scholarly journals First genomic prediction and genome‐wide association for complex growth‐related traits in Rock Bream (Oplegnathus fasciatus)

2021 ◽  
Author(s):  
Jie Gong ◽  
Ji Zhao ◽  
Qiaozhen Ke ◽  
Bijun Li ◽  
Zhixiong Zhou ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Genome Wide Association ◽  
Oplegnathus Fasciatus ◽  
Rock Bream ◽  
Genome Wide

scholarly journals Genome‐wide association and genomic prediction for biomass yield in a genetically diverseMiscanthus sinensisgermplasm panel phenotyped at five locations in Asia and North America

GCB Bioenergy ◽  
2019 ◽  
Author(s):  
Lindsay V. Clark ◽  
Maria S. Dwiyanti ◽  
Kossonou G. Anzoua ◽  
Joe E. Brummer ◽  
Bimal Kumar Ghimire ◽  
...  
Keyword(s):  
North America ◽  
Genomic Prediction ◽  
Biomass Yield ◽  
Genome Wide Association ◽  
Genome Wide

scholarly journals Genome-wide association study and accuracy of genomic prediction for teat number in Duroc pigs using genotyping-by-sequencing

2017 ◽  
Vol 49 (1) ◽  
Author(s):  
Cheng Tan ◽  
Zhenfang Wu ◽  
Jiangli Ren ◽  
Zhuolin Huang ◽  
Dewu Liu ◽  
...  
Keyword(s):  
Association Study ◽  
Genomic Prediction ◽  
Genome Wide Association Study ◽  
Genotyping By Sequencing ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Teat Number

Genome-wide association mapping and genomic prediction of yield-related traits and starch pasting properties in cassava

2021 ◽  
Author(s):  
Chalermpol Phumichai ◽  
Pornsak Aiemnaka ◽  
Piyaporn Nathaisong ◽  
Sirikan Hunsawattanakul ◽  
Phasakorn Fungfoo ◽  
...  
Keyword(s):  
Association Mapping ◽  
Genomic Prediction ◽  
Pasting Properties ◽  
Genome Wide Association ◽  
Genome Wide

scholarly journals Genomic Prediction and Genome-Wide Association Studies of Flour Yield and Alveograph Quality Traits Using Advanced Winter Wheat Breeding Material

Genes ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 669 ◽  
Author(s):  
Peter S. Kristensen ◽  
Just Jensen ◽  
Jeppe R. Andersen ◽  
Carlos Guzmán ◽  
Jihad Orabi ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Genomic Prediction ◽  
Association Studies ◽  
Wheat Breeding ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Quality Traits ◽  
Breeding Programs ◽  
Genome Wide ◽  
Flour Yield

Use of genetic markers and genomic prediction might improve genetic gain for quality traits in wheat breeding programs. Here, flour yield and Alveograph quality traits were inspected in 635 F6 winter wheat breeding lines from two breeding cycles. Genome-wide association studies revealed single nucleotide polymorphisms (SNPs) on chromosome 5D significantly associated with flour yield, Alveograph P (dough tenacity), and Alveograph W (dough strength). Additionally, SNPs on chromosome 1D were associated with Alveograph P and W, SNPs on chromosome 1B were associated with Alveograph P, and SNPs on chromosome 4A were associated with Alveograph L (dough extensibility). Predictive abilities based on genomic best linear unbiased prediction (GBLUP) models ranged from 0.50 for flour yield to 0.79 for Alveograph W based on a leave-one-out cross-validation strategy. Predictive abilities were negatively affected by smaller training set sizes, lower genetic relationship between lines in training and validation sets, and by genotype–environment (G×E) interactions. Bayesian Power Lasso models and genomic feature models resulted in similar or slightly improved predictions compared to GBLUP models. SNPs with the largest effects can be used for screening large numbers of lines in early generations in breeding programs to select lines that potentially have good quality traits. In later generations, genomic predictions might be used for a more accurate selection of high quality wheat lines.

Genome-wide association study and genomic prediction for resistance against Streptococcus agalactiae in hybrid red tilapia (Oreochromis spp.)

Aquaculture ◽  
2020 ◽  
Vol 525 ◽  
pp. 735297 ◽  
Author(s):  
Sila Sukhavachana ◽  
Pumipat Tongyoo ◽  
Cecile Massault ◽  
Nichanun McMillan ◽  
Amorn Leungnaruemitchai ◽  
...  
Keyword(s):  
Association Study ◽  
Streptococcus Agalactiae ◽  
Genomic Prediction ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Red Tilapia ◽  
Genome Wide

scholarly journals 0326 Genome-wide association study and accuracy of genomic prediction for teat number in Duroc pigs using genotyping by sequencing

2016 ◽  
Vol 94 (suppl_5) ◽  
pp. 156-157
Author(s):  
C. Tan ◽  
Y. Da ◽  
Z. Wu ◽  
D. Liu ◽  
X. He ◽  
...  
Keyword(s):  
Association Study ◽  
Genomic Prediction ◽  
Genome Wide Association Study ◽  
Genotyping By Sequencing ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Teat Number

scholarly journals Genetic Correlation, Genome-Wide Association and Genomic Prediction of Portable NIRS Predicted Carotenoids in Cassava Roots

2019 ◽  
Vol 10 ◽  
Author(s):  
Ugochukwu N. Ikeogu ◽  
Deniz Akdemir ◽  
Marnin D. Wolfe ◽  
Uche G. Okeke ◽  
Amaefula Chinedozi ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Genomic Prediction ◽  
Genome Wide Association ◽  
Genome Wide

scholarly journals Genome-wide association mapping and genomic prediction unravels CBSD resistance in a Manihot esculenta breeding population

2017 ◽  
Author(s):  
Siraj Ismail Kayondo ◽  
Dunia Pino Del Carpio ◽  
Roberto Lozano ◽  
Alfred Ozimati ◽  
Marnin Wolfe ◽  
...  
Keyword(s):  
Association Mapping ◽  
Genomic Prediction ◽  
Manihot Esculenta ◽  
Prediction Models ◽  
Genome Wide Association ◽  
Cassava Mosaic Disease ◽  
Growth Stages ◽  
Chromosome 11 ◽  
Genome Wide ◽  
Severity Scores

AbstractCassava (Manihot esculenta Crantz), a key carbohydrate dietary source for millions of people in Africa, faces severe yield loses due to two viral diseases: cassava brown streak disease (CBSD) and cassava mosaic disease (CMD). The completion of the cassava genome sequence and the whole genome marker profiling of clones from African breeding programs (www.nextgencassava.org) provides cassava breeders the opportunity to deploy additional breeding strategies and develop superior varieties with both farmer and industry preferred traits. Here the identification of genomic segments associated with resistance to CBSD foliar symptoms and root necrosis as measured in two breeding panels at different growth stages and locations is reported. Using genome-wide association mapping and genomic prediction models we describe the genetic architecture for CBSD severity and identify loci strongly associated on chromosomes 4 and 11. Moreover, the significantly associated region on chromosome 4 colocalises with a Manihot glaziovii introgression segment and the significant SNP markers on chromosome 11 are situated within a cluster of nucleotide-binding site leucine-rich repeat (NBS-LRR) genes previously described in cassava. Overall, predictive accuracy values found in this study varied between CBSD severity traits and across GS models with Random Forest and RKHS showing the highest predictive accuracies for foliar and root CBSD severity scores.

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