Diversity measurement combining relative abundances and taxonomic distinctiveness of species

Estimating genome-wide DNA methylation heterogeneity with methylation patterns

BACKGROUND

In a heterogeneous population of cells, individual cells can behave differently and respond variably to the environment. This cellular diversity can be assessed by measuring DNA methylation patterns. The loci with variable methylation patterns are informative of cellular heterogeneity and may serve as biomarkers of diseases and developmental progression. Cell-to-cell methylation heterogeneity can be evaluated through single-cell methylomes or computational techniques for pooled cells. However, the feasibility and performance of these approaches to precisely estimate methylation heterogeneity require further assessment.

RESULTS

Here, we proposed model-based methods adopted from a mathematical framework originally from biodiversity, to estimate genome-wide DNA methylation heterogeneity. We evaluated the performance of our models and the existing methods with feature comparison, and tested on both synthetic datasets and real data. Overall, our methods have demonstrated advantages over others because of their better correlation with the actual heterogeneity. We also demonstrated that methylation heterogeneity offers an additional layer of biological information distinct from the conventional methylation level. In the case studies, we showed that distinct profiles of methylation heterogeneity in CG and non-CG methylation can predict the regulatory roles between genomic elements in Arabidopsis. This opens up a new direction for plant epigenomics. Finally, we demonstrated that our score might be able to identify loci in human cancer samples as putative biomarkers for early cancer detection.

CONCLUSIONS

We adopted the mathematical framework from biodiversity into three model-based methods for analyzing genome-wide DNA methylation heterogeneity to monitor cellular heterogeneity. Our methods, namely MeH, have been implemented, evaluated with existing methods, and are open to the research community.

Development of the Circular Bioeconomy: Drivers and Indicators

The EU’s 2018 Bioeconomy Strategy Update and the European Green Deal recently confirmed that the bioeconomy is high on the political agenda in Europe. Here, we propose a conceptual analysis framework for quantifying and analyzing the development of the EU bioeconomy. The bioeconomy has several related concepts (e.g., bio-based economy, green economy, and circular economy) and there are clear synergies between these concepts, especially between the bioeconomy and circular economy concepts. Analyzing the driving factors provides important information for monitoring activities. We first derive the scope of the bioeconomy framework in terms of bioeconomy sectors and products to be involved, the needed geographical coverage and resolution, and time period. Furthermore, we outline a set of indicators linked to the objectives of the EU’s bioeconomy strategy. In our framework, measuring developments will, in particular, focus on the bio-based sectors within the bioeconomy as biomass and food production is already monitored. The selected indicators commit to the EU Bioeconomy Strategy objectives and conform with findings from previous studies and stakeholder consultation. Additionally, several new indicators have been suggested and they are related to measuring the impact of changes in supply, demand drivers, resource availability, and policies on sustainability goals.

Taxonomically Informed Scoring Enhances Confidence in Natural Products Annotation

Mass spectrometry (MS) offers unrivalled sensitivity for the metabolite profiling of complex biological matrices encountered in natural products (NP) research. The massive and complex sets of spectral data generated by such platforms require computational approaches for their interpretation. Within such approaches, computational metabolite annotation automatically links spectral data to candidate structures via a score, which is usually established between the acquired data and experimental or theoretical spectral databases (DB). This process leads to various candidate structures for each MS features. However, at this stage, obtaining high annotation confidence level remains a challenge notably due to the extensive chemodiversity of specialized metabolomes. The design of a metascore is a way to capture complementary experimental attributes and improve the annotation process. Here, we show that integrating the taxonomic position of the biological source of the analyzed samples and candidate structures enhances confidence in metabolite annotation. A script is proposed to automatically input such information at various granularity levels (species, genus, and family) and complement the score obtained between experimental spectral data and output of available computational metabolite annotation tools (ISDB-DNP, MS-Finder, Sirius). In all cases, the consideration of the taxonomic distance allowed an efficient re-ranking of the candidate structures leading to a systematic enhancement of the recall and precision rates of the tools (1.5- to 7-fold increase in the F1 score). Our results clearly demonstrate the importance of considering taxonomic information in the process of specialized metabolites annotation. This requires to access structural data systematically documented with biological origin, both for new and previously reported NPs. In this respect, the establishment of an open structural DB of specialized metabolites and their associated metadata, particularly biological sources, is timely and critical for the NP research community.

Distance-based functional diversity measures and their decomposition: a framework based on Hill numbers

Hill numbers (or the “effective number of species”) are increasingly used to characterize species diversity of an assemblage. This work extends Hill numbers to incorporate species pairwise functional distances calculated from species traits. We derive a parametric class of functional Hill numbers, which quantify “the effective number of equally abundant and (functionally) equally distinct species” in an assemblage. We also propose a class of mean functional diversity (per species), which quantifies the effective sum of functional distances between a fixed species to all other species. The product of the functional Hill number and the mean functional diversity thus quantifies the (total) functional diversity, i.e., the effective total distance between species of the assemblage. The three measures (functional Hill numbers, mean functional diversity and total functional diversity) quantify different aspects of species trait space, and all are based on species abundance and species pairwise functional distances. When all species are equally distinct, our functional Hill numbers reduce to ordinary Hill numbers. When species abundances are not considered or species are equally abundant, our total functional diversity reduces to the sum of all pairwise distances between species of an assemblage. The functional Hill numbers and the mean functional diversity both satisfy a replication principle, implying the total functional diversity satisfies a quadratic replication principle. When there are multiple assemblages defined by the investigator, each of the three measures of the pooled assemblage (gamma) can be multiplicatively decomposed into alpha and beta components, and the two components are independent. The resulting beta component measures pure functional differentiation among assemblages and can be further transformed to obtain several classes of normalized functional similarity (or differentiation) measures, including N-assemblage functional generalizations of the classic Jaccard, Sørensen, Horn and Morisita-Horn similarity indices. The proposed measures are applied to artificial and real data for illustration.

NEW MEASURES FOR COMPARING THE SPECIES DIVERSITY FOUND IN TWO OR MORE HABITATS

Both the weighted entropy, which generalizes the Shannon entropy, and the weighted quadratic index, which generalizes the Gini-Simpson index, are used for getting a unified treatment of some diversity measures proposed recently in ecology. The weights may reflect the ecological importance, rarity, or economic value of the species from a given habitat. The weighted measures, being concave functions, may be used in the additive partition of diversity. The weighted quadratic index has a special advantage over the weighted entropy because its maximum value has a simple analytical formula which allows us to introduce a normed measure of dissimilarity between habitats. A special case of weighted quadratic index is the Rich-Gini-Simpson index which, unlike the Shannon entropy and the classic Gini-Simpson index, behaves well when the number of species is very large. The weighted entropy and the weighted quadratic index may also be used to measure the global diversity among the subsets of species. In this context, Rao's quadratic index of diversity between the pairs of species, based on the phylogenetic distance between species, is obtained as a particular case and is generalized to measure the diversity among the triads of species as well.

Phylogenetic diversity measures based on Hill numbers

We propose a parametric class of phylogenetic diversity (PD) measures that are sensitive to both species abundance and species taxonomic or phylogenetic distances. This work extends the conventional parametric species-neutral approach (based on 'effective number of species' or Hill numbers) to take into account species relatedness, and also generalizes the traditional phylogenetic approach (based on 'total phylogenetic length') to incorporate species abundances. The proposed measure quantifies 'the mean effective number of species' over any time interval of interest, or the 'effective number of maximally distinct lineages' over that time interval. The product of the measure and the interval length quantifies the 'branch diversity' of the phylogenetic tree during that interval. The new measures generalize and unify many existing measures and lead to a natural definition of taxonomic diversity as a special case. The replication principle (or doubling property), an important requirement for species-neutral diversity, is generalized to PD. The widely used Rao's quadratic entropy and the phylogenetic entropy do not satisfy this essential property, but a simple transformation converts each to our measures, which do satisfy the property. The proposed approach is applied to forest data for interpreting the effects of thinning.

A new phylogenetic diversity measure generalizing the shannon index and its application to phyllostomid bats

Protecting biodiversity involves preserving the maximum number and abundance of species while giving special attention to species with unique genetic or morphological characteristics. In balancing different priorities, conservation policymakers may consider quantitative measures that compare diversity across ecological communities. To serve this purpose, a measure should increase or decrease with changes in community composition in a way that reflects what is valued, including species richness, evenness, and distinctness. However, counterintuitively, studies have shown that established indices, including those that emphasize average interspecies phylogenetic distance, may increase with the elimination of species. We introduce a new diversity index, the phylogenetic entropy, which generalizes in a natural way the Shannon index to incorporate species relatedness. Phylogenetic entropy favors communities in which highly distinct species are more abundant, but it does not advocate decreasing any species proportion below a community structure-dependent threshold. We contrast the behavior of multiple indices on a community of phyllostomid bats in the Selva Lacandona. The optimal genus distribution for phylogenetic entropy populates all genera in a linear relationship to their total phylogenetic distance to other genera. Two other indices favor eliminating 12 out of the 23 genera.

Relational diversity

In biology, the measurement of diversity traditionally focusses on reporting number of unambiguously distinguishable types, thus referring to qualitative (discontinuously varying) traits. Inclusion of frequencies or other weights has produced a large variety of diversity indices. Quantitative (continuously varying) traits do not readily fit into this perspective. In fact, in the context of quantitative traits, the concept of diversity is not always clearly distinguished from the (statistical) notion of dispersion. In many cases the ambiguity even extends to qualitative traits. This is at variance with the broad spectrum of diversity issues ranging, e.g., from ecological and genetic aspects of diversity to functional, structural, systematic, or evolutionary (including phylogenetic) aspects. In view of the urgent need for a more consistent perspective, it is called to attention that all of these aspects, whether of qualitative or quantitative nature, can be gathered under the common roof of binary relations (for qualitative traits two objects are related, for example, if they share the same trait state). A comprehensive concept of (relational) diversity can be developed in two steps: (1) determine the number of unrelated pairs of objects among all admissible pairs as a measure of implicit (relative) diversity, (2) invoke the concept of effective number to transform the implicit measure of diversity into an explicit (absolute) measure. The transformation operates by equating the observed implicit diversity to the implicit diversity obtained for the ideal model of an equivalence relation with classes of equal size. The number of these classes specifies the effective number as an explicit measure of diversity. The wealth of problems that can be treated from this unified perspective is briefly addressed by classifying and interpreting established diversity indices in the light of relational diversity. Desirable applications to the above-mentioned aspects are specified with the help of types of relations such as order, hierarchical, and tree relations. Corresponding biological issues including taxonomic community diversity, mating system, food web, sociological, cladistic and phylogenetic, or hypercycle diversity are suggested for future consideration.