Journal of animal breeding and genetics = Zeitschrift für Tierzüchtung und Züchtungsbiologie最新文献

{"title":"Defining smallholders' breeding objectives for common Tigray highland sheep in Northern Ethiopia.","authors":"Kiflay Welday,&nbsp;Solomon Abegaz,&nbsp;Mengistu Urge,&nbsp;Ayele Abebe,&nbsp;Gebretensae Mezgebe","doi":"10.1111/jbg.12736","DOIUrl":"https://doi.org/10.1111/jbg.12736","url":null,"abstract":"<p><p>A sound breeding objective is a basis for genetic improvement in the overall economic merit of farm animals. This study aimed to define smallholders' sheep breeding objectives using a conjoint-based choice experiment and bio-economic model. Multinomial logistic regression analysis showed differences (p < 0.001) among the derived weights allocated by farmers to body size, twining rate, mothering ability, libido, tail type, colour and lambing interval which formed the high priority traits. The likelihood values of farmer's top three preferred traits for ram were body size (0.659 ± 0.009), tail type (0.325 ± 0.016) and libido (0.247 ± 0.016) while body size (0.459 ± 0.010), twining rate (0.313 ± 0.010) and mothering ability (0.261 ± 0.010) were more preferred traits for selection of breeding ewes. Conjoint-based choice experiment and bio-economic model indicated that live body weight at 6 months of age, twining rate (litter size) and mothering ability (preweaning lamb survival) were the most economically important traits of the breeding ewes. A genetic improvement by one genetic standard deviation (σ_a ) in these traits resulted in a profit of Ethiopian Birr 36.03-60.47/ewe/year. A fair correlation (r = 0.63) was observed between farmers' traits preference (conjoint-based choice card experiment) and the estimated economic value of traits indicating a good relationship between farmers' preferences for traits and economic values of the traits. This would indicate that weighting traits in selection indexes with farmers' trait selection using a conjoint-based choice experiment would direct genetic improvement towards desired profitability. Moreover, the fair correspondence between the two methods suggests that bio-economic modelling, if designed properly considering farmers' concerns, could be used to reflect farmers' breeding objectives. Therefore, for reasonable genetic progress and sheep flock profitability, more attention should be given to litter size, preweaning lamb survival and body weight at 6 months of age as they are preferred by farmers and their economic weights. Further, research on the modalities for complementary use of the two methods to define breeding objectives under smallholder conditions is warranted.</p>","PeriodicalId":252687,"journal":{"name":"Journal of animal breeding and genetics = Zeitschrift für Tierzüchtung und Züchtungsbiologie","volume":" ","pages":"623-633"},"PeriodicalIF":2.6,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40606711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Consequences of incorrect genetic parameter estimates for single-trait and multi-trait genetic evaluations in honeybees.","authors":"Manuel Du,&nbsp;Richard Bernstein,&nbsp;Andreas Hoppe,&nbsp;Kaspar Bienefeld","doi":"10.1111/jbg.12728","DOIUrl":"https://doi.org/10.1111/jbg.12728","url":null,"abstract":"<p><p>Genetic and residual variances of traits are important input parameters for best linear unbiased prediction (BLUP) breeding value estimation. In honeybees, estimates of these variances are often associated with large standard errors, entailing a risk to perform genetic evaluations under wrong premises. The consequences hereof have not been sufficiently studied. In particular, there are no adequate investigations on this topic accounting for multi-trait selection or genetic peculiarities of the honeybee. We performed simulation studies and explored the consequences of selection for honeybee populations with a broad range of true and assumed genetic parameters. We found that in single-trait evaluations, the response to selection was barely compromised by assuming erroneous parameters, so that reductions in genetic progress after 20 years never exceeded 21%. Phenotypic selection appeared inferior to BLUP selection, particularly under low heritabilities. Parameter choices for genetic evaluation had great effects on inbreeding development. By wrongly assuming high heritabilities, inbreeding rates were reduced by up to 74%. When parallel selection was performed for two traits, the right choice of genetic parameters appeared considerably more crucial as several incorrect premises yielded inadvertent negative selection for one of the traits. This phenomenon occurred in multiple constellations in which the selection traits expressed a negative genetic correlation. It was not reflected in the estimated breeding values. Our results indicate that breeding efforts heavily rely on detailed knowledge on genetic parameters, particularly when multi-trait selection is performed. Thus, considerable effort should be invested into precise parameter estimations.</p>","PeriodicalId":252687,"journal":{"name":"Journal of animal breeding and genetics = Zeitschrift für Tierzüchtung und Züchtungsbiologie","volume":" ","pages":"666-678"},"PeriodicalIF":2.6,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40468740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome-wide association for milk urea concentration in Dual-Purpose Belgian Blue cows.","authors":"Hadi Atashi,&nbsp;Yansen Chen,&nbsp;Hélène Wilmot,&nbsp;Sylvie Vanderick,&nbsp;Xavier Hubin,&nbsp;Nicolas Gengler","doi":"10.1111/jbg.12732","DOIUrl":"https://doi.org/10.1111/jbg.12732","url":null,"abstract":"<p><p>The objectives of this study were to estimate genetic parameters and identify genomic regions associated with milk urea concentration (MU) in Dual-Purpose Belgian Blue (DPBB) cows. The data were 29,693 test-day records of milk yield (MY), fat yield (FY), protein yield (PY), fat percentage (FP), protein percentage (PP) and MU collected between 2014 and 2020 on 2498 first parity cows (16,935 test-day records) and 1939 second-parity cows (12,758 test-day records) from 49 herds in the Walloon Region of Belgium. Data of 28,266 single nucleotide polymorphisms (SNP), located on 29 Bos taurus autosomes (BTA), on 1699 animals (639 males and 1060 females) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method using a single chain of 100,000 iterations after a burn-in period of 20,000. SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by windows of 25 consecutive SNPs (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. The mean (SD) of MU was 22.89 (10.07) and 22.35 (10.07) mg/dl for first and second parity, respectively. The mean (SD) heritability estimates for daily MU were 0.18 (0.01) and 0.22 (0.02), for first and second parity, respectively. The mean (SD) genetic correlations between daily MU and MY, FY, PY, FP and PP were -0.05 (0.09), -0.07 (0.11), -0.03 (0.13), -0.05 (0.08) and -0.03 (0.11) for first parity, respectively. The corresponding values estimated for second parity were 0.02 (0.10), -0.02 (0.09), 0.02 (0.08), -0.08 (0.06) and -0.05 (0.05). The genome-wide association analyses identified three genomic regions (BTA2, BTA3 and BTA13) associated with MU. The identified regions showed contrasting results between parities and among different stages within each parity. This suggests that different groups of candidate genes underlie the phenotypic expression of MU between parities and among different lactation stages within a parity. The results of this study can be used for future implementation and use of genomic evaluation to reduce MU in DPBB cows.</p>","PeriodicalId":252687,"journal":{"name":"Journal of animal breeding and genetics = Zeitschrift für Tierzüchtung und Züchtungsbiologie","volume":" ","pages":"710-722"},"PeriodicalIF":2.6,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40505110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome-wide scan for signatures of selection in the Brangus cattle genome.","authors":"Paulo Álvarez Cecco,&nbsp;Andrés Rogberg Muñoz,&nbsp;Marianela Balbi,&nbsp;Martín Bonamy,&nbsp;Sebastián Munilla,&nbsp;Natalia Soledad Forneris,&nbsp;Pilar Peral García,&nbsp;Rodolfo Juan Carlos Cantet,&nbsp;Guillermo Giovambattista,&nbsp;María Elena Fernández","doi":"10.1111/jbg.12733","DOIUrl":"https://doi.org/10.1111/jbg.12733","url":null,"abstract":"<p><p>Brangus is a composite cattle breed developed with the objective of combining the advantages of Angus and Zebuine breeds (Brahman, mainly) in tropical climates. The aim of this work was to estimate breed composition both genome-wide and locally, at the chromosome level, and to uncover genomic regions evidencing positive selection in the Argentinean Brangus population/nucleus. To do so, we analysed marker data from 478 animals, including Brangus, Angus and Brahman. Average breed composition was 35.0% ± 9.6% of Brahman, lower than expected according to the theoretical fractions deduced by the usual cross-breeding practice in this breed. Local ancestry analysis evidenced that breed composition varies between chromosomes, ranging from 19.6% for BTA26 to 56.1% for BTA5. Using approaches based on allelic frequencies and linkage disequilibrium, genomic regions with putative selection signatures were identified in several chromosomes (BTA1, BTA5, BTA6 and BTA14). These regions harbour genes involved in horn development, growth, lipid metabolism, reproduction and immune response. We argue that the overlapping of a chromosome segment originated in one of the parental breeds and over-represented in the sample with the location of a signature of selection constitutes evidence of a selection process that has occurred in the breed since its take off in the 1950s. In this regard, our results could contribute to the understanding of the genetic mechanisms involved in cross-bred cattle adaptation and productivity in tropical environments.</p>","PeriodicalId":252687,"journal":{"name":"Journal of animal breeding and genetics = Zeitschrift für Tierzüchtung und Züchtungsbiologie","volume":" ","pages":"679-694"},"PeriodicalIF":2.6,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40530462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic parameters of immune traits for Landrace and Large White pig breeds.","authors":"Katharina Roth,&nbsp;Maren Julia Pröll-Cornelissen,&nbsp;Esther Maren Heuß,&nbsp;Christina Mechthilde Dauben,&nbsp;Hubert Henne,&nbsp;Anne Kathrin Appel,&nbsp;Karl Schellander,&nbsp;Ernst Tholen,&nbsp;Christine Große-Brinkhaus","doi":"10.1111/jbg.12735","DOIUrl":"https://doi.org/10.1111/jbg.12735","url":null,"abstract":"<p><p>Improving the immunocompetence towards pathogens represents a desirable objective of breeding strategies to increase resilience. However, the immune system is complex and the genetic foundation of the underlying components is not yet clarified. In the present study, we focused on 22 blood parameters of 1,144 Landrace (LR) and Large White (LW) piglets at the age of 6-7 weeks. The immune profiles covered immune cells, red blood cell characteristics and cytokines. Genetic parameters based on pedigree information along with possible environmental effects were estimated. Litter effects play an important role in the expression of immune parameters of their young progenies. Hence, litter impacts on the piglet's immune profile including the immune parameters of the dam itself were investigated by different models. To incorporate the complexity of the immune network, the data were further investigated with a principal component analysis. Immune traits showed low to high breed-specific heritabilities (h² ). Strong positive r_g were estimated among red blood cell characteristics (0.77-0.99) and among cytokines (0.48-0.99). Neutrophils and lymphocytes illustrated a high negative r_g (-0.96 to -0.98). The litter impact on piglet's immunity was examined and strengthened already observed breed differences. In LR, h² (0.22-0.15) and litter effect (c² ) (0.52-0.44) for IFN-γ decreased after statistical consideration of maternal impact. In LW, a decrease in h² (0.32-0.18) for IFN-γ and an increase in c² (0.54-0.56) were observed. Here, sufficient correlations were detected within various immune traits and functional biological networks of principal components. Most immune traits are heritable and are promising to cover global breed-specific immunocompetence in pigs. The analysis of immune traits has to be extended in order to find an optimal range and to characterize relationships between immunity and performance to gain an improved immune system without accidental losses in productivity.</p>","PeriodicalId":252687,"journal":{"name":"Journal of animal breeding and genetics = Zeitschrift für Tierzüchtung und Züchtungsbiologie","volume":" ","pages":"695-709"},"PeriodicalIF":2.6,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40572251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phenotypic and genetic diversity of domestic yak (Bos grunniens) in high-altitude rangelands of Gilgit-Baltistan, Pakistan.","authors":"Asif Hameed,&nbsp;Eva Schlecht,&nbsp;Muhammad Tariq,&nbsp;Andreas Buerkert,&nbsp;Carsten Scheper,&nbsp;Sven König,&nbsp;Regina Roessler","doi":"10.1111/jbg.12730","DOIUrl":"https://doi.org/10.1111/jbg.12730","url":null,"abstract":"<p><p>Due to climate change, irrigated agriculture may become restricted in the mountain valleys in northern Pakistan in the future. Hence, the importance of yak (Bos grunniens) keeping in the mountain ranges as risk-mitigating strategy for mountain dwellers will potentially increase. However, little is known about the current status of the domestic yak in this region. We therefore used phenotypic characteristics and 13 microsatellite loci to determine the phenotypic differences and the level of genetic differentiation between populations of six valleys. Larger body measures and partially different physical appearance were observed in Shimshal and Khaplu yaks, especially when compared with yaks in the Chapurson valley. Overall, the mean observed heterozygosity was similar to the mean expected heterozygosity. Average genetic diversity was highest in the Hopar population and lowest in the Haramosh population. A low F_IS value indicated that individuals were less related than expected under a model of random mating. Three distinct genetic clusters were found for the six yak populations under study. Genetic distances were largest between Shimshal and Khaplu populations, and lowest between populations of Phandar and Hopar. It is concluded that yaks of Shimshal, Khaplu and Haramosh valleys were genetically distinct from yak populations in Chapurson, Hopar and Phandar valleys, indicating that the free-range conditions and pastoral yak rearing system in the region have preserved the underlying genetic diversity of the yak populations.</p>","PeriodicalId":252687,"journal":{"name":"Journal of animal breeding and genetics = Zeitschrift für Tierzüchtung und Züchtungsbiologie","volume":" ","pages":"723-737"},"PeriodicalIF":2.6,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40469850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Managing genomes of conserved livestock breeds with historical introgression to decrease genetic overlap with other breeds.","authors":"Yu Wang,&nbsp;Jörn Bennewitz,&nbsp;Robin Wellmann","doi":"10.1111/jbg.12405","DOIUrl":"https://doi.org/10.1111/jbg.12405","url":null,"abstract":"<p><p>Recovering the native genetic background of a breed and increasing the founder genome equivalent (FGE) that is contributed by a breed to the gene pool of the species can increase its value for conservation. The suitability of several strategies was compared, whereby a hypothetical multi-breed population, the core set, was used to approximate the genetic diversity of the species. Twenty-five generations of management were simulated based on genotypes of German Angler cattle. The scenarios were compared when the kinship reached 0.10. The native contribution (NC) increased in a population with 400 births per generation from 0.317 to 0.706, whereas 1,000 births enabled to reach 0.894. This scenario maximized the NC, constrained the native kinship, and the kinship of the core set so that its genetic diversity could not decrease. It increased the proportions of mainstream breeds because their genes were removed from the target breed. A substantial increase of the FGE was achieved in some other scenarios, which arose from reduced genetic overlap and from increased diversity within the breed. The latter factor is especially important for breeds with high contributions to the core set.</p>","PeriodicalId":252687,"journal":{"name":"Journal of animal breeding and genetics = Zeitschrift für Tierzüchtung und Züchtungsbiologie","volume":" ","pages":"505-517"},"PeriodicalIF":2.6,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/jbg.12405","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37266863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of group records of feed intake to select for feed efficiency in rabbit.","authors":"Miriam Piles,&nbsp;Juan Pablo Sánchez","doi":"10.1111/jbg.12395","DOIUrl":"https://doi.org/10.1111/jbg.12395","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Models for genetic evaluation of feed efficiency (FE) for animals housed in groups when they are either fed ad libitum (F) or on restricted (R) feeding were implemented. Definitions of FE on F included group records of feed intake ( &lt;math&gt; &lt;msub&gt;&lt;mover&gt;&lt;mi&gt;FI&lt;/mi&gt; &lt;mo&gt;¯&lt;/mo&gt;&lt;/mover&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; ) and individual records of growth rate (G&lt;sub&gt;F&lt;/sub&gt; ) and metabolic weight (M&lt;sub&gt;F&lt;/sub&gt; ). Growth rate (G&lt;sub&gt;R&lt;/sub&gt; ) as FE measurement on R was used. Data corresponded to 5,336 kits from a rabbit sire line, from 1,255 litters in 14 batches and 667 cages. A five-trait mixed model (also with metabolic weight on R, M&lt;sub&gt;R&lt;/sub&gt; ) was implemented including, for each trait, the systematic effects of batch, body weight at weaning, parity order and litter size; and the random effects of litter, additive genetic and individual. A Bayesian analysis was performed. Conditional traits such as &lt;math&gt; &lt;mrow&gt; &lt;msub&gt;&lt;mover&gt;&lt;mi&gt;FI&lt;/mi&gt; &lt;mo&gt;¯&lt;/mo&gt;&lt;/mover&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mrow&gt;&lt;mo&gt;|&lt;/mo&gt;&lt;/mrow&gt; &lt;msub&gt;&lt;mi&gt;M&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;msub&gt;&lt;mi&gt;G&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;/mrow&gt; &lt;/math&gt; and &lt;math&gt; &lt;mrow&gt;&lt;msub&gt;&lt;mi&gt;G&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mrow&gt;&lt;mo&gt;|&lt;/mo&gt;&lt;/mrow&gt; &lt;msub&gt;&lt;mi&gt;M&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;msub&gt;&lt;mover&gt;&lt;mi&gt;FI&lt;/mi&gt; &lt;mo&gt;¯&lt;/mo&gt;&lt;/mover&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;/mrow&gt; &lt;/math&gt; were obtained from elements of additive genetics ( &lt;math&gt; &lt;msub&gt; &lt;mfenced&gt; &lt;msub&gt;&lt;mover&gt;&lt;mi&gt;FI&lt;/mi&gt; &lt;mo&gt;¯&lt;/mo&gt;&lt;/mover&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mrow&gt;&lt;mo&gt;|&lt;/mo&gt;&lt;/mrow&gt; &lt;msub&gt;&lt;mi&gt;M&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;msub&gt;&lt;mi&gt;G&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;/mfenced&gt; &lt;mi&gt;g&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; and &lt;math&gt; &lt;msub&gt; &lt;mfenced&gt;&lt;msub&gt;&lt;mi&gt;G&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mrow&gt;&lt;mo&gt;|&lt;/mo&gt;&lt;/mrow&gt; &lt;msub&gt;&lt;mi&gt;M&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;msub&gt;&lt;mover&gt;&lt;mi&gt;FI&lt;/mi&gt; &lt;mo&gt;¯&lt;/mo&gt;&lt;/mover&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;/mfenced&gt; &lt;mi&gt;g&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; ) or phenotypic ( &lt;math&gt; &lt;msub&gt; &lt;mfenced&gt; &lt;msub&gt;&lt;mover&gt;&lt;mi&gt;FI&lt;/mi&gt; &lt;mo&gt;¯&lt;/mo&gt;&lt;/mover&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mrow&gt;&lt;mo&gt;|&lt;/mo&gt;&lt;/mrow&gt; &lt;msub&gt;&lt;mi&gt;M&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;msub&gt;&lt;mi&gt;G&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;/mfenced&gt; &lt;mi&gt;p&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; and &lt;math&gt; &lt;msub&gt; &lt;mfenced&gt;&lt;msub&gt;&lt;mi&gt;G&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mrow&gt;&lt;mo&gt;|&lt;/mo&gt;&lt;/mrow&gt; &lt;msub&gt;&lt;mi&gt;M&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;msub&gt;&lt;mover&gt;&lt;mi&gt;FI&lt;/mi&gt; &lt;mo&gt;¯&lt;/mo&gt;&lt;/mover&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;/mfenced&gt; &lt;mi&gt;p&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; ) (co)variance matrices. In the first case, heritabilities were low (0.07 and 0.06 for &lt;math&gt; &lt;msub&gt; &lt;mfenced&gt; &lt;msub&gt;&lt;mover&gt;&lt;mi&gt;FI&lt;/mi&gt; &lt;mo&gt;¯&lt;/mo&gt;&lt;/mover&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mrow&gt;&lt;mo&gt;|&lt;/mo&gt;&lt;/mrow&gt; &lt;msub&gt;&lt;mi&gt;M&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;msub&gt;&lt;mi&gt;G&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;/mfenced&gt; &lt;mi&gt;g&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; and &lt;math&gt; &lt;msub&gt; &lt;mfenced&gt;&lt;msub&gt;&lt;mi&gt;G&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mrow&gt;&lt;mo&gt;|&lt;/mo&gt;&lt;/mrow&gt; &lt;msub&gt;&lt;mi&gt;M&lt;/mi&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;msub&gt;&lt;mover&gt;&lt;mi&gt;FI&lt;/mi&gt; &lt;mo&gt;¯&lt;/mo&gt;&lt;/mover&gt; &lt;mi&gt;F&lt;/mi&gt;&lt;/msub&gt; &lt;/mfenced&gt; &lt;mi&gt;g&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; , respectively) but null genetic correlation between the conditional and conditioning traits is guaranteed. In the second case, heritabilities were higher (0","PeriodicalId":252687,"journal":{"name":"Journal of animal breeding and genetics = Zeitschrift für Tierzüchtung und Züchtungsbiologie","volume":" ","pages":"474-483"},"PeriodicalIF":2.6,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/jbg.12395","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37184659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of heritability of feeding behaviour traits and their correlation with production traits in Finnish Yorkshire pigs.","authors":"Alper T Kavlak,&nbsp;Pekka Uimari","doi":"10.1111/jbg.12408","DOIUrl":"https://doi.org/10.1111/jbg.12408","url":null,"abstract":"<p><p>A major proportion of the costs of pork production is related to feed. The feed conversion rate (FCR) or residual feed intake (RFI) is thus commonly included in breeding programmes. Feeding behaviour traits do not directly have economic value but, if correlated with production traits, can be used as auxiliary traits. The aim of this study was to estimate the heritability of feeding behaviour traits and their genetic correlations with production traits in the Finnish Yorkshire pig population. The data were available from 3,235 pigs. Feeding behaviour was measured as the number of visits per day (NVD), time spent in feeding per day (TPD), daily feed intake (DFI), time spent feeding per visit (TPV), feed intake per visit (FPV) and feed intake rate (FR). The test station phase was divided into five periods. Estimates of heritabilities of feeding behaviour traits varied from 0.17 to 0.47. Strong genetic correlations were obtained between behaviour traits in all periods. However, only DFI was strongly correlated with the production traits. Interestingly, a moderate positive genetic correlation was obtained between FR and backfat thickness (0.1-0.5) and between FR and average daily gain (0.3-0.4), depending on the period. Based on the results, there is no additional benefit from including feeding-related traits other than those commonly used (FCR and RFI) in the breeding programme. However, if correlated with animal welfare, the feeding behaviour traits could be valuable in the breeding programme.</p>","PeriodicalId":252687,"journal":{"name":"Journal of animal breeding and genetics = Zeitschrift für Tierzüchtung und Züchtungsbiologie","volume":" ","pages":"484-494"},"PeriodicalIF":2.6,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/jbg.12408","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40450292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combined approaches to identify genomic regions involved in phenotypic differentiation between low divergent breeds: Application in Sardinian sheep populations.","authors":"Salvatore Mastrangelo,&nbsp;Slim Ben Jemaa,&nbsp;Gianluca Sottile,&nbsp;Sara Casu,&nbsp;Baldassare Portolano,&nbsp;Elena Ciani,&nbsp;Fabio Pilla","doi":"10.1111/jbg.12422","DOIUrl":"https://doi.org/10.1111/jbg.12422","url":null,"abstract":"<p><p>Selective breeding has led to modifications in the genome of many livestock breeds. In this study, we identified the genomic regions that may explain some of the phenotypic differences between two closely related breeds from Sardinia. A total of 44 animals, 20 Sardinian Ancestral Black (SAB) and 24 Sardinian White (SW), were genotyped using the Illumina Ovine 50K array. A total of 68, 38 and 15 significant markers were identified using the case-control genome-wide association study (GWAS), the Bayesian population differentiation analysis (F_ST ) and the Rsb metric, respectively. Comparisons among the approaches revealed a total of 22 overlapping markers between GWAS and F_ST and one marker between GWAS and Rsb. Three markers detected by Rsb were also located near (<2 Mb) to highly significant regions identified by GWAS and F_ST analyses. Moreover, one candidate marker identified by GWAS and F_ST approaches was located in a run of homozygosity island that was shared by both breeds. We identified several genes involved in many phenotypic differences (such as stature and growth, reproduction, ear size, coat colour, behaviour) between the two analysed breeds. This study shows that combining several genome-wide approaches could improve discovery of regions involved in the variability of breeding traits and responsible for the phenotypic diversity even between closely related breeds. Overall, the combination of such genome-wide methods can be extended to other livestock breeds that share between them a similar genetic background, to understand the process that shapes the patterns of genetic variability between closely related populations.</p>","PeriodicalId":252687,"journal":{"name":"Journal of animal breeding and genetics = Zeitschrift für Tierzüchtung und Züchtungsbiologie","volume":" ","pages":"526-534"},"PeriodicalIF":2.6,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/jbg.12422","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37341405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}