Biology subjects

Yanez, J.

Publications and source records attributed to Yanez, J..

12 recordsLinked to original sources

bioRxiv2024

100 years domestication of penaeid shrimp and meta-analysis of breeding traits

Penaeid shrimp farming plays a pivotal role in ensuring future food security and promoting economic sustainability. Compared to the extensive long history of domestication observed in terrestrial agriculture species, the domestication and selective breeding of penaeids are relatively recent endeavors. Selective breeding aimed at improving production traits holds significant promise for enhancing efficiency and reducing the environmental impact of shrimp farming, thereby contributing to its long-term sustainability. Assessing genotype-by-environment (G-by-E) interactions is essential in breeding programs to ensure that improved penaeid shrimp strains perform consistently across different production environments, with genomic selection proving more effective than sib-testing alone in mitigating environmental sensitivity. Genome editing tools like CRISPR/Cas9 offer significant potential to accelerate genetic gains in penaeid shrimp by enabling rapid introduction of desired genetic changes, with recent advancements showing promising results in achieving high transfection efficiency in shrimp embryos. Additionally, artificial intelligence and machine learning are being leveraged to streamline phenotyping and enhance decision-making in shrimp breeding and farming, improving efficiency and accuracy in managing traits and predicting disease outbreaks. Herein, we provide an overview and update on the domestication of penaeid shrimp, including the current status of domestication for principal farmed species, key milestones in domestication history, targeted breeding traits in selective breeding programs, the advantages of integrating genomeic selection for enhancing production traits, and future directions for selective breeding of penaeid shrimp.

genetics↗

bioRxiv2022

Meta-analysis of GWAS for sea lice load in Atlantic salmon

Sea lice (Caligus rogercresseyi) is an ectoparasite that causes major production losses in the salmon aquaculture industry of the southern hemisphere. Atlantic salmon (Salmo salar) is an important salmonid for the aquaculture industry and a species which is highly susceptible to sea lice infestation. Genetic variation for resistance to sea lice, defined as parasite load, has been found in Atlantic salmon. In addition, sea lice load has been shown to be a polygenic trait, controlled by several quantitative trait loci (QTL) which have small to medium effect, making them difficult to map with sufficient statistical power when sample sizes are limited. The use of medium density single nucleotide polymorphisms (SNP) can also adversely affect the success of identifying genetic variants significantly associated to sea lice load. In order to improve the ability to detect QTL significantly associated to sea lice load, we combined genotype imputation from medium- to high SNP-density and performed genome-wide association studies (GWAS) across different populations of Atlantic salmon. The imputation of genotypes of 6,144 fish challenged against sea lice from four year-classes was performed to increase density from 70K SNPs to 600K SNPs. A meta-GWAS was then carried out for three different traits: lice count, lice density and log-lice density. Using this approach, we detected a genomic region highly associated to sea lice load on Atlantic salmon chromosomes (ssa) 3 and 12 pronounced peaks and several other regions surpassing the significance threshold across almost all other chromosomes. We also identified important genes within the QTL regions, many of these genes are involved in tissue reparation, such as Mucin-16-like isoform X2 and Filamentous growth regulator 23-like isoform X1. The QTL region on ssa03 also contained cytoskeletal-modifying and immune response related genes such as Coronin 1A and Claudin. Our results confirm the highly polygenic architecture of sea lice load, but they also show that high experimental power can lead to the identification of candidate genes and thus to increased insight into the biology of sea lice resistance in Altantic salmon.

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

Investigating mechanisms underlying genetic resistance to Salmon Rickettsial Syndrome in Atlantic salmon using RNA sequencing

BackgroundSalmon Rickettsial Syndrome (SRS), caused by Piscirickettsia salmonis, is one of the primary causes of morbidity and mortality in Atlantic salmon aquaculture, particularly in Chile. Host resistance is a heritable trait, and functional genomic studies have highlighted genes and pathways important in the response of salmon to the bacteria. However, the functional mechanisms underpinning genetic resistance are not yet well understood. In the current study, a large population of salmon pre-smolts were challenged with P. salmonis, with mortality levels recorded and samples taken for genotyping. In parallel, head kidney and liver samples were taken from animals of the same population with high and low genomic breeding values for resistance, and used for RNA-Sequencing to compare their transcriptome profile both pre and post infection. ResultsA significant and moderate heritability (h2 = 0.43) was shown for the trait of binary survival. Genome-wide association analyses using 38K imputed SNP genotypes across 2,251 animals highlighted that resistance is a polygenic trait. Several thousand genes were identified as differentially expressed between controls and infected samples, and enriched pathways related to the host immune response were highlighted. In addition, several networks with significant correlation with SRS resistance breeding values were identified, suggesting their involvement in mediating genetic resistance. These included apoptosis, cytoskeletal organisation, and the inflammasome. ConclusionsWhile resistance to SRS is a polygenic trait, this study has highlighted several relevant networks and genes that are likely to play a role in mediating genetic resistance. These genes may be future targets for functional studies, including genome editing, to further elucidate their role underpinning genetic variation in host resistance.

genomics↗

bioRxiv2020

Detection of selection signatures in farmed coho salmon (Oncorhynchus kisutch) using dense genome-wide information

Animal domestication and artificial selection give rise to gradual changes at the genomic level in populations. Subsequent footprints of selection known as selection signatures or selective sweeps have been traced in the genomes of many animal livestock species by exploiting variations in linkage disequilibrium patterns and/or reduction of genetic diversity. Domestication of most aquatic species is recent in comparison with land animals, and salmonids are one of the most important fish species in aquaculture. Coho salmon (Oncorhynchus kisutch), cultivated primarily in Chile, has been subject to breeding programs to improve growth, disease resistance traits, and flesh color. This study aimed to identify selection signatures that may be involved in adaptation to culture conditions and traits of productive interest. To do so, individuals of two domestic populations cultured in Chile were genotyped with 200 thousand SNPs, and analyses were conducted using iHS, XP-EHH and CLR. Several signatures of selection on different chromosomal regions were detected across both populations. Some of the identified regions under selection contained genes such anapc2, alad, chp2 and myn that have been previously associated with body weight in Atlantic salmon or sec24d and robo1 that have been associated with disease resistance to Piscirickettsia salmonis in coho salmon. Findings in our study can contribute to an integrated genome-wide map of selection signatures, to help identify the genetic mechanisms of phenotypic diversity in coho salmon.

genetics↗

bioRxiv2020

Estimates of autozygosity through runs of homozygosity in farmed coho salmon

The characterization of runs of homozygosity (ROH), using high-density single nucleotide polymorphisms (SNPs) allows inferences to be made about the past demographic history of animal populations and the genomic ROH has become a common approach to characterize the inbreeding. We aimed to analyze and characterize ROH patterns and compare different genomic and pedigree-based methods to estimate the inbreeding coefficient in two pure lines (POP A and B) and one recently admixed line (POP C) of coho salmon breeding nuclei, genotyped using a 200K Affymetrix Axiom(R) myDesign Custom SNP Array. A large number and greater mean length of ROH were found for the two "pure" lines and the recently admixed line (POP C) showed the lowest number and smaller mean length of ROH. The ROH analysis for different length classes suggests that all three coho salmon lines the genome is largely composed of a high number of short segments (<4 Mb), and for POP C no segment >16 Mb was found. A high variable number of ROH, mean length and inbreeding values across chromosomes; positively the consequence of artificial selection. Pedigree-based inbreeding values tended to underestimate genomic-based inbreeding levels, which in turn varied depending on the method used for estimation. The high positive correlations between different genomic-based inbreeding coefficients suggest that they are consistent and may be more accurate than pedigree-based methods, given that they capture information from past and more recent demographic events, even when there are no pedigree records available.

genomics↗

bioRxiv2020

Mate selection provides similar genetic progress and average inbreeding than optimum contribution selection in the long-term

Optimum contribution selection (OCS) and mate selection (MS) are alternative strategies to maximize genetic gain under controlled rates of inbreeding. There is evidence in the literature that MS outperforms OCS in controlling inbreeding under the same expected genetic gain in the short-term. It is unclear, however, if the same would occur in the long-term. This study aimed to compare OCS and MS regarding short and long-term genetic progress and inbreeding, using simulated data. The structure of the simulated population aimed to mimic an aquaculture breeding program. Twenty discrete generations were simulated, considering 50 families and 2,000 offspring per generation, and a trait with a heritability of 0.3. OCS and MS were applied using a differential evolution (DE) algorithm, under an objective function that accounted for genetic merit, inbreeding of the future progeny and coancestry among selection candidates. For OCS, the optimization process consisted of selection based on optimum contribution followed by minimum inbreeding mating. Objective functions using different weights on coancestry were tested. For each application, 20 replicates were simulated and the results were compared based on their average. Both strategies, OCS and MS, were very effective in controlling inbreeding over the generations. In the short-term, MS was more efficient than OCS in controlling inbreeding under the same genetic gain. In the long-term, OCS and MS resulted in similar genetic progress and average inbreeding, under the same penalty on coancestry.

genetics↗

bioRxiv2019

Whole genome re-sequencing reveals recent signatures of selection in three strains of farmed Nile tilapia (Oreochromis niloticus)

Nile tilapia (Oreochromis niloticus Linnaeus, 1758) belong to the second most cultivated group of fish in the world, mainly because of its favorable characteristics for production. Genetic improvement programs in this species began in the late 1980s to enhance some traits of commercial interest. The resulting domestication process of Nile tilapia may have modified the genome through selective pressure, leaving signals that can be detected at the molecular level. In this work, signatures of selection were identified using genome-wide SNP data, using two complementary methods based in extended haplotype homozygosity (EHH)._Whole-genome sequencing of 326 individuals from three strains (A, B and C) of farmed tilapia from two countries (Brazil and Costa Rica) was carried out using Illumina HiSeq 2500 technology. After applying conventional SNP-calling and quality-control pipelines, a total of ~1.3M high-quality SNPs were inferred and used as input for the Integrated Haplotype Score (|iHS|) and standardized log-ratio of integrated EHH between pairs of populations (Rsb) methods. We detected 16, 174 and 96 candidate genes subjected to selection in strain A, B, and C, respectively. These candidate genes represent putative genomic landmarks that could contain functions of biological and commercial interest.

genomics↗

bioRxiv2019

Genome-wide association study and low-cost genomic predictions for growth and fillet yield in Nile tilapia (Oreochromis niloticus)

Fillet yield (FY) and harvest weight (HW) are economically important traits in Nile tilapia production. Genetic improvement of these traits, especially for FY, are lacking, due to the absence of efficient methods to measure the traits without sacrificing fish and the use of information from relatives to selection. However, genomic information could be used by genomic selection to improve traits that are difficult to measure directly in selection candidates, as in the case of FY. The objectives of this study were: (i) to perform genome-wide association studies (GWAS) to dissect the genetic architecture of FY and HW, (ii) to evaluate the accuracy of genotype imputation and (iii) to assess the accuracy of genomic selection using true and imputed low-density (LD) single nucleotide polymorphism (SNP) panels to determine a cost-effective strategy for practical implementation of genomic information in tilapia breeding programs. The data set consisted of 5,866 phenotyped animals and 1,238 genotyped animals (108 parents and 1,130 offspring) using a 50K SNP panel. The GWAS were performed using all genotyped and phenotyped animals. The genotyped imputation was performed from LD panels (LD0.5K, LD1K and LD3K) to high-density panel (HD), using information from parents and 20% of offspring in the reference set and the remaining 80% in the validation set. In addition, we tested the accuracy of genomic selection using true and imputed genotypes comparing the accuracy obtained from pedigree-based best linear unbiased prediction (PBLUP) and genomic predictions. The results from GWAS supports evidence of the polygenic nature of FY and HW. The accuracy of imputation ranged from 0.90 to 0.98 for LD0.5K and LD3K, respectively. The accuracy of genomic prediction outperformed the estimated breeding value from PBLUP. The use of imputation for genomic selection resulted in an increased relative accuracy independent of the trait and LD panel analyzed. The present results suggest that genotype imputation could be a cost-effective strategy for genomic selection in tilapia breeding programs.

genomics↗

bioRxiv2019

Genome-wide association analysis for resistance to infectious pancreatic necrosis virus identifies candidate genes involved in viral replication and immune response in rainbow trout (Oncorhynchus mykiss)

Infectious pancreatic necrosis (IPN) is a viral disease with considerable negative impact on the rainbow trout (Oncorhynchus mykiss) aquaculture industry. The aim of the present work was to detect genomic regions that explain resistance to infectious pancreatic necrosis virus (IPNV) in rainbow trout. A total of 2,278 fish from 58 full-sib families were challenged with IPNV. Of the challenged fish, 768 individuals were genotyped (488 resistant and 280 susceptible), using a 57K single nucleotide polymorphisms (SNPs) panel Axiom(R), Affymetrix(R). A genome-wide association study (GWAS) was performed using the phenotypes time to death (TD) and binary survival (BS), along with the genotypes of the challenged fish using a Bayesian model (Bayes C). Heritabilities for resistance to IPNV estimated using pedigree information, were 0.39 and 0.32 for TD and BS, respectively. Heritabilities for resistance to IPNV estimated using genomic information, were 0.50 and 0.54 for TD and BS, respectively. The Bayesian GWAS detected a SNP located on chromosome 5 explaining 18% of the genetic variance for TD. A SNP located on chromosome 23 was detected explaining 9% of the genetic variance for BS. The proximity of Sentrin-specific protease 5 (SENP5) to a significant SNP makes it a candidate gene for resistance against IPNV. However, the moderate-low proportion of variance explained by the detected marker leads to the conclusion that the incorporation of all genomic information, through genomic selection, would be the most appropriate approach to accelerate genetic progress for the improvement of resistance against IPNV in rainbow trout.

genomics↗

bioRxiv2018

Discovery and functional annotation of quantitative trait loci affecting resistance to sea lice in Atlantic salmon

Sea lice (Caligus rogercresseyi) are ectoparasitic copepods which have a large negative economic and welfare impact in Atlantic salmon (Salmo salar) aquaculture, particularly in Chile. A multi-faceted prevention and control strategy is required to tackle lice, and selective breeding contributes via cumulative improvement of host resistance to the parasite. While host resistance has been shown to be heritable, little is yet known about the individual loci that contribute to this resistance, the potential underlying genes, and their mechanisms of action. In this study we took a multifaceted approach to identify and characterise quantitative trait loci (QTL) affecting hose resistance in a population of 2,688 Caligus-challenged Atlantic salmon post-smolts from a commercial breeding programme. We used low and medium density genotyping to collect genome-wide SNP marker data for all animals. Moderate heritablility estimates of 0.28 and 0.24 were obtained for lice density (as a measure of host resistance) and growth during infestation respectively. Three QTL explaining between 7 and 13 % of the genetic variation in resistance to sea lice (as represented by the traits of lice density) were detected on chromosomes 3, 18 and 21. Characterisation of these QTL regions was undertaken using RNA sequencing and pooled whole genome sequencing data. This resulted in the identification of a shortlist of potential underlying causative genes, and candidate functional mutations for further study. For example, candidates within the chromosome 3 QTL include a putative premature stop mutation in TOB1 (an anti-proliferative transcription factor involved in T cell regulation) and an uncharacterized protein which showed significant differential allelic expression (implying the existence of a cis-acting regulatory mutation). While host resistance to sea lice is polygenic in nature, the results of this study highlight significant QTL regions together explaining a moderate proportion of the heritability of the trait. Future investigation of these QTL may enable improved knowledge of the functional mechanisms of host resistance to sea lice, and incorporation of functional variants to improve genomic selection accuracy.

genetics↗

bioRxiv2017

Gene expression response to sea lice in Atlantic salmon skin: an RNA-Seq comparison between resistant and susceptible animals

BackgroundSea lice are parasitic copepods that cause large economic losses to salmon aquaculture worldwide. Frequent chemotherapeutic treatments are typically required to control this parasite, and alternative measures such as breeding for improved host resistance are desirable. Insight into the host-parasite interaction and mechanisms of host resistance can lead to improvements in selective breeding, and potentially novel treatment targets. In this study, RNA sequencing was used to study the skin transcriptome of Atlantic salmon parasitized with sea lice (C. rogercresseyi). The overall aims were to compare the transcriptomic profile of skin at louse attachment sites and healthy skin, and to assess differences between animals with varying levels of resistance to the parasite.\n\nResultsAtlantic salmon were challenged with C. rogercresseyi, growth and lice count measurements were taken for each fish. 21 animals were selected and RNA-Seq was performed on skin from a louse attachment site, and skin distal to attachment sites for each animal. These animals were classified into family-balanced groups according to the traits of resistance (high vs low lice count), and growth during infestation (an indication of tolerance). Overall comparison of skin from louse attachment sites versus healthy skin showed that 4,355 genes were differentially expressed, indicating local up-regulation of several immune pathways and activation of tissue repair mechanisms. Comparison between resistant and susceptible animals highlighted expression differences in several immune response and pattern recognition genes, and also myogenic and iron availability factors. Genomic regions showing signs of differentiation between resistant and susceptible fish were identified using an Fst analysis.\n\nConclusionsComparison of the skin transcriptome between louse attachment sites and healthy skin has yielded a detailed profile of genes and pathways with putative roles in the local host immune response to C. rogercresseyi. The difference in skin gene expression profile between resistant and susceptible animals led to the identification of several immune and myogenic pathways potentially involved in host resistance. Components of these pathways may be targets for studies aimed at improved or novel treatment strategies, or to prioritise candidate functional polymorphisms to enhance genomic selection for host resistance in commercial salmon farming.

genetics↗