Genetics Selection Evolution最新文献

{"title":"Across-country genetic and genomic analyses of foot score traits in American and Australian Angus cattle.","authors":"Amanda B Alvarenga,&nbsp;Kelli J Retallick,&nbsp;Andre Garcia,&nbsp;Stephen P Miller,&nbsp;Andrew Byrne,&nbsp;Hinayah R Oliveira,&nbsp;Luiz F Brito","doi":"10.1186/s12711-023-00850-x","DOIUrl":"10.1186/s12711-023-00850-x","url":null,"abstract":"<p><strong>Background: </strong>Hoof structure and health are essential for the welfare and productivity of beef cattle. Therefore, we assessed the genetic and genomic background of foot score traits in American (US) and Australian (AU) Angus cattle and investigated the feasibility of performing genomic evaluations combining data for foot score traits recorded in US and AU Angus cattle. The traits evaluated were foot angle (FA) and claw set (CS). In total, 109,294 and ~ 1.12 million animals had phenotypic and genomic information, respectively. Four sets of analyses were performed: (1) genomic connectedness between US and AU Angus cattle populations and population structure, (2) estimation of genetic parameters, (3) single-step genomic prediction of breeding values, and (4) single-step genome-wide association studies for FA and CS.</p><p><strong>Results: </strong>There was no clear genetic differentiation between US and AU Angus populations. Similar heritability estimates (FA: 0.22-0.24 and CS: 0.22-0.27) and moderate-to-high genetic correlations between US and AU foot scores (FA: 0.61 and CS: 0.76) were obtained. A joint-genomic prediction using data from both populations outperformed within-country genomic evaluations. A genomic prediction model considering US and AU datasets as a single population performed similarly to the scenario accounting for genotype-by-environment interactions (i.e., multiple-trait model considering US and AU records as different traits), even though the genetic correlations between countries were lower than 0.80. Common significant genomic regions were observed between US and AU for FA and CS. Significant single nucleotide polymorphisms were identified on the Bos taurus (BTA) chromosomes BTA1, BTA5, BTA11, BTA13, BTA19, BTA20, and BTA23. The candidate genes identified were primarily from growth factor gene families, including FGF12 and GDF5, which were previously associated with bone structure and repair.</p><p><strong>Conclusions: </strong>This study presents comprehensive population structure and genetic and genomic analyses of foot scores in US and AU Angus cattle populations, which are essential for optimizing the implementation of genomic selection for improved foot scores in Angus cattle breeding programs. We have also identified candidate genes associated with foot scores in the largest Angus cattle populations in the world and made recommendations for genomic evaluations for improved foot score traits in the US and AU.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10621155/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71429288","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":"Approaching autozygosity in a small pedigree of Gochu Asturcelta pigs.","authors":"Katherine D Arias, Juan Pablo Gutiérrez, Iván Fernández, Isabel Álvarez, Félix Goyache","doi":"10.1186/s12711-023-00846-7","DOIUrl":"10.1186/s12711-023-00846-7","url":null,"abstract":"<p><strong>Background: </strong>In spite of the availability of single nucleotide polymorphism (SNP) array data, differentiation between observed homozygosity and that caused by mating between relatives (autozygosity) introduces major difficulties. Homozygosity estimators show large variation due to different causes, namely, Mendelian sampling, population structure, and differences among chromosomes. Therefore, the ascertainment of how inbreeding is reflected in the genome is still an issue. The aim of this research was to study the usefulness of genomic information for the assessment of genetic diversity in the highly endangered Gochu Asturcelta pig breed. Pedigree depth varied from 0 (founders) to 4 equivalent discrete generations (t). Four homozygosity parameters (runs of homozygosity, F_ROH; heterozygosity-rich regions, F_HRR; Li and Horvitz's, F_LH; and Yang and colleague's F_YAN) were computed for each individual, adjusted for the variability in the base population (BP; six individuals) and further jackknifed over autosomes. Individual increases in homozygosity (depending on t) and increases in pairwise homozygosity (i.e., increase in the parents' mean) were computed for each individual in the pedigree, and effective population size (N_e) was computed for five subpopulations (cohorts). Genealogical parameters (individual inbreeding, individual increase in inbreeding, and N_e) were used for comparisons.</p><p><strong>Results: </strong>The mean F was 0.120 ± 0.074 and the mean BP-adjusted homozygosity ranged from 0.099 ± 0.081 (F_LH) to 0.152 ± 0.075 (F_YAN). After jackknifing, the mean values were slightly lower. The increase in pairwise homozygosity tended to be twofold higher than the corresponding individual increase in homozygosity values. When compared with genealogical estimates, estimates of N_e obtained using F_YAN tended to have low root-mean-squared errors. However, N_e estimates based on increases in pairwise homozygosity using both F_ROH and F_HRR estimates of genomic inbreeding had lower root-mean-squared errors.</p><p><strong>Conclusions: </strong>Parameters characterizing homozygosity may not accurately depict losses of variability in small populations in which breeding policy prohibits matings between close relatives. After BP adjustment, the performance of F_ROH and F_HRR was highly consistent. Assuming that an increase in homozygosity depends only on pedigree depth can lead to underestimating it in populations with shallow pedigrees. An increase in pairwise homozygosity computed from either F_ROH or F_HRR is a promising approach for characterizing autozygosity.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10601182/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50163843","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":"Combined single-step evaluation of functional longevity of dairy cows including correlated traits.","authors":"Laure-Hélène Maugan, Roberta Rostellato, Thierry Tribout, Sophie Mattalia, Vincent Ducrocq","doi":"10.1186/s12711-023-00839-6","DOIUrl":"10.1186/s12711-023-00839-6","url":null,"abstract":"<p><strong>Background: </strong>For years, multiple trait genetic evaluations have been used to increase the accuracy of estimated breeding values (EBV) using information from correlated traits. In France, accurate approximations of multiple trait evaluations were implemented for traits that are described by different models by combining the results of univariate best linear unbiased prediction (BLUP) evaluations. Functional longevity (FL) is the trait that has most benefited from this approach. Currently, with many single-step (SS) evaluations, only univariate FL evaluations can be run. The aim of this study was to implement a \"combined\" SS (CSS) evaluation that extends the \"combined\" BLUP evaluation to obtain more accurate genomic (G) EBV for FL when information from five correlated traits (somatic cell score, clinical mastitis, conception rate for heifers and cows, and udder depth) is added.</p><p><strong>Results: </strong>GEBV obtained from univariate SS (USS) evaluations and from a CSS evaluation were compared. The correlations between these GEBV showed the benefits of including information from correlated traits. Indeed, a CSS evaluation run without any performances on FL showed that the indirect information from correlated traits to evaluate FL was substantial. USS and CSS evaluations that mimic SS evaluations with data available in 2016 were compared. For each evaluation separately, the GEBV were sorted and then split into 10 consecutive groups (deciles). Survival curves were calculated for each group, based on the observed productive life of these cows as known in 2021. Regardless of their genotyping status, the worst group of heifers based on their GEBV in 2016 was well identified in the CSS evaluation and they had a substantially shorter herd life, while those in the best heifer group had a longer herd life. The gaps between groups were more important for the genotyped than the ungenotyped heifers, which indicates better prediction of future survival.</p><p><strong>Conclusions: </strong>A CSS evaluation is an efficient tool to improve FL. It allows a proper combination of information on functional traits that influence culling. In contrast, because of the strong selection intensity on young bulls for functional traits, the benefit of such a \"combined\" evaluation of functional traits is more modest for these males.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10601146/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50163844","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":"Comparative analyses of dynamic transcriptome profiles highlight key response genes and dominant isoforms for muscle development and growth in chicken.","authors":"Zhang Wang, Weihua Tian, Dandan Wang, Yulong Guo, Zhimin Cheng, Yanyan Zhang, Xinyan Li, Yihao Zhi, Donghua Li, Zhuanjian Li, Ruirui Jiang, Guoxi Li, Yadong Tian, Xiangtao Kang, Hong Li, Ian C Dunn, Xiaojun Liu","doi":"10.1186/s12711-023-00849-4","DOIUrl":"10.1186/s12711-023-00849-4","url":null,"abstract":"<p><strong>Background: </strong>Modern breeding strategies have resulted in significant differences in muscle mass between indigenous chicken and specialized broiler. However, the molecular regulatory mechanisms that underlie these differences remain elusive. The aim of this study was to identify key genes and regulatory mechanisms underlying differences in breast muscle development between indigenous chicken and specialized broiler.</p><p><strong>Results: </strong>Two time-series RNA-sequencing profiles of breast muscles were generated from commercial Arbor Acres (AA) broiler (fast-growing) and Chinese indigenous Lushi blue-shelled-egg (LS) chicken (slow-growing) at embryonic days 10, 14, and 18, and post-hatching day 1 and weeks 1, 3, and 5. Principal component analysis of the transcriptome profiles showed that the top four principal components accounted for more than 80% of the total variance in each breed. The developmental axes between the AA and LS chicken overlapped at the embryonic stages but gradually separated at the adult stages. Integrative investigation of differentially-expressed transcripts contained in the top four principal components identified 44 genes that formed a molecular network associated with differences in breast muscle mass between the two breeds. In addition, alternative splicing analysis revealed that genes with multiple isoforms always had one dominant transcript that exhibited a significantly higher expression level than the others. Among the 44 genes, the TNFRSF6B gene, a mediator of signal transduction pathways and cell proliferation, harbored two alternative splicing isoforms, TNFRSF6B-X1 and TNFRSF6B-X2. TNFRSF6B-X1 was the dominant isoform in both breeds before the age of one week. A switching event of the dominant isoform occurred at one week of age, resulting in TNFRSF6B-X2 being the dominant isoform in AA broiler, whereas TNFRSF6B-X1 remained the dominant isoform in LS chicken. Gain-of-function assays demonstrated that both isoforms promoted the proliferation of chicken primary myoblasts, but only TNFRSF6B-X2 augmented the differentiation and intracellular protein content of chicken primary myoblasts.</p><p><strong>Conclusions: </strong>For the first time, we identified several key genes and dominant isoforms that may be responsible for differences in muscle mass between slow-growing indigenous chicken and fast-growing commercial broiler. These findings provide new insights into the regulatory mechanisms underlying breast muscle development in chicken.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10591418/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49694152","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 prediction based on selective linkage disequilibrium pruning of low-coverage whole-genome sequence variants in a pure Duroc population.","authors":"Di Zhu, Yiqiang Zhao, Ran Zhang, Hanyu Wu, Gengyuan Cai, Zhenfang Wu, Yuzhe Wang, Xiaoxiang Hu","doi":"10.1186/s12711-023-00843-w","DOIUrl":"10.1186/s12711-023-00843-w","url":null,"abstract":"<p><strong>Background: </strong>Although the accumulation of whole-genome sequencing (WGS) data has accelerated the identification of mutations underlying complex traits, its impact on the accuracy of genomic predictions is limited. Reliable genotyping data and pre-selected beneficial loci can be used to improve prediction accuracy. Previously, we reported a low-coverage sequencing genotyping method that yielded 11.3 million highly accurate single-nucleotide polymorphisms (SNPs) in pigs. Here, we introduce a method termed selective linkage disequilibrium pruning (SLDP), which refines the set of SNPs that show a large gain during prediction of complex traits using whole-genome SNP data.</p><p><strong>Results: </strong>We used the SLDP method to identify and select markers among millions of SNPs based on genome-wide association study (GWAS) prior information. We evaluated the performance of SLDP with respect to three real traits and six simulated traits with varying genetic architectures using two representative models (genomic best linear unbiased prediction and BayesR) on samples from 3579 Duroc boars. SLDP was determined by testing 180 combinations of two core parameters (GWAS P-value thresholds and linkage disequilibrium r²). The parameters for each trait were optimized in the training population by five fold cross-validation and then tested in the validation population. Similar to previous GWAS prior-based methods, the performance of SLDP was mainly affected by the genetic architecture of the traits analyzed. Specifically, SLDP performed better for traits controlled by major quantitative trait loci (QTL) or a small number of quantitative trait nucleotides (QTN). Compared with two commercial SNP chips, genotyping-by-sequencing data, and an unselected whole-genome SNP panel, the SLDP strategy led to significant improvements in prediction accuracy, which ranged from 0.84 to 3.22% for real traits controlled by major or moderate QTL and from 1.23 to 11.47% for simulated traits controlled by a small number of QTN.</p><p><strong>Conclusions: </strong>The SLDP marker selection method can be incorporated into mainstream prediction models to yield accuracy improvements for traits with a relatively simple genetic architecture, however, it has no significant advantage for traits not controlled by major QTL. The main factors that affect its performance are the genetic architecture of traits and the reliability of GWAS prior information. Our findings can facilitate the application of WGS-based genomic selection.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583454/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49685287","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":"Multi-breed genomic evaluation for tropical beef cattle when no pedigree information is available.","authors":"Ben J Hayes, James Copley, Elsie Dodd, Elizabeth M Ross, Shannon Speight, Geoffry Fordyce","doi":"10.1186/s12711-023-00847-6","DOIUrl":"10.1186/s12711-023-00847-6","url":null,"abstract":"<p><strong>Background: </strong>It has been challenging to implement genomic selection in multi-breed tropical beef cattle populations. If commercial (often crossbred) animals could be used in the reference population for these genomic evaluations, this could allow for very large reference populations. In tropical beef systems, such animals often have no pedigree information. Here we investigate potential models for such data, using marker heterozygosity (to model heterosis) and breed composition derived from genetic markers, as covariates in the model. Models treated breed effects as either fixed or random, and included genomic best linear unbiased prediction (GBLUP) and BayesR. A tropically-adapted beef cattle dataset of 29,391 purebred, crossbred and composite commercial animals was used to evaluate the models.</p><p><strong>Results: </strong>Treating breed effects as random, in an approach analogous to genetic groups allowed partitioning of the genetic variance into within-breed and across breed-components (even with a large number of breeds), and estimation of within-breed and across-breed genomic estimated breeding values (GEBV). We demonstrate that moderately-accurate (0.30-0.43) GEBV can be calculated using these models. Treating breed effects as random gave more accurate GEBV than treating breed as fixed. A simple GBLUP model where no breed effects were fitted gave the same accuracy (and correlations of GEBV very close to 1) as a model where GEBV for within-breed and the GEBV for (random) across-breed effects were included. When GEBV were predicted for herds with no data in the reference population, BayesR resulted in the highest accuracy, with 3% accuracy improvement averaged across traits, especially when the validation population was less related to the reference population. Estimates of heterosis from our models were in line with previous estimates from beef cattle. A method for estimating the number of effective breed comparisons for each breed combination accumulated across contemporary groups is presented.</p><p><strong>Conclusions: </strong>When no pedigree is available, breed composition and heterosis for inclusion in multi-breed genomic evaluation can be estimated from genotypes. When GEBV were predicted for herds with no data in the reference population, BayesR resulted in the highest accuracy.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10578004/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41241102","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":"Sequence-based GWAS meta-analyses for beef production traits.","authors":"Marie-Pierre Sanchez, Thierry Tribout, Naveen K Kadri, Praveen K Chitneedi, Steffen Maak, Chris Hozé, Mekki Boussaha, Pascal Croiseau, Romain Philippe, Mirjam Spengeler, Christa Kühn, Yining Wang, Changxi Li, Graham Plastow, Hubert Pausch, Didier Boichard","doi":"10.1186/s12711-023-00848-5","DOIUrl":"10.1186/s12711-023-00848-5","url":null,"abstract":"<p><strong>Background: </strong>Combining the results of within-population genome-wide association studies (GWAS) based on whole-genome sequences into a single meta-analysis (MA) is an accurate and powerful method for identifying variants associated with complex traits. As part of the H2020 BovReg project, we performed sequence-level MA for beef production traits. Five partners from France, Switzerland, Germany, and Canada contributed summary statistics from sequence-based GWAS conducted with 54,782 animals from 15 purebred or crossbred populations. We combined the summary statistics for four growth, nine morphology, and 15 carcass traits into 16 MA, using both fixed effects and z-score methods.</p><p><strong>Results: </strong>The fixed-effects method was generally more informative to provide indication on potentially causal variants, although we combined substantially different traits in each MA. In comparison with within-population GWAS, this approach highlighted (i) a larger number of quantitative trait loci (QTL), (ii) QTL more frequently located in genomic regions known for their effects on growth and meat/carcass traits, (iii) a smaller number of genomic variants within the QTL, and (iv) candidate variants that were more frequently located in genes. MA pinpointed variants in genes, including MSTN, LCORL, and PLAG1 that have been previously associated with morphology and carcass traits. We also identified dozens of other variants located in genes associated with growth and carcass traits, or with a function that may be related to meat production (e.g., HS6ST1, HERC2, WDR75, COL3A1, SLIT2, MED28, and ANKAR). Some of these variants overlapped with expression or splicing QTL reported in the cattle Genotype-Tissue Expression atlas (CattleGTEx) and could therefore regulate gene expression.</p><p><strong>Conclusions: </strong>By identifying candidate genes and potential causal variants associated with beef production traits in cattle, MA demonstrates great potential for investigating the biological mechanisms underlying these traits. As a complement to within-population GWAS, this approach can provide deeper insights into the genetic architecture of complex traits in beef cattle.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568825/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41220687","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":"The mRNA-lncRNA landscape of multiple tissues uncovers key regulators and molecular pathways that underlie heterosis for feed intake and efficiency in laying chickens.","authors":"Jingwei Yuan, Jinmeng Zhao, Yanyan Sun, Yuanmei Wang, Yunlei Li, Aixin Ni, Yunhe Zong, Hui Ma, Panlin Wang, Lei Shi, Jilan Chen","doi":"10.1186/s12711-023-00834-x","DOIUrl":"10.1186/s12711-023-00834-x","url":null,"abstract":"<p><strong>Background: </strong>Heterosis is routinely exploited to improve animal performance. However, heterosis and its underlying molecular mechanism for feed intake and efficiency have been rarely explored in chickens. Feed efficiency continues to be an important breeding goal trait since feed accounts for 60 to 70% of the total production costs in poultry. Here, we profiled the mRNA-lncRNA landscape of 96 samples of the hypothalamus, liver and duodenum mucosa from White Leghorn (WL), Beijing-You chicken (YY), and their reciprocal crosses (WY and YW) to elucidate the regulatory mechanisms of heterosis.</p><p><strong>Results: </strong>We observed negative heterosis for both feed intake and residual feed intake (RFI) in YW during the laying period from 43 to 46 weeks of age. Analysis of the global expression pattern showed that non-additivity was a major component of the inheritance of gene expression in the three tissues for YW but not for WY. The YW-specific non-additively expressed genes (YWG) and lncRNA (YWL) dominated the total number of non-additively expressed genes and lncRNA in the hypothalamus and duodenum mucosa. Enrichment analysis of YWG showed that mitochondria components and oxidation phosphorylation (OXPHOS) pathways were shared among the three tissues. The OXPHOS pathway was enriched by target genes for YWL with non-additive inheritance of expression in the liver and duodenum mucosa. Weighted gene co-expression network analysis revealed divergent co-expression modules associated with feed intake and RFI in the three tissues from WL, YW, and YY. Among the negatively related modules, the OXPHOS pathway was enriched by hub genes in the three tissues, which supports the critical role of oxidative phosphorylation. Furthermore, protein quantification of ATP5I was highly consistent with ATP5I expression in the liver, which suggests that, in crossbred YW, non-additive gene expression is down-regulated and decreases ATP production through oxidative phosphorylation, resulting in negative heterosis for feed intake and efficiency.</p><p><strong>Conclusions: </strong>Our results demonstrate that non-additively expressed genes and lncRNA involved in oxidative phosphorylation in the hypothalamus, liver, and duodenum mucosa are key regulators of the negative heterosis for feed intake and RFI in layer chickens. These findings should facilitate the rational choice of suitable parents for producing crossbred chickens.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10559425/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41175352","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":"Interpreting single-step genomic evaluation as a neural network of three layers: pedigree, genotypes, and phenotypes.","authors":"Tianjing Zhao, Hao Cheng","doi":"10.1186/s12711-023-00838-7","DOIUrl":"10.1186/s12711-023-00838-7","url":null,"abstract":"<p><p>The single-step approach has become the most widely-used methodology for genomic evaluations when only a subset of phenotyped individuals in the pedigree are genotyped, where the genotypes for non-genotyped individuals are imputed based on gene contents (i.e., genotypes) of genotyped individuals through their pedigree relationships. We proposed a new method named single-step neural network with mixed models (NNMM) to represent single-step genomic evaluations as a neural network of three sequential layers: pedigree, genotypes, and phenotypes. These three sequential layers of information create a unified network instead of two separate steps, allowing the unobserved gene contents of non-genotyped individuals to be sampled based on pedigree, observed genotypes of genotyped individuals, and phenotypes. In addition to imputation of genotypes using all three sources of information, including phenotypes, genotypes, and pedigree, single-step NNMM provides a more flexible framework to allow nonlinear relationships between genotypes and phenotypes, and for individuals to be genotyped with different single-nucleotide polymorphism (SNP) panels. The single-step NNMM has been implemented in the software package \"JWAS'.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10546757/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41175351","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":"Towards genetic improvement of social behaviours in livestock using large-scale sensor data: data simulation and genetic analysis.","authors":"Zhuoshi Wang, Harmen Doekes, Piter Bijma","doi":"10.1186/s12711-023-00840-z","DOIUrl":"10.1186/s12711-023-00840-z","url":null,"abstract":"<p><strong>Background: </strong>Harmful social behaviours, such as injurious feather pecking in poultry and tail biting in swine, reduce animal welfare and production efficiency. While these behaviours are heritable, selective breeding is still limited due to a lack of individual phenotyping methods for large groups and proper genetic models. In the near future, large-scale longitudinal data on social behaviours will become available, e.g. through computer vision techniques, and appropriate genetic models will be needed to analyse such data. In this paper, we investigated prospects for genetic improvement of social traits recorded in large groups by (1) developing models to simulate and analyse large-scale longitudinal data on social behaviours, and (2) investigating required sample sizes to obtain reasonable accuracies of estimated genetic parameters and breeding values (EBV).</p><p><strong>Results: </strong>Latent traits were defined as representing tendencies of individuals to be engaged in social interactions by distinguishing between performer and recipient effects. Animal movement was assumed random and without genetic variation, and performer and recipient interaction effects were assumed constant over time. Based on the literature, observed-scale heritabilities ([Formula: see text]) of performer and recipient effects were both set to 0.05, 0.1, or 0.2, and the genetic correlation ([Formula: see text]) between those effects was set to - 0.5, 0, or 0.5. Using agent-based modelling, we simulated ~ 200,000 interactions for 2000 animals (~ 1000 interactions per animal) with a half-sib family structure. Variance components and breeding values were estimated with a general linear mixed model. The estimated genetic parameters did not differ significantly from the true values. When all individuals and interactions were included in the analysis, the accuracy of EBV was 0.61, 0.70, and 0.76 for [Formula: see text] = 0.05, 0.1, and 0.2, respectively (for [Formula: see text]= 0). Including 2000 individuals each with only ~ 100 interactions, already yielded promising accuracies of 0.47, 0.60, and 0.71 for [Formula: see text] = 0.05, 0.1, and 0.2, respectively (with [Formula: see text] = 0). Similar results were found with [Formula: see text] of - 0.5 or 0.5.</p><p><strong>Conclusions: </strong>We developed models to simulate and genetically analyse social behaviours for animals that are kept in large groups, anticipating the availability of large-scale longitudinal data in the near future. We obtained promising accuracies of EBV with ~ 100 interactions per individual, which would correspond to a few weeks of recording. Therefore, we conclude that animal breeding can be a promising strategy to improve social behaviours in livestock.</p>","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10537099/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41154040","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}