Molecular Ecology Resources最新文献

Zoo populations of threatened species are a valuable resource for the restoration of wild populations. However, their small effective population size poses a risk to long-term viability, especially in species with high genetic load. Recent bioinformatic developments can identify harmful genetic variants in genome data. Here, we advance this approach, analysing the genetic load in the threatened pink pigeon (Nesoenas mayeri). We lifted the mutation-impact scores that had been calculated for the chicken (Gallus gallus) to estimate the genetic load in six pink pigeons. Additionally, we perform in silico crossings to predict the genetic load and realized load of potential offspring. We thus identify the optimal mate pairs that are theoretically expected to produce offspring with the least inbreeding depression. We use computer simulations to show how genomics-informed conservation can reduce the genetic load whilst reducing the loss of genome-wide diversity. Genomics-informed management is likely to become instrumental in maintaining the long-term viability of zoo populations.

Parasitic plants have a heterotrophic lifestyle, in which they withdraw all or part of their nutrients from their host through the haustorium. Despite the release of many draft genomes of parasitic plants, the genome evolution related to the parasitism feature of facultative parasites remains largely unknown. In this study, we present a high-quality chromosomal-level genome assembly for the facultative parasite Pedicularis kansuensis (Orobanchaceae), which invades both legume and grass host species in degraded grasslands on the Qinghai-Tibet Plateau. This species has the largest genome size compared with other parasitic species, and expansions of long terminal repeat retrotransposons accounting for 62.37% of the assembly greatly contributed to the genome size expansion of this species. A total of 42,782 genes were annotated, and the patterns of gene loss in P. kansuensis differed from other parasitic species. We also found many mobile mRNAs between P. kansuensis and one of its host species, but these mobile mRNAs could not compensate for the functional losses of missing genes in P. kansuensis. In addition, we identified nine horizontal gene transfer (HGT) events from rosids and monocots, as well as one single-gene duplication events from HGT genes, which differ distinctly from that of other parasitic species. Furthermore, we found evidence for HGT through transferring genomic fragments from phylogenetically remote host species. Taken together, these findings provide genomic insights into the evolution of facultative parasites and broaden our understanding of the diversified genome evolution in parasitic plants and the molecular mechanisms of plant parasitism.

There is growing interest in uncovering genetic kinship patterns in past societies using low-coverage palaeogenomes. Here, we benchmark four tools for kinship estimation with such data: lcMLkin, NgsRelate, KIN, and READ, which differ in their input, IBD estimation methods, and statistical approaches. We used pedigree and ancient genome sequence simulations to evaluate these tools when only a limited number (1 to 50 K, with minor allele frequency ≥0.01) of shared SNPs are available. The performance of all four tools was comparable using ≥20 K SNPs. We found that first-degree related pairs can be accurately classified even with 1 K SNPs, with 85% F₁ scores using READ and 96% using NgsRelate or lcMLkin. Distinguishing third-degree relatives from unrelated pairs or second-degree relatives was also possible with high accuracy (F₁ > 90%) with 5 K SNPs using NgsRelate and lcMLkin, while READ and KIN showed lower success (69 and 79% respectively). Meanwhile, noise in population allele frequencies and inbreeding (first-cousin mating) led to deviations in kinship coefficients, with different sensitivities across tools. We conclude that using multiple tools in parallel might be an effective approach to achieve robust estimates on ultra-low-coverage genomes.

Phylogenetic studies now routinely require manipulating and summarizing thousands of data files. For most of these tasks, currently available software requires considerable computing resources and substantial knowledge of command-line applications. We develop an ultrafast and memory-efficient software, SEGUL, that performs common phylogenomic dataset manipulations and calculates statistics summarizing essential data features. Our software is available as standalone command-line interface (CLI) and graphical user interface (GUI) applications, and as a library for Rust, R and Python, with possible support of other languages. The CLI and library versions run native on Windows, Linux and macOS, including Apple ARM Macs. The GUI version extends support to include mobile iOS, iPadOS and Android operating systems. SEGUL leverages the high performance of the Rust programming language to offer fast execution times and low memory footprints regardless of dataset size and platform choice. The inclusion of a GUI minimizes bioinformatics barriers to phylogenomics while SEGUL's efficiency reduces economic barriers by allowing analysis on inexpensive hardware. Our support for mobile operating systems further enables teaching phylogenomics where access to computing power is limited.

Preparation of DNA polymorphism datasets for analysis is an important step in evolutionary genetic and molecular ecology studies. Ever-growing dataset sizes make this step time consuming, but few convenient software tools are available to facilitate processing of large-scale datasets including thousands of sequence alignments. Here I report “processor of sequences v4” (proSeq4)—a user-friendly multiplatform software for preparation and evolutionary genetic analyses of genome- or transcriptome-scale sequence polymorphism datasets. The program has an easy-to-use graphic user interface and is designed to process and analyse many thousands of datasets. It supports over two dozen file formats, includes a flexible sequence editor and various tools for data visualization, quality control and most commonly used evolutionary genetic analyses, such as NJ-phylogeny reconstruction, DNA polymorphism analyses and coalescent simulations. Command line tools (e.g. vcf2fasta) are also provided for easier integration into bioinformatic pipelines. Apart of molecular ecology and evolution research, proSeq4 may be useful for teaching, e.g. for visual illustration of different shapes of phylogenies generated with coalescent simulations in different scenarios. ProSeq4 source code and binaries for Windows, MacOS and Ubuntu are available from https://sourceforge.net/projects/proseq/.

Over the past few years, insects have been used as samplers of vertebrate diversity by assessing the ingested-derived DNA (iDNA), and dung beetles have been shown to be a good mammal sampler given their broad feeding preference, wide distribution and easy sampling. Here, we tested and optimized the use of iDNA from dung beetles to assess the mammal community by evaluating if some biological and methodological aspects affect the use of dung beetles as mammal species samplers. We collected 403 dung beetles from 60 pitfall traps. iDNA from each dung beetle was sequenced by metabarcoding using two mini-barcodes (12SrRNA and 16SrRNA). We assessed whether dung beetles with different traits related to feeding, nesting and body size differed in the number of mammal species found in their iDNA. We also tested differences among four killing solutions in preserving the iDNA and compared the effectiveness of each mini barcode to recover mammals. We identified a total of 50 mammal OTUs (operational taxonomic unit), including terrestrial and arboreal species from 10 different orders. We found that at least one mammal-matching sequence was obtained from 70% of the dung beetle specimens. The number of mammal OTUs obtained did not vary with dung beetle traits as well as between the killing solutions. The 16SrRNA mini-barcode recovered a higher number of mammal OTUs than 12SrRNA, although both sets were partly non-overlapping. Thus, the complete mammal diversity may not be achieved by using only one of them. This study refines the methodology for routine assessment of tropical mammal communities via dung beetle ‘samplers’ and its universal applicability independently of the species traits of local beetle communities.

Lignin, as an abundant organic carbon, plays a vital role in the global carbon cycle. However, our understanding of the global lignin-degrading microbiome remains elusive. The greatest barrier has been absence of a comprehensive and accurate functional gene database. Here, we first developed a curated functional gene database (LCdb) for metagenomic profiling of lignin degrading microbial consortia. Via the LCdb, we draw a clear picture describing the global biogeography of communities with lignin-degrading potential. They exhibit clear niche differentiation at the levels of taxonomy and functional traits. The terrestrial microbiomes showed the highest diversity, yet the lowest correlations. In particular, there were few correlations between genes involved in aerobic and anaerobic degradation pathways, showing a clear functional redundancy property. In contrast, enhanced correlations, especially closer inter-connections between anaerobic and aerobic groups, were observed in aquatic consortia in response to the lower diversity. Specifically, dypB and dypA, are widespread on Earth, indicating their essential roles in lignin depolymerization. Estuarine and marine consortia featured the laccase and mnsod genes, respectively. Notably, the roles of archaea in lignin degradation were revealed in marine ecosystems. Environmental factors strongly influenced functional traits, but weakly shaped taxonomic groups. Null mode analysis further verified that composition of functional traits was deterministic, while taxonomic composition was highly stochastic, demonstrating that the environment selects functional genes rather than taxonomic groups. Our study not only develops a useful tool to study lignin degrading microbial communities via metagenome sequencing but also advances our understanding of ecological traits of these global microbiomes.

The origin of flight and laryngeal echolocation in bats is likely to have been accompanied by evolutionary changes in other aspects of their sensory biology. Of all sensory modalities in bats, olfaction is perhaps the least well understood. Olfactory receptors (ORs) function in recognizing odour molecules, with crucial roles in evaluating food, as well as in processing social information. Here we compare OR repertoire sizes across taxa and apply a new pipeline that integrates comparative genome data with protein structure modelling and then we employ molecular docking techniques with small molecules to analyse OR functionality based on binding energies. Our results suggest a sharp contraction in odorant recognition of the functional OR repertoire during the origin of bats, consistent with a reduced dependence on olfaction. We also compared bat lineages with contrasting different ecological characteristics and found evidence of differences in OR gene expansion and contraction, and in the composition of ORs with different tuning breadths. The strongest binding energies of ORs in non-echolocating fruit-eating bats were seen to correspond to ester odorants, although we did not detect a quantitative advantage of functional OR repertoires in these bats compared with echolocating insectivorous species. Overall, our findings based on molecular modelling and computational docking suggest that bats have undergone olfactory evolution linked to dietary adaptation. Our results from extant and ancestral bats help to lay the groundwork for targeted experimental functional tests in the future.