Molecular Ecology Resources Journal Impact Factor & Information

Publisher: Wiley

Current impact factor: 3.71

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 3.712
2013 Impact Factor 5.626
2012 Impact Factor 7.432
2011 Impact Factor 3.062
2010 Impact Factor 1.631
2009 Impact Factor 1.251
2008 Impact Factor 0

Impact factor over time

Impact factor

Additional details

5-year impact 4.99
Cited half-life 4.50
Immediacy index 1.63
Eigenfactor 0.03
Article influence 1.65
Other titles Molecular ecology resources (Online)
ISSN 1755-0998
OCLC 190864867
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details


  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author cannot archive a post-print version
  • Restrictions
    • 12 months embargo
  • Conditions
    • Some journals have separate policies, please check with each journal directly
    • On author's personal website, institutional repositories, arXiv, AgEcon, PhilPapers, PubMed Central, RePEc or Social Science Research Network
    • Author's pre-print may not be updated with Publisher's Version/PDF
    • Author's pre-print must acknowledge acceptance for publication
    • Non-Commercial
    • Publisher's version/PDF cannot be used
    • Publisher source must be acknowledged with citation
    • Must link to publisher version with set statement (see policy)
    • If OnlineOpen is available, BBSRC, EPSRC, MRC, NERC and STFC authors, may self-archive after 12 months
    • If OnlineOpen is available, AHRC and ESRC authors, may self-archive after 24 months
    • Publisher last contacted on 07/08/2014
    • This policy is an exception to the default policies of 'Wiley'
  • Classification

Publications in this journal

  • Paul D Blischak · Laura S Kubatko · Andrea D Wolfe ·
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    ABSTRACT: Despite the increasing opportunity to collect large-scale data sets for population genomic analyses, the use of high throughput sequencing to study populations of polyploids has seen little application. This is due in large part to problems associated with determining allele copy number in the genotypes of polyploid individuals (allelic dosage uncertainty-ADU), which complicates the calculation of important quantities such as allele frequencies. Here we describe a statistical model to estimate biallelic SNP frequencies in a population of autopolyploids using high throughput sequencing data in the form of read counts.We bridge the gap from data collection (using restriction enzyme based techniques [e.g., GBS, RADseq]) to allele frequency estimation in a unified inferential framework using a hierarchical Bayesian model to sum over genotype uncertainty. Simulated data sets were generated under various conditions for tetraploid, hexaploid and octoploid populations to evaluate the model's performance and to help guide the collection of empirical data. We also provide an implementation of our model in the R package polyfreqs and demonstrate its use with two example analyses that investigate (i) levels of expected and observed heterozygosity and (ii) model adequacy. Our simulations show that the number of individuals sampled from a population has a greater impact on estimation error than sequencing coverage. The example analyses also show that our model and software can be used to make inferences beyond the estimation of allele frequencies for autopolyploids by providing assessments of model adequacy and estimates of heterozygosity. This article is protected by copyright. All rights reserved.
    Molecular Ecology Resources 11/2015; DOI:10.1111/1755-0998.12493
  • D J Machado · M L Lyra · T Grant ·
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    ABSTRACT: Next-generation sequencing continues to revolutionize biodiversity studies by generating unprecedented amounts of DNA sequence data for comparative genomic analysis. However, these data are produced as millions or billions of short reads of variable quality that cannot be directly applied in comparative analyses, creating a demand for methods to facilitate assembly. We optimized an in silico strategy to efficiently reconstruct high-quality mitochondrial genomes directly from genomic reads. We tested this strategy using sequences from five species of frogs: Hylodes meridionalis (Hylodidae), Hyloxalus yasuni (Dendrobatidae), Pristimantis fenestratus (Craugastoridae), and Melanophryniscus simplex and Rhinella sp. (Bufonidae). These are the first mitogenomes published for these species, the genera Hylodes, Hyloxalus, Pristimantis, Melanophryniscus, and Rhinella, and the families Craugastoridae and Hylodidae. Sequences were generated using only half of one lane of a standard Illumina HiqSeq 2000 flow cell, resulting in fewer than 8 million reads. We analyzed the reads of Hylodes meridionalis using three different assembly strategies: 1. reference-based (using Bowtie2); 2. de novo (using ABySS, SOAPdenovo2 and Velvet); and 3. baiting and iterative mapping (using MIRA and MITObim). Mitogenomes were assembled exclusively with strategy 3, which we employed to assemble the remaining mitogenomes. Annotations were performed with MITOS and confirmed by comparison with published amphibian mitochondria. In most cases, we recovered all 13 coding genes, 22 tRNAs, and 2 ribosomal subunit genes, with minor gene rearrangements. Our results show that few raw reads can be sufficient to generate high-quality scaffolds, making any Illumina machine run using genomic multiplex libraries a potential source of data for organelle assemblies as by-catch. This article is protected by copyright. All rights reserved.
    Molecular Ecology Resources 11/2015; DOI:10.1111/1755-0998.12492
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    ABSTRACT: DNA sequences offer powerful tools for describing the members and interactions of natural communities. In this paper, we establish the to-date most comprehensive library of DNA barcodes for a terrestrial site, including all known macroscopic animals and vascular plants of an intensively-studied area of the High Arctic, the Zackenberg Valley in Northeast Greenland. To demonstrate its utility, we apply the library to identify nearly 20 000 arthropod individuals from two Malaise traps, each operated for two summers. Drawing on this material, we estimate the coverage of previous morphology-based species inventories, derive a snapshot of faunal turnover in space and time, and describe the abundance and phenology of species in the rapidly changing arctic environment. Overall, 403 terrestrial animal and 160 vascular plant species were recorded by morphology-based techniques. DNA barcodes (CO1) offered high resolution in discriminating among the local animal taxa, with 92% of morphologically distinguishable taxa assigned to unique Barcode Index Numbers (BINs) and 93% to monophyletic clusters. For vascular plants, resolution was lower, with 54% of species forming monophyletic clusters based on barcode regions rbcLa and ITS2. Malaise catches revealed 122 BINs not detected by previous sampling and DNA barcoding. The insect community was dominated by a few highly abundant taxa. Even closely-related taxa differed in phenology, emphasizing the need for species-level resolution when describing ongoing shifts in arctic communities and ecosystems. The DNA barcode library now established for Zackenberg offers new scope for such explorations, and for the detailed dissection of interspecific interactions throughout the community. This article is protected by copyright. All rights reserved.
    Molecular Ecology Resources 11/2015; DOI:10.1111/1755-0998.12489
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    ABSTRACT: DNA metabarcoding is a powerful new tool allowing characterization of species assemblages using high-throughput amplicon sequencing. The utility of DNA metabarcoding for quantifying relative species abundances is currently limited by both biological and technical biases which influence sequence read counts. We tested the idea of sequencing 50/50 mixtures of target species and a control species in order to generate relative correction factors (RCFs) that account for multiple sources of bias and are applicable to field studies. RCFs will be most effective if they are not affected by input mass ratio or co-occurring species. In a model experiment involving three target fish species and a fixed control, we found RCFs did vary with input ratio but in a consistent fashion, and that 50/50 RCFs applied to DNA sequence counts from various mixtures of the target species still greatly improved relative abundance estimates (e.g., average per species error of 19 ± 8% for uncorrected versus 3 ± 1% for corrected estimates). To demonstrate the use of correction factors in a field setting, we calculated 50/50 RCFs for 18 harbour seal (Phoca vitulina) prey species (RCFs ranging from 0.68 to 3.68). Applying these corrections to field-collected seal scats affected species percentages from individual samples (Δ 6.7 ± 6.6%) more than population level species estimates (Δ 1.7 ± 1.2%). Our results indicate that the 50/50 RCF approach is an effective tool for evaluating and correcting biases in DNA metabarcoding studies. The decision to apply correction factors will be influenced by the feasibility of creating tissue mixtures for the target species, and the level of accuracy needed to meet research objectives. This article is protected by copyright. All rights reserved.
    Molecular Ecology Resources 11/2015; DOI:10.1111/1755-0998.12490
  • [Show abstract] [Hide abstract]
    ABSTRACT: With advances in high-throughput sequencing technologies, de novo transcriptome sequencing and assembly has become a cost-effective method to obtain comprehensive genetic information of a species of interest, especially in non-model species with large genomes such as spiders. However, high-quality RNA is essential for successful sequencing and sample preservation conditions require careful consideration for the effective storage of field-collected samples. To this end, we report a streamlined feasibility study of various storage conditions and their effects on de novo transcriptome assembly results. The storage parameters considered include temperatures ranging from room temperature to -80°C; preservatives, including ethanol, RNAlater, TRIzol, and RNAlater-ICE; and sample submersion states. As a result, intact RNA was extracted and assembly was successful when samples were preserved at low temperatures regardless of the type of preservative used. The assemblies as well as the gene expression profiles were shown to be robust to RNA degradation, when 30 million 150 bp paired-end reads are obtained. The parameters for sample storage, RNA extraction, library preparation, sequencing, and in silico assembly considered in this work provide a guideline for the study of field-collected samples of spiders. This article is protected by copyright. All rights reserved.
    Molecular Ecology Resources 11/2015; DOI:10.1111/1755-0998.12485
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    ABSTRACT: Speciation is central to evolutionary biology, and to elucidate it, we need to catch the early genetic changes that set nascent taxa on their path to species status (Via 2009). That challenge is difficult, of course, for two chief reasons: (i) serendipity is required to catch speciation in the act; and (ii) after a short time span with lingering gene flow, differentiation may be low and/or embodied only in rare alleles that are difficult to sample. In this issue of Molecular Ecology Resources, Smouse et al. (2015) have noted that optimal assessment of differentiation within and between nascent species should be robust to these challenges, and they identified a measure based on Shannon's information theory that has many advantages for this and numerous other tasks. The Shannon measure exhibits complete additivity of information at different levels of subdivision. Of all the family of diversity measures (‘0’ or allele counts, ‘1’ or Shannon, ‘2’ or heterozygosity, FST and related metrics) Shannon's measure comes closest to weighting alleles by their frequencies. For the Shannon measure, rare alleles that represent early signals of nascent speciation are neither down-weighted to the point of irrelevance, as for level 2 measures, nor up-weighted to overpowering importance, as for level 0 measures (Chao et al. 2010, 2015). Shannon measures have a long history in population genetics, dating back to Shannon's PhD thesis in 1940 (Crow 2001), but have received only sporadic attention, until a resurgence of interest in the last ten years, as reviewed briefly by Smouse et al. (2015).
    Molecular Ecology Resources 11/2015; 15(6). DOI:10.1111/1755-0998.12458
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    ABSTRACT: Recent developments in genotyping technologies coupled with the growing desire to characterise genome variation in Anopheles populations opens the opportunity to develop more effective genotyping strategies for high-throughput screening. A major bottleneck of this goal is nucleic acid extraction. Here, we examined the feasibility of using intact portions of a mosquito's leg as sources of template DNA for whole genome amplification (WGA) by Primer-Extension Pre-amplification. We used the Agena Biosciences MassARRAY platform (formerly Sequenom) to genotype 78 SNPs for 265 WGA leg samples. We performed nucleic acid extraction on 36 mosquito carcasses and compared the genotype call concordance with their corresponding legs, and observed full concordance. Using three legs instead of one improved genotyping success rates (96% versus 89%, respectively), although this difference was not significant. We provide a proof of concept that WGA reactions can be performed directly on mosquito legs, thereby eliminating the need to extract nucleic acid. This approach is straightforward, sensitive and allows both species determination and genotyping of Anopheles mosquitoes to be performed in a high-throughput manner. Our protocol also leaves the mosquito body intact facilitating other experimental analysis to be undertaken on the same sample. Based on our findings, this method would also be suitable for use with other insect species. This article is protected by copyright. All rights reserved.
    Molecular Ecology Resources 10/2015; DOI:10.1111/1755-0998.12473