Xue Wang, Zipeng Zhang, Hehe Du, Christina Pfeiffer, Gábor Mészáros, Xiangdong Ding
{"title":"Predictive ability of multi-population genomic prediction methods of phenotypes for reproduction traits in Chinese and Austrian pigs","authors":"Xue Wang, Zipeng Zhang, Hehe Du, Christina Pfeiffer, Gábor Mészáros, Xiangdong Ding","doi":"10.1186/s12711-024-00915-5","DOIUrl":"https://doi.org/10.1186/s12711-024-00915-5","url":null,"abstract":"Multi-population genomic prediction can rapidly expand the size of the reference population and improve genomic prediction ability. Machine learning (ML) algorithms have shown advantages in single-population genomic prediction of phenotypes. However, few studies have explored the effectiveness of ML methods for multi-population genomic prediction. In this study, 3720 Yorkshire pigs from Austria and four breeding farms in China were used, and single-trait genomic best linear unbiased prediction (ST-GBLUP), multitrait GBLUP (MT-GBLUP), Bayesian Horseshoe (BayesHE), and three ML methods (support vector regression (SVR), kernel ridge regression (KRR) and AdaBoost.R2) were compared to explore the optimal method for joint genomic prediction of phenotypes of Chinese and Austrian pigs through 10 replicates of fivefold cross-validation. In this study, we tested the performance of different methods in two scenarios: (i) including only one Austrian population and one Chinese pig population that were genetically linked based on principal component analysis (PCA) (designated as the “two-population scenario”) and (ii) adding reference populations that are unrelated based on PCA to the above two populations (designated as the “multi-population scenario”). Our results show that, the use of MT-GBLUP in the two-population scenario resulted in an improvement of 7.1% in predictive ability compared to ST-GBLUP, while the use of SVR and KKR yielded improvements in predictive ability of 4.5 and 5.3%, respectively, compared to MT-GBLUP. SVR and KRR also yielded lower mean square errors (MSE) in most population and trait combinations. In the multi-population scenario, improvements in predictive ability of 29.7, 24.4 and 11.1% were obtained compared to ST-GBLUP when using, respectively, SVR, KRR, and AdaBoost.R2. However, compared to MT-GBLUP, the potential of ML methods to improve predictive ability was not demonstrated. Our study demonstrates that ML algorithms can achieve better prediction performance than multitrait GBLUP models in multi-population genomic prediction of phenotypes when the populations have similar genetic backgrounds; however, when reference populations that are unrelated based on PCA are added, the ML methods did not show a benefit. When the number of populations increased, only MT-GBLUP improved predictive ability in both validation populations, while the other methods showed improvement in only one population.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"29 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141452815","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}
Wim Gorssen, Carmen Winters, Roel Meyermans, Léa Chapard, Katrijn Hooyberghs, Jürgen Depuydt, Steven Janssens, Han Mulder, Nadine Buys
{"title":"Breeding for resilience in finishing pigs can decrease tail biting, lameness and mortality","authors":"Wim Gorssen, Carmen Winters, Roel Meyermans, Léa Chapard, Katrijn Hooyberghs, Jürgen Depuydt, Steven Janssens, Han Mulder, Nadine Buys","doi":"10.1186/s12711-024-00919-1","DOIUrl":"https://doi.org/10.1186/s12711-024-00919-1","url":null,"abstract":"Previous research showed that deviations in longitudinal data are heritable and can be used as a proxy for pigs’ general resilience. However, only a few studies investigated the relationship between these resilience traits and other traits related to resilience and welfare. Therefore, this study investigated the relationship between resilience traits derived from deviations in longitudinal data and traits related to animal resilience, health and welfare, such as tail and ear biting wounds, lameness and mortality. In our experiment, 1919 finishing pigs with known pedigree (133 Piétrain sires and 266 crossbred dams) were weighed every 2 weeks and scored for physical abnormalities, such as lameness and ear and tail biting wounds (17,066 records). Resilience was assessed via deviations in body weight, deviations in weighing order and deviations in observed activity during weighing. The association between these resilience traits and physical abnormality traits was investigated and genetic parameters were estimated. Deviations in body weight had moderate heritability estimates (h2 = 25.2 to 36.3%), whereas deviations in weighing order (h2 = 4.2%) and deviations in activity during weighing (h2 = 12.0%) had low heritability estimates. Moreover, deviations in body weight were positively associated and genetically correlated with tail biting wounds (rg = 0.22 to 0.30), lameness (rg = 0.15 to 0.31) and mortality (rg = 0.19 to 0.33). These results indicate that events of tail biting, lameness and mortality are associated with deviations in pigs’ body weight evolution. This relationship was not found for deviations in weighing order and activity during weighing. Furthermore, individual body weight deviations were positively correlated with uniformity at the pen level, providing evidence that breeding for these resilience traits might increase both pigs’ resilience and within-family uniformity. In summary, our findings show that breeding for resilience traits based on deviations in longitudinal weight data can decrease pigs’ tail biting wounds, lameness and mortality while improving uniformity at the pen level. These findings are valuable for pig breeders, as they offer evidence that these resilience traits are an indication of animals’ general health, welfare and resilience. Moreover, these results will stimulate the quantification of resilience via longitudinal body weights in other species.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"31 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141430342","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}
Janet E. Fulton, Amy M. McCarron, Ashlee R. Lund, Wioleta Drobik-Czwarno, Abigail Mullen, Anna Wolc, Joanna Szadkowska, Carl J. Schmidt, Robert L. Taylor
{"title":"The RHCE gene encodes the chicken blood system I","authors":"Janet E. Fulton, Amy M. McCarron, Ashlee R. Lund, Wioleta Drobik-Czwarno, Abigail Mullen, Anna Wolc, Joanna Szadkowska, Carl J. Schmidt, Robert L. Taylor","doi":"10.1186/s12711-024-00911-9","DOIUrl":"https://doi.org/10.1186/s12711-024-00911-9","url":null,"abstract":"There are 13 known chicken blood systems, which were originally detected by agglutination of red blood cells by specific alloantisera. The genomic region or specific gene responsible has been identified for four of these systems (A, B, D and E). We determined the identity of the gene responsible for the chicken blood system I, using DNA from multiple birds with known chicken I blood system serology, 600K and 54K single nucleotide polymorphism (SNP) data, and lowpass sequence information. The gene responsible for the chicken I blood system was identified as RHCE, which is also one of the genes responsible for the highly polymorphic human Rh blood group locus, for which maternal/fetal antigenic differences can result in fetal hemolytic anemia with fetal mortality. We identified 17 unique RHCE haplotypes in the chicken, with six haplotypes corresponding to known I system serological alleles. We also detected deletions in the RHCE gene that encompass more than 6000 bp and that are predicted to remove its last seven exons. RHCE is the gene responsible for the chicken I blood system. This is the fifth chicken blood system for which the responsible gene and gene variants are known. With rapid DNA-based testing now available, the impact of I blood system variation on response against disease, general immune function, and animal production can be investigated in greater detail.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"1 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141425471","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":"Investigating the impact of paternal age, paternal heat stress, and estimation of non-genetic paternal variance on dairy cow phenotype","authors":"Corentin Fouéré, Chris Hozé, Florian Besnard, Mekki Boussaha, Didier Boichard, Marie-Pierre Sanchez","doi":"10.1186/s12711-024-00918-2","DOIUrl":"https://doi.org/10.1186/s12711-024-00918-2","url":null,"abstract":"Linear models that are commonly used to predict breeding values in livestock species consider paternal influence solely as a genetic effect. However, emerging evidence in several species suggests the potential effect of non-genetic semen-mediated paternal effects on offspring phenotype. This study contributes to such research by analyzing the extent of non-genetic paternal effects on the performance of Holstein, Montbéliarde, and Normande dairy cows. Insemination data, including semen Batch Identifier (BI, a combination of bull identification and collection date), was associated with various traits measured in cows born from the insemination. These traits encompassed stature, milk production (milk, fat, and protein yields), udder health (somatic cell score and clinical mastitis), and female fertility (conception rates of heifers and cows). We estimated (1) the effects of age at collection and heat stress during spermatogenesis, and (2) the variance components associated with BI or Weekly aggregated BI (WBI). Overall, the non-genetic paternal effect estimates were small and of limited biological importance. However, while heat stress during spermatogenesis did not show significant associations with any of the traits studied in daughters, we observed significant effects of bull age at semen collection on the udder health of daughters. Indeed, cows born from bulls collected after 1500 days of age had higher somatic cell scores compared to those born from bulls collected at a younger age (less than 400 days old) in both Holstein and Normande breeds (+ 3% and + 5% of the phenotypic mean, respectively). In addition, across all breeds and traits analyzed, the estimates of non-genetic paternal variance were consistently low, representing on average 0.13% and 0.09% of the phenotypic variance for BI and WBI, respectively (ranging from 0 to 0.7%). These estimates did not significantly differ from zero, except for milk production traits (milk, fat, and protein yields) in the Holstein breed and protein yield in the Montbéliarde breed when WBI was considered. Our findings indicate that non-genetic paternal information transmitted through semen does not substantially influence the offspring phenotype in dairy cattle breeds for routinely measured traits. This lack of substantial impact may be attributed to limited transmission or minimal exposure of elite bulls to adverse conditions.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"46 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334153","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}
Paula Reich, Sandra Möller, Kathrin F. Stock, Wietje Nolte, Mario von Depka Prondzinski, Reinhard Reents, Ernst Kalm, Christa Kühn, Georg Thaller, Clemens Falker-Gieske, Jens Tetens
{"title":"Genomic analyses of withers height and linear conformation traits in German Warmblood horses using imputed sequence-level genotypes","authors":"Paula Reich, Sandra Möller, Kathrin F. Stock, Wietje Nolte, Mario von Depka Prondzinski, Reinhard Reents, Ernst Kalm, Christa Kühn, Georg Thaller, Clemens Falker-Gieske, Jens Tetens","doi":"10.1186/s12711-024-00914-6","DOIUrl":"https://doi.org/10.1186/s12711-024-00914-6","url":null,"abstract":"Body conformation, including withers height, is a major selection criterion in horse breeding and is associated with other important traits, such as health and performance. However, little is known about the genomic background of equine conformation. Therefore, the aim of this study was to use imputed sequence-level genotypes from up to 4891 German Warmblood horses to identify genomic regions associated with withers height and linear conformation traits. Furthermore, the traits were genetically characterised and putative causal variants for withers height were detected. A genome-wide association study (GWAS) for withers height confirmed the presence of a previously known quantitative trait locus (QTL) on Equus caballus (ECA) chromosome 3 close to the LCORL/NCAPG locus, which explained 16% of the phenotypic variance for withers height. An additional significant association signal was detected on ECA1. Further investigations of the region on ECA3 identified a few promising candidate causal variants for withers height, including a nonsense mutation in the coding sequence of the LCORL gene. The estimated heritability for withers height was 0.53 and ranged from 0 to 0.34 for the conformation traits. GWAS identified significantly associated variants for more than half of the investigated conformation traits, among which 13 showed a peak on ECA3 in the same region as withers height. Genetic parameter estimation revealed high genetic correlations between these traits and withers height for the QTL on ECA3. The use of imputed sequence-level genotypes from a large study cohort led to the discovery of novel QTL associated with conformation traits in German Warmblood horses. The results indicate the high relevance of the QTL on ECA3 for various conformation traits, including withers height, and contribute to deciphering causal mutations for body size in horses.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"111 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141315582","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}
Hui Wen, Jay S. Johnson, Leonardo S. Gloria, Andre C. Araujo, Jacob M. Maskal, Sharlene Olivette Hartman, Felipe E. de Carvalho, Artur Oliveira Rocha, Yijian Huang, Francesco Tiezzi, Christian Maltecca, Allan P. Schinckel, Luiz F. Brito
{"title":"Genetic parameters for novel climatic resilience indicators derived from automatically-recorded vaginal temperature in lactating sows under heat stress conditions","authors":"Hui Wen, Jay S. Johnson, Leonardo S. Gloria, Andre C. Araujo, Jacob M. Maskal, Sharlene Olivette Hartman, Felipe E. de Carvalho, Artur Oliveira Rocha, Yijian Huang, Francesco Tiezzi, Christian Maltecca, Allan P. Schinckel, Luiz F. Brito","doi":"10.1186/s12711-024-00908-4","DOIUrl":"https://doi.org/10.1186/s12711-024-00908-4","url":null,"abstract":"Longitudinal records of automatically-recorded vaginal temperature (TV) could be a key source of data for deriving novel indicators of climatic resilience (CR) for breeding more resilient pigs, especially during lactation when sows are at an increased risk of suffering from heat stress (HS). Therefore, we derived 15 CR indicators based on the variability in TV in lactating sows and estimated their genetic parameters. We also investigated their genetic relationship with sows’ key reproductive traits. The heritability estimates of the CR traits ranged from 0.000 ± 0.000 for slope for decreased rate of TV (SlopeDe) to 0.291 ± 0.047 for sum of TV values below the HS threshold (HSUB). Moderate to high genetic correlations (from 0.508 ± 0.056 to 0.998 ± 0.137) and Spearman rank correlations (from 0.431 to 1.000) between genomic estimated breeding values (GEBV) were observed for five CR indicators, i.e. HS duration (HSD), the normalized median multiplied by normalized variance (Nor_medvar), the highest TV value of each measurement day for each individual (MaxTv), and the sum of the TV values above (HSUA) and below (HSUB) the HS threshold. These five CR indicators were lowly to moderately genetically correlated with shoulder skin surface temperature (from 0.139 ± 0.008 to 0.478 ± 0.048) and respiration rate (from 0.079 ± 0.011 to 0.502 ± 0.098). The genetic correlations between these five selected CR indicators and sow reproductive performance traits ranged from − 0.733 to − 0.175 for total number of piglets born alive, from − 0.733 to − 0.175 for total number of piglets born, and from − 0.434 to − 0.169 for number of pigs weaned. The individuals with the highest GEBV (most climate-sensitive) had higher mean skin surface temperature, respiration rate (RR), panting score (PS), and hair density, but had lower mean body condition scores compared to those with the lowest GEBV (most climate-resilient). Most of the CR indicators evaluated are heritable with substantial additive genetic variance. Five of them, i.e. HSD, MaxTv, HSUA, HSUB, and Nor_medvar share similar underlying genetic mechanisms. In addition, individuals with higher CR indicators are more likely to exhibit better HS-related physiological responses, higher body condition scores, and improved reproductive performance under hot conditions. These findings highlight the potential benefits of genetically selecting more heat-tolerant individuals based on CR indicators.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"7 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141299045","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}
Irene van den Berg, Amanda J. Chamberlain, Iona M. MacLeod, Tuan V. Nguyen, Mike E. Goddard, Ruidong Xiang, Brett Mason, Susanne Meier, Claire V. C. Phyn, Chris R. Burke, Jennie E. Pryce
{"title":"Using expression data to fine map QTL associated with fertility in dairy cattle","authors":"Irene van den Berg, Amanda J. Chamberlain, Iona M. MacLeod, Tuan V. Nguyen, Mike E. Goddard, Ruidong Xiang, Brett Mason, Susanne Meier, Claire V. C. Phyn, Chris R. Burke, Jennie E. Pryce","doi":"10.1186/s12711-024-00912-8","DOIUrl":"https://doi.org/10.1186/s12711-024-00912-8","url":null,"abstract":"Female fertility is an important trait in dairy cattle. Identifying putative causal variants associated with fertility may help to improve the accuracy of genomic prediction of fertility. Combining expression data (eQTL) of genes, exons, gene splicing and allele specific expression is a promising approach to fine map QTL to get closer to the causal mutations. Another approach is to identify genomic differences between cows selected for high and low fertility and a selection experiment in New Zealand has created exactly this resource. Our objective was to combine multiple types of expression data, fertility traits and allele frequency in high- (POS) and low-fertility (NEG) cows with a genome-wide association study (GWAS) on calving interval in Australian cows to fine-map QTL associated with fertility in both Australia and New Zealand dairy cattle populations. Variants that were significantly associated with calving interval (CI) were strongly enriched for variants associated with gene, exon, gene splicing and allele-specific expression, indicating that there is substantial overlap between QTL associated with CI and eQTL. We identified 671 genes with significant differential expression between POS and NEG cows, with the largest fold change detected for the CCDC196 gene on chromosome 10. Our results provide numerous candidate genes associated with female fertility in dairy cattle, including GYS2 and TIGAR on chromosome 5 and SYT3 and HSD17B14 on chromosome 18. Multiple QTL regions were located in regions with large numbers of copy number variants (CNV). To identify the causal mutations for these variants, long read sequencing may be useful. Variants that were significantly associated with CI were highly enriched for eQTL. We detected 671 genes that were differentially expressed between POS and NEG cows. Several QTL detected for CI overlapped with eQTL, providing candidate genes for fertility in dairy cattle.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"336 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141264867","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}
Christine Anglhuber, Christian Edel, Eduardo C. G. Pimentel, Reiner Emmerling, Kay-Uwe Götz, Georg Thaller
{"title":"Definition of metafounders based on population structure analysis","authors":"Christine Anglhuber, Christian Edel, Eduardo C. G. Pimentel, Reiner Emmerling, Kay-Uwe Götz, Georg Thaller","doi":"10.1186/s12711-024-00913-7","DOIUrl":"https://doi.org/10.1186/s12711-024-00913-7","url":null,"abstract":"Limitations of the concept of identity by descent in the presence of stratification within a breeding population may lead to an incomplete formulation of the conventional numerator relationship matrix ( $$mathbf{A}$$ ). Combining $$mathbf{A}$$ with the genomic relationship matrix ( $$mathbf{G}$$ ) in a single-step approach for genetic evaluation may cause inconsistencies that can be a source of bias in the resulting predictions. The objective of this study was to identify stratification using genomic data and to transfer this information to matrix $$mathbf{A}$$ , to improve the compatibility of $$mathbf{A}$$ and $$mathbf{G}$$ . Using software to detect population stratification (ADMIXTURE), we developed an iterative approach. First, we identified 2 to 40 strata ( $$k$$ ) with ADMIXTURE, which we then introduced in a stepwise manner into matrix $$mathbf{A}$$ , to generate matrix $${mathbf{A}}^{{varvec{Gamma}}}$$ using the metafounder methodology. Improvements in consistency between matrix $$mathbf{G}$$ and $${mathbf{A}}^{{varvec{Gamma}}}$$ were evaluated by regression analysis and through the comparison of the overall mean and mean diagonal values of both matrices. The approach was tested on genotype and pedigree information of European and North American Brown Swiss animals (85,249). Analyses with ADMIXTURE were initially performed on the full set of genotypes (S1). In addition, we used an alternative dataset where we avoided sampling of closely related animals (S2). Results of the regression analyses of standard $$mathbf{A}$$ on $$mathbf{G}$$ were – 0.489, 0.780 and 0.647 for intercept, slope and fit of the regression. When analysing S1 data results of the regression for $${mathbf{A}}^{{varvec{Gamma}}}$$ on $$mathbf{G}$$ corresponding values were – 0.028, 1.087 and 0.807 for $$k$$ =7, while there was no clear optimum $$k$$ . Analyses of S2 gave a clear optimal $$k$$ =24, with − 0.020, 0.998 and 0.817 as results of the regression. For this $$k$$ differences in mean and mean diagonal values between both matrices were negligible. The derivation of hidden stratification information based on genotyped animals and its integration into $$mathbf{A}$$ improved compatibility of the resulting $${mathbf{A}}^{{varvec{Gamma}}}$$ and $$mathbf{G}$$ considerably compared to the initial situation. In dairy breeding populations with large half-sib families as sub-structures it is necessary to balance the data when applying population structure analysis to obtain meaningful results.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"4 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141264874","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}
Pablo A. S. Fonseca, Aroa Suárez-Vega, Juan J. Arranz, Beatriz Gutiérrez-Gil
{"title":"Integration of selective sweeps across the sheep genome: understanding the relationship between production and adaptation traits","authors":"Pablo A. S. Fonseca, Aroa Suárez-Vega, Juan J. Arranz, Beatriz Gutiérrez-Gil","doi":"10.1186/s12711-024-00910-w","DOIUrl":"https://doi.org/10.1186/s12711-024-00910-w","url":null,"abstract":"Livestock populations are under constant selective pressure for higher productivity levels for different selective purposes. This pressure results in the selection of animals with unique adaptive and production traits. The study of genomic regions associated with these unique characteristics has the potential to improve biological knowledge regarding the adaptive process and how it is connected to production levels and resilience, which is the ability of an animal to adapt to stress or an imbalance in homeostasis. Sheep is a species that has been subjected to several natural and artificial selective pressures during its history, resulting in a highly specialized species for production and adaptation to challenging environments. Here, the data from multiple studies that aim at mapping selective sweeps across the sheep genome associated with production and adaptation traits were integrated to identify confirmed selective sweeps (CSS). In total, 37 studies were used to identify 518 CSS across the sheep genome, which were classified as production (147 prodCSS) and adaptation (219 adapCSS) CSS based on the frequency of each type of associated study. The genes within the CSS were associated with relevant biological processes for adaptation and production. For example, for adapCSS, the associated genes were related to the control of seasonality, circadian rhythm, and thermoregulation. On the other hand, genes associated with prodCSS were related to the control of feeding behaviour, reproduction, and cellular differentiation. In addition, genes harbouring both prodCSS and adapCSS showed an interesting association with lipid metabolism, suggesting a potential role of this process in the regulation of pleiotropic effects between these classes of traits. The findings of this study contribute to a deeper understanding of the genetic link between productivity and adaptability in sheep breeds. This information may provide insights into the genetic mechanisms that underlie undesirable genetic correlations between these two groups of traits and pave the way for a better understanding of resilience as a positive ability to respond to environmental stressors, where the negative effects on production level are minimized.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"90 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141074293","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}
Julien Corbeau, Cécile Grohs, Jeanlin Jourdain, Mekki Boussaha, Florian Besnard, Anne Barbat, Vincent Plassard, Julie Rivière, Christophe Hamelin, Jeremy Mortier, Didier Boichard, Raphaël Guatteo, Aurélien Capitan
{"title":"A recurrent de novo missense mutation in COL1A1 causes osteogenesis imperfecta type II and preterm delivery in Normande cattle","authors":"Julien Corbeau, Cécile Grohs, Jeanlin Jourdain, Mekki Boussaha, Florian Besnard, Anne Barbat, Vincent Plassard, Julie Rivière, Christophe Hamelin, Jeremy Mortier, Didier Boichard, Raphaël Guatteo, Aurélien Capitan","doi":"10.1186/s12711-024-00909-3","DOIUrl":"https://doi.org/10.1186/s12711-024-00909-3","url":null,"abstract":"Nine male and eight female calves born to a Normande artificial insemination bull named “Ly” were referred to the French National Observatory of Bovine Abnormalities for multiple fractures, shortened gestation, and stillbirth or perinatal mortality. Using Illumina BovineSNP50 array genotypes from affected calves and 84 half-sib controls, the associated locus was mapped to a 6.5-Mb interval on chromosome 19, assuming autosomal inheritance with germline mosaicism. Subsequent comparison of the whole-genome sequences of one case and 5116 control genomes, followed by genotyping in the affected pedigree, identified a de novo missense substitution within the NC1 domain of the COL1A1 gene (Chr19 g.36,473,965G > A; p.D1412N) as unique candidate variant. Interestingly, the affected residue was completely conserved among 243 vertebrate orthologs, and the same substitution in humans has been reported to cause type II osteogenesis imperfecta (OI), a connective tissue disorder that is characterized primarily by bone deformity and fragility. Moreover, three COL1A1 mutations have been described to cause the same syndrome in cattle. Necropsy, computed tomography, radiology, and histology confirmed the diagnosis of type II OI, further supporting the causality of this variant. In addition, a detailed analysis of gestation length and perinatal mortality in 1387 offspring of Ly and more than 160,000 progeny of 63 control bulls allowed us to statistically confirm in a large pedigree the association between type II OI and preterm delivery, which is probably due to premature rupture of fetal membranes and has been reported in several isolated cases of type II OI in humans and cattle. Finally, analysis of perinatal mortality rates and segregation distortion supported a low level of germ cell mosaicism in Ly, with an estimate of 4.5% to 7.7% of mutant sperm and thus 63 to 107 affected calves born. These numbers contrast with the 17 cases reported and raise concerns about the underreporting of congenital defects to heredo-surveillance platforms, even for textbook genetic syndromes. In conclusion, we describe a large animal model for a recurrent substitution in COL1A1 that is responsible for type II OI in humans. More generally, this study highlights the utility of such datasets and large half-sib families available in livestock species to characterize sporadic genetic defects.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"21 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141074240","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}