Pub Date : 2025-12-17DOI: 10.1186/s12711-025-01020-x
Endika Varela-Martínez,Ana Afonso,Dimitra Mainou,Fábio Teixeira,Telmo Nunes,Pedro Vieira,Inês Sarraguça,Cristina Martins,Natalia Campbell,Rafael Cordeiro da Silva,Tiago Perloiro,Luís Madeira de Carvalho,Ana Cristina Ferreira,Luís Telo da Gama,Helga Waap,Andreia J Amaral
BACKGROUNDAlthough coccidial infection is often asymptomatic in sheep, both clinical and subclinical forms of the disease are linked to considerable production losses, mainly in young lambs. Studies aiming to identify genetic markers for use in selection programs towards increasing genetic resistance to coccidiosis are lacking and have yet to be performed in Portuguese Merino sheep. The purpose of this study was to identify genomic regions associated with resistance to coccidiosis by conducting a genome-wide association study (GWAS) in Portuguese Merino sheep.RESULTSFrom an initial population of 1,022 sheep having known phenotypic characteristics, 206 and 202 distinct animals were genotyped using 50 K and 600 K Single Nucleotide Polymorphism (SNP) arrays, respectively. After the 50 K array was imputed using a 600 K array as reference, an association analysis was performed for faecal oocyst counts (FOC). We identified 12 SNPs that were significantly associated with resistance by using a chromosome-wide significance threshold. The significant SNPs were related to Ccser1, Thsd4, Eci1, Tnfrsf12a, Chrm3 and Slc20a2 genes. We identified 80 candidate genes located in the proximity of the significant SNPs using the defined confidence regions. Two types of gene set enrichment analyses were performed. Enrichment based on the set of candidate genes, identified the terms virus receptor activity and exogenous protein binding to be enriched, both due to two claudins, CLDN6 and CLDN9. Enrichment based on gene interactions, showed enrichment of terms related to transport vesicles, mainly due to the presence of Rab proteins.CONCLUSIONSGiven the role that Rab and Claudins play in host-parasite relationships, these results suggest the existence of reliable markers associated with resistance to coccidiosis. These markers should be explored in future studies to further validate their use in marker assisted selection, with the goal of enhancing sustainability of the breed conservation-management program.
{"title":"Claudin and Rab proteins are key molecular components involved in coccidiosis resistance in Portuguese Merino sheep.","authors":"Endika Varela-Martínez,Ana Afonso,Dimitra Mainou,Fábio Teixeira,Telmo Nunes,Pedro Vieira,Inês Sarraguça,Cristina Martins,Natalia Campbell,Rafael Cordeiro da Silva,Tiago Perloiro,Luís Madeira de Carvalho,Ana Cristina Ferreira,Luís Telo da Gama,Helga Waap,Andreia J Amaral","doi":"10.1186/s12711-025-01020-x","DOIUrl":"https://doi.org/10.1186/s12711-025-01020-x","url":null,"abstract":"BACKGROUNDAlthough coccidial infection is often asymptomatic in sheep, both clinical and subclinical forms of the disease are linked to considerable production losses, mainly in young lambs. Studies aiming to identify genetic markers for use in selection programs towards increasing genetic resistance to coccidiosis are lacking and have yet to be performed in Portuguese Merino sheep. The purpose of this study was to identify genomic regions associated with resistance to coccidiosis by conducting a genome-wide association study (GWAS) in Portuguese Merino sheep.RESULTSFrom an initial population of 1,022 sheep having known phenotypic characteristics, 206 and 202 distinct animals were genotyped using 50 K and 600 K Single Nucleotide Polymorphism (SNP) arrays, respectively. After the 50 K array was imputed using a 600 K array as reference, an association analysis was performed for faecal oocyst counts (FOC). We identified 12 SNPs that were significantly associated with resistance by using a chromosome-wide significance threshold. The significant SNPs were related to Ccser1, Thsd4, Eci1, Tnfrsf12a, Chrm3 and Slc20a2 genes. We identified 80 candidate genes located in the proximity of the significant SNPs using the defined confidence regions. Two types of gene set enrichment analyses were performed. Enrichment based on the set of candidate genes, identified the terms virus receptor activity and exogenous protein binding to be enriched, both due to two claudins, CLDN6 and CLDN9. Enrichment based on gene interactions, showed enrichment of terms related to transport vesicles, mainly due to the presence of Rab proteins.CONCLUSIONSGiven the role that Rab and Claudins play in host-parasite relationships, these results suggest the existence of reliable markers associated with resistance to coccidiosis. These markers should be explored in future studies to further validate their use in marker assisted selection, with the goal of enhancing sustainability of the breed conservation-management program.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"21 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145771572","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}
BACKGROUNDCarcass composition traits, such as lean meat percentage, bone percentage, and number of ribs, are critical factors determining meat production and profitability of pigs. Traditional slaughter measurements are time-consuming, labor-intensive and invasive and cannot be evaluated on selection candidates. However, computed tomography scanning, a non-invasive technique, enables in vivo measurement of these traits, facilitating rapid accumulation of extensive phenotypic data. Despite these advances, the genetic mechanisms underlying computed tomography-based carcass traits remain largely unexplored.RESULTSIn this study, we performed a multi-ancestry genome-wide association meta-analysis (MA-GWAMA) using low-coverage whole-genome sequencing data from four breeds (1222 Duroc, 582 Landrace, 1018 Yorkshire, and 448 Piétrain). In total, we identified 11 independent genome-wide significant loci associated with carcass composition traits in the meta-analysis. Compared to standard genomic best linear unbiased prediction, weighting MA-GWAMA-significant SNPs increased genomic prediction accuracy in an independent population (N = 365, including 136 Duroc, 65 Landrace, 50 Piétrain, and 114 Yorkshire) by 16.3% for lean meat percentage, by 6.1% for bone percentage, and by 79.4% for number of ribs. Integrating MA-GWAMA results with public eQTL and single-cell data prioritized ALPK2 as a candidate gene for lean meat percentage, and ABCD4 and SLC8A3 as candidate genes for the number of ribs.CONCLUSIONSOur study demonstrates the efficacy of computed tomography phenotyping coupled with multi-omics integration for dissecting the genetic architecture of porcine carcass composition traits. The prioritized variants and genes provide valuable targets for molecular breeding programs to enhance meat quality in pigs.
{"title":"Multi-ancestry genome-wide association meta-analysis identifies candidate genes for computed tomography-based carcass composition traits in pigs.","authors":"He Han,Pengfei Yu,Zhenyang Zhang,Ran Wei,Wei Zhao,Xiaoliang Hou,Jianlan Wang,Yongqi He,Yan Fu,Zhen Wang,Yuchun Pan,Qishan Wang,Zhe Zhang","doi":"10.1186/s12711-025-01023-8","DOIUrl":"https://doi.org/10.1186/s12711-025-01023-8","url":null,"abstract":"BACKGROUNDCarcass composition traits, such as lean meat percentage, bone percentage, and number of ribs, are critical factors determining meat production and profitability of pigs. Traditional slaughter measurements are time-consuming, labor-intensive and invasive and cannot be evaluated on selection candidates. However, computed tomography scanning, a non-invasive technique, enables in vivo measurement of these traits, facilitating rapid accumulation of extensive phenotypic data. Despite these advances, the genetic mechanisms underlying computed tomography-based carcass traits remain largely unexplored.RESULTSIn this study, we performed a multi-ancestry genome-wide association meta-analysis (MA-GWAMA) using low-coverage whole-genome sequencing data from four breeds (1222 Duroc, 582 Landrace, 1018 Yorkshire, and 448 Piétrain). In total, we identified 11 independent genome-wide significant loci associated with carcass composition traits in the meta-analysis. Compared to standard genomic best linear unbiased prediction, weighting MA-GWAMA-significant SNPs increased genomic prediction accuracy in an independent population (N = 365, including 136 Duroc, 65 Landrace, 50 Piétrain, and 114 Yorkshire) by 16.3% for lean meat percentage, by 6.1% for bone percentage, and by 79.4% for number of ribs. Integrating MA-GWAMA results with public eQTL and single-cell data prioritized ALPK2 as a candidate gene for lean meat percentage, and ABCD4 and SLC8A3 as candidate genes for the number of ribs.CONCLUSIONSOur study demonstrates the efficacy of computed tomography phenotyping coupled with multi-omics integration for dissecting the genetic architecture of porcine carcass composition traits. The prioritized variants and genes provide valuable targets for molecular breeding programs to enhance meat quality in pigs.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"24 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145771573","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}
Pub Date : 2025-12-16DOI: 10.1186/s12711-025-01017-6
Hui Wen,Harvey D Blackburn,Henrique A Mulim,Hinayah R Oliveira,Susanne Hermesch,Ching-Yi Chen,Justin Holl,Allan P Schinckel,Luiz F Brito
BACKGROUNDDuroc is one of the most popular terminal sire pig breeds worldwide due to its greater growth rate, meat quality, feed efficiency, and carcass characteristics compared to other breeds. Despite the breed's popularity, its developmental history, genetic diversity, and genetic relationships with other pig breeds remain largely unknown. Therefore, the primary objective of this study was to investigate population structure and genetic diversity of Duroc subpopulations from Europe, North America, and Australia, and of other pig breeds.RESULTSThe studied pig populations were differentiated into five subgroups(European and North American Durocs, Australian Durocs, Asian-Pacific pig breeds, and two other breed groups [OBP1 and OBP2]), consistent with their geographical origins, as revealed by population structure analyses. The estimated effective population size (Ne) of Duroc subpopulations ranged from 17 to 47, while the Ne for the combined Duroc subpopulations was 172. A total of 140,713 runs of homozygosity (ROHs) were identified across all individuals, with 98,039 ROHs in Durocs and 42,674 in other pig breeds. Durocs had a greater number and proportion of longer ROHs (> 8 Mb) compared to other pig breeds. The ROH-based inbreeding (FROH) values were significantly greater in Durocs than in most of the other breeds, indicating the need for better management of genetic diversity in the breed. We observed strong correlations (> 0.65) between different inbreeding metrics in all the studied pig populations. A total of 43, 18, 27, 37, and 20 candidate genes were identified in the ROH islands for European and North American Durocs, Australian Durocs, Asian-Pacific pigs, OBP1, and OBP2 pigs, respectively. The significant KEGG pathways were mainly related to growth, metabolism, immune system, cellular processes, and signal transduction.CONCLUSIONSSignificant differences exist in genetic diversity, population structure, and ancestry within Duroc subpopulations and between Duroc and other pig breeds. The observed inbreeding levels in Duroc subpopulations indicate the need for better management of genetic diversity within the breed. Functional enrichment analyses of shared ROH islands provide new insights into biological pathways shaped by selection decisions in the past decades, especially those related to the immune system and energy metabolism.
{"title":"Characterization of genomic diversity and population structure of worldwide Duroc subpopulations and other pig breeds.","authors":"Hui Wen,Harvey D Blackburn,Henrique A Mulim,Hinayah R Oliveira,Susanne Hermesch,Ching-Yi Chen,Justin Holl,Allan P Schinckel,Luiz F Brito","doi":"10.1186/s12711-025-01017-6","DOIUrl":"https://doi.org/10.1186/s12711-025-01017-6","url":null,"abstract":"BACKGROUNDDuroc is one of the most popular terminal sire pig breeds worldwide due to its greater growth rate, meat quality, feed efficiency, and carcass characteristics compared to other breeds. Despite the breed's popularity, its developmental history, genetic diversity, and genetic relationships with other pig breeds remain largely unknown. Therefore, the primary objective of this study was to investigate population structure and genetic diversity of Duroc subpopulations from Europe, North America, and Australia, and of other pig breeds.RESULTSThe studied pig populations were differentiated into five subgroups(European and North American Durocs, Australian Durocs, Asian-Pacific pig breeds, and two other breed groups [OBP1 and OBP2]), consistent with their geographical origins, as revealed by population structure analyses. The estimated effective population size (Ne) of Duroc subpopulations ranged from 17 to 47, while the Ne for the combined Duroc subpopulations was 172. A total of 140,713 runs of homozygosity (ROHs) were identified across all individuals, with 98,039 ROHs in Durocs and 42,674 in other pig breeds. Durocs had a greater number and proportion of longer ROHs (> 8 Mb) compared to other pig breeds. The ROH-based inbreeding (FROH) values were significantly greater in Durocs than in most of the other breeds, indicating the need for better management of genetic diversity in the breed. We observed strong correlations (> 0.65) between different inbreeding metrics in all the studied pig populations. A total of 43, 18, 27, 37, and 20 candidate genes were identified in the ROH islands for European and North American Durocs, Australian Durocs, Asian-Pacific pigs, OBP1, and OBP2 pigs, respectively. The significant KEGG pathways were mainly related to growth, metabolism, immune system, cellular processes, and signal transduction.CONCLUSIONSSignificant differences exist in genetic diversity, population structure, and ancestry within Duroc subpopulations and between Duroc and other pig breeds. The observed inbreeding levels in Duroc subpopulations indicate the need for better management of genetic diversity within the breed. Functional enrichment analyses of shared ROH islands provide new insights into biological pathways shaped by selection decisions in the past decades, especially those related to the immune system and energy metabolism.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"9 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145765343","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}
Pub Date : 2025-12-16DOI: 10.1186/s12711-025-01022-9
Felix Heinrich,Thomas M Lange,Faisal Ramzan,Mehmet Gültas,Armin O Schmitt
BACKGROUNDGenomic selection relies on a variety of statistical and machine learning methods to predict phenotypes from genomic data. Since no single method consistently outperforms others across datasets, evaluating and comparing model performance is essential. However, standard evaluation metrics such as Pearson's correlation coefficient and mean squared error treat genomic prediction as a regression problem, assessing overall fit rather than the effectiveness of selecting top-performing individuals for breeding. This disconnect can lead to suboptimal model selection in practice.RESULTSTo address this, we present the normalized cumulative gain (NCG) as an alternative evaluation measure that directly measures the phenotypic gain achieved from the individuals selected by the model. We applied this measure on four animal and plant datasets to compare nine commonly used methods for genomic prediction.CONCLUSIONSNCG offers an intuitive and interpretable measure of selection efficiency, focusing solely on the individuals that would actually be chosen. We further demonstrate that calculating the performance under all possible selection thresholds provides more information than a single or few arbitrary thresholds. This more granular analysis shows that the performance of the methods may differ under varying selection intensities and can provide guidance for the choice of selection intensity. Our approach is implemented in R and is available at https://github.com/FelixHeinrich/GS_Comparison_with_NCG.
{"title":"Normalized cumulative gain as an alternative evaluation measure for genomic selection models.","authors":"Felix Heinrich,Thomas M Lange,Faisal Ramzan,Mehmet Gültas,Armin O Schmitt","doi":"10.1186/s12711-025-01022-9","DOIUrl":"https://doi.org/10.1186/s12711-025-01022-9","url":null,"abstract":"BACKGROUNDGenomic selection relies on a variety of statistical and machine learning methods to predict phenotypes from genomic data. Since no single method consistently outperforms others across datasets, evaluating and comparing model performance is essential. However, standard evaluation metrics such as Pearson's correlation coefficient and mean squared error treat genomic prediction as a regression problem, assessing overall fit rather than the effectiveness of selecting top-performing individuals for breeding. This disconnect can lead to suboptimal model selection in practice.RESULTSTo address this, we present the normalized cumulative gain (NCG) as an alternative evaluation measure that directly measures the phenotypic gain achieved from the individuals selected by the model. We applied this measure on four animal and plant datasets to compare nine commonly used methods for genomic prediction.CONCLUSIONSNCG offers an intuitive and interpretable measure of selection efficiency, focusing solely on the individuals that would actually be chosen. We further demonstrate that calculating the performance under all possible selection thresholds provides more information than a single or few arbitrary thresholds. This more granular analysis shows that the performance of the methods may differ under varying selection intensities and can provide guidance for the choice of selection intensity. Our approach is implemented in R and is available at https://github.com/FelixHeinrich/GS_Comparison_with_NCG.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"161 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145765344","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}
Pub Date : 2025-12-13DOI: 10.1186/s12711-025-01018-5
Simon Pouil,Joël Aubin,Florence Phocas
BACKGROUNDWith growing societal concerns about the sustainability of food production systems, there is increasing interest in considering not only economic gains but also environmental issues in breeding programs of farmed species. In this study, we compared expected selection responses for breeding programs aiming to minimize environmental impacts of the production of rainbow trout in France, one of the most important fish species in salmonid aquaculture. The consequences of genetic improvement based on environmental merit indices were investigated in a hypothetical rainbow trout production farm with a constant annual production of 300 tonnes of fish. The merit indices included three different traits: thermal growth coefficient (TGC), daily feed intake (DFI), and survival (SR). A cradle-to-farm-gate life cycle assessment was conducted to evaluate the environmental values of each trait, which served as weightings in breeding goals aiming at minimizing expected environmental impacts by genetic selection. We explored nine different environmental impact categories: climate change, terrestrial acidification, freshwater eutrophication, marine eutrophication, terrestrial ecotoxicology, freshwater ecotoxicology, land use, water dependence, and cumulative energy demand.RESULTSSelection accuracy ranged from 0.34 to 0.43, with the lowest accuracy observed for the breeding goal targeting reduced water dependence, and the highest for those targeting reductions in eutrophication and terrestrial ecotoxicity. Annual genetic gains in reductions of environmental impacts, expressed per tonne of trout, were high for reducing eutrophication potential (- 6.80 to - 2.61%) and terrestrial ecotoxicity (- 4.14 to - 1.59%), but negligible for water use reduction (- 0.04 to - 0.01%). Genetic changes in DFI and TGC led to substantial annual gains in feed conversion ratio, from 1.7 to 4.8%. However, SR showed no improvement and often declined, highlighting the difficulty of balancing genetic gains across traits.CONCLUSIONSWe demonstrated the benefits of using environmental values in breeding goals to minimize environmental impacts at the farm level, while maintaining high genetic gains in feed efficiency traits. Nevertheless, we also showed that selection efficiency was highly dependent of the impact category. Our results suggested that another selection strategy should be considered to avoid unfavourable consequences on SR.
{"title":"Deriving breeding goals and expected selection responses to reduce environmental impacts in rainbow trout farming.","authors":"Simon Pouil,Joël Aubin,Florence Phocas","doi":"10.1186/s12711-025-01018-5","DOIUrl":"https://doi.org/10.1186/s12711-025-01018-5","url":null,"abstract":"BACKGROUNDWith growing societal concerns about the sustainability of food production systems, there is increasing interest in considering not only economic gains but also environmental issues in breeding programs of farmed species. In this study, we compared expected selection responses for breeding programs aiming to minimize environmental impacts of the production of rainbow trout in France, one of the most important fish species in salmonid aquaculture. The consequences of genetic improvement based on environmental merit indices were investigated in a hypothetical rainbow trout production farm with a constant annual production of 300 tonnes of fish. The merit indices included three different traits: thermal growth coefficient (TGC), daily feed intake (DFI), and survival (SR). A cradle-to-farm-gate life cycle assessment was conducted to evaluate the environmental values of each trait, which served as weightings in breeding goals aiming at minimizing expected environmental impacts by genetic selection. We explored nine different environmental impact categories: climate change, terrestrial acidification, freshwater eutrophication, marine eutrophication, terrestrial ecotoxicology, freshwater ecotoxicology, land use, water dependence, and cumulative energy demand.RESULTSSelection accuracy ranged from 0.34 to 0.43, with the lowest accuracy observed for the breeding goal targeting reduced water dependence, and the highest for those targeting reductions in eutrophication and terrestrial ecotoxicity. Annual genetic gains in reductions of environmental impacts, expressed per tonne of trout, were high for reducing eutrophication potential (- 6.80 to - 2.61%) and terrestrial ecotoxicity (- 4.14 to - 1.59%), but negligible for water use reduction (- 0.04 to - 0.01%). Genetic changes in DFI and TGC led to substantial annual gains in feed conversion ratio, from 1.7 to 4.8%. However, SR showed no improvement and often declined, highlighting the difficulty of balancing genetic gains across traits.CONCLUSIONSWe demonstrated the benefits of using environmental values in breeding goals to minimize environmental impacts at the farm level, while maintaining high genetic gains in feed efficiency traits. Nevertheless, we also showed that selection efficiency was highly dependent of the impact category. Our results suggested that another selection strategy should be considered to avoid unfavourable consequences on SR.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"29 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145746652","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}
Pub Date : 2025-12-09DOI: 10.1186/s12711-025-01019-4
Bjarke G Poulsen,Daniela Lourenco,Tage Ostersen,Bjarne Nielsen,Natália G Leite,Mark Henryon,Ole F Christensen
BACKGROUNDThe aim of this study was to compare different statistical models for predicting breeding values for sow survival with right-censored phenotypes from rotationally crossbred and commercial sows. We tested two hypotheses. First, we hypothesized that single-trait relative risk models predict more accurate breeding values than single-trait linear repeatability models. Second, we hypothesized that a reproductive stage stratified linear repeatability model predicts more accurate breeding values than the standard single-trait linear repeatability models. The single-trait models predict breeding values for survival between farrowings, while the reproductive stage stratified models predict breeding values for both survival between a farrowing and the next service, and survival between a service and the next farrowing. The validation criterion was the Pearson correlation between adjusted phenotypes for the lifetime number of litters produced and predicted breeding values for survival converted to lifetime number of litters produced. All validation criteria were compared to one another and against zero using appropriate statistical tests and correction for multiple tests. Each model was constructed with two different multi-breed relationship matrices to ensure that the results were not affected by the choice between them.RESULTSThe values of the validation criteria for the single-trait models were significantly larger than zero and similar (0.02). The values of the validation criteria for the reproductive stage stratified linear repeatability models were both significantly larger than zero and significantly larger than those from the single-trait models (0.04 vs. 0.02).CONCLUSIONSThe relative risk and linear repeatability single-trait models for survival between subsequent farrowings predicted equally accurate breeding values (0.02), while the linear repeatability two-trait models for survival from services to their subsequent farrowings and farrowings to the subsequent services predicted more accurate breeding values than the single-trait models (0.04 vs. 0.02). However, the accuracy of breeding values was small for all models because the survival phenotypes used for prediction were censored and the heritability of complete survival times was moderate (8-9%). Therefore, the comparison would benefit from reevaluation in other populations, and the models should be improved upon before implementation in practical breeding programs.
背景：本研究的目的是比较旋转杂交母猪和商业母猪右删型母猪存活率的不同统计模型。我们检验了两个假设。首先，我们假设单性状相对风险模型比单性状线性可重复性模型预测更准确的育种值。其次，我们假设繁殖阶段分层线性可重复性模型比标准单性状线性可重复性模型预测更准确的育种值。单性状模型预测了两次分娩之间的存活率，而繁殖阶段分层模型预测了一次分娩和下一次分娩之间以及一次分娩和下一次分娩之间的存活率。验证标准是校正后的表型与转换为一生产仔数的预测繁殖值之间的Pearson相关性。使用适当的统计检验和多次检验的校正，将所有验证标准相互比较，并与零进行比较。每个模型都由两个不同的多品种关系矩阵构建，以确保结果不受它们之间选择的影响。结果单性状模型的验证标准值均显著大于零且相似（0.02）。生殖期分层线性重复性模型的验证标准值均显著大于零，且显著大于单性状模型的验证标准值（0.04 vs. 0.02）。结论相对危险度单性状模型和线性可重复性单性状模型预测的后续产仔之间的繁殖值准确度相同（0.02），而从产仔到后续产仔和产仔到后续产仔生存的线性可重复性双性状模型预测的繁殖值准确度高于单性状模型（0.04 vs. 0.02）。然而，所有模型的育种值的准确性都很小，因为用于预测的存活表型被剔除，并且完全存活时间的遗传力中等（8-9%）。因此，在其他种群中进行重新评估将有利于比较，在实际育种计划实施之前，应该对模型进行改进。
{"title":"Comparison between repeatability, reproductive stage stratified repeatability, and relative risk models for prediction of breeding values for functional survival in rotationally crossbred sows.","authors":"Bjarke G Poulsen,Daniela Lourenco,Tage Ostersen,Bjarne Nielsen,Natália G Leite,Mark Henryon,Ole F Christensen","doi":"10.1186/s12711-025-01019-4","DOIUrl":"https://doi.org/10.1186/s12711-025-01019-4","url":null,"abstract":"BACKGROUNDThe aim of this study was to compare different statistical models for predicting breeding values for sow survival with right-censored phenotypes from rotationally crossbred and commercial sows. We tested two hypotheses. First, we hypothesized that single-trait relative risk models predict more accurate breeding values than single-trait linear repeatability models. Second, we hypothesized that a reproductive stage stratified linear repeatability model predicts more accurate breeding values than the standard single-trait linear repeatability models. The single-trait models predict breeding values for survival between farrowings, while the reproductive stage stratified models predict breeding values for both survival between a farrowing and the next service, and survival between a service and the next farrowing. The validation criterion was the Pearson correlation between adjusted phenotypes for the lifetime number of litters produced and predicted breeding values for survival converted to lifetime number of litters produced. All validation criteria were compared to one another and against zero using appropriate statistical tests and correction for multiple tests. Each model was constructed with two different multi-breed relationship matrices to ensure that the results were not affected by the choice between them.RESULTSThe values of the validation criteria for the single-trait models were significantly larger than zero and similar (0.02). The values of the validation criteria for the reproductive stage stratified linear repeatability models were both significantly larger than zero and significantly larger than those from the single-trait models (0.04 vs. 0.02).CONCLUSIONSThe relative risk and linear repeatability single-trait models for survival between subsequent farrowings predicted equally accurate breeding values (0.02), while the linear repeatability two-trait models for survival from services to their subsequent farrowings and farrowings to the subsequent services predicted more accurate breeding values than the single-trait models (0.04 vs. 0.02). However, the accuracy of breeding values was small for all models because the survival phenotypes used for prediction were censored and the heritability of complete survival times was moderate (8-9%). Therefore, the comparison would benefit from reevaluation in other populations, and the models should be improved upon before implementation in practical breeding programs.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"1 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145710787","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}
Pub Date : 2025-11-27DOI: 10.1186/s12711-025-01016-7
Moh Sallam,Lina Göransson,Anne Larsen,Helena Wall,Wael Alhamid,Stefan Gunnarsson,Martin Johnsson,Dirk-Jan de Koning
BACKGROUNDPoultry is a global industry with laying hens that are genetically optimized for high egg yield. Keel bone fractures can affect up to 80% of laying hens, posing welfare and production problems. Therefore, genetic selection to reduce keel fractures is important. However, the lack of a reliable, automated, and heritable phenotypes for keel bones makes this a challenging task. The aim of this study was to (1) develop automated analyses of radiographic images to phenotype keel bones, and (2) investigate whether the proposed phenotypes are heritable and genetically correlated with the post-dissection scores of keel bone fractures and deviations. A total of 1051 laying hens (Bovans Brown and Lohmann Brown) from a commercial farm were x-rayed, followed by keel bone dissection and scoring for deviations and fractures. Furthermore, blood was sampled for genotyping using 50 K Illumina SNP chips. Keel bones were segmented (with ~ 0.90 accuracy) from the radiographic images using deep learning models, after which the images were automatically measured for general geometry and radiopacity. Multi-trait genomic restricted maximum likelihood was used to estimate genetic parameters.RESULTSHeritability estimates ranged from 0.28 to 0.30 for both keel deviations and fractures observed post-dissection. The automated phenotypes had heritability estimates ranging from 0.07 to 0.10 for keel radiopacity and from 0.11 to 0.39 for keel geometry. Estimates of genetic correlations of keel geometry with keel deviation and fractures ranged from -0.57 to 0.72.CONCLUSIONSAutomated methods were developed for measuring keel bone radiopacity and geometry. Keel concave area was found to be a reliable and heritable phenotype that breeding companies can use to reduce keel deviations and fractures. These methods can also be adapted to measure other bones (e.g., tibiotarsal) or objects (e.g., eggs), allowing breeders to quickly compute phenotypes for keel, tibia, and egg size from the same radiographic image. The developed methods are well-suited for large-scale studies to assess different housing environments and nutrition strategies aimed at improving keel bone conditions.
家禽业是一个全球性的产业，其蛋鸡是经过基因优化的高产蛋鸡。高达80%的蛋鸡会受到龙骨骨折的影响，造成福利和生产问题。因此，通过遗传选择来减少龙骨骨折是很重要的。然而，缺乏可靠的、自动化的和可遗传的龙骨表型使得这项任务具有挑战性。本研究的目的是：(1)开发自动分析的影像学图像，以龙骨表型，(2)调查所提出的表型是否可遗传，并与龙骨骨折和偏差的解剖后评分遗传相关。对来自某商业农场的1051只蛋鸡（Bovans Brown和Lohmann Brown）进行x光检查，随后进行龙骨解剖并对偏差和骨折进行评分。此外，使用50 K Illumina SNP芯片采集血液进行基因分型。使用深度学习模型从放射图像中分割龙骨（精度约为0.90），然后自动测量图像的一般几何形状和放射不透明度。采用多性状基因组限制性最大似然法估计遗传参数。结果解剖后观察到的龙骨偏差和骨折的评分范围为0.28至0.30。自动表型的遗传率估计范围从0.07到0.10的龙骨放射度和从0.11到0.39的龙骨几何。龙骨几何形状与龙骨偏差和骨折的遗传相关性估计在-0.57到0.72之间。结论建立了测量龙骨放射透明度和几何形状的自动化方法。龙骨凹区被发现是一种可靠的遗传表型，育种公司可以利用它来减少龙骨偏差和骨折。这些方法也可以用于测量其他骨骼（例如，胫跖骨）或物体（例如，鸡蛋），使育种者能够快速计算龙骨、胫骨和鸡蛋大小的表型。开发的方法非常适合大规模研究，以评估不同的住房环境和营养策略，旨在改善龙骨状况。
{"title":"Genetics of digital phenotypes of keel bone in layer chickens and correlations with keel bone fractures and deviations.","authors":"Moh Sallam,Lina Göransson,Anne Larsen,Helena Wall,Wael Alhamid,Stefan Gunnarsson,Martin Johnsson,Dirk-Jan de Koning","doi":"10.1186/s12711-025-01016-7","DOIUrl":"https://doi.org/10.1186/s12711-025-01016-7","url":null,"abstract":"BACKGROUNDPoultry is a global industry with laying hens that are genetically optimized for high egg yield. Keel bone fractures can affect up to 80% of laying hens, posing welfare and production problems. Therefore, genetic selection to reduce keel fractures is important. However, the lack of a reliable, automated, and heritable phenotypes for keel bones makes this a challenging task. The aim of this study was to (1) develop automated analyses of radiographic images to phenotype keel bones, and (2) investigate whether the proposed phenotypes are heritable and genetically correlated with the post-dissection scores of keel bone fractures and deviations. A total of 1051 laying hens (Bovans Brown and Lohmann Brown) from a commercial farm were x-rayed, followed by keel bone dissection and scoring for deviations and fractures. Furthermore, blood was sampled for genotyping using 50 K Illumina SNP chips. Keel bones were segmented (with ~ 0.90 accuracy) from the radiographic images using deep learning models, after which the images were automatically measured for general geometry and radiopacity. Multi-trait genomic restricted maximum likelihood was used to estimate genetic parameters.RESULTSHeritability estimates ranged from 0.28 to 0.30 for both keel deviations and fractures observed post-dissection. The automated phenotypes had heritability estimates ranging from 0.07 to 0.10 for keel radiopacity and from 0.11 to 0.39 for keel geometry. Estimates of genetic correlations of keel geometry with keel deviation and fractures ranged from -0.57 to 0.72.CONCLUSIONSAutomated methods were developed for measuring keel bone radiopacity and geometry. Keel concave area was found to be a reliable and heritable phenotype that breeding companies can use to reduce keel deviations and fractures. These methods can also be adapted to measure other bones (e.g., tibiotarsal) or objects (e.g., eggs), allowing breeders to quickly compute phenotypes for keel, tibia, and egg size from the same radiographic image. The developed methods are well-suited for large-scale studies to assess different housing environments and nutrition strategies aimed at improving keel bone conditions.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"126 1","pages":"69"},"PeriodicalIF":4.1,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145613293","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}
Pub Date : 2025-11-13DOI: 10.1186/s12711-025-01013-w
A. Bouquet, M. Slagboom, J. R. Thomasen, M. Kargo, N. C. Friggens, L. Puillet
Predicting selection response for lactation efficiency in dairy cows is challenging, as the expression of this complex trait depends on dynamic interactions between the ability of cows to acquire nutrients and allocate them to different life functions. Moreover, the relative emphasis of these components may change due to energetic trade-offs between life functions when kept in limiting environments. The objective of this study is to present a new approach combining mechanistic and breeding scheme simulations to predict selection response on components of lactation efficiency of dairy cows under a non-limiting nutritional environment and when transferred to a limiting environment with a moderate feed restriction. These predictions were compared to the ones obtained with the conventional method used in quantitative genetics considering a typical dairy cattle breeding scheme and several breeding goals (BG) aiming at improving milk production, lactation efficiency and fertility. In the non-limiting environment, selection responses predicted by the two methods differed for both milk production and fertility. The sign and magnitude of differences depended on BGs. Selection response predictions were consistent only for BGs that did not change much the body reserve mobilization patterns of cows, and hence their conception probability. Indeed, pregnancy status impacted energy allocation of cows and consequently milk production, more energy being allocated to lactation in case of reproductive failure. Differences in selection response between modelling approaches were slightly increased when cows were reared in the limiting environment. Overall, the choice of prediction method led to substantial BG reranking with respect to selection response on milk production and fertility. Mechanistic-based predictions of selection response for lifetime efficiency were also sensitive to the nutritional environment and BG. Combining mechanistic and genetic modelling is a promising approach to benchmark breeding strategies of dairy cow lactation efficiency and better anticipate the impact of changes in energetic trade-offs induced both by selection and changes in the nutritional environment. Moreover, the simulations of phenotypic trajectories over cow lifetime before and after selection enabled a better understanding of the mechanisms underlying genetic improvement.
{"title":"Interfacing mechanistic and breeding scheme simulation to predict selection response on lactation efficiency in dairy cows under different nutritional environments","authors":"A. Bouquet, M. Slagboom, J. R. Thomasen, M. Kargo, N. C. Friggens, L. Puillet","doi":"10.1186/s12711-025-01013-w","DOIUrl":"https://doi.org/10.1186/s12711-025-01013-w","url":null,"abstract":"Predicting selection response for lactation efficiency in dairy cows is challenging, as the expression of this complex trait depends on dynamic interactions between the ability of cows to acquire nutrients and allocate them to different life functions. Moreover, the relative emphasis of these components may change due to energetic trade-offs between life functions when kept in limiting environments. The objective of this study is to present a new approach combining mechanistic and breeding scheme simulations to predict selection response on components of lactation efficiency of dairy cows under a non-limiting nutritional environment and when transferred to a limiting environment with a moderate feed restriction. These predictions were compared to the ones obtained with the conventional method used in quantitative genetics considering a typical dairy cattle breeding scheme and several breeding goals (BG) aiming at improving milk production, lactation efficiency and fertility. In the non-limiting environment, selection responses predicted by the two methods differed for both milk production and fertility. The sign and magnitude of differences depended on BGs. Selection response predictions were consistent only for BGs that did not change much the body reserve mobilization patterns of cows, and hence their conception probability. Indeed, pregnancy status impacted energy allocation of cows and consequently milk production, more energy being allocated to lactation in case of reproductive failure. Differences in selection response between modelling approaches were slightly increased when cows were reared in the limiting environment. Overall, the choice of prediction method led to substantial BG reranking with respect to selection response on milk production and fertility. Mechanistic-based predictions of selection response for lifetime efficiency were also sensitive to the nutritional environment and BG. Combining mechanistic and genetic modelling is a promising approach to benchmark breeding strategies of dairy cow lactation efficiency and better anticipate the impact of changes in energetic trade-offs induced both by selection and changes in the nutritional environment. Moreover, the simulations of phenotypic trajectories over cow lifetime before and after selection enabled a better understanding of the mechanisms underlying genetic improvement.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"54 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145498983","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}
Pork is a primary source of animal protein worldwide, and intramuscular fat (IMF) content is a key determinant of meat quality and consumer preference. To identify genetic regulators of IMF content, we leveraged RNA sequencing and whole-genome resequencing data from 79 Laiwu pigs renowned for high IMF content to conduct expression quantitative trait locus (eQTL) mapping. We integrated eQTL results with genome-wide association study (GWAS) data from 453 Chinese Lulai Black pigs (a crossbreed of Laiwu and Yorkshire pigs), and systematically identified candidate regulatory genes for IMF content by incorporating weighted gene co-expression network analysis (WGCNA) and correlation analysis in this population. We identified 9,763 cis-eQTLs at the genome-wide level (p < 5E−08) and 1,337 cis-eQTLs at the suggestive level (p < 5E−06). A 2.02 Mb cis-QTL region on Sus scrofa chromosome 9, containing 587 cis-eQTLs regulating MED17 expression, overlapped with an IMF-associated QTL detected by GWAS in Lulai Black pigs, a Laiwu-Yorkshire crossbreed. WGCNA identified three critical co-expression modules related to IMF content, with MED17 acting as a critical gene in a module linked to adipogenesis and lipid metabolism. Correlation analysis showed MED17 expression was negatively correlated with IMF content (FDR = 1.58E−02). In 3T3-L1 preadipocytes, adenovirus-mediated Med17 overexpression significantly reduced adipogenic differentiation and altered expression of adipogenesis-related genes (Pparg, Adipoq, Srebf1, Cpt1a, and Atgl), indicating that Med17 modulates adipocyte differentiation and lipid metabolism. This study identifies MED17 as a novel regulator of IMF content in pigs, bridging genomic variation, gene expression networks, and phenotypic traits. These findings provide mechanistic insights into IMF deposition and highlight the potential of integrative multi-omics approaches for genetic improvement of pork quality traits in breeding programs.
{"title":"Integrative analysis of genome and transcriptome reveals a novel regulator for pork intramuscular fat content","authors":"Xueyan Zhao, Jingxuan Li, Wanli Jia, Yifan Ren, Yanping Wang, Tizhong Shan, Jiying Wang","doi":"10.1186/s12711-025-01014-9","DOIUrl":"https://doi.org/10.1186/s12711-025-01014-9","url":null,"abstract":"Pork is a primary source of animal protein worldwide, and intramuscular fat (IMF) content is a key determinant of meat quality and consumer preference. To identify genetic regulators of IMF content, we leveraged RNA sequencing and whole-genome resequencing data from 79 Laiwu pigs renowned for high IMF content to conduct expression quantitative trait locus (eQTL) mapping. We integrated eQTL results with genome-wide association study (GWAS) data from 453 Chinese Lulai Black pigs (a crossbreed of Laiwu and Yorkshire pigs), and systematically identified candidate regulatory genes for IMF content by incorporating weighted gene co-expression network analysis (WGCNA) and correlation analysis in this population. We identified 9,763 cis-eQTLs at the genome-wide level (p < 5E−08) and 1,337 cis-eQTLs at the suggestive level (p < 5E−06). A 2.02 Mb cis-QTL region on Sus scrofa chromosome 9, containing 587 cis-eQTLs regulating MED17 expression, overlapped with an IMF-associated QTL detected by GWAS in Lulai Black pigs, a Laiwu-Yorkshire crossbreed. WGCNA identified three critical co-expression modules related to IMF content, with MED17 acting as a critical gene in a module linked to adipogenesis and lipid metabolism. Correlation analysis showed MED17 expression was negatively correlated with IMF content (FDR = 1.58E−02). In 3T3-L1 preadipocytes, adenovirus-mediated Med17 overexpression significantly reduced adipogenic differentiation and altered expression of adipogenesis-related genes (Pparg, Adipoq, Srebf1, Cpt1a, and Atgl), indicating that Med17 modulates adipocyte differentiation and lipid metabolism. This study identifies MED17 as a novel regulator of IMF content in pigs, bridging genomic variation, gene expression networks, and phenotypic traits. These findings provide mechanistic insights into IMF deposition and highlight the potential of integrative multi-omics approaches for genetic improvement of pork quality traits in breeding programs.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"24 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145447197","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}
The relative abundance of some bacteria in the gut of pigs is heritable, suggesting that host genetics may recursively influence boar semen quality by affecting the composition and function of gut microbiota. Therefore, it is essential to elucidate the specific contributions of heritable versus non-heritable gut microbiota to semen quality traits. Our study aimed to identify heritable and non-heritable bacterial taxa at the genus level in the boar gut and to predict their functions and respective contributions to semen quality traits. At the genus level, 39 heritable and 91 non-heritable bacterial taxa were identified. Functional analysis revealed that predicted microbial functions in both groups were primarily enriched in carbohydrate, nucleotide, and amino acid metabolism. We further analyzed the average microbiability of heritable and non-heritable bacteria on short-chain fatty acids (SCFAs) and semen quality traits. The relative abundance of heritable bacteria was found to contribute more to SCFAs levels and semen quality than non-heritable bacteria. Mediation analysis revealed that SCFAs could mediate the influence of the relative abundance of heritable bacteria on host phenotypes, identifying 99 significant genus-SCFAs-semen quality trait mediation links. Our findings underscore the substantial role of the relative abundance of heritable gut bacteria in shaping porcine semen quality through SCFAs mediation. These results highlight the potential of targeted microbiome interventions to enhance reproductive traits in pigs.
{"title":"Unraveling the role of bacteria with heritable versus non-heritable relative abundance in the gut on boar semen quality","authors":"Liangliang Guo, Xiaoqi Pei, Jiajian Tan, Haiqing Sun, Siwen Jiang, Hongkui Wei, Jian Peng","doi":"10.1186/s12711-025-00990-2","DOIUrl":"https://doi.org/10.1186/s12711-025-00990-2","url":null,"abstract":"The relative abundance of some bacteria in the gut of pigs is heritable, suggesting that host genetics may recursively influence boar semen quality by affecting the composition and function of gut microbiota. Therefore, it is essential to elucidate the specific contributions of heritable versus non-heritable gut microbiota to semen quality traits. Our study aimed to identify heritable and non-heritable bacterial taxa at the genus level in the boar gut and to predict their functions and respective contributions to semen quality traits. At the genus level, 39 heritable and 91 non-heritable bacterial taxa were identified. Functional analysis revealed that predicted microbial functions in both groups were primarily enriched in carbohydrate, nucleotide, and amino acid metabolism. We further analyzed the average microbiability of heritable and non-heritable bacteria on short-chain fatty acids (SCFAs) and semen quality traits. The relative abundance of heritable bacteria was found to contribute more to SCFAs levels and semen quality than non-heritable bacteria. Mediation analysis revealed that SCFAs could mediate the influence of the relative abundance of heritable bacteria on host phenotypes, identifying 99 significant genus-SCFAs-semen quality trait mediation links. Our findings underscore the substantial role of the relative abundance of heritable gut bacteria in shaping porcine semen quality through SCFAs mediation. These results highlight the potential of targeted microbiome interventions to enhance reproductive traits in pigs.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"36 2 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145447198","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：