University of Cambridge
Cambridge CB2 1LR
It is well studied that the diversity of animal and plant morphologies is established through embryo development (= embryogenesis), a key process to generate complex multicellular life. Embryogenesis provides the developmental framework to establish the organismal organisation (= body plan) of a multicellular organism by passing through a defined series of developmental stages that are governed by genetic programs of gene expression. The correct execution of these programs is crucial for generating and maintaining the vast organismal complexity such as eyes, head, limbs, etc. that define animals and plants. This developmental series from a zygote to a mature embryo is known to pass through stages governed by different developmental constraints (= limitations on phenotypic variability caused by the structure, character, composition, or dynamics of the developmental system). This difference in developmental constraints results from the execution of different gene regulatory programs that guide the developmental series of the embryo. Three major shifts occur during embryo development: Fertilization/Cleavage - Organogenesis - Patterning/Growth. Thus, embryogenesis can be divided into three phases: early embryogenesis, mid-embryogenesis and late-embryogenesis. In each phase (early, mid and late) developmental constraints were shown to correlate with different patterns of embryo morphology. When comparing animal embryos between different species it has been observed that they show high morphological dissimilarity during early embryogenesis, low dissimilarity during mid-embryogenesis, and again high dissimilarity during late embryogenesis.
Primarily investigated in animals for the past two centuries, today this phenomenon denoting the morphological pattern of high dissimilarity – low dissimilarity – high dissimilarity between animal embryos is referred to as developmental hourglass model (Duboule, 1994; Raff, 1996) and it remains to be the most prominent hypothesis aiming to explain the morphological and molecular conservation of mid-stage embryos (= phylotypic stage). It has been discussed whether or not the developmental hourglass model can be used to investigate and explain the origin and conservation of extant animal body plans to correlate the diversity and constraint of animal forms with patterns found in embryogenesis (Irie and Kuratani, 2014).
In my previous role as PhD student in Halle (Saale), Germany I could demonstrate that the developmental transcriptomes of plants also follow transcriptomic hourglass patterns (Quint, Drost et al., 2012; Drost et al., 2015; Drost et al., 2016). Surprisingly, these molecular hourglass pattern in plants are comparable to the patterns found in animals. This finding suggests that both phenomena evolved independently in animals and plants and challenges the prominent hypothesis in animals that postulates that the origin of the morphological hourglass phenomenon is due to constraints on body plan establishment (Quint, Drost et al., 2012; Drost et al. 2016). As a result, I speculated that not body plan formation or organogenesis are generating the morphological pattern of dissimilarity and constrain animal and plant forms, but rather a more fundamental process that serves as switch that separates two functional programs (Drost et al., 2016). I referred to this switch as organizational checkpoint and concluded that molecular hourglass patterns are a feature of multiple biological processes.
In my current position as Research Associate in Jerzy Paszkowski’s lab I focus on the prediction and epigenetic control of transposable elements (TEs) to study how host organisms restrict transposition events. Transposable elements are genetic elements that comprise a vast array of DNA sequences, having the ability to move to new sites in genomes either directly by a cut-and-paste mechanism or indirectly through an RNA intermediate (retrotransposons). These mobile genetic elements (initially referred to as “jumping genes”) contribute to genome structure and genome evolution and are considered key to investigate mechanisms of phenotypic adaptation, diversification, and evolution.
Currently, I am developing the mathematical and computational frameworks to confidently detect potentially active LTR retrotransposons based on DNA sequence features. For this purpose, I first developed the open source software tool biomartr to automate the data retrieval step of “raw” genome assemblies (https://github.com/HajkD/biomartr). Second, I developed the novel meta-analytics tool LTRpred to de-novo annotate LTR retrotransposons in any genome of interest. To investigate the dynamics of LTR retrotransposon abundance across species, phyla and kingdoms I applied LTRpred to perform comparative genomics studies on this set of annotated LTR retrotransposons.
News about my research:
Quint M, Drost HG, Gabel A, Ullrich KK, Boenn M, Grosse I. A transcriptomic hourglass in plant embryogenesis. Nature 490, 89-101 (2012).
Drost HG, Gabel A, Grosse I, Quint M. Evidence for active maintenance of phylotranscriptomic hourglass patterns in animal and plant embryogenesis. Mol Biol Evol. 32:1221-1231 (2015).
Drost HG, Bellstädt J, Ó'Maoiléidigh DS, Silva AT, Gabel A, Weinholdt C, Ryan PT, Dekkers BJW, Bentsink L, Hilhorst H, Ligterink W, Wellmer F, Grosse I, and Quint M. Post-embryonic hourglass patterns mark ontogenetic transitions in plant development. Mol. Biol. Evol. 33(5): 1158-1163 (2016).
Ryan PT, O‘Maoileidigh DS, HG Drost, et al. Patterns of gene expression during Arabidopsis flower development from the time of initiation to maturation. BMC Genomics 16:488 (2015).
Dekkers BJW, Pearce S, van Bolderen-Veldkamp RP, Marshall A, Widera P, Gilbert J, Drost HG et al. Transcriptional dynamics of two seed compartments with opposing roles in Arabidopsis seed germination. Plant Physiology 163 (1), 205-215 (2013).
Drost HG, Janitza P, Grosse I, Quint M. Cross-kingdom comparison of the developmental hourglass. Current Opinion in Genetics & Development 45: 69–75 (2017).
Drost HG, Paszkowski J. Biomartr: genomic data retrieval with R. Bioinformatics (2017). doi: 10.1093/bioinformatics/btw821.