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Timely and accurate biodiversity analysis poses an ongoing challenge for the success of biomonitoring programs. Morphology-based identification of bioindicator taxa is time consuming, and rarely supports species-level resolution especially for immature life stages. Much work has been done in the past decade to develop alternative approaches for biodiversity analysis using DNA sequence-based approaches such as molecular phylogenetics and DNA barcoding. On-going assembly of DNA barcode reference libraries will provide the basis for a DNA-based identification system. The use of recently introduced next-generation sequencing (NGS) approaches in biodiversity science has the potential to further extend the application of DNA information for routine biomonitoring applications to an unprecedented scale. Here we demonstrate the feasibility of using 454 massively parallel pyrosequencing for species-level analysis of freshwater benthic macroinvertebrate taxa commonly used for biomonitoring. We designed our experiments in order to directly compare morphology-based, Sanger sequencing DNA barcoding, and next-generation environmental barcoding approaches. Our results show the ability of 454 pyrosequencing of mini-barcodes to accurately identify all species with more than 1% abundance in the pooled mixture. Although the approach failed to identify 6 rare species in the mixture, the presence of sequences from 9 species that were not represented by individuals in the mixture provides evidence that DNA based analysis may yet provide a valuable approach in finding rare species in bulk environmental samples. We further demonstrate the application of the environmental barcoding approach by comparing benthic macroinvertebrates from an urban region to those obtained from a conservation area. Although considerable effort will be required to robustly optimize NGS tools to identify species from bulk environmental samples, our results indicate the potential of an environmental barcoding approach for biomonitoring programs.

Background: The goal of DNA barcoding is to develop a species-specific sequence library for all eukaryotes. A 650 bp fragment of the cytochrome c oxidase 1 (CO1) gene has been used successfully for species-level identification in several animal groups. It may be difficult in practice, however, to retrieve a 650 bp fragment from archival specimens, (because of DNA degradation) or from environmental samples (where universal primers are needed).

We analyzed the nucleotide contents of several completely sequenced genomes, and we show that nucleotide bias can have a dramatic effect on the amino acid composition of the encoded proteins. By surveying the genes in 21 completely sequenced eubacterial and archaeal genomes, along with the entire Saccharomyces cerevisiae genome and two Plasmodium falciparum chromosomes, we show that biased DNA encodes biased proteins on a genomewide scale. The predicted bias affects virtually all genes within the genome, and it could be clearly seen even when we limited the analysis to sets of homologous gene sequences. Parallel patterns of compositional bias were found within the archaea and the eubacteria. We also found a positive correlation between the degree of amino acid bias and the magnitude of protein sequence divergence. We conclude that mutational bias can have a major effect on the molecular evolution of proteins. These results could have important implications for the interpretation of protein-based molecular phylogenies and for the inference of functional protein adaptation from comparative sequence data.

No abstract

Genes that belong to the same functional pathways are often packaged into operons in prokaryotes. However, aside from examples in nematode genomes, this form of transcriptional regulation appears to be absent in eukaryotes. Nevertheless, a number of recent studies have shown that gene order in eukaryotic genomes is not completely random, and that genes with similar expression patterns tend to be clustered together. What remains unclear is whether co-expressed genes have been gathered together by natural selection to facilitate their regulation, or if the genes are co-expressed simply by virtue of their being close together in the genome. Here, we show that gene expression clusters tend to contain fewer chromosomal breakpoints between human and mouse than expected by chance, which indicates that they are being held together by natural selection. This conclusion applies to clusters defined on the basis of broad (housekeeping) expression, or on the basis of correlated transcription profiles across tissues. Contrary to previous reports, we find that genes with high expression are not clustered to a greater extent than expected by chance and are not conserved during evolution.

The characterization of biodiversity is a crucial element of ecological investigations as well as environmental assessment and monitoring activities. Increasingly, amplicon-based environmental DNA metabarcoding (alternatively, marker gene metagenomics) is used for such studies given its ability to provide biodiversity data from various groups of organisms simply from analysis of bulk environmental samples such as water, soil or sediments. The Illumina MiSeq is currently the most popular tool for carrying out this work, but we set out to determine whether typical studies were reading enough DNA to detect rare organisms (i.e., those that may be of greatest interest such as endangered or invasive species) present in the environment. We collected sea water samples along two transects in Conception Bay, Newfoundland and analyzed them on the MiSeq with a sequencing depth of 100,000 reads per sample (exceeding the 60,000 per sample that is typical of similar studies). We then analyzed these same samples on Illumina’s newest high-capacity platform, the NovaSeq, at a depth of 7 million reads per sample. Not surprisingly, the NovaSeq detected many more taxa than the MiSeq thanks to its much greater sequencing depth. However, contrary to our expectations this pattern was true even in depth-for-depth comparisons. In other words, the NovaSeq can detect more DNA sequence diversity within samples than the MiSeq, even at the exact same sequencing depth. Even when samples were reanalyzed on the MiSeq with a sequencing depth of 1 million reads each, the MiSeq’s ability to detect new sequences plateaued while the NovaSeq continued to detect new sequence variants. These results have important biological implications. The NovaSeq found 40% more metazoan families in this environment than the MiSeq, including some of interest such as marine mammals and bony fish so the real-world implications of these findings are significant. These results are most likely associated to the advances incorporated in the NovaSeq, especially a patterned flow cell, which prevents similar sequences that are neighbours on the flow cell (common in metabarcoding studies) from being erroneously merged into single spots by the sequencing instrument. This study sets the stage for incorporating eDNA metabarcoding in comprehensive analysis of oceanic samples in a wide range of ecological and environmental investigations.

BackgroundThe rapid and accurate identification of species is a critical component of large-scale biodiversity monitoring programs. DNA arrays (micro and macro) and DNA barcodes are two molecular approaches that have recently garnered much attention. Here, we compare these two platforms for identification of an important group, the mammals.ResultsOur analyses, based on the two commonly used mitochondrial genes cytochrome c oxidase I (the standard DNA barcode for animal species) and cytochrome b (a common species-level marker), suggest that both arrays and barcodes are capable of discriminating mammalian species with high accuracy. We used three different datasets of mammalian species, comprising different sampling strategies. For DNA arrays we designed three probes for each species to address intraspecific variation. As for DNA barcoding, our analyses show that both cytochrome c oxidase I and cytochrome b genes, and even smaller fragments of them (mini-barcodes) can successfully discriminate species in a wide variety of specimens.ConclusionThis study showed that DNA arrays and DNA barcodes are valuable molecular methods for biodiversity monitoring programs. Both approaches were capable of discriminating among mammalian species in our test assemblages. However, because designing DNA arrays require advance knowledge of target sequences, the use of this approach could be limited in large scale monitoring programs where unknown haplotypes might be encountered. DNA barcodes, by contrast, are sequencing-based and therefore could provide more flexibility in large-scale studies.