ABSTRACT
Premise: Most studies of the movement of orchid fruits and roots during plant development have focused on morphological observations; however, further genetic analysis is required to understand the molecular mechanisms underlying this phenomenon. A precise tool is required to observe these movements and harvest tissue at the correct position and time for transcriptomics research. Methods: We utilized three-dimensional (3D) micro-computed tomography (CT) scans to capture the movement of fast-growing Erycina pusilla roots, and built an integrated bioinformatics pipeline to process 3D images into 3D time-lapse videos. To record the movement of slowly developing E. pusilla and Phalaenopsis equestris fruits, two-dimensional (2D) photographs were used. Results: The E. pusilla roots twisted and resupinated multiple times from early development. The first period occurred in the early developmental stage (77-84 days after germination [DAG]) and the subsequent period occurred later in development (140-154 DAG). While E. pusilla fruits twisted 45° from 56-63 days after pollination (DAP), the fruits of P. equestris only began to resupinate a week before dehiscence (133 DAP) and ended a week after dehiscence (161 DAP). Discussion: Our methods revealed that each orchid root and fruit had an independent direction and degree of torsion from the initial to the final position. Our innovative approaches produced detailed spatial and temporal information on the resupination of roots and fruits during orchid development.
ABSTRACT
Modest effect sizes have limited the clinical applicability of genetic associations with rheumatic diseases. Genetic risk scores (GRSs) have emerged as a promising solution to translate genetics into useful tools. In this review, we provide an overview of the recent literature on GRSs in rheumatic diseases. We describe six categories for which GRSs are used: (a) disease (outcome) prediction, (b) genetic commonalities between diseases, (c) disease differentiation, (d) interplay between genetics and environmental factors, (e) heritability and transferability, and (f) detecting causal relationships between traits. In our review of the literature, we identified current lacunas and opportunities for future work. First, the shortage of non-European genetic data restricts the application of many GRSs to European populations. Next, many GRSs are tested in settings enriched for cases that limit the transferability to real life. If intended for clinical application, GRSs are ideally tested in the relevant setting. Finally, there is much to elucidate regarding the co-occurrence of clinical traits to identify shared causal paths and elucidate relationships between the diseases. GRSs are useful instruments for this. Overall, the ever-continuing research on GRSs gives a hopeful outlook into the future of GRSs and indicates significant progress in their potential applications.
