Whole-genome sequencing approaches for conservation biology: Advantages, limitations and practical recommendations

Whole genome resequencing revealed genomic variants and functional pathways related to adaptation in Indian yak populations

The present study aims to identify genomic variants through a whole genome sequencing (WGS) approach and uncover biological pathways associated with adaptation and fitness in Indian yak populations. A total of 30 samples (10 from each population) were included from Arunachali, Himachali and Ladakhi yak populations. WGS analysis revealed a total of 32171644, 27260825, and 32632460 SNPs and 4865254, 4429941, and 4847513 Indels in the Arunachali, Himachali, and Ladakhi yaks, respectively. Genes such as RYR2, SYNE2, BOLA, HF1, and the novel transcript ENSBGRG00000011079 were found to have the maximum number of high impact variants in all three yak populations, and might play a major role in local adaptation. Functional enrichment analysis of genes harboring high impact SNPs revealed overrepresented pathways related to response to stress, immune system regulation, and high-altitude adaptation. This study provides comprehensive information about genomic variants and their annotation in Indian yak populations, thus would serve as a data resource for researchers working on the yaks. Furthermore, it could be well exploited for better yak conservation strategies by estimating population genetics parameters viz., effective population size, inbreeding, and observed and expected heterozygosity.

Virulence Potential and Antimicrobial Resistance of Listeria monocytogenes Isolates Obtained from Beef and Beef-Based Products Deciphered Using Whole-Genome Sequencing

Listeria monocytogenes is a ubiquitous bacterial pathogen that threatens the food chain and human health. In this study, whole-genome sequencing (WGS) was used for the genomic characterization of L. monocytogenes (n = 24) from beef and beef-based products. Multilocus Sequence Type (MLST) analysis revealed that ST204 of CC204 was the most common sequence type (ST). Other sequence types detected included ST1 and ST876 of CC1, ST5 of CC5, ST9 of CC9, ST88 of CC88, ST2 and ST1430 of CC2, and ST321 of CC321. Genes encoding for virulence factors included complete LIPI-1 (pfrA-hly-plcA-plcB-mpl-actA) from 54% (13/24) of the isolates of ST204, ST321, ST1430, and ST9 and internalin genes inlABC that were present in all the STs. All the L. monocytogenes STs carried four intrinsic/natural resistance genes, fosX, lin, norB, and mprF, conferring resistance to fosfomycin, lincosamide, quinolones, and cationic peptides, respectively. Plasmids pLGUG1 and J1776 were the most detected (54% each), followed by pLI100 (13%) and pLM5578 (7%). The prophage profile, vB_LmoS_188, was overrepresented amongst the isolates, followed by LP_101, LmoS_293_028989, LP_030_2_021539, A006, and LP_HM00113468. Listeria genomic island 2 (LGI-2) was found to be present in all the isolates, while Listeria genomic island 3 (LGI-3) was present in a subset of isolates (25%). The type VII secretion system was found in 42% of the isolates, and sortase A was present in all L. monocytogenes genomes. Mobile genetic elements and genomic islands did not harbor any virulence, resistance, or environmental adaptation genes that may benefit L. monocytogenes. All the STs did not carry genes that confer resistance to first-line antibiotics used for the treatment of listeriosis. The characterization of L. monocytogenes in our study highlighted the environmental resistance and virulence potential of L. monocytogenes and the risk posed to the public, as this bacterium is frequently found in food and food processing environments.

Detection of rare variants among nuclei populating the arbuscular mycorrhizal fungal model species Rhizophagus irregularis DAOM197198

Identifying genuine polymorphic variants is a significant challenge in sequence data analysis, although detecting low-frequency variants in sequence data is essential for estimating demographic parameters and investigating genetic processes, such as selection, within populations. Arbuscular mycorrhizal (AM) fungi are multinucleate organisms, in which individual nuclei collectively operate as a population, and the extent of genetic variation across nuclei has long been an area of scientific interest. In this study, we investigated the patterns of polymorphism discovery and the alternate allele frequency distribution by comparing polymorphism discovery in 2 distinct genomic sequence datasets of the AM fungus model species, Rhizophagus irregularis strain DAOM197198. The 2 datasets used in this study are publicly available and were generated either from pooled spores and hyphae or amplified single nuclei from a single spore. We also estimated the intraorganismal variation within the DAOM197198 strain. Our results showed that the 2 datasets exhibited different frequency patterns for discovered variants. The whole-organism dataset showed a distribution spanning low-, intermediate-, and high-frequency variants, whereas the single-nucleus dataset predominantly featured low-frequency variants with smaller proportions in intermediate and high frequencies. Furthermore, single nucleotide polymorphism density estimates within both the whole organism and individual nuclei confirmed the low intraorganismal variation of the DAOM197198 strain and that most variants are rare. Our study highlights the methodological challenges associated with detecting low-frequency variants in AM fungal whole-genome sequence data and demonstrates that alternate alleles can be reliably identified in single nuclei of AM fungi.

Construction of a Full-Length Transcriptome of Western Honeybee Midgut Tissue and Improved Genome Annotation

Honeybees are an indispensable pollinator in nature with pivotal ecological, economic, and scientific value. However, a full-length transcriptome for Apis mellifera, assembled with the advanced third-generation nanopore sequencing technology, has yet to be reported. Here, nanopore sequencing of the midgut tissues of uninoculated and Nosema ceranae-inoculated A. mellifera workers was conducted, and the full-length transcriptome was then constructed and annotated based on high-quality long reads. Next followed improvement of sequences and annotations of the current reference genome of A. mellifera. A total of 5,942,745 and 6,664,923 raw reads were produced from midguts of workers at 7 days post-inoculation (dpi) with N. ceranae and 10 dpi, while 7,100,161 and 6,506,665 raw reads were generated from the midguts of corresponding uninoculated workers. After strict quality control, 6,928,170, 6,353,066, 5,745,048, and 6,416,987 clean reads were obtained, with a length distribution ranging from 1 kb to 10 kb. Additionally, 16,824, 17,708, 15,744, and 18,246 full-length transcripts were respectively detected, including 28,019 nonredundant ones. Among these, 43,666, 30,945, 41,771, 26,442, and 24,532 full-length transcripts could be annotated to the Nr, KOG, eggNOG, GO, and KEGG databases, respectively. Additionally, 501 novel genes (20,326 novel transcripts) were identified for the first time, among which 401 (20,255), 193 (13,365), 414 (19,186), 228 (12,093), and 202 (11,703) were respectively annotated to each of the aforementioned five databases. The expression and sequences of three randomly selected novel transcripts were confirmed by RT-PCR and Sanger sequencing. The 5' UTR of 2082 genes, the 3' UTR of 2029 genes, and both the 5' and 3' UTRs of 730 genes were extended. Moreover, 17,345 SSRs, 14,789 complete ORFs, 1224 long non-coding RNAs (lncRNAs), and 650 transcription factors (TFs) from 37 families were detected. Findings from this work not only refine the annotation of the A. mellifera reference genome, but also provide a valuable resource and basis for relevant molecular and -omics studies.

Genotype-phenotype evaluation of the heterogeneity in biofilm formation by diverse Bacillus licheniformis strains isolated from dairy products

The spoilage bacterium Bacillus licheniformis has been identified as a quick and strong biofilm former in the dairy industry. In our previous study, intra-species variation in bacterial biofilms has been observed in diverse B. licheniformis strains from different genetic backgrounds; however, the mechanisms driving the observed heterogeneity of biofilms remain to be determined. In this study, the genotype-phenotype evaluation of the heterogeneity in biofilm formation of four B. licheniformis strains were examined. The heterogeneity in biofilm phenotype was accessed in aspects of bacterial growth and motility, cell viability, biofilm matrix production, and biofilm architectures. The underlying mechanisms of the intra-species variability in biofilms were also explored by whole genome resequencing (WGR). Results from bacterial motility tests showed a diverse motility among the strains, but there was no clear correlation between bacterial motility and biofilm formation. The cell viability results showed a different number of live cells in biofilms at the intra-species level. Analysis of chemical components in biofilm matrix demonstrated the great intra-species differences regarding extracellular matrix composition, and a negative correlation between biofilm formation on stainless steel and the protein: carbohydrate ratio in biofilm matrix was observed. Confocal laser scanning microscopy analysis also revealed the intra-species variability by showing great differences in general properties of B. licheniformis biofilms. WGR results identified important pathways involved in biofilm formation, such as two-component systems, quorum sensing, starch and sucrose metabolism, ABC transporters, glyoxylate and dicarboxylate metabolism, purine metabolism, and a phosphotransferase system. Overall, the above results emphasize the necessity of exploring the intra-species variation in biofilms, and would provide in-depth knowledge for designing efficient biofilm control strategies in the dairy industry.

Translating genomic advances into biodiversity conservation

A key action of the new Global Biodiversity Framework is the maintenance of genetic diversity in all species to safeguard their adaptive potential. To achieve this goal, a translational mindset, which aims to convert results of basic research into direct practical benefits, needs to be applied to biodiversity conservation. Despite much discussion on the value of genomics to conservation, a disconnect between those generating genomic resources and those applying it to biodiversity management remains. As global efforts to generate reference genomes for non-model species increase, investment into practical biodiversity applications is critically important. Applications such as understanding population and multispecies diversity and longitudinal monitoring need support alongside education for policymakers on integrating the data into evidence-based decisions. Without such investment, the opportunity to revolutionize global biodiversity conservation using genomics will not be fully realized.

Chromosome-level genome assembly and population genomic analysis reveal evolution and local adaptation in common hairfin anchovy (Setipinna tenuifilis)

Understanding the genetic structure and the factors associated with adaptive diversity has significant implications for the effective management of wild populations under threat from overfishing and climate change. The common hairfin anchovy (Setipinna tenuifilis) is an economically and ecologically important pelagic fish species, spanning a broad latitudinal gradient along marginal seas of the Northwest Pacific. In this study, we constructed the first reference genome of S. tenuifilis using PacBio long reads and high-resolution chromosome conformation capture (Hi-C) technology. The assembled genome was 798.38 Mb with a contig N50 of 1.43 Mb and a scaffold N50 of 32.42 Mb, which were anchored onto 24 pseudochromosomes. A total of 22,019 genes were functionally annotated, which accounted for 95.27% of the predicted protein-coding genes. Chromosomal collinearity analysis revealed chromosome fusion or fission events in Clupeiformes species. Three genetic groups of S. tenuifilis were revealed along the Chinese coast using restriction site-associated DNA sequencing (RADseq). We investigated the influence of four bioclimatic variables as potential drivers of adaptive divergence in S. tenuifilis, suggesting that these environmental variables, especially sea surface temperature, may play important roles as drivers of spatially varying selection for S. tenuifilis. We also identified candidate functional genes underlying adaptive mechanisms and ecological tradeoffs using redundancy analysis (RDA) and BayeScan analysis. In summary, this study sheds light on the evolution and spatial patterns of genetic variation of S. tenuifilis, providing a valuable genomic resource for further biological and genetic studies on this species and other closely related Clupeiformes.

Genetic and behavioral differences between above and below ground Culex pipiens bioforms

Efficiency of mosquito-borne disease transmission is dependent upon both the preference and fidelity of mosquitoes as they seek the blood of vertebrate hosts. While mosquitoes select their blood hosts through multi-modal integration of sensory cues, host-seeking is primarily an odor-guided behavior. Differences in mosquito responses to hosts and their odors have been demonstrated to have a genetic component, but the underlying genomic architecture of these responses has yet to be fully resolved. Here, we provide the first characterization of the genomic architecture of host preference in the polymorphic mosquito species, Culex pipiens. The species exists as two morphologically identical bioforms, each with distinct avian and mammalian host preferences. Cx. pipiens females with empirically measured host responses were prepared into reduced representation DNA libraries and sequenced to identify genomic regions associated with host preference. Multiple genomic regions associated with host preference were identified on all 3 Culex chromosomes, and these genomic regions contained clusters of chemosensory genes, as expected based on work in Anopheles gambiae complex mosquitoes and in Aedes aegypti. One odorant receptor and one odorant binding protein gene showed one-to-one orthologous relationships to differentially expressed genes in A. gambiae complex members with divergent host preferences. Overall, our work identifies a distinct set of odorant receptors and odorant binding proteins that may enable Cx. pipiens females to distinguish between their vertebrate blood host species, and opens avenues for future functional studies that could measure the unique contributions of each gene to host preference phenotypes.

The role of introgressive hybridization in shaping the geographically isolated gene pools of wax palm populations (genus Ceroxylon)

The speciation continuum is the process by which genetic groups diverge until they reach reproductive isolation. It has become common in the literature to show that this process is gradual and flickering, with possibly many instances of secondary contact and introgression after divergence has started. The level of divergence might vary among genomic regions due to, among others, the different forces and roles of selection played by the shared regions. Through hybrid capture, we sequenced ca. 4,000 nuclear regions in populations of six species of wax palms, five of which form a monophyletic group (genus Ceroxylon, Arecaceae: Ceroxyloideae). We show that in this group, the different populations show varying degrees of introgressive hybridization, and two of them are backcrosses of the other three 'pure' species. This is particularly interesting because these three species are dioecious, have a shared main pollinator, and have slightly overlapping reproductive seasons but highly divergent morphologies. Our work supports shows wax palms diverge under positive and background selection in allopatry, and hybridize due to secondary contact and inefficient reproductive barriers, which sustain genetic diversity. Introgressed regions are generally not under positive selection. Peripheral populations are backcrosses of other species; thus, introgressive hybridization is likely modulated by demographic effects rather than selective pressures. In general, these species might function as an 'evolutionary syngameon' where expanding, peripheral, small, and isolated populations maintain diversity by crossing with available individuals of other wax palms. In the Andean context, species can benefit from gained variation from a second taxon or the enhancement of population sizes by recreating a common genetic pool.

DEGAP: Dynamic elongation of a genome assembly path

Genome assembly remains to be a major task in genomic research. Despite the development over the past decades of different assembly software programs and algorithms, it is still a great challenge to assemble a complete genome without any gaps. With the latest DNA circular consensus sequencing (CCS) technology, several assembly programs can now build a genome from raw sequencing data to contigs; however, some complex sequence regions remain as unresolved gaps. Here, we present a novel gap-filling software, DEGAP (Dynamic Elongation of a Genome Assembly Path), that resolves gap regions by utilizing the dual advantages of accuracy and length of high-fidelity (HiFi) reads. DEGAP identifies differences between reads and provides 'GapFiller' or 'CtgLinker' modes to eliminate or shorten gaps in genomes. DEGAP adopts an iterative elongation strategy that automatically and dynamically adjusts parameters according to three complexity factors affecting the genome to determine the optimal extension path. DEGAP has already been successfully applied to decipher complex genomic regions in several projects and may be widely employed to generate more gap-free genomes.

Comparison of ddRADseq and EUChip60K SNP genotyping systems for population genetics and genomic selection in Eucalyptus dunnii (Maiden)

Eucalyptus dunnii is one of the most important Eucalyptus species for short-fiber pulp production in regions where other species of the genus are affected by poor soil and climatic conditions. In this context, E. dunnii holds promise as a resource to address and adapt to the challenges of climate change. Despite its rapid growth and favorable wood properties for solid wood products, the advancement of its improvement remains in its early stages. In this work, we evaluated the performance of two single nucleotide polymorphism, (SNP), genotyping methods for population genetics analysis and Genomic Selection in E. dunnii. Double digest restriction-site associated DNA sequencing (ddRADseq) was compared with the EUChip60K array in 308 individuals from a provenance-progeny trial. The compared SNP set included 8,011 and 19,008 informative SNPs distributed along the 11 chromosomes, respectively. Although the two datasets differed in the percentage of missing data, genome coverage, minor allele frequency and estimated genetic diversity parameters, they revealed a similar genetic structure, showing two subpopulations with little differentiation between them, and low linkage disequilibrium. GS analyses were performed for eleven traits using Genomic Best Linear Unbiased Prediction (GBLUP) and a conventional pedigree-based model (ABLUP). Regardless of the SNP dataset, the predictive ability (PA) of GBLUP was better than that of ABLUP for six traits (Cellulose content, Total and Ethanolic extractives, Total and Klason lignin content and Syringyl and Guaiacyl lignin monomer ratio). When contrasting the SNP datasets used to estimate PAs, the GBLUP-EUChip60K model gave higher and significant PA values for six traits, meanwhile, the values estimated using ddRADseq gave higher values for three other traits. The PAs correlated positively with narrow sense heritabilities, with the highest correlations shown by the ABLUP and GBLUP-EUChip60K. The two genotyping methods, ddRADseq and EUChip60K, are generally comparable for population genetics and genomic prediction, demonstrating the utility of the former when subjected to rigorous SNP filtering. The results of this study provide a basis for future whole-genome studies using ddRADseq in non-model forest species for which SNP arrays have not yet been developed.

How Can Genomics Help or Hinder Wildlife Conservation?

Genomic data are becoming increasingly affordable and easy to collect, and new tools for their analysis are appearing rapidly. Conservation biologists are interested in using this information to assist in management and planning but are typically limited financially and by the lack of genomic resources available for non-model taxa. It is therefore important to be aware of the pitfalls as well as the benefits of applying genomic approaches. Here, we highlight recent methods aimed at standardizing population assessments of genetic variation, inbreeding, and forms of genetic load and methods that help identify past and ongoing patterns of genetic interchange between populations, including those subjected to recent disturbance. We emphasize challenges in applying some of these methods and the need for adequate bioinformatic support. We also consider the promises and challenges of applying genomic approaches to understand adaptive changes in natural populations to predict their future adaptive capacity.

How Fish Population Genomics Can Promote Sustainable Fisheries: A Road Map

Maintenance of genetic diversity in marine fishes targeted by commercial fishing is a grand challenge for the future. Most of these species are abundant and therefore important for marine ecosystems and food security. Here, we present a road map of how population genomics can promote sustainable fisheries. In these species, the development of reference genomes and whole genome sequencing is key, because genetic differentiation at neutral loci is usually low due to large population sizes and gene flow. First, baseline allele frequencies representing genetically differentiated populations within species must be established. These can then be used to accurately determine the composition of mixed samples, forming the basis for population demographic analysis to inform sustainably set fish quotas. SNP-chip analysis is a cost-effective method for determining baseline allele frequencies and for population identification in mixed samples. Finally, we describe how genetic marker analysis can transform stock identification and management.

Hound: a novel tool for automated mapping of genotype to phenotype in bacterial genomes assembled de novo

Increasing evidence suggests that microbial species have a strong within species genetic heterogeneity. This can be problematic for the analysis of prokaryote genomes, which commonly relies on a reference genome to guide the assembly process. Differences between reference and sample genomes will therefore introduce errors in final assembly, jeopardizing the detection from structural variations to point mutations-critical for genomic surveillance of antibiotic resistance. Here we present Hound, a pipeline that integrates publicly available tools to assemble prokaryote genomes de novo, detect user-given genes by similarity to report mutations found in the coding sequence, promoter, as well as relative gene copy number within the assembly. Importantly, Hound can use the query sequence as a guide to merge contigs, and reconstruct genes that were fragmented by the assembler. To showcase Hound, we screened through 5032 bacterial whole-genome sequences isolated from farmed animals and human infections, using the amino acid sequence encoded by blaTEM-1, to detect and predict resistance to amoxicillin/clavulanate which is driven by over-expression of this gene. We believe this tool can facilitate the analysis of prokaryote species that currently lack a reference genome, and can be scaled either up to build automated systems for genomic surveillance or down to integrate into antibiotic susceptibility point-of-care diagnostics.

Contrasting patterns of sequence variation in steelhead populations reflect distinct evolutionary processes

Multiple evolutionary processes influence genome-wide allele frequencies and quantifying effects of genetic drift, and multiple forms of selection remain challenging in natural populations. Here, we investigate variation at major effect loci in contrast to patterns of neutral drift across a wide collection of steelhead (Oncorhynchus mykiss) populations that have declined in abundance due to anthropogenic impacts. Whole-genome resequencing of 74 populations of steelhead revealed genome-wide patterns (~8 million SNPs) consistent with expected neutral population structure. However, allelic variation at major effect loci associated with adult migration timing (chromosome 28: GREB1L/ROCK1) and age at maturity (chromosome 25: SIX6) reflected how selection has acted on phenotypic variation in contrast with neutral structure. Variation at major effect loci was influenced by evolutionary processes with differing signals between the strongly divergent Coastal and Inland lineages, while allele frequencies within and among populations within the Inland lineage have been driven by local natural selection as well as recent anthropogenic influences. Recent anthropogenic effects appeared to have influenced the frequency of major effect alleles including artificial selection for specific traits in hatchery stocks with subsequent gene flow into natural populations. Selection from environmental factors at various scales has also likely influenced variation for major effect alleles. These results reveal evolutionary mechanisms that influence allele frequencies at major effect loci that are critical for conservation of phenotypic traits and life history variation of this protected species.

Microsatellites reveal divergence in population genetic diversity, and structure of osyris lanceolata (santalaceae) in Uganda and Kenya

BACKGROUND

Osyris lanceolata (Hochst. & Steud.) (Santalaceae) is a multipurpose plant highly valued culturally and economically in Africa. However, O. lanceolata populations have rapidly dwindled in East Africa due to overexploitation and this is believed to cause further consequences on the species' genetic diversity and structure within the region. Information regarding a species' genetic diversity and structure is necessary for conservation but this is currently lacking for O. lanceolata in Uganda and Kenya. Lack of adequate scientific data hinders conservation efforts hence threatening the species survival and livelihoods. This study investigated patterns in genetic diversity and structure of O. lanceolata in Uganda and Kenya. Ten polymorphic microsatellite loci were used to genotype 210 individuals: 96 from Ugandan and 114 from Kenyan populations.

RESULTS

All populations were highly polymorphic (80-100% polymorphism). A genetic differentiation was found between Kenyan and Ugandan populations. The highest genetic differentiation was among individuals and the least among populations. The Kenyan populations showed higher genetic diversity than Ugandan populations. The Ugandan populations showed more marker deviations from Hardy-Weinberg equilibrium and inbreeding coefficient. Two populations showed evidence of going through a recent bottleneck. There was significant genetic differentiation and structuring at higher K values into larger clusters and observed admixture between populations. The populations were significantly isolated by altitude as opposed to distance and climatic variables. Main barriers were associated with altitude differences. The data supports the idea of long-distance gene-flow between high altitude populations in both countries.

CONCLUSION

The divergence in genetic structure suggests unrecognised taxonomic units within O. lanceolata which are characteristic to lower altitudes and higher altitudes including most Kenyan populations with divergent evolutionary patterns. Geographical barriers and environmental gradients could have influenced this genetic divergence, and such patterns may escalate the species microevolutionary processes into full allopatric speciation. Further investigations into the species' genetic admixture and emerging taxonomic units are necessary to guide conservation strategies in the region.

Widespread Deviant Patterns of Heterozygosity in Whole-Genome Sequencing Due to Autopolyploidy, Repeated Elements, and Duplication

Most population genomic tools rely on accurate single nucleotide polymorphism (SNP) calling and filtering to meet their underlying assumptions. However, genomic complexity, resulting from structural variants, paralogous sequences, and repetitive elements, presents significant challenges in assembling contiguous reference genomes. Consequently, short-read resequencing studies can encounter mismapping issues, leading to SNPs that deviate from Mendelian expected patterns of heterozygosity and allelic ratio. In this study, we employed the ngsParalog software to identify such deviant SNPs in whole-genome sequencing (WGS) data with low (1.5×) to intermediate (4.8×) coverage for four species: Arctic Char (Salvelinus alpinus), Lake Whitefish (Coregonus clupeaformis), Atlantic Salmon (Salmo salar), and the American Eel (Anguilla rostrata). The analyses revealed that deviant SNPs accounted for 22% to 62% of all SNPs in salmonid datasets and approximately 11% in the American Eel dataset. These deviant SNPs were particularly concentrated within repetitive elements and genomic regions that had recently undergone rediploidization in salmonids. Additionally, narrow peaks of elevated coverage were ubiquitous along all four reference genomes, encompassed most deviant SNPs, and could be partially associated with transposons and tandem repeats. Including these deviant SNPs in genomic analyses led to highly distorted site frequency spectra, underestimated pairwise FST values, and overestimated nucleotide diversity. Considering the widespread occurrence of deviant SNPs arising from a variety of sources, their important impact in estimating population parameters, and the availability of effective tools to identify them, we propose that excluding deviant SNPs from WGS datasets is required to improve genomic inferences for a wide range of taxa and sequencing depths.

Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data

BACKGROUND

Microhaplotypes have the potential to be more cost-effective than SNPs for applications that require genetic panels of highly variable loci. However, development of microhaplotype panels is hindered by a lack of methods for estimating microhaplotype allele frequency from low-coverage whole genome sequencing or pooled sequencing (pool-seq) data.

RESULTS

We developed new methods for estimating microhaplotype allele frequency from low-coverage whole genome sequence and pool-seq data. We validated these methods using datasets from three non-model organisms. These methods allowed estimation of allele frequency and expected heterozygosity at depths routinely achieved from pooled sequencing.

CONCLUSIONS

These new methods will allow microhaplotype panels to be designed using low-coverage WGS and pool-seq data to discover and evaluate candidate loci. The python script implementing the two methods and documentation are available at https://www.github.com/delomast/mhFromLowDepSeq .

Adaptation to the High-Arctic island environment despite long-term reduced genetic variation in Svalbard reindeer

Typically much smaller in number than their mainland counterparts, island populations are ideal systems to investigate genetic threats to small populations. The Svalbard reindeer (Rangifer tarandus platyrhynchus) is an endemic subspecies that colonized the Svalbard archipelago ca. 6,000-8,000 years ago and now shows numerous physiological and morphological adaptations to its arctic habitat. Here, we report a de-novo chromosome-level assembly for Svalbard reindeer and analyze 133 reindeer genomes spanning Svalbard and most of the species' Holarctic range, to examine the genomic consequences of long-term isolation and small population size in this insular subspecies. Empirical data, demographic reconstructions, and forward simulations show that long-term isolation and high inbreeding levels may have facilitated the reduction of highly deleterious-and to a lesser extent, moderately deleterious-variation. Our study indicates that long-term reduced genetic diversity did not preclude local adaptation to the High Arctic, suggesting that even severely bottlenecked populations can retain evolutionary potential.

Population Genomics of Pooled Samples: Unveiling Symbiont Infrapopulation Diversity and Host-Symbiont Coevolution

Microscopic symbionts represent crucial links in biological communities. However, they present technical challenges in high-throughput sequencing (HTS) studies due to their small size and minimal high-quality DNA yields, hindering our understanding of host-symbiont coevolution at microevolutionary and macroevolutionary scales. One approach to overcome those barriers is to pool multiple individuals from the same infrapopulation (i.e., individual host) and sequence them together (Pool-Seq), but individual-level information is then compromised. To simultaneously address both issues (i.e., minimal DNA yields and loss of individual-level information), we implemented a strategic Pool-Seq approach to assess variation in sequencing performance and categorize genetic diversity (single nucleotide polymorphisms (SNPs)) at both the individual-level and infrapopulation-level for microscopic feather mites. To do so, we collected feathers harboring mites (Proctophyllodidae: Amerodectes protonotaria) from four individual Prothonotary Warblers (Parulidae: Protonotaria citrea). From each of the four hosts (i.e., four mite infrapopulations), we conducted whole-genome sequencing on three extraction pools consisting of different numbers of mites (1 mite, 5 mites, and 20 mites). We found that samples containing pools of multiple mites had more sequencing reads map to the feather mite reference genome than did the samples containing only a single mite. Mite infrapopulations were primarily genetically structured by their associated individual hosts (not pool size) and the majority of SNPs were shared by all pools within an infrapopulation. Together, these results suggest that the patterns observed are driven by evolutionary processes occurring at the infrapopulation level and are not technical signals due to pool size. In total, despite the challenges presented by microscopic symbionts in HTS studies, this work highlights the value of both individual-level and infrapopulation-level sequencing toward our understanding of host-symbiont coevolution at multiple evolutionary scales.

Whole genome analyses reveal weak signatures of population structure and environmentally associated local adaptation in an important North American pollinator, the bumble bee Bombus vosnesenskii

Studies of species that experience environmental heterogeneity across their distributions have become an important tool for understanding mechanisms of adaptation and predicting responses to climate change. We examine population structure, demographic history and environmentally associated genomic variation in Bombus vosnesenskii, a common bumble bee in the western USA, using whole genome resequencing of populations distributed across a broad range of latitudes and elevations. We find that B. vosnesenskii exhibits minimal population structure and weak isolation by distance, confirming results from previous studies using other molecular marker types. Similarly, demographic analyses with Sequentially Markovian Coalescent models suggest that minimal population structure may have persisted since the last interglacial period, with genomes from different parts of the species range showing similar historical effective population size trajectories and relatively small fluctuations through time. Redundancy analysis revealed a small amount of genomic variation explained by bioclimatic variables. Environmental association analysis with latent factor mixed modelling (LFMM2) identified few outlier loci that were sparsely distributed throughout the genome and although a few putative signatures of selective sweeps were identified, none encompassed particularly large numbers of loci. Some outlier loci were in genes with known regulatory relationships, suggesting the possibility of weak selection, although compared with other species examined with similar approaches, evidence for extensive local adaptation signatures in the genome was relatively weak. Overall, results indicate B. vosnesenskii is an example of a generalist with a high degree of flexibility in its environmental requirements that may ultimately benefit the species under periods of climate change.

Prioritizing Endangered Species in Genome Sequencing: Conservation Genomics in Action with the First Platinum-Standard Reference-Quality Genome of the Critically Endangered European Mink Mustela lutreola L., 1761

The European mink Mustela lutreola (Mustelidae) ranks among the most endangered mammalian species globally, experiencing a rapid and severe decline in population size, density, and distribution. Given the critical need for effective conservation strategies, understanding its genomic characteristics becomes paramount. To address this challenge, the platinum-quality, chromosome-level reference genome assembly for the European mink was successfully generated under the project of the European Mink Centre consortium. Leveraging PacBio HiFi long reads, we obtained a 2586.3 Mbp genome comprising 25 scaffolds, with an N50 length of 154.1 Mbp. Through Hi-C data, we clustered and ordered the majority of the assembly (>99.9%) into 20 chromosomal pseudomolecules, including heterosomes, ranging from 6.8 to 290.1 Mbp. The newly sequenced genome displays a GC base content of 41.9%. Additionally, we successfully assembled the complete mitochondrial genome, spanning 16.6 kbp in length. The assembly achieved a BUSCO (Benchmarking Universal Single-Copy Orthologs) completeness score of 98.2%. This high-quality reference genome serves as a valuable genomic resource for future population genomics studies concerning the European mink and related taxa. Furthermore, the newly assembled genome holds significant potential in addressing key conservation challenges faced by M. lutreola. Its applications encompass potential revision of management units, assessment of captive breeding impacts, resolution of phylogeographic questions, and facilitation of monitoring and evaluating the efficiency and effectiveness of dedicated conservation strategies for the European mink. This species serves as an example that highlights the paramount importance of prioritizing endangered species in genome sequencing projects due to the race against time, which necessitates the comprehensive exploration and characterization of their genomic resources before their populations face extinction.

Contrasting genomic consequences of anthropogenic reintroduction and natural recolonization in high-arctic wild reindeer

Anthropogenic reintroduction can supplement natural recolonization in reestablishing a species' distribution and abundance. However, both reintroductions and recolonizations can give rise to founder effects that reduce genetic diversity and increase inbreeding, potentially causing the accumulation of genetic load and reduced fitness. Most current populations of the endemic high-arctic Svalbard reindeer (Rangifer tarandus platyrhynchus) originate from recent reintroductions or recolonizations following regional extirpations due to past overharvesting. We investigated and compared the genomic consequences of these two paths to reestablishment using whole-genome shotgun sequencing of 100 Svalbard reindeer across their range. We found little admixture between reintroduced and natural populations. Two reintroduced populations, each founded by 12 individuals around four decades (i.e. 8 reindeer generations) ago, formed two distinct genetic clusters. Compared to the source population, these populations showed only small decreases in genome-wide heterozygosity and increases in inbreeding and lengths of runs of homozygosity. In contrast, the two naturally recolonized populations without admixture possessed much lower heterozygosity, higher inbreeding and longer runs of homozygosity, possibly caused by serial population founder effects and/or fewer or more genetically related founders than in the reintroduction events. Naturally recolonized populations can thus be more vulnerable to the accumulation of genetic load than reintroduced populations. This suggests that in some organisms even small-scale reintroduction programs based on genetically diverse source populations can be more effective than natural recolonization in establishing genetically diverse populations. These findings warrant particular attention in the conservation and management of populations and species threatened by habitat fragmentation and loss.

Fine-scale environmentally associated spatial structure of lumpfish (Cyclopterus lumpus) across the Northwest Atlantic

Lumpfish, Cyclopterus lumpus, have historically been harvested throughout Atlantic Canada and are increasingly in demand as a solution to controlling sea lice in Atlantic salmon farms-a process which involves both the domestication and the transfer of lumpfish between geographic regions. At present, little is known regarding population structure and diversity of wild lumpfish in Atlantic Canada, limiting attempts to assess the potential impacts of escaped lumpfish individuals from salmon pens on currently at-risk wild populations. Here, we characterize the spatial population structure and genomic-environmental associations of wild populations of lumpfish throughout the Northwest Atlantic using both 70K SNP array data and whole-genome re-sequencing data (WGS). At broad spatial scales, our results reveal a large environmentally associated genetic break between the southern populations (Gulf of Maine and Bay of Fundy) and northern populations (Newfoundland and the Gulf of St. Lawrence), linked to variation in ocean temperature and ice cover. At finer spatial scales, evidence of population structure was also evident in a distinct coastal group in Newfoundland and significant isolation by distance across the northern region. Both evidence of consistent environmental associations and elevated genome-wide variation in F ST values among these three regional groups supports their biological relevance. This study represents the first extensive description of population structure of lumpfish in Atlantic Canada, revealing evidence of broad and fine geographic scale environmentally associated genomic diversity. Our results will facilitate the commercial use of lumpfish as a cleaner fish in Atlantic salmon aquaculture, the identification of lumpfish escapees, and the delineation of conservation units of this at-risk species throughout Atlantic Canada.

Best practices for genotype imputation from low-coverage sequencing data in natural populations

Monitoring genetic diversity in wild populations is a central goal of ecological and evolutionary genetics and is critical for conservation biology. However, genetic studies of nonmodel organisms generally lack access to species-specific genotyping methods (e.g. array-based genotyping) and must instead use sequencing-based approaches. Although costs are decreasing, high-coverage whole-genome sequencing (WGS), which produces the highest confidence genotypes, remains expensive. More economical reduced representation sequencing approaches fail to capture much of the genome, which can hinder downstream inference. Low-coverage WGS combined with imputation using a high-confidence reference panel is a cost-effective alternative, but the accuracy of genotyping using low-coverage WGS and imputation in nonmodel populations is still largely uncharacterized. Here, we empirically tested the accuracy of low-coverage sequencing (0.1-10×) and imputation in two natural populations, one with a large (n = 741) reference panel, rhesus macaques (Macaca mulatta), and one with a smaller (n = 68) reference panel, gelada monkeys (Theropithecus gelada). Using samples sequenced to coverage as low as 0.5×, we could impute genotypes at >95% of the sites in the reference panel with high accuracy (median r2  ≥ 0.92). We show that low-coverage imputed genotypes can reliably calculate genetic relatedness and population structure. Based on these data, we also provide best practices and recommendations for researchers who wish to deploy this approach in other populations, with all code available on GitHub (https://github.com/mwatowich/LoCSI-for-non-model-species). Our results endorse accurate and effective genotype imputation from low-coverage sequencing, enabling the cost-effective generation of population-scale genetic datasets necessary for tackling many pressing challenges of wildlife conservation.

Efficient and Highly Continuous Chromosome-Level Genome Assembly of the First Chameleon Genome

Most amniote genomes are diploid and moderate in size (∼1-6 Gbp) and contain a large proportion of repetitive sequences. The development of next-generation sequencing technology, especially the emergence of high-fidelity (HiFi) long-read data, has made it feasible to resolve high-quality genome assembly for nonmodel species efficiently. However, reference genomes for squamate reptiles have lagged behind other amniote lineages. Here, we de novo assembled the first genome from the Chameleonidae family, the panther chameleon (Furcifer pardalis). We obtained telomere-to-telomere contigs using only HiFi data, reaching a contig N50 of 158.72 Mbp. The final chromosome-level assembly is 1.61 Gbp in size, and 100% of primary contigs were placed to pseudochromosomes using Hi-C interaction data. We also found that sequencing depth > 30 folds can ensure both the integrity and accuracy of the genome, whereas insufficient depth led to false increase in genome size and proportion of duplicated genes. We provide a high-quality reference genome valuable for evolutionary and ecological studies in chameleons as well as provide comparative genomic resources for squamate reptiles.

Key triggers of adaptive genetic variability of sessile oak [Q. petraea (Matt.) Liebl.] from the Balkan refugia: outlier detection and association of SNP loci from ddRAD-seq data

Knowledge on the genetic composition of Quercus petraea in south-eastern Europe is limited despite the species' significant role in the re-colonisation of Europe during the Holocene, and the diverse climate and physical geography of the region. Therefore, it is imperative to conduct research on adaptation in sessile oak to better understand its ecological significance in the region. While large sets of SNPs have been developed for the species, there is a continued need for smaller sets of SNPs that are highly informative about the possible adaptation to this varied landscape. By using double digest restriction site associated DNA sequencing data from our previous study, we mapped RAD-seq loci to the Quercus robur reference genome and identified a set of SNPs putatively related to drought stress-response. A total of 179 individuals from eighteen natural populations at sites covering heterogeneous climatic conditions in the southeastern natural distribution range of Q. petraea were genotyped. The detected highly polymorphic variant sites revealed three genetic clusters with a generally low level of genetic differentiation and balanced diversity among them but showed a north-southeast gradient. Selection tests showed nine outlier SNPs positioned in different functional regions. Genotype-environment association analysis of these markers yielded a total of 53 significant associations, explaining 2.4-16.6% of the total genetic variation. Our work exemplifies that adaptation to drought may be under natural selection in the examined Q. petraea populations.

Genomic Insights into the Origin of a Thermotolerant Tomato Line and Identification of Candidate Genes for Heat Stress

Climate change represents the main problem for agricultural crops, and the constitution of heat-tolerant genotypes is an important breeder’s strategy to reduce yield losses. The aim of the present study was to investigate the whole genome of a heat-tolerant tomato genotype (E42), in order to identify candidate genes involved in its response to high temperature. E42 presented a high variability for chromosomes 1, 4, 7 and 12, and phylogenetic analysis highlighted its relationship with the wild S. pimpinellifolium species. Variants with high (18) and moderate (139) impact on protein function were retrieved from two lists of genes related to heat tolerance and reproduction. This analysis permitted us to prioritize a subset of 35 candidate gene mapping in polymorphic regions, some colocalizing in QTLs controlling flowering in tomato. Among these genes, we identified 23 HSPs, one HSF, six involved in flowering and five in pollen activity. Interestingly, one gene coded for a flowering locus T1 and mapping on chromosome 11 resides in a QTL region controlling flowering and also showed 100% identity with an S. pimpinellifolium allele. This study provides useful information on both the E42 genetic background and heat stress response, and further studies will be conducted to validate these genes.

How genomics can help biodiversity conservation

The availability of public genomic resources can greatly assist biodiversity assessment, conservation, and restoration efforts by providing evidence for scientifically informed management decisions. Here we survey the main approaches and applications in biodiversity and conservation genomics, considering practical factors, such as cost, time, prerequisite skills, and current shortcomings of applications. Most approaches perform best in combination with reference genomes from the target species or closely related species. We review case studies to illustrate how reference genomes can facilitate biodiversity research and conservation across the tree of life. We conclude that the time is ripe to view reference genomes as fundamental resources and to integrate their use as a best practice in conservation genomics.

Genome survey and genetic characterization of Acacia pachyceras O. Schwartz

Acacia pachyceras O. Schwartz (Leguminoseae), a woody tree growing in Kuwait is critically endangered. High throughput genomic research is immediately needed to formulate effective conservation strategies for its rehabilitation. We therefore, performed a genome survey analysis of the species. Whole genome sequencing generated ~97 Gb of raw reads (92x coverage) with a per base quality score above Q30. The k-mer analysis (17 mer) revealed its genome to be 720Mb in size with an average guanine-cytosine (GC) ratio of 35%. The assembled genome was analyzed for repeat regions (45.4%-interspersed repeats; 9%-retroelements; 2%-DNA transposons). BUSCO assessment of completeness of genome identified 93% of assembly to be complete. Gene alignments in BRAKER2 yielded 34,374 transcripts corresponding to 33,650 genes. Average length of coding sequences and protein sequences were recorded as 1,027nts and 342aa, respectively. GMATA software filtered a total of 901,755 simple sequence repeats (SSRs) regions against which 11,181 unique primers were designed. A subset of 110 SSR primers were PCR validated and demonstrated for its application in genetic diversity analysis of Acacia. The SSR primers successfully amplified A. gerrardii seedlings DNA depicting cross transferability among species. The principal coordinate analysis and the split decomposition tree (bootstrapping runs of 1000 replicates) distributed the Acacia genotypes into two clusters. The flow cytometry analysis revealed the A. pachyceras genome to be polyploid (6x). The DNA content was predicted as 2.46 pg, 1.23 pg, and 0.41 pg corresponding to 2C DNA, 1C DNA and 1Cx DNA, respectively. The results provide a base for further high throughput genomic studies and molecular breeding for its conservation.

Double Digest Restriction-Site Associated DNA Sequencing (ddRADseq) Technology

Double digest restriction-site associated DNA sequencing (ddRADseq) technology combines genome reduced representation by digestion with two restriction enzymes and next generation sequencing (NGS) to obtain thousands of markers (SNP, SSR, and InDels) and genotype tens to hundreds of samples simultaneously. In this chapter, we describe a 96-plex derived ddRADseq protocol that can be set up to obtain different depth of coverage per locus and can be exploited to model and non-model plant species.

Current Progress, Applications and Challenges of Multi-Omics Approaches in Sesame Genetic Improvement

Sesame is one of the important traditional oil crops in the world, and has high economic and nutritional value. Recently, due to the novel high throughput sequencing techniques and bioinformatical methods, the study of the genomics, methylomics, transcriptomics, proteomics and metabonomics of sesame has developed rapidly. Thus far, the genomes of five sesame accessions have been released, including white and black seed sesame. The genome studies reveal the function and structure of the sesame genome, and facilitate the exploitation of molecular markers, the construction of genetic maps and the study of pan-genomes. Methylomics focus on the study of the molecular level changes under different environmental conditions. Transcriptomics provide a powerful tool to study abiotic/biotic stress, organ development, and noncoding RNAs, and proteomics and metabonomics also provide some support in studying abiotic stress and important traits. In addition, the opportunities and challenges of multi-omics in sesame genetics breeding were also described. This review summarizes the current research status of sesame from the perspectives of multi-omics and hopes to provide help for further in-depth research on sesame.

Whole-genome resequencing reveals complex effects of geographical-palaeoclimatic interactions on diversification of moustache toads in East Asia

Geographical features and palaeoclimatic fluctuations are two classical evolutionary forces that shape genetic diversification within species. Fine-grained analysis of the mechanisms involved through population demographic processes, however, remains limited. Taking advantage of two recently published reference genomes, we resequenced the genomes and examined the evolutionary history of the moustache toads, a group endemic to East Asia where complex topography and fluctuating palaeoclimate are known to have had profound impacts on organisms. Moustache toads probably originated in southeast Yunnan, China, and diversified towards the northwestern of Yunnan, as well as central and eastern China. Further exploration based on three widespread species (Leptobrachium ailaonicum, L. boringii and L. liui) using demographic modelling and species distribution models revealed that mountains and river valleys in East Asia not only functioned as geographical barriers, but also provided dispersal corridors and facilitated continuous migration or post-glacial secondary contact among moustache toad populations. Furthermore, periodic oscillation of effective population sizes accompanying fluctuations of historical temperature and population contraction at the Last Glacial Maximum support the widespread impact of climatic changes of the Pleistocene on species diversification in East Asia. This impact was moderate for populations of L. ailaonicum and L. boringii in the southwestern mountains but severe for populations of L. liui in the eastern lowland regions of continental East Asia, which is supported by different degrees of change of their effective population sizes. Our findings reveal mechanisms underlying genetic diversification among moustache toads, and highlight the power of genomic data and demographic modelling for examining complex historical population-level processes and for understanding how geographical and palaeoclimatic factors interactively shape current intraspecific diversity.

Whole genome resequencing identifies local adaptation associated with environmental variation for redband trout

Aquatic ectotherms are predicted to harbour genomic signals of local adaptation resulting from selective pressures driven by the strong influence of climate conditions on body temperature. We investigated local adaptation in redband trout (Oncorhynchus mykiss gairdneri) using genome scans for 547 samples from 11 populations across a wide range of habitats and thermal gradients in the interior Columbia River. We estimated allele frequencies for millions of single nucleotide polymorphism loci (SNPs) across populations using low-coverage whole genome resequencing, and used population structure outlier analyses to identify genomic regions under divergent selection between populations. Twelve genomic regions showed signatures of local adaptation, including two regions associated with genes known to influence migration and developmental timing in salmonids (GREB1L, ROCK1, SIX6). Genotype-environment association analyses indicated that diurnal temperature variation was a strong driver of local adaptation, with signatures of selection driven primarily by divergence of two populations in the northern extreme of the subspecies range. We also found evidence for adaptive differences between high-elevation desert vs. montane habitats at a smaller geographical scale. Finally, we estimated vulnerability of redband trout to future climate change using ecological niche modelling and genetic offset analyses under two climate change scenarios. These analyses predicted substantial habitat loss and strong genetic shifts necessary for adaptation to future habitats, with the greatest vulnerability predicted for high-elevation desert populations. Our results provide new insight into the complexity of local adaptation in salmonids, and important predictions regarding future responses of redband trout to climate change.

Increasing the production of the bioactive compounds in medicinal mushrooms: an omics perspective

Macroscopic fungi, mainly higher basidiomycetes and some ascomycetes, are considered medicinal mushrooms and have long been used in different areas due to their pharmaceutically/nutritionally valuable bioactive compounds. However, the low production of these bioactive metabolites considerably limits the utilization of medicinal mushrooms both in commerce and clinical trials. As a result, many attempts, ranging from conventional methods to novel approaches, have been made to improve their production. The novel strategies include conducting omics investigations, constructing genome-scale metabolic models, and metabolic engineering. So far, genomics and the combined use of different omics studies are the most utilized omics analyses in medicinal mushroom research (both with 31% contribution), while metabolomics (with 4% contribution) is the least. This article is the first attempt for reviewing omics investigations in medicinal mushrooms with the ultimate aim of bioactive compound overproduction. In this regard, the role of these studies and systems biology in elucidating biosynthetic pathways of bioactive compounds and their contribution to metabolic engineering will be highlighted. Also, limitations of omics investigations and strategies for overcoming them will be provided in order to facilitate the overproduction of valuable bioactive metabolites in these valuable organisms.

A low-density single nucleotide polymorphism panel for brown trout (Salmo trutta L.) suitable for exploring genetic diversity at a range of spatial scales

The rivers of southern England and northern France which drain into the English Channel contain several genetically unique groups of trout (Salmo trutta L.) that have suffered dramatic declines in numbers over the past 40 years. Knowledge of levels and patterns of genetic diversity is essential for effective management of these vulnerable populations. Using restriction site-associated DNA sequencing (RADseq) data, we describe the development and characterisation of a panel of 95 single nucleotide polymorphism (SNP) loci for trout from this region and investigate their applicability and variability in both target (i.e., southern English) and non-target trout populations from northern Britain and Ireland. In addition, we present three case studies which demonstrate the utility and resolution of these genetic markers at three levels of spatial separation:(a) between closely related populations in nearby rivers, (b) within a catchment and (c) when determining parentage and familial relationships between fish sampled from a single site, using both empirical and simulated data. The SNP loci will be useful for population genetic and assignment studies on brown trout within the UK and beyond.

Fidelity varies in the symbiosis between a gutless marine worm and its microbial consortium

BACKGROUND

Many animals live in intimate associations with a species-rich microbiome. A key factor in maintaining these beneficial associations is fidelity, defined as the stability of associations between hosts and their microbiota over multiple host generations. Fidelity has been well studied in terrestrial hosts, particularly insects, over longer macroevolutionary time. In contrast, little is known about fidelity in marine animals with species-rich microbiomes at short microevolutionary time scales, that is at the level of a single host population. Given that natural selection acts most directly on local populations, studies of microevolutionary partner fidelity are important for revealing the ecological and evolutionary processes that drive intimate beneficial associations within animal species.

RESULTS

In this study on the obligate symbiosis between the gutless marine annelid Olavius algarvensis and its consortium of seven co-occurring bacterial symbionts, we show that partner fidelity varies across symbiont species from strict to absent over short microevolutionary time. Using a low-coverage sequencing approach that has not yet been applied to microbial community analyses, we analysed the metagenomes of 80 O. algarvensis individuals from the Mediterranean and compared host mitochondrial and symbiont phylogenies based on single-nucleotide polymorphisms across genomes. Fidelity was highest for the two chemoautotrophic, sulphur-oxidizing symbionts that dominated the microbial consortium of all O. algarvensis individuals. In contrast, fidelity was only intermediate to absent in the sulphate-reducing and spirochaetal symbionts with lower abundance. These differences in fidelity are likely driven by both selective and stochastic forces acting on the consistency with which symbionts are vertically transmitted.

CONCLUSIONS

We hypothesize that variable degrees of fidelity are advantageous for O. algarvensis by allowing the faithful transmission of their nutritionally most important symbionts and flexibility in the acquisition of other symbionts that promote ecological plasticity in the acquisition of environmental resources. Video Abstract.

Utility and challenges of using whole‐genome resequencing to detect emerging insect and mite resistance in agroecosystems

Arthropods that invade agricultural ecosystems systematically evolve resistance to the control measures used against them, and this remains a significant and ongoing challenge for sustainable food production systems. Early detection of resistance evolution could prompt remedial action to slow the spread of resistance alleles in the landscape. Historical approaches used to detect emerging resistance included phenotypic monitoring of agricultural pest populations, as well as monitoring of allele frequency changes at one or a few candidate pesticide resistance genes. In this article, I discuss the successes and limitations of these traditional monitoring approaches and then consider whether whole‐genome scanning could be applied to samples collected from agroecosystems over time for resistance monitoring. I examine the qualities of agroecosystems that could impact application of this approach to pesticide resistance monitoring and describe a recent retrospective analysis where genome scanning successfully detected an oligogenic response to selection by pesticides years prior to pest management failure. I conclude by considering areas of further study that will shed light on the feasibility of applying whole‐genome scanning for resistance risk monitoring in agricultural pest species.

African wild dogs (Lycaon pictus) from the Kruger National Park, South Africa are currently not inbred but have low genomic diversity

African wild dogs (Lycaon pictus) have undergone severe population reductions and are listed as endangered on the International Union for Conservation of Nature Red List. Small, isolated populations have the potential to suffer from threats to their genetic diversity that may impact species viability and future survival. This study provides the first set of population-wide genomic data to address conservation concerns for this endangered species. Whole genome sequencing data were generated for 71 free-ranging African wild dogs from the Kruger National Park (KNP), South Africa, and used to estimate important population genomic parameters. Genomic diversity metrics revealed that variation levels were low; however, this African wild dog population showed low levels of inbreeding. Very few first- and second-order relationships were observed in this cohort, with most relationships falling into the third-order or distant category. Patterns of homozygosity could have resulted from historical inbreeding or a loss in genome variation due to a population bottleneck. Although the results suggest that this stronghold African wild dog population maintains low levels of inbreeding, likely due to their cooperative breeding system, it may lead to a continuous population decline when a reduced number of suitable mates are available. Consequently, the low genomic variation may influence species viability over time. This study highlights the importance of assessing population genomic parameters to set conservation priorities. Future studies should include the investigation of the potential of this endangered species to adapt to environmental changes considering the low genomic diversity in this population.

Genome–Environment Associations, an Innovative Tool for Studying Heritable Evolutionary Adaptation in Orphan Crops and Wild Relatives

Leveraging innovative tools to speed up prebreeding and discovery of genotypic sources of adaptation from landraces, crop wild relatives, and orphan crops is a key prerequisite to accelerate genetic gain of abiotic stress tolerance in annual crops such as legumes and cereals, many of which are still orphan species despite advances in major row crops. Here, we review a novel, interdisciplinary approach to combine ecological climate data with evolutionary genomics under the paradigm of a new field of study: genome–environment associations (GEAs). We first exemplify how GEA utilizes in situ georeferencing from genotypically characterized, gene bank accessions to pinpoint genomic signatures of natural selection. We later discuss the necessity to update the current GEA models to predict both regional- and local- or micro-habitat–based adaptation with mechanistic ecophysiological climate indices and cutting-edge GWAS-type genetic association models. Furthermore, to account for polygenic evolutionary adaptation, we encourage the community to start gathering genomic estimated adaptive values (GEAVs) for genomic prediction (GP) and multi-dimensional machine learning (ML) models. The latter two should ideally be weighted by de novo GWAS-based GEA estimates and optimized for a scalable marker subset. We end the review by envisioning avenues to make adaptation inferences more robust through the merging of high-resolution data sources, such as environmental remote sensing and summary statistics of the genomic site frequency spectrum, with the epigenetic molecular functionality responsible for plastic inheritance in the wild. Ultimately, we believe that coupling evolutionary adaptive predictions with innovations in ecological genomics such as GEA will help capture hidden genetic adaptations to abiotic stresses based on crop germplasm resources to assist responses to climate change.

“I shall endeavor to find out how nature’s forces act upon one another, and in what manner the geographic environment exerts its influence on animals and plants. In short, I must find out about the harmony in nature” Alexander von Humboldt—Letter to Karl Freiesleben, June 1799.

Sequencing Bait: Nuclear and Mitogenome Assembly of an Abundant Coastal Tropical and Subtropical Fish, Atherinomorus stipes

Genetic data from nonmodel species can inform ecology and physiology, giving insight into a species' distribution and abundance as well as their responses to changing environments, all of which are important for species conservation and management. Moreover, reduced sequencing costs and improved long-read sequencing technology allows researchers to readily generate genomic resources for nonmodel species. Here, we apply Oxford Nanopore long-read sequencing and low-coverage (∼1x) whole genome short-read sequencing technology (Illumina) to assemble a genome and examine population genetics of an abundant tropical and subtropical fish, the hardhead silverside (Atherinomorus stipes). These fish are found in shallow coastal waters and are frequently included in ecological models because they serve as abundant prey for commercially and ecologically important species. Despite their importance in sub-tropical and tropical ecosystems, little is known about their population connectivity and genetic diversity. Our A. stipes genome assembly is about 1.2 Gb with comparable repetitive element content (∼47%), number of protein duplication events, and DNA methylation patterns to other teleost fish species. Among five sampled populations spanning 43 km of South Florida and the Florida Keys, we find little population structure suggesting high population connectivity.

Discerning the global phylogeographic distribution of Phyllosticta citricarpa by means of whole genome sequencing

Phyllosticta citricarpa is a fungal pathogen causing citrus black spot (CBS). As a regulated pest in some countries, the presence of the pathogen limits the export of fruit and is therefore of agricultural and economic importance. In this study, we used high throughput sequencing data to infer the global phylogeographic distribution of this pathogen, including 71 isolates from eight countries, Argentina, Australia, Brazil, China, Cuba, Eswatini, South Africa and the United States of America. We assembled draft genomes and used a pairwise read mapping approach for the detection and enumeration of variants between isolates. We performed SSR marker discovery based on the assembled genome with the best assembly statistics, and generated genotype profiles for all isolates with 1987 SSR markers in silico. Furthermore, we identified 32,560 SNPs relative to a reference sequence followed by population genetic analyses based on the three datasets; pairwise variant counts, SSR genotypes and SNP genotypes. All three analysis approaches gave similar overall results. Possible pathways of dissemination among the populations from China, Australia, southern Africa and the Americas are postulated. The Chinese population is the most diverse, and is genetically the furthest removed from all other populations, and is therefore considered the closest to the origin of the pathogen. Isolates from Australia, Eswatini and the South African province Mpumalanga are closely associated and clustered together with those from Argentina and Brazil. The Eastern Cape, North West, and KwaZulu-Natal populations in South Africa grouped in another cluster, while isolates from Limpopo are distributed between the two aforementioned clusters. Southern African populations showed a close relationship to populations in North America, and could be a possible source of P. citricarpa populations that are now found in North America. This study represents the largest whole genome sequencing survey of P. citricarpa to date and provides a more comprehensive assessment of the population genetic diversity and connectivity of P. citricarpa from different geographic origins. This information could further assist in a better understanding of the epidemiology of the CBS pathogen, its long-distance dispersal and dissemination pathways, and can be used to refine phytosanitary regulations and management programmes for the disease.

Identification of key candidate genes for wing length-related traits by whole-genome resequencing in 772 geese

1. A total of 772, 420-day-old Xingguo gray geese (XGG) were sequenced using a low-depth (~1×) whole-genome resequencing strategy to reveal the genetic mechanism of wing length-related traits by genome-wide association analysis (GWAS).2. The results showed that 119 SNPs had genome-wide significance for wing length in five regions of chromosome 4, of which the most significant locus (P=7.95E-11) was located upstream of RBM47 and explained 7.3% of phenotypic variation.3. A total of 219 SNPs located on chromosome 4 that were associated with 2-joint-wing length, of which four SNPs reached the genome-wide significant level. However, for the length of 1-joint-wing and primary feather, we did not detect any associated locus.4. Six promising candidate genes, RBM47, SLAIN2, GRXCR1, SLC10A4, APBB2 and NSUN7 on chromosome 4, may play an important role in the growth and development of feathers, muscles and bones.

A De Novo Chromosome-level Genome Assembly of the White-tailed Deer, Odocoileus virginianus

Cervids are distinguished by the shedding and regrowth of antlers. Furthermore, they provide insights into prion and other diseases. Genomic resources can facilitate studies of the genetic underpinnings of deer phenotypes, behavior, and disease resistance. Widely distributed in North America, the white-tailed deer (Odocoileus virginianus) has recreational, commercial, and food source value for many households. We present a genome generated using DNA from a single Illinois white-tailed sequenced on the PacBio Sequel II platform and assembled using Wtdbg2. Omni-C chromatin conformation capture sequencing was used to scaffold the genome contigs. The final assembly was 2.42 Gb, consisting of 508 scaffolds with a contig N50 of 21.7 Mb, a scaffold N50 of 52.4 Mb, and a BUSCO complete score of 93.1%. Thirty-six chromosome pseudomolecules comprised 93% of the entire sequenced genome length. A total of 20 651 predicted genes using the BRAKER pipeline were validated using InterProScan. Chromosome length assembly sequences were aligned to the genomes of related species to reveal corresponding chromosomes.

Genomic reaction norms inform predictions of plastic and adaptive responses to climate change

Genomic reaction norms represent the range of gene expression phenotypes (usually mRNA transcript levels) expressed by a genotype along an environmental gradient. Reaction norms derived from common‐garden experiments are powerful approaches for disentangling plastic and adaptive responses to environmental change in natural populations. By treating gene expression as a phenotype in itself, genomic reaction norms represent invaluable tools for exploring causal mechanisms underlying organismal responses to climate change across multiple levels of biodiversity.

Our goal is to provide the context, framework and motivation for applying genomic reaction norms to study the responses of natural populations to climate change.

Here, we describe the utility of integrating genomics with common‐garden‐gradient experiments under a reaction norm analytical framework to answer fundamental questions about phenotypic plasticity, local adaptation, their interaction (i.e. genetic variation in plasticity) and future adaptive potential.

An experimental and analytical framework for constructing and analysing genomic reaction norms is presented within the context of polygenic climate change responses of structured populations with gene flow. Intended for a broad eco‐evo readership, we first briefly review adaptation with gene flow and the importance of understanding the genomic basis and spatial scale of adaptation for conservation and management of structured populations under anthropogenic change. Then, within a high‐dimensional reaction norm framework, we illustrate how to distinguish plastic, differentially expressed (difference in reaction norm intercepts) and differentially plastic (difference in reaction norm slopes) genes, highlighting the areas of opportunity for applying these concepts.

We conclude by discussing how genomic reaction norms can be incorporated into a holistic framework to understand the eco‐evolutionary dynamics of climate change responses from molecules to ecosystems. We aim to inspire researchers to integrate gene expression measurements into common‐garden experimental designs to investigate the genomics of climate change responses as sequencing costs become increasingly accessible.

Identification of Key Candidate Genes for Beak Length Phenotype by Whole-Genome Resequencing in Geese

The domestic goose is an important economic animal in agriculture and its beak, a trait with high heritability, plays an important role in promoting food intake and defending against attacks. In this study, we sequenced 772 420-day-old Xingguo gray geese (XGG) using a low-depth (~1 ×) whole-genome resequencing strategy. We detected 12,490,912 single nucleotide polymorphisms (SNPs) using the standard GATK and imputed with STITCH. We then performed a genome-wide association study on the beak length trait in XGG. The results indicated that 57 SNPs reached genome-wide significance levels for the beak length trait and were assigned to seven genes, including TAPT1, DHX15, CCDC149, LGI2, SEPSECS, ANAPC4, and Slc34a2. The different genotypes of the most significant SNP (top SNP), which was located upstream of LGI2 and explained 7.24% of the phenotypic variation in beak length, showed significant differences in beak length. Priority-based significance analysis concluded that CCDC149, LGI2, and SEPSECS genes in the most significant quantitative trait locus interval were the most plausible positional and functional candidate genes for beak length development in the XGG population. These findings not only enhance our understanding of the genetic mechanism of the beak length phenotype in geese, but also lay the foundation for further studies to facilitate the genetic selection of traits in geese.

Recapitulating whole genome based population genetic structure for Indian wild tigers through an ancestry informative marker panel

Identification of genetic structure within wildlife populations have implications in their conservation and management. Accurately inferring population genetic structure requires whole-genome data across the geographical range of the species, which can be resource-intensive. A cheaper strategy is to employ a subset of markers that can efficiently recapitulate the population genetic structure inferred by the whole genome data. Such ancestry informative markers (AIMs), have rarely been developed for endangered species such as tigers utilizing single nucleotide polymorphisms (SNPs). Here, we first identify the population structure of the Indian tiger using whole-genome sequences and then develop an AIMs panel with a minimum number of SNPs that can recapitulate this structure. We identified four population clusters of Indian tigers with North-East, North-West, and South Indian tigers forming three separate groups, and Terai and Central Indian tigers forming a single cluster. To evaluate the robustness of our AIMs, we applied it to a separate dataset of tigers from across India. Out of 92 SNPs present in our AIMs panel, 49 were present in the new dataset. These 49 SNPs were sufficient to recapitulate the population genetic structure obtained from the whole genome data. To the best of our knowledge, this is the first-ever SNP-based AIMs panel for big cats, which can be used as a cost-effective alternative to whole-genome sequencing for detecting the biogeographical origin of Indian tigers. Our study can be used as a guideline for developing an AIMs panel for the management of other endangered species where obtaining whole genome sequences are difficult.

Linking genetic, morphological, and behavioural divergence between inland island and mainland deer mice

The island syndrome hypothesis (ISH) stipulates that, as a result of local selection pressures and restricted gene flow, individuals from island populations should differ from individuals within mainland populations. Specifically, island populations are predicted to contain individuals that are larger, less aggressive, more sociable, and that invest more in their offspring. To date, tests of the ISH have mainly compared oceanic islands to continental sites, and rarely smaller spatial scales such as inland watersheds. Here, using a novel set of genome-wide SNP markers in wild deer mice (Peromyscus maniculatus) we conducted a genomic assessment of predictions underlying the ISH in an inland riverine island system: analysing island-mainland population structure, and quantifying heritability of phenotypes thought to underlie the ISH. We found clear genomic differentiation between the island and mainland populations and moderate to high marker-based heritability estimates for overall variation in traits previously found to differ in line with the ISH between mainland and island locations. F_ST outlier analyses highlighted 12 loci associated with differentiation between mainland and island populations. Together these results suggest that the island populations examined are on independent evolutionary trajectories, the traits considered have a genetic basis (rather than phenotypic variation being solely due to phenotypic plasticity). Coupled with the previous results showing significant phenotypic differentiation between the island and mainland groups in this system, this study suggests that the ISH can hold even on a small spatial scale.

Comparative genomics and selection analysis of Yeonsan Ogye black chicken with whole-genome sequencing

Yeonsan Ogye (OGYE; Gallus gallus domesticus) is a rare indigenous chicken breed that inhabits the Korean Peninsula. This breed has completely black coloring, including plumage, skin, eyes, beak, and internal organs. Despite these unique morphological characteristics, the population of OGYE has declined without in-depth research into their genome research. Therefore, this study aimed to compare the whole genome of OGYE to 12 other chicken populations, including ancestral breed, commercial breeds, Chinese indigenous breeds, and Korean native chickens. We focused on revealing the selection signature of OGYE, which has occurred through environmental pressures in the Korean Peninsula. Genome-wide selection analysis has identified local adaptation traits, such as egg development, that contribute to fetal viability and innate immune response to prevent viral and microbes infection in OGYE. In particular, SPP1 (Secreted Phosphoprotein 1), HSP90AA1 (Heat Shock Protein 90 Alpha Family Class A Member 1), and P2RX4 (Purinergic Receptor P2X 4) could have considerable involvement in egg development and RNASEL (Ribonuclease L), BRIP1 (BRCA1 Interacting Protein C-terminal Helicase 1), and TLR4 (Toll-Like Receptor 4) are crucial for the determination of the innate immune response. This study revealed the unique genetic diversity of OGYE at the genome-wide level. Furthermore, we emphasized the sustainable management of genetic resources and formulated breeding strategies for livestock on the Korean Peninsula.