Reduced Representation Sequencing Research Articles

Improve-RRBS: a novel tool to correct the 3’ trimming of reduced representation sequencing reads

Abstract Motivation Reduced Representation Bisulfite Sequencing (RRBS) is a popular approach to determine DNA methylation of the CpG-rich regions of the genome. However, we observed that false positive differentially methylated sites (DMS) are also identified using the standard computational analysis. Results During RRBS library preparation the MspI digested DNA undergo end-repair by a cytosine at the 3’ end of the fragments. After sequencing, Trim Galore cuts these end-repaired nucleotides. However, Trim Galore fails to detect end-repair when it overlaps with the 3’ end of the sequencing reads. We found that these non-trimmed cytosines bias methylation calling, thus can identify DMS erroneously. To circumvent this problem, we developed improve-RRBS, which efficiently identifies and hides these cytosines from methylation calling with a false positive rate of maximum 0.5%. To test improve-RRBS, we investigated four datasets from four laboratories and two different species. We found non-trimmed 3’ cytosines in all datasets analyzed and as much as > 50% of false positive DMS under certain conditions. By applying improve-RRBS, these DMS completely disappeared from all comparisons. Availability improve-RRBS is a freely available python package https://pypi.org/project/iRRBS/ or https://github.com/fothia/improve-RRBS to be implemented in RRBS pipelines. Supplementary information Supplementary data are available at Bioinformatics Advances online.

Maize Kernel-Associated Metagenomes Reveal Potential Microbe–Microbe Interactions that Underlie Fusarium Ear Rot Disease

As an alternative to host resistance, transgenic expression of entomocidal and antimicrobial proteins from Bacillus thuringiensis ( Bt) in maize can mitigate Fusarium ear rot (FER). This study evaluated FER in Bt and conventional maize and the role of microbes in the kernel-associated metagenome using quantitative reduced representation sequencing. Our results revealed significant differences in FER severity across environments and varieties and between inoculation treatments. The lower FER scores of conventional maize Spectrum 6416 relative to other varieties highlighted resistant alleles in maize germplasm, whereas strong correlations indicated FER-induced yield loss. Mitigation of FER by transgenes was validated by about threefold enrichment of Fusarium verticillioides ( Fv) postinoculation compared with nonsignificant Fv enrichment in conventional maize. Although the major causal pathogen of FER, Fv, was the most abundant species in the metagenomes ( r = 0.41 to 0.49), a similar degree of correlation was observed between FER and several Fusarium spp. ( r = 0.2 to 0.56). The potential FER-suppressing properties of Talaromyces stipitatus and Ustilago maydis were indicated by negative correlations with FER ( r = –0.22 to –0.42), Fv, and some Fusarium spp. The more FER-resistant varieties consistently enriched for potential FER-suppressing Burkholderia cenocepacia (negatively correlated with Fv). This suggests host genetic background-dependent recruitment of beneficial microbes that suppress pathogens and that microbe–microbe interactions play a role in FER severity. Quantitative and species/strain-level metagenomic profiles hold promise for identifying robust disease-suppressing microbes and microbes that act in synergy with pathogens and for developing holobiont-aware breeding strategies that account for host–microbiome coevolution and host genotype, microbiome/metagenome, and environment interactions. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Readsynth: short-read simulation for consideration of composition-biases in reduced metagenome sequencing approaches

BackgroundThe application of reduced metagenomic sequencing approaches holds promise as a middle ground between targeted amplicon sequencing and whole metagenome sequencing approaches but has not been widely adopted as a technique. A major barrier to adoption is the lack of read simulation software built to handle characteristic features of these novel approaches. Reduced metagenomic sequencing (RMS) produces unique patterns of fragmentation per genome that are sensitive to restriction enzyme choice, and the non-uniform size selection of these fragments may introduce novel challenges to taxonomic assignment as well as relative abundance estimates.ResultsThrough the development and application of simulation software, readsynth, we compare simulated metagenomic sequencing libraries with existing RMS data to assess the influence of multiple library preparation and sequencing steps on downstream analytical results. Based on read depth per position, readsynth achieved 0.79 Pearson’s correlation and 0.94 Spearman’s correlation to these benchmarks. Application of a novel estimation approach, fixed length taxonomic ratios, improved quantification accuracy of simulated human gut microbial communities when compared to estimates of mean or median coverage.ConclusionsWe investigate the possible strengths and weaknesses of applying the RMS technique to profiling microbial communities via simulations with readsynth. The choice of restriction enzymes and size selection steps in library prep are non-trivial decisions that bias downstream profiling and quantification. The simulations investigated in this study illustrate the possible limits of preparing metagenomic libraries with a reduced representation sequencing approach, but also allow for the development of strategies for producing and handling the sequence data produced by this promising application.

Metagenome-enabled models improve genomic predictive ability and identification of herbivory-limiting genes in sweetpotato

Abstract Plant-insect interactions are often influenced by host-/insect-associated metagenomic community members. Relative abundance of insects and the microbes that modulate their interactions were obtained from sweetpotato (Ipomoea batatas) leaf-associated metagenomes using quantitative reduced representation sequencing and strain/species level profiling with the Qmatey software. Positive correlations were found between whitefly (Bemisia tabaci) and its endosymbionts (Candidatus Hamiltonella defensa, Candidatus Portiera aleyrodidarum, and Rickettsia spp.) and negative correlations with nitrogen-fixing bacteria that implicate nitric oxide in sweetpotato-whitefly interaction. Genome-wide associations using 252,975 dosage-based markers, and metagenomes as a covariate to reduce false positive rates, implicated ethylene and cell wall modification in sweetpotato-whitefly interaction. The predictive abilities (PA) for whitefly and Ocypus olens abundance were high in both populations (68-69% and 33.3-35.8%, respectively, and 69.9% for Frankliniella occidentalis). The metagBLUP (gBLUP) prediction model, which fits the background metagenome-based Cao dissimilarity matrix instead of the marker-based relationship matrix (G-matrix), revealed moderate PA (35.3-49.1%) except for O. olens (3-10.1%). Significant gain in PA after modeling the metagenome as a covariate (gGBLUP, ≤11%) confirms quantification accuracy and that the metagenome modulates phenotypic expression and might account for the missing heritability problem. Significant gains in PA were also revealed after fitting allele dosage (≤17.4%) and dominance effects (≤4.6%). Pseudo-diploidized genotype data underperformed for dominance models. Including segregation distorted loci (SDL) increased PA by 6-17.1%, suggesting traits associated with fitness cost might benefit from the inclusion of SDL. Our findings confirm the holobiont theory of host-metagenome co-evolution and underscore its potential for breeding within the context of GxGxE interactions.

Genome composition and GC content influence loci distribution in reduced representation genomic studies

BackgroundGenomic architecture is a key evolutionary trait for living organisms. Due to multiple complex adaptive and neutral forces which impose evolutionary pressures on genomes, there is a huge variability of genomic features. However, their variability and the extent to which genomic content determines the distribution of recovered loci in reduced representation sequencing studies is largely unexplored.ResultsHere, by using 80 genome assemblies, we observed that whereas plants primarily increase their genome size by expanding their intergenic regions, animals expand both intergenic and intronic regions, although the expansion patterns differ between deuterostomes and protostomes. Loci mapping in introns, exons, and intergenic categories obtained by in silico digestion using 2b-enzymes are positively correlated with the percentage of these regions in the corresponding genomes, suggesting that loci distribution mostly mirrors genomic architecture of the selected taxon. However, exonic regions showed a significant enrichment of loci in all groups regardless of the used enzyme. Moreover, when using selective adaptors to obtain a secondarily reduced loci dataset, the percentage and distribution of retained loci also varied. Adaptors with G/C terminals recovered a lower percentage of selected loci, with a further enrichment of exonic regions, while adaptors with A/T terminals retained a higher percentage of loci and slightly selected more intronic regions than expected.ConclusionsOur results highlight how genome composition, genome GC content, RAD enzyme choice and use of base-selective adaptors influence reduced genome representation techniques. This is important to acknowledge in population and conservation genomic studies, as it determines the abundance and distribution of loci.

Impacts of Quaternary climatic changes on the diversification of riverine cichlids in the lower Congo River.

Climatic and geomorphological changes during the Quaternary period impacted global patterns of speciation and diversification across a wide range of taxa, but few studies have examined these effects on African riverine fishes. The lower Congo River is an excellent natural laboratory for understanding complex speciation and population diversification processes as it is hydrologically extremely dynamic and recognized as a continental hotspot of diversity harboring many narrowly endemic species. A previous study using genome-wide SNP data highlighted the importance of dynamic hydrological regimes to the diversification and speciation in lower Congo River cichlids. However, historical climate and hydrological changes (e.g., reduced river discharge during extended dry periods) have likely also influenced ichthyofaunal diversification processes in this system. The lower Congo River offers a unique opportunity to study climate-driven changes in river discharge, given the massive volume of water from the entire Congo basin flowing through this short stretch of the river. Here, we, for the first time, investigate the impacts of paleoclimatic factors on ichthyofaunal diversification in this system by inferring divergence times and modeling patterns of gene flow in four endemic lamprologine cichlids, including the blind cichlid, Lamprologus lethops. Our results suggest that Quaternary climate changes associated with river discharge fluctuations may have impacted the diversification of species along the system. Our study, using reduced representation sequencing (2RADseq), indicates that the lower Congo River lamprologines emerged during the Early-Middle Pleistocene transition, characterized as one of the earth's major climatic transformation periods. Modeling results suggest that gene flow across populations and between species was not constant but occurred in temporally constrained pulses. We show that these results correlate with glacial-interglacial fluctuations. The current hyper-diverse fish assemblages of the lower Congo River riverscape likely reflect the synergistic effects of multiple drivers fueling complex evolutionary processes through time.

The origin, connectivity, and individual specialization of island wolves after deer extirpation.

Wolves are assumed to be ungulate obligates, however, a recently described pack on Pleasant Island, Alaska USA, is persisting on sea otters and other marine resources without ungulate prey, violating this long-held assumption. We address questions about these wolves regarding their origin and fate, degree of isolation, risk of inbreeding depression, and diet specialization by individual and sex. We applied DNA metabarcoding and genotyping by amplicon sequencing using 957 scats collected from 2016 to 2022, and reduced representation sequencing of tissue samples to establish a detailed understanding of Pleasant Island wolf ecology and compare them with adjacent mainland wolves. Dietary overlap was higher among individual wolves on Pleasant Island (Pianka's index mean 0.95 ± 0.03) compared to mainland wolves (0.70 ± 0.21). The individual diets of island wolves were dominated by sea otter, ranging from 40.6% to 63.2% weighted percent of occurrence (wPOO) (mean 55.5 ± 8.7). In contrast, individual mainland wolves primarily fed on ungulates (42.2 ± 21.3) or voles during a population outbreak (31.2 ± 23.2). We traced the origin of the Pleasant Island pack to a mainland pair that colonized around 2013 and produced several litters. After this breeding pair was killed, their female offspring and an immigrant male became the new breeders in 2019. We detected 20 individuals of which 8 (40%) were trapped and killed while two died of natural causes during the 6-year study. Except for the new breeding male, the pedigree analysis and genotype results showed no additional movement to or from the island, indicating limited dispersal but no evidence of inbreeding. Our findings suggest wolves exhibit more flexible foraging behavior than previously believed, and hunting strategies can substantially differ between individuals within or between packs. Nevertheless, anthropogenic and natural mortality combined with limited connectivity to the mainland may inhibit the continued persistence of Pleasant Island wolves.

Ecological characteristics explain neutral genetic variation of three coastal sparrow species.

Eco-phylogeographic approaches to comparative population genetic analyses allow for the inclusion of intrinsic influences as drivers of intraspecific genetic structure. This insight into microevolutionary processes, including changes within a species or lineage, provides better mechanistic understanding of species-specific interactions and enables predictions of evolutionary responses to environmental change. In this study, we used single nucleotide polymorphisms (SNPs) identified from reduced representation sequencing to compare neutral population structure, isolation by distance (IBD), genetic diversity and effective population size (Ne) across three closely related and co-distributed saltmarsh sparrow species differing along a specialization gradient-Nelson's (Ammospiza nelsoni subvirgata), saltmarsh (A. caudacuta) and seaside sparrows (A. maritima maritima). Using an eco-phylogeographic lens within a conservation management context, we tested predictions about species' degree of evolutionary history and ecological specialization to tidal marshes, habitat, current distribution and population status on population genetic metrics. Population structure differed among the species consistent with their current distribution and habitat factors, rather than degree of ecological specialization: seaside sparrows were panmictic, saltmarsh sparrows showed hierarchical structure and Nelson's sparrows were differentiated into multiple, genetically distinct populations. Neutral population genetic theory and demographic/evolutionary history predicted patterns of genetic diversity and Ne rather than degree of ecological specialization. Patterns of population variation and evolutionary distinctiveness (Shapely metric) suggest different conservation measures for long-term persistence and evolutionary potential in each species. Our findings contribute to a broader understanding of the complex factors influencing genetic variation, beyond specialist-generalist status and support the role of an eco-phylogeographic approach in population and conservation genetics.

Chromosome-scale genome assembly of Poa trivialis and population genomics reveal widespread gene flow in a cool-season grass seed production system.

Poa trivialis (L.) is a cool-season grass species found in various environments worldwide. In addition to being a desired turfgrass species, it is a common weed of agricultural systems and natural areas. As a weed, it is an important contaminant of commercial cool-season grass seed lots, resulting in widespread gene flow facilitated by human activities and causing significant economic losses to farmers. To better understand and manage infestations, we assembled and annotated a haploid genome of P. trivialis and studied troublesome field populations from Oregon, the largest cool-season grass seed producing region in the United States. The genome assembly resulted in 1.35 Gb of DNA sequence distributed among seven chromosome-scale scaffolds, revealing a high content of transposable elements, conserved synteny with Poa annua, and a close relationship with other C3 grasses. A reduced-representation sequencing analysis of field populations revealed limited genetic diversity and suggested potential gene flow and human-assisted dispersal in the region. The genetic resources and insights into P. trivialis provided by this study will improve weed management strategies and enable the development of molecular detection tests for contaminated seed lots to limit seed-mediated gene flow. These resources should also be beneficial for turfgrass breeders seeking to improve desirable traits of commercial P. trivialis varieties and help to guide breeding efforts in other crops to enhance the resiliency of agricultural ecosystems under climate change. Significance Statement: The chromosome-scale assembly of Poa trivialis and population genomic analyses provide crucial insights into the gene flow of weedy populations in agricultural systems and contribute a valuable genomic resource for the plant science community.

Remnant kenngoor (Phascogale calura) retain genetic connectivity and genetic diversity in a highly fragmented landscape

Kenngoor (Phascogale calura) persist in < 1% of their original distribution, occupying highly fragmented remnant habitat in south-west Western Australia, with very little known of the genetic diversity of the remaining wild populations. Recently, the species has been translocated to managed reserves to improve its conservation. Understanding genetic structure and patterns of genetic diversity is crucial to inform conservation translocations for species recovery. This study aims to (1) assess genetic structure and genetic diversity across remaining wild locations, (2) assess long-term genetic outcomes of a mixed-source wild-to-wild translocation, and (3) estimate global effective population size. We genotyped 209 samples from 13 locations of fragmented remnant habitat using reduced representation sequencing. An isolation by distance model best explained genetic structure across the survey areas, with evidence of fine scale divergence of two northern locations. Allelic richness and autosomal heterozygosity measures indicated that diversity is spread uniformly across locations, and no locations showed signs of inbreeding or strong genetic drift. The mixed-source translocation has retained the diversity of the wider species ten years post-translocation. Overall, our results suggest that connectivity between survey areas has largely been maintained and that no location has substantially lower genetic diversity, despite the highly fragmented nature of remnant kenngoor habitat. Future translocations should aim to represent a mixture of genetically divergent locations to maintain the diversity present at the species level. Ongoing conservation management will be required to ensure the long-term viability of the species in this fragmented landscape.

Evolutionary stamps for adaptation traced in Cervus nippon genome using reduced representation sequencing

Evolutionary stamps for adaptation traced in Cervus nippon genome using reduced representation sequencing

Algal symbiont genera but not coral host genotypes correlate to stony coral tissue loss disease susceptibility among Orbicella faveolata colonies in South Florida

Stony coral tissue loss disease (SCTLD) has spread throughout the entirety of Florida’s Coral Reef (FCR) and across the Caribbean, impacting at least 30 coral species. The threatened hermatypic coral, Orbicella faveolata, demonstrates intraspecific variation in SCTLD affectedness with some colonies experiencing chronic disease lesions, while other nearby O. faveolata colonies appear unaffected with no disease signs over long monitoring periods. This study evaluated potential genotypic underpinnings of variable disease responses to SCTLD by monitoring and sampling 90 O. faveolata colonies from southeast Florida and the lower Florida Keys. High resolution analyses of &amp;gt;11,000 single nucleotide polymorphisms (SNPs) generated from 2bRAD sequencing indicated there were no SNP loci or genetic lineages significantly associated with O. faveolata SCTLD affectedness. Genotypic differences may still contribute to SCTLD susceptibility; however, these differences were not captured using this reduced representation sequencing approach. Algal symbiont community structure characterized from 2bRAD data revealed that the presence of Durusdinium spp. corresponded with SCTLD-affected colonies as compared to unaffected colonies, suggesting that algal symbiont community make-up may play some role in SCTLD resistance. Data generated by this study will be combined with complementary molecular and physiological approaches to further investigate the complex drivers of intraspecific SCTLD susceptibility and resilience.

Identification of Novel Induced Mutations in Seed and Vegetatively Propagated Plants from Reduced Representation or Whole Genome Sequencing Data.

Treatment of plants with chemical mutagens results primarily in the production of novel single nucleotide variants. Mutagenesis is a mostly random process and as such plants derived from mutagenesis of different seeds or in vitro material are expected to accumulate different mutations. An important step in the creation of a mutant population for forward or reverse genetics is the choice of treatment conditions (e.g., dosage) such that sufficient mutations accumulate while not adversely affecting propagation of the plant. DNA sequencing provides a quick method to evaluate the effect of different treatment conditions and their effect on the density and spectrum of accumulated mutations. Whole genome sequencing or reduced representation sequencing is carried out followed by mapping to a reference genome and production of a Variant Call Format (VCF) file. We provide here a method for generating a multi-sample VCF from mutagenized plants and describe a new tool to streamline the process of recovering unique induced mutations and determining their possible effect on gene function.

Genetic Diversity Assessment in Plants from Reduced Representation Sequencing Data.

Genetic diversity refers to the variety of genetic traits within a population or a species. It is an essential aspect of both plant ecology and plant breeding because it contributes to the adaptability, survival, and resilience of populations in changing environments. This chapter outlines a pipeline for estimating genetic diversity statistics from reduced representation or whole genome sequencing data. The pipeline involves obtaining DNA sequence reads, mapping the corresponding reads to a reference genome, calling variants from the alignments, and generating an unbiased estimation of nucleotide diversity and divergence between populations. The pipeline is suitable for single-end Illumina reads and can be adjusted for paired-end reads. The resulting pipeline provides a comprehensive approach for aligning and analyzing sequencing data to estimate genetic diversity.

MCPtaggR: R package for accurate genotype calling in reduced representation sequencing data by eliminating error-prone markers based on genome comparison.

Reduced representation sequencing (RRS) offers cost-effective, high-throughput genotyping platforms such as genotyping-by-sequencing (GBS). RRS reads are typically mapped onto a reference genome. However, mapping reads harbouring mismatches against the reference can potentially result in mismapping and biased mapping, leading to the detection of error-prone markers that provide incorrect genotype information. We established a genotype-calling pipeline named mappable collinear polymorphic tag genotyping (MCPtagg) to achieve accurate genotyping by eliminating error-prone markers. MCPtagg was designed for the RRS-based genotyping of a population derived from a biparental cross. The MCPtagg pipeline filters out error-prone markers prior to genotype calling based on marker collinearity information obtained by comparing the genome sequences of the parents of a population to be genotyped. A performance evaluation on real GBS data from a rice F2 population confirmed its effectiveness. Furthermore, our performance test using a genome assembly that was obtained by genome sequence polishing on an available genome assembly suggests that our pipeline performs well with converted genomes, rather than necessitating de novo assembly. This demonstrates its flexibility and scalability. The R package, MCPtaggR, was developed to provide functions for the pipeline and is available at https://github.com/tomoyukif/MCPtaggR.

Characterization of the Ruminal Microbiome of Water Buffaloes (Bubalus bubalis) Kept in Different Ecosystems in the Eastern Amazon.

Increasing the efficiency of rumen fermentation is one of the main ways to maximize the production of ruminants. It is therefore important to understand the ruminal microbiome, as well as environmental influences on that community. However, there are no studies that describe the ruminal microbiota in buffaloes in the Amazon. The objective of this study was to characterize the rumen microbiome of the water buffalo (Bubalus bubalis) in the eastern Amazon in the dry and rainy seasons in three grazing ecosystems: Baixo Amazonas (BA), Continente do Pará (CP), Ilha do Marajó (IM), and in a confinement system: Tomé-Açu (TA). Seventy-one crossbred male buffaloes (Murrah × Mediterranean) were used, aged between 24 and 36 months, with an average weight of 432 kg in the rainy season and 409 kg in the dry season, and fed on native or cultivated pastures. In the confinement system, the feed consisted of sorghum silage, soybean meal, wet sorghum premix, and commercial feed. Samples of the diet from each ecosystem were collected for bromatological analysis. The collections of ruminal content were carried out in slaughterhouses, with the rumen completely emptied and homogenized, the solid and liquid fractions separated, and the ruminal pH measured. DNA was extracted from the rumen samples, then sequenced using Restriction Enzyme Reduced Representation Sequencing. The taxonomic composition was largely similar between ecosystems. All 61 genera in the reference database were recognized, including members of the domains Bacteria and Archaea. The abundance of 23 bacterial genera differed significantly (p < 0.01) between the Tomé-Açu confinement and other ecosystems. Bacillus, Ruminococcus, and Bacteroides had lower abundance in samples from the Tomé-Açu system. Among the Archaea, the genus Methanomicrobium was less abundant in Tomé-Açu, while Methanosarcina was more abundant. There was a difference caused by all evaluated factors, but the diet (available or offered) was what most influenced the ruminal microbiota.

Population genomic structure of a widespread, urban-dwelling mammal: The eastern grey squirrel (Sciurus carolinensis).

Urbanization is a persistent and widespread driver of global environmental change, potentially shaping evolutionary processes due to genetic drift and reduced gene flow in cities induced by habitat fragmentation and small population sizes. We tested this prediction for the eastern grey squirrel (Sciurus carolinensis), a common and conspicuous forest-dwelling rodent, by obtaining 44K SNPs using reduced representation sequencing (ddRAD) for 403 individuals sampled across the species' native range in eastern North America. We observed moderate levels of genetic diversity, low levels of inbreeding, and only a modest signal of isolation-by-distance. Clustering and migration analyses show that estimated levels of migration and genetic connectivity were higher than expected across cities and forested areas, specifically within the eastern portion of the species' range dominated by urbanization, and genetic connectivity was less than expected within the western range where the landscape is fragmented by agriculture. Landscape genetic methods revealed greater gene flow among individual squirrels in forested regions, which likely provide abundant food and shelter for squirrels. Although gene flow appears to be higher in areas with more tree cover, only slight discontinuities in gene flow suggest eastern grey squirrels have maintained connected populations across urban areas in all but the most heavily fragmented agricultural landscapes. Our results suggest urbanization shapes biological evolution in wildlife species depending strongly on the composition and habitability of the landscape matrix surrounding urban areas.

Genomic signals of local adaptation across climatically heterogenous habitats in an invasive tropical fruit fly (Bactrocera tryoni)

Local adaptation plays a key role in the successful establishment of pest populations in new environments by enabling them to tolerate novel biotic and abiotic conditions experienced outside their native range. However, the genomic underpinnings of such adaptive responses remain unclear, especially for agriculturally important pests. We investigated population genomic signatures in the tropical/subtropical Queensland fruit fly, Bactrocera tryoni, which has an expanded range encompassing temperate and arid zones in Australia, and tropical zones in the Pacific Islands. Using reduced representation sequencing data from 28 populations, we detected allele frequency shifts associated with the native/invasive status of populations and identified environmental factors that have likely driven population differentiation. We also determined that precipitation, temperature, and geographic variables explain allelic shifts across the distribution range of B. tryoni. We found spatial heterogeneity in signatures of local adaptation across various climatic conditions in invaded areas. Specifically, disjunct invasive populations in the tropical Pacific Islands and arid zones of Australia were characterised by multiple significantly differentiated single nucleotide polymorphisms (SNPs), some of which were associated with genes with well-understood function in environmental stress (e.g., heat and desiccation) response. However, invasive populations in southeast Australian temperate zones showed higher gene flow with the native range and lacked a strong local adaptive signal. These results suggest that population connectivity with the native range has differentially affected local adaptive patterns in different invasive populations. Overall, our findings provide insights into the evolutionary underpinnings of invasion success of an important horticultural pest in climatically distinct environments.

Population genomic diversity and structure in the golden bandicoot: a history of isolation, extirpation, and conservation

Using genetic information to develop and implement conservation programs is vital for maintaining biodiversity and ecosystem resilience. Evaluation of the genetic variability within and among remnant populations can inform management of both natural and translocated populations to maximise species’ adaptive potential, mitigate negative impacts of inbreeding, and subsequently minimise risk of extinction. Here we use reduced representation sequencing to undertake a genetic assessment of the golden bandicoot (Isoodon auratus), a threatened marsupial endemic to Australia. The currently recognised taxon consists of three subspecies distributed among multiple natural and translocated populations. After confirming the genetic distinctiveness of I. auratus from two closely related taxa, I. fusciventer and I. macrourus, we identified four genetic clusters within I. auratus. These clusters exhibited substantial genetic differentiation (pairwise FST values ranging from 0.18 to 0.65, pairwise DXY ranging from 0.1 to 0.168), reflecting long-term isolation of some populations on offshore islands and the influence of genetic drift. Mainland natural populations in the Kimberley region had the highest genetic diversity and the largest contribution to overall allelic and gene diversity compared to both natural and translocated island populations. A population translocated to Guluwuru Island in the Northern Territory had the lowest genetic diversity. Our data suggest that island populations can appear genetically unique due to genetic drift and this needs to be taken into account when considering genetic diversity in conservation efforts to maintain overall genetic diversity of the species. We effectively demonstrate how genomic information can guide practical conservation planning, especially when declining species are represented by multiple isolated populations.

Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

BackgroundProducing animal protein while reducing the animal’s impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible.ResultsMetagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets.ConclusionsVariation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual’s future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting.