In brief in Figure 1, two main approaches to the study of aDNA are metabarcoding, the taxonomic identification of the community via analysis of short DNA sequences of one or a few genes, and metagenomics, the analysis of total DNA of the community via whole-genome sequencing. For workflow of the wet laboratory, total DNA is initially isolated from the sample, for example, sediment cores. Next, the DNA metabarcoding standard steps include PCR amplification, library preparation, and sequencing followed by bioinformatic analyses. Depending on the targeted organisms, the specific primers are used to amplify DNA fragments, e.g., the mitochondrial COI region [56], foraminiferal 37f hypervariable region [57-59], and the internal transcribed spacer (ITS) region [60]. For distinguishing samples during bioinformatic processing, specific tags or indexes are added using ligation or other PCR-round. After quantification and normalization steps, the final library is then sequenced on one of the various available sequencing platforms, e.g., Illumina, Ion Torrent, PacBio, or Oxford Nanopore. In contrast, after collecting suitable samples under the guideline of aDNA research, the wet lab workflow for (shotgun) metagenomics can be roughly divided into three steps: DNA extraction, library preparation, and sequencing, without PCR.
4.1. Metabarcoding and its limitations
To date, most paleoecological aDNA investigations have employed the widely used DNA metabarcoding method, usually, with a focus on a particular organismal group [61]. DNA metabarcoding represents a molecular approach to contemporary taxonomy and identification, e.g., plant [50, 62-65], fungi [60], foraminifera [57, 58], metazoan [56, 66, 67]. The PCR-metabarcoding approach uses primer pairs to target and maximize portions of the hypervariable regions of the phylogenetic marker genes. Amplicons from separate samples are then given molecular barcodes, pooled together, and sequenced by amplicon-based HTS approaches. Fragments of aDNA are analyzed with a bioinformatics pipeline and identified from environmental archives, by comparison, them against sequences of reference database taken from modern reference organisms [29, 36, 68, 69].
However, metabarcoding which is applied to environmental aDNA is complicated by its natural degradation. The PCR-based approach for sequencing can generate incorrect sequence data from aDNA for several reasons. The total amplified sequence count is likely to reflect the original abundance of different DNA sequences in the sample. Damages of aDNA could inhibit DNA polymerase progression or prevent primers from binding to templates during PCR. The aDNA fragments are extremely short and low-yields, while preferential random amplification is longer or requires abundant DNA molecules. As a result, a lot of PCR cycles are needed, and false-positive findings are more frequent, and heavily biased towards well-preserved or more abundant sequences, possibly from present-day DNA contamination during the first few cycles [37, 70]. It can be induced predictably biased in multi-template PCR and significantly distort the final output. To solve this problem, PCRs can be repeated independently and increase the total number of replicates for each sample as well as using negative controls should be applied [71]. This approach makes short and rare sequences more likely to be identified than if only one replicate were used since they are likely to be missed in a single PCR but should be expected in one or more of the repeat PCRs. Further, based on using genetic markers in molecular studies of previous paleo-microbiome research, the length of taxonomic marker genes is a major cause of differential amplification resulting in a taxonomic bias in ancient reconstructions [72].
4.2. Shotgun sequencing and Whole Genome Sequencing
Shotgun sequencing is the untargeted (shotgun) sequencing of all genetic material (metagenomics) present in a sample, which has the potential to look for population genomic variation from multi-taxon mixtures and independent of DNA fragment size [36, 72]. Compared to metabarcoding, the shotgun approach is less subject to bias introduced by laboratory processing, ever-reducing sequencing costs. Generally, shotgun sequencing randomly breaks DNA sequences of the entire chromosome or entire genome into many small fragments and reassembles the sequences by computers via observing the overlapping sequences or regions. The shotgun approach can detect this genomic variation of the population by utilizing extensive intraspecific genomic reference datasets [73, 74] or assembling de novo genomes [75, 76]. Furthermore, the whole-genome shotgun (WGS) method entails sequencing many overlapping DNA fragments in parallel and then using a computer to assemble the small fragments into larger contigs and, eventually, chromosomes within a short period. NGS has also been used to obtain RNA and pathogen genome sequences from ancient plant remains [77]. The adoption of NGS technologies significantly expanded the range of aDNA studies possible, enabling the analysis of full chloroplast [54, 78], and mitochondrial and nuclear genomes [79, 80] from ancient samples. For instance, chloroplast and mitochondrial genomes of single-celled microalgae (Nannochloropsis limnetica) were successfully reconstructed from 20 000-year-old lake sediments [12].
Shotgun sequencing is a faster method and cheaper to carry out compared with traditional sequencing. Usefully, the advent of the shotgun approach permits statistical data analyses to detect specific substitutions that are normally present at the ends of ancient DNA fragments, therefore confirming whether a sequence or set of sequences is relatively ancient and not modern contamination, as well as improving the specificity and sensitivity of taxonomic identification [81, 82]. In some cases, as for eukaryotes in sedaDNA, if the targeted DNA is rare compared to the total genomic DNA, producing large numbers of short sequencing reads [83] is required to recover sufficient genetic information and perform meaningful statistical analyses, particularly useful for aDNA analysis for its fragmentation and degradation [84]. Usefully, the ends of older sequences retrieved using a shotgun approach will show deamination damage, which can confirm whether a sequence or set of sequences is relatively ancient and not modern contamination. Although whole ancient genomes are becoming more readily accessible, mitochondrial [13, 85, 86] or chloroplast [12, 54, 78] genomes are an alternative choice in aDNA studies dealing with samples with high DNA degradation, and low DNA yields. Before sequencing, another alternative option applies the hybridization capture technique [78, 87]. The constraint of shotgun sequencing might be solved by using the hybridization capture approach before sequencing to enrich the DNA of the targeted species in the samples. To do this, small segments of DNA from the species and target sites of interest can be used as baits, with the matching sites of interest in ancient DNA libraries being hybridized. This technique, originally developed for modern DNA, is commonly applied in ancient DNA studies, particularly for use on single specimens [88] and with a focus on mammals, mostly using mitochondrial DNA [89, 90], chloroplast and nuclear DNA [78, 91-93], cave sediments [19], permafrost samples [22].
4.3. Bioinformatics considerations
Now the shotgun approach provides an alternative approach to metabarcoding for determining for taxonomic and functional profiling of metagenome-assembled genomes. The amount of genetic data has risen exponentially and vast amounts of that are mostly uploaded to and stored on public archives, for example, European Bioinformatic Institute’s (EBI) European Nucleotide Archive (ENA, https://www.ebi.ac.uk/ena/) or the US National Center for Biotechnology Information (NCBI)’s Sequence Read Archive (SRA, https://www.ncbi.nlm.nih.gov/sra). However, it brings huge challenges at the stage of bioinformatics for its analysis. A vast of bioinformatics tools, protocols and studies have been introduced to improve efficiency in analyzing ancient metagenomic data. Bioinformatics tools designed for aDNA metagenomics as mapDamage [94-96], PyDamage [97] or open-sourced/mapping guidelines pipeline [98, 99] for estimating DNA damage, SourceTracker [100] for identifying the proportions of endogenous and contaminant signals in each sample; resolving the sequencing errors [96, 101]; MEGAN [102, 103], PIA [104] for taxonomic identification; KEGG [105], EGGnog [106], SEED [107] protein databases for functional profiles can be analysed in MEGAN, reference-free alternative approaches based on k-mer counts [108] to annotate metagenomes. However, differences between metagenomic analysis pipelines produce systematic biases [25], which will require the development of more accurate analysis pipelines for ancient DNA.
Nevertheless, several issues currently limit the shotgun sequencing approach. Cytosine deamination patterns of sedaDNA molecules impede de novo assembly of contigs [10, 109]. The limitation of sufficiently curated genome-scale reference data substantially reduces the potential for success of the bioinformatic analyses with metagenomic data, for example, plants [77, 110], and eukaryotic [111, 112]. The large fraction of taxa present in the environment, but not represented in databases is still problematic. In these cases, metagenomic data can vary in content across samples from the same or similar environments. In contrast, there are more than 130,000 genome or near-complete sequences available from different phyla that have been sequenced along with a variety of microorganisms, including archaea, fungi, and viruses [113-115]. Based on the annotated reference genomes or clade-specific [116] or universal markers [117], appropriate normalization by genome size [55], and taxon relative abundances can be estimated. This led to the development of the field of paleomicrobiology [1, 32], to the analysis of deposited microbial DNA to study microbial diversity, ecology, and evolution in environmental archives.
4.4. Applications of ancient environmental metagenomics
The shotgun of sedaDNA in paleoecology from lake sediment cores combined a multi-proxy approach [14], and marine environments [37, 40], which has provided greater taxonomic resolution and extended the historical record of aquatic ecosystems to centennial or even millennial time scales. These sedaDNA archives can be used to characterize biodiversity trends, illuminate past food web dynamics, and reconstruct long-term environmental changes in aquatic ecosystems. As ecology and paleoecology merge, both short-term and long-term trends as a consequence of human actions on aquatic ecosystems have been traced using paleogenomic research in freshwater ecosystems [118-120] and marine sediments [121, 122].
Paleogenomics is a branch of research concerned with reconstructing and analyzing genetic data from extinct organisms. Ancient genomes may be used to explore the evolution of present species in great detail by sequencing ancient DNA preserved in subfossil remains [54, 123] or environmental archives [1, 12]. By analyzing large-scale environmental DNA metagenomic study of ancient plant and mammal communities, tracking the ancient population origins, movements and interrelationships, the evolutionary genomic changes at both macro- and micro-evolutionary temporal scales of the microbiome, vegetation, animals and Homo species [12, 13], as well as identification of phenotypic features over large temporal and geographical scales [89, 90, 124]. For example, a study on DNA retrieved from Arctic permafrost and lake sediment samples by Wang et al. [13] demonstrated that steppe–tundra flora dominated the Arctic during the Last Glacial Maximum, followed by the regional divergence of vegetation during the Holocene epoch. The extinction of several now-extinct megafauna species enabled the survival of some ancient plants and animals. Moreover, analysis of mammoth environmental DNA reveals a previously unsampled mitochondrial lineage. Additionally, the genetic material preserved in sedimentary archives offers a unique way to uncover the role of microorganisms in past ecosystems and their responses to environmental perturbations. Genomic reconstruction of historical and present microbial communities from ancient permafrost samples in Siberian broadened our understanding of biogeochemical changes [32]. Furthermore, this study provides insights into microorganisms' long-term survival strategies from the past paleoenvironment to present-day freezing-temperature conditions.
V. Summary
In conclusion, the fields of aDNA are increasingly turning to the environmental archives and provide great potential for entire paleoecosystems and paleoclimate reconstructions. As technology advances and procedures are optimized, metagenomic-based approaches, from metabarcoding (amplicon-based) to shotgun and true ancient metagenomics, are part of the next breakthrough in paleogenetic, offering the potential for better species identification and quantitative estimations of their abundances in large-scale biodiversity comparisons over both time and place. Importantly, further basic studies are needed to use a full understanding of its potential and limitations for applications of the use of metagenomics for ancient eDNA.
Acknowledgement
The research was financially supported by the Norwegian Financial Mechanism for 2014-2021, project no 2019/34/H/ST10/00682, full title: “Sedimentary ancient DNA - a new proxy to investigate the impact of environmental change on past and present biodiversity in Nordic Seas”.
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