UCEasy: A software package for automating and simplifying the analysis of ultraconserved elements (UCEs)

The use of Ultraconserved Elements (UCEs) as genetic markers in phylogenomics has become popular and has provided promising results. Although UCE data can be easily obtained from targeted enriched sequencing, the protocol for in silico analysis of UCEs consist of the execution of heterogeneous and complex tools, a challenge for scientists without training in bioinformatics. Developing tools with the adoption of best practices in research software can lessen this problem by improving the execution of computational experiments, thus promoting better reproducibility. We present UCEasy, an easy-to-install and easy-to-use software package with a simple command line interface that facilitates the computational analysis of UCEs from sequencing samples, following the best practices of research software. UCEasy is a wrapper that standardises, automates and simplifies the quality control of raw reads, assembly and extraction and alignment of UCEs, generating at the end a data matrix with different levels of completeness that can be used to infer phylogenetic trees. We demonstrate the functionalities of UCEasy by reproducing the published results of phylogenomic studies of the bird genus Turdus (Aves) and of Adephaga families (Coleoptera) containing genomic datasets to efficiently extract UCEs.

Using ultraconserved elements to reconstruct the termite tree of life

The phylogenetic history of termites has been investigated using mitochondrial genomes and transcriptomes. However, both sets of markers have limitations. Mitochondrial genomes represent a single genetic marker likely to yield phylogenetic trees presenting incongruences with species trees, and transcriptomes can only be obtained from well-preserved samples. In contrast, ultraconserved elements (UCEs) include a great many independent markers that can be retrieved from poorly preserved samples. Here, we designed termite-specific baits targeting 50,616 UCE loci. We tested our UCE bait set on 42 samples of termites and three samples of Cryptocercus, for which we generated low-coverage highly-fragmented genome assemblies and successfully extracted in silico between 3,426 to 42,860 non-duplicated UCEs per sample. Our maximum likelihood phylogenetic tree, reconstructed using the 5,934 UCE loci retrieved from upward of 75% of samples, was congruent with transcriptome-based phylogenies, demonstrating that our UCE bait set is reliable and phylogenetically informative. Combined with non-destructive DNA extraction protocols, our UCE bait set provides the tool needed to carry out a global taxonomic revision of termites based on poorly preserved specimens such as old museum samples. The Termite UCE database is maintained at: https://github.com/oist/TER-UCE-DB/.

Target enrichment of long open reading frames and ultraconserved elements to link microevolution and macroevolution in non-model organisms

Despite the increasing accessibility of high-throughput sequencing, obtaining high-quality genomic data on non-model organisms without proximate well-assembled and annotated genomes remains challenging. Here we describe a workflow that takes advantage of distant genomic resources and ingroup transcriptomes to select and jointly enrich long open reading frames (ORFs) and ultraconserved elements (UCEs) from genomic samples for integrative studies of microevolutionary and macroevolutionary dynamics. This workflow is applied to samples of the African unionid bivalve tribe Coelaturini (Parreysiinae) at basin and continent-wide scales. Our results indicate that ORFs are efficiently captured without prior identification of intron-exon boundaries. The enrichment of UCEs was less successful, but nevertheless produced a substantial dataset. Exploratory continent-wide phylogenetic analyses with ORF supercontigs (>515,000 parsimony informative sites) resulted in a fully resolved phylogeny, the backbone of which was also retrieved with UCEs (>11,000 informative sites), although some branches lack support in the latter case. Variant calling on the exome of Coelaturini from the Malawi Basin produced ~2,000 SNPs per population pair. Nucleotide diversity and population differentiation was low compared to previous estimates in mollusks, but comparable to those in recently diversifying Malawi cichlids and other taxa at an early stage of speciation. Skimming non-specific sequence data obtained for Coelaturini of the Malawi Basin, we reconstructed the maternally-inherited mitogenome, which displays an identical gene order to that of the most recent common ancestor of Unionidae. Overall, our workflow and results provide exciting perspectives for the development of integrative genomic studies on micro- and macroevolutionary dynamics in non-model organisms.

Divergence time estimation of Galliformes based on the best gene shopping scheme of ultraconserved elements

Background Divergence time estimation is fundamental to understanding many aspects of the evolution of organisms, such as character evolution, diversification, and biogeography. With the development of sequence technology, improved analytical methods, and knowledge of fossils for calibration, it is possible to obtain robust molecular dating results. However, while phylogenomic datasets show great promise in phylogenetic estimation, the best ways to leverage the large amounts of data for divergence time estimation has not been well explored. A potential solution is to focus on a subset of data for divergence time estimation, which can significantly reduce the computational burdens and avoid problems with data heterogeneity that may bias results. Results In this study, we obtained thousands of ultraconserved elements (UCEs) from 130 extant galliform taxa, including representatives of all genera, to determine the divergence times throughout galliform history. We tested the effects of different “gene shopping” schemes on divergence time estimation using a carefully, and previously validated, set of fossils. Our results found commonly used clock-like schemes may not be suitable for UCE dating (or other data types) where some loci have little information. We suggest use of partitioning (e.g., PartitionFinder) and selection of tree-like partitions may be good strategies to select a subset of data for divergence time estimation from UCEs. Our galliform time tree is largely consistent with other molecular clock studies of mitochondrial and nuclear loci. With our increased taxon sampling, a well-resolved topology, carefully vetted fossil calibrations, and suitable molecular dating methods, we obtained a high quality galliform time tree. Conclusions We provide a robust galliform backbone time tree that can be combined with more fossil records to further facilitate our understanding of the evolution of Galliformes and can be used as a resource for comparative and biogeographic studies in this group.