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Biology subjects

Das Roy, R.

Publications and source records attributed to Das Roy, R..

6 recordsLinked to original sources

'broadSeq', a benchmarking tool to contrast differential gene expression methods and identify when genomic neighbourhood matters

Several tools are available to detect differential gene expression. The predominant approach of different statistical methods is to consider changes in gene expression independent from their genomic context. Previously, DELocal was introduced that takes into consideration gene expression dynamics in the genomic neighbourhood. Whereas DELocal was shown to identify developmentally regulated genes in developing mouse tooth, its performance in other biological conditions remains undetermined. To benchmark DElocal together with other methods, we develop another tool 'broadSeq'. It provides easy to use interface for methods like DELocal , deseq2, limma, edger, EBSeq and many more. Here we report benchmarking results on different data sets that comprise wild type developing mouse organs from different embryonic time points, and also human cancer data. The examined datasets are from the heart, kidney, liver, brain, forebrain, and hindbrain. We found that most methods produce relatively comparable lists of differentially expressed genes. Nevertheless, DELocal identifies partially distinct sets of genes compared to the other methods. Evaluating the identified genes using gene and disease ontology terms show that the uniquely detected genes by DELocal are biologically relevant and also highly expressed compared to the genes identified by the other methods. Because consistently highly expressed genes show relatively subtle fold changes, the neighbourhood concept of DELocal appears to correct for the difficulty in detecting these differential expression of highly expressed genes. Finally, we provide the tools as combined bioconductor packages, allowing researchers to explore and decide the best methods for their data and questions.

bioinformatics↗

Eco-evolutionary dynamics and environmental detoxification jointly shape bacterial community response to antibiotic perturbation

Microbial communities frequently encounter recurrent antibiotic disturbance, yet how ecological, evolutionary, and environmental processes jointly shape the response remains unresolved. Here we experimentally disentangle these mechanisms using a 23-species bacterial community exposed to ampicillin pulses with pre-pulse and resistance priming. Pre-pulse priming preconditioned community composition toward resistant taxa, reducing compositional change during the main pulse. Resistance priming was the dominant determinant of community response, buffering compositional change, relaxing selection, and altering gene expression. This buffering arose from both evolution of higher resistance and accelerated ampicillin detoxification by a dominant degrader, which transiently reduced antibiotic effects and favoured non-degrading taxa. Yet buffering did not translate into better recovery: because resistance was coupled to competitive dominance, diversity remained comparable to or below that of ancestral communities, and dominance was reinforced. Together, we show that antibiotic history reshapes microbial disturbance response through coupled eco-evolutionary and environmental feedbacks, generating a trade-off between resistance and recovery.

evolutionary biology↗

The developmental basis for scaling of mammalian tooth size

When evolution leads to differences in body size, organs generally scale along. A well-known example of the tight relationship between organ and body size is the scaling of mammalian molar teeth. To investigate how teeth scale during development and evolution, we compared molar development in mouse and rat from initiation through final size. Whereas the linear dimensions of the rat first lower molar are twice that of the mouse molar, their shapes are largely the same. We found that scaling of the molars starts early, and that the rat molar is patterned equally as fast but in a larger size than the mouse molar. Using transcriptomics, we discovered that a known regulator of body size, insulin-like growth factor 1 (Igf1), is more highly expressed in the rat molars compared to the mouse molars. Ex vivo and in vivo mouse models demonstrated that modulation of the IGF pathway reproduces several aspects of the observed scaling process. Furthermore, analysis of IGF1-treated mouse molars and computational modeling indicate that IGF signaling scales teeth by simultaneously enhancing growth and by inhibiting the cusp patterning program, thereby providing a relatively simple mechanism for scaling teeth during development and evolution. Finally, comparative data from shrews to elephants suggest that this scaling mechanism regulates the minimum tooth size possible, as well as the patterning potential of large teeth.

developmental biology↗

Transcriptomic landscape of early hair follicle and epidermal development

Morphogenesis of ectodermal organs, such as hair, tooth, and mammary gland, starts with the formation of local epithelial thickenings, or placodes, but it remains to be determined how distinct cell types and differentiation programs are established during ontogeny. Here, we use bulk and single-cell transcriptomics and pseudotime modelling to address these questions in developing hair follicles and epidermis, and produce a comprehensive transcriptomic profile of cellular populations in the hair placode and interplacodal epithelium. We report previously unknown cell populations and marker genes, including early suprabasal and genuine interfollicular basal markers, and propose the identity of suprabasal progenitors. By uncovering four different hair placode cell populations organized in three spatially distinct areas, with fine gene expression gradients between them, we posit early establishment of cell fates. This work is accompanied by a readily accessible online tool to stimulate further research on skin appendages and their progenitors.

developmental biology↗

DELocal: Chromosomal neighbourhoods having genes of diverse functions allow improved identification of differentially expressed genes

Although most genes share their chromosomal neighbourhood with other genes, distribution of genes has not been explored in the context of individual organ development; the common focus of developmental biology studies. Because developmental processes are often associated with initially subtle changes in gene expression, here we explored whether neighbouring genes are informative in the identification of differentially expressed genes. First, we quantified the chromosomal neighbourhood patterns of genes having related functional roles in the mammalian genome. Although the majority of protein coding genes have at least five neighbours within 1 Mb window around each gene, very few of these neighbours regulate development of the same organ. Analyses of transcriptomes of developing mouse molar teeth revealed that whereas expression of genes regulating tooth development changes, their neighbouring genes show no marked changes, irrespective of their level of expression. Finally, we test whether inclusion of gene neighbourhood in the analyses of differential expression could provide additional benefits. For the analyses, we developed an algorithm, called DELocal that identifies differentially expressed genes by comparing their expression changes to changes in adjacent genes in their chromosomal regions. Our results show that DELocal removes detection bias towards large changes in expression, thereby allowing identification of even subtle changes in development. Future studies, including the detection of differential expression, may benefit from, and further characterize the significance of gene-gene neighbour relationships. Author SummaryDevelopment of organs is typically associated with small and hard to detect changes in gene expression. Here we examined how often genes regulating specific organs are neighbours to each other in the genome, and whether this gene neighbourhood helps in the detection of changes in gene expression. We found that genes regulating individual organ development are very rarely close to each other in the mouse and human genomes. We built an algorithm, called DELocal, to detect changes in gene expression that incorporates information about neighbouring genes. Using transcriptomes of developing mouse molar teeth containing gene expression profiles of thousands of genes, we show how genes regulating tooth development are ranked high by DELocal even if their expression level changes are subtle. We propose that developmental biology studies can benefit from gene neighbourhood analyses in the detection of differential expression and identification of organ specific genes.

bioinformatics↗

Keystone genes of mammalian tooth patterning and quantification of their expression

When a null mutation of a gene causes a complete developmental arrest, the gene is typically considered essential for life. Yet, in most cases null mutations have more subtle effects on the phenotype. Here we used the phenotypic severity of mutations as a tool to examine system-level dynamics of gene expression. We classify genes required for the normal development of the mouse molar into different categories that range from essential to subtle modification of the phenotype. Collectively, we call these the developmental keystone genes. Transcriptome profiling using microarray and RNAseq analyses of patterning stage mouse molars show highly elevated expression levels for genes essential for the progression of tooth development, a result reminiscent of essential genes in single cell organisms. Elevated expression levels of progression genes were also detected in developing rat molars, suggesting evolutionary conservation of this system-level dynamics. Single-cell RNAseq analyses of developing mouse molars reveal that even though the size of the expression domain, measured in number of cells, is the main driver of organ-level expression, progression genes show high cell-level transcript abundances. Progression genes are also upregulated within their pathways, which themselves are highly expressed. In contrast, a high proportion of the genes required for normal tooth patterning are secreted ligands that are expressed in fewer cells than their receptors and intracellular components. Overall, even though expression patterns of individual genes can be highly different, conserved system-level principles of gene expression can be detected using phenotypically defined gene categories.

developmental biology↗