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Mestre, C.

Publications and source records attributed to Mestre, C..

3 recordsLinked to original sources

Prime-Editing in Marchantia paleacea: Expanding the Genome-Editing Toolbox in Bryophytes

Since the development of CRISPR-based genome editing tools, a number of novel technologies have emerged. This includes Prime-Editing that acts as a search and replace genome editing tool. Prime-Editing has been deployed across multiple clades, including in a few flowering plants. Here, we report on the development of an efficient Prime Editor (PE) for the model bryophyte Marchantia. Initial tests were conducted on Acetolactate Synthase as a target and revealed an average efficiency above 40%. The system has been developed in the GoldenGate cloning system, facilitating construct design. The development of PE in Marchantia expands the Genome-Editing tools available for this emerging model in plant biology.

plant biology↗

Enhancer/gene relationships: need for more reliable genome-wide reference sets

Differences in cells functions arise from differential action of regulatory elements, in particular enhancers. Like promoters, enhancers are genomic regions bound by transcription factors (TF) that activate the expression of one or several genes by getting physically close to them in the 3D space of the nucleus. As there is increasing evidence that variants associated with common diseases are located in enhancers active in cell types relevant to these diseases, knowing the set of enhancers and more importantly the sets of genes activated by each enhancer (the so-called enhancer/gene or E/G relationships) in a cell type, will certainly help understanding these diseases. There are three broad approaches for the genome-wide identification of E/G relationships in a cell type: (1) genetic link methods or eQTL, (2) functional link methods based on 1D functional data such as open chromatin, histone mark and gene expression and (3) spatial link methods based on 3D data such as HiC. Since (1) and (3) are costly, there has been a focus on developing functional link methods and using data from (1) and (3) to evaluate them, however there is still no consensus on the best functional link method to date. For this reason we decided to start from the two latest benchmarks of the field, namely from the CRISPRi-FlowFISH (CRiFF) technique and from 3D and eQTL data in BENGI, and to evaluate the two methods claimed to be the best one on each of these benchmark studies, namely the ABC model and the Average-Rank method respectively, on the other methods reference data. Not only did we manage to reproduce the results of the two benchmarks but we also saw that none of the two methods performed best on the two reference data. While CRiFF reference data are very reliable, it is not genome-wide and is mostly available on a cancer cell type. On the other hand BENGI is genome-wide but may contain many false positives. This study therefore calls for new reliable and genome-wide E/G reference data rather than new functional link E/G identification methods.

bioinformatics↗

Discovering genomic regions associated with the phenotypic differentiation of European local pig breeds

BackgroundIntensive selection of modern pig breeds resulted in genetic improvement of productive traits while local pig breeds remained less performant. As they have been bred in extensive systems, they have adapted to specifical environmental conditions resulting in a rich genotypic and phenotypic diversity. This study is based on European local pig breeds genetically characterized using DNA-pool sequencing data and phenotypically characterized using breed level phenotypes related to stature, fatness, growth and reproductive performance traits. These data were analyzed using a dedicated approach to detect selection signatures linked to phenotypic traits in order to uncover potential candidate genes that may be under adaptation to specific environments. ResultsGenetic data analysis of European pig breeds revealed four main axes of genetic variation represented by Iberian and modern breeds (i.e. Large White, Landrace, and Duroc). In addition, breeds clustered according to their geographical origin, for example French Gascon and Basque breeds, Italian Apulo Calabrese and Casertana breeds, Spanish Iberian and Portuguese Alentejano breeds. Principal component analysis of phenotypic data distinguished between larger and leaner breeds with better growth potential and reproductive performance on one hand and breeds that were smaller, fatter, and had low growth and reproductive efficiency on the other hand. Linking selection signatures with phenotype identified 16 significant genomic regions associated with stature, 24 with fatness, 2 with growth and 192 with reproduction. Among them, several regions contained candidate genes with possible biological effect on stature, fatness, growth and reproduction performance traits. For example, strong associations were found for stature in two regions containing the ANXA4 and ANTXR1 genes, for fatness containing the DNMT3A and POMC genes and for reproductive performance containing the HSD17B7 gene. ConclusionsThe present study on European local pig breeds used a dedicated approach for searching selection signatures supported by phenotypic data at the breed level to identify potential candidate genes that may have adapted to different living environments and production systems. Results can be useful to define conservation programs of local pig breeds.

genetics↗