Phenotyping in the era of genomics:MaTrics– a digital character matrix to document mammalian phenotypic traits coded numerically

Abstract

A new and uniquely structured matrix of mammalian phenotypes, MaTrics (Mammalian Traits for Comparative Genomics) is presented in a digital form. By focussing on mammalian species for which genome assemblies are available, MaTrics provides an interface between mammalogy and comparative genomics.MaTrics was developed as part of a project to link phenotypic differences between mammals to differences in their genomes using Forward Genomics. Apart from genomes this approach requires information on homologous phenotypes that are numerically encoded (presence-absence; multistate character coding*) in a matrix. MaTrics provides these data, links them to at least one reference (e.g., literature, photographs, histological sections, CT-scans, or museum specimens) and makes them available in a machine actionable NEXUS-format. By making the data computer readable, MatTrics opens a new way for digitizing collections. Currently, MaTrics covers 147 mammalian species and includes 207 characters referring to structure, morphology, physiology, ecology and ethology. Researching these traits revealed substantial knowledge gaps, highlighting the need for substantial phenotyping efforts in the genomic era. Using the trait information documented in MaTrics, previous Forward Genomics screens identified changes in genes that are associated with various phenotypes, ranging from fully-aquatic lifestyle to dietary specializations. These results motivate the continuous expansion of phenotype information, both by filling research gaps or by adding additional taxa and traits. MaTrics is digitally available online within the data repository Morph·D·Base (www.morphdbase.de).

Reconstruction of evolutionary changes in fat and toxin consumption reveals associations with gene losses in mammals: A case study for the lipase inhibitor PNLIPRP1 and the xenobiotic receptor NR1I3

“…Recording feeding habits and dietary components as distinct categories in a trait matrix (recording as traits and states) is one approach to associate gene loss with species‐specific dietary components such as fat or toxins (Stefen et al, 2021). However, definitions and the level of details given on feeding habit categories or description of main dietary components varies from study to study (e.g., Hecker et al, 2019b; Román‐Palacios et al, 2019).…”

“…Similar to the diet model, it focuses on the major proportion of food actually found in the stomach. Primary data were collected from the literature, and the results of trait recording are deposited as part of a larger trait matrix (Stefen et al, 2021; https://www.morphdbase.de/?MaTrics-Mx-v1).…”

“…Although this is showcased in our study of PNLIPRP1 , such approach is also relevant for research on detoxification molecules. By recording dietary components and feeding habits in a fully documented and publicly available data repository (Morph·D·Base; MaTrics : https://www.morphdbase.de/?MaTrics-Mx-v1, Stefen et al, 2021), the data collection used for this study can be applied to further post hoc studies of comparative genomic data (e.g., initiatives such as Zoonomia; Genereux et al, 2020; https://zoonomiaproject.org/). Our study also revealed the substantial lack of knowledge about diet, diet composition and feeding habits.…”

“…These research gaps ranged between 1% and up to 60%, depending on the requirements of the diet composition models M1–M4. Apart from nutrition, the knowledge gap on general/basic phenotypic information is substantial for mammals (Stefen et al, 2021). Nonetheless, the present study serves as an example that the combination of comparative genomics (e.g., Forward Genomics) and comparative trait analyses is a powerful tool.…”