Genetics Selection Evolution最新文献

{"title":"Phenotypic and genetic analysis of energy partitioning and feed efficiency in Atlantic salmon.","authors":"Anna Kristina Sonesson, Gareth Frank Difford, Ashie Norris, Bjarne Hatlen","doi":"10.1186/s12711-026-01045-w","DOIUrl":"10.1186/s12711-026-01045-w","url":null,"abstract":"<p><strong>Background: </strong>There are both economic and environmental motivations to improve feed efficiency. However, direct genetic improvement of feed efficiency ratio (FER; weight gain/feed intake) is difficult. Alternatively, improved FER might be achieved indirectly by selection for increased growth rate and reduced body fat. The aims of this study were (i) to perform a phenotypic analysis of energy partitioning traits among Atlantic salmon families; (ii) to estimate heritability and genetic relationships among feed efficiency and underlying traits; (iii) to determine an optimal breeding strategy to improve feed efficiency in Atlantic salmon.</p><p><strong>Results: </strong>Moderate genomic heritability estimates were obtained for most traits, e.g. feed intake (0.35), weight gain (0.42), feed efficiency ratio (0.19) and energy density of the gained weight (0.26). Heritability for residual feed intake was 0.04. Genetic correlation between feed efficiency and growth or energy density of the gained weight was 0.68 and -0.64, respectively. A selection index including weight gain and energy density of the gained weight was most beneficial to increase FER. The effect of body energy (reflecting fat deposition) was half of what could be predicted if energy efficiency (EE; energy gain/energy intake) was constant. The fish retained 50 and 49% of the energy and protein intake, respectively. Energy loss was due to heat (29% of intake), faecal loss (18%) and nitrogen excretion (3%). The derived energy and protein budget traits displayed low to moderate genomic heritability (h2 = 0.01-0.31). Protein efficiency reflected FER.</p><p><strong>Conclusions: </strong>Genetic selection for weight gain and against energy density of the gained weight will improve feed efficiency ratio in Atlantic salmon without the need for individual feed intake records. The results suggest that by selection against body energy, and given the same weight gain, 50% of the reduction in body energy can be realised as reduced feed intake and thus improved FER.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"58 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13154555/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147857555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Restructuring breeding programs 1: Integration of diversity.","authors":"Tobias A M Niehoff,Jan Ten Napel,Mario P L Calus","doi":"10.1186/s12711-026-01046-9","DOIUrl":"https://doi.org/10.1186/s12711-026-01046-9","url":null,"abstract":"","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"27 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147755001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breeding for sheep robustness: simulation of the consequences of ewe-lamb energy allocation trade-offs.","authors":"Maya Hiltpold,Ronan Trépos,Frédéric Douhard","doi":"10.1186/s12711-026-01047-8","DOIUrl":"https://doi.org/10.1186/s12711-026-01047-8","url":null,"abstract":"","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"102 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147751346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating GWAS and eQTL analysis to decipher genetic mechanisms of feed efficiency and feeding behaviors in pigs.","authors":"Zhenyang Zhang,Yongqi He,Wei Zhao,Ran Wei,He Han,Quanjun Zhan,Pengfei Yu,Sisi Li,Xiaoliang Hou,Jianlan Wang,Qingbo Zhao,Yan Fu,Zitao Chen,Zhen Wang,Yuchun Pan,Qishan Wang,Zhe Zhang","doi":"10.1186/s12711-026-01048-7","DOIUrl":"https://doi.org/10.1186/s12711-026-01048-7","url":null,"abstract":"","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"21 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147751318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From pixels to breeding values: genetic analysis of detection and movement traits in laying hens using automated tracking data of ArUco-marked birds.","authors":"T Osorio-Gallardo,A van Putten,D Janssen,M F Schrauf,M F Giersberg,T B Rodenburg,P Bijma","doi":"10.1186/s12711-026-01043-y","DOIUrl":"https://doi.org/10.1186/s12711-026-01043-y","url":null,"abstract":"BACKGROUNDAutomated tracking technologies make it possible to perform large-scale genetic analyses of behavioural traits in livestock. However, behavioural phenotypes derived from automated systems can be noisy, incomplete, or difficult to interpret in terms of specific behaviours or welfare outcomes. This study evaluated the feasibility of using ArUco marker-based tracking to derive three behavioural phenotypes expressed in the litter area (detected or not, minutes detected, walking speed) in a population of 1,132 crossbred laying hens kept under semi-commercial conditions.RESULTSDespite the fact that 63% of the time, individuals were not detected due to occlusion or system limitations, the tracking method yielded sufficient data (on average 5,326 detections per individual per hour) to estimate genetic parameters with genomic prediction. All traits exhibited significant additive genetic variance, with heritability estimates ranging from 0.05 to 0.08 for hourly measurements and from 0.13 to 0.26 for daily measurements. Genetic correlations revealed shared architecture between detection traits (detected or not and minutes detected, [Formula: see text]= 0.71), but an unexpected strong negative correlation between walking speed and minutes detected ([Formula: see text]= -0.73) probably because faster individuals sooner disappeared from the camera's field of view. Cross-validation accuracies were modest (0.25-0.32), while model-based accuracies were nearly twice as high. Multi-trait modelling did not improve the accuracy of estimated breeding values.CONCLUSIONSOur results demonstrate that automated tracking can generate useful phenotypes for the genetic evaluation of complex behaviours. The current methodology provides individual-level behavioural data suitable for genetic analyses, though its application at scale still requires substantial effort in data collection and processing. Additionally, further ethological understanding is required to confirm which specific behaviours these traits reflect.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"64 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147648978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comparative study on recombination activity in cattle.","authors":"Dörte Wittenburg,Nina Melzer,Nayyer Abdollahi Sisi,Xi Ding,Franz R Seefried","doi":"10.1186/s12711-026-01041-0","DOIUrl":"https://doi.org/10.1186/s12711-026-01041-0","url":null,"abstract":"BACKGROUNDGenetic diversity among cattle breeds exists due to their demographic history and different breeding objectives for meat, dairy or dual purpose. Taking this into account, targeted breeding strategies can be further enhanced by employing breed-specific genetic maps. The aim of this study was to derive genetic maps (also known as linkage maps) for a selection of commercial breeds.RESULTSWe analysed genotype data from six cattle breeds with sample size ranging from 4,181 to 76,875. Several different assays were used for genotyping, resulting in a high proportion of systematically missing data. Thus, we streamlined the data preparation and analysed the data with three different approaches. We investigated the frequency of paternal and maternal recombination events and derived genetic-map coordinates of about 50K SNP markers. Estimates of male map length varied from 26.97 to 29.83 M between breeds, whereas length of female maps ranged from 23.32 to 26.08 M. Female recombination activity and female genetic maps were clearly distinct from the outcome in males. In particular, male maps of Brown Swiss, Simmental and Angus clustered separately from other male maps and female maps of dairy breeds were distinct from female maps of dual-purpose breeds. Furthermore, a genomewide association study on mean autosomal crossover count and intra-chromosomal allelic shuffling per parent revealed two chromosomal regions on BTA6 and BTA10 with strong evidence found in Brown Swiss and Swiss Holstein; another suggestive signal was detected on BTA10. These regions were in close proximity to genes with known impact on recombination activity.CONCLUSIONBreed-specific female maps could be clearly differentiated from male maps. Though female maps clustered together depending on breed purpose, this was not the case for male maps. All results on empirical data were implemented in the updated version of the R Shiny app CLARITY v3.0.0. This resource can contribute to several instances of genomic evaluations - from improving haplotype phasing to implementing novel breeding strategies.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"3 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147625576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Linkage- and ROH-based genomic relationship matrices for IBD based management of genetic diversity.","authors":"Oda B Wæge,Xijiang Yu,Peer Berg,Theo Meuwissen","doi":"10.1186/s12711-026-01044-x","DOIUrl":"https://doi.org/10.1186/s12711-026-01044-x","url":null,"abstract":"","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"1 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147578346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic analysis of iris pigmentation in Swiss pig breeds identifies a missense KITLG variant as a potential causal factor for pale and heterochromatic irises.","authors":"Wim Gorssen, Naveen Kumar Kadri, Negar Khayatzadeh, Alexander S Leonard, Qiongyu He, Arnav Mehrotra, Stefan Neuenschwander, Hubert Pausch","doi":"10.1186/s12711-026-01040-1","DOIUrl":"10.1186/s12711-026-01040-1","url":null,"abstract":"<p><strong>Background: </strong>Iris pigmentation is a heritable trait with a complex genetic architecture. While the genetic basis of iris pigmentation has been extensively studied in humans, little is known about iris pigmentation in pigs. Iris pigmentation in pigs varies from different shades of brown or pale irises to heterochromia manifesting either as different colors between both irises (heterochromia iridum) or multiple colors within a single iris (heterochromia iridis). This study investigates the genetics of iris pigmentation variability in the Swiss Landrace and Swiss Large White pig breeds.</p><p><strong>Results: </strong>Iris pigmentation was phenotyped in 837 Swiss Landrace and 328 Swiss Large White pigs of which the majority also had array-derived genotypes. A high prevalence of heterochromia iridum (18.6%) was observed in the Swiss Landrace breed. Heritability estimates for iris pigmentation were high in both breeds (h² = 57.6-64.4%). Iris pigmentation was not genetically correlated with production traits. Genome-wide association analysis identified several loci associated with iris pigmentation (P < 10^-5), including regions near functional candidate genes such as TYR, ALX4 and DCT. The strongest association was detected near the KITLG gene, which was identified as a candidate gene for iris pigmentation in a previous study on Italian Large White pigs. Fine-mapping identified a highly significantly associated (P = 2.0 × 10^-12) missense variant in KITLG (5_94084790_G > A, rs342599807, p.R124K) as a potential causal variant for pale and heterochromatic iris pigmentation in Swiss pigs.</p><p><strong>Conclusions: </strong>Our findings provide new insights into the genetic architecture of iris pigmentation in pigs and indicate that KITLG plays a key role. The identification of a putative causal missense variant offers a foundation for further functional studies aiming to better understand pigmentation traits in pigs.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13023151/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147516825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic estimates of Identity-By-Descent relationships in large scale data sets.","authors":"Theo Meuwisen,Xijiang Yu,Peer Berg","doi":"10.1186/s12711-026-01038-9","DOIUrl":"https://doi.org/10.1186/s12711-026-01038-9","url":null,"abstract":"BACKGROUNDGenomic relationship and inbreeding estimates are either based on genetic drift (e.g. the Genomic Relationship Matrix; GRM), homozygosity (e.g. Runs of Homozygosity; ROH), or Identity-By-Descent (IBD). A genomic IBD-based relationship matrix, Gla, is obtained by linkage analysis which uses genomic data to distinguish paternal versus maternal inheritances of chromosomal segments to replace the 50/50 probabilities used to calculate pedigree-based relationships (A matrix). Our aim was to develop a fast approximate algorithm, FGla, to estimate the Gla matrix in large complex pedigrees making use of dense marker genotypes, and to compare Gla to A, GRM and ROH based inbreeding (FROH) in simulated and a large scale Norwegian Red Cattle (NRF) data set.RESULTSGiven pedigree data and ≥ 3 generations of 45 k marker genotypes, marker positions were detected that unambiguously identified maternal/paternal inheritance, and inheritances at intermediate positions were imputed by the Viterbi algorithm from the positions with known inheritance. Any remaining unknown inheritances were randomly sampled (paternal or maternal), and the sampling errors that this introduced were averaged out by the large number of marker loci used (correlation between replicated estimates: 0.9998). Also, calculations were limited to the relationship coefficients that were actually needed, assuming that relationships for a limited set of candidates were needed. The accuracy of estimated Gla coefficients increased from 0.971 to 0.998, when genotyping increased from the actually genotyped NRF cattle towards all pedigreed animals. The accuracy of the GRM was 0.936, but required only genotyping of the animals whose relationships were needed. Gla relationships were approximately unbiased in the Best Linear Unbiased Prediction (BLUP) sense. Hence, if Gla based inbreeding management predicts an increase in relationships then an identical increase in true IBD relationships is expected. Gla uses the same base population as A, namely that of the pedigree.CONCLUSIONSAn approximate computationally efficient multipoint linkage analysis algorithm was developed to estimate unbiased IBD-based relationship and inbreeding coefficients. Its unbiasedness and precise definition of the base population makes it well suited for the genomic management of inbreeding and genomic optimal contribution selection. In addition, Gla based optimal contribution selection is neutral with respect to allele frequency changes.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"9 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147447015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic analysis of the inbreeding load for body weight, carcass and reproductive traits in the Rubia Gallega beef cattle population.","authors":"Carlos Hervás-Rivero,David López-Carbonell,Manuel Sánchez-Díaz,Luis Varona","doi":"10.1186/s12711-026-01039-8","DOIUrl":"https://doi.org/10.1186/s12711-026-01039-8","url":null,"abstract":"BACKGROUNDInbreeding, resulting from mating between relatives, leads to inbreeding depression, which can be traced back to hidden ancestral inbreeding loads. These loads exhibit variability and act as additive genetic effects that are only expressed in the inbred offspring. The objective of this study was to quantify the variance of the inbreeding loads and its correlation with additive genetic effects for seven traits in the Rubia Gallega population: birth weight, weaning weight, cold carcass weight, carcass conformation, carcass fatness, calving interval, and age at first parity. A single-step GBLUP Bayesian analysis was used by a Gibbs sampler. Additionally, the equivalence between GBLUP and SNP-BLUP was used for locating the genomic regions associated with the highest variances.RESULTSThe pedigree included 522,885 animals, of which 4984 were genotyped with the Axiom_BovMDv3 chip. A total of 246,393 individuals were inbred, with an average inbreeding coefficient of 0.044 ± 0.059, attributed to 4712 ancestors through 9.8 million partial inbreeding contributions. The estimated proportion of phenotypic variance explained by inbreeding loads for an inbreeding coefficient of 0.10 ranged from 0.012 (Birth weight) to 0.101 (Weaning weight), consistently below the heritabilities of the traits. Genetic correlations between inbreeding load and additive effects were always negative. The average prediction accuracy for inbreeding-load effects in young selection candidates was low and exceeded 0.7 only in older animals. The genomic distribution of additive and inbreeding load variances was uneven, with some regions overlapping and others being specific to inbreeding load.CONCLUSIONSThis study demonstrates that the inbreeding load variance is low compared to the additive genetic variance across a range of growth, carcass, and reproductive traits. The results were also consistent with a previous study that theoretically demonstrated a negative correlation between additive effects and inbreeding load. The potential to purge deleterious alleles appears limited, largely due to the low prediction accuracy observed in young individuals. Nevertheless, the higher accuracy of inbreeding-load estimates in ancestral animals could still be exploited to guide the unavoidable inbreeding in small populations through informed mating strategies, thereby minimizing undesirable inbreeding-depression effects. The heterogeneous genomic distribution of the inbreeding load suggests new opportunities for identifying genes in which deleterious or semideleterious alleles may be located.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"56 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147447016","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}