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Sobel, J.

Publications and source records attributed to Sobel, J..

2 recordsLinked to original sources

Transposition, duplication, and divergence of the telomerase RNA underlies the Mimulus telomere evolution

Telomeres are nucleoprotein complexes with a crucial role of protecting chromosome ends. It consists of simple repeat sequences and dedicated telomere-binding proteins. Because of its vital functions, components of the telomere, for example its sequence, should be under strong evolutionary constraint. But across all plants, telomere sequences display a range of variation and the evolutionary mechanism driving this diversification is largely unknown. Here, we discovered in Monkeyflower (Mimulus) the telomere sequence is even variable between species. We investigated the basis of Mimulus telomere sequence evolution by studying the long noncoding telomerase RNA (TR), which is a core component of the telomere maintenance complex and determines the telomere sequence. We conducted total RNA-based de novo transcriptomics from 16 Mimulus species and analyzed reference genomes from 6 species, and discovered Mimulus species have evolved at least three different telomere sequences: (AAACCCT)n, (AAACCCG)n, and (AAACCG)n. Unexpectedly, we discovered several species with TR duplications and the paralogs had functional consequences that could influence telomere evolution. For instance, M. lewisii had two sequence-divergent TR paralogs and synthesized a telomere with sequence heterogeneity, consisting of AAACCG and AAACCCG repeats. Evolutionary analysis of the M. lewisii TR paralogs indicated it had arisen from a transposition-mediate duplication process. Further analysis of the TR from multiple Mimulus species showed the gene had frequently transposed and inserted into new chromosomal positions during Mimulus evolution. From our results, we propose the TR transposition, duplication, and divergence model to explain the evolutionary sequence turnovers in Mimulus and potentially all plant telomeres.

evolutionary biology↗

Griottes: a generalist tool for network generation from segmented tissue images

Microscopy techniques and image segmentation algorithms have improved dramatically this decade, leading to an ever increasing amount of biological images and a greater reliance on imaging to investigate biological questions. This has created a need for methods to extract the relevant information on the behaviors of cells and their interactions, while reducing the amount of computing power required to organize this information. This task can be performed by using a network representation in which the cells and their properties are encoded in the nodes, while the neighborhood interactions are encoded by the links. Here we introduce Griottes, an open-source tool to build the "network twin" of 2D and 3D tissues from segmented microscopy images. We show how the library can provide a wide range of biologically relevant metrics on individual cells and their neighborhoods, with the objective of providing multi-scale biological insights. The librarys capacities are demonstrated on different image and data types. This library is provided as an open-source tool that can be integrated into common image analysis workflows to increase their capacities.

bioinformatics↗