determine if the use of continuous genotypes is limited to a specific method. A disease, a flowering and a growth trait with h (2) of 0.51, 0.78 and 0.91 were associated with a hexaploid chrysanthemum genotypes. The data set consisted of 55,825 probes and 228 samples. RESULTS: We were able to detect associating probes using continuous genotypes for multiple traits, using different regression methods. The identified probe sets were overlapping, but not identical between the methods. Baysian regression was the most restrictive method, resulting in ten probes for one trait and none for the others. Linear and partial least squares regression led to numerous associating probes. Association based on genotype classes resulted in similar values, but missed several significant probes. A simulation study was used to successfully validate the number of associating markers. CONCLUSIONS: Association of various phenotypic traits with continuous genotypes is successful with both uni- and multivariate regression methods. Genotype calling does not improve the association and shows no advantages in this study. Instead, use of continuous genotypes simplifies the analysis, saves computational time and results more potential markers.

Coala: an R framework for coalescent simulation.

UNLABELLED: Simulation programs based on the coalescent efficiently generate genetic data according to a given model of evolution. We present coala, an R package for calling coalescent simulators with a unified syntax. It can execute simulations with several programs, calculate additional summary statistics and combine multiple simulations to create biologically more realistic data. AVAILABILITY AND IMPLEMENTATION: The package is publicly available on CRAN and on https://github.com/statgenlmu/coala under the conditions of the MIT license. CONTACT: metzler@bio.lmu.de.

Strawberry Accessions with Reduced Drosophila suzukii Emergence From Fruits.

Drosophila suzukii is threatening soft fruit production worldwide due to the females' ability to pierce through the intact skin of ripe fruits and lay eggs inside. Larval consumption and the associated microbial infection cause rapid fruit degradation, thus drastic yield and economic loss. Cultivars that limit the proliferation of flies may be ideal to counter this pest; however, they have not yet been developed or identified. To search for potential breeding material, we investigated the rate of adult D. suzukii emergence from individual fruits (fly emergence) of 107 accessions of Fragaria species that had been exposed to egg-laying D. suzukii females. We found significant variation in fly emergence across strawberries, which correlated with accession and fruit diameter, and to a lesser extent with the strawberry species background. We identified accessions with significantly reduced fly emergence, not explained by their fruit diameter. These accessions constitute valuable breeding material for strawberry cultivars that limit D. suzukii spread.

NGS population genetics analyses reveal divergent evolution of a Lyme Borreliosis agent in Europe and Asia.

Borrelia bavariensis is a recently described agent of Lyme disease within the B. burgdorferi sensu lato species complex and exhibits a strong capacity for human pathogenicity. B. bavariensis strains are widely distributed in Eurasia spanning the distribution range of the tick vectors Ixodes persulcatus and I. ricinus. It has been suggested that B. bavariensis forms two populations, one of which arose through vector adaptation and geographic expansion. We have performed phylogenetic and population genetic analyses with next-generation sequencing data of 26 strains of B. bavariensis targeting the main linear chromosome and two plasmids (lp54, cp26). A very low number of single nucleotide polymorphisms (SNPs) was found in the European population and a deep branching pattern between European and Asian B. bavariensis was observed in all phylogenies. The results confirm the population structure of B. bavariensis and strongly support the hypothesis of clonal expansion of the European population of B. bavariensis. In addition, signals of positive selection identified in the populations further support the hypothesis that the European population of B. bavariensis likely underwent vector adaptation in its recent evolutionary history. Identified genes represent promising candidates for experimental vector adaptation studies. Thus, this species forms a very good model to study vector adaptation, which is known to play an important role in the geographic distribution of B. burgdorferi. Analysis of well known virulence determinants that are attributed to severity of clinical manifestation in B. burgdorferi s.s. revealed no variation within the European population of B. bavariensis, underlining the importance of including various Borrelia species into investigations that aim to understand the pathogenesis of Lyme disease agents.

Modeling shortest path selection of the ant Linepithema humile using psychophysical theory and realistic parameter values.

The emergence of self-organizing behavior in ants has been modeled in various theoretical approaches in the past decades. One model explains experimental observations in which Argentine ants (Linepithema humile) selected the shorter of two alternative paths from their nest to a food source (shortest path experiments). This model serves as an important example for the emergence of collective behavior and self-organization in biological systems. In addition, it inspired the development of computer algorithms for optimization problems called ant colony optimization (ACO). In the model, a choice function describing how ants react to different pheromone concentrations is fundamental. However, the parameters of the choice function were not deduced experimentally but freely adapted so that the model fitted the observations of the shortest path experiments. Thus, important knowledge was lacking about crucial model assumptions. A recent study on the Argentine ant provided this information by measuring the response of the ants to varying pheromone concentrations. In said study, the above mentioned choice function was fitted to the experimental data and its parameters were deduced. In addition, a psychometric function was fitted to the data and its parameters deduced. Based on these findings, it is possible to test the shortest path model by applying realistic parameter values. Here we present the results of such tests using Monte Carlo simulations of shortest path experiments with Argentine ants. We compare the choice function and the psychometric function, both with parameter values deduced from the above-mentioned experiments. Our results show that by applying the psychometric function, the shortest path experiments can be explained satisfactorily by the model. The study represents the first example of how psychophysical theory can be used to understand and model collective foraging behavior of ants based on trail pheromones. These findings may be important for other models of pheromone guided ant behavior and might inspire improved ACO algorithms.

scrm: efficiently simulating long sequences using the approximated coalescent with recombination.

MOTIVATION: Coalescent-based simulation software for genomic sequences allows the efficient in silico generation of short- and medium-sized genetic sequences. However, the simulation of genome-size datasets as produced by next-generation sequencing is currently only possible using fairly crude approximations. RESULTS: We present the sequential coalescent with recombination model (SCRM), a new method that efficiently and accurately approximates the coalescent with recombination, closing the gap between current approximations and the exact model. We present an efficient implementation and show that it can simulate genomic-scale datasets with an essentially correct linkage structure.

ReformAlign: improved multiple sequence alignments using a profile-based meta-alignment approach.

BACKGROUND: Obtaining an accurate sequence alignment is fundamental for consistently analyzing biological data. Although this problem may be efficiently solved when only two sequences are considered, the exact inference of the optimal alignment easily gets computationally intractable for the multiple sequence alignment case. To cope with the high computational expenses, approximate heuristic methods have been proposed that address the problem indirectly by progressively aligning the sequences in pairs according to their relatedness. These methods however are not flexible to change the alignment of an already aligned group of sequences in the view of new data, resulting thus in compromises on the quality of the deriving alignment. In this paper we present ReformAlign, a novel meta-alignment approach that may significantly improve on the quality of the deriving alignments from popular aligners. We call ReformAlign a meta-aligner as it requires an initial alignment, for which a variety of alignment programs can be used. The main idea behind ReformAlign is quite straightforward: at first, an existing alignment is used to construct a standard profile which summarizes the initial alignment and then all sequences are individually re-aligned against the formed profile. From each sequence-profile comparison, the alignment of each sequence against the profile is recorded and the final alignment is indirectly inferred by merging all the individual sub-alignments into a unified set. The employment of ReformAlign may often result in alignments which are significantly more accurate than the starting alignments. RESULTS: We evaluated the effect of ReformAlign on the generated alignments from ten leading alignment methods using real data of variable size and sequence identity. The experimental results suggest that the proposed meta-aligner approach may often lead to statistically significant more accurate alignments. Furthermore, we show that ReformAlign results in more substantial improvement in cases where the starting alignment is of relatively inferior quality or when the input sequences are harder to align. CONCLUSIONS: The proposed profile-based meta-alignment approach seems to be a promising and computationally efficient method that can be combined with practically all popular alignment methods and may lead to significant improvements in the generated alignments.