Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement

Heredity

Volumn 116, Issue 4, 2016, Pages 395-408

  Spindel, J E ^a   Begum, H ^b,d   Akdemir, D ^a   Collard, B ^b   Redona E ^b,e   Jannink, J L ^a,c   McCouch, S ^a  

^a Cornell University ^*  (United States)

^b INTERNATIONAL RICE RESEARCH INSTITUTE   (Philippines)

^c ROBERT W HOLLEY CENTER FOR AGRICULTURE AND HEALTH   (United States)

^d BANGLADESH RICE RESEARCH INSTITUTE   (Bangladesh)

^e MISSISSIPPI STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURAL MODELING; AGRICULTURAL PRODUCTION; BREEDING POPULATION; CLIMATE CHANGE; CROP IMPROVEMENT; FOOD SECURITY; GENETIC ANALYSIS; GENETIC VARIATION; GENOME; GLOBAL CLIMATE; PLANT BREEDING; POPULATION GROWTH; RICE;

GENETIC MARKER;

AGRICULTURE; BIOLOGICAL MODEL; GENETIC ASSOCIATION STUDY; GENETIC MARKER; GENETICS; GENOTYPE; ORYZA; PHENOTYPE; PLANT BREEDING; PLANT GENOME; PROCEDURES; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL MODEL;

AGRICULTURE; GENETIC ASSOCIATION STUDIES; GENETIC MARKERS; GENOME, PLANT; GENOTYPE; MODELS, GENETIC; MODELS, STATISTICAL; ORYZA; PHENOTYPE; PLANT BREEDING; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 84960374900     PISSN: 0018067X     EISSN: 13652540     Source Type: Journal    
DOI: 10.1038/hdy.2015.113     Document Type: Article

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