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Inversion polymorphisms are responsible for many ecologically important phenotypes and are often found under balancing selection. However, the same features that ensure their large role in local adaptation—especially reduced recombination between alternate arrangements—mean that uncovering the precise loci within inversions that control these phenotypes is unachievable using standard mapping approaches. Here, we take advantage of long‐term balancing selection on a pair of inversions in the mosquito Anopheles gambiae to map desiccation tolerance via pool‐GWAS. Two polymorphic inversions on chromosome 2 of this species (denoted 2La and 2Rb) are associated with arid and hot conditions in Africa and are maintained in spatially and temporally heterogeneous environments. After measuring thousands of wild‐caught individuals for survival under desiccation stress, we used phenotypically extreme individuals homozygous for alternative arrangements at the 2La inversion to construct pools for whole‐genome sequencing. Genomewide association mapping using these pools revealed dozens of significant SNPs within both 2La and 2Rb, many of which neighboured genes controlling ion channels or related functions. Our results point to the promise of similar approaches in systems with inversions maintained by balancing selection and provide a list of candidate genes underlying the specific phenotypes controlled by the two inversions studied here. [ABSTRACT FROM AUTHOR]

Motivation Site concordance factors (sCFs) have become a widely used way to summarize discordance in phylogenomic datasets. However, the original version of sCFs was calculated by sampling a quartet of tip taxa and then applying parsimony-based criteria for discordance. This approach has the potential to be strongly affected by multiple hits at a site (homoplasy), especially when substitution rates are high or taxa are not closely related. Results Here, we introduce a new method for calculating sCFs. The updated version uses likelihood to generate probability distributions of ancestral states at internal nodes of the phylogeny. By sampling from the states at internal nodes adjacent to a given branch, this approach substantially reduces—but does not abolish—the effects of homoplasy and taxon sampling. Availability and implementation Updated sCFs are implemented in IQ-TREE 2.2.2. The software is freely available at https://github.com/iqtree/iqtree2/releases. Supplementary information Supplementary information is available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Edible bananas result from interspecific hybridization between Musa acuminata and Musa balbisiana, as well as among subspecies in M. acuminata. Four particular M. acuminata subspecies have been proposed as the main contributors of edible bananas, all of which radiated in a short period of time in southeastern Asia. Clarifying the evolution of these lineages at a whole-genome scale is therefore an important step toward understanding the domestication and diversification of this crop. This study reports the de novo genome assembly and gene annotation of a representative genotype from three different subspecies of M. acuminata. These data are combined with the previously published genome of the fourth subspecies to investigate phylogenetic relationships. Analyses of shared and unique gene families reveal that the four subspecies are quite homogenous, with a core genome representing at least 50% of all genes and very few M. acuminata species-specific gene families. Multiple alignments indicate high sequence identity between homologous single copy-genes, supporting the close relationships of these lineages. Interestingly, phylogenomic analyses demonstrate high levels of gene tree discordance, due to both incomplete lineage sorting and introgression. This pattern suggests rapid radiation within Musa acuminata subspecies that occurred after the divergence with M. balbisiana. Introgression between M. a. ssp. malaccensis and M. a. ssp. burmannica was detected across the genome, though multiple approaches to resolve the subspecies tree converged on the same topology. To support evolutionary and functional analyses, we introduce the PanMusa database, which enables researchers to exploration of individual gene families and trees. [ABSTRACT FROM AUTHOR]

Inversion polymorphisms in the African malaria vector Anopheles gambiae segregate along climatic gradients of aridity. Despite indirect evidence of their adaptive significance, little is known of the phenotypic targets of selection or the underlying genetic mechanisms. Here we adopt a systems genetics approach to explore the interaction of two inversions on opposite arms of chromosome 2 with gender, climatic conditions, and one another. We measure organismal traits and transcriptional profiles in 8-d-old adults of both sexes and four alternative homokaryotypic classes reared under two alternative climatic regimes. We show that karyotype strongly influences both organismal traits and transcriptional profiles but that the strength and direction of the effects depend upon complex interactions with gender and environmental conditions and between inversions on independent arms. Our data support the suppressed recombination model for the role of inversions in local adaptation, and--supported by transcriptional and physiological measurements following perturbation with the drug rapamycin--suggest that one mechanism underlying their adaptive role may be the maintenance of energy homeostasis. [ABSTRACT FROM AUTHOR]

Abstract: With advances in sequencing technology, research in the field of landscape genetics can now be conducted at unprecedented spatial and genomic scales. This has been especially evident when using sequence data to visualize patterns of genetic differentiation across a landscape due to demographic history, including changes in migration. Two recent model‐based visualization methods that can highlight unusual patterns of genetic differentiation across a landscape, SpaceMix and EEMS, are increasingly used. While SpaceMix's model can infer long‐distance migration, EEMS’ model is more sensitive to short‐distance changes in genetic differentiation, and it is unclear how these differences may affect their results in various situations. Here, we compare SpaceMix and EEMS side by side using landscape genetics simulations representing different migration scenarios. While both methods excel when patterns of simulated migration closely match their underlying models, they can produce either un‐intuitive or misleading results when the simulated migration patterns match their models less well, and this may be difficult to assess in empirical data sets. We also introduce unbundled principal components (un‐PC), a fast, model‐free method to visualize patterns of genetic differentiation by combining principal components analysis (PCA), which is already used in many landscape genetics studies, with the locations of sampled individuals. Un‐PC has characteristics of both SpaceMix and EEMS and works well with simulated and empirical data. Finally, we introduce msLandscape, a collection of tools that streamline the creation of customizable landscape‐scale simulations using the popular coalescent simulator ms and conversion of the simulated data for use with un‐PC, SpaceMix and EEMS. [ABSTRACT FROM AUTHOR]

Genome-scale sequencing has been of great benefit in recovering species trees but has not provided final answers. Despite the rapid accumulation of molecular sequences, resolving short and deep branches of the tree of life has remained a challenge and has prompted the development of new strategies that can make the best use of available data. One such strategy--the concatenation of gene alignments--can be successful when coupled with many tree estimation methods, but has also been shown to fail when there are high levels of incomplete lineage sorting. Here, we focus on the failure of likelihood-based methods in retrieving a rooted, asymmetric four-taxon species tree from concatenated data when the species tree is in or near the anomaly zone--a region of parameter space where the most common gene tree does not match the species tree because of incomplete lineage sorting. First, we use coalescent theory to prove that most informative sites will support the species tree in the anomaly zone, and that as a consequence maximum-parsimony succeeds in recovering the species tree from concatenated data. We further show that maximum-likelihood tree estimation from concatenated data fails both inside and outside the anomaly zone, and that this failure cannot be easily predicted from the topology of the most common gene tree. We demonstrate that likelihood-based methods often fail in a region partially overlapping the anomaly zone, likely because of the lower relative cost of substitutions on discordant gene tree branches that are absent from the species tree. Our results confirm and extend previous reports on the performance of these methods applied to concatenated data from a rooted, asymmetric four-taxon species tree, and highlight avenues for future work improving the performance of methods aimed at recovering species tree. [ABSTRACT FROM AUTHOR]

Polyploidy can have a huge impact on the evolution of species, and it is a common occurrence, especially in plants. The two types of polyploids-autopolyploids and allopolyploids-differ in the level of divergence between the genes that are brought together in the new polyploid lineage. Because allopolyploids are formed via hybridization, the homoeologous copies of genes within them are at least as divergent as orthologs in the parental species that came together to formthem. This means that common methods for estimating the parental lineages of allopolyploidy events are not accurate, and can lead to incorrect inferences about the number of gene duplications and losses. Here, we have adapted an algorithm for topologybased gene-tree reconciliation to work with multi-labeled trees (MUL-trees). By definition, MUL-trees have some tips with identical labels, which makes them a natural representation of the genomes of polyploids. Using this new reconciliation algorithm we can: accurately place allopolyploidy events on a phylogeny, identify the parental lineages that hybridized to form allopolyploids, distinguish between allo-, auto-, and (in most cases) no polyploidy, and correctly count the number of duplications and losses in a set of gene trees. We validate our method using gene trees simulated with and without polyploidy, and revisit the history of polyploidy in data from the clades including both baker's yeast and bread wheat. Our re-analysis of the yeast data confirms the allopolyploid origin and parental lineages previously identified for this group. The method presented here should find wide use in the growing number of genomes from species with a history of polyploidy. [ABSTRACT FROM AUTHOR]