Pub Date : 2025-07-16DOI: 10.1186/s12711-025-00986-y
Jianhai Chen, Ivan Jakovlić, Mikhail Sablin, Shengqian Xia, Zhixiang Xu, Yapin Guo, Renzuo Kuang, Jie Zhong, Yangying Jia, Nhien Thuy Thi Tran, Hao Yang, Hong Ma, Nikica Šprem, Jianlin Han, Di Liu, Yunxia Zhao, Shuhong Zhao
Domestic piglets often die of hypothermia, whereas Eurasian wild boar (Sus scrofa) thrives from tropical lowlands to subarctic forests. The thermoregulation of wild boar offers a natural experiment to uncover the genetic basis of cold adaptation. We conducted whole-genome resequencing on wild populations from cold regions (northern and northeastern Asia, with six samples) and warm regions (southeastern Asia and southern China, with five samples). By integrating publicly available data, we compiled a core dataset of 48 wild boar samples and an extended dataset of 445 wild boar and domestic pig samples to identify candidate genes related to cold adaptation. To investigate the functional effects of two candidate variants under positive selection, we performed CUT&Tag and RNA-seq using the northeastern Asian Min pig breed as a proxy for a cold-adapted population. Our study identified candidate genes associated with cold adaptation, which are significantly enriched in thermogenesis, fat cell development, and adipose tissue pathways. We discovered two enhancer variants under positive selection: an intronic variant of IGF1R (rs341219502) and an exonic variant of BRD4 (rs327139795). These variants exhibited the highest differentiation between populations of wild boar and domestic pigs in cold and warm region populations. Furthermore, these rare variants were absent in outgroup species and warm-region wild boars but were nearly fixed in cold-region populations. The H3K27ac CUT&Tag profiling revealed that the rs341219502 variant of IGF1R is linked to the gain of novel binding sites for three transcription factors involving regulatory changes in enhancer function. In contrast, the rs327139795 variant of BRD4 may result in the loss of a phosphorylation site due to an alteration in the amino acid sequence. Our study identified candidate genes for cold adaptation in wild boar. The variant rs341219502 in the IGF1R enhancer and the variant rs327139795 in the BRD4 exon, both of which were under positive selection and nearly fixed in populations from cold regions, suggest they may have originated de novo in these populations. Further analysis indicated that rs341219502 could influence enhancer function, while rs327139795 may affect amino acid alterations. Overall, our study highlights the adaptive evolution of genomic molecules that contribute to the remarkable environmental flexibility of wild boar.
{"title":"Positive selection on rare variants of IGF1R and BRD4 underlying the cold adaptation of wild boar","authors":"Jianhai Chen, Ivan Jakovlić, Mikhail Sablin, Shengqian Xia, Zhixiang Xu, Yapin Guo, Renzuo Kuang, Jie Zhong, Yangying Jia, Nhien Thuy Thi Tran, Hao Yang, Hong Ma, Nikica Šprem, Jianlin Han, Di Liu, Yunxia Zhao, Shuhong Zhao","doi":"10.1186/s12711-025-00986-y","DOIUrl":"https://doi.org/10.1186/s12711-025-00986-y","url":null,"abstract":"Domestic piglets often die of hypothermia, whereas Eurasian wild boar (Sus scrofa) thrives from tropical lowlands to subarctic forests. The thermoregulation of wild boar offers a natural experiment to uncover the genetic basis of cold adaptation. We conducted whole-genome resequencing on wild populations from cold regions (northern and northeastern Asia, with six samples) and warm regions (southeastern Asia and southern China, with five samples). By integrating publicly available data, we compiled a core dataset of 48 wild boar samples and an extended dataset of 445 wild boar and domestic pig samples to identify candidate genes related to cold adaptation. To investigate the functional effects of two candidate variants under positive selection, we performed CUT&Tag and RNA-seq using the northeastern Asian Min pig breed as a proxy for a cold-adapted population. Our study identified candidate genes associated with cold adaptation, which are significantly enriched in thermogenesis, fat cell development, and adipose tissue pathways. We discovered two enhancer variants under positive selection: an intronic variant of IGF1R (rs341219502) and an exonic variant of BRD4 (rs327139795). These variants exhibited the highest differentiation between populations of wild boar and domestic pigs in cold and warm region populations. Furthermore, these rare variants were absent in outgroup species and warm-region wild boars but were nearly fixed in cold-region populations. The H3K27ac CUT&Tag profiling revealed that the rs341219502 variant of IGF1R is linked to the gain of novel binding sites for three transcription factors involving regulatory changes in enhancer function. In contrast, the rs327139795 variant of BRD4 may result in the loss of a phosphorylation site due to an alteration in the amino acid sequence. Our study identified candidate genes for cold adaptation in wild boar. The variant rs341219502 in the IGF1R enhancer and the variant rs327139795 in the BRD4 exon, both of which were under positive selection and nearly fixed in populations from cold regions, suggest they may have originated de novo in these populations. Further analysis indicated that rs341219502 could influence enhancer function, while rs327139795 may affect amino acid alterations. Overall, our study highlights the adaptive evolution of genomic molecules that contribute to the remarkable environmental flexibility of wild boar.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"4 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144640363","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 : 2025-07-14DOI: 10.1186/s12711-025-00983-1
Erin G. Smith, Samuel F. Walkom, Dominic L. Waters, Sam A. Clark
General resilience in animals can be quantified by analysing the variability in longitudinal data. However, it is unclear whether resilience indicators derived from different longitudinal data series can predict resilience to known or unknown disturbances in sheep. This study aimed to use two sources of longitudinal data, wool fibre diameter and body weight, to develop potential indicators for resilience to the known stress of weaning and overall resilience to unknown disturbances. The genetic parameters of these traits were assessed, along with the genetic correlations between traits from different data series and different definitions of resilience. Additionally, correlations between resilience indicators, health and production traits were estimated to evaluate the suitability of including resilience indicators in breeding programs. Fibre diameter and body weight records from approximately 6500 yearling Merino sheep were used to estimate four resilience indicators of resilience towards unknown disturbances: log-transformed variance (Lnvar), lag-1 Auto (Auto), skewness (Skewness) and absolute difference in the deviations (ABS) from these curves. Three other traits, rate of change in the response and recovery (ROC_response and ROC_recovery) and area between curves (ABC) during a known disturbance of weaning, were also estimated. Resilience indicators were found to be lowly heritable (0.03 ± 0.01 to 0.18 ± 0.04). Genetic correlations between the general resilience indicator and the indicator of resilience to weaning stress were generally moderate, particularly in the wool fibre diameter data, suggesting these may represent similar traits. Genetic correlations between resilience indicators derived from wool fibre diameter and body weight data were typically weak to moderate, which indicates that they possibly capture different aspects of resilience. The genetic correlations between resilience indicators and health traits were mostly low, except for body condition score. Correlations between resilience and production traits were low to moderate and favourable. Resilience indicators based on deviations in wool fibre diameter and body weight can be used to potentially select animals that are less affected by environmental disturbances. The genetic correlations between resilience indicators and health and production traits suggest that these traits could be included in breeding programs to improve resilience without adversely affecting production traits.
动物的一般恢复力可以通过分析纵向数据的可变性来量化。然而，尚不清楚来自不同纵向数据系列的弹性指标是否可以预测绵羊对已知或未知干扰的弹性。本研究旨在利用两种纵向数据来源，羊毛纤维直径和体重，以开发对已知断奶应激和对未知干扰的整体恢复能力的潜在指标。分析了这些性状的遗传参数，以及不同数据序列和不同弹性定义性状之间的遗传相关性。此外，还估计了恢复力指标、健康和生产性状之间的相关性，以评估将恢复力指标纳入育种计划的适用性。利用约6500只美利奴羊的纤维直径和体重记录，估计了对未知干扰的弹性的4个指标：对数变换方差（Lnvar）、lag-1 Auto （Auto）、偏度（skewness）和这些曲线的绝对偏差差（ABS）。另外三个特征，在已知的断奶干扰期间，反应和恢复的变化率（ROC_response和ROC_recovery）和曲线间面积（ABC）也被估计。恢复力指标的可遗传性较低（0.03±0.01 ~ 0.18±0.04）。一般恢复力指标和断奶应激恢复力指标之间的遗传相关性一般是中等的，特别是在羊毛纤维直径数据中，这表明它们可能代表相似的性状。从羊毛纤维直径和体重数据得出的弹性指标之间的遗传相关性通常为弱至中等，这表明它们可能捕获了弹性的不同方面。韧性指标与健康性状的遗传相关性除体质评分外，其余均较低。恢复力与生产性状的相关性为低至中等和有利。基于羊毛纤维直径和体重偏差的弹性指标可用于潜在地选择受环境干扰影响较小的动物。抗逆性指标与健康和生产性状之间的遗传相关性表明，这些性状可以纳入育种计划，以提高抗逆性，而不会对生产性状产生不利影响。
{"title":"Estimating the genetic parameters of resilience toward known and unknown disturbances in sheep using wool fibre diameter and body weight variability","authors":"Erin G. Smith, Samuel F. Walkom, Dominic L. Waters, Sam A. Clark","doi":"10.1186/s12711-025-00983-1","DOIUrl":"https://doi.org/10.1186/s12711-025-00983-1","url":null,"abstract":"General resilience in animals can be quantified by analysing the variability in longitudinal data. However, it is unclear whether resilience indicators derived from different longitudinal data series can predict resilience to known or unknown disturbances in sheep. This study aimed to use two sources of longitudinal data, wool fibre diameter and body weight, to develop potential indicators for resilience to the known stress of weaning and overall resilience to unknown disturbances. The genetic parameters of these traits were assessed, along with the genetic correlations between traits from different data series and different definitions of resilience. Additionally, correlations between resilience indicators, health and production traits were estimated to evaluate the suitability of including resilience indicators in breeding programs. Fibre diameter and body weight records from approximately 6500 yearling Merino sheep were used to estimate four resilience indicators of resilience towards unknown disturbances: log-transformed variance (Lnvar), lag-1 Auto (Auto), skewness (Skewness) and absolute difference in the deviations (ABS) from these curves. Three other traits, rate of change in the response and recovery (ROC_response and ROC_recovery) and area between curves (ABC) during a known disturbance of weaning, were also estimated. Resilience indicators were found to be lowly heritable (0.03 ± 0.01 to 0.18 ± 0.04). Genetic correlations between the general resilience indicator and the indicator of resilience to weaning stress were generally moderate, particularly in the wool fibre diameter data, suggesting these may represent similar traits. Genetic correlations between resilience indicators derived from wool fibre diameter and body weight data were typically weak to moderate, which indicates that they possibly capture different aspects of resilience. The genetic correlations between resilience indicators and health traits were mostly low, except for body condition score. Correlations between resilience and production traits were low to moderate and favourable. Resilience indicators based on deviations in wool fibre diameter and body weight can be used to potentially select animals that are less affected by environmental disturbances. The genetic correlations between resilience indicators and health and production traits suggest that these traits could be included in breeding programs to improve resilience without adversely affecting production traits.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"23 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144622229","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}
In recent years, genetic evaluations in cattle breeding have shifted from purely national evaluations to multinational evaluations considering relatives from other countries. Integrating international estimated breeding values (EBVs) into national genomic evaluations presents challenges due to differences in evaluation methodologies and data sources. This study focused on the impact of blending internationally derived EBVs with national EBVs in the single-step genomic evaluation of German beef cattle using three approaches to deregressing EBVs. The national phenotypic data for four breeds (Angus, Charolais, Limousin, and Simmental) were obtained from the routine German beef cattle evaluation of December 2022, and the international EBVs were obtained from the routine Interbeef evaluation of January 2023. Scalar (Garrick (GA), Van Raden (VR)) and matrix deregression approaches were compared for reversibility of EBVs. A forward validation study was used to evaluate the accuracy, dispersion and level bias obtained in a purely national single-step evaluation, and single-step genomic evaluations blended with DRPs obtained from the three deregression approaches. A validation study based on forward prediction showed improved accuracy, and reduced dispersion bias in the EBVs blended with international EBVs compared to purely national EBVs, particularly for the direct and maternal effects of 200-day weight. As expected, Pearson correlation analysis revealed that the matrix deregression (> 0.99) approach outperformed the scalar deregression approaches (0.75–0.99), exhibiting a greater correlation between the EBVs obtained from DRPs and the EBVs obtained from phenotypes across the various breeds and traits in our study. A forward validation study with and without integrating foreign data across the three deregression methods showed improvement in reducing dispersion bias, as indicated by the regression coefficient. The GEBVs from an evaluation incorporating foreign information with national data showed a higher correlation to the GEBVs from a truncated evaluation than those from an evaluation without foreign information. These findings underscore the importance of accurately integrating foreign EBVs to enhance national genomic evaluations and genetic progress in livestock populations. Our results show that the matrix approach to deregressing EBVs performs optimally across traits and breeds. However, the VR deregression approach can serve as an alternative in situations where the matrix deregression approach might be too technical to implement.
近年来，牛的遗传评价已从单纯的国家评价转向考虑其他国家亲缘关系的多国评价。由于评估方法和数据来源的差异，将国际估计育种值（ebv）整合到国家基因组评估中存在挑战。本研究的重点是在德国肉牛的单步基因组评估中，使用三种方法去除ebv，将国际衍生ebv与本国ebv混合的影响。4个品种（安格斯、夏洛莱、利穆赞和西蒙塔尔）的全国表型数据来自2022年12月的德国肉牛常规评估，国际ebv数据来自2023年1月的Interbeef常规评估。比较标量(Garrick （GA), Van Raden (VR)）和矩阵去回归方法对ebv可逆性的影响。采用前向验证研究来评估纯国家单步评估获得的准确性、离散度和水平偏差，以及单步基因组评估与三种去回归方法获得的DRPs混合。一项基于前向预测的验证研究表明，与纯粹的国内ebv相比，ebv与国际ebv混合的准确性更高，分散偏差减少，特别是对200天体重的直接和母体影响。正如预期的那样，Pearson相关分析显示，矩阵去回归方法（> 0.99）优于标量去回归方法（0.75-0.99），表明在我们的研究中，从DRPs中获得的ebv与从各种品种和性状的表型中获得的ebv之间存在更大的相关性。一项有和没有整合国外数据的前向验证研究表明，三种去回归方法在减少分散偏差方面有所改善，如回归系数所示。与不包含外国信息的评估相比，包含外国信息和国家数据的评估的gebv与截断评估的gebv具有更高的相关性。这些发现强调了准确整合外来ebv对加强国家基因组评估和牲畜种群遗传进展的重要性。我们的研究结果表明，矩阵方法解除ebv在性状和品种中表现最佳。然而，在矩阵解算方法可能过于技术性而无法实现的情况下，VR解算方法可以作为一种替代方案。
{"title":"The impact of deregressed foreign breeding values on national beef cattle single-step genomic evaluation","authors":"Damilola Adekale, Zengting Liu, Ross Evans, Thierry Pabiou, Reinhard Reents, Dierck Segelke, Jens Tetens","doi":"10.1186/s12711-025-00982-2","DOIUrl":"https://doi.org/10.1186/s12711-025-00982-2","url":null,"abstract":"In recent years, genetic evaluations in cattle breeding have shifted from purely national evaluations to multinational evaluations considering relatives from other countries. Integrating international estimated breeding values (EBVs) into national genomic evaluations presents challenges due to differences in evaluation methodologies and data sources. This study focused on the impact of blending internationally derived EBVs with national EBVs in the single-step genomic evaluation of German beef cattle using three approaches to deregressing EBVs. The national phenotypic data for four breeds (Angus, Charolais, Limousin, and Simmental) were obtained from the routine German beef cattle evaluation of December 2022, and the international EBVs were obtained from the routine Interbeef evaluation of January 2023. Scalar (Garrick (GA), Van Raden (VR)) and matrix deregression approaches were compared for reversibility of EBVs. A forward validation study was used to evaluate the accuracy, dispersion and level bias obtained in a purely national single-step evaluation, and single-step genomic evaluations blended with DRPs obtained from the three deregression approaches. A validation study based on forward prediction showed improved accuracy, and reduced dispersion bias in the EBVs blended with international EBVs compared to purely national EBVs, particularly for the direct and maternal effects of 200-day weight. As expected, Pearson correlation analysis revealed that the matrix deregression (> 0.99) approach outperformed the scalar deregression approaches (0.75–0.99), exhibiting a greater correlation between the EBVs obtained from DRPs and the EBVs obtained from phenotypes across the various breeds and traits in our study. A forward validation study with and without integrating foreign data across the three deregression methods showed improvement in reducing dispersion bias, as indicated by the regression coefficient. The GEBVs from an evaluation incorporating foreign information with national data showed a higher correlation to the GEBVs from a truncated evaluation than those from an evaluation without foreign information. These findings underscore the importance of accurately integrating foreign EBVs to enhance national genomic evaluations and genetic progress in livestock populations. Our results show that the matrix approach to deregressing EBVs performs optimally across traits and breeds. However, the VR deregression approach can serve as an alternative in situations where the matrix deregression approach might be too technical to implement.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"14 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144622210","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 : 2025-07-14DOI: 10.1186/s12711-025-00976-0
Bernadett Hegedűs, Natália Galoro Leite, J. Elizabeth Bolhuis, Piter Bijma
Ear and tail biting are behaviours in pigs that cause both welfare problems and financial losses. Data collection of behaviour is difficult at the large scale needed for breeding. The damage inflicted on victims can, however, serve as a proxy for animal breeding. Here, we analysed tail and ear damage scores on their original scale, binary scale, and summed versions of these damage traits to investigate which trait definition is best for genetic selection. Using data from six purebred lines (33,329 animals in total) we aimed to (1) estimate genetic parameters for ear and tail damage using direct genetic models, (2) estimate the genetic correlation between tail and ear damage, (3) compare different trait definitions and their impact on accuracy, dispersion, and bias of estimated breeding values (EBV), and (4) compare expected responses to selection for each trait definition. The heritability of the damage traits ranged from 0.04 to 0.06. Ear and tail damage were moderately correlated (0.41–0.45), meaning that the genetic propensity of being a victim is a different trait for tail versus ear biting. Estimates of the accuracy of the EBV for the traits with a five-fold cross-validation and the linear regression method based on pedigree relationships ranged from 0.27 to 0.57, the dispersion from 0.91 to 1.18, and the bias was negligible. With a selected proportion of 5%, genetic progress of ~ 0.20–0.78 genetic standard deviations per generation can be reached, depending on the trait. It was trait dependent whether direct or indirect selection yielded the most response. Ear and tail damage are heritable traits and are moderately positively correlated. The EBV for the evaluated traits related to ear and tail damage showed moderate accuracies, minor dispersion, and no bias. We hypothesize that from a welfare perspective, ear and tail damage on the original scale are the relevant breeding goal traits. For ear damage on the original scale, the highest response to selection can be expected when selecting on the trait itself, whereas for tail damage on the original scale, selection on summed damage showed the highest gain. Results from this study show that genetic improvement of the direct genetic effect of ear and tail damage is possible.
{"title":"Genetic parameters and potential of reducing tail and ear damage in pigs through breeding","authors":"Bernadett Hegedűs, Natália Galoro Leite, J. Elizabeth Bolhuis, Piter Bijma","doi":"10.1186/s12711-025-00976-0","DOIUrl":"https://doi.org/10.1186/s12711-025-00976-0","url":null,"abstract":"Ear and tail biting are behaviours in pigs that cause both welfare problems and financial losses. Data collection of behaviour is difficult at the large scale needed for breeding. The damage inflicted on victims can, however, serve as a proxy for animal breeding. Here, we analysed tail and ear damage scores on their original scale, binary scale, and summed versions of these damage traits to investigate which trait definition is best for genetic selection. Using data from six purebred lines (33,329 animals in total) we aimed to (1) estimate genetic parameters for ear and tail damage using direct genetic models, (2) estimate the genetic correlation between tail and ear damage, (3) compare different trait definitions and their impact on accuracy, dispersion, and bias of estimated breeding values (EBV), and (4) compare expected responses to selection for each trait definition. The heritability of the damage traits ranged from 0.04 to 0.06. Ear and tail damage were moderately correlated (0.41–0.45), meaning that the genetic propensity of being a victim is a different trait for tail versus ear biting. Estimates of the accuracy of the EBV for the traits with a five-fold cross-validation and the linear regression method based on pedigree relationships ranged from 0.27 to 0.57, the dispersion from 0.91 to 1.18, and the bias was negligible. With a selected proportion of 5%, genetic progress of ~ 0.20–0.78 genetic standard deviations per generation can be reached, depending on the trait. It was trait dependent whether direct or indirect selection yielded the most response. Ear and tail damage are heritable traits and are moderately positively correlated. The EBV for the evaluated traits related to ear and tail damage showed moderate accuracies, minor dispersion, and no bias. We hypothesize that from a welfare perspective, ear and tail damage on the original scale are the relevant breeding goal traits. For ear damage on the original scale, the highest response to selection can be expected when selecting on the trait itself, whereas for tail damage on the original scale, selection on summed damage showed the highest gain. Results from this study show that genetic improvement of the direct genetic effect of ear and tail damage is possible.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"38 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144622209","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 : 2025-07-11DOI: 10.1186/s12711-025-00985-z
Berihu Welderufael, Isidore Houaga, R. Chris Gaynor, Gregor Gorjanc, John M. Hickey
Accurate assignment of breed origin of alleles (BOA) at a heterozygote locus may help to introduce a resilient or adaptive haplotype in crossbreeding. In this study, we developed and tested a method to assign breed of origin for individual alleles in crossbred dairy cattle. After generations of mating within and between local breeds as well as the importation of exotic bulls, five rounds of selected crossbred cows were simulated to mimic a dairy breeding program in the low- and middle-income countries (LMICs). In each round of selection, the alleles of those crossbred animals were phased and assigned to their breed of origin (being either local or exotic). Across all core lengths and modes of phasing (with offset—move 50% of the core length forward or no-offset), the average percentage of alleles correctly assigned a breed origin was 95.76%, with only 1.39% incorrectly assigned and 2.85% missing or unassigned. On consensus, the average percentage of alleles correctly assigned a breed origin was 93.21%, with only 0.46% incorrectly assigned and 6.33% missing or unassigned. This high proportion of alleles correctly assigned a breed origin resulted in a high core-based mean accuracy of 0.99 and a very high consensus-based (most frequently observed assignment across all the scenarios) mean accuracy of 1.00. The algorithm’s assignment yield and accuracy were affected by the choice of threshold levels for the best match of assignments. The threshold level had the opposite effect on assignment yield and assignment accuracy. A less stringent threshold generated higher assignment yields and lower assignment accuracy. We developed an algorithm that accurately assigns a breed origin to alleles of crossbred animals designed to represent breeding programs in the LMICs. The developed algorithm is straightforward in its application and does not require prior knowledge of pedigree, which makes it more relevant and applicable in LMICs breeding programs.
{"title":"Accurate determination of breed origin of alleles in a simulated smallholder crossbred dairy cattle population","authors":"Berihu Welderufael, Isidore Houaga, R. Chris Gaynor, Gregor Gorjanc, John M. Hickey","doi":"10.1186/s12711-025-00985-z","DOIUrl":"https://doi.org/10.1186/s12711-025-00985-z","url":null,"abstract":"Accurate assignment of breed origin of alleles (BOA) at a heterozygote locus may help to introduce a resilient or adaptive haplotype in crossbreeding. In this study, we developed and tested a method to assign breed of origin for individual alleles in crossbred dairy cattle. After generations of mating within and between local breeds as well as the importation of exotic bulls, five rounds of selected crossbred cows were simulated to mimic a dairy breeding program in the low- and middle-income countries (LMICs). In each round of selection, the alleles of those crossbred animals were phased and assigned to their breed of origin (being either local or exotic). Across all core lengths and modes of phasing (with offset—move 50% of the core length forward or no-offset), the average percentage of alleles correctly assigned a breed origin was 95.76%, with only 1.39% incorrectly assigned and 2.85% missing or unassigned. On consensus, the average percentage of alleles correctly assigned a breed origin was 93.21%, with only 0.46% incorrectly assigned and 6.33% missing or unassigned. This high proportion of alleles correctly assigned a breed origin resulted in a high core-based mean accuracy of 0.99 and a very high consensus-based (most frequently observed assignment across all the scenarios) mean accuracy of 1.00. The algorithm’s assignment yield and accuracy were affected by the choice of threshold levels for the best match of assignments. The threshold level had the opposite effect on assignment yield and assignment accuracy. A less stringent threshold generated higher assignment yields and lower assignment accuracy. We developed an algorithm that accurately assigns a breed origin to alleles of crossbred animals designed to represent breeding programs in the LMICs. The developed algorithm is straightforward in its application and does not require prior knowledge of pedigree, which makes it more relevant and applicable in LMICs breeding programs.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"275 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144603163","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}
Meat quality plays an important economic role in the meat industry and livestock breeding programmes. Intramuscular fat content (IMF) is one of the main meat quality parameters and its genetic improvement has led breeders to investigate its genomic architecture and correlation with other relevant traits. Genetic markers associated with causal variants for these traits can be identified by bivariate analyses. In this study, we used two rabbit lines divergently selected for IMF to perform bivariate GWAS with the aim of detecting pleiotropic genomic regions between IMF and several weight, fat, and meat quality traits. Additionally, whole-genome sequencing data from these lines were used to identify potential causal variants associated with the genetic markers. The main pleiotropic region was found on Oryctolagus cuniculus chromosome (OCC) 1 between 35.4 Mb and 38.2 Mb, explaining up to 2.66% of the IMF genetic variance and being associated with all traits analysed, except muscle lightness. In this region, the potentially causal variants found pointed to PLIN2, SH3GL2, CNTLN, and BNC2 as the main candidate genes affecting the different weight, fat depots and meat quality traits. Other relevant pleiotropic regions found were those on OCC3 (148.94–150.89 Mb) and on OCC7 (27.07–28.44 Mb). The first was associated with all fat depot traits and explained the highest percentage of genetic variance, up to 10.90% for scapular fat. Several allelic variants were found in this region, all located in the novel gene ENSOCUG00000000157 (orthologous to ST3GAL1 in other species), involved in lipid metabolism, suggesting it as the main candidate affecting fat deposition. The region on OCC7 was associated with most meat quality traits and explained 8.48% of the genetic variance for pH. No allele variants were found to segregate differently between the lines in this region; however, it remains a promising region for future functional studies. Our results showed that bivariate models assuming pleiotropic effects are valuable tools to identify genomic regions simultaneously associated with IMF and several weight, fat and meat quality traits. Overall, our results provided relevant insights into the correlations and relationships between traits at the genomic level, together with potential functional mutations, which would be relevant for exploration in rabbit and other livestock breeding programmes.
{"title":"Bivariate GWAS performed on rabbits divergently selected for intramuscular fat content reveals pleiotropic genomic regions and genes related to meat and carcass quality traits","authors":"Bolívar Samuel Sosa-Madrid, Agostina Zubiri-Gaitán, Noelia Ibañez-Escriche, Agustín Blasco, Pilar Hernández","doi":"10.1186/s12711-025-00971-5","DOIUrl":"https://doi.org/10.1186/s12711-025-00971-5","url":null,"abstract":"Meat quality plays an important economic role in the meat industry and livestock breeding programmes. Intramuscular fat content (IMF) is one of the main meat quality parameters and its genetic improvement has led breeders to investigate its genomic architecture and correlation with other relevant traits. Genetic markers associated with causal variants for these traits can be identified by bivariate analyses. In this study, we used two rabbit lines divergently selected for IMF to perform bivariate GWAS with the aim of detecting pleiotropic genomic regions between IMF and several weight, fat, and meat quality traits. Additionally, whole-genome sequencing data from these lines were used to identify potential causal variants associated with the genetic markers. The main pleiotropic region was found on Oryctolagus cuniculus chromosome (OCC) 1 between 35.4 Mb and 38.2 Mb, explaining up to 2.66% of the IMF genetic variance and being associated with all traits analysed, except muscle lightness. In this region, the potentially causal variants found pointed to PLIN2, SH3GL2, CNTLN, and BNC2 as the main candidate genes affecting the different weight, fat depots and meat quality traits. Other relevant pleiotropic regions found were those on OCC3 (148.94–150.89 Mb) and on OCC7 (27.07–28.44 Mb). The first was associated with all fat depot traits and explained the highest percentage of genetic variance, up to 10.90% for scapular fat. Several allelic variants were found in this region, all located in the novel gene ENSOCUG00000000157 (orthologous to ST3GAL1 in other species), involved in lipid metabolism, suggesting it as the main candidate affecting fat deposition. The region on OCC7 was associated with most meat quality traits and explained 8.48% of the genetic variance for pH. No allele variants were found to segregate differently between the lines in this region; however, it remains a promising region for future functional studies. Our results showed that bivariate models assuming pleiotropic effects are valuable tools to identify genomic regions simultaneously associated with IMF and several weight, fat and meat quality traits. Overall, our results provided relevant insights into the correlations and relationships between traits at the genomic level, together with potential functional mutations, which would be relevant for exploration in rabbit and other livestock breeding programmes.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"107 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144611388","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 : 2025-07-01DOI: 10.1186/s12711-025-00981-3
Hegang Li, Mengmeng Du, Xiaokun Lin, Xinxin Cao, Lu Leng, F. M. Perez Campo, Dongliang Xu, Lele Hou, Xiaoxiao Gao, Jianyu Zhou, Ming Cheng, Jianguang Wang, Qinan Zhao, Yin Chen, Feng Yang, Jinshan Zhao
Horn development is a key ruminant trait involving multi-cell type coordination via molecular pathways. This study used scRNA-seq to analyze cellular heterogeneity and fate trajectories during early horn bud niche formation, revealing key gene expression profiles. Combining with hematoxylin–eosin (HE) staining and immunohistochemical analysis, we further verified the asynchronous developmental pathways of key cells in the skin tissue of fetal goat horn bud at induction (embryonic day (E) 50; E50), organogenesis (E60), and cytodifferentiation (E70) stages, and demonstrated the signal transmission routes for the development of early horn buds. We revealed temporal and spatial differences of the main signal transmission of horn bud development combining with existing literatures. We speculated that multiple cell types under the guidance of nerve cells collaborated on horn bud initiation in dairy goats. In detail, neural cells receive initial horn bud signals, stimulating hair follicle cell degeneration and transmitting to dermal cells, which evolve through intermediates, amplify signals to epithelial cells, and differentiate into mesenchymal cells. Nerve cell branches also trigger neural crest cell production/migration, working with chondrocytes to promote keratinocyte differentiation for horn bud formation. In addition, we further identified the early horn bud developmental specific events, including the screening of biological functions, signaling pathways and key candidate genes. This study employed scRNA-seq to characterize cell fate trajectories and gene expression profiles in goat fetal horn buds. Histological comparisons between hornless and horned fetuses revealed cellular heterogeneity in epithelial, dermal, nerve, and hair follicle cells, with pseudo-time analysis identifying distinct differentiation paths. Dermal and epithelial cell transcriptional dynamics were critical for horn bud initiation (branch 1), supported by immunohistochemistry. Keratinocyte and nerve cell state transitions actively regulated horn development, with asynchronous cell development visualized via immunohistochemistry. Functional enrichment analyses (GO/KEGG) highlighted neural crest development and keratinocyte differentiation pathways, identifying candidate genes (EGR1, ZEB2, SFRP2, KRT10, FMOD, CENPW, LDB1, TWIST1) involved in horn morphogenesis. These findings advance understanding of goat horn development and genetic determinants.
{"title":"Multiple cell types guided by neurocytes orchestrate horn bud initiation in dairy goats","authors":"Hegang Li, Mengmeng Du, Xiaokun Lin, Xinxin Cao, Lu Leng, F. M. Perez Campo, Dongliang Xu, Lele Hou, Xiaoxiao Gao, Jianyu Zhou, Ming Cheng, Jianguang Wang, Qinan Zhao, Yin Chen, Feng Yang, Jinshan Zhao","doi":"10.1186/s12711-025-00981-3","DOIUrl":"https://doi.org/10.1186/s12711-025-00981-3","url":null,"abstract":"Horn development is a key ruminant trait involving multi-cell type coordination via molecular pathways. This study used scRNA-seq to analyze cellular heterogeneity and fate trajectories during early horn bud niche formation, revealing key gene expression profiles. Combining with hematoxylin–eosin (HE) staining and immunohistochemical analysis, we further verified the asynchronous developmental pathways of key cells in the skin tissue of fetal goat horn bud at induction (embryonic day (E) 50; E50), organogenesis (E60), and cytodifferentiation (E70) stages, and demonstrated the signal transmission routes for the development of early horn buds. We revealed temporal and spatial differences of the main signal transmission of horn bud development combining with existing literatures. We speculated that multiple cell types under the guidance of nerve cells collaborated on horn bud initiation in dairy goats. In detail, neural cells receive initial horn bud signals, stimulating hair follicle cell degeneration and transmitting to dermal cells, which evolve through intermediates, amplify signals to epithelial cells, and differentiate into mesenchymal cells. Nerve cell branches also trigger neural crest cell production/migration, working with chondrocytes to promote keratinocyte differentiation for horn bud formation. In addition, we further identified the early horn bud developmental specific events, including the screening of biological functions, signaling pathways and key candidate genes. This study employed scRNA-seq to characterize cell fate trajectories and gene expression profiles in goat fetal horn buds. Histological comparisons between hornless and horned fetuses revealed cellular heterogeneity in epithelial, dermal, nerve, and hair follicle cells, with pseudo-time analysis identifying distinct differentiation paths. Dermal and epithelial cell transcriptional dynamics were critical for horn bud initiation (branch 1), supported by immunohistochemistry. Keratinocyte and nerve cell state transitions actively regulated horn development, with asynchronous cell development visualized via immunohistochemistry. Functional enrichment analyses (GO/KEGG) highlighted neural crest development and keratinocyte differentiation pathways, identifying candidate genes (EGR1, ZEB2, SFRP2, KRT10, FMOD, CENPW, LDB1, TWIST1) involved in horn morphogenesis. These findings advance understanding of goat horn development and genetic determinants.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"36 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520821","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 : 2025-06-23DOI: 10.1186/s12711-025-00984-0
Joe-Menwer Tabet, Ignacio Aguilar, Matias Bermann, Daniela Lourenco, Ignacy Misztal, Paul M. VanRaden, Zulma G. Vitezica, Andres Legarra
Differential treatment of daughters of the same sire within a herd is modelled as the herd-sire effect. Recent changes in management practices may have led to the extensive use of certain bulls in a limited number of herds. In that case, although the effect can be well accounted for in genetic evaluation models, some approximation methods for reliabilities do not consider it correctly, leading to an overestimation of some sires’ approximated reliabilities. This study assessed the potential bias of these approximated reliabilities due to the herd-sire effect in both simulated and real dairy cattle records. Two existing methods were tested: Misztal–Wiggans, which includes a specific modification for herd-sire, and Tier–Meyer, which does not. We also modified and tested a Tier–Meyer method considering the herd-sire effect. We observed that in the presence of the herd-sire effect, reliabilities obtained by approximations were overestimated by the Tier–Meyer method for sires with many daughters in a limited number of herds. This was true even for sires with a large number of daughters. The Misztal–Wiggans method performed correctly. We introduced a modified Tier–Meyer method that weighs the information transmitted by the daughter to the sire as a function of the herd-sire information. As a result, the modified Tier–Meyer method performed well in both simulated and real data. For cows, the inclusion of the herd-sire effect had minimal impact. This study identified possible overestimation of approximated reliabilities of sires with daughters concentrated in a few herds when there is a herd-sire effect. This bias occurs when the herd-sire effect is not correctly modeled in reliability approximation methods. Methods that specifically accounted for the herd-sire effect produced unbiased reliability estimates.
{"title":"Correcting overestimation of approximate traditional reliabilities with herd-sire interactions when young genomic bulls are used in few herds","authors":"Joe-Menwer Tabet, Ignacio Aguilar, Matias Bermann, Daniela Lourenco, Ignacy Misztal, Paul M. VanRaden, Zulma G. Vitezica, Andres Legarra","doi":"10.1186/s12711-025-00984-0","DOIUrl":"https://doi.org/10.1186/s12711-025-00984-0","url":null,"abstract":"Differential treatment of daughters of the same sire within a herd is modelled as the herd-sire effect. Recent changes in management practices may have led to the extensive use of certain bulls in a limited number of herds. In that case, although the effect can be well accounted for in genetic evaluation models, some approximation methods for reliabilities do not consider it correctly, leading to an overestimation of some sires’ approximated reliabilities. This study assessed the potential bias of these approximated reliabilities due to the herd-sire effect in both simulated and real dairy cattle records. Two existing methods were tested: Misztal–Wiggans, which includes a specific modification for herd-sire, and Tier–Meyer, which does not. We also modified and tested a Tier–Meyer method considering the herd-sire effect. We observed that in the presence of the herd-sire effect, reliabilities obtained by approximations were overestimated by the Tier–Meyer method for sires with many daughters in a limited number of herds. This was true even for sires with a large number of daughters. The Misztal–Wiggans method performed correctly. We introduced a modified Tier–Meyer method that weighs the information transmitted by the daughter to the sire as a function of the herd-sire information. As a result, the modified Tier–Meyer method performed well in both simulated and real data. For cows, the inclusion of the herd-sire effect had minimal impact. This study identified possible overestimation of approximated reliabilities of sires with daughters concentrated in a few herds when there is a herd-sire effect. This bias occurs when the herd-sire effect is not correctly modeled in reliability approximation methods. Methods that specifically accounted for the herd-sire effect produced unbiased reliability estimates.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"25 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144341292","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 : 2025-06-17DOI: 10.1186/s12711-025-00977-z
Solène Fresco, Marie-Pierre Sanchez, Didier Boichard, Sébastien Fritz, Pauline Martin
Due to their contribution to global warming, methane emissions from ruminants have been the subject of considerable scientific interest. It has been proposed that such emissions might be reduced using genetic selection; proposed phenotypes differ in the measurement methods used (direct or predicted methane emissions) and in the unit under consideration (g/d, g/kg of milk, g/kg of intake, residual methane emissions). Identifying the quantitative trait loci (QTLs) and candidate genes responsible for genetic variation in methane emissions allows a better understanding of the underlying genetic architecture of these phenotypes. Therefore, the aim of this study was to identify the genomic regions associated with six methane traits predicted from milk mid-infrared (MIR) spectra (0.33 ≤ R2 ≤ 0.88) in French Holstein dairy cows using genome-wide association studies at the whole-genome-sequence level. Six methane emission traits—in g/d, in g/kg of fat- and protein-corrected milk, and in g/kg of dry matter intake—were predicted from milk MIR spectra routinely collected by French milk recording companies. A genome-wide association study of the predicted methane emissions of 40,609 primiparous Holstein cows was conducted using imputed whole-genome-sequence data. This analysis revealed 57 genomic regions of interest; between 1 and 8 QTLs were identified on each of the autosomes except 4, 12, 21, 24 and 26. We identified multiple genomic regions that were shared by two or more predicted methane traits, illustrating their common genetic basis. Functional annotation revealed potential candidate genes, in particular FASN, DGAT1, ACSS2, and KCNIP4, which could be involved in biological pathways possibly related to methane production. The methane traits studied here, which were predicted from milk MIR spectra, appear to be highly polygenic. Several genomic regions associated with these traits contain candidate genes previously associated with milk traits. Functional annotation and comparisons with studies using direct methane measurements support some potential candidate genes involved in biological pathways related to methane production. However, the overlap with genes influencing milk traits highlights the challenge of distinguishing whether these regions genuinely influence methane emissions or reflect the use of milk MIR spectra to predict the phenotypes.
{"title":"Sequence-based GWAS reveals genes and variants associated with predicted methane emissions in French dairy cows","authors":"Solène Fresco, Marie-Pierre Sanchez, Didier Boichard, Sébastien Fritz, Pauline Martin","doi":"10.1186/s12711-025-00977-z","DOIUrl":"https://doi.org/10.1186/s12711-025-00977-z","url":null,"abstract":"Due to their contribution to global warming, methane emissions from ruminants have been the subject of considerable scientific interest. It has been proposed that such emissions might be reduced using genetic selection; proposed phenotypes differ in the measurement methods used (direct or predicted methane emissions) and in the unit under consideration (g/d, g/kg of milk, g/kg of intake, residual methane emissions). Identifying the quantitative trait loci (QTLs) and candidate genes responsible for genetic variation in methane emissions allows a better understanding of the underlying genetic architecture of these phenotypes. Therefore, the aim of this study was to identify the genomic regions associated with six methane traits predicted from milk mid-infrared (MIR) spectra (0.33 ≤ R2 ≤ 0.88) in French Holstein dairy cows using genome-wide association studies at the whole-genome-sequence level. Six methane emission traits—in g/d, in g/kg of fat- and protein-corrected milk, and in g/kg of dry matter intake—were predicted from milk MIR spectra routinely collected by French milk recording companies. A genome-wide association study of the predicted methane emissions of 40,609 primiparous Holstein cows was conducted using imputed whole-genome-sequence data. This analysis revealed 57 genomic regions of interest; between 1 and 8 QTLs were identified on each of the autosomes except 4, 12, 21, 24 and 26. We identified multiple genomic regions that were shared by two or more predicted methane traits, illustrating their common genetic basis. Functional annotation revealed potential candidate genes, in particular FASN, DGAT1, ACSS2, and KCNIP4, which could be involved in biological pathways possibly related to methane production. The methane traits studied here, which were predicted from milk MIR spectra, appear to be highly polygenic. Several genomic regions associated with these traits contain candidate genes previously associated with milk traits. Functional annotation and comparisons with studies using direct methane measurements support some potential candidate genes involved in biological pathways related to methane production. However, the overlap with genes influencing milk traits highlights the challenge of distinguishing whether these regions genuinely influence methane emissions or reflect the use of milk MIR spectra to predict the phenotypes.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"22 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144304448","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 : 2025-06-13DOI: 10.1186/s12711-025-00978-y
Dong-Feng Wang, Pablo Orozco-terWengel, Hosein Salehian-Dehkordi, Ali Esmailizadeh, Feng-Hua Lv
Asiatic mouflon (Ovis gmelini) consists of several subspecies mainly distributed in Armenia, southern Azerbaijan, Cyprus, northern, southern, and western regions of Iran, and eastern and central regions of Turkey nowadays. Genome analyses of Asiatic mouflon in Iran revealed that they could have diverged from the direct ancestor of domestic sheep, and showed genetic introgression into domestic sheep after domestication. However, the impact of the Asiatic mouflon subspecies in Iran on sheep domestication remains unclear. Here, we conducted a comprehensive population genomics analysis of Asiatic mouflon in Iran with 788 whole-genome sequences (including 40 from Asiatic mouflon), 1104 whole mitogenomes (105 from Asiatic mouflon), and 239 Y chromosomes (21 from Asiatic mouflon). Whole-genome sequence analyses revealed two subpopulations of Asiatic mouflon in Iran: O. gmelini_2 limited on Kaboodan Island in Urmia Lake National Park and O. gmelini_1 over a wide geographic area. Phylogenetic analyses of Asiatic mouflon in Iran based on uniparental variants revealed a monophyletic lineage with the mitochondrial haplogroups C/E, and clustered into a monophyletic with Y-chromosomal lineage HY2 of sheep. Additionally, introgression tests detected significant signals of genetic introgression from O. gmelini_2 to four sheep populations (e.g., Garut, Bangladeshi, Nellore, and Sumatra) in South and Southeast Asia. In the four sheep populations, selective tests and introgression signals revealed that the wild introgression could have contributed to their body size, fat metabolism and local adaptation to the hot and humid environments in the Indian Peninsula. Our results clarified subpopulation structure of Asiatic mouflon in Iran, identifying two distinct groups: O. gmelini_1 and O. gmelini_2. Additionally, we suggest a potential genetic contribution to domestic sheep by introgression, with maternal haplogroup C and paternal lineage HY2 likely originating from the Asiatic mouflon populations in Iran. Our findings offer new insights into domestication of sheep and subsequent introgressions events from wild relatives to domestic populations.
{"title":"Genomic analyses of Asiatic Mouflon in Iran provide insights into the domestication and evolution of sheep","authors":"Dong-Feng Wang, Pablo Orozco-terWengel, Hosein Salehian-Dehkordi, Ali Esmailizadeh, Feng-Hua Lv","doi":"10.1186/s12711-025-00978-y","DOIUrl":"https://doi.org/10.1186/s12711-025-00978-y","url":null,"abstract":"Asiatic mouflon (Ovis gmelini) consists of several subspecies mainly distributed in Armenia, southern Azerbaijan, Cyprus, northern, southern, and western regions of Iran, and eastern and central regions of Turkey nowadays. Genome analyses of Asiatic mouflon in Iran revealed that they could have diverged from the direct ancestor of domestic sheep, and showed genetic introgression into domestic sheep after domestication. However, the impact of the Asiatic mouflon subspecies in Iran on sheep domestication remains unclear. Here, we conducted a comprehensive population genomics analysis of Asiatic mouflon in Iran with 788 whole-genome sequences (including 40 from Asiatic mouflon), 1104 whole mitogenomes (105 from Asiatic mouflon), and 239 Y chromosomes (21 from Asiatic mouflon). Whole-genome sequence analyses revealed two subpopulations of Asiatic mouflon in Iran: O. gmelini_2 limited on Kaboodan Island in Urmia Lake National Park and O. gmelini_1 over a wide geographic area. Phylogenetic analyses of Asiatic mouflon in Iran based on uniparental variants revealed a monophyletic lineage with the mitochondrial haplogroups C/E, and clustered into a monophyletic with Y-chromosomal lineage HY2 of sheep. Additionally, introgression tests detected significant signals of genetic introgression from O. gmelini_2 to four sheep populations (e.g., Garut, Bangladeshi, Nellore, and Sumatra) in South and Southeast Asia. In the four sheep populations, selective tests and introgression signals revealed that the wild introgression could have contributed to their body size, fat metabolism and local adaptation to the hot and humid environments in the Indian Peninsula. Our results clarified subpopulation structure of Asiatic mouflon in Iran, identifying two distinct groups: O. gmelini_1 and O. gmelini_2. Additionally, we suggest a potential genetic contribution to domestic sheep by introgression, with maternal haplogroup C and paternal lineage HY2 likely originating from the Asiatic mouflon populations in Iran. Our findings offer new insights into domestication of sheep and subsequent introgressions events from wild relatives to domestic populations.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"22 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144278508","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}
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