Biology subjects

Fraslin, C.

Publications and source records attributed to Fraslin, C..

8 recordsLinked to original sources

bioRxiv2025

Transcriptomic study of WSSV infection in Litopenaeus vannamei lymphoid organ via single nuclei RNA sequencing

BackgroundAquaculture is the fastest growing farmed food sector and is a key part of global food security. Crustacean aquaculture, while being one of the most profitable sectors, is threatened by pathogenic diseases such as white spot disease (WSD), which results in severe stock losses and threatens animal health and welfare. In this study, we used novel techniques to study the impact of white spot syndrome virus (WSSV), the causative agent of WSD, on Pacific whiteleg shrimp (Litopenaeus vannamei), and uncover additional information that may be used in creating WSSV-resistant shrimp stocks. ResultsWe successfully developed a novel nuclei isolation protocol optimized for shrimp tissues to prepare our samples for single nuclei RNA-sequencing following a pathogen challenge comprising of 32 adult whiteleg shrimp infected with WSSV either through their feed or by injection. We constructed the first penaeid shrimp lymphoid organ cell atlas to improve our understanding of the characteristics of this immune organ, constructed the UMAPs and identified marker genes that define distinct cell clusters to reveal the biological functions of different cell types within this organ. ConclusionBy comparing gene expression between the control and WSSV-infected samples we uncovered multiple genes of interest that that have the potential to be used as targets for CRISPR gene editing for WSSV-resistance in Pacific whiteleg shrimp. These genes have the potential to be valuable assets for future gene editing studies in commercially important penaeid shrimp species. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=90 SRC="FIGDIR/small/693182v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1be071org.highwire.dtl.DTLVardef@2c3da6org.highwire.dtl.DTLVardef@835e67org.highwire.dtl.DTLVardef@aacff1_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

Optimization of reference population for imputation of low-density SNPs panel for genomic prediction in Atlantic salmon.

In recent years many advances have been made towards developing cost-efficient low-density genomic tools for a wider implementation of genomic selection in aquaculture breeding programmes. Genotype imputation from very low-density (LD) SNP panels of just a few hundred markers to high-density (HD) SNP panels has become a promising strategy to reduce the cost of genotyping while maintaining accurate genomic prediction. The objective of this study is to assess the impact of the makeup of HD-genotyped reference populations on i) the accuracy of imputation for LD-genotyped individuals and ii) the accuracy of genomic prediction for three traits of importance in Atlantic salmon production: growth, resistance to cardiomyopathy syndrome and resistance to pancreas disease. An Atlantic salmon population genotyped with a 47K SNP array was used for the study, along with an in silico LD panel of 554 SNPs. Five reference population scenarios for imputation were tested, which could include only the parents of the candidates for selection, a combination of parents and candidates, or just candidates. All scenarios resulted in highly accurate imputation rates (over 80%) except when the HD reference population was only composed of selection candidates. Nonetheless, the accuracy of imputation barely had an impact on the accuracy of genomic prediction, as the imputed datasets performed very similarly to the HD-panel. Adding a proportion of the offspring to the reference population, in addition to the parents, did not result in any benefit in terms of genomic prediction. Imputation is a cost-effective and robust option for genomic selection in aquaculture.

genetics↗

bioRxiv2025

Amoebic gill disease (AGD) in Atlantic Salmon investigated through a holo-omic lens

Interactions between host genetics and the resident microbiota are complex. Understanding these interactions offers interesting alternatives for addressing gill health and disease resistance in salmonids. Amoebic gill disease (AGD), caused by Neoparamoeba perurans, remains a threat to Atlantic salmon, particularly in aquaculture settings where prevention and treatment options are scant. Selective breeding or genetic engineering towards increased AGD resilience present viable prevention strategies. While a number of studies have addressed AGD resistance in Atlantic salmon using transcriptomic and quantitative genetic approaches, the role of the Atlantic salmon gill microbiota in influencing AGD resilience and susceptibility needs further investigation. Addressing this, we leveraged a holo-omic approach using 16S rRNA bacterial profiling, and quantitative genetics, by considering the microbiota as an extended resistance trait of the salmon. We investigated the microbiota of AGD challenged Atlantic salmon in terms of two common resistance indicator traits: gill score and amoebic load. Subsequently we performed a GWAS using both the traditional indicator traits and traits of the microbiota. We found that the gill microbiota of the AGD affected salmon in this study was dominated by two bacterial families Simkaniaceae and Arcobacteracea. We found that microbial diversity and the relative abundance of Simkaniaceae, potentially derived from the amoeba, varied moderately with indicator traits. Additionally we identified several genomic regions that showed suggestive association with gill score and traits of the microbiota, and explored potential candidate genes for AGD resistance. Although much is still unclear regarding gill microbiota dynamics in gill disease, this study highlights the potential of addressing AGD through an integrative approach that considers the interplay between host genetics, the microbiota, and their roles in disease resistance.

genomics↗

bioRxiv2024

In-depth investigation of genome to refine QTL positions for spontaneous sex-reversal in XX rainbow trout

Sex determination is a flexible process in fish, controlled by genetics or environmental factors or a combination of both depending on the species. Revealing the underlying molecular mechanisms may have important implications for research on reproductive development in vertebrates, as well as sex-ratio control and selective breeding in fish. Phenotypic sex in rainbow trout is primarily controlled by a XX/XY male heterogametic sex determination system. Unexpectedly in genetically XX all-female farmed populations, a small proportion of males or intersex individuals are regularly observed. This spontaneous masculinisation is a highly heritable trait, controlled by minor sex-modifier genes that remain unknown, although several QTL regions were detected in previous studies. In this work we used genome-based approaches and various statistical methods to investigate these QTL regions. We validated in six different French farmed populations DNA markers we had previously identified in a different commercial population on chromosomes Omy1, Omy12 and Omy20. We also identified functional candidate genes located that may be involved in spontaneous masculinisation by reducing germ cell proliferation and repressing oogenesis of XX-rainbow trout in the absence of the master sex determining gene. In particular, syndig1, tlx1 and hells on Omy1, as well as khdrbs2 and csmd1 on Omy20 deserve further investigation as potential sex-modifier genes to precise their functional roles as well as their interaction with rearing temperature. Those findings could be used to produce all-female populations that are preferred by farmers due to a delayed maturation of females and higher susceptibility of male trout to diseases.

genetics↗

bioRxiv2023

Potential of imputation for cost-efficient genomic selection for resistance to Flavobacterium columnare in rainbow trout (Oncorhynchus mykiss)

BackgroundFlavobacterium columnare is the pathogen agent of columnaris disease, a major emerging disease affecting rainbow trout aquaculture. Selective breeding using genomic selection has potential to achieve cumulative improvement of host resistance. However, genomic selection is expensive partly due to the cost of genotyping high numbers of animals using high-density SNP arrays. The objective of this study was to assess the efficiency of genomic selection for resistance to F. columnare using in silico low-density (LD) panels combined with imputation. After a natural outbreak of columnaris disease, 2,874 challenged fish and 469 fish from the parental generation (n=81 parents) were genotyped with 27,907 SNPs. The efficiency of genomic prediction using LD-panels was assessed for panels of 10 different densities, created in silico using two sampling methods, random and equally spaced. All LD-panels were also imputed to the full 28K HD-panel using the parental generation as the reference population, and genomic predictions were reevaluated. The potential of prioritizing SNPs showing association with resistance to F. columnare was also tested for the six lower densities. ResultsSimilar results were obtained with random and equally spaced sampling of SNPs for accuracy of both imputation and genomic predictions. Using LD-panels of at least 3,000 makers or lower density panels (as low as 300 markers) combined with imputation resulted in comparable accuracy to the 28K HD-panel and 11% higher accuracy than pedigree-based predictions. ConclusionsCompared to using the commercial HD-panel, LD-panels with imputation may provide a more affordable route to genomic prediction of breeding values, supporting wider adoption of genomic selection in aquaculture breeding programmes.

genetics↗

bioRxiv2022

Genome-wide association and genomic prediction of resistance to Flavobacterium columnare in a farmed rainbow trout population

Columnaris disease is an emerging disease affecting farmed rainbow trout (Oncorhynchus mykiss) globally. In aquaculture breeding, genomic selection has been increasingly used to improve traits that are difficult to measure on candidate fish (such as disease resistance traits). Following a natural outbreak of columnaris disease, 3,054 exposed fish and their 81 parents (33 dams and 48 sires) were genotyped with the 57K SNP Axiom trout genotyping array. Genetic parameters of host resistance (measured as a binary survival trait) were estimated, a genome wide association study was performed, and the accuracy of pedigree-based and genomic prediction was estimated. After quality controls, 2,874 challenged fish (1,403 dead fish and 1,471 alive fish) and 78 parents genotyped for 27,907 SNPs remained. Pedigree based heritability was estimated to be 0.18 and 0.35 on the observed and underlying scale, respectively. Genomic heritability was estimated to be 0.21 and 0.43 on the observed and underlying scale, respectively. A quantitative trait loci (QTL) was detected on chromosome Omy3, significant at the genome-wide level, along with several suggestive QTLs on two other chromosomes. The additive effect on mortality proportion of the peak SNP from Omy3 was estimated to be 0.11 (0.018; se). Pedigree-based prediction accuracy was 0.59, and the use of genomic evaluation increased the prediction accuracy by at least 13.6%. Using the second iteration of a weighted genomic-based evaluation increased the prediction accuracy by 18.6% compared to the pedigree-based model. These results suggest that resistance is a suitable target trait for genetic improvement by selective breeding, and genomic selection may be a useful approach to speed up this process.

genomics↗

bioRxiv2021

The impact of genetic relationship between training and validation populations on genomic prediction accuracy in Atlantic salmon

The potential of genomic selection to improve production traits has been widely demonstrated in many aquaculture species. Atlantic salmon breeding programmes typically consist of sibling testing schemes, where traits that cannot be measured on the selection candidates are measured on the candidates siblings (such as disease resistance traits). While annual testing on close relatives is effective, it is expensive due to high genotyping and phenotyping costs. Therefore, accurate prediction of breeding values in distant relatives could significantly reduce the cost of genomic selection. The aims of this study were (i) to evaluate the impact of decreasing the genomic relationship between the training and validation populations on the accuracy of genomic prediction for two key target traits; body weight and resistance to sea lice; and (ii) to assess the interaction of genetic relationship with SNP density, a major determinant of genotyping costs. Phenotype and genotype data from two year classes of a commercial breeding population of Atlantic salmon were used. The accuracy of genomic predictions obtained within a year class was similar to that obtained combining the data from the two year classes for sea lice count (0.49 - 0.48) and body weight (0.63 - 0.61), but prediction accuracy was close to zero when the prediction was performed across year groups. Systematically reducing the relatedness between the training and validation populations within a year class resulted in decreasing accuracy of genomic prediction; when the training and validation populations were set up to contain no relatives with genomic relationships >0.3, the accuracies fell from 0.48 to 0.27 for sea lice count and from 0.63 to 0.29 for body weight. Lower relatedness between training and validation populations also tended to result in highly biased predictions. No clear interaction between decreasing SNP density and relatedness between training and validation population was found. These results confirm the importance of genetic relationships between training and selection candidate populations in salmon breeding programmes, and suggests that prediction across generations using existing approaches would severely compromise the efficacy of genomic selection.

genomics↗

bioRxiv2020

Genetic determinism of spontaneous masculinisation in XX female rainbow trout: new insights using medium throughput genotyping and whole-genome sequencing

Rainbow trout has a male heterogametic (XY) sex determination system controlled by a major sex-determining gene, sdY. Unexpectedly, a few phenotypically masculinised fish are regularly observed in all-female farmed trout stocks. To better understand the genetic determinism underlying spontaneous maleness in XX-rainbow trout, we recorded the phenotypic sex of 20,210 XX-rainbow trout from a French farm at 10 and 15 months post-hatching. The masculinisation rate was 1.45%. We performed two genome-wide association studies (GWAS) using both medium-throughput genotyping (31,811 SNPs) and whole-genome sequencing (WGS, 8.7 million SNPs) on a subsample of 1,139 individuals classified as females, intersex or males. The genomic heritability of maleness ranged between 0.48 and 0.62 depending on the method and number of SNPs used for estimation. At the 31K SNPs level, we detected four QTLs on three chromosomes (Omy1, Omy12 and Omy20). Using WGS information, we narrowed down the positions of the two QTLs detected on Omy1 to 96 kb and 347 kb respectively, with the second QTL explaining up to 14% of the total genetic variance of maleness. Within this QTL, we detected three putative candidate genes, fgfa8, cyp17a1 and an uncharacterised protein (LOC110527930), which might be involved in spontaneous maleness of XX-female rainbow trout.

genomics↗