Why more biologists must embrace quantitative modeling.

Biology as a field has transformed since the time of its foundation from an organized enterprise cataloging the diversity of the natural world to a quantitatively rigorous science seeking to answer complex questions about the functions of organisms and their interactions with each other and their environments. As the mathematical rigor of biological analyses has improved, quantitative models have been developed to describe multi-mechanistic systems and to test complex hypotheses. However, applications of quantitative models have been uneven across fields, and many biologists lack the foundational training necessary to apply them in their research or to interpret their results to inform biological problem-solving efforts. This gap in scientific training has created a false dichotomy of "biologists'' and "modelers" that only exacerbates the barriers to working biologists seeking additional training in quantitative modeling. Here, we make the argument that all biologists are modelers, and are capable of using sophisticated quantitative modeling in their work. We highlight four benefits of conducting biological research within the framework of quantitative models, identify the potential producers and consumers of information produced by such models, and make recommendations for strategies to overcome barriers to their widespread implementation. Improved understanding of quantitative modeling could guide the producers of biological information to better apply biological measurements through analyses that evaluate mechanisms, and allow consumers of biological information to better judge the quality and applications of the information they receive. As our explanations of biological phenomena increase in complexity, so too must we embrace modeling as a foundational skill.

Alignment-free genome comparison enables accurate geographic sourcing of white oak DNA.

BACKGROUND: The application of genomic data and bioinformatics for the identification of restricted or illegally-sourced natural products is urgently needed. The taxonomic identity and geographic provenance of raw and processed materials have implications in sustainable-use commercial practices, and relevance to the enforcement of laws that regulate or restrict illegally harvested materials, such as timber. Improvements in genomics make it possible to capture and sequence partial-to-complete genomes from challenging tissues, such as wood and wood products. RESULTS: In this paper, we report the success of an alignment-free genome comparison method, [Formula: see text] that differentiates different geographic sources of white oak (Quercus) species with a high level of accuracy with very small amount of genomic data. The method is robust to sequencing errors, different sequencing laboratories and sequencing platforms. CONCLUSIONS: This method offers an approach based on genome-scale data, rather than panels of pre-selected markers for specific taxa. The method provides a generalizable platform for the identification and sourcing of materials using a unified next generation sequencing and analysis framework.

Erratum: Author Correction: Evolutionary history of plant hosts and fungal symbionts predicts the strength of mycorrhizal mutualism.

[This corrects the article DOI: 10.1038/s42003-018-0120-9.].

Evolutionary history of plant hosts and fungal symbionts predicts the strength of mycorrhizal mutualism.

Most plants engage in symbioses with mycorrhizal fungi in soils and net consequences for plants vary widely from mutualism to parasitism. However, we lack a synthetic understanding of the evolutionary and ecological forces driving such variation for this or any other nutritional symbiosis. We used meta-analysis across 646 combinations of plants and fungi to show that evolutionary history explains substantially more variation in plant responses to mycorrhizal fungi than the ecological factors included in this study, such as nutrient fertilization and additional microbes. Evolutionary history also has a different influence on outcomes of ectomycorrhizal versus arbuscular mycorrhizal symbioses; the former are best explained by the multiple evolutionary origins of ectomycorrhizal lifestyle in plants, while the latter are best explained by recent diversification in plants; both are also explained by evolution of specificity between plants and fungi. These results provide the foundation for a synthetic framework to predict the outcomes of nutritional mutualisms.

Disentangling genetic structure for genetic monitoring of complex populations.

Genetic monitoring estimates temporal changes in population parameters from molecular marker information. Most populations are complex in structure and change through time by expanding or contracting their geographic range, becoming fragmented or coalescing, or increasing or decreasing density. Traditional approaches to genetic monitoring rely on quantifying temporal shifts of specific population metrics-heterozygosity, numbers of alleles, effective population size-or measures of geographic differentiation such as FST. However, the accuracy and precision of the results can be heavily influenced by the type of genetic marker used and how closely they adhere to analytical assumptions. Care must be taken to ensure that inferences reflect actual population processes rather than changing molecular techniques or incorrect assumptions of an underlying model of population structure. In many species of conservation concern, true population structure is unknown, or structure might shift over time. In these cases, metrics based on inappropriate assumptions of population structure may not provide quality information regarding the monitored population. Thus, we need an inference model that decouples the complex elements that define population structure from estimation of population parameters of interest and reveals, rather than assumes, fine details of population structure. Encompassing a broad range of possible population structures would enable comparable inferences across biological systems, even in the face of range expansion or contraction, fragmentation, or changes in density. Currently, the best candidate is the spatial Λ-Fleming-Viot (SLFV) model, a spatially explicit individually based coalescent model that allows independent inference of two of the most important elements of population structure: local population density and local dispersal. We support increased use of the SLFV model for genetic monitoring by highlighting its benefits over traditional approaches. We also discuss necessary future directions for model development to support large genomic datasets informing real-world management and conservation issues.

Home-field advantage? evidence of local adaptation among plants, soil, and arbuscular mycorrhizal fungi through meta-analysis.

BACKGROUND: Local adaptation, the differential success of genotypes in their native versus foreign environment, arises from various evolutionary processes, but the importance of concurrent abiotic and biotic factors as drivers of local adaptation has only recently been investigated. Local adaptation to biotic interactions may be particularly important for plants, as they associate with microbial symbionts that can significantly affect their fitness and may enable rapid evolution. The arbuscular mycorrhizal (AM) symbiosis is ideal for investigations of local adaptation because it is globally widespread among most plant taxa and can significantly affect plant growth and fitness. Using meta-analysis on 1170 studies (from 139 papers), we investigated the potential for local adaptation to shape plant growth responses to arbuscular mycorrhizal inoculation. RESULTS: The magnitude and direction for mean effect size of mycorrhizal inoculation on host biomass depended on the geographic origin of the soil and symbiotic partners. Sympatric combinations of plants, AM fungi, and soil yielded large increases in host biomass compared to when all three components were allopatric. The origin of either the fungi or the plant relative to the soil was important for explaining the effect of AM inoculation on plant biomass. If plant and soil were sympatric but allopatric to the fungus, the positive effect of AM inoculation was much greater than when all three components were allopatric, suggesting potential local adaptation of the plant to the soil; however, if fungus and soil were sympatric (but allopatric to the plant) the effect of AM inoculation was indistinct from that of any allopatric combinations, indicating maladaptation of the fungus to the soil. CONCLUSIONS: This study underscores the potential to detect local adaptation for mycorrhizal relationships across a broad swath of the literature. Geographic origin of plants relative to the origin of AM fungal communities and soil is important for describing the effect of mycorrhizal inoculation on plant biomass, suggesting that local adaptation represents a powerful factor for the establishment of novel combinations of fungi, plants, and soils. These results highlight the need for subsequent investigations of local adaptation in the mycorrhizal symbiosis and emphasize the importance of routinely considering the origin of plant, soil, and fungal components.

MycoDB, a global database of plant response to mycorrhizal fungi.

Plants form belowground associations with mycorrhizal fungi in one of the most common symbioses on Earth. However, few large-scale generalizations exist for the structure and function of mycorrhizal symbioses, as the nature of this relationship varies from mutualistic to parasitic and is largely context-dependent. We announce the public release of MycoDB, a database of 4,010 studies (from 438 unique publications) to aid in multi-factor meta-analyses elucidating the ecological and evolutionary context in which mycorrhizal fungi alter plant productivity. Over 10 years with nearly 80 collaborators, we compiled data on the response of plant biomass to mycorrhizal fungal inoculation, including meta-analysis metrics and 24 additional explanatory variables that describe the biotic and abiotic context of each study. We also include phylogenetic trees for all plants and fungi in the database. To our knowledge, MycoDB is the largest ecological meta-analysis database. We aim to share these data to highlight significant gaps in mycorrhizal research and encourage synthesis to explore the ecological and evolutionary generalities that govern mycorrhizal functioning in ecosystems.

Accurate diagnostics for Bovine tuberculosis based on high-throughput sequencing.

BACKGROUND: Bovine tuberculosis (bTB) is an enduring contagious disease of cattle that has caused substantial losses to the global livestock industry. Despite large-scale eradication efforts, bTB continues to persist. Current bTB tests rely on the measurement of immune responses in vivo (skin tests), and in vitro (bovine interferon-γ release assay). Recent developments are characterized by interrogating the expression of an increasing number of genes that participate in the immune response. Currently used assays have the disadvantages of limited sensitivity and specificity, which may lead to incomplete eradication of bTB. Moreover, bTB that reemerges from wild disease reservoirs requires early and reliable diagnostics to prevent further spread. In this work, we use high-throughput sequencing of the peripheral blood mononuclear cells (PBMCs) transcriptome to identify an extensive panel of genes that participate in the immune response. We also investigate the possibility of developing a reliable bTB classification framework based on RNA-Seq reads. METHODOLOGY/PRINCIPAL FINDINGS: Pooled PBMC mRNA samples from unaffected calves as well as from those with disease progression of 1 and 2 months were sequenced using the Illumina Genome Analyzer II. More than 90 million reads were splice-aligned against the reference genome, and deposited to the database for further expression analysis and visualization. Using this database, we identified 2,312 genes that were differentially expressed in response to bTB infection (p<10(-8)). We achieved a bTB infected status classification accuracy of more than 99% with split-sample validation on newly designed and learned mixtures of expression profiles. CONCLUSIONS/SIGNIFICANCE: We demonstrated that bTB can be accurately diagnosed at the early stages of disease progression based on RNA-Seq high-throughput sequencing. The inclusion of multiple genes in the diagnostic panel, combined with the superior sensitivity and broader dynamic range of RNA-Seq, has the potential to improve the accuracy of bTB diagnostics. The computational pipeline used for the project is available from http://code.google.com/p/bovine-tb-prediction.

HighSSR: high-throughput SSR characterization and locus development from next-gen sequencing data.

MOTIVATION: Microsatellites are among the most useful genetic markers in population biology. High-throughput sequencing of microsatellite-enriched libraries dramatically expedites the traditional process of screening recombinant libraries for microsatellite markers. However, sorting through millions of reads to distill high-quality polymorphic markers requires special algorithms tailored to tolerate sequencing errors in locus reconstruction, distinguish paralogous loci, rarify raw reads originating from the same amplicon and sort out various artificial fragments resulting from recombination or concatenation of auxiliary adapters. Existing programs warrant improvement. RESULTS: We describe a microsatellite prediction framework named HighSSR for microsatellite genotyping based on high-throughput sequencing. We demonstrate the utility of HighSSR in comparison to Roche gsAssembler on two Roche 454 GS FLX runs. The majority of the HighSSR-assembled loci were reliably mapped against model organism reference genomes. HighSSR demultiplexes pooled libraries, assesses locus polymorphism and implements Primer3 for the design of PCR primers flanking polymorphic microsatellite loci. As sequencing costs drop and permit the analysis of all project samples on next-generation platforms, this framework can also be used for direct simple sequence repeats genotyping. AVAILABILITY: http://code.google.com/p/highssr/

The fat body transcriptomes of the yellow fever mosquito Aedes aegypti, pre- and post- blood meal.

BACKGROUND: The fat body is the main organ of intermediary metabolism in insects and the principal source of hemolymph proteins. As part of our ongoing efforts to understand mosquito fat body physiology and to identify novel targets for insect control, we have conducted a transcriptome analysis of the fat body of Aedes aegypti before and in response to blood feeding. RESULTS: We created two fat body non-normalized EST libraries, one from mosquito fat bodies non-blood fed (NBF) and another from mosquitoes 24 hrs post-blood meal (PBM). 454 pyrosequencing of the non-normalized libraries resulted in 204,578 useable reads from the NBF sample and 323,474 useable reads from the PBM sample. Alignment of reads to the existing reference Ae. aegypti transcript libraries for analysis of differential expression between NBF and PBM samples revealed 116,912 and 115,051 matches, respectively. De novo assembly of the reads from the NBF sample resulted in 15,456 contigs, and assembly of the reads from the PBM sample resulted in 15,010 contigs. Collectively, 123 novel transcripts were identified within these contigs. Prominently expressed transcripts in the NBF fat body library were represented by transcripts encoding ribosomal proteins. Thirty-five point four percent of all reads in the PBM library were represented by transcripts that encode yolk proteins. The most highly expressed were transcripts encoding members of the cathepsin b, vitellogenin, vitellogenic carboxypeptidase, and vitelline membrane protein families. CONCLUSION: The two fat body transcriptomes were considerably different from each other in terms of transcript expression in terms of abundances of transcripts and genes expressed. They reflect the physiological shift of the pre-feeding fat body from a resting state to vitellogenic gene expression after feeding.

Phylogenetic and geographical relationships of hantavirus strains in eastern and western Paraguay.

Recently, we reported the discovery of several potential rodent reservoirs of hantaviruses in western (Holochilus chacarius) and eastern Paraguay (Akodon montensis, Oligoryzomys chacoensis, and O. nigripes). Comparisons of the hantavirus S- and M-segments amplified from these four rodents revealed significant differences from each another and from other South American hantaviruses. The ALP strain from the semiarid Chaco ecoregion clustered with Leguna Negra and Rio Mamore (LN/RM), whereas the BMJ-NEB strain from the more humid lower Chaco ecoregion formed a clade with Oran and Bermejo. The other two strains, AAI and IP37/38, were distinct from known hantaviruses. With respect to the S-segment sequence, AAI from eastern Paraguay formed a clade with ALP/LN/RM, but its M-segment clustered with Pergamino and Maciel, suggesting a possible reassortment. AAI was found in areas experiencing rapid land cover fragmentation and change within the Interior Atlantic Forest. IP37/38 did not show any strong association with any of the known hantavirus strains.

Heterotachy and tree building: a case study with plastids and eubacteria.

The nature of heterotachy at the center of recent controversy over the relative performance of tree-building methods is different from the form of heterotachy that has been inferred in empirical studies. The latter have suggested that proportions of variable sites (p(var)) vary among orthologues and among paralogues. However, the strength of this inference, describing what may be one of the most important evolutionary properties of sequence data, has remained weak. Consequently, other models of sequence evolution have been proposed to explain some long-branch attraction (LBA) problems that could be attributed to differences in p(var). For an empirical case with plastid and eubacterial RNA polymerase sequences, we confirm using capture-recapture estimates and simulations that p(var) can differ among orthologues in anciently diverged evolutionary lineages. We find that parsimony and a least squares distance method that implements an overly simple model of sequence evolution are susceptible to LBA induced by this form of heterotachy. Although homogeneous maximum likelihood inference was found to be robust to model misspecification in our specific example, we caution against assuming that it will always be so.

Potential importance of error catastrophe to the development of antiviral strategies for hantaviruses.

Hantaviruses represent an important and growing source of disease emergence in both established and developing countries. The New World hantaviruses have been touted as potential biological weapons because of their lethality to humans and high infectivity as an aerosol. It is also important to acknowledge the threat that hantaviruses can represent to US troops that operate in a foreign territory endemic for hantavirus infection, as was demonstrated in the Korean War. Effective vaccines, immunotherapeutics and antivirals for the prophylaxis or treatment of hantaviral infections are not available. Recent evidence that hantaviruses are prone to error catastrophe opens the door to the development of new therapeutic strategies. Possible future directions for applying lethal mutagenesis as a strategy for the development of novel and more effective antiviral therapies for treatment of hantavirus infections are discussed.

Maximum-likelihood estimation of relatedness.

Relatedness between individuals is central to many studies in genetics and population biology. A variety of estimators have been developed to enable molecular marker data to quantify relatedness. Despite this, no effort has been given to characterize the traditional maximum-likelihood estimator in relation to the remainder. This article quantifies its statistical performance under a range of biologically relevant sampling conditions. Under the same range of conditions, the statistical performance of five other commonly used estimators of relatedness is quantified. Comparison among these estimators indicates that the traditional maximum-likelihood estimator exhibits a lower standard error under essentially all conditions. Only for very large amounts of genetic information do most of the other estimators approach the likelihood estimator. However, the likelihood estimator is more biased than any of the others, especially when the amount of genetic information is low or the actual relationship being estimated is near the boundary of the parameter space. Even under these conditions, the amount of bias can be greatly reduced, potentially to biologically irrelevant levels, with suitable genetic sampling. Additionally, the likelihood estimator generally exhibits the lowest root mean-square error, an indication that the bias in fact is quite small. Alternative estimators restricted to yield only biologically interpretable estimates exhibit lower standard errors and greater bias than do unrestricted ones, but generally do not improve over the maximum-likelihood estimator and in some cases exhibit even greater bias. Although some nonlikelihood estimators exhibit better performance with respect to specific metrics under some conditions, none approach the high level of performance exhibited by the likelihood estimator across all conditions and all metrics of performance.

Design and implementation of a domain specific language for phylogenetic inference.

Domain experts think and reason at a high level of abstraction when they solve problems in their domain of expertise. We present the design and motivation behind a domain specific language, called phi LOG, to enable biologists to program solutions to phylogenetic inference problems at a very high level of abstraction. The implementation infrastructure (interpreter, compiler, debugger) for the DSL is automatically obtained through a software engineering framework based on Denotational Semantics and Logic Programming.

ARE POPULATIONS ISLANDS? ANALYSIS OF CHLOROPLAST DNA VARIATION IN AQUILEGIA.

The degree to which conspecific populations are interconnected via ongoing gene flow remains an important focus of evolutionary biology. One major difficulty in distinguishing ongoing gene flow from historical subdivision is that either process can generate similar estimates of apparent gene flow. Thus, gene flow estimates themselves are insufficient to distinguish between these alternatives. However, genetic data coupled with additional information about demography and distribution do allow a distinction to be made. Here we address the specific question, does gene flow link populations of Aquilegia? In a survey of a 525 B.P. chloroplast DNA fragment sampled from 251 individual plants from 18 populations of three taxa, five haplotypes were identified. No significant relationship between geographic distance and apparent gene flow between population pairs existed. Further, the estimated level of gene flow was entirely compatible with a historical subdivision of Aquilegia populations during the late Pleistocene or early Holocene. Therefore, these patterns of variation are due not to ongoing gene flow, but rather to historical association among populations. Thus Aquilegia populations may be considered as distinct evolutionary entities with regard to seed-mediated processes. As a result, comparative analysis of ecological traits undergoing potentially rapid evolution (e.g., life histories, mating systems, inbreeding depression) should be possible in these taxa.

EVOLUTIONARY DIVERGENCE AND CHARACTER DISPLACEMENT IN TWO PHENOTYPICALLY-VARIABLE, COMPETING SPECIES.

Theoretical studies of character displacement lead to the view that evolutionary divergence depends primarily on incomplete utilization of available resources. Those models which incorporate constraints preventing complete utilization of resources, even in the absence of competitors, all predict character displacement. Those models which allow greater flexibility of resource use within a species predict correspondingly less divergence. Indeed, Matessi and Jayakar (1980, 1981) based their conditions for occurrence of character displacement on underutilization of resources. I extend a model used by Slatkin (1980, 1983) and Taper and Case (1985) which allows each species to fully utilize its resources in the absence of competitors. I concentrate on the biologically reasonable case in which the species, though similar, differ in their ecological characteristics. As a result of this greater biological realism, I arrive at a different conclusion regarding the conditions which lead to character displacement. The presence of a variety of biological differences between species-including as a subset those which result from resource underutilization-leads to divergence with respect to a quantitatively inherited character, due to interspecific competitive interactions. The resulting displacement can be large and depends little on the parameters chosen. The only exception, involving a character with very low heritability, occurs when the non-interactive phenotypic differences are much greater than those associated with studies of character displacement in natural populations. Thus, under conditions comparable to those encountered in the field, involving similar yet not identical species, evolutionary divergence is a consequence of interspecific competition.