Genome sequencing and population genomics in non-model organisms

Genomics identifies koala populations at risk across eastern Australia

Koalas are an iconic, endangered, Australian marsupial. Disease, habitat destruction, and catastrophic mega-fires have reduced koalas to remnant patches of their former range. With increased likelihood of extreme weather events and ongoing habitat clearing across Australia, koala populations are vulnerable to further declines and isolation. Small, isolated populations are considered at risk when there is increased inbreeding, erosion of genomic diversity, and loss of adaptive potential, all of which reduce their ability to respond to prevailing threats. Here, we characterized the current genomic landscape of koalas using data from The Koala Genome Survey, a joint initiative between the Australian Federal and New South Wales Governments that aimed to provide a future-proofed baseline genomic dataset across the koala's range in eastern Australia. We identified several regions of the continent where koalas have low genomic diversity and high inbreeding, as measured by runs of homozygosity. These populations included coastal sites along southeast Queensland and northern and mid-coast New South Wales, as well as southern New South Wales and Victoria. Analysis of genomic vulnerability to future climates revealed that northern koala populations were more at risk due to the extreme expected changes in this region, but that the adaptation required was minimal compared with other species. Our genomic analyses indicate that continued development, particularly linear infrastructure along coastal sites, and resultant habitat destruction are causing isolation and subsequent genomic erosion across many koala populations. Habitat protection and the formation of corridors must be employed for all koala populations to maintain current levels of diversity. For highly isolated koala populations, active management may be the only way to improve genomic diversity in the short term. If koalas are to be conserved for future generations, reversing their genomic isolation must be a priority in conservation planning.

TraitTrainR: accelerating large-scale simulation under models of continuous trait evolution

Motivation

The scale and scope of comparative trait data are expanding at unprecedented rates, and recent advances in evolutionary modeling and simulation sometimes struggle to match this pace. Well-organized and flexible applications for conducting large-scale simulations of evolution hold promise in this context for understanding models and more so our ability to confidently estimate them with real trait data sampled from nature.

Results

We introduce TraitTrainR, an R package designed to facilitate efficient, large-scale simulations under complex models of continuous trait evolution. TraitTrainR employs several output formats, supports popular trait data transformations, accommodates multi-trait evolution, and exhibits flexibility in defining input parameter space and model stacking. Moreover, TraitTrainR permits measurement error, allowing for investigation of its potential impacts on evolutionary inference. We envision a wealth of applications of TraitTrainR, and we demonstrate one such example by examining the problem of evolutionary model selection in three empirical phylogenetic case studies. Collectively, these demonstrations of applying TraitTrainR to explore problems in model selection underscores its utility and broader promise for addressing key questions, including those related to experimental design and statistical power, in comparative biology.

Availability and implementation

TraitTrainR is developed in R 4.4.0 and is freely available at https://github.com/radamsRHA/TraitTrainR/, which includes detailed documentation, quick-start guides, and a step-by-step tutorial.

Utilizing proteomics to identify and optimize microalgae strains for high-quality dietary protein: a review

Algae-derived protein has immense potential to provide high-quality protein foods for the expanding human population. To meet its potential, a broad range of scientific tools are required to identify optimal algal strains from the hundreds of thousands available and identify ideal growing conditions for strains that produce high-quality protein with functional benefits. A research pipeline that includes proteomics can provide a deeper interpretation of microalgal composition and biochemistry in the pursuit of these goals. To date, proteomic investigations have largely focused on pathways that involve lipid production in selected microalgae species. Herein, we report the current state of microalgal proteome measurement and discuss promising approaches for the development of protein-containing food products derived from algae.

Whole genome resequencing-based analysis of plateau adaptation in Meiren yak (Bos grunniens)

The Meiren yak is an important genetic resource in Gansu Province, China. In this study, we aimed to explore the evolutionary history and population structure of the genetic resource of Meiren yak and to mine the characteristic genes of Meiren yak. We analysed a total of 93 yaks of eight yak breeds based on whole genome resequencing combined with population genomics and used θπ ratio and Fst method to screen the selected sites in the genome region. The results proved that Meiren yak can be used as a potential genetic resource in Gansu Province. The genes in Meiren yak with positive selection in selection signal analysis were subjected to the Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses, which indicated that the genes were related to the adaptability to high altitude and hypoxic environment. By analysing the genetic variation of Meiren yak at the genome-wide level, this study provided a theoretical basis for genetic improvement of Meiren yak and for the development of high-quality yak resources.

Beyond genes-for-behaviour: The potential for genomics to resolve long-standing questions in avian brood parasitism

Behavioural ecology by definition of its founding 'Tinbergian framework' is an integrative field, however, it lags behind in incorporating genomic methods. 'Finding the gene/s for a behaviour' is still rarely feasible or cost-effective in the wild but as we show here, genomic data can be used to address broader questions. Here we use avian brood parasitism, a model system in behavioural ecology as a case study to highlight how behavioural ecologists could use the full potential of state-of-the-art genomic tools. Brood parasite-host interactions are one of the most easily observable and amenable natural laboratories of antagonistic coevolution, and as such have intrigued evolutionary biologists for decades. Using worked examples, we demonstrate how genomic data can be used to study the causes and mechanisms of (co)evolutionary adaptation and answer three key questions for the field: (i) Where and when should brood parasitism evolve?, (ii) When and how should hosts defend?, and (iii) Will coevolution persist with ecological change? In doing so, we discuss how behavioural and molecular ecologists can collaborate to integrate Tinbergen's questions and achieve the coherent science that he promoted to solve the mysteries of nature.

Whole-genome resequencing improves the utility of otoliths as a critical source of DNA for fish stock research and monitoring

Fish ear bones, known as otoliths, are often collected in fisheries to assist in management, and are a common sample type in museum and national archives. Beyond their utility for ageing, morphological and trace element analysis, otoliths are a repository of valuable genomic information. Previous work has shown that DNA can be extracted from the trace quantities of tissue remaining on the surface of otoliths, despite the fact that they are often stored dry at room temperature. However, much of this work has used reduced representation sequencing methods in clean lab conditions, to achieve adequate yields of DNA, libraries and ultimately single-nucleotide polymorphisms (SNPs). Here, we pioneer the use of small-scale (spike-in) sequencing to screen contemporary otolith samples prepared in regular molecular biology (in contrast to clean) laboratories for contamination and quality levels, submitting for whole-genome resequencing only samples above a defined endogenous DNA threshold. Despite the typically low quality and quantity of DNA extracted from otoliths, we are able to produce whole-genome libraries and ultimately sets of filtered, unlinked and even putatively adaptive SNPs of ample numbers for downstream uses in population, climate and conservation genomics. By comparing with a set of tissue samples from the same species, we are able to highlight the quality and efficacy of otolith samples from DNA extraction and library preparation, to bioinformatic preprocessing and SNP calling. We provide detailed schematics, protocols and scripts of our approach, such that it can be adopted widely by the community, improving the use of otoliths as a source of valuable genomic data.

TargetCall: eliminating the wasted computation in basecalling via pre-basecalling filtering

Basecalling is an essential step in nanopore sequencing analysis where the raw signals of nanopore sequencers are converted into nucleotide sequences, that is, reads. State-of-the-art basecallers use complex deep learning models to achieve high basecalling accuracy. This makes basecalling computationally inefficient and memory-hungry, bottlenecking the entire genome analysis pipeline. However, for many applications, most reads do not match the reference genome of interest (i.e., target reference) and thus are discarded in later steps in the genomics pipeline, wasting the basecalling computation. To overcome this issue, we propose TargetCall, the first pre-basecalling filter to eliminate the wasted computation in basecalling. TargetCall's key idea is to discard reads that will not match the target reference (i.e., off-target reads) prior to basecalling. TargetCall consists of two main components: (1) LightCall, a lightweight neural network basecaller that produces noisy reads, and (2) Similarity Check, which labels each of these noisy reads as on-target or off-target by matching them to the target reference. Our thorough experimental evaluations show that TargetCall 1) improves the end-to-end basecalling runtime performance of the state-of-the-art basecaller by 3.31 × while maintaining high ( 98.88 % ) recall in keeping on-target reads, 2) maintains high accuracy in downstream analysis, and 3) achieves better runtime performance, throughput, recall, precision, and generality than prior works. TargetCall is available at https://github.com/CMU-SAFARI/TargetCall.

Integrating evolutionary genomics of forest trees to inform future tree breeding amid rapid climate change

Global climate change is leading to rapid and drastic shifts in environmental conditions, posing threats to biodiversity and nearly all life forms worldwide. Forest trees serve as foundational components of terrestrial ecosystems and play a crucial and leading role in combating and mitigating the adverse effects of extreme climate events, despite their own vulnerability to these threats. Therefore, understanding and monitoring how natural forests respond to rapid climate change is a key priority for biodiversity conservation. Recent progress in evolutionary genomics, driven primarily by cutting-edge multi-omics technologies, offers powerful new tools to address several key issues. These include precise delineation of species and evolutionary units, inference of past evolutionary histories and demographic fluctuations, identification of environmentally adaptive variants, and measurement of genetic load levels. As the urgency to deal with more extreme environmental stresses grows, understanding the genomics of evolutionary history, local adaptation, future responses to climate change, and conservation and restoration of natural forest trees will be critical for research at the nexus of global change, population genomics, and conservation biology. In this review, we explore the application of evolutionary genomics to assess the effects of global climate change using multi-omics approaches and discuss the outlook for breeding of climate-adapted trees.

Contrasting Genomic Diversity and Inbreeding Levels Among Two Closely Related Falcon Species With Overlapping Geographic Distributions

Genomic resources are valuable to examine historical demographic patterns and their effects to better inform management and conservation of threatened species. We evaluated population trends and genome-wide variation in the near-threatened Orange-breasted Falcon (Falco deiroleucus) and its more common sister species, the Bat Falcon (F. rufigularis), to explore how the two species differ in genomic diversity as influenced by their contrasting long-term demographic histories. We generated and aligned whole genome resequencing data for 12 Orange-breasted Falcons and 9 Bat Falcons to an annotated Gyrfalcon (F. rusticolus) reference genome that retained approximately 22.4 million biallelic autosomal SNPs (chromosomes 1-22). Our analyses indicated much lower genomic diversity in Orange-breasted Falcons compared to Bat Falcons. All sampled Orange-breasted Falcons were significantly more inbred than the sampled Bat Falcons, with values similar to those observed in island-mainland species comparisons. The distribution of runs of homozygosity showed variation suggesting long-term low population size and the possibility of bottlenecks in Orange-breasted Falcons contrasting with consistently larger populations in Bat Falcons. Analysis of genetic load suggests that Orange-breasted Falcons are less likely to experience inbreeding depression than Bat Falcons due to reduced inbreeding load but are at elevated risk from fixation of deleterious gene variants and perhaps a reduced adaptive potential. These genomic analyses highlight differences in the historical demography of two closely related species that have influenced their current genomic diversity and should result in differing strategies for their continued conservation.

A Latitudinal Gradient of Reference Genomes

Global inequality rooted in legacies of colonialism and uneven development can lead to systematic biases in scientific knowledge. In ecology and evolutionary biology, findings, funding and research effort are disproportionately concentrated at high latitudes, while biological diversity is concentrated at low latitudes. This discrepancy may have a particular influence in fields like phylogeography, molecular ecology and conservation genetics, where the rise of genomics has increased the cost and technical expertise required to apply state-of-the-art methods. Here, we ask whether a fundamental biogeographic pattern-the latitudinal gradient of species richness in tetrapods-is reflected in the available reference genomes, an important data resource for various applications of molecular tools for biodiversity research and conservation. We also ask whether sequencing approaches differ between the Global South and Global North, reviewing the last 5 years of conservation genetics research in four leading journals. We find that extant reference genomes are scarce relative to species richness at low latitudes and that reduced representation and whole-genome sequencing are disproportionately applied to taxa in the Global North. We conclude with recommendations to close this gap and improve international collaborations in biodiversity genomics.

Demographic History and Inbreeding in Two Declining Sea Duck Species Inferred From Whole-Genome Sequence Data

Anthropogenic impact has transitioned from threatening already rare species to causing significant declines in once numerous organisms. Long-tailed duck (Clangula hyemalis) and velvet scoter (Melanitta fusca) were once important quarry sea duck species in NW Europe, but recent declines resulted in their reclassification as vulnerable on the IUCN Red List. We sequenced and assembled genomes for both species and resequenced 15 individuals of each. Using analyses based on site frequency spectra and sequential Markovian coalescence, we found C. hyemalis to show more historical demographic stability, whereas M. fusca was affected particularly by the Last (Weichselian) Glaciation. This likely reflects C. hyemalis breeding continuously across the Arctic, with cycles of glaciation primarily shifting breeding areas south or north without major population declines, whereas the more restricted southern range of M. fusca would lead to significant range contraction during glaciations. Both species showed evidence of declines over the past thousands of years, potentially reflecting anthropogenic pressures with the recent decline indicating an accelerated process. Analysis of runs of homozygosity (ROH) showed low but nontrivial inbreeding, with F ROH from 0.012 to 0.063 in C. hyemalis and ranging from 0 to 0.047 in M. fusca. Lengths of ROH suggested that this was due to ongoing background inbreeding rather than recent declines. Overall, despite demographically important declines, this has not yet led to strong inbreeding and genetic erosion, and the most pressing conservation concern may be the risk of density-dependent (Allee) effects. We recommend monitoring of inbreeding using ROH analysis as a cost-efficient method to track future developments to support effective conservation of these species.

Taking advantage of reference-guided assembly in a slowly-evolving lineage: Application to Testudo graeca

BACKGROUND

Obtaining de novo chromosome-level genome assemblies greatly enhances conservation and evolutionary biology studies. For many research teams, long-read sequencing technologies (that produce highly contiguous assemblies) remain unaffordable or unpractical. For the groups that display high synteny conservation, these limitations can be overcome by a reference-guided assembly using a close relative genome. Among chelonians, tortoises (Testudinidae) are considered one of the most endangered taxa, which calls for more genomic resources. Here we make the most of high synteny conservation in chelonians to produce the first chromosome-level genome assembly of the genus Testudo with one of the most iconic tortoise species in the Mediterranean basin: Testudo graeca.

RESULTS

We used high-quality, paired-end Illumina sequences to build a reference-guided assembly with the chromosome-level reference of Gopherus evgoodei. We reconstructed a 2.29 Gb haploid genome with a scaffold N50 of 107.598 Mb and 5.37% gaps. We sequenced 25,998 protein-coding genes, and identified 41.2% of the assembly as repeats. Demographic history reconstruction based on the genome revealed two events (population decline and recovery) that were consistent with previously suggested phylogeographic patterns for the species. This outlines the value of such reference-guided assemblies for phylogeographic studies.

CONCLUSIONS

Our results highlight the value of using close relatives to produce de novo draft assemblies in species where such resources are unavailable. Our annotated genome of T. graeca paves the way to delve deeper into the species' evolutionary history and provides a valuable resource to enhance direct conservation efforts on their threatened populations.

A spatial approach to jointly estimate Wright's neighborhood size and long-term effective population size

Spatially continuous patterns of genetic differentiation, which are common in nature, are often poorly described by existing population genetic theory or methods that assume either panmixia or discrete, clearly definable populations. There is therefore a need for statistical approaches in population genetics that can accommodate continuous geographic structure, and that ideally use georeferenced individuals as the unit of analysis, rather than populations or subpopulations. In addition, researchers are often interested in describing the diversity of a population distributed continuously in space; this diversity is intimately linked to both the dispersal potential and the population density of the organism. A statistical model that leverages information from patterns of isolation by distance to jointly infer parameters that control local demography (such as Wright's neighborhood size), and the long-term effective size (Ne) of a population would be useful. Here, we introduce such a model that uses individual-level pairwise genetic and geographic distances to infer Wright's neighborhood size and long-term Ne. We demonstrate the utility of our model by applying it to complex, forward-time demographic simulations as well as an empirical dataset of the two-form bumblebee (Bombus bifarius). The model performed well on simulated data relative to alternative approaches and produced reasonable empirical results given the natural history of bumblebees. The resulting inferences provide important insights into the population genetic dynamics of spatially structured populations.

Improved assembly of the Pungitius pungitius reference genome

The nine-spined stickleback (Pungitius pungitius) has been increasingly used as a model system in studies of local adaptation and sex chromosome evolution but its current reference genome assembly is far from perfect, lacking distinct sex chromosomes. We generated an improved assembly of the nine-spined stickleback reference genome (98.3% BUSCO completeness) with the aid of linked-read mapping. While the new assembly (v8) was of similar size as the earlier version (v7), we were able to assign 4.4 times more contigs to the linkage groups and improve the contiguity of the genome. Moreover, the new assembly contains a ∼22.8 Mb Y-linked scaffold (LG22) consisting mainly of previously assigned X-contigs, putative Y-contigs, putative centromere contigs, and highly repetitive elements. The male individual showed an even mapping depth on LG12 (pseudo X chromosome) and LG22 (Y-linked scaffold) in the segregating sites, suggesting near-pure X and Y representation in the v8 assembly. A total of 26,803 genes were annotated, and about 33% of the assembly was found to consist of repetitive elements. The high proportion of repetitive elements in LG22 (53.10%) suggests it can be difficult to assemble the complete sequence of the species' Y chromosome. Nevertheless, the new assembly is a significant improvement over the previous version and should provide a valuable resource for genomic studies of stickleback fishes.

Genome resequencing reveals population divergence and local adaptation of blacklegged ticks in the United States

Tick vectors and tick-borne disease are increasingly impacting human populations globally. An important challenge is to understand tick movement patterns, as this information can be used to improve management and predictive modelling of tick population dynamics. Evolutionary analysis of genetic divergence, gene flow and local adaptation provides insight on movement patterns at large spatiotemporal scales. We develop low coverage, whole genome resequencing data for 92 blacklegged ticks, Ixodes scapularis, representing range-wide variation across the United States. Through analysis of population genomic data, we find that tick populations are structured geographically, with gradual isolation by distance separating three population clusters in the northern United States, southeastern United States and a unique cluster represented by a sample from Tennessee. Populations in the northern United States underwent population contractions during the last glacial period and diverged from southern populations at least 50 thousand years ago. Genome scans of selection provide strong evidence of local adaptation at genes responding to host defences, blood-feeding and environmental variation. In addition, we explore the potential of low coverage genome sequencing of whole-tick samples for documenting the diversity of microbial pathogens and recover important tick-borne pathogens such as Borrelia burgdorferi. The combination of isolation by distance and local adaptation in blacklegged ticks demonstrates that gene flow, including recent expansion, is limited to geographical scales of a few hundred kilometres.

Genetic analysis of a Kaijiang duck conservation population through genome-wide scan

1. The Kaijiang duck is a native Chinese breed known for its excellent egg laying performance, killing-out percentage (88.57%), and disease resistance. The assessment of population genetic structure is the basis for understanding the genetics of indigenous breeds and for their protection and management.2. In this study, whole-genome sequencing was performed on 60 Kaijiang ducks to identify genetic variations and investigate the population structure. Homozygosity (ROH) analysis was conducted to assess inbreeding levels in the population.3. The study revealed a moderate level of inbreeding, indicated by an average inbreeding coefficient of 0.1043. This may impact the overall genetic diversity.4. Genomic Regions of Interest identified included 168 genomic regions exhibiting high levels of autozygosity. These regions were associated with processes including muscle growth, pigmentation, neuromodulation, and growth and reproduction.5. The significance of these pathways indicated their potential role in shaping the desirable traits of the Kaijiang duck. These findings provide insights into the genetic basis of the Kaijiang duck's desirable traits and can inform future breeding and conservation efforts.

Gene flow throughout the evolutionary history of a colour polymorphic and generalist clownfish

Even seemingly homogeneous on the surface, the oceans display high environmental heterogeneity across space and time. Indeed, different soft barriers structure the marine environment, which offers an appealing opportunity to study various evolutionary processes such as population differentiation and speciation. Here, we focus on Amphiprion clarkii (Actinopterygii; Perciformes), the most widespread of clownfishes that exhibits the highest colour polymorphism. Clownfishes can only disperse during a short pelagic larval phase before their sedentary adult lifestyle, which might limit connectivity among populations, thus facilitating speciation events. Consequently, the taxonomic status of A. clarkii has been under debate. We used whole-genome resequencing data of 67 A. clarkii specimens spread across the Indian and Pacific Oceans to characterize the species' population structure, demographic history and colour polymorphism. We found that A. clarkii spread from the Indo-Pacific Ocean to the Pacific and Indian Oceans following a stepping-stone dispersal and that gene flow was pervasive throughout its demographic history. Interestingly, colour patterns differed noticeably among the Indonesian populations and the two populations at the extreme of the sampling distribution (i.e. Maldives and New Caledonia), which exhibited more comparable colour patterns despite their geographic and genetic distances. Our study emphasizes how whole-genome studies can uncover the intricate evolutionary past of wide-ranging species with diverse phenotypes, shedding light on the complex nature of the species concept paradigm.

GALEON: a comprehensive bioinformatic tool to analyse and visualize gene clusters in complete genomes

MOTIVATION

Gene clusters, defined as a set of genes encoding functionally related proteins, are abundant in eukaryotic genomes. Despite the increasing availability of chromosome-level genomes, the comprehensive analysis of gene family evolution remains largely unexplored, particularly for large and highly dynamic gene families or those including very recent family members. These challenges stem from limitations in genome assembly contiguity, particularly in repetitive regions such as large gene clusters. Recent advancements in sequencing technology, such as long reads and chromatin contact mapping, hold promise in addressing these challenges.

RESULTS

To facilitate the identification, analysis, and visualization of physically clustered gene family members within chromosome-level genomes, we introduce GALEON, a user-friendly bioinformatic tool. GALEON identifies gene clusters by studying the spatial distribution of pairwise physical distances among gene family members along with the genome-wide gene density. The pipeline also enables the simultaneous analysis and comparison of two gene families and allows the exploration of the relationship between physical and evolutionary distances. This tool offers a novel approach for studying the origin and evolution of gene families.

AVAILABILITY AND IMPLEMENTATION

GALEON is freely available from https://www.ub.edu/softevol/galeon and https://github.com/molevol-ub/galeon.

The cacao gene atlas: a transcriptome developmental atlas reveals highly tissue-specific and dynamically-regulated gene networks in Theobroma cacao L

BACKGROUND

Theobroma cacao, the cocoa tree, is a tropical crop grown for its highly valuable cocoa solids and fat which are the basis of a 200-billion-dollar annual chocolate industry. However, the long generation time and difficulties associated with breeding a tropical tree crop have limited the progress of breeders to develop high-yielding disease-resistant varieties. Development of marker-assisted breeding methods for cacao requires discovery of genomic regions and specific alleles of genes encoding important traits of interest. To accelerate gene discovery, we developed a gene atlas composed of a large dataset of replicated transcriptomes with the long-term goal of progressing breeding towards developing high-yielding elite varieties of cacao.

RESULTS

We describe the creation of the Cacao Transcriptome Atlas, its global characterization and define sets of genes co-regulated in highly organ- and temporally-specific manners. RNAs were extracted and transcriptomes sequenced from 123 different tissues and stages of development representing major organs and developmental stages of the cacao lifecycle. In addition, several experimental treatments and time courses were performed to measure gene expression in tissues responding to biotic and abiotic stressors. Samples were collected in replicates (3-5) to enable statistical analysis of gene expression levels for a total of 390 transcriptomes. To promote wide use of these data, all raw sequencing data, expression read mapping matrices, scripts, and other information used to create the resource are freely available online. We verified our atlas by analyzing the expression of genes with known functions and expression patterns in Arabidopsis (ACT7, LEA19, AGL16, TIP13, LHY, MYB2) and found their expression profiles to be generally similar between both species. We also successfully identified tissue-specific genes at two thresholds in many tissue types represented and a set of genes highly conserved across all tissues.

CONCLUSION

The Cacao Gene Atlas consists of a gene expression browser with graphical user interface and open access to raw sequencing data files as well as the unnormalized and CPM normalized read count data mapped to several cacao genomes. The gene atlas is a publicly available resource to allow rapid mining of cacao gene expression profiles. We hope this resource will be used to help accelerate the discovery of important genes for key cacao traits such as disease resistance and contribute to the breeding of elite varieties to help farmers increase yields.

Temporal genomics in Hawaiian crickets reveals compensatory intragenomic coadaptation during adaptive evolution

Theory predicts that compensatory genetic changes reduce negative indirect effects of selected variants during adaptive evolution, but evidence is scarce. Here, we test this in a wild population of Hawaiian crickets using temporal genomics and a high-quality chromosome-level cricket genome. In this population, a mutation, flatwing, silences males and rapidly spread due to an acoustically-orienting parasitoid. Our sampling spanned a social transition during which flatwing fixed and the population went silent. We find long-range linkage disequilibrium around the putative flatwing locus was maintained over time, and hitchhiking genes had functions related to negative flatwing-associated effects. We develop a combinatorial enrichment approach using transcriptome data to test for compensatory, intragenomic coevolution. Temporal changes in genomic selection were distributed genome-wide and functionally associated with the population's transition to silence, particularly behavioural responses to silent environments. Our results demonstrate how 'adaptation begets adaptation'; changes to the sociogenetic environment accompanying rapid trait evolution can generate selection provoking further, compensatory adaptation.

snpAIMeR: R package for evaluating ancestry informative marker contributions in non-model population diagnostics

MOTIVATION

Single nucleotide polymorphism (SNP) markers are increasingly popular for population genomics and inferring ancestry for individuals of unknown origin. Because large SNP datasets are impractical for rapid and routine analysis, diagnostics rely on panels of highly informative markers. Strategies exist for selecting these markers, however, resources for efficiently evaluating their performance are limited for non-model systems.

RESULTS

snpAIMeR is a user-friendly R package that evaluates the efficacy of genomic markers for the cluster assignment of unknown individuals. It is intended to help minimize panel size and genotyping effort by determining the informativeness of candidate diagnostic markers. Provided genotype data from individuals of known origin, it uses leave-one-out cross-validation to determine population assignment rates for individual markers and marker combinations.

AVAILABILITY AND IMPLEMENTATION

snpAIMeR is available on CRAN (https://CRAN.R-project.org/package=snpAIMeR).

Abiotic Stress Tolerance Boosted by Genetic Diversity in Plants

Plant breeding [...].

Genomic insights on conservation priorities for North Sea houting and European lake whitefish (Coregonus spp.)

Population genomics analysis holds great potential for informing conservation of endangered populations. We focused on a controversial case of European whitefish (Coregonus spp.) populations. The endangered North Sea houting is the only coregonid fish that tolerates oceanic salinities and was previously considered a species (C. oxyrhinchus) distinct from European lake whitefish (C. lavaretus). However, no firm evidence for genetic-based salinity adaptation has been available. Also, studies based on microsatellite and mitogenome data suggested surprisingly recent divergence (c. 2500 years bp) between houting and lake whitefish. These data types furthermore have provided no evidence for possible inbreeding. Finally, a controversial taxonomic revision recently classified all whitefish in the region as C. maraena, calling conservation priorities of houting into question. We used whole-genome and ddRAD sequencing to analyse six lake whitefish populations and the only extant indigenous houting population. Demographic inference indicated post-glacial expansion and divergence between lake whitefish and houting occurring not long after the Last Glaciation, implying deeper population histories than previous analyses. Runs of homozygosity analysis suggested not only high inbreeding (FROH up to 30.6%) in some freshwater populations but also FROH up to 10.6% in the houting prompting conservation concerns. Finally, outlier scans provided evidence for adaptation to high salinities in the houting. Applying a framework for defining conservation units based on current and historical reproductive isolation and adaptive divergence led us to recommend that the houting be treated as a separate conservation unit regardless of species status. In total, the results underscore the potential of genomics to inform conservation practices, in this case clarifying conservation units and highlighting populations of concern.

Accurate Bayesian inference of sex chromosome karyotypes and sex-linked scaffolds from low-depth sequencing data

The identification of sex-linked scaffolds and the genetic sex of individuals, i.e. their sex karyotype, is a fundamental step in population genomic studies. If sex-linked scaffolds are known, single individuals may be sexed based on read counts of next-generation sequencing data. If both sex-linked scaffolds as well as sex karyotypes are unknown, as is often the case for non-model organisms, they have to be jointly inferred. For both cases, current methods rely on arbitrary thresholds, which limits their power for low-depth data. In addition, most current methods are limited to euploid sex karyotypes (XX and XY). Here we develop BeXY, a fully Bayesian method to jointly infer the posterior probabilities for each scaffold to be autosomal, X- or Y-linked and for each individual to be any of the sex karyotypes XX, XY, X0, XXX, XXY, XYY and XXYY. If the sex-linked scaffolds are known, it also identifies autosomal trisomies and estimates the sex karyotype posterior probabilities for single individuals. As we show with downsampling experiments, BeXY has higher power than all existing methods. It accurately infers the sex karyotype of ancient human samples with as few as 20,000 reads and accurately infers sex-linked scaffolds from data sets of just a handful of samples or with highly imbalanced sex ratios, also in the case of low-quality reference assemblies. We illustrate the power of BeXY by applying it to both whole-genome shotgun and target enrichment sequencing data of ancient and modern humans, as well as several non-model organisms.

Fasta2Structure: a user-friendly tool for converting multiple aligned FASTA files to STRUCTURE format

BACKGROUND

The STRUCTURE software has gained popularity as a tool for population structure and genetic analysis. Nevertheless, formatting data to meet STRUCTURE's specific requirements can be daunting and susceptible to errors, especially when handling multilocus data. This article highlights the creation of a graphical user interface (GUI) application tailored to streamline the process of converting multiple sequence alignments into a single, cohesive file that is compatible with the STRUCTURE software.

RESULTS

The application has been developed utilizing Tkinter for the GUI and Biopython for handling FASTA files. This program processes the files, pinpoints variable sites, and converts the sequences into a binary format. Subsequently, the sequences are concatenated and presented within the graphical interface's text area, enabling users to review and confirm the results. Furthermore, the program stores the concatenated results in a file, delivering a ready-to-use input for the STRUCTURE software.

CONCLUSION

This application offers an efficient and dependable solution for transforming multiple aligned FASTA files into a concatenated binary format file, which is compatible with the STRUCTURE software. With its user-friendly graphical interface and error-reduction approach, this tool proves invaluable for researchers engaged in population structure and genetic analysis.

High-Quality Genome Assemblies Reveal Evolutionary Dynamics of Repetitive DNA and Structural Rearrangements in the Drosophila virilis Subgroup

High-quality genome assemblies across a range of nontraditional model organisms can accelerate the discovery of novel aspects of genome evolution. The Drosophila virilis group has several attributes that distinguish it from more highly studied species in the Drosophila genus, such as an unusual abundance of repetitive elements and extensive karyotype evolution, in addition to being an attractive model for speciation genetics. Here, we used long-read sequencing to assemble five genomes of three virilis group species and characterized sequence and structural divergence and repetitive DNA evolution. We find that our contiguous genome assemblies allow characterization of chromosomal arrangements with ease and can facilitate analysis of inversion breakpoints. We also leverage a small panel of resequenced strains to explore the genomic pattern of divergence and polymorphism in this species and show that known demographic histories largely predicts the extent of genome-wide segregating polymorphism. We further find that a neo-X chromosome in Drosophila americana displays X-like levels of nucleotide diversity. We also found that unusual repetitive elements were responsible for much of the divergence in genome composition among species. Helitron-derived tandem repeats tripled in abundance on the Y chromosome in D. americana compared to Drosophila novamexicana, accounting for most of the difference in repeat content between these sister species. Repeats with characteristics of both transposable elements and satellite DNAs expanded by 3-fold, mostly in euchromatin, in both D. americana and D. novamexicana compared to D. virilis. Our results represent a major advance in our understanding of genome biology in this emerging model clade.

A Fast, Reproducible, High-throughput Variant Calling Workflow for Population Genomics

The increasing availability of genomic resequencing data sets and high-quality reference genomes across the tree of life present exciting opportunities for comparative population genomic studies. However, substantial challenges prevent the simple reuse of data across different studies and species, arising from variability in variant calling pipelines, data quality, and the need for computationally intensive reanalysis. Here, we present snpArcher, a flexible and highly efficient workflow designed for the analysis of genomic resequencing data in nonmodel organisms. snpArcher provides a standardized variant calling pipeline and includes modules for variant quality control, data visualization, variant filtering, and other downstream analyses. Implemented in Snakemake, snpArcher is user-friendly, reproducible, and designed to be compatible with high-performance computing clusters and cloud environments. To demonstrate the flexibility of this pipeline, we applied snpArcher to 26 public resequencing data sets from nonmammalian vertebrates. These variant data sets are hosted publicly to enable future comparative population genomic analyses. With its extensibility and the availability of public data sets, snpArcher will contribute to a broader understanding of genetic variation across species by facilitating the rapid use and reuse of large genomic data sets.

selscan 2.0: scanning for sweeps in unphased data

SUMMARY

Several popular haplotype-based statistics for identifying recent or ongoing positive selection in genomes require knowledge of haplotype phase. Here, we provide an update to selscan which implements a re-definition of these statistics for use in unphased data.

AVAILABILITY AND IMPLEMENTATION

Source code and binaries are freely available at https://github.com/szpiech/selscan, implemented in C/C++, and supported on Linux, Windows, and MacOS.

A second unveiling: Haplotig masking of the eastern oyster genome improves population-level inference

Genome assembly can be challenging for species that are characterized by high amounts of polymorphism, heterozygosity, and large effective population sizes. High levels of heterozygosity can result in genome mis-assemblies and a larger than expected genome size due to the haplotig versions of a single locus being assembled as separate loci. Here, we describe the first chromosome-level genome for the eastern oyster, Crassostrea virginica. Publicly released and annotated in 2017, the assembly has a scaffold N50 of 54 mb and is over 97.3% complete based on BUSCO analysis. The genome assembly for the eastern oyster is a critical resource for foundational research into molluscan adaptation to a changing environment and for selective breeding for the aquaculture industry. Subsequent resequencing data suggested the presence of haplotigs in the original assembly, and we developed a post hoc method to break up chimeric contigs and mask haplotigs in published heterozygous genomes and evaluated improvements to the accuracy of downstream analysis. Masking haplotigs had a large impact on SNP discovery and estimates of nucleotide diversity and had more subtle and nuanced effects on estimates of heterozygosity, population structure analysis, and outlier detection. We show that haplotig masking can be a powerful tool for improving genomic inference, and we present an open, reproducible resource for the masking of haplotigs in any published genome.

Genomic DNA extraction optimization and validation for genome sequencing using the marine gastropod Kellet's whelk

Next-generation sequencing technologies, such as Nanopore MinION, Illumina Hiseq and Novaseq, and PacBio Sequel II, hold immense potential for advancing genomic research on non-model organisms, including the vast majority of marine species. However, application of these technologies to marine invertebrate species is often impeded by challenges in extracting and purifying their genomic DNA due to high polysaccharide content and other secondary metabolites. In this study, we help resolve this issue by developing and testing DNA extraction protocols for Kellet's whelk (Kelletia kelletii), a subtidal gastropod with ecological and commercial importance, by comparing four DNA extraction methods commonly used in marine invertebrate studies. In our comparison of extraction methods, the Salting Out protocol was the least expensive, produced the highest DNA yields, produced consistent high DNA quality, and had low toxicity. We validated the protocol using an independent set of tissue samples, then applied it to extract high-molecular-weight (HMW) DNA from over three thousand Kellet's whelk tissue samples. The protocol demonstrated scalability and, with added clean-up, suitability for RAD-seq, GT-seq, as well as whole genome sequencing using both long read (ONT MinION) and short read (Illumina NovaSeq) sequencing platforms. Our findings offer a robust and versatile DNA extraction and clean-up protocol for supporting genomic research on non-model marine organisms, to help mediate the under-representation of invertebrates in genomic studies.

Diversity across organisational scale emerges through dispersal ability and speciation dynamics in tropical fish

BACKGROUND

Biodiversity exists at different levels of organisation: e.g. genetic, individual, population, species, and community. These levels of organisation all exist within the same system, with diversity patterns emerging across organisational scales through several key processes. Despite this inherent interconnectivity, observational studies reveal that diversity patterns across levels are not consistent and the underlying mechanisms for variable continuity in diversity across levels remain elusive. To investigate these mechanisms, we apply a spatially explicit simulation model to simulate the global diversification of tropical reef fishes at both the population and species levels through emergent population-level processes.

RESULTS

We find significant relationships between the population and species levels of diversity which vary depending on both the measure of diversity and the spatial partitioning considered. In turn, these population-species relationships are driven by modelled biological trait parameters, especially the divergence threshold at which populations speciate.

CONCLUSIONS

To explain variation in multi-level diversity patterns, we propose a simple, yet novel, population-to-species diversity partitioning mechanism through speciation which disrupts continuous diversity patterns across organisational levels. We expect that in real-world systems this mechanism is driven by the molecular dynamics that determine genetic incompatibility, and therefore reproductive isolation between individuals. We put forward a framework in which the mechanisms underlying patterns of diversity across organisational levels are universal, and through this show how variable patterns of diversity can emerge through organisational scale.

Landscape genomics analysis provides insights into future climate change-driven risk in rhesus macaque

Climate change significantly affects the suitability of wildlife habitats. Thus, understanding how animals adapt ecologically and genetically to climate change is important for targeted species protection. Rhesus macaques (Macaca mulatta) are widely distributed and multi-climatically adapted primates. This study explored how rhesus macaques adapt to climate change by integrating ecological and genetic methods and applying species distribution models (SDMs) and a gradient forest (GF) model. The findings suggested that temperature seasonality primarily affects habitat suitability and indicated that climate change will have a dramatic impact on macaque populations in the future. We also applied genotype-environment association (GEA) analyses and selection signature analyses to identify genes associated with climate change and provide possible explanations for the adaptation of rhesus macaques to climatic environments. The population genomics analyses suggested that the Taihang population has the highest genomic vulnerability with inbreeding and low heterozygosity. Combined with the higher ecological vulnerability, additional conservation strategies are required for this population under higher risk of climate change. Our work measured the impact of climate change and enabled the identification of populations that exhibit high vulnerability to severe climate change. Such information is useful for selecting populations of rhesus macaques as subject of long-term monitoring or evolutionary rescue under future climate change.

Genetic Diversity and Signatures of Selection in the Roughskin Sculpin (Trachidermus fasciatus) Revealed by Whole Genome Sequencing

The roughskin sculpin (Trachidermus fasciatus) is an endangered fish species in China. In recent years, artificial breeding technology has made significant progress, and the population of roughskin sculpin has recovered in the natural environment through enhancement programs and the release of juveniles. However, the effects of released roughskin sculpin on the genetic structure and diversity of wild populations remain unclear. Studies on genetic diversity analysis based on different types and numbers of molecular markers have yielded inconsistent results. In this study, we obtained 2,610,157 high-quality SNPs and 494,698 InDels through whole-genome resequencing of two farmed populations and one wild population. Both farmed populations showed consistent levels of genomic polymorphism and a slight increase in linkage compared with wild populations. The population structure of the two farmed populations was distinct from that of the wild population, but the degree of genetic differentiation was low (overall average Fst = 0.015). Selective sweep analysis showed that 523,529 genes were selected in the two farmed populations, and KEGG enrichment analysis showed that the selected genes were related to amino acid metabolism, which might be caused by artificial feeding. The findings of this study provide valuable additions to the existing genomic resources to help conserve roughskin sculpin populations.

Genomic signals of local adaptation in Picea crassifolia

BACKGROUND

Global climate change poses a grave threat to biodiversity and underscores the importance of identifying the genes and corresponding environmental factors involved in the adaptation of tree species for the purposes of conservation and forestry. This holds particularly true for spruce species, given their pivotal role as key constituents of the montane, boreal, and sub-alpine forests in the Northern Hemisphere.

RESULTS

Here, we used transcriptomes, species occurrence records, and environmental data to investigate the spatial genetic distribution of and the climate-associated genetic variation in Picea crassifolia. Our comprehensive analysis employing ADMIXTURE, principal component analysis (PCA) and phylogenetic methodologies showed that the species has a complex population structure with obvious differentiation among populations in different regions. Concurrently, our investigations into isolation by distance (IBD), isolation by environment (IBE), and niche differentiation among populations collectively suggests that local adaptations are driven by environmental heterogeneity. By integrating population genomics and environmental data using redundancy analysis (RDA), we identified a set of climate-associated single-nucleotide polymorphisms (SNPs) and showed that environmental isolation had a more significant impact than geographic isolation in promoting genetic differentiation. We also found that the candidate genes associated with altitude, temperature seasonality (Bio4) and precipitation in the wettest month (Bio13) may be useful for forest tree breeding.

CONCLUSIONS

Our findings deepen our understanding of how species respond to climate change and highlight the importance of integrating genomic and environmental data in untangling local adaptations.

Anemonefishes: A model system for evolutionary genomics

Anemonefishes are an iconic group of coral reef fish particularly known for their mutualistic relationship with sea anemones. This mutualism is especially intriguing as it likely prompted the rapid diversification of anemonefish. Understanding the genomic architecture underlying this process has indeed become one of the holy grails of evolutionary research in these fishes. Recently, anemonefishes have also been used as a model system to study the molecular basis of highly complex traits such as color patterning, social sex change, larval dispersal and life span. Extensive genomic resources including several high-quality reference genomes, a linkage map, and various genetic tools have indeed enabled the identification of genomic features controlling some of these fascinating attributes, but also provided insights into the molecular mechanisms underlying adaptive responses to changing environments. Here, we review the latest findings and new avenues of research that have led to this group of fish being regarded as a model for evolutionary genomics.

Integrating Pool-seq uncertainties into demographic inference

Next-generation sequencing of pooled samples (Pool-seq) is a popular method to assess genome-wide diversity patterns in natural and experimental populations. However, Pool-seq is associated with specific sources of noise, such as unequal individual contributions. Consequently, using Pool-seq for the reconstruction of evolutionary history has remained underexplored. Here we describe a novel Approximate Bayesian Computation (ABC) method to infer demographic history, explicitly modelling Pool-seq sources of error. By jointly modelling Pool-seq data, demographic history and the effects of selection due to barrier loci, we obtain estimates of demographic history parameters accounting for technical errors associated with Pool-seq. Our ABC approach is computationally efficient as it relies on simulating subsets of loci (rather than the whole-genome) and on using relative summary statistics and relative model parameters. Our simulation study results indicate Pool-seq data allows distinction between general scenarios of ecotype formation (single versus parallel origin) and to infer relevant demographic parameters (e.g. effective sizes and split times). We exemplify the application of our method to Pool-seq data from the rocky-shore gastropod Littorina saxatilis, sampled on a narrow geographical scale at two Swedish locations where two ecotypes (Wave and Crab) are found. Our model choice and parameter estimates show that ecotypes formed before colonization of the two locations (i.e. single origin) and are maintained despite gene flow. These results indicate that demographic modelling and inference can be successful based on pool-sequencing using ABC, contributing to the development of suitable null models that allow for a better understanding of the genetic basis of divergent adaptation.

Demographically explicit scans for barriers to gene flow using gIMble

Identifying regions of the genome that act as barriers to gene flow between recently diverged taxa has remained challenging given the many evolutionary forces that generate variation in genetic diversity and divergence along the genome, and the stochastic nature of this variation. Progress has been impeded by a conceptual and methodological divide between analyses that infer the demographic history of speciation and genome scans aimed at identifying locally maladaptive alleles i.e. genomic barriers to gene flow. Here we implement genomewide IM blockwise likelihood estimation (gIMble), a composite likelihood approach for the quantification of barriers, that bridges this divide. This analytic framework captures background selection and selection against barriers in a model of isolation with migration (IM) as heterogeneity in effective population size (Ne) and effective migration rate (me), respectively. Variation in both effective demographic parameters is estimated in sliding windows via pre-computed likelihood grids. gIMble includes modules for pre-processing/filtering of genomic data and performing parametric bootstraps using coalescent simulations. To demonstrate the new approach, we analyse data from a well-studied pair of sister species of tropical butterflies with a known history of post-divergence gene flow: Heliconius melpomene and H. cydno. Our analyses uncover both large-effect barrier loci (including well-known wing-pattern genes) and a genome-wide signal of a polygenic barrier architecture.

Power of neutrality tests for detecting natural selection

Detection of natural selection is one of the main interests in population genetics. Thus, many tests have been developed for detecting natural selection using genomic data. Although it is recognized that the utility of tests depends on several evolutionary factors, such as the timing of selection, strength of selection, frequency of selected alleles, demographic events, and initial frequency of selected allele when selection started acting (softness of selection), the relationships between such evolutionary factors and the power of tests are not yet entirely clear. In this study, we investigated the power of 4 tests: Tajiama's D, Fay and Wu's H, relative extended haplotype homozygosity (rEHH), and integrated haplotype score (iHS), under ranges of evolutionary parameters and demographic models to quantitatively expand the understanding of approaches for detecting selection. The results show that each test detects selection within a limited parameter range, and there are still wide ranges of parameters for which none of these tests work effectively. In addition, the parameter space in which each test shows the highest power overlaps the empirical results of previous research. These results indicate that our present perspective of adaptation is limited to only a part of actual adaptation.

High quality genome assemblies reveal evolutionary dynamics of repetitive DNA and structural rearrangements in the Drosophila virilis sub-group

High-quality genome assemblies across a range of non-traditional model organisms can accelerate the discovery of novel aspects of genome evolution. The Drosophila virilis group has several attributes that distinguish it from more highly studied species in the Drosophila genus, such as an unusual abundance of repetitive elements and extensive karyotype evolution, in addition to being an attractive model for speciation genetics. Here we used long-read sequencing to assemble five genomes of three virilis group species and characterized sequence and structural divergence and repetitive DNA evolution. We find that our contiguous genome assemblies allow characterization of chromosomal arrangements with ease and can facilitate analysis of inversion breakpoints. We also leverage a small panel of resequenced strains to explore the genomic pattern of divergence and polymorphism in this species and show that known demographic histories largely predicts the extent of genome-wide segregating polymorphism. We further find that a neo-X chromosome in D. americana displays X-like levels of nucleotide diversity. We also found that unusual repetitive elements were responsible for much of the divergence in genome composition among species. Helitron-derived tandem repeats tripled in abundance on the Y chromosome in D. americana compared to D. novamexicana, accounting for most of the difference in repeat content between these sister species. Repeats with characteristics of both transposable elements and satellite DNAs expanded by three-fold, mostly in euchromatin, in both D. americana and D. novamexicana compared to D. virilis. Our results represent a major advance in our understanding of genome biology in this emerging model clade.

Exceptional population genomic homogeneity in the black brittle star Ophiocomina nigra (Ophiuroidea, Echinodermata) along the Atlantic-Mediterranean coast

The Atlantic-Mediterranean marine transition is characterised by strong oceanographic barriers and steep environmental gradients that generally result in connectivity breaks between populations from both basins and may lead to local adaptation. Here, we performed a population genomic study of the black brittle star, Ophiocomina nigra, covering most of its distribution range along the Atlantic-Mediterranean region. Interestingly, O. nigra is extremely variable in its coloration, with individuals ranging from black to yellow-orange, and different colour morphs inhabiting different depths and habitats. In this work, we used a fragment of the mitochondrial COI gene and 2,374 genome-wide ddRADseq-derived SNPs to explore: (a) whether the different colour morphs of O. nigra represent different evolutionary units; (b) the disruptive effects of major oceanographic fronts on its population structure; and (c) genomic signals of local adaptation to divergent environments. Our results revealed exceptional population homogeneity, barely affected by oceanographic fronts, with no signals of local adaptation nor genetic differentiation between colour morphs. This remarkable panmixia likely results from a long pelagic larval duration, a large effective population size and recent demographic expansions. Our study unveils an extraordinary phenotypic plasticity in O. nigra, opening further research questions on the ecological and molecular mechanisms underpinning coloration in Ophiuroidea.

Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

Omics of an Enigmatic Marine Amoeba Uncovers Unprecedented Gene Trafficking from Giant Viruses and Provides Insights into Its Complex Life Cycle

Amoebozoa include lineages of diverse ecology, behavior, and morphology. They are assumed to encompass members with the largest genome sizes of all living things, yet genomic studies in the group are limited. Trichosphaerium, a polymorphic, multinucleate, marine amoeba with a complicated life cycle, has puzzled experts for over a century. In an effort to explore the genomic diversity and investigate extraordinary behavior observed among the Amoebozoa, we used integrated omics approaches to study this enigmatic marine amoeba. Omics data, including single-cell transcriptomics and cytological data, demonstrate that Trichosphaerium sp. possesses the complete meiosis toolkit genes. These genes are expressed in life stages of the amoeba including medium and large cells. The life cycle of Trichosphaerium sp. involves asexual processes via binary fission and multiple fragmentation of giant cells, as well as sexual-like processes involving genes implicated in sexual reproduction and polyploidization. These findings are in stark contrast to a life cycle previously reported for this amoeba. Despite the extreme morphological plasticity observed in Trichosphaerium, our genomic data showed that populations maintain a species-level intragenomic variation. A draft genome of Trichosphaerium indicates elevated lateral gene transfer (LGT) from bacteria and giant viruses. Gene trafficking in Trichosphaerium is the highest within Amoebozoa and among the highest in microbial eukaryotes.

The influence of transposable elements on animal colouration

Transposable elements (TEs) are mobile genetic sequences present within host genomes. TEs can contribute to the evolution of host traits, since transposition is mutagenic and TEs often contain host regulatory and protein coding sequences. We review cases where TEs influence animal colouration, reporting major patterns and outstanding questions. TE-induced colouration phenotypes typically arise via introduction of novel regulatory sequences and splice sites, affecting pigment cell development or pigment synthesis. We discuss if particular TE types may be more frequently involved in the evolution of colour variation in animals, given that examples involving long terminal repeat (LTR) elements appear to dominate. Currently, examples of TE-induced colouration phenotypes in animals mainly concern model and domesticated insect and mammal species. However, several influential recent examples, coupled with increases in genome sequencing, suggest cases reported from wild species will increase considerably.

When One's Not Enough: Colony Pool-Seq Outperforms Individual-Based Methods for Assessing Introgression in Apis mellifera mellifera

The human management of honey bees (Apis mellifera) has resulted in the widespread introduction of subspecies outside of their native ranges. One well known example of this is Apis mellifera mellifera, native to Northern Europe, which has now been significantly introgressed by the introduction of C lineage honey bees. Introgression has consequences for species in terms of future adaptive potential and long-term viability. However, estimating introgression in colony-living haplodiploid species is challenging. Previous studies have estimated introgression using individual workers, individual drones, multiple drones, and pooled workers. Here, we compare introgression estimates via three genetic approaches: SNP array, individual RAD-seq, and pooled colony RAD-seq. We also compare two statistical approaches: a maximum likelihood cluster program (ADMIXTURE) and an incomplete lineage sorting model (ABBA BABA). Overall, individual approaches resulted in lower introgression estimates than pooled colonies when using ADMIXTURE. However, the pooled colony ABBA BABA approach resulted in generally lower introgression estimates than all three ADMIXTURE estimates. These results highlight that sometimes one individual is not enough to assess colony-level introgression, and future studies that do use colony pools should not be solely dependent on clustering programs for introgression estimates.

Evaluation of Different SNP Analysis Software and Optimal Mining Process in Tree Species

Single nucleotide polymorphism (SNP) is one of the most widely used molecular markers to help researchers understand the relationship between phenotypes and genotypes. SNP calling mainly consists of two steps, including read alignment and locus identification based on statistical models, and various software have been developed and applied in this issue. Meanwhile, in our study, very low agreement (<25%) was found among the prediction results generated by different software, which was much less consistent than expected. In order to obtain the optimal protocol of SNP mining in tree species, the algorithm principles of different alignment and SNP mining software were discussed in detail. And the prediction results were further validated based on in silico and experimental methods. In addition, hundreds of validated SNPs were provided along with some practical suggestions on program selection and accuracy improvement were provided, and we wish that these results could lay the foundation for the subsequent analysis of SNP mining.

A Genomic Quantitative Study on the Contribution of the Ancestral-State Bases Relative to Derived Bases in the Divergence and Local Adaptation of Populus davidiana

Identifying alleles associated with adaptation to new environments will advance our understanding of evolution from the molecular level. Previous studies have found that the Populus davidiana southwest population in East Asia has differentiated from other populations in the range. We aimed to evaluate the contributions of the ancestral-state bases (ASBs) relative to derived bases (DBs) in the local adaptation of P. davidiana in the Yunnan-Guizhou Plateau from a quantitative perspective using whole-genome re-sequencing data from 90 P. davidiana samples from three regions across the species range. Our results showed that the uplift of the Qinghai-Tibet Plateau during the Neogene and associated climate fluctuations during the Middle Pleistocene were likely an important factor in the early divergence of P. davidiana. Highly differentiated genomic regions between populations were inferred to have undergone strong linked natural selection, and ASBs are the chief means by which populations of P. davidiana adapt to novel environmental conditions; however, when adapting to regions with high environmental differences relative to the ancestral range, the proportion of DBs was significantly higher than that of background regions, as ASBs are insufficient to cope with these environments. Finally, a number of genes were identified in the outlier region.

A spatial approach to jointly estimate Wright's neighborhood size and long-term effective population size

Spatially continuous patterns of genetic differentiation, which are common in nature, are often poorly described by existing population genetic theory or methods that assume panmixia or discrete, clearly definable populations. There is therefore a need for statistical approaches in population genetics that can accommodate continuous geographic structure, and that ideally use georeferenced individuals as the unit of analysis, rather than populations or subpopulations. In addition, researchers are often interested describing the diversity of a population distributed continuously in space, and this diversity is intimately linked to the dispersal potential of the organism. A statistical model that leverages information from patterns of isolation-by-distance to jointly infer parameters that control local demography (such as Wright's neighborhood size), and the long-term effective size (Ne) of a population would be useful. Here, we introduce such a model that uses individual-level pairwise genetic and geographic distances to infer Wright's neighborhood size and long-term Ne. We demonstrate the utility of our model by applying it to complex, forward-time demographic simulations as well as an empirical dataset of the Red Sea clownfish (Amphiprion bicinctus). The model performed well on simulated data relative to alternative approaches and produced reasonable empirical results given the natural history of clownfish. The resulting inferences provide important insights into the population genetic dynamics of spatially structure populations.

Revealing the potential regulatory relationship between HSP70, HSP90 and HSF genes under temperature stress

Heat Shock Protein (HSPs) gene family members play fundamental roles in different environmental stress tolerances, protect the structure and function of cells, and perform a significant task in cellular homeostasis. In this study, we conducted a genome-wide identification, evolutionary relationship analysis and gene expression analysis of the HSP70, HSP90, and HSF gene families in Ruditapes philippinarum. We identified 83 RpHSP70, 6 RpHSP90, and 3 RpHSF genes in R. philippinarum. The structural characteristics, chromosomal localization, and the gene structure map were constructed to reveal the characteristics of protein structures. Furthermore, the expression profiling of transcriptome data showed the expression pattern of HSP70, HSP90 and HSF genes in Manila clam from different populations, and under high and low temperature stress. In addition, we performed protein-protein interaction network analysis between HSP70, HSP90, and HSF gene family which enabled us to recognize the regulatory relationship between the two HSP gene families and the HSF gene family. Furthermore, the predicted sub-cellular location revealed a diversified subcellular distribution of HSP70, HSP90, and HSF proteins, which may be directly or indirectly associated with functional diversification under heat stress condition.

Jasmonic acid enhances osmotic stress responses by MYC2-mediated inhibition of protein phosphatase 2C1 and response regulators 26 transcription factor in tomato

The jasmonic acid (JA) signaling pathway is involved in the plant response to drought stress. JA and other hormones synergistically regulate the drought response in plants. However, the molecular mechanism underlying this synergism remains poorly defined. In the present study, transcriptome analyses of guard cells and quantitative PCR experiments revealed that MYC2 negatively regulated the negative regulator of ABA signaling, SlPP2C1, and the type-B response regulator in the cytokinin pathway, SlRR26, and this negative regulation was direct. SlRR26 overexpression reduced drought tolerance in transgenic tomatoes, whereas slrr26^cr lines were more tolerant to drought. SlRR26 negatively modulated reactive oxygen species levels in stomata and stomatal closure through RobhB. Moreover, SlRR26 overexpression counteracted JA-mediated stomatal closure, suggesting that SlRR26 played a negative role in the JA-mediated drought response. These findings suggest that MYC2 plays a key role in JA-regulated stomatal closure under drought stress by inhibiting SlPP2C1 and SlRR26.

Genomic signals of local adaptation and hybridization in Asian white birch

Disentangling the numerous processes that affect patterns of genome-wide diversity in widespread tree species has important implications for taxonomy, conservation, and forestry. Here, we investigate the population genomic structure of Asian white birch (Betula platyphylla) in China and seek to explain it in terms of hybridization, demography and adaptation. We generate whole genome sequence data from 83 individuals across the species range in China. Combining this with an existing data set for 79 European and Russian white birches, we show a clear distinction between B. pendula and B. platyphylla, which have sometimes been lumped taxonomically. Genomic diversity of B. platyphylla in north-western China and Central Russia is affected greatly by hybridization with B. pendula. Excluding these hybridized populations, B. platyphylla in China has a linear distribution from north-eastern to south-western China, along the edge of the inland mountainous region. Within this distribution, three genetic clusters are found, which we model as long diverged with subsequent episodes of gene flow. Patterns of covariation between allele frequencies and environmental variables in B. platyphylla suggest the role of natural selection in the distribution of diversity at 7609 SNPs of which 3767 were significantly differentiated among the genetic clusters. The putative adaptive SNPs are distributed throughout the genome and span 1633 genic regions. Of these genic regions, 87 were previously identified as candidates for selective sweeps in Eurasian B. pendula. We use the 7609 environmentally associated SNPs to estimate the risk of nonadaptedness for each sequenced B. platyphylla individual under a scenario of future climate change, highlighting areas where populations may be under future threat from rising temperatures.