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Autor: Rajeev Varshney
Abiotic stress tolerance: Genetics, genomics, and breeding
Yunbi Xu Rajeev Varshney (2023)
Artículo
Wheat Ancestors Modern Varieties Agronomic Performance CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ABIOTIC STRESS GENETICS GENOMICS BREEDING GERMPLASM DROUGHT STRESS
Spurthi Nayak Polavarapu Kavi Kishor Rajeev Varshney (2010)
Artículo
Simple Sequence Repeats Mapping Population Translational Studies CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ANCHORS CHICKPEAS CICER ARIETINUM GENETIC MAPS GENETIC MARKERS MEDICAGO MEDICAGO TRUNCATULA MICROSATELLITES SINGLE NUCLEOTIDE POLYMORPHISM GENES
Manish Pandey Trushar Shah David Bertioli Rajeev Varshney (2012)
Artículo
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BACKCROSSING GENOTYPES GROUNDNUTS MICROSATELLITES ARACHIS HYPOGAEA CHROMOSOME MAPPING PLANTS GENETIC MARKERS QUANTITATIVE TRAIT LOCI TETRAPLOIDY
Osval Antonio Montesinos-Lopez ABELARDO MONTESINOS LOPEZ RICARDO ACOSTA DIAZ Rajeev Varshney Jose Crossa ALISON BENTLEY (2022)
Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to
the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.
Artículo
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA Bayes Theorem Genome Inflammatory Bowel Diseases Models, Genetic Plant Breeding
MAHENDAR THUDI Abhishek Bohra Spurthi Nayak Trushar Shah R. Varma Penmetsa Nepolean Thirunavukkarasu Pooran Gaur Pawan Kulwal Hari Upadhyaya Polavarapu Kavi Kishor Rajeev Varshney (2011)
Artículo
Molecular Markers Recombinant Inbred Lines CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENETIC MARKERS MICROSATELLITES PLANTS DNA CHICKPEAS ARRAYS TECHNOLOGY CHROMOSOME MAPPING GENETIC VARIATION GENOTYPES MOLECULAR CLONING