The soybean cyst nematode (Heterodera glycines) is a sedentary plant parasite that exceeds a billion dollars in yield losses annually. It has spread across the soybean-producing world, emerging as the primary pathogen of soybeans. This problem is exacerbated by H. glycines populations overcoming the limited sources of natural resistance in soybean and by the lack of effective and safe alternative treatments. Although there are genetic determinants that render soybean plants resistant to certain nematode genotypes, resistant soybean cultivars are increasingly ineffective because their multi-year usage has selected for virulent H. glycines populations. Successful H. glycines infection relies on the comprehensive re-engineering of soybean root cells into a syncytium, as well as the long-term suppression of host defenses to ensure syncytial viability. At the forefront of these complex molecular interactions are effectors, the proteins secreted by H. glycines into host root tissues. The mechanisms that control genomic effector acquisition, diversification, and selection are important insights needed for the development of essential novel control strategies. As a foundation to obtain this understanding, we developed a nine scaffold, 158Mb pseudomolecule assembly of the H. glycines genome using PacBio, Chicago, and Hi-C sequencing. An annotation of 22,465 genes was predicted using a Mikado pipeline informed by published short- and long-read expression data. Here we present results from our assembly and annotation of the H. glycines genome.

[Definitive version of this article may be found here] The mitochondrial gene cytochrome-c-oxidase subunit 1 (COI) is useful in many taxa for phylogenetics, population genetics, metabarcoding, and rapid species identifications. However, the phylum Ctenophora (comb jellies) has historically been difficult to study due to divergent mitochondrial sequences and the corresponding inability to amplify COI with degenerate and standard COI ‘barcoding’ primers. As a result, there are very few COI sequences available for ctenophores, despite over 200 described species in the phylum. Here, we designed new primers and amplified the COI fragment from members of all major groups of ctenophores, including many undescribed species. Phylogenetic analyses of the resulting COI sequences revealed high diversity within many groups that was not evident from more conserved 18S rDNA sequences, in particular among the Lobata. The COI phylogenetic results also revealed unexpected community structure within the genus Bolinopsis, suggested new species within the genus Bathocyroe, and supported the ecological and morphological differences of some species such as Lampocteis cruentiventer and similar lobates (Lampocteis sp. ‘V’ stratified by depth, and ‘A’ differentiated by color). The newly described primers reported herein provide important tools to enable researchers to illuminate the diversity of ctenophores worldwide via quick molecular identifications, improve the ability to analyze environmental DNA by improving reference libraries and amplifications, and enable a new breadth of population genetic studies.

Many model organisms have obtained a prominent status due to an advantageous combination of their life-history characteristics, genetic properties and also practical considerations. In non-crop plants, Arabidopsis thaliana is the most renowned model and has been used as study system to elucidate numerous biological processes at the molecular level. Once a complete genome sequence was available, research has markedly accelerated and further established A. thaliana as the reference to stimulate studies in other species with different biology. Within the Brassicaceae family, the arctic-alpine perennial Arabis alpina has become a model complementary to A. thaliana to study life-history evolution and ecological genomics in harsh environments. In this review, we provide an overview of the properties that facilitated the rapid emergence of A. alpina as a plant model. We summarize the evolutionary history of A. alpina, including the diversification of its mating system, and discuss recent progress in the molecular dissection of developmental traits that are related to its perennial life history and environmental adaptation. We indicate open questions from which future research might be developed in other Brassicaceae species or more distantly related plant families.

Identifying local adaptation in bottlenecked species is essential for conservation management. Selection detection methods have an important role in species management plans, assessments of adaptive capacity, and looking for responses to climate change. Yet, the allele frequency changes exploited in selection detection methods are similar to those caused by the strong neutral genetic drift expected during a bottleneck. Consequently, it is often unclear what accuracy selection detection methods have across bottlenecked populations. In this study, simulations were used to explore if signals of selection could be confidently distinguished from genetic drift across 23 bottlenecked and reintroduced populations of Alpine ibex (Capra ibex). The meticulously recorded demographic history of the Alpine ibex was used to generate comprehensive simulated SNP data. The simulated SNPs were then used to benchmark the confidence we could place in outliers identified in empirical Alpine ibex SNP data. Within the simulated dataset, the false positive rates were high for all selection detection methods but fell substantially when two or more methods were combined. True positive rates were consistently low and became negligible with increased stringency. Despite finding many outlier loci in the empirical Alpine ibex SNPs, none could be distinguished from genetic drift-driven false positives. Unfortunately, the low true positive rate also prevents the exclusion of recent local adaptation within the Alpine ibex. The baselines and stringent approach outlined here should be applied to other bottlenecked species to ensure the risk of false positive, or negative, signals of selection are accounted for in conservation management plans.

DNA metabarcoding is an important tool for molecular ecology. However, its effectiveness hinges on the quality of reference sequence databases and classification parameters employed. Here we evaluate the performance of MiFish 12S taxonomic assignments using a case study of California Current Large Marine Ecosystem fishes to determine best practices for metabarcoding. Specifically, we use a taxonomy cross-validation by identity framework to compare classification performance between a global database comprised of all available sequences and a curated database that only includes sequences of fishes from the California Current Large Marine Ecosystem. We demonstrate that the curated, regional database provides higher assignment accuracy than the comprehensive global database. We also document a tradeoff between accuracy and misclassification across a range of taxonomic cutoff scores, highlighting the importance of parameter selection for taxonomic classification. Furthermore, we compared assignment accuracy with and without the inclusion of additionally generated reference sequences. To this end, we sequenced tissue from 605 species using the MiFish 12S primers, adding 253 species to GenBank’s existing 550 California Current Large Marine Ecosystem fish sequences. We then compared species and reads identified from seawater environmental DNA samples using global databases with and without our generated references, and the regional database. The addition of new references allowed for the identification of 16 native taxa and 17.0% of total reads from eDNA samples, including species with vast ecological and economic value. Together these results demonstrate the importance of comprehensive and curated reference databases for effective metabarcoding and the need for locus-specific validation efforts.

Current knowledge on environmental distribution and taxon richness of free-living bacteria is mainly based on cultivation-independent investigations employing 16S rRNA gene sequencing methods. Yet, 16S rRNA genes are evolutionarily rather conserved, resulting in limited taxonomic and ecological resolutions provided by this marker. We used a faster evolving protein-encoding marker to reveal ecological patterns hidden within a single OTU defined by >99% 16S rRNA sequence similarity. The studied taxon, subcluster PnecC of the genus Polynucleobacter, represents a ubiquitous group of planktonic freshwater bacteria with cosmopolitan distribution, which is very frequently detected by diversity surveys of freshwater systems. Based on genome taxonomy and a large set of genome sequences, a sequence similarity threshold for delineation of species-like taxa could be established. In total, 600 species-like taxa were detected in 99 freshwater habitats scattered across three regions representing a latitudinal range of 3400 km (42°N to 71°N) and a pH gradient of 4.2 to 8.6. Besides the unexpectedly high richness, the increased taxonomic resolution revealed structuring of Polynucleobacter communities by a couple of macroecological trends, which was previously only demonstrated for phylogenetically much broader groups of bacteria. A unexpected pattern was the almost complete compositional separation of Polynucleobacter communities of Ca2+-rich and Ca2+-poor habitats, which strongly resembled the vicariance of plant species on silicate and limestone soils. The presented new cultivation-independent approach opened a window to an incredible, previously unseen diversity, and enables investigations aiming on deeper understanding of how environmental conditions shape bacterial communities and drive evolution of free-living bacteria.

The bean bug (Riptortus pedestris) causes great economic losses of soybeans by piercing and sucking pods and seeds. Although R. pedestris has become the focus of numerous studies associated with insect–microbe interactions, plant–insect interactions, and pesticide resistance, a lack of genomic resources has limited deeper insights. In this study, we report the first R. pedestris genome at the chromosomal level using PacBio, Illumina, and Hi-C technologies. The assembled genome was 1.193 Gb in size with a contig N50 of 13.97 Mb. More than 95.7% of the total genome bases were successfully anchored to 6 unique chromosomes, with the scaffold N50 reaching 181.34 Mb. Genome resequencing of male and female individuals and chromosomic staining demonstrated that the sex chromosome system of R. pedestris is XO, and the shortest chromosome is the X chromosome. In total, 21,562 protein-coding genes were predicted, 21,320 of which were validated as being expressed in different tissues or different developmental stages. Evolutionary analysis demonstrated that R. pedestris and Oncopeltus fasciatus formed a sister group and split ∼35 million years ago. Additionally, a 5.04 Mb complete genome of symbiotic Serratia marcescens Rip1 was assembled, and the virulence factors that account for successful colonization in the host midgut were identified. The high-quality R. pedestris genome provides a valuable resource for further research, as well as for the pest management of bug pests.

Interactions of organisms with their environment are complex and environmental regulation at different levels of biological organization is often non-linear. Therefore, the genotype to phenotype continuum requires study at multiple levels of organization. While studies of transcriptome regulation are now common for many species, quantitative studies of environmental effects on proteomes are needed. Here we report the generation of a data-independent acquisition (DIA) assay library that enables simultaneous targeted proteomics of thousands of Oreochromis niloticus kidney proteins using a label- and gel-free workflow that is well suited for ecologically relevant field samples. We demonstrate the usefulness of this DIA assay library by discerning environmental effects on the kidney proteome of O. niloticus. Moreover, we demonstrate that the DIA assay library approach generates data that are complimentary rather than redundant to transcriptomics data. Transcript and protein abundance differences in kidneys of tilapia acclimated to freshwater and brackish water (25 g/kg) were correlated for 2114 unique genes. A high degree of non-linearity in salinity-dependent regulation of transcriptomes and proteomes was revealed suggesting that the regulation of O. niloticus renal function by environmental salinity relies heavily on post-transcriptional mechanisms. The application of functional enrichment analyses using STRING and KEGG to DIA assay datasets is demonstrated by identifying myo-inositol metabolism, antioxidant and xenobiotic functions, and signaling mechanisms as key elements controlled by salinity in tilapia kidneys. The DIA assay library resource presented here can be adopted for other tissues and other organisms to study proteome dynamics during changing ecological contexts.

The diploid Poropuntius huangchuchieni in the cyprinid family, which is widely distributed in the Mekong and Red River basins, is one of the most closely related diploid progenitor-like species of allotetraploid common carp, which was generated by merging of two diploid genomes during evolution. Therefore, the P. huangchuchieni genome is essential for polyploidy evolution studies in Cyprinidae. Here, we report a high-quality chromosome-level genome assembly of P. huangchuchieni by integrating Oxford Nanopore and Hi-C technology. The assembled genome size was 1021.38 Mb, 895.66 Mb of which was anchored onto 25 chromosomes with a N50 of 32.93 Mb. The genome contained 486.28 Mb repetitive elements and 24,099 protein-coding genes. Approximately 95.9% of the complete BUSCOs were detected, suggesting a high completeness of the genome. Evolutionary analysis revealed that P. huangchuchieni diverged from Cyprinus carpio at approximately 12 Mya. Genome comparison between P. huangchuchieni and the B subgenome of C. carpio provided insights into chromosomal rearrangements during the allotetraploid speciation. With the complete gene set, 17,474 orthologous genes were identified between P. huangchuchieni and C. carpio, providing a broad view of the gene component in the allotetraploid genome, which is critical for future genetic analyses. The high-quality genomic dataset created for P. huangchuchieni provides a diploid progenitor-like reference for the evolution and adaptation of allotetraploid carps.

Fungi form diverse communities and play essential roles in many terrestrial ecosystems, yet there are methodological challenges in taxonomic and phylogenetic placement of fungi from environmental sequences. To address such challenges we investigated spatio-temporal structure of a fungal community using soil metabarcoding with four different sequencing strategies: short amplicon sequencing of the ITS2 region (300–400\ bp) with Illumina MiSeq, Ion Torrent Ion S5, and PacBio RS II, all from the same PCR library, as well as long amplicon sequencing of the full ITS and partial LSU regions (1200–1600\ bp) with PacBio RS II. Resulting community structure and diversity depended more on statistical method than sequencing technology. The use of long-amplicon sequencing enables construction of a phylogenetic tree from metabarcoding reads, which facilitates taxonomic identification of sequences. However, long reads present issues for denoising algorithms in diverse communities. We present a solution that splits the reads into shorter homologous regions prior to denoising, and then reconstructs the full denoised reads. In the choice between short and long amplicons, we suggest a hybrid approach using short amplicons for sampling breadth and depth, and long amplicons to characterize the local species pool for improved identification and phylogenetic analyses.

Characterization of microbial assemblages via environmental DNA metabarcoding is increasingly being used in routine monitoring programs due to its sensitivity and cost-effectiveness. Several programs have been developed recently which infer functional profiles from 16S rRNA gene data using hidden-state prediction (HSP) algorithms. These might offer an economic and scalable alter-native to shotgun metagenomics. To date, HSP-based methods have seen limited use for benthic marine surveys and their performance in these environments remains unevaluated. In this study, 16S rRNA metabarcoding was applied to sediment samples collected at 0 and ≥ 1200 m from Norwegian salmon farms, and three metabolic inference approaches (PAPRICA, PICRUSt2 and TAX4FUN2) evaluated against metagenomics and environmental data. While metabarcoding and metagenomics recovered a comparable functional diversity, the taxonomic composition differed be-tween approaches, with genera richness up to 20× higher for metabarcoding. Comparisons between the sensitivity (highest true positive rates) and specificity (lowest true negative rates) of HSP-based programs in detecting functions found in metagenomics data ranged, respectively, from 0.52 and 0.60 to 0.76 and 0.79. However, little correlation was observed between the relative abundance of their specific functions. Functional beta-diversity of HSP-based data was strongly associated with that of metagenomics (r ≥ 0.86 for PAPRICA and TAX4FUN2) and responded similarly to the impact of fish farm activities. Our results demonstrate that although HSP-based metabarcoding approaches provide a slightly different functional profile than metagenomics, partly due to recovering a distinct community, they represent a cost-effective and valuable tool for characterizing and assessing the effects of fish farming on benthic ecosystems.

The burbot (Lota lota) is the only member of the cod family (Gadidae) that is adapted solely to freshwater. This species shows the widest longitudinal range of freshwater fish in the world. The burbot is a good model for studies on adaptive genome evolution from marine to freshwater environment. However, no high-quality reference genome has been released. Here, the first chromosome-level genome of the burbot was constructed using PacBio long sequencing and Hi-C technology. A total of 95.24 Gb polished PacBio sequences were generated, and the preliminary genome assembly was 575.83 Mb in size with a contig N50 size of 2.15 Mb. The assembled sequences were anchored to 22 pseudo-chromosomes by using the Hi-C data. The final assembled genome after Hi-C correction was 575.92 Mb, with a contig N50 of 2.01 Mb and a scaffold N50 of 22.10 Mb. A total of 22,067 protein-coding genes were predicted, 94.82% of which were functionally annotated. Phylogenetic analyses indicated that burbot diverged with the Atlantic cod about 44.4 million years ago. In addition, 377 putative genes that appear to be under positive selection in burbot were identified. These positively selected genes might adapt to the freshwater environment. These genome data provide an invaluable resource for the ecological and evolutionary study of the order Gadiformes.

The Ocean Barcode Atlas (OBA) is a user friendly web service designed for biologists who wish to explore the biodiversity and biogeography of marine organisms locked in otherwise difficult to mine planetary scale DNA metabarcode datasets. Using just a web browser, a comprehensive picture of the diversity of a taxon or a barcode sequence is visualized graphically on world maps and interactive charts. Interactive results panels allow dynamic threshold adjustments and the display of diversity results in their environmental context measured at the time of sampling (temperature, oxygen, latitude, etc.). Ecological analyses such as alpha and beta-diversity plots are produced via publication quality vector graphics representations. Currently, the Ocean Barcode Altas is deployed online with the i) Tara Oceans eukaryotic 18S-V9 rDNA metabarcodes, ii) Tara Oceans 16S/18S rRNA miTags, and iii) 16S-V4V5 metabarcodes collected during the Malaspina-2010 expedition. Additional prokaryotic or eukaryotic plankton barcode datasets will be added upon availability, given they provide the required complement of barcodes (including raw reads to compute barcode abundance) associated with their contextual environmental variables. Ocean Barcode Atlas is a freely-available web service at: http://oba.mio.osupytheas.fr/ocean-atlas/.

DNA metabarcoding has become a powerful approach for analyzing complex communities from environmental samples, but there are still methodological challenges limiting its full potential. While conserved DNA markers, like 16S and 18S, often are not able to discriminate among closely related species, other more variable markers – like the fungal ITS region, may include considerable intraspecific variation, which can lead to over-splitting of species during DNA metabarcoding analyses. Here we assess the effects of intraspecific sequence variation in DNA metabarcoding, by analyzing local populations of eleven fungal species. We investigated the allelic diversity of ITS2 haplotypes using both Sanger sequencing and high throughput sequencing (HTS), coupled with error correction with the software DADA2. All focal species, except one, included some level of intraspecific variation in the ITS2 region. Overall, we observed a high correspondence between haplotypes generated by Sanger sequencing and HTS, with the exception of a few additional haplotypes detected using either approach. These extra haplotypes, often occurring in low frequencies, were likely due to PCR and sequencing errors or intragenomic variation in the rDNA region. The presence of intraspecific (and possibly intragenomic) variation in ITS2 suggest that haplotypes (or ASVs) should not be used as basic units in ITS-based fungal community analyses, but an extra clustering step is needed to approach species-level resolution.

Gradient Forests is a machine learning algorithm that is gaining in popularity for studying the environmental drivers of genomic variation and for incorporating genomic information into climate change impact assessments. Here we provide the first experimental evaluation of the ability of ‘genomic offsets’ - a metric of climate maladaptation derived from Gradient Forests - to predict organismal responses to environmental change. We used high-throughput sequencing, genome scans, and several methods (including Gradient Forests) to identify candidate loci associated with climate adaptation in balsam poplar (Populus balsamifera L.). Individuals collected throughout balsam poplar’s range also were planted in two common garden experiments. We used Gradient Forests to relate candidate loci to environmental gradients and to predict the expected magnitude of response (i.e., the genetic offset) of populations when transplanted from their “home” environment to the new environments in the common gardens. We then compared the predicted genetic offsets to measurements of population performance in the common gardens. We found the expected inverse relationship between genetic offset and performance in the common gardens: populations with larger predicted genetic offsets performed worse in the common gardens than populations with smaller offsets. Also, genetic offset better predicted performance in the common gardens than did ‘naive’ climate distances. Our results provide preliminary evidence that genomic offsets may provide a first order estimate of the degree of expected maladaptation of populations exposed to rapid environmental change.

The peach fruit moth (PFM), Carposina sasakii Matsumura, is a major phytophagous orchard pest widely distributed across Northeast Asia. Here, we report the chromosome-level genome for the PFM, representing the first genome for the family Carposinidae, from the lepidopteran superfamily Copromorphoidea. The genome was assembled into 404.83 Mb sequences using PacBio long-read and Illumina short-read sequences, including 275 contigs, with a contig N50 length of 2.62 Mb. All contigs were assembled into 32 linkage groups assisted by the Hi-C technique, including 30 autosomes, a female-specific W chromosome and a Z chromosome. BUSCO analysis showed that 98.2% genes were complete and 0.4% of genes were fragmented, while 1.4% of genes were missing in the assembled genome. In total, 23,218 protein-coding genes were predicted, of which 82.72% were functionally annotated. Because of the importance of diapause triggered by photoperiod in PFM, five circadian genes in the PFM as well as in the other related species were annotated, and potential genes related to diapause and photoperiodic reaction were also identified from transcriptome sequencing. In addition, manual annotation of detoxification gene families was undertaken and showed a higher number of ABC and GST genes in PFM than in most other lepidopterans, in contrast to a lower number of UGT genes, suggesting different detoxication pathways in this moth. The high-quality genome provides a resource for comparative evolutionary studies of this moth and its relatives within the context of radiations across Lepidoptera.

Understanding the processes of environmental DNA (eDNA) persistence and degradation is essential to determine the spatiotemporal scale of eDNA signals and accurately estimate species distribution. The effects of environmental factors on eDNA persistence have previously been examined; however, the influence of the physiochemical and molecular states of eDNA on its persistence is not completely understood. Here, we performed meta-analyses including 26 previously published papers on the estimation of first-order eDNA decay rate constants, and assessed the effects of filter pore size, DNA fragment size, target gene, and environmental conditions on eDNA decay rates. Almost all supported models included the interactions between the filter pore size and water temperature, between the target gene and water temperature, and between the target gene and water source, implying the influence of complex interactions between the eDNA state and environmental conditions on eDNA persistence. These findings were generally consistent with the results of a re-analysis of a previous tank experiment which measured the time-series changes in marine fish eDNA concentrations in multiple size fractions after fish removal. Our results suggest that the mechanism of eDNA persistence and degradation cannot be fully understood without knowing not only environmental factors but also cellular and molecular states of eDNA in water. Further verification of the relationship between eDNA state and persistence is required by obtaining more information on eDNA persistence in various experimental and environmental conditions, which will enhance our knowledge on eDNA persistence and support our findings.

Non-random mating among individuals can lead to spatial clustering of genetically similar individuals and population stratification. This deviation from panmixia is commonly observed in natural populations. Consequently, individuals can have parentage in single populations or involving hybridization between differentiated populations. Accounting for this mixture and structure is important when mapping the genetics of traits and learning about the formative evolutionary processes that shape genetic variation among individuals and populations. Stratified genetic relatedness among individuals is commonly quantified using estimates of ancestry that are derived from a statistical model. Development of these models for polyploid and mixed-ploidy individuals and populations has lagged behind those for diploids. Here, we extend and test a hierarchical Bayesian model, called entropy, which can utilize low-depth sequence data to estimate genotype and ancestry parameters in autopolyploid and mixed-ploidy individuals (including sex chromosomes and autosomes within individuals). Our analysis of simulated data illustrated the trade-off between sequencing depth and genome coverage and found lower error associated with low depth sequencing across a larger fraction of the genome than with high depth sequencing across a smaller fraction of the genome. The model has high accuracy and sensitivity as verified with simulated data and through analysis of admixture among populations of diploid and tetraploid Arabidopsis arenosa.