Hybrid breeding for biomass yield in winter triticale: II. Combining ability and hybrid prediction     

Johannes Trini  Hans Peter Maurer  Sigrid Weissmann  Tobias Würschum 《Plant Breeding》2020,139(5):906-915

Accurate hybrid prediction and knowledge about the relative contribution of general (GCA) and specific combining ability (SCA) are of utmost importance for efficient hybrid breeding. We therefore evaluated 91 triticale single-cross hybrids in field trials at seven environments for plant height, heading time, fresh biomass, dry matter content and dry biomass. Fresh and dry biomass showed the highest proportion (23%) of variance due to SCA. Prediction accuracies based on GCA were slightly higher than based on mid-parent values. Utilizing parental kinship information yielded the highest prediction accuracies when both parental lines have been tested in other hybrid combinations, but still moderate-to-low prediction accuracies for two untested parents. Thus, hybrid prediction for biomass traits in triticale is currently promising based on mid-parent values as emphasized by our simulation study, but can be expected to shift to GCA-based prediction with an increasing importance of GCA due to selection in hybrid breeding. Moreover, the performance of potential hybrids between newly developed lines can be predicted with moderate accuracy using genomic relationship information.  相似文献   

South-Western blot mapping方法的建立及其应用于锥虫细胞核中DNA结合蛋白的观察     

欧永春  T.Baltz 《中国兽医学报》1992,(2)

South-Westerm blot mapping是一种结合Western blotting和Southern blotting某些特点的方法.本文介绍用其成功地观察到锥虫核蛋白中DNA结合蛋白的情况,并对一个分子量在40000左右、于较严谨条件下与DNA结合的核蛋白进行了特性鉴定.该蛋白等量地存在于锥虫的前循环期和血液期,对双链DNA有较大的亲和力,并能与酵母菌复制起始片段结合.本文还介绍了锥虫细胞核的提取技术和核蛋白的制备技术.  相似文献   

DNA甲基化与基因组印记     

束婧婷 《畜牧兽医杂志》2005,24(6):18-20

综合论述了DNA甲基化与基因组印记的最新研究进展,论述了它们的生物学意义,并阐述了两者的关系.  相似文献   

The impact of truncating data on the predictive ability for single‐step genomic best linear unbiased prediction          下载免费PDF全文

Jeremy T. Howard  Tom A. Rathje  Caitlyn E. Bruns  Danielle F. Wilson‐Wells  Stephen D. Kachman  Matthew L. Spangler 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2018,135(4):251-262

Simulated and swine industry data sets were utilized to assess the impact of removing older data on the predictive ability of selection candidate estimated breeding values (EBV) when using single‐step genomic best linear unbiased prediction (ssGBLUP). Simulated data included thirty replicates designed to mimic the structure of swine data sets. For the simulated data, varying amounts of data were truncated based on the number of ancestral generations back from the selection candidates. The swine data sets consisted of phenotypic and genotypic records for three traits across two breeds on animals born from 2003 to 2017. Phenotypes and genotypes were iteratively removed 1 year at a time based on the year an animal was born. For the swine data sets, correlations between corrected phenotypes (Cp) and EBV were used to evaluate the predictive ability on young animals born in 2016–2017. In the simulated data set, keeping data two generations back or greater resulted in no statistical difference (p‐value > 0.05) in the reduction in the true breeding value at generation 15 compared to utilizing all available data. Across swine data sets, removing phenotypes from animals born prior to 2011 resulted in a negligible or a slight numerical increase in the correlation between Cp and EBV. Truncating data is a method to alleviate computational issues without negatively impacting the predictive ability of selection candidate EBV.  相似文献   

Single step genomic evaluation for female fertility in Nordic Red dairy cattle          下载免费PDF全文

Kaarina Matilainen  Ismo Strandén  Gert Pedersen Aamand  Esa A. Mäntysaari 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2018,135(5):337-348

Joint Nordic (Denmark, Finland, Sweden) genetic evaluation of female fertility is currently based on the multiple trait multilactation animal model (BLUP). Here, single step genomic model (ssGBLUP) was applied for the Nordic Red dairy cattle fertility evaluation. The 11 traits comprised of nonreturn rate and days from first to last insemination in heifers and first three parities, and days from calving to first insemination in the first three parities. Traits had low heritabilities (0.015–0.04), but moderately high genetic correlations between the parities (0.60–0.88). Phenotypic data included 4,226,715 animals with records and pedigree 5,445,392 animals. Unknown parents were assigned into 332 phantom parent groups (PPG). In mixed model equations animals were associated with PPG effects through the pedigree or both the pedigree and genomic information. Genotype information of 46,914 SNPs was available for 33,969 animals in the pedigree. When PPG used pedigree information only, BLUP converged after 2,420 iterations whereas the ssGBLUP evaluation needed over ten thousand iterations. When the PPG effects were solved accounting both the pedigree and the genomic information, the ssGBLUP model converged after 2,406 iterations. Also, with the latter model breeding values by ssGBLUP and BLUP became more consistent and genetic trends followed each other well. Models were validated using forward prediction of the young bulls. Reliabilities and variance inflation of predicted genomic breeding values (values for parent averages in brackets) for the 11 traits ranged 0.22–0.31 (0.10–0.27) and 0.81–0.95 (0.83–1.06), respectively. The ssGBLUP model gave always higher validation reliabilities than BLUP, but largest increases were for the cow fertility traits.  相似文献   

Genomic prediction for yields,processing and nutritional quality traits in cultivated potato (Solanum tuberosum L.)          下载免费PDF全文

Ephrem Habyarimana  Bruno Parisi  Giuseppe Mandolino 《Plant Breeding》2017,136(2):245-252

Current potato breeding approaches are hampered by several factors including costly seed tubers, tetrasomic inheritance and inbreeding depression. Genomic selection (GS) demonstrated interesting results regardless of the ploidy level, and can be harnessed to circumvent these problems. In this work, three GS models were evaluated using 50,107 informative SilicoDArT markers and 11 traits in two values for cultivation and use (VCU) potato trials. Two key breeding problems modelled included predicting the performance of (i) new and unphenotyped clones (cross‐validation) and (ii) a VCU using another as training set (TS). GS models performed comparably. Cross‐validation accuracy was high for D35, D45, DMW and BVAL, in ascending order. Prediction accuracies of the VCUs were highly correlated, but the best prediction was obtained for the smaller VCU using the bigger as TS. Cross‐validation and VCU prediction accuracies were higher when bigger TSs were used. The findings herein indicate that GS can be attractively integrated in potato breeding, particularly in early clonal generations to predict and select for traits with low heritability which would otherwise require more testing years, environments and resources.  相似文献   

Genome-wide identification and expression analysis of anthocyanin biosynthetic genes in Brassica juncea          下载免费PDF全文

ZHANG Da-wei  LIU Li-li  ZHOU Ding-gang  LIU Xian-jun  LIU Zhong-song  YAN Ming-li 《农业科学学报》2020,19(5):1250-1260

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利用基因组信息提高畜禽生产性能研究进展     

周喜荣  于丽娟  张玉华  玛尔孜亚·亚森  蒋晓梅  拉扎特·艾尼瓦尔  张艳花 《中国畜牧兽医》2020,47(1):156-163

为了满足人们对畜产品需求的快速增长，必须在加快畜禽产业发展的同时把对环境的影响降到最低，提高畜禽遗传特性有望促进这一问题的解决。进入21世纪以来，以基因组选择为核心的分子育种技术迎来了发展机遇，利用该技术可实现早期准确选择，从而大幅度缩短世代间隔，加快群体遗传进展，并显著降低育种成本。虽然在某些畜种中（如奶牛），基因组选择取得了成功，群体也获得较大遗传进展，但仍无法满足快速增长的需求。因此，亟需寻找能够进一步加快遗传进展的方法。研究表明，在SNP标记数据中加入目标性状的已知功能基因信息，可以提高基因组育种值预测的准确性，进而加快遗传进展。而挖掘更多基因组信息的同时，开发更优化的分析方法可以更有助于目标的实现。文章总结了主要畜禽物种的可用基因组数据，包括牛、绵羊、山羊、猪和鸡以及这些数据是如何有助于鉴定影响重要性状的遗传标记和基因，从而进一步提高基因组选择的准确性。  相似文献   

Selecting the hologenome to breed for an improved feed efficiency in pigs—A novel selection index     

Ramona Weishaar  Robin Wellmann  Amelia Camarinha-Silva  Markus Rodehutscord  Jörn Bennewitz 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2020,137(1):14-22

Most traits in animal breeding, including feed efficiency traits in pigs, are affected by many genes with small effect and have a moderately high heritability between 0.1 and 0.5, which enables efficient selection. Since the microbiota composition in the gastrointestinal tract is also partly heritable and was shown to have a substantial effect on feed efficiency, the host genes affect the phenotype not only directly by altering metabolic pathways, but also indirectly by changing the microbiota composition. The effect of the microbiota composition on the breeding value of an animal is the conditional expectation of its breeding value, given the vector with microbiota frequencies, that is The breeding value of an animal can therefore be decomposed into a heritable contribution that arises from an altered microbiota composition and a heritable contribution that arises from altered metabolic pathways within the animal, so Instead of selecting for breeding value , an index comprising the two components and with appropriate weights, that is , can be used. The present study shows how this breeding strategy can be applied in pig genomic selection breeding scheme for two feed efficiency traits and daily gain.  相似文献   

Emerging issues in genomic selection     

Ignacy Misztal  Ignacio Aguilar  Daniela Lourenco  Li Ma  Juan Pedro Steibel  Miguel Toro 《Journal of animal science》2021,99(6)

Genomic selection (GS) is now practiced successfully across many species. However, many questions remain, such as long-term effects, estimations of genomic parameters, robustness of genome-wide association study (GWAS) with small and large datasets, and stability of genomic predictions. This study summarizes presentations from the authors at the 2020 American Society of Animal Science (ASAS) symposium. The focus of many studies until now is on linkage disequilibrium between two loci. Ignoring higher-level equilibrium may lead to phantom dominance and epistasis. The Bulmer effect leads to a reduction of the additive variance; however, the selection for increased recombination rate can release anew genetic variance. With genomic information, estimates of genetic parameters may be biased by genomic preselection, but costs of estimation can increase drastically due to the dense form of the genomic information. To make the computation of estimates feasible, genotypes could be retained only for the most important animals, and methods of estimation should use algorithms that can recognize dense blocks in sparse matrices. GWASs using small genomic datasets frequently find many marker-trait associations, whereas studies using much bigger datasets find only a few. Most of the current tools use very simple models for GWAS, possibly causing artifacts. These models are adequate for large datasets where pseudo-phenotypes such as deregressed proofs indirectly account for important effects for traits of interest. Artifacts arising in GWAS with small datasets can be minimized by using data from all animals (whether genotyped or not), realistic models, and methods that account for population structure. Recent developments permit the computation of P-values from genomic best linear unbiased prediction (GBLUP), where models can be arbitrarily complex but restricted to genotyped animals only, and single-step GBLUP that also uses phenotypes from ungenotyped animals. Stability was an important part of nongenomic evaluations, where genetic predictions were stable in the absence of new data even with low prediction accuracies. Unfortunately, genomic evaluations for such animals change because all animals with genotypes are connected. A top-ranked animal can easily drop in the next evaluation, causing a crisis of confidence in genomic evaluations. While correlations between consecutive genomic evaluations are high, outliers can have differences as high as 1 SD. A solution to fluctuating genomic evaluations is to base selection decisions on groups of animals. Although many issues in GS have been solved, many new issues that require additional research continue to surface.  相似文献