Molecular Ecology Resources最新文献

{"title":"The accuracy of predicting maladaptation to new environments with genomic data.","authors":"Brandon M Lind, Katie E Lotterhos","doi":"10.1111/1755-0998.14008","DOIUrl":"https://doi.org/10.1111/1755-0998.14008","url":null,"abstract":"<p><p>Rapid environmental change poses unprecedented challenges to species persistence. To understand the extent that continued change could have, genomic offset methods have been used to forecast maladaptation of natural populations to future environmental change. However, while their use has become increasingly common, little is known regarding their predictive performance across a wide array of realistic and challenging scenarios. Here, we evaluate the performance of currently available offset methods (gradientForest, the Risk-Of-Non-Adaptedness, redundancy analysis with and without structure correction and LFMM2) using an extensive set of simulated data sets that vary demography, adaptive architecture and the number and spatial patterns of adaptive environments. For each data set, we train models using either all, adaptive or neutral marker sets and evaluate performance using in silico common gardens by correlating known fitness with projected offset. Using over 4,849,600 of such evaluations, we find that (1) method performance is largely due to the degree of local adaptation across the metapopulation (LA), (2) adaptive marker sets provide minimal performance advantages, (3) performance within the species range is variable across gardens and declines when offset models are trained using additional non-adaptive environments and (4) despite (1) performance declines more rapidly in globally novel climates (i.e. a climate without an analogue within the species range) for metapopulations with greater LA than lesser LA. We discuss the implications of these results for management, assisted gene flow and assisted migration.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":" ","pages":"e14008"},"PeriodicalIF":5.5,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142102711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Taxonomic and abundance biases affect the record of marine eukaryotic plankton communities in sediment DNA archives","authors":"Ngoc-Loi Nguyen,&nbsp;Joanna Pawłowska,&nbsp;Marek Zajaczkowski,&nbsp;Agnes K. M. Weiner,&nbsp;Tristan Cordier,&nbsp;Danielle M. Grant,&nbsp;Stijn De Schepper,&nbsp;Jan Pawłowski","doi":"10.1111/1755-0998.14014","DOIUrl":"10.1111/1755-0998.14014","url":null,"abstract":"<p>Environmental DNA (<i>e</i>DNA) preserved in marine sediments is increasingly being used to study past ecosystems. However, little is known about how accurately marine biodiversity is recorded in sediment <i>e</i>DNA archives, especially planktonic taxa. Here, we address this question by comparing eukaryotic diversity in 273 <i>e</i>DNA samples from three water depths and the surface sediments of 24 stations in the Nordic Seas. Analysis of 18S-V9 metabarcoding data reveals distinct eukaryotic assemblages between water and sediment <i>e</i>DNA. Only 40% of Amplicon Sequence Variants (ASVs) detected in water were also found in sediment <i>e</i>DNA. Remarkably, the ASVs shared between water and sediment accounted for 80% of total sequence reads suggesting that a large amount of plankton DNA is transported to the seafloor, predominantly from abundant phytoplankton taxa. However, not all plankton taxa were equally archived on the seafloor. The plankton DNA deposited in the sediments was dominated by diatoms and showed an underrepresentation of certain nano- and picoplankton taxa (Picozoa or Prymnesiophyceae). Our study offers the first insights into the patterns of plankton diversity recorded in sediment in relation to seasonality and spatial variability of environmental conditions in the Nordic Seas. Our results suggest that the genetic composition and structure of the plankton community vary considerably throughout the water column and differ from what accumulates in the sediment. Hence, the interpretation of sedimentary <i>e</i>DNA archives should take into account potential taxonomic and abundance biases when reconstructing past changes in marine biodiversity.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"24 8","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142071609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The answer, my friend, is blowin’ in the wind: Blow sampling provides a new dimension to whale population monitoring","authors":"Elena Valsecchi","doi":"10.1111/1755-0998.14012","DOIUrl":"10.1111/1755-0998.14012","url":null,"abstract":"<p>Marine mammals play a fundamental role in the functioning of healthy marine ecosystems and are important indicator species. Studying their biology, distributions, behaviour and health are still technically and logistically demanding for researchers. However, the efforts and commitment have not been in vain, since we are witnessing constant and exponential advancement in the study of these animals, thanks to technological progress in numerous fields. These include miniaturization and performance of biologger tags, which are equipped with sensors for measuring physiological parameters, hydrophones, accelerometers, time-depth records and spatial locations; the use of high throughput ‘Next Generation’ Sequencing to gain genetic information about communities and individual species from nucleic acids in environmental samples at miniscule concentrations; through, to the possibility of monitoring species with autonomous aerial and underwater vehicles. In parallel advances in computing and statistical modelling frameworks support the analysis of increasingly large and complex data sets. In this issue, O'Mahony et al. (2024) draw from at least two of these innovations: (a) the collection of biological material retrieved from large whales' blows using a modified drone and (b) the use of the samples to infer a wide spectrum of genetic information (both nuclear and mitochondrial) about the target animal/population. The methodology is not completely novel, but the study shows an impressive advancement in the amount of data obtained compared to preceding studies using the same approach. In the wake of these promising results, future perspectives are evaluated in relation to alternative sampling methodologies currently in use. It is possible to speculate that, in the next few years, the combination of non-invasive molecular profiling and enhanced drone technology (e.g. assembling increasingly smaller components, thus expanding capacity for autonomous operation) will open up perspectives that were unimaginable at the beginning of this millennium.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"24 8","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.14012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142071610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stability of environmental DNA methylation and its utility in tracing spawning in fish","authors":"Itsuki T. Hirayama,&nbsp;Luhan Wu,&nbsp;Toshifumi Minamoto","doi":"10.1111/1755-0998.14011","DOIUrl":"10.1111/1755-0998.14011","url":null,"abstract":"<p>The use of environmental DNA (eDNA) is becoming prevalent as a novel method of ecological monitoring. Although eDNA can provide critical information on the distribution and biomass of particular taxa, the DNA sequences of an organism remain unaltered throughout its existence, which complicates the accurate identification of crucial events, including spawning. Therefore, we examined DNA methylation as a novel source of information from eDNA, considering that the methylation patterns in eggs and sperm released during spawning differ from those of somatic tissues. Despite its potential applications, little is known about eDNA methylation, including its stability and methods for detection and quantification. Therefore, we conducted tank experiments and performed methylation analysis targeting 18S rDNA through bisulphite amplicon sequencing. In the target region, eDNA methylation was not affected by degradation and was equivalent to the methylation rate of genomic DNA from somatic tissues. Unmethylated DNA, abundant in the ovaries, was detected in the eDNA released during fish spawning. These results indicate that eDNA methylation is a stable signal reflecting targeted gene methylation and further demonstrate that germ cell-specific methylation patterns can be used as markers for detecting fish spawning.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"24 8","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142003203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-quality genome assemblies for nine non-model North American insect species representing six orders (Insecta: Coleoptera, Diptera, Hemiptera, Hymenoptera, Lepidoptera, Neuroptera)","authors":"Kimberly K. O. Walden,&nbsp;Yanghui Cao,&nbsp;Christopher J. Fields,&nbsp;Alvaro G. Hernandez,&nbsp;Gloria A. Rendon,&nbsp;Gene E. Robinson,&nbsp;Rachel K. Skinner,&nbsp;Jeffrey A. Stein,&nbsp;Christopher H. Dietrich","doi":"10.1111/1755-0998.14010","DOIUrl":"10.1111/1755-0998.14010","url":null,"abstract":"<p>Field-collected specimens were used to obtain nine high-quality genome assemblies from a total of 10 insect species native to prairies and savannas of central Illinois (USA): <i>Mellilla xanthometata</i> (Lepidoptera: Geometridae), <i>Stenolophus ochropezus</i> (Coleoptera: Carabidae), <i>Forcipata loca</i> (Hemiptera: Cicadellidae), <i>Coelinius</i> sp. (Hymenoptera: Braconidae), <i>Thaumatomyia glabra</i> (Diptera: Chloropidae), <i>Brachynemurus abdominalus</i> (Neuroptera: Myrmeleontidae), <i>Catonia carolina</i> (Hemiptera: Achilidae), <i>Oncometopia orbona</i> (Hemiptera: Cicadellidae), <i>Flexamia atlantica</i> (Hemiptera: Cicadellidae) and <i>Stictocephala bisonia</i> (Hemiptera: Membracidae). Sequencing library preparation from single specimens was successful despite extremely small DNA yields (&lt;0.1 μg) for some samples. Additional sequencing and assembly workflows were adapted to each sample depending on the initial DNA yield. PacBio circular consensus (CCS/HiFi) or continuous long reads (CLR) libraries were used to sequence DNA fragments up to 50 kb in length, with Illumina sequenced linked-reads (TellSeq libraries) and Omni-C libraries used for scaffolding and gap-filling. Assembled genome sizes ranged from 135 MB to 3.2 GB. The number of assembled scaffolds ranged from 47 to &gt;13,000, with the longest scaffold per assembly ranging from ~23 to 439 Mb. Genome completeness was high, with BUSCO scores ranging from 85.5% completeness for the largest genome (<i>Stictocephala bisonia</i>) to 98.8% completeness for the smallest genome (<i>Coelinius</i> sp.). The unique content was estimated using RepeatMasker and GenomeScope2, which ranged from 50.7% to 75.8% and roughly decreased with increasing genome size. Structural annotation predicted a range of 19,281–72,469 protein models for sequenced species. Sequencing costs per genome at the time ranged from US$3–5k, averaged ~1600 CPU-hours on a high-performance cluster and required approximately 14 h of bioinformatics analyses with samples using PacBio HiFi data. Most assemblies would benefit from further manual curation to correct possible scaffold misjoins and translocations suggested by off-diagonal or depleted signals in Omni-C contact maps.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"24 8","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.14010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141999007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of spatial demographic maps from polymorphism data using a neural network","authors":"Chris C. R. Smith,&nbsp;Gilia Patterson,&nbsp;Peter L. Ralph,&nbsp;Andrew D. Kern","doi":"10.1111/1755-0998.14005","DOIUrl":"10.1111/1755-0998.14005","url":null,"abstract":"<p>A fundamental goal in population genetics is to understand how variation is arrayed over natural landscapes. From first principles we know that common features such as heterogeneous population densities and barriers to dispersal should shape genetic variation over space, however there are few tools currently available that can deal with these ubiquitous complexities. Geographically referenced single nucleotide polymorphism (SNP) data are increasingly accessible, presenting an opportunity to study genetic variation across geographic space in myriad species. We present a new inference method that uses geo-referenced SNPs and a deep neural network to estimate spatially heterogeneous maps of population density and dispersal rate. Our neural network trains on simulated input and output pairings, where the input consists of genotypes and sampling locations generated from a continuous space population genetic simulator, and the output is a map of the true demographic parameters. We benchmark our tool against existing methods and discuss qualitative differences between the different approaches; in particular, our program is unique because it infers the magnitude of both dispersal and density as well as their variation over the landscape, and it does so using SNP data. Similar methods are constrained to estimating relative migration rates, or require identity-by-descent blocks as input. We applied our tool to empirical data from North American grey wolves, for which it estimated mostly reasonable demographic parameters, but was affected by incomplete spatial sampling. Genetic based methods like ours complement other, direct methods for estimating past and present demography, and we believe will serve as valuable tools for applications in conservation, ecology and evolutionary biology. An open source software package implementing our method is available from https://github.com/kr-colab/mapNN.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"24 7","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.14005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141994887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MycoAI: Fast and accurate taxonomic classification for fungal ITS sequences","authors":"Luuk Romeijn,&nbsp;Andrius Bernatavicius,&nbsp;Duong Vu","doi":"10.1111/1755-0998.14006","DOIUrl":"10.1111/1755-0998.14006","url":null,"abstract":"<p>Efficient and accurate classification of DNA barcode data is crucial for large-scale fungal biodiversity studies. However, existing methods are either computationally expensive or lack accuracy. Previous research has demonstrated the potential of deep learning in this domain, successfully training neural networks for biological sequence classification. We introduce the MycoAI Python package, featuring various deep learning models such as BERT and CNN tailored for fungal Internal Transcribed Spacer (ITS) sequences. We explore different neural architecture designs and encoding methods to identify optimal models. By employing a multi-head output architecture and multi-level hierarchical label smoothing, MycoAI effectively generalizes across the taxonomic hierarchy. Using over 5 million labelled sequences from the UNITE database, we develop two models: MycoAI-BERT and MycoAI-CNN. While we emphasize the necessity of verifying classification results by AI models due to insufficient reference data, MycoAI still exhibits substantial potential. When benchmarked against existing classifiers such as DNABarcoder and RDP on two independent test sets with labels present in the training dataset, MycoAI models demonstrate high accuracy at the genus and higher taxonomic levels, with MycoAI-CNN being the fastest and most accurate. In terms of efficiency, MycoAI models can classify over 300,000 sequences within 5 min. We publicly release the MycoAI models, enabling mycologists to classify their ITS barcode data efficiently. Additionally, MycoAI serves as a platform for developing further deep learning-based classification methods. The source code for MycoAI is available under the MIT Licence at https://github.com/MycoAI/MycoAI.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"24 8","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.14006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141994888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scanning amplicons with CRISPR-Dx detects endangered amphibians in environmental DNA","authors":"Flurin Leugger,&nbsp;Michel Schmidlin,&nbsp;Martina Lüthi,&nbsp;Zacharias Kontarakis,&nbsp;Loïc Pellissier","doi":"10.1111/1755-0998.14009","DOIUrl":"10.1111/1755-0998.14009","url":null,"abstract":"<p>More efficient methods for extensive biodiversity monitoring are required to support rapid measures to address the biodiversity crisis. While environmental DNA (eDNA) metabarcoding and quantitative PCR (qPCR) methods offer advantages over traditional monitoring approaches, their large-scale application is limited by the time and labour required for developing assays and/or for analysis. CRISPR (clustered regularly interspaced short palindromic repeats) diagnostic technologies (Dx) may overcome some of these limitations, but they have been used solely with species-specific primers, restricting their versatility for biodiversity monitoring. Here, we demonstrate the feasibility of designing species-specific CRISPR-Dx assays in silico within a short metabarcoding fragment using a general primer set, a methodology we term ‘ampliscanning’, for 18 of the 22 amphibian species in Switzerland. We sub-selected nine species, including three classified as regionally endangered, to test the methodology using eDNA sampled from ponds at nine sites. We compared the ampliscanning detections to data from traditional monitoring at these sites. Ampliscanning was successful at detecting target species with different prevalences across the landscape. With only one visit, we detected more species per site than three traditional monitoring visits (visual and acoustic detections by trained experts), in particular more elusive species and previously undocumented but expected populations. Ampliscanning detected 25 species/site combinations compared to 12 with traditional monitoring. Sensitivity analyses showed that larger numbers of field visits and PCR replicates are more important for reliable detection than many technical replicates at the CRISPR-Dx assay level. Given the reduced sampling and analysis effort, our results highlight the benefits of eDNA and CRISPR-Dx combined with universal primers for large-scale monitoring of multiple endangered species across landscapes to inform conservation measures.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"24 8","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.14009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141994889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging genomic load estimates to optimize captive breeding programmes","authors":"Evelyn L. Jensen,&nbsp;Rachel Gray,&nbsp;Joshua M. Miller","doi":"10.1111/1755-0998.14007","DOIUrl":"10.1111/1755-0998.14007","url":null,"abstract":"<p>Rapid biodiversity loss threatens many species with extinction. Captive populations of species of conservation concern (such as those housed in zoos and dedicated breeding centres) act as an insurance should wild populations go extinct or need supplemental individuals to boost populations. Limited resources mean that captive populations are almost always small and started from few founding individuals. As a result, captive populations require careful management to minimize negative genetic impacts, with decisions about which individuals to breed together often guided by the principle of minimizing relatedness. Typically this strategy aims to retain 90% of genetic diversity over 200 years (Soulé et al., <i>Zoo Biology</i>, 1986, 5, 101), but it has a weakness in that it does not directly manage for genetic load. In this issue of Molecular Ecology Resources, Speak et al. (<i>Molecular Ecology Resources</i>, 2024, e13967) present a novel proof-of-concept study for taking this next step and incorporating estimates of individual genetic load into the planning of captive breeding, using an approach that is likely to be widely applicable to many captive populations.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"24 7","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.14007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141974648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Macrobial airborne environmental DNA analysis: A review of progress, challenges, and recommendations for an emerging application","authors":"Mark Johnson,&nbsp;Matthew A. Barnes","doi":"10.1111/1755-0998.13998","DOIUrl":"10.1111/1755-0998.13998","url":null,"abstract":"<p>In the context of looming global biodiversity loss, effective species detection represents a critical concern for ecological research and management. Environmental DNA (eDNA) analysis, which refers to the collection and taxonomic identification of genetic fragments that are shed from an organism into its surroundings, emerged approximately 15 years ago as a sensitive tool for species detection. Today, one of the frontiers of eDNA research concerns the collection and analysis of genetic material in dust and other airborne materials, termed airborne eDNA analysis. As the study of airborne eDNA matures, it is an appropriate time to review the foundational and emerging studies that make up the current literature, and use the reviewed literature to summarize, synthesize, and forecast the major challenges and opportunities for this advancing research front. Specifically, we use the “ecology of eDNA” framework to organize our findings across the origin, state, transport, and fate of airborne genetic materials in the environment, and summarize what is so far known of their interactions with surrounding abiotic and biotic factors, including population and community ecologies and ecosystem processes. Within this work we identify key challenges, opportunities, and future directions associated with the application of airborne eDNA development. Lastly, we discuss the development of applications, partnerships, and messaging that promote development and growth of the field. Together, the broad potential of eDNA analysis and the rate at which research is accelerating in this field suggest that the sky's the limit for airborne eDNA science.</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":"24 7","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1755-0998.13998","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141900298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}