Molecular Ecology Resources最新文献

Oliveira, V., A. R. M. Polónia, D. F. R. Cleary, et al. 2021. “Characterization of putative circular plasmids in sponge-associated bacterial communities using a selective multiply-primed rolling circle amplification.” Molecular Ecology Resources 21, no. 1: 110–121. https://doi.org/10.1111/1755-0998.13248.

The authors of the above article noticed an error in the DNA concentration which is detailed in the ‘Methods’ section, section 2.3 (‘Selective multiply-primed rolling circle amplification’), paragraph 2. The correct text should read as ‘1 μL template DNA (ca. 200 ng)’.

The authors apologise for this error and any inconvenience it may have caused.

Low coverage ‘genome-skims’ are often used to assemble organelle genomes and ribosomal gene sequences for cost-effective phylogenetic and barcoding studies. Natural history collections hold invaluable biological information, yet poor preservation resulting in degraded DNA often hinders polymerase chain reaction-based analyses. However, it is possible to generate libraries and sequence the short fragments typical of degraded DNA to generate genome-skims from museum collections. Here we introduce a snakemake toolkit comprised of three pipelines skim2mito, skim2rrna and gene2phylo, designed to unlock the genomic potential of historical museum specimens using genome skimming. Specifically, skim2mito and skim2rrna perform the batch assembly, annotation and phylogenetic analysis of mitochondrial genomes and nuclear ribosomal genes, respectively, from low-coverage genome skims. The third pipeline gene2phylo takes a set of gene alignments and performs phylogenetic analysis of individual genes, partitioned analysis of concatenated alignments and a phylogenetic analysis based on gene trees. We benchmark our pipelines with simulated data, followed by testing with a novel genome skimming dataset from both recent and historical solariellid gastropod samples. We show that the toolkit can recover mitochondrial and ribosomal genes from poorly preserved museum specimens of the gastropod family Solariellidae, and the phylogenetic analysis is consistent with our current understanding of taxonomic relationships. The generation of bioinformatic pipelines that facilitate processing large quantities of sequence data from the vast repository of specimens held in natural history museum collections will greatly aid species discovery and exploration of biodiversity over time, ultimately aiding conservation efforts in the face of a changing planet.

Across the tree of life, many organisms are able to reproduce clonally, via vegetative spread, budding or parthenogenesis. In population genetic analyses of clonally reproducing organisms, it is common practice to retain only a single representative per multilocus genotype. Though this practice of clone correction is widespread, the theoretical justification behind it has been very little studied. Here, I use individual-based simulations to study the effect of clone correction on the estimation of the genetic summary statistics H_O, H_S, F_IS, F_ST, F′′_ST and D_est. The simulations follow the standard finite island model, consisting of a set of populations connected by gene flow, but with a variable rate of sexual versus asexual reproduction. The results of the simulations show that by itself, the inclusion of replicated genotypes does not lead to a deviation in the values of the summary statistics, except when the rate of sexual reproduction is less than about one in thousand. However, clone correction can introduce a strong deviation in the values of most of the statistics, when compared to a scenario of full sexual reproduction. For H_S and F_IS, this deviation can be informative about the process of asexual reproduction, but for F_ST, F′′_ST and D_est, clone correction can lead to incorrect conclusions. I therefore argue that clone correction is not strictly necessary, but can in some cases be insightful. However, when clone correction is applied, it is imperative that results for both the corrected and uncorrected data are presented.

In the realm of genome assembly, even minor errors can send researchers down to rabbit holes of unintended misinterpretation. Enter Klumpy—a tool designed to help detecting these elusive mistakes before they cause significant problems. By providing detailed, region-specific assessments and an intuitive visualisation platform, Klumpy (Madrigal, et al. 2024) empowers researchers to pinpoint and resolve potential issues with precision, paving the way for more reliable downstream analyses and discoveries.

Spiders are a hyperdiverse taxon and among the most abundant predators in nearly all terrestrial habitats. Their success is often attributed to key developments in their evolution such as silk and venom production and major apomorphies such as a whole-genome duplication. Resolving deep relationships within the spider tree of life has been historically challenging, making it difficult to measure the relative importance of these novelties for spider evolution. Whole-genome data offer an essential resource in these efforts, but also for functional genomic studies. Here, we present de novo assemblies for three spider species: Ryuthela nishihirai (Liphistiidae), a representative of the ancient Mesothelae, the suborder that is sister to all other extant spiders; Uloborus plumipes (Uloboridae), a cribellate orbweaver whose phylogenetic placement is especially challenging; and Cheiracanthium punctorium (Cheiracanthiidae), which represents only the second family to be sequenced in the hyperdiverse Dionycha clade. These genomes fill critical gaps in the spider tree of life. Using these novel genomes along with 25 previously published ones, we examine the evolutionary history of spidroin gene and structural hox cluster diversity. Our assemblies provide critical genomic resources to facilitate deeper investigations into spider evolution. The near chromosome-level genome of the ‘living fossil’ R. nishihirai represents an especially important step forward, offering new insights into the origins of spider traits.

Current rDNA reference sequence databases are tailored towards shorter DNA markers, such as parts of the 16/18S marker or the internally transcribed spacer (ITS) region. However, due to advances in long-read DNA sequencing technologies, longer stretches of the rDNA operon are increasingly used in environmental sequencing studies to increase the phylogenetic resolution. There is, therefore, a growing need for longer rDNA reference sequences. Here, we present the ribosomal operon database (ROD), which includes eukaryotic full-length rDNA operons fished from publicly available genome assemblies. Full-length operons were detected in 34.1% of the 34,701 examined eukaryotic genome assemblies from NCBI. In most cases (53.1%), more than one operon variant was detected, which can be due to intragenomic operon copy variability, allelic variation in non-haploid genomes, or technical errors from the sequencing and assembly process. The highest copy number found was 5947 in Zea mays. In total, 453,697 unique operons were detected, with 69,480 operon variant clusters remaining after intragenomic clustering at 99% sequence identity. The operon length varied extensively across eukaryotes, ranging from 4136 to 16,463 bp, which will lead to considerable polymerase chain reaction (PCR) bias during amplification of the entire operon. Clustering the full-length operons revealed that the different parts (i.e., 18S, 28S, and the hypervariable regions V4 and V9 of 18S) provide divergent taxonomic resolution, with 18S, the V4 and V9 regions being the most conserved. The ROD will be updated regularly to provide an increasing number of full-length rDNA operons to the scientific community.

One essential initial step in the analysis of ancient DNA is to authenticate that the DNA sequencing reads are actually from ancient DNA. This is done by assessing if the reads exhibit typical characteristics of post-mortem damage (PMD), including cytosine deamination and nicks. We present a novel statistical method implemented in a fast multithreaded programme, ngsBriggs that enables rapid quantification of PMD by estimation of the Briggs ancient damage model parameters (Briggs parameters). Using a multinomial model with maximum likelihood fit, ngsBriggs accurately estimates the parameters of the Briggs model, quantifying the PMD signal from single and double-stranded DNA regions. We extend the original Briggs model to capture PMD signals for contemporary sequencing platforms and show that ngsBriggs accurately estimates the Briggs parameters across a variety of contamination levels. Classification of reads into ancient or modern reads, for the purpose of decontamination, is significantly more accurate using ngsBriggs than using other methods available. Furthermore, ngsBriggs is substantially faster than other state-of-the-art methods. ngsBriggs offers a practical and accurate method for researchers seeking to authenticate ancient DNA and improve the quality of their data.