Molecular Ecology Resources

Tang, Cheng‐Yi; Li, Song; Wang, Yun‐Tong; Wang, Xi

doi: 10.1111/1755-0998.13104pmid: 31625679

Boraginales (the forget‐me‐not order) is a core group within the lamiids clade. However, until now, no genome from Boraginales has been reported, and published transcriptomes are also rare. Here, we report the first Boraginales species de novo genome (i.e. Echium plantagineum genome) and seven other Boraginales species transcriptomes to probe three issues: (i) Boraginales' phylogenetic position within the lamiids clade; (ii) potential whole genome duplications (WGDs) in Boraginales; and (iii) candidate key enzyme genes in the alkannin/shikonin core pathway. The results showed that: (i) Boraginales was most probably closer to the Solanales/Gentianales clade than the Lamiales clade, at least based on the single‐copy orthologous genes from genome/transcriptome data; (ii) after the gamma (γ) event, Boraginaceae (classified into the Boraginales I clade) probably underwent at least two rounds of WGD, whereas Heliotropiaceae and Ehretiaceae (classified into the Boraginales II clade) probably underwent only one round of WGD; and (iii) several candidate key enzyme genes in the alkannin/shikonin core pathway were inferred, e.g. genes corresponding to geranyl cyclase, naphthol hydroxylase and O‐acyl transferase.

Bragg, Jason G.; Cuneo, Peter; Sherieff, Ahamad; Rossetto, Maurizio

doi: 10.1111/1755-0998.13074pmid: 31448539

Translocations of threatened species can reduce the risk of extinction from a catastrophic event. For plants, translocation consists of moving individuals, seeds, or cuttings from a native (source) population to a new site. Ideally a translocation population would be genetically diverse and consist of fit founding individuals. In practice, there are challenges to designing such a population, including constraints on the availability of material, and tradeoffs between different goals. Here, we present an approach for designing a translocation population that identifies sets of founders that are optimized according to multiple criteria (e.g., genetic diversity), while also conforming to constraints on the representation of different founders (e.g., propagation success). It uses flexible inputs, including SNP genotypes, matrices of similarity between individuals, and vectors of phenotype data. We apply the approach to a critically endangered plant, Hibbertia puberula subsp. glabrescens (Dilleniaceae), which was genotyped at thousands of SNP loci. The goals of minimizing genetic similarity among the founding individuals and maximizing genetic diversity were largely complementary: populations optimized for one of these criteria were near‐optimal for the other. We also performed analyses in which we minimized genetic similarity among founding individuals while imposing selection (against hypothetical deleterious alleles, and against undesirable phenotypes, respectively), and here characterized sharp tradeoffs. This was useful in allowing the benefits of selection to be weighed against costs in terms of genetic similarity. In summary, we present an approach for designing a translocation population that allows flexible inputs, the imposition of realistic constraints, and examination of conflicting goals.

Schmidt, Danielle A.; Campbell, Nathan R.; Govindarajulu, Purnima; Larsen, Karl W.; Russello, Michael A.

doi: 10.1111/1755-0998.13090pmid: 31483931

Minimally invasive sampling (MIS) is widespread in wildlife studies; however, its utility for massively parallel DNA sequencing (MPS) is limited. Poor sample quality and contamination by exogenous DNA can make MIS challenging to use with modern genotyping‐by‐sequencing approaches, which have been traditionally developed for high‐quality DNA sources. Given that MIS is often more appropriate in many contexts, there is a need to make such samples practical for harnessing MPS. Here, we test the ability for Genotyping‐in‐Thousands by sequencing (GT‐seq), a multiplex amplicon sequencing approach, to effectively genotype minimally invasive cloacal DNA samples collected from the Western Rattlesnake (Crotalus oreganus), a threatened species in British Columbia, Canada. As there was no previous genetic information for this species, an optimized panel of 362 SNPs was selected for use with GT‐seq from a de novo restriction site‐associated DNA sequencing (RADseq) assembly. Comparisons of genotypes generated within and among RADseq and GT‐seq for the same individuals found low rates of genotyping error (GT‐seq: 0.50%; RADseq: 0.80%) and discordance (2.57%), the latter likely due to the different genotype calling models employed. GT‐seq mean genotype discordance between blood and cloacal swab samples collected from the same individuals was also minimal (1.37%). Estimates of population diversity parameters were similar across GT‐seq and RADseq data sets, as were inferred patterns of population structure. Overall, GT‐seq can be effectively applied to low‐quality DNA samples, minimizing the inefficiencies presented by exogenous DNA typically found in minimally invasive samples and continuing the expansion of molecular ecology and conservation genetics in the genomics era.

Cao, Min; Xu, Kuipeng; Yu, Xinzi; Bi, Guiqi; Liu, Yang; Kong, Fanna; Sun, Peipei; Tang, Xianghai; Du, Guoying; Ge, Yuan; Wang, Dongmei; Mao, Yunxiang

doi: 10.1111/1755-0998.13102pmid: 31600851

Winiarski, Kristopher J.; Peterman, William E.; Whiteley, Andrew R.; McGarigal, Kevin

doi: 10.1111/1755-0998.13089pmid: 31484210

The importance of assessing spatial data at multiple scales when modelling species–environment relationships has been highlighted by several empirical studies. However, no landscape genetics studies have optimized landscape resistance surfaces by evaluating relevant spatial predictors at multiple spatial scales. Here, we model multiscale/layer landscape resistance surfaces to estimate resistance to inferred gene flow for two vernal pool breeding salamander species, spotted (Ambystoma maculatum) and marbled (A. opacum) salamanders. Multiscale resistance surface models outperformed spatial layers modelled at their original spatial scale. A resistance surface with forest land cover at a 500‐m Gaussian kernel bandwidth and normalized vegetation index at a 100‐m Gaussian kernel bandwidth was the top optimized resistance surface for A. maculatum, while a resistance surface with traffic rate and topographic curvature, both at a 500‐m Gaussian kernel bandwidth, was the top optimized resistance surface for A. opacum. Species‐specific resistant kernels were fit at all vernal pools in our study area with the optimized multiscale/layer resistance surface controlling kernel spread. Vernal pools were then evaluated and scored based on surrounding upland habitat (local score) and connectivity with other vernal pools on the landscape, with resistant kernels driving vernal pool connectivity scores. As expected, vernal pools that scored highest were in areas within forested habitats and with high vernal pool densities and low species‐specific landscape resistance. Our findings highlight the success of using a novel analytical approach in a multiscale framework with applications beyond vernal pool amphibian conservation.

Zhang, Lijuan; Li, Song; Luo, Junyu; Du, Pei; Wu, Linke; Li, Yarong; Zhu, Xiangzhen; Wang, Li; Zhang, Shuai; Cui, Jinjie

doi: 10.1111/1755-0998.13100pmid: 31599108

The ladybird beetle Propylea japonica is an important natural enemy in agro‐ecological systems. Studies on the strong tolerance of P. japonica to high temperatures and insecticides, and its population and phenotype diversity have recently increased. However, abundant genome resources for obtaining insights into stress‐resistance mechanisms and genetic intra‐species diversity for P. japonica are lacking. Here, we constructed the P. japonica genome maps using Pacific Bioscience (PacBio) and Illumina sequencing technologies. The genome size was 850.90 Mb with a contig N50 of 813.13 kb. The Hi‐C sequence data were used to upgrade draft genome assemblies; 4,777 contigs were assembled to 10 chromosomes; and the final draft genome assembly was 803.93 Mb with a contig N50 of 813.98 kb and a scaffold N50 of 100.34 Mb. Approximately 495.38 Mb of repeated sequences was annotated. The 18,018 protein‐coding genes were predicted, of which 95.78% were functionally annotated, and 1,407 genes were species‐specific. The phylogenetic analysis showed that P. japonica diverged from the ancestor of Anoplophora glabripennis and Tribolium castaneum ~ 236.21 million years ago. We detected that some important gene families involved in detoxification of pesticides and tolerance to heat stress were expanded in P. japonica, especially cytochrome P450 and Hsp70 genes. Overall, the high‐quality draft genome sequence of P. japonica will provide invaluable resource for understanding the molecular mechanisms of stress resistance and will facilitate the research on population genetics, evolution and phylogeny of Coccinellidae. This genome will also provide new avenues for conserving the diversity of predator insects.

Ji, Yinqiu; Huotari, Tea; Roslin, Tomas; Schmidt, Niels Martin; Wang, Jiaxin; Yu, Douglas W.; Ovaskainen, Otso

doi: 10.1111/1755-0998.13057pmid: 31293086

The accurate quantification of eukaryotic species abundances from bulk samples remains a key challenge for community ecology and environmental biomonitoring. We resolve this challenge by combining shotgun sequencing, mapping to reference DNA barcodes or to mitogenomes, and three correction factors: (a) a percent‐coverage threshold to filter out false positives, (b) an internal‐standard DNA spike‐in to correct for stochasticity during sequencing, and (c) technical replicates to correct for stochasticity across sequencing runs. The SPIKEPIPE pipeline achieves a strikingly high accuracy of intraspecific abundance estimates (in terms of DNA mass) from samples of known composition (mapping to barcodes R2 = .93, mitogenomes R2 = .95) and a high repeatability across environmental‐sample replicates (barcodes R2 = .94, mitogenomes R2 = .93). As proof of concept, we sequence arthropod samples from the High Arctic, systematically collected over 17 years, detecting changes in species richness, species‐specific abundances, and phenology. SPIKEPIPE provides cost‐efficient and reliable quantification of eukaryotic communities.

Colicchio, Jack; Monnahan, Patrick J.; Wessinger, Carolyn A.; Brown, Keely; Kern, James Russell; Kelly, John K.

doi: 10.1111/1755-0998.13094pmid: 31519042

The estimation of outcrossing rates in hermaphroditic species has been a major focus in the evolutionary study of reproductive strategies, and is also essential for plant breeding and conservation. Surprisingly, genomics has thus far minimally influenced outcrossing rate studies. In this article, we generalize a Bayesian inference method (BORICE) to accommodate genomic data from multiple subpopulations of a species. As an empirical demonstration, BORICE is applied to 115 maternal families of Mimulus guttatus. The analysis shows that low‐level whole genome sequencing of parents and offspring is sufficient for individualized mating system estimation: 208 offspring (88.5%) were definitively called as outcrossed, 23 (9.8%) as selfed. After mating system parameters are established (each offspring as outcrossed or selfed and the inbreeding level of maternal plants), BORICE outputs posterior genotype probabilities for each SNP genomewide. Individual SNP calls are often burdened with considerable uncertainty and distilling information from closely linked sites (within genomic windows) can be a useful strategy. For the Mimulus data, principal components based on window statistics were sufficient to diagnose inversion polymorphisms and estimate their effects on spatial structure, phenotypic and fitness measures. More generally, mating system estimation with BORICE can set the stage for population and quantitative genomic analyses, particularly researchers collect phenotypic or fitness data from maternal individuals.

Cassin‐Sackett, Loren

doi: 10.1111/1755-0998.13122pmid: 31777170

Genomic technologies continue to shed light on important ecological and evolutionary questions. Nonetheless, these new tools are applied disproportionately in a small fraction of global biodiversity, partly because of technical challenges to studying highly diverse taxa that occur in low abundances in an environment (e.g., marine and microbial communities). As a result, our understanding of ecological and evolutionary processes lags in many taxa. In a From the Cover manuscript in this issue of Molecular Ecology Resources, Galen, Borner, Williamson, Witt, and Perkins (2020) present a novel approach for characterizing diversity that combines metatranscriptomics with rigorous bioinformatic processing to dramatically improve detection and identification of diverse, low‐abundance avian blood parasites. Their approach is an exciting application of available tools that increases our potential for a deeper understanding of diversity in other communities of low‐abundance, highly diverse taxa.

doi: 10.1111/1755-0998.13037pmid: N/A