Genetics Selection Evolution最新文献

{"title":"Estimation of genetic parameters for the implementation of selective breeding in commercial insect production","authors":"Laura Skrubbeltrang Hansen, Stine Frey Laursen, Simon Bahrndorff, Morten Kargo, Jesper Givskov Sørensen, Goutam Sahana, Hanne Marie Nielsen, Torsten Nygaard Kristensen","doi":"10.1186/s12711-024-00894-7","DOIUrl":"https://doi.org/10.1186/s12711-024-00894-7","url":null,"abstract":"There is a burgeoning interest in using insects as a sustainable source of food and feed, particularly by capitalising on various waste materials and by-products that are typically considered of low value. Enhancing the commercial production of insects can be achieved through two main approaches: optimising environmental conditions and implementing selective breeding strategies. In order to successfully target desirable traits through selective breeding, having a thorough understanding of the genetic parameters pertaining to those traits is essential. In this study, a full-sib half-sib mating design was used to estimate variance components and heritabilities for larval size and survival at day seven of development, development time and survival from egg to adult, and to estimate correlations between these traits, within an outbred population of house flies (Musca domestica), using high-throughput phenotyping for data collection. The results revealed low to intermediate heritabilities and positive genetic correlations between all traits except development time and survival to day seven of development and from egg to adulthood. Surprisingly, larval size at day seven exhibited a comparatively low heritability (0.10) in contrast to development time (0.25), a trait that is believed to have a stronger association with overall fitness. A decline in family numbers resulting from low mating success and high overall mortality reduced the amount of available data which resulted in large standard errors for the estimated parameters. Environmental factors made a substantial contribution to the phenotypic variation, which was overall high for all traits. There is potential for genetic improvement in all studied traits and estimates of genetic correlations indicate a partly shared genetic architecture among the traits. All estimates have large standard errors. Implementing high-throughput phenotyping is imperative for the estimation of genetic parameters in fast developing insects, and facilitates age synchronisation, which is vital in a breeding population. In spite of endeavours to minimise non-genetic sources of variation, all traits demonstrated substantial influences from environmental components. This emphasises the necessity of thorough attention to the experimental design before breeding is initiated in insect populations.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140209789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The genetics of resilience and its relationships with egg production traits and antibody traits in chickens","authors":"Tom V. L. Berghof, Nicolas Bedere, Katrijn Peeters, Marieke Poppe, Jeroen Visscher, Han A. Mulder","doi":"10.1186/s12711-024-00888-5","DOIUrl":"https://doi.org/10.1186/s12711-024-00888-5","url":null,"abstract":"Resilience is the capacity of an animal to be minimally affected by disturbances or to rapidly return to its initial state before exposure to a disturbance. Resilient livestock are desired because of their improved health and increased economic profit. Genetic improvement of resilience may also lead to trade-offs with production traits. Recently, resilience indicators based on longitudinal data have been suggested, but they need further evaluation to determine whether they are indeed predictive of improved resilience, such as disease resilience. This study investigated different resilience indicators based on deviations between expected and observed egg production (EP) by exploring their genetic parameters, their possible trade-offs with production traits, and their relationships with antibody traits in chickens. Egg production in a nucleus breeding herd environment based on 1-week-, 2-week-, or 3-week-intervals of two purebred chicken lines, a white egg-laying (33,825 chickens) and a brown egg-laying line (34,397 chickens), were used to determine deviations between observed EP and expected average batch EP, and between observed EP and expected individual EP. These deviations were used to calculate three types of resilience indicators for two life periods of each individual: natural logarithm-transformed variance (ln(variance)), skewness, and lag-one autocorrelation (autocorrelation) of deviations from 25 to 83 weeks of age and from 83 weeks of age to end of life. Then, we estimated their genetic correlations with EP traits and with two antibody traits. The most promising resilience indicators were those based on 1-week-intervals, as they had the highest heritability estimates (0.02–0.12) and high genetic correlations (above 0.60) with the same resilience indicators based on longer intervals. The three types of resilience indicators differed genetically from each other, which indicates that they possibly capture different aspects of resilience. Genetic correlations of the resilience indicator traits based on 1-week-intervals with EP traits were favorable or zero, which means that trade-off effects were marginal. The resilience indicator traits based on 1-week-intervals also showed no genetic correlations with the antibody traits, which suggests that they are not informative for improved immunity or vice versa in the nucleus environment. This paper gives direction towards the evaluation and implementation of resilience indicators, i.e. to further investigate resilience indicator traits based on 1-week-intervals, in breeding programs for selecting genetically more resilient layer chickens.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle","authors":"Marina Martínez-Álvaro, Jennifer Mattock, Óscar González-Recio, Alejandro Saborío-Montero, Ziqing Weng, Joana Lima, Carol-Anne Duthie, Richard Dewhurst, Matthew A. Cleveland, Mick Watson, Rainer Roehe","doi":"10.1186/s12711-024-00887-6","DOIUrl":"https://doi.org/10.1186/s12711-024-00887-6","url":null,"abstract":"Growth rate is an important component of feed conversion efficiency in cattle and varies across the different stages of the finishing period. The metabolic effect of the rumen microbiome is essential for cattle growth, and investigating the genomic and microbial factors that underlie this temporal variation can help maximize feed conversion efficiency at each growth stage. By analysing longitudinal body weights during the finishing period and genomic and metagenomic data from 359 beef cattle, our study demonstrates that the influence of the host genome on the functional rumen microbiome contributes to the temporal variation in average daily gain (ADG) in different months (ADG1, ADG2, ADG3, ADG4). Five hundred and thirty-three additive log-ratio transformed microbial genes (alr-MG) had non-zero genomic correlations (rg) with at least one ADG-trait (ranging from |0.21| to |0.42|). Only a few alr-MG correlated with more than one ADG-trait, which suggests that a differential host-microbiome determinism underlies ADG at different stages. These alr-MG were involved in ribosomal biosynthesis, energy processes, sulphur and aminoacid metabolism and transport, or lipopolysaccharide signalling, among others. We selected two alternative subsets of 32 alr-MG that had a non-uniform or a uniform rg sign with all the ADG-traits, regardless of the rg magnitude, and used them to develop a microbiome-driven breeding strategy based on alr-MG only, or combined with ADG-traits, which was aimed at shaping the rumen microbiome towards increased ADG at all finishing stages. Combining alr-MG information with ADG records increased prediction accuracy of genomic estimated breeding values (GEBV) by 11 to 22% relative to the direct breeding strategy (using ADG-traits only), whereas using microbiome information, only, achieved lower accuracies (from 7 to 41%). Predicted selection responses varied consistently with accuracies. Restricting alr-MG based on their rg sign (uniform subset) did not yield a gain in the predicted response compared to the non-uniform subset, which is explained by the absence of alr-MG showing non-zero rg at least with more than one of the ADG-traits. Our work sheds light on the role of the microbial metabolism in the growth trajectory of beef cattle at the genomic level and provides insights into the potential benefits of using microbiome information in future genomic breeding programs to accurately estimate GEBV and increase ADG at each finishing stage in beef cattle.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140139531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Confidence intervals for validation statistics with data truncation in genomic prediction","authors":"Matias Bermann, Andres Legarra, Alejandra Alvarez Munera, Ignacy Misztal, Daniela Lourenco","doi":"10.1186/s12711-024-00883-w","DOIUrl":"https://doi.org/10.1186/s12711-024-00883-w","url":null,"abstract":"Validation by data truncation is a common practice in genetic evaluations because of the interest in predicting the genetic merit of a set of young selection candidates. Two of the most used validation methods in genetic evaluations use a single data partition: predictivity or predictive ability (correlation between pre-adjusted phenotypes and estimated breeding values (EBV) divided by the square root of the heritability) and the linear regression (LR) method (comparison of “early” and “late” EBV). Both methods compare predictions with the whole dataset and a partial dataset that is obtained by removing the information related to a set of validation individuals. EBV obtained with the partial dataset are compared against adjusted phenotypes for the predictivity or EBV obtained with the whole dataset in the LR method. Confidence intervals for predictivity and the LR method can be obtained by replicating the validation for different samples (or folds), or bootstrapping. Analytical confidence intervals would be beneficial to avoid running several validations and to test the quality of the bootstrap intervals. However, analytical confidence intervals are unavailable for predictivity and the LR method. We derived standard errors and Wald confidence intervals for the predictivity and statistics included in the LR method (bias, dispersion, ratio of accuracies, and reliability). The confidence intervals for the bias, dispersion, and reliability depend on the relationships and prediction error variances and covariances across the individuals in the validation set. We developed approximations for large datasets that only need the reliabilities of the individuals in the validation set. The confidence intervals for the ratio of accuracies and predictivity were obtained through the Fisher transformation. We show the adequacy of both the analytical and approximated analytical confidence intervals and compare them versus bootstrap confidence intervals using two simulated examples. The analytical confidence intervals were closer to the simulated ones for both examples. Bootstrap confidence intervals tend to be narrower than the simulated ones. The approximated analytical confidence intervals were similar to those obtained by bootstrapping. Estimating the sampling variation of predictivity and the statistics in the LR method without replication or bootstrap is possible for any dataset with the formulas presented in this study.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140064146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GWABLUP: genome-wide association assisted best linear unbiased prediction of genetic values","authors":"Theo Meuwissen, Leiv Sigbjorn Eikje, Arne B. Gjuvsland","doi":"10.1186/s12711-024-00881-y","DOIUrl":"https://doi.org/10.1186/s12711-024-00881-y","url":null,"abstract":"Since the very beginning of genomic selection, researchers investigated methods that improved upon SNP-BLUP (single nucleotide polymorphism best linear unbiased prediction). SNP-BLUP gives equal weight to all SNPs, whereas it is expected that many SNPs are not near causal variants and thus do not have substantial effects. A recent approach to remedy this is to use genome-wide association study (GWAS) findings and increase the weights of GWAS-top-SNPs in genomic predictions. Here, we employ a genome-wide approach to integrate GWAS results into genomic prediction, called GWABLUP. GWABLUP consists of the following steps: (1) performing a GWAS in the training data which results in likelihood ratios; (2) smoothing the likelihood ratios over the SNPs; (3) combining the smoothed likelihood ratio with the prior probability of SNPs having non-zero effects, which yields the posterior probability of the SNPs; (4) calculating a weighted genomic relationship matrix using the posterior probabilities as weights; and (5) performing genomic prediction using the weighted genomic relationship matrix. Using high-density genotypes and milk, fat, protein and somatic cell count phenotypes on dairy cows, GWABLUP was compared to GBLUP, GBLUP (topSNPs) with extra weights for GWAS top-SNPs, and BayesGC, i.e. a Bayesian variable selection model. The GWAS resulted in six, five, four, and three genome-wide significant peaks for milk, fat and protein yield and somatic cell count, respectively. GWABLUP genomic predictions were 10, 6, 7 and 1% more reliable than those of GBLUP for milk, fat and protein yield and somatic cell count, respectively. It was also more reliable than GBLUP (topSNPs) for all four traits, and more reliable than BayesGC for three of the traits. Although GWABLUP showed a tendency towards inflation bias for three of the traits, this was not statistically significant. In a multitrait analysis, GWABLUP yielded the highest accuracy for two of the traits. However, for SCC, which was relatively unrelated to the yield traits, including yield trait GWAS-results reduced the reliability compared to a single trait analysis. GWABLUP uses GWAS results to differentially weigh all the SNPs in a weighted GBLUP genomic prediction analysis. GWABLUP yielded up to 10% and 13% more reliable genomic predictions than GBLUP for single and multitrait analyses, respectively. Extension of GWABLUP to single-step analyses is straightforward.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140000861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expected values for the accuracy of predicted breeding values accounting for genetic differences between reference and target populations","authors":"Beatriz C. D. Cuyabano, Didier Boichard, Cedric Gondro","doi":"10.1186/s12711-024-00876-9","DOIUrl":"https://doi.org/10.1186/s12711-024-00876-9","url":null,"abstract":"Genetic merit, or breeding values as referred to in livestock and crop breeding programs, is one of the keys to the successful selection of animals in commercial farming systems. The developments in statistical methods during the twentieth century and single nucleotide polymorphism (SNP) chip technologies in the twenty-first century have revolutionized agricultural production, by allowing highly accurate predictions of breeding values for selection candidates at a very early age. Nonetheless, for many breeding populations, realized accuracies of predicted breeding values (PBV) remain below the theoretical maximum, even when the reference population is sufficiently large, and SNPs included in the model are in sufficient linkage disequilibrium (LD) with the quantitative trait locus (QTL). This is particularly noticeable over generations, as we observe the so-called erosion of the effects of SNPs due to recombinations, accompanied by the erosion of the accuracy of prediction. While accurately quantifying the erosion at the individual SNP level is a difficult and unresolved task, quantifying the erosion of the accuracy of prediction is a more tractable problem. In this paper, we describe a method that uses the relationship between reference and target populations to calculate expected values for the accuracies of predicted breeding values for non-phenotyped individuals accounting for erosion. The accuracy of the expected values was evaluated through simulations, and a further evaluation was performed on real data. Using simulations, we empirically confirmed that our expected values for the accuracy of PBV accounting for erosion were able to correctly determine the prediction accuracy of breeding values for non-phenotyped individuals. When comparing the expected to the realized accuracies of PBV with real data, only one out of the four traits evaluated presented accuracies that were significantly higher than the expected, approaching $$sqrt{{{text{h}}}^{2}}$$ . We defined an index of genetic correlation between reference and target populations, which summarizes the expected overall erosion due to differences in allele frequencies and LD patterns between populations. We used this correlation along with a trait’s heritability to derive expected values for the accuracy ( $${text{R}}$$ ) of PBV accounting for the erosion, and demonstrated that our derived $${text{E}}left[{text{R}}|{text{erosion}}right]$$ is a reliable metric.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139994288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Searching for homozygous haplotype deficiency in Manech Tête Rousse dairy sheep revealed a nonsense variant in the MMUT gene affecting newborn lamb viability.","authors":"Maxime Ben Braiek, Carole Moreno-Romieux, Céline André, Jean-Michel Astruc, Philippe Bardou, Arnaud Bordes, Frédéric Debat, Francis Fidelle, Itsasne Granado-Tajada, Chris Hozé, Florence Plisson-Petit, François Rivemale, Julien Sarry, Némuel Tadi, Florent Woloszyn, Stéphane Fabre","doi":"10.1186/s12711-024-00886-7","DOIUrl":"10.1186/s12711-024-00886-7","url":null,"abstract":"<p><strong>Background: </strong>Recessive deleterious variants are known to segregate in livestock populations, as in humans, and some may be lethal in the homozygous state.</p><p><strong>Results: </strong>We used phased 50 k single nucleotide polymorphism (SNP) genotypes and pedigree data to scan the genome of 6845 Manech Tête Rousse dairy sheep to search for deficiency in homozygous haplotypes (DHH). Five Manech Tête Rousse deficient homozygous haplotypes (MTRDHH1 to 5) were identified, with a homozygous deficiency ranging from 84 to 100%. These haplotypes are located on Ovis aries chromosome (OAR)1 (MTRDHH2 and 3), OAR10 (MTRDHH4), OAR13 (MTRDHH5), and OAR20 (MTRDHH1), and have carrier frequencies ranging from 7.8 to 16.6%. When comparing at-risk matings between DHH carriers to safe matings between non-carriers, two DHH (MTRDHH1 and 2) were linked with decreased insemination success and/or increased stillbirth incidence. We investigated the MTRDHH1 haplotype, which substantially increased stillbirth rate, and identified a single nucleotide variant (SNV) inducing a premature stop codon (p.Gln409*) in the methylmalonyl-CoA mutase (MMUT) gene by using a whole-genome sequencing approach. We generated homozygous lambs for the MMUT mutation by at-risk mating between heterozygous carriers, and most of them died within the first 24 h after birth without any obvious clinical symptoms. Reverse transcriptase-qPCR and western blotting on post-mortem liver and kidney biological samples showed a decreased expression of MMUT mRNA in the liver and absence of a full-length MMUT protein in the mutant homozygous lambs.</p><p><strong>Conclusions: </strong>We identified five homozygous deficient haplotypes that are likely to harbor five independent deleterious recessive variants in sheep. One of these was detected in the MMUT gene, which is associated with lamb lethality in the homozygous state. A specific management of these haplotypes/variants in the MTR dairy sheep selection program would help enhance the overall fertility and lamb survival.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10905913/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139998264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Identification of candidate regulatory genes for intramuscular fatty acid composition in pigs by transcriptome analysis","authors":"Jesús Valdés-Hernández, Josep M. Folch, Daniel Crespo-Piazuelo, Magí Passols, Cristina Sebastià, Lourdes Criado-Mesas, Anna Castelló, Armand Sánchez, Yuliaxis Ramayo-Caldas","doi":"10.1186/s12711-024-00885-8","DOIUrl":"https://doi.org/10.1186/s12711-024-00885-8","url":null,"abstract":"<p><b>Correction: Genetics Selection Evolution (2024) 56:12</b><b>https://doi.org/10.1186/s12711-024-00882-x</b></p><p>After publication of original article [1], we noticed that two errors were introduced during production:</p><ol>\u0000<li>\u0000<span>(1)</span>\u0000<p>In the <b>Bioinformatic and statistical analyses</b> section, the corresponding information on the <b>X</b> and <b>Y</b> matrices has been removed in three places:</p>\u0000<p>The part “A regularized canonical correlation analysis (rCCA) was performed using the expression dataset of the 12,381 genes (matrix) and the 15 FA traits (matrix) measured on the 129 individuals. The rCCA multivariate approach is implemented in the mixOmics v6.14.1 package [12], which allows subsets of canonical variables that maximize the correlation between two datasets (“and”, respectively of sizes n × p and n × q) to be identified [22].”</p>\u0000<p>Should be “A regularized canonical correlation analysis (rCCA) was performed using the expression dataset of the 12,381 genes (matrix <b>Y</b>) and the 15 FA traits (matrix <b>X</b>) measured on the 129 individuals. The rCCA multivariate approach is implemented in the mixOmics v6.14.1 package [10], which allows to identify the subsets of canonical variables that maximize the correlation between two datasets (“<b>X</b> and <b>Y</b>”, respectively of sizes n × p and n × q) [22].”</p>\u0000</li>\u0000<li>\u0000<span>(2)</span>\u0000<p>In the Funding section, the following term “https://doi.org/” has been automatically added to the funding source in three places. In fact, the correct funding source should be “MCIN/AEI/10.13039/501100011033” and not “MCIN/AEI/https://doi.org/10.13039/501100011033”.</p>\u0000</li>\u0000</ol><ol data-track-component=\"outbound reference\"><li data-counter=\"1.\"><p>Valdés-Hernández J, Folch JM, Crespo-Piazuelo D, Passols M, Sebastià C, Criado-Mesas L, Castelló A, Sánchez A, Ramayo-Caldas Y. Identification of candidate regulatory genes for intramuscular fatty acid composition in pigs by transcriptome analysis. Genet Sel Evol. 2024;56:12. https://doi.org/10.1186/s12711-024-00882-x.</p><p>Article CAS PubMed PubMed Central Google Scholar </p></li></ol><p>Download references<svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"><use xlink:href=\"#icon-eds-i-download-medium\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"></use></svg></p><h3>Authors and Affiliations</h3><ol><li><p>Plant and Animal Genomics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus UAB, Bellaterra, Spain</p><p>Jesús Valdés-Hernández, Josep M. Folch, Magí Passols, Cristina Sebastià, Lourdes Criado-Mesas, Anna Castelló &amp; Armand Sánchez</p></li><li><p>Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, Bellaterra, Spain</p><p>Jesús Valdés-Hernández, Josep M. Folch, Cristina Sebastià, Anna Castelló &amp; Armand Sánchez</p></li><li><p>Departament de Genètica i Millora Animal, Institut de Recerca y Tecnologia Agraroalimentàri","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139967315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome-wide detection of positive and balancing signatures of selection shared by four domesticated rainbow trout populations (Oncorhynchus mykiss)","authors":"Katy Paul, Gwendal Restoux, Florence Phocas","doi":"10.1186/s12711-024-00884-9","DOIUrl":"https://doi.org/10.1186/s12711-024-00884-9","url":null,"abstract":"Evolutionary processes leave footprints along the genome over time. Highly homozygous regions may correspond to positive selection of favorable alleles, while maintenance of heterozygous regions may be due to balancing selection phenomena. We analyzed data from 176 fish from four disconnected domestic rainbow trout populations that were genotyped using a high-density Axiom Trout genotyping 665K single nucleotide polymorphism array, including 20 from the US and 156 from three French lines. Using methods based on runs of homozygosity and extended haplotype homozygosity, we detected signatures of selection in these four populations. Nine genomic regions that included 253 genes were identified as being under positive selection in all four populations Most were located on chromosome 2 but also on chromosomes 12, 15, 16, and 20. In addition, four heterozygous regions that contain 29 genes that are putatively under balancing selection were also shared by the four populations. These were located on chromosomes 10, 13, and 19. Regardless of the homozygous or heterozygous nature of the regions, in each region, we detected several genes that are highly conserved among vertebrates due to their critical roles in cellular and nuclear organization, embryonic development, or immunity. We identified new candidate genes involved in rainbow trout fitness, as well as 17 genes that were previously identified to be under positive selection, 10 of which in other fishes (auts2, atp1b3, zp4, znf135, igf-1α, brd2, col9a2, mrap2, pbx1, and emilin-3). Using material from disconnected populations of different origins allowed us to draw a genome-wide map of signatures of positive selection that are shared between these rainbow trout populations, and to identify several regions that are putatively under balancing selection. These results provide a valuable resource for future investigations of the dynamics of genetic diversity and genome evolution during domestication.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139925532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of candidate regulatory genes for intramuscular fatty acid composition in pigs by transcriptome analysis","authors":"Jesús Valdés-Hernández, Josep M. Folch, Daniel Crespo-Piazuelo, Magí Passols, Cristina Sebastià, Lourdes Criado-Mesas, Anna Castelló, Armand Sánchez, Yuliaxis Ramayo-Caldas","doi":"10.1186/s12711-024-00882-x","DOIUrl":"https://doi.org/10.1186/s12711-024-00882-x","url":null,"abstract":"Intramuscular fat (IMF) content and its fatty acid (FA) composition are typically controlled by several genes, each with a small effect. In the current study, to pinpoint candidate genes and putative regulators involved in FA composition, we performed a multivariate integrative analysis between intramuscular FA and transcriptome profiles of porcine longissimus dorsi (LD) muscle. We also carried out a combination of network, regulatory impact factor (RIF), in silico prediction of putative target genes, and functional analyses to better support the biological relevance of our findings. For this purpose, we used LD RNA-Seq and intramuscular FA composition profiles of 129 Iberian × Duroc backcrossed pigs. We identified 378 correlated variables (13 FA and 365 genes), including six FA (C20:4n-6, C18:2n-6, C20:3n-6, C18:1n-9, C18:0, and C16:1n-7) that were among the most interconnected variables in the predicted network. The detected FA-correlated genes include genes involved in lipid and/or carbohydrate metabolism or in regulation of IMF deposition (e.g., ADIPOQ, CHUK, CYCS, CYP4B1, DLD, ELOVL6, FBP1, G0S2, GCLC, HMGCR, IDH3A, LEP, LGALS12, LPIN1, PLIN1, PNPLA8, PPP1R1B, SDR16C5, SFRP5, SOD3, SNW1, and TFRC), meat quality (GALNT15, GOT1, MDH1, NEU3, PDHA1, SDHD, and UNC93A), and transport (e.g., EXOC7 and SLC44A2). Functional analysis highlighted 54 over-represented gene ontology terms, including well-known biological processes and pathways that regulate lipid and carbohydrate metabolism. RIF analysis suggested a pivotal role for six transcription factors (CARHSP1, LBX1, MAFA, PAX7, SIX5, and TADA2A) as putative regulators of gene expression and intramuscular FA composition. Based on in silico prediction, we identified putative target genes for these six regulators. Among these, TADA2A and CARHSP1 had extreme RIF scores and present novel regulators in pigs. In addition, the expression of TADA2A correlated (either positively or negatively) with C20:4n-6, C18:2n-6, C20:3n-6, C18:1n-9, and that of CARHSP1 correlated (positively) with the C16:1n-7 lipokine. We also found that these two transcription factors share target genes that are involved in lipid metabolism (e.g., GOT1, PLIN1, and TFRC). This integrative analysis of muscle transcriptome and intramuscular FA profile revealed valuable information about key candidate genes and potential regulators for FA and lipid metabolism in pigs, among which some transcription factors are proposed to control gene expression and modulate FA composition differences.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139720404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}