Phylogenetic signal from rearrangements in 18 Anopheles species by joint scaffolding extant and ancestral genomes

Abstract

BackgroundGenomes rearrangements carry valuable information for phylogenetic inference or the elucidation of molecular mechanisms of adaptation. However, the detection of genome rearrangements is often hampered by current deficiencies in data and methods: Genomes obtained from short sequence reads have generally very fragmented assemblies, and comparing multiple gene orders generally leads to computationally intractable algorithmic questions.ResultsWe present a computational method, ADseq, which, by combining ancestral gene order reconstruction, comparative scaffolding and de novo scaffolding methods, overcomes these two caveats. ADseq provides simultaneously improved assemblies and ancestral genomes, with statistical supports on all local features. Compared to previous comparative methods, it runs in polynomial time, it samples solutions in a probabilistic space, and it can handle a significantly larger gene complement from the considered extant genomes, with complex histories including gene duplications and losses. We use ADseq to provide improved assemblies and a genome history made of duplications, losses, gene translocations, rearrangements, of 18 complete Anopheles genomes, including several important malaria vectors. We also provide additional support for a differentiated mode of evolution of the sex chromosome and of the autosomes in these mosquito genomes.ConclusionsWe demonstrate the method’s ability to improve extant assemblies accurately through a procedure simulating realistic assembly fragmentation. We study a debated issue regarding the phylogeny of the Gambiae complex group of Anopheles genomes in the light of the evolution of chromosomal rearrangements, suggesting that the phylogenetic signal they carry can differ from the phylogenetic signal carried by gene sequences, more prone to introgression.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4466-7) contains supplementary material, which is available to authorized users.

Detecting Introgression in Anopheles Mosquito Genomes Using a Reconciliation-Based Approach

“…christyi ; but in this precise case, within the clade of Asian mosquitoes the best available assembled genome is An. minimus, which is fragmented in around one hundred scaffolds [1], which likely reduces its effectiveness as a support for a synteny analysis. Our synteny-based approach would then naturally benefit from better assembled genomes, including ancestral genomes [1].…”

“…The species tree relating these species is given in Fig. 1; it is the so-called X-phylogeny used in [1]. In our experiments, we consider this tree as undated, i.e.…”

“…The 14 genomes contain a single fully assembled genome, An. gambia, while some others are assembled at the contig level; we refer the reader to [1] for a precise discussion on the assembly of these genomes. The considered genomes contain from 10, 000 to above 14, 000 genes, that have been clustered prior to our study into homologous gene families using the OrthoDB algorithm [27] and represent an improvement of the set of gene families used in [1].…”

“…An important observation is the large number of very small gene families, likely due to errors in assembling genes or in clustering genes into homologous families, an expected issue with large-scale multi-species genomic data sets. For each family, a multiple sequences alignment (MSA) of the coding sequences of the genes belonging to the family was obtained using the method described in [1].…”

Evolutionary superscaffolding and chromosome anchoring to improve Anopheles genome assemblies

“…ADSEQ analysis first builds reconciled gene trees for each orthologous group (gene family), then for pairs of gene families for which extant genomic adjacencies are observed, or suggested by sequencing data, a duplication-aware parsimonious evolutionary scenario is computed, via Dynamic Programming (DP), that also predicts extant adjacencies between genes at the extremities of contigs or scaffolds. This DP algorithm also accounts for scaffolding scores obtained from paired-end reads mapped onto contigs and provides a probabilistic score for each predicted extant adjacency, based on sampling optimal solutions (Anselmetti et al 2018). ADSEQ was applied across the full anopheline input dataset to predict scaffold adjacencies (Supplementary Online Material: Table S3).…”