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Results for “Genomics”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 811 records · Page 45Linked to original sources

bioRxiv2018

Genome-wide signatures of local adaptation among seven stoneflies species along a nationwide latitudinal gradient in Japan

BackgroundEnvironmental heterogeneity continuously produces a selective pressure that results in genomic variation among organisms; understanding this relationship remains a challenge in evolutionary biology. Here, we evaluated the degree of genome-environmental association of seven stonefly species across a wide geographic area in Japan and additionally identified putative environmental drivers and their effect on co-existing multiple stonefly species. Double-digest restriction-associated DNA (ddRAD) libraries were independently sequenced for 219 individuals from 23 sites across four geographical regions along a nationwide latitudinal gradient in Japan.\n\nResultsA total of 4,251 candidate single nucleotide polymorphisms (SNPs) strongly associated with local adaptation were discovered using Latent mixed models; of these, 294 SNPs showed strong correlation with environmental variables, specifically precipitation and altitude, using distance-based redundancy analysis. Genome-genome comparison among the seven species revealed a high sequence similarity of candidate SNPs within a geographical region, suggesting the occurrence of a parallel evolution process.\n\nConclusionsOur results revealed genomic signatures of local adaptation and their influence on multiple, co-occurring species. These results can be potentially applied for future studies on river management and climatic stressor impacts.

genomics↗

bioRxiv2018

Genome structure and evolution of Antirrhnum majus L.

Snapdragon (Antirrhinum majus L.), a member of Plantaginaceae, is an important model for plant genetics and molecular studies on plant growth and development, transposon biology and self-incompatibility. Here we report a high-quality genome assembly of A. majus cultivated JI7 (A. majus cv.JI7) of a 510 Mb with 37,714 annotated protein-coding genes. The scaffolds covering 97.12% of the assembled genome were anchored on 8 chromosomes. Comparative and evolutionary analyses revealed that Plantaginaceae and Solanaceae diverged from their most recent ancestor around 62 million years ago (MYA). We also revealed the genetic architectures associated with complex traits such as flower asymmetry and self-incompatibility including a unique TCP duplication around 46-49 MYA and a near complete{psi} S-locus of ca.2 Mb. The genome sequence obtained in this study not only provides the first genome sequenced from Plantaginaceae but also bring the popular plant model system of Antirrhinum into a genomic age.

genomics↗

bioRxiv2018

Identification of essential regulatory elements in the human genome

The identification of essential regulatory elements is central to the understanding of the consequences of genetic variation. Here we use novel genomic data and machine learning techniques to map essential regulatory elements and to guide functional validation. We train an XGBoost model using 38 functional and structural features, including genome essentiality metrics, 3D genome organization and enhancer reporter STARR-seq data to differentiate between pathogenic and control non-coding genetic variants. We validate the accuracy of prediction by using data from tiling-deletion-based and CRISPR interference screens of activity of cis-regulatory elements. In neurodevelopmental disorders, the model (ncER, non-coding Essential Regulation) maps essential genomic segments within deletions and rearranged topologically associated domains linked to human disease. We show that the approach successfully identifies essential regulatory elements in the human genome.

genomics↗

bioRxiv2018

DNA barcodes for rapid, whole genome, single-molecule analyses

We report an approach for visualizing DNA sequence and using these DNA barcodes to search complex mixtures of genomic material for DNA molecules of interest. We demonstrate three applications of this methodology; by identifying specific molecules of interest from a dataset containing gigabasepairs of genome; by straightforward strain-typing of bacteria from such a dataset and, finally, by locating infecting virus molecules in a background of human genomic material. DNA barcodes enable quantitative understanding of complex genome mixtures, on a large scale. As a result of the dense fluorescent labelling of the DNA, individual barcodes of the order 40 kilobase pairs in length can be reliably identified. This means DNA can be prepared for imaging using standard handling and purification techniques. The recorded dataset provides stable physical and electronic records of the total genomic content of a sample that can be readily searched for a molecule or region of interest.

genomics↗

bioRxiv2018

Generating a sequence map of the pig pan-genome

Pigs (Sus scrofa) exhibit diverse phenotypes in different breeds shaped by the combined effects of various local adaptation and artificial selection. To comprehensively characterize the genetic diversity of pigs, we construct a pig pan-genome by comparing genome assemblies of 11 representative pig breeds with the reference genome (Sscrofa11.1). Approximately 72.5 Mb non-redundant sequences were identified as pan-sequences which were absent from the Sscrofa11.1. On average, 41.7 kb of spurious heterozygous SNPs per individual are removed and 12.9 kb novel SNPs per individual are recovered using pan-genome as the reference for SNP calling, thereby providing enhanced resolution for genetic diversity in pigs. Homolog annotation and analysis using RNA-seq and Hi-C data indicate that these pan-sequences contain protein-coding regions and regulatory elements. These pan-sequences can further improve the interpretation of local 3D structure. The pan-genome as well as the accompanied web-based database will serve as a primary resource for exploration of genetic diversity and promote pig breeding and biomedical research.

genomics↗

bioRxiv2018

Early signals of vaccine driven perturbation seen in pneumococcal carriage population genomic data

Pneumococcal conjugate vaccines (PCV) have reduced pneumococcal diseases globally. Despite this, much remains to be learned about their effect on pathogen population structure. Here we undertook whole genome sequencing of 660 pneumococcal strains from asymptomatic carriers to investigate population restructuring in pneumococcal strains sampled before and after PCV13 introduction in a previously vaccine-naive setting. We show substantial decreasing frequency of vaccine-type (VT) strains and their strain diversity post-vaccination in the vaccinated but not unvaccinated age groups indicative of direct but limited or delayed indirect effect of vaccination. Clearance of identical VT serotypes associated with multiple lineages occurred regardless of their genetic background. Interestingly, despite the increasing frequency of non-vaccine type (NVT) strains through serotype replacement, the serotype diversity was not fully restored to the levels observed prior to vaccination implying limited serotype replacement. The frequency of antibiotic resistant strains was low and remained largely unchanged post-vaccination but intermediate-penicillin-resistant lineages were reduced in the post vaccine population. Significant perturbations marked by changing frequency of accessory genes associated with diverse functions especially mobile genetic elements and bacteriocin activity were detected. This phylogenomic analysis demonstrates early vaccine-induced pneumococcal population restructuring not only at serotype but also accessory genome level.\n\nAuthor summaryDifferent formulations of PCVs have been effective in reducing the invasive pneumococcal disease burden globally. Clinical trials have started to indicate high impact and effectiveness of PCV13 in Sub Saharan Africa (SSA) but there is limited understanding of how the introduction of PCVs alters the population structure of pneumococcal strains at serotype and genomic level. Here we investigated this using pneumococcal strains sampled pre- and post-PCV13 introduction from a previously vaccine naive setting in Northern Malawi. Our findings reveal decrease in frequency of VT serotypes and their associated lineages in the largely vaccinated under-five population but not older individuals indicating a direct but limited or delayed indirect protection. The diversity of serotypes also decreased post-vaccination in VT strains in the under-fives but there was no change in NVT strains suggesting incomplete serotype replacement. At the genomic level, logistic regression revealed changing frequency of accessory genes largely associated with mobile genetic elements but such changes did not include any antibiotic resistance genes. These findings show significant perturbations at serotype and accessory genome level in carried pneumococcal population after two years from PCV13 introduction but the pneumococcal population was still perturbed and had not returned to a new equilibrium state.

genomics↗

bioRxiv2018

Illumina and Nanopore methods for whole genome sequencing of hepatitis B virus (HBV)

Advancing interventions to tackle the huge global burden of hepatitis B virus (HBV) infection depends on improved insights into virus epidemiology, transmission, within-host diversity, drug resistance and pathogenesis, all of which can be facilitated by the large-scale generation of full-length virus genome data. Here we describe advances to a protocol to exploit the circular HBV genome structure, using isothermal rolling-circle amplification to enrich for HBV DNA and to generate concatemeric amplicons containing multiple successive copies of the same genome. We show that this product is suitable for Nanopore sequencing as single reads, as well as for generating short-read Illumina sequences. Nanopore reads can be used to implement a straightforward method for error correction that reduces the per-read error rate, by comparing multiple genome copies combined into a single concatemer and by comparing reads generated from plus and minus strands. Thus we can achieve improved consensus sequencing accuracy of 99.7% and resolve intra-sample sequence variants to form whole-genome haplotypes. The combination of isothermal amplification and Nanopore sequencing offers the longer-term potential to develop point-of-care tests for HBV, which could also be adapted for other viruses.

genomics↗

bioRxiv2018

High-quality assembly of sweet basil genome

Sweet basil, sometimes called the King of Herbs, is well known for its culinary uses, especially in the Italian sauce Pesto. It is also used in traditional medicine, as a source for essential oils and as an ornamental plant. So far, basil was bred by classical and traditional methods due to lack of a reference genome that will allow optimized application of the most up-to-date sequencing techniques. Here, we report on the first completion of the sweet basil genome of the cultivar Perrie, a fresh-cut Genovese-type basil, using several next generation sequencing platforms followed by genome assembly with NRGENEs DeNovoMAGIC assembly tool. We determined that the genome size of sweet basil is 2.13 Gbp and assembled it into 12,212 scaffolds. The high-quality of the assembly is reflected in that more than 90% of the assembly size is composed of only 107 scaffolds. An independent analysis of single copy orthologues genes showed a 93% completeness which reveal also that 74% of them were duplicated, indicating that the sweet basil is a tetraploid organism. A reference genome of sweet basil will enable to develop precise molecular markers for various agricultural important traits such as disease resistance and tolerance to various environmental conditions. We will gain a better understanding of the underlying mechanisms of various metabolic processes such as aroma production and pigment accumulation. Finally, it will save time and money for basil breeders and scientists and ensure higher throughput and robustness in future studies.

genomics↗

bioRxiv2018

Identification of large-scale genomic rearrangements during wheat evolution and the underlying mechanisms

Following allopolyploidization, nascent polyploid wheat species react with massive genomic rearrangements, including deletion of transposable element-containing sequences. While such massive rearrangements are considered to be a prominent process in wheat genome evolution and speciation, their structure, extent, and underlying mechanisms remain poorly understood. In this study, we retrieved ~3500 insertions of a specific variant of Fatima, one of the most dynamic long-terminal repeat retrotransposons in wheat from the recently available high-quality genome drafts of Triticum aestivum (bread wheat) and Triticum turgidum ssp. dicoccoides or wild emmer, the allotetraploid mother of all modern wheats. The dynamic nature of Fatima facilitated the identification of large (i.e., up to ~ 1 million bases) Fatima-containing insertions/deletions (InDels) upon comparison of bread wheat and wild emmer genomes. We characterized 11 such InDels using computer-assisted analysis followed by PCR validation, and found that they occurred via unequal intra-strand recombination or double-strand break events. In most cases, InDels breakpoints were located within transposable element sequences. Additionally, we observed one case of introgression of novel DNA fragments from an unknown source into the wheat genome. Our data thus indicate that massive large-scale DNA rearrangements might play a prominent role in wheat speciation.

genomics↗

bioRxiv2018

Genome-wide analysis of drug resistant Mycobacterium tuberculosis isolates causing pulmonary and extrapulmonary tuberculosis in Russia

Mycobacterium tuberculosis is a highly studied pathogen due to public health importance. Despite progress in M.tuberculosis genome diversity analysis there remain insufficient data on genome analysis of M.tuberculosis strains associated with pulmonary vs. extrapulmonary TB (PTB or XPTB respectively) tissue localization. Here we conduct comparative analysis of whole-genome sequence (WGS) for clinical M.tuberculosis strains collected from patients with PTB (n=72) and XPTB (n=73) localization. We further analyze the incidence of point mutations widely used for drug resistance detection in laboratory practice.\n\nM.tuberculosis isolates were collected from patients with varying clinical status from 2007 to 2014 in Russia. Bacterial DNA was extracted and sequenced using MiSeq platform (Illumina).\n\nWGS data allowed identifying M.tuberculosis substrains associated with distinctions in the occurrence in PTB v s. XPTB cases. There occurred little statistically significant specific DNA variants or genotypes diagnostic of tissue distribution, however phylogenetic analyses did reveal M.tuberculosis genetic substrains associated with TB localization. XPTB was associated with Beijing CAO, A and 4.8 groups, while PTB localization was associated with group LAM (4.3). Further, XPTB strain in some cases showed elevated drug resistance patterns relative to PTB isolates. HIV is significantly associated with the development of XPTB in the Beijing B0/W148 group and among unclustered Beijing isolates.\n\nThis research analysis pinpointed genomic markers identified in XPTB and PTB with detailed characterization of drug-resistance markers of Russian M.tuberculosis isolates. We suggest that further comprehensive analysis of bacterial and human biological signatures might allow for better understanding consistent pattern of XPTB development.\n\nSummaryThis paper gives genome-wide characteristics of Mycobacterium tuberculosis strains collected from pulmonary and extrapulmonary tuberculosis patients:\n\n- M.tuberculosis genetic strains associated with TB tissue localization,\n\n- influence of HIV co-infection on TB dissemination;\n\n- mutations associated with M.tuberculosis drug resistance.

genomics↗

bioRxiv2018

Nanopore sequencing significantly improves genome assembly of the eukaryotic protozoan parasite Trypanosoma cruzi

Chagas disease was described by Carlos Chagas, who first identified the parasite Trypanosoma cruzi from a two-year-old girl called Berenice. Many T. cruzi sequencing projects based on short reads have demonstrated that genome assembly and downstream comparative analyses are extremely challenging in this species, given that half of its genome is composed of repetitive sequences. Here, we report de novo assemblies, annotation and comparative analyses of the Berenice strain using a combination of Illumina short reads and MinION long reads. Our work demonstrates that Nanopore sequencing improves T. cruzi assembly contiguity and increases the assembly size in ~16 Mb. Specifically, we found that assembly improvement also refines the completeness of coding regions for both single copy genes and repetitive transposable elements. Beyond its historical and epidemiological importance, Berenice constitutes a fundamental resource since it now represents the best-quality assembly available for TcII, a highly prevalent lineage causing human infections in South America. The availability of Berenice genome expands the known genetic diversity of T. cruzi and facilitates more comprehensive evolutionary inferences. Our work represents the first report of Nanopore technology used to resolve complex protozoan genomes, supporting its subsequent application for improving trypanosomatid and other highly repetitive genomes.

genomics↗

bioRxiv2018

Nucleosome positioning stability is a significant modulator of germline mutation rate variation across the human genome

Understanding the patterns and genesis of germline de novo mutations is important for studying genome evolution and human diseases. Nucleosome organization is suggested to be a contributing factor to mutation rate variation across the genome. However, the small number of published de novo mutations and the low resolution of earlier nucleosome maps limited our understanding of how nucleosome organization affects germline mutation rates in the human genome. Here, we systematically investigated the relationship between nucleosome organization and fine-scale mutation rate variation by analyzing >300,000 de novo mutations from whole-genome trio sequencing and high-resolution nucleosome maps in human. We found that de novo mutation rates are elevated around strong, translationally stable nucleosomes, a previously under-appreciated aspect. We confirmed this observation having controlled for local sequence context and other potential confounding factors. Analysis of the underlying mutational processes suggests that the increased mutation rates around strong nucleosomes are shaped by a combination of low-fidelity replication, frequent DNA damage and insufficient/error-prone repair in these regions. Interestingly, strong nucleosomes are preferentially located in young SINE/LINE elements, implying frequent nucleosome re-positioning (i.e. shifting of dyad position) and their contribution to hypermutation at new retrotransposons during evolution. These findings provide novel insights into how chromatin organization affects germline mutation rates and have important implications in human genetics and genome evolution.

genomics↗

bioRxiv2018

Microbial contamination in the genome of the domesticated olive

Draft genomes of both the wild and domesticated olive were recently published. While working with these genomes, we identified contamination in the domesticated olive genome representing .06% of basepairs and 1.3% of scaffolds. We used targeted and untargeted approaches to identify the contaminating sequences, the majority of which were Aureobasidium pullulans. We applied the same method to the wild olive genome and did not find evidence of contamination. Although contamination in the domesticated olive genome was not prolific, it could lead to biased results either from functional content encoded in the contaminant sequences, or from using it to separate microbial reads from olive reads in microbiome studies.

genomics↗

bioRxiv2018

Accurate tracking of the mutational landscape of diploid hybrid genomes reveals genetic background effects

BackgroundGenome evolution promotes diversity within a population via mutations, recombination, and whole-genome duplication. However, quantifying precisely these factors in diploid hybrid genomes is challenging. Here we present an integrated experimental and computational workflow to accurately track the mutational landscape of yeast diploid hybrids (MuLoYDH) in terms of single-nucleotide variants, small insertions/deletions, copy-number variants and loss-of-heterozygosity. ResultsHaploid Saccharomyces parents were combined into diploid hybrids with fully phased genome and controlled levels of heterozygosity. The resulting hybrids represented the ancestral state and were evolved under different laboratory protocols. Variant simulations enabled to efficiently integrate competitive and standard mapping, depending on local levels of heterozygosity and read length. Experimental validations proved high accuracy and resolution of our computational approach. Finally, applying MuLoYDH to four different diploids revealed striking genetic background effects. Homozygous S. cerevisiae showed ~4-fold higher mutation rate compared to S. paradoxus. In contrast, interspecies hybrids exhibited mutation rates similar to intraspecies hybrids despite 10-fold higher heterozygosity. MuLoYDH unveiled that a substantial fraction of the genome (~200 bp per generation) was shaped by loss-of-heterozygosity and this process was strongly inhibited by high levels of heterozygosity. ConclusionsWe report a comprehensive framework for characterizing the mutational spectrum of yeast diploid hybrids with unprecedented resolution, which can be generalised to other genetic systems. Applying MuLoYDH to laboratory-evolved hybrids provided novel quantitative insights into the evolutionary processes that mould yeast genomes.

genomics↗

bioRxiv2019

Vitamin D: marker, cause or consequence of depression? An exploration using genomics

BackgroundTrials testing the effect of vitamin D or omega-3 fatty acids (n3-PUFA) supplementation on major depressive disorder (MDD) reported conflicting findings. These trials were boosted by epidemiological evidence suggesting an inverse association of circulating 25-hydroxyvitamin D (25-OH-D) and n3-PUFA levels with MDD. Observational associations may emerge from unresolved confounding, shared genetic risk, or direct causal relationships. We explored the nature of these associations exploiting data and statistical tools from genomics. MethodsResults from GWAS on 25-OH-D (N = 79366), n3-PUFA (N = 24925) and MDD (135458 cases, 344901 controls) were applied to individual-level data (>2,000 subjects with measures of genotype, DSM-IV lifetime MDD diagnoses and circulating 25-OH-D and n3-PUFA) and summary-level data analyses. Shared genetic risk between traits was tested by polygenic risk scores (PRS). Two-sample Mendelian Randomization (2SMR) analyses tested the potential bidirectional causality between traits. OutcomeIn individual-level data, PRS were associated with the phenotype of the same trait (PRS 25-OH-D p = 1.4e-20, PRS N3-PUFA p = 9.3e-6, PRS MDD p = 1.4e-4), but not with the other phenotypes, suggesting a lack of shared genetic effects. In summary-level data, 2SMR analyses provided no evidence of a causal role on MDD of 25-OH-D (p = 0.50) or n3-PUFA (p = 0.16), or for a causal role of MDD on 25-OH-D (p = 0.25) or n3-PUFA (p = 0.66). ConclusionsApplying genomics tools indicated that that shared genetic risk or direct causality between 25-OH-D, n3-PUFA and MDD is unlikely: unresolved confounding may explain the associations reported in observational studies. These findings represent a cautionary tale for testing supplementation of these compounds in preventing or treating MDD. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSMeta-analyses of trials testing the effect of vitamin D or omega-3 fatty acids (n3-PUFA) supplementation on major depressive disorder (MDD) reported conflicting findings, including small clinical effect or no effect. These trials were boosted by epidemiological evidence suggesting an inverse association of circulating 25-hydroxyvitamin D (25-OH-D) and n3-PUFA levels with MDD. However, observational associations may emerge from different scenarios, including unresolved confounding, shared genetic risk, or direct causal relationships. Added value of this studyGenomics provides unique opportunities to investigate shared risk and causality between traits applying new statistical tools and results from genome-wide association studies (GWAS). In the present study we examined the nature of the association of 25-OH-D and n3-PUFA with MDD using the latest data and tools from genomics. We found no significant evidence of shared genetic risk or direct causality between vitamin D or n-3 PUFA and MDD; at this stage, unresolved confounding should be considered the most likely explanation for the association reported by observational studies. Implications of all the available evidenceFindings from the present study, in conjunction with previous conflicting evidence from clinical studies, represent a cautionary tale for further research testing the potential therapeutic effect of vitamin D and n3-PUFA supplementation on depression, as the expectations of a direct causal effect of these compounds on mood should be substantially reconsidered. Genomic tools could be efficiently employed to examine the nature of observational associations emerging in epidemiology, providing some indications on the most promising associations to be prioritized in subsequent intervention studies.

genomics↗

bioRxiv2014

Efficient synergistic single-cell genome assembly

As the vast majority of all microbes are unculturable, single-cell sequencing has become a significant method to gain insight into microbial physiology. Single-cell sequencing methods, currently powered by multiple displacement genome amplification (MDA), have passed important milestones such as finishing and closing the genome of a prokaryote. However, the quality and reliability of genome assemblies from single cells are still unsatisfactory due to uneven coverage depth and the absence of scattered chunks of the genome in the final collection of reads caused by MDA bias. In this work, our new algorithm Hybrid De novo Assembler (HyDA) demonstrates the power of co-assembly of multiple single-cell genomic data sets through significant improvement of the assembly quality in terms of predicted functional elements and length statistics. Co-assemblies contain significantly more base pairs and protein coding genes, cover more subsystems, and consist of longer contigs compared to individual assemblies by the same algorithm as well as state-of-the-art single-cell assemblers SPAdes and IDBA-UD. Hybrid De novo Assembler (HyDA) is also able to avoid chimeric assemblies by detecting and separating shared and exclusive pieces of sequence for input data sets. By replacing one deep single-cell sequencing experiment with a few single-cell sequencing experiments of lower depth, the co-assembly method can hedge against the risk of failure and loss of the sample, without significantly increasing sequencing cost. Application of the single-cell coassembler HyDA to the study of three uncultured members of an alkane-degrading methanogenic community validated the usefulness of the co-assembly concept.

Bioinformatics↗

bioRxiv2014

HGTector: An automated method facilitating genome-wide discovery of putative horizontal gene transfers

A new computational method of rapid, exhaustive and genome-wide detection of HGT was developed, featuring the systematic analysis of BLAST hit distribution patterns in the context of a priori defined hierarchical evolutionary categories. Genes that fall beyond a series of statistically determined thresholds are identified as not adhering to the typical vertical history of the organisms in question, but instead having a putative horizontal origin. Tests on simulated genomic data suggest that this approach effectively targets atypically distributed genes that are highly likely to be HGT-derived, and exhibits robust performance compared to conventional BLAST-based approaches. This method was further tested on real genomic datasets, including Rickettsia genomes, and was compared to previous studies. Results show consistency with currently employed categories of HGT prediction methods. In-depth analysis of both simulated and real genomic data suggests that the method is notably insensitive to stochastic events such as gene loss, rate variation and database error, which are common challenges to the current methodology. An automated pipeline was created to implement this approach and was made publicly available at: https://github.com/DittmarLab/HGTector. The program is versatile, easily deployed, has low requirements for computational resources, and is an effective tool for initial or standalone large-scale discovery of candidate HGT-derived genes.

Bioinformatics↗

bioRxiv2014

Background selection as baseline for nucleotide variation across the Drosophila genome

The constant removal of deleterious mutations by natural selection causes a reduction in neutral diversity and efficacy of selection at genetically linked sites (a process called Background Selection, BGS). Population genetic studies, however, often ignore BGS effects when investigating demographic events or the presence of other types of selection. To obtain a more realistic evolutionary expectation that incorporates the unavoidable consequences of deleterious mutations, we generated high-resolution landscapes of variation across the Drosophila melanogaster genome under a BGS scenario independent of polymorphism data. We find that BGS plays a significant role in shaping levels of variation across the entire genome, including long introns and intergenic regions distant from annotated genes. We also find that a very large percentage of the observed variation in diversity across autosomes can be explained by BGS alone, up to 70% across individual chromosome arms, thus indicating that BGS predictions can be used as baseline to infer additional types of selection and demographic events. This approach allows detecting several outlier regions with signal of recent adaptive events and selective sweeps. The use of a BGS baseline, however, is particularly appropriate to investigate the presence of balancing selection and our study exposes numerous genomic regions with the predicted signature of higher polymorphism than expected when a BGS context is taken into account. Importantly, we show that these conclusions are robust to the mutation and selection parameters of the BGS model. Finally, analyses of protein evolution together with previous comparisons of genetic maps between Drosophila species, suggest temporally variable recombination landscapes and thus, local BGS effects that may differ between extant and past phases. Because genome-wide BGS and temporal changes in linkage effects can skew approaches to estimate demographic and selective events, future analyses should incorporate BGS predictions and capture local recombination variation across genomes and along lineages.

Evolutionary Biology↗