In a recent paper, "Environmental DNA: What's behind the term? Clarifying the terminology and recommendations for its future use in biomonitoring," Pawlowski et al. argue that the term eDNA should be used to refer to the pool of DNA isolated from environmental samples, as opposed to only extra-organismal DNA from macro-organisms. We agree with this view. However, we are concerned that their proposed two-level terminology specifying sampling environment and targeted taxa is overly simplistic and might hinder rather than improve clear communication about environmental DNA and its use in biomonitoring. This terminology is based on categories that are often difficult to assign and uninformative, and it overlooks a fundamental distinction within eDNA: the type of DNA (organismal or extra-organismal) from which ecological interpretations are derived.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

In a recent paper, “Environmental DNA: What’s behind the term? Clarifying the terminology and recommendations for its future use in biomonitoring”, Pawlowski et al. argue that the term eDNA should be used to refer to the pool of DNA isolated from environmental samples, as opposed to only extra-organismal DNA from macro-organisms. We agree with this view. However, we are concerned that their proposed two-level terminology specifying sampling environment and targeted taxa is overly simplistic and might hinder rather than improve clear communication about environmental DNA and its use in biomonitoring. Not only is this terminology based on categories that are often difficult to assign and uninformative, but it ignores what is in our opinion the most important distinction within eDNA: the type of DNA (organismal or extra-organismal) from which ecological interpretations are derived.

The rich diversity of morphology and behavior displayed across primate species provides an informative context in which to study the impact of genomic diversity on fundamental biological processes. Analysis of that diversity provides insight into long-standing questions in evolutionary and conservation biology and is urgent given severe threats these species are facing. Here, we present high-coverage whole-genome data from 233 primate species representing 86% of genera and all 16 families. This dataset was used, together with fossil calibration, to create a nuclear DNA phylogeny and to reassess evolutionary divergence times among primate clades. We found within-species genetic diversity across families and geographic regions to be associated with climate and sociality, but not with extinction risk. Furthermore, mutation rates differ across species, potentially influenced by effective population sizes. Lastly, we identified extensive recurrence of missense mutations previously thought to be human specific. This study will open a wide range of research avenues for future primate genomic research.

Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole-genome sequencing data for 809 individuals from 233 primate species and identified 4.3 million common protein-altering variants with orthologs in humans. We show that these variants can be inferred to have nondeleterious effects in humans based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases.

The novel coronavirus SARS-CoV-2, which in humans leads to the disease COVID-19, has caused global disruption and more than 2 million fatalities since it first emerged in late 2019. As we write, infection rates are at their highest point globally and are rising extremely rapidly in some areas due to more infectious variants. The primary target of SARS-CoV-2 is the cellular receptor angiotensin-converting

Biodiversity is declining on a planetary scale at an alarming rate due to anthropogenic factors. Classical biodiversity monitoring approaches are time-consuming, resource-intensive, and not scalable to address the current biodiversity crisis. The environmental DNA-based next-generation biomonitoring framework provides an efficient, scalable, and holistic solution for evaluating changes in various ecological entities. However, its scope is currently limited to monitoring targeted groups of organisms using metabarcoding, which suffers from various PCR-induced biases. To utilise the full potential of next-generation biomonitoring, we intended to develop PCR-free genomic technologies that can deliver unbiased biodiversity data across the tree of life in a single assay. Here, we present a novel metagenomic workflow comprising of a lysis-free extracellular DNA enrichment protocol from large-volume filtered water samples, a completely PCR-free library preparation step, an ultra-deep next-generation sequencing, and a pseudo-taxonomic assignment strategy using the dual lowest common ancestor algorithm. We demonstrate the utility of our approach in a pilot-scale spatially-replicated experimental setup in Chilika, a large hyper-diverse brackish lagoon ecosystem in India. Using incidence-based statistics, we show that biodiversity across the tree of life, from microorganisms to the relatively low-abundant macroorganisms such as Arthropods and Fishes, can be effectively detected with about one billion paired-end reads using our reproducible workflow. With decreasing costs of sequencing and the increasing availability of genomic resources from the earth biogenome project, our approach can be tested in different ecosystems and adapted for large-scale rapid assessment of biodiversity across the tree of life. *1

Long-term captive populations often accumulate genetic changes that are detrimental to their survival in the wild. Periodic genetic evaluation of captive populations is thus necessary to identify deleterious changes and minimize their impact through planned breeding. Pygmy hog (Porcula salvania) is an endangered species with a small population inhabiting the tall sub-Himalayan grasslands of Assam, India. A conservation breeding program of pygmy hog from six founders has produced a multi-generational captive population destined for reintroduction into the wild. However, the impact of conservation breeding on its genetic diversity remained undocumented. Here, we evaluate temporal genetic changes in 39 pygmy hogs from eight consecutive generations of a captive population using genome-wide SNPs, mitochondrial genomes, and MHC sequences, and explore the relationship between genetic diversity and reproductive success. We find that pygmy hog harbors a very low genome-wide heterozygosity (H) compared to other members of the Suidae family. However, within the captive population we find excess heterozygosity and a significant increase in H from the wild-caught founders to the individuals in subsequent generations due to the selective pairing strategy. The MHC and mitochondrial nucleotide diversities were lower in captive generations compared to the founders with a high prevalence of low-frequency MHC haplotypes and more unique mitochondrial genomes. Further, even though no signs of genetic inbreeding were observed from the estimates of individual inbreeding coefficient F and between individuals (FIS) in each generation, the kinship coefficient showed a slightly increasing trend in the recent generations, due to a relatively smaller non-random sample size compared to the entire captive population. Surprisingly, male pygmy hogs that had higher heterozygosity also showed lower breeding success. We briefly discuss the implications of our findings in the context of breeding management and recommend steps to minimize the genetic effects of long-term captive breeding.

Biodiversity is declining on a planetary scale at an alarming rate due to anthropogenic factors. Classical biodiversity monitoring approaches are time-consuming, resource-intensive, and not scalable to address the current biodiversity crisis. The environmental DNA-based next-generation biomonitoring framework provides an efficient, scalable, and holistic solution for evaluating changes in various ecological entities. However, its scope is currently limited to monitoring targeted groups of organisms using metabarcoding, which suffers from various PCR-induced biases. To utilise the full potential of next-generation biomonitoring, we intended to develop PCR-free genomic technologies that can deliver unbiased biodiversity data across the tree of life in a single assay. Here, we describe a novel metagenomic workflow comprising of a customised extracellular DNA enrichment protocol from large-volume filtered water samples, a completely PCR-free library preparation step, an ultra-deep next-generation sequencing, and a pseudo-taxonomic assignment strategy using the dual lowest common ancestor algorithm. We demonstrate the utility of our approach in a pilot-scale spatially-replicated experimental setup in Chilika, a large hyper-diverse brackish lagoon ecosystem in India. Using incidence-based statistics, we show that biodiversity across the tree of life, from microorganisms to the relatively low-abundant macroorganisms such as Arthropods and Fishes, can be effectively detected with about one billion paired-end reads using our reproducible workflow. With decreasing costs of sequencing and the increasing availability of genomic resources from the earth biogenome project, our approach can be tested in different ecosystems and adapted for large-scale rapid assessment of biodiversity across the tree of life