scholarly journals Optimising Genomic Selection in Wheat: Effect of Marker Density, Population Size and Population Structure on Prediction Accuracy

2018 ◽  
Vol 8 (9) ◽  
pp. 2889-2899 ◽  
Author(s):  
Adam Norman ◽  
Julian Taylor ◽  
James Edwards ◽  
Haydn Kuchel
Keyword(s):  
Population Structure ◽  
Population Size ◽  
Genomic Selection ◽  
Prediction Accuracy ◽  
Marker Density ◽  
Density Population

scholarly journals Optimization of Genomic Selection to Improve Disease Resistance in Two Marine Fishes, the European Sea Bass (Dicentrarchus labrax) and the Gilthead Sea Bream (Sparus aurata)

2021 ◽  
Vol 12 ◽  
Author(s):  
Ronan Griot ◽  
François Allal ◽  
Florence Phocas ◽  
Sophie Brard-Fudulea ◽  
Romain Morvezen ◽  
...  
Keyword(s):  
Population Size ◽  
Genomic Selection ◽  
Sparus Aurata ◽  
Sea Bass ◽  
Gilthead Sea Bream ◽  
Sea Bream ◽  
Full Density ◽  
Marker Density ◽  
Training Population ◽  
European Sea Bass

Disease outbreaks are a major threat to the aquaculture industry, and can be controlled by selective breeding. With the development of high-throughput genotyping technologies, genomic selection may become accessible even in minor species. Training population size and marker density are among the main drivers of the prediction accuracy, which both have a high impact on the cost of genomic selection. In this study, we assessed the impact of training population size as well as marker density on the prediction accuracy of disease resistance traits in European sea bass (Dicentrarchus labrax) and gilthead sea bream (Sparus aurata). We performed a challenge to nervous necrosis virus (NNV) in two sea bass cohorts, a challenge to Vibrio harveyi in one sea bass cohort and a challenge to Photobacterium damselae subsp. piscicida in one sea bream cohort. Challenged individuals were genotyped on 57K–60K SNP chips. Markers were sampled to design virtual SNP chips of 1K, 3K, 6K, and 10K markers. Similarly, challenged individuals were randomly sampled to vary training population size from 50 to 800 individuals. The accuracy of genomic-based (GBLUP model) and pedigree-based estimated breeding values (EBV) (PBLUP model) was computed for each training population size using Monte-Carlo cross-validation. Genomic-based breeding values were also computed using the virtual chips to study the effect of marker density. For resistance to Viral Nervous Necrosis (VNN), as one major QTL was detected, the opportunity of marker-assisted selection was investigated by adding a QTL effect in both genomic and pedigree prediction models. As training population size increased, accuracy increased to reach values in range of 0.51–0.65 for full density chips. The accuracy could still increase with more individuals in the training population as the accuracy plateau was not reached. When using only the 6K density chip, accuracy reached at least 90% of that obtained with the full density chip. Adding the QTL effect increased the accuracy of the PBLUP model to values higher than the GBLUP model without the QTL effect. This work sets a framework for the practical implementation of genomic selection to improve the resistance to major diseases in European sea bass and gilthead sea bream.

scholarly journals Genomic Prediction in Pea: Effect of Marker Density and Training Population Size and Composition on Prediction Accuracy

2015 ◽  
Vol 6 ◽  
Author(s):  
Nadim Tayeh ◽  
Anthony Klein ◽  
Marie-Christine Le Paslier ◽  
Françoise Jacquin ◽  
Hervé Houtin ◽  
...  
Keyword(s):  
Population Size ◽  
Genomic Prediction ◽  
Prediction Accuracy ◽  
Marker Density ◽  
Training Population ◽  
And Training

Effect of Population Structure on Prediction Accuracy of Soybean 100-Seed Weight by Genomic Selection

2018 ◽  
Vol 44 (1) ◽  
pp. 43
Author(s):  
Yan-Song MA ◽  
Zhang-Xiong LIU ◽  
Zi-Xiang WEN ◽  
Shu-Hong WEI ◽  
Chun-Ming YANG ◽  
...  
Keyword(s):  
Population Structure ◽  
Genomic Selection ◽  
Seed Weight ◽  
Prediction Accuracy ◽  
100 Seed Weight

scholarly journals Prediction Accuracies of Genomic Selection for Nine Commercially Important Traits in the Portuguese Oyster (Crassostrea angulata) Using DArT-Seq Technology

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 210
Author(s):  
Sang V. Vu ◽  
Cedric Gondro ◽  
Ngoc T. H. Nguyen ◽  
Arthur R. Gilmour ◽  
Rick Tearle ◽  
...  
Keyword(s):  
Moisture Content ◽  
Genomic Selection ◽  
Shell Length ◽  
Prediction Accuracy ◽  
Genomic Information ◽  
Morphometric Traits ◽  
Shell Weight ◽  
Shell Width ◽  
Crassostrea Angulata ◽  
Selection For

Genomic selection has been widely used in terrestrial animals but has had limited application in aquaculture due to relatively high genotyping costs. Genomic information has an important role in improving the prediction accuracy of breeding values, especially for traits that are difficult or expensive to measure. The purposes of this study were to (i) further evaluate the use of genomic information to improve prediction accuracies of breeding values from, (ii) compare different prediction methods (BayesA, BayesCπ and GBLUP) on prediction accuracies in our field data, and (iii) investigate the effects of different SNP marker densities on prediction accuracies of traits in the Portuguese oyster (Crassostrea angulata). The traits studied are all of economic importance and included morphometric traits (shell length, shell width, shell depth, shell weight), edibility traits (tenderness, taste, moisture content), and disease traits (Polydora sp. and Marteilioides chungmuensis). A total of 18,849 single nucleotide polymorphisms were obtained from genotyping by sequencing and used to estimate genetic parameters (heritability and genetic correlation) and the prediction accuracy of genomic selection for these traits. Multi-locus mixed model analysis indicated high estimates of heritability for edibility traits; 0.44 for moisture content, 0.59 for taste, and 0.72 for tenderness. The morphometric traits, shell length, shell width, shell depth and shell weight had estimated genomic heritabilities ranging from 0.28 to 0.55. The genomic heritabilities were relatively low for the disease related traits: Polydora sp. prevalence (0.11) and M. chungmuensis (0.10). Genomic correlations between whole weight and other morphometric traits were from moderate to high and positive (0.58–0.90). However, unfavourably positive genomic correlations were observed between whole weight and the disease traits (0.35–0.37). The genomic best linear unbiased prediction method (GBLUP) showed slightly higher accuracy for the traits studied (0.240–0.794) compared with both BayesA and BayesCπ methods but these differences were not significant. In addition, there is a large potential for using low-density SNP markers for genomic selection in this population at a number of 3000 SNPs. Therefore, there is the prospect to improve morphometric, edibility and disease related traits using genomic information in this species.

scholarly journals How Do the Population Structure Changes of China Affect Carbon Emissions? An Empirical Study Based on Ridge Regression Analysis

2021 ◽  
Vol 13 (6) ◽  
pp. 3319
Author(s):  
Chulin Pan ◽  
Huayi Wang ◽  
Hongpeng Guo ◽  
Hong Pan
Keyword(s):  
Population Structure ◽  
Regression Analysis ◽  
Population Size ◽  
Carbon Emissions ◽  
Ridge Regression ◽  
Employment Structure ◽  
Consumption Structure ◽  
Structure Changes ◽  
Size Population ◽  
Ridge Regression Analysis

This study focuses on the impact of population structure changes on carbon emissions in China from 1995 to 2018. This paper constructs the multiple regression model and uses the ridge regression to analyze the relationship between population structure changes and carbon emissions from four aspects: population size, population age structure, population consumption structure, and population employment structure. The results showed that these four variables all had a significant impact on carbon emissions in China. The ridge regression analysis confirmed that the population size, population age structure, and population employment structure promoted the increase in carbon emissions, and their contribution ratios were 3.316%, 2.468%, 1.280%, respectively. However, the influence of population consumption structure (−0.667%) on carbon emissions was negative. The results showed that the population size had the greatest impact on carbon emissions, which was the main driving factor of carbon emissions in China. Chinese population will bring huge pressure on the environment and resources in the future. Therefore, based on the comprehensive analysis, implementing the one-child policy will help slow down China’s population growth, control the number of populations, optimize the population structure, so as to reduce carbon emissions. In terms of employment structure and consumption structure, we should strengthen policy guidance and market incentives, raising people’s low-carbon awareness, optimizing energy-consumption structure, improving energy efficiency, so as to effectively control China’s carbon emissions.

scholarly journals Population dynamics in northwestern China

2021 ◽  
Author(s):  
Xueyan Yang ◽  
Wanxin Li ◽  
Wen Jing ◽  
Chezhuo Gao ◽  
Rui Li ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Population Structure ◽  
Population Size ◽  
Ethnic Groups ◽  
Northwestern China ◽  
Average Level ◽  
Han Population ◽  
Sex Structure ◽  
Biological Sex

AbstractThis article analyzes the population dynamics in northwestern China from roughly 2010 to 2020. The area’s dynamics showed a slow, stable increase in population size, a stable increase in the population of non-Han ethnic groups, which increased at a more rapidly than the Han population, and population rejuvenation coupled with a population structure that aged. The biological sex structure fluctuated within a balanced range in northwestern China. Urbanization advanced in northwestern China, throughout this period, but the area’s level of urbanization is still significantly lower than the average level of urbanization nationally.

scholarly journals Legacy of draught cattle breeds of South India: Insights into population structure, genetic admixture and maternal origin

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0246497
Author(s):  
Vandana Manomohan ◽  
Ramasamy Saravanan ◽  
Rudolf Pichler ◽  
Nagarajan Murali ◽  
Karuppusamy Sivakumar ◽  
...  
Keyword(s):  
Population Structure ◽  
Population Size ◽  
Effective Population Size ◽  
South India ◽  
Genetic Admixture ◽  
Zebu Cattle ◽  
Effective Population ◽  
Cattle Breeds ◽  
South Indian ◽  
Indian Cattle

The present study is the first comprehensive report on diversity, population structure, genetic admixture and mitochondrial DNA variation in South Indian draught type zebu cattle. The diversity of South Indian cattle was moderately high. A significantly strong negative correlation coefficient of -0.674 (P<0.05) was observed between the effective population size of different breeds and their estimated FIS. The genetic structure analysis revealed the distinctness of Kangayam, Vechur and Punganur cattle from the rest of the zebu breeds. The results showed the influence of Hallikar breed in the development of most Mysore type cattle breeds of South India with the exception of Kangayam. Bayesian clustering analysis was performed to assess the taurine admixture in South Indian zebu cattle using purebred Jersey and Holstein-Friesian as reference genotypes. Relatively high levels of taurine admixture (>6.25%) was observed in Punganur, Vechur, Umblachery and Pulikulam cattle breeds. Two major maternal haplogroups, I1 and I2, typical of zebu cattle were observed, with the former being predominant than the later. The pairwise differences among the I2 haplotypes of South Indian cattle were relatively higher than West Indian (Indus valley site) zebu cattle. The results indicated the need for additional sampling and comprehensive analysis of mtDNA control region variations to unravel the probable location of origin and domestication of I2 zebu lineage. The present study also revealed major concerns on South Indian zebu cattle (i) risk of endangerment due to small effective population size and high rate of inbreeding (ii) lack of sufficient purebred zebu bulls for breeding and (iii) increasing level of taurine admixture in zebu cattle. Availability of purebred semen for artificial insemination, incorporation of genomic/molecular information to identify purebred animals and increased awareness among farmers will help to maintain breed purity, conserve and improve these important draught cattle germplasms of South India.

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