Single-gene resolution of locally adaptive genetic variation in Mexican maize

作者: Daniel J Gates , Dan Runcie , Garrett M. Janzen , Alberto Romero Navarro , Martha Willcox

DOI: 10.1101/706739

关键词:

摘要: Abstract Threats to crop production due climate change are one of the greatest challenges facing plant breeders today. While considerable adaptive variation exists in traditional landraces, natural populations wild relatives, and ex situ germplasm collections, separating alleles from linked deleterious variants that impact agronomic traits is challenging has limited utility these diverse resources. Modern genome editing techniques such as CRISPR offer a potential solution by targeting specific for transfer new backgrounds, but methods require higher degree precision than mapping approaches can achieve. Here we present high-resolution genome-wide association analysis identify loci exhibiting patterns large panel more 4500 maize landraces representing breadth genetic diversity Mexico. We evaluate associations between genotype performance 13 common gardens across range environments, identifying hundreds candidate genes underlying environment interaction. further with Mexico show associated yield flowering time our field trials predict independent drought trials. Our results indicate necessary adapt crops changing have been subject ongoing environmental adaptation be identified both phenotypic association.

参考文章(89)
Mirza Hasanuzzaman, Kamrun Nahar, Masayuki Fujita, None, Role of Tocopherol (Vitamin E) in Plants: Abiotic Stress Tolerance and Beyond Emerging Technologies and Management of Crop Stress Tolerance#R##N#Volume 2: A Sustainable Approach. pp. 267- 289 ,(2014) , 10.1016/B978-0-12-800875-1.00012-0
Jesse R. Lasky, Hari D. Upadhyaya, Punna Ramu, Santosh Deshpande, C. Tom Hash, Jason Bonnette, Thomas E. Juenger, Katie Hyma, Charlotte Acharya, Sharon E. Mitchell, Edward S. Buckler, Zachary Brenton, Stephen Kresovich, Geoffrey P. Morris, Genome-environment associations in sorghum landraces predict adaptive traits. Science Advances. ,vol. 1, pp. 1- 13 ,(2015) , 10.1126/SCIADV.1400218
I. Harris, P.D. Jones, T.J. Osborn, D.H. Lister, Updated high‐resolution grids of monthly climatic observations – the CRU TS3.10 Dataset International Journal of Climatology. ,vol. 34, pp. 623- 642 ,(2014) , 10.1002/JOC.3711
H.-Y. Hung, L. M. Shannon, F. Tian, P. J. Bradbury, C. Chen, S. A. Flint-Garcia, M. D. McMullen, D. Ware, E. S. Buckler, J. F. Doebley, J. B. Holland, ZmCCT and the genetic basis of day-length adaptation underlying the postdomestication spread of maize Proceedings of the National Academy of Sciences of the United States of America. ,vol. 109, pp. 11068- 11069 ,(2012) , 10.1073/PNAS.1203189109
Gustavo Dias Almeida, Dan Makumbi, Cosmos Magorokosho, Sudha Nair, Aluízio Borém, Jean-Marcel Ribaut, Marianne Bänziger, Boddupalli M. Prasanna, Jose Crossa, Raman Babu, QTL mapping in three tropical maize populations reveals a set of constitutive and adaptive genomic regions for drought tolerance Theoretical and Applied Genetics. ,vol. 126, pp. 583- 600 ,(2013) , 10.1007/S00122-012-2003-7
Jeffrey C. Glaubitz, Terry M. Casstevens, Fei Lu, James Harriman, Robert J. Elshire, Qi Sun, Edward S. Buckler, TASSEL-GBS: a high capacity genotyping by sequencing analysis pipeline PLOS ONE. ,vol. 9, ,(2014) , 10.1371/JOURNAL.PONE.0090346
Matthew B. Hufford, Enrique Martínez-Meyer, Brandon S. Gaut, Luis E. Eguiarte, Maud I. Tenaillon, Inferences from the Historical Distribution of Wild and Domesticated Maize Provide Ecological and Evolutionary Insight PLoS ONE. ,vol. 7, pp. e47659- ,(2012) , 10.1371/JOURNAL.PONE.0047659
T. Ohgawara, S. Kobayashi, S. Ishii, K. Yoshinaga, I. Oiyama, Fertile fruit trees obtained by somatic hybridization: navel orange (Citrus sinensis) and Troyer citrange (C. sinensis x Poncirus trifoliata). Theoretical and Applied Genetics. ,vol. 81, pp. 141- 143 ,(1991) , 10.1007/BF00215714
Christian Riedelsheimer, Yariv Brotman, Michaël Méret, Albrecht E. Melchinger, Lothar Willmitzer, The maize leaf lipidome shows multilevel genetic control and high predictive value for agronomic traits Scientific Reports. ,vol. 3, pp. 2479- 2479 ,(2013) , 10.1038/SREP02479