Biology subjects

Sulpice, R.

Publications and source records attributed to Sulpice, R..

2 recordsLinked to original sources

bioRxiv2024

Draft genome of Palmaria palmata and intraspecific genetic variations in the North-East Atlantic

The rhodophyte Palmaria palmata (L.) Weber & Mohr is one of the target species of a growing European seaweed industry due to its high content of protein and essential amino acids which makes it suitable for human food, dietary supplements, and as salmon feed. However, the lack of a published nuclear genome limits phylogenetics analyses and gene function investigations which could help the development of a breeding programme. We present the first draft genome of P. palmata that was obtained with PacBio HiFi long read sequencing with average coverage of 10x, consisting of an assembly of 1.05 Gb, N50=2.75Mb and BUSCO completeness of 72.1%. Additionally, a population study on the whole genome of 33 P. palmata individuals from across the Northern East Atlantic area found three main clusters consistent with their geographic distribution: (1) Denmark and Norway, (2) France and western Ireland, (3) Faroe Islands. All individuals from Northern Ireland share ancestry with western Ireland and Denmark, and some individuals from the Faroe Islands show admixture from Faroe, western Ireland and Northern Ireland. These results represent a fundamental step towards breeding and genetic studies to further explore the vastly unexploited economic potential of Palmaria palmata. Highlights- We report the first draft genome of Palmaria palmata, from PacBio HiFi long reads. - The size of the genome, 1.05 Gb, is among the largest so far among the Rhodophyta. - Busco completeness of 72.1% and contig N50 of 2.75 Mb indicate good quality. - The genomes of 33 more individuals from North Atlantic Europe have been sequenced. - Phylogenetic analysis found three clusters consistent with geographic distribution.

genomics↗

bioRxiv2024

AlGrow: a graphical interface for easy, fast and accurate area and growth analysis of heterogeneously colored targets.

Image analysis is widely used in plant biology to determine growth rates and other phenotypic characters, with segmentation into foreground and background being a primary challenge. Statistical clustering and learning approaches can reduce the need for user input into this process, though these are computationally demanding, can generalise poorly and are not intuitive to end users. As such, simple strategies that rely on the definition of a range of target colors are still frequently adopted. These are limited by the geometries in color space that are implicit to their definition; i.e. thresholds define cuboid volumes and selected colors with a radius define spheroid volumes. A more comprehensive specification of target color is a hull, in color space, enclosing the set of colors in the image foreground. We developed AlGrow, a software tool that allows users to easily define hulls by clicking on the source image or a three-dimensional projection of its colors. We implemented convex hulls and then alpha-hulls, i.e. a limit applied to hull edge length, to support concave surfaces and disjoint color volumes. AlGrow also provides automated annotation by detecting internal circular markers, such as pot margins, and applies relative indexes to support movement. Analysis of publicly available Arabidopsis image series and metadata demonstrated effective automated annotation and mean Dice coefficients of >0.95 following training on only the first and last images in each series. AlGrow provides both graphical and command line interfaces and is released free and open-source with compiled binaries for the major operating systems.

bioinformatics↗