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Characterization of adaptation mechanisms in sorghum using a multireference back-cross nested association mapping design and envirotyping
V. Garin, C. Diallo, ML. Tékété, K. Théra, B. Guitton, K. Dagno, AG. Diallo, M. Kouressy, W. Leiser, F. Rattunde, I. Sissoko, A. Touré, B. Nébié, M. Samaké, J. Kholovà, J. Frouin, D. Pot, M. Vaksmann, E. Weltzien, N. Témé, JF. Rami
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články, práce podpořená grantem
Grantová podpora
P500PB_203030
Swiss National Science Foundation - Switzerland
NLK
Free Medical Journals
od 1916 do Před 6 měsíci
Freely Accessible Science Journals
od 1916 do Před 1 rokem
Europe PubMed Central
od 1916 do Před 1 rokem
Open Access Digital Library
od 1916-01-01
Open Access Digital Library
od 1916-01-01
Medline Complete (EBSCOhost)
od 1916-01-01 do Před 1 rokem
PubMed
38381593
DOI
10.1093/genetics/iyae003
Knihovny.cz E-zdroje
- MeSH
- fenotyp MeSH
- jedlá semena genetika MeSH
- lokus kvantitativního znaku MeSH
- mapování chromozomů MeSH
- Sorghum * genetika MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Identifying the genetic factors impacting the adaptation of crops to environmental conditions is of key interest for conservation and selection purposes. It can be achieved using population genomics, and evolutionary or quantitative genetics. Here we present a sorghum multireference back-cross nested association mapping population composed of 3,901 lines produced by crossing 24 diverse parents to 3 elite parents from West and Central Africa-back-cross nested association mapping. The population was phenotyped in environments characterized by differences in photoperiod, rainfall pattern, temperature levels, and soil fertility. To integrate the multiparental and multi-environmental dimension of our data we proposed a new approach for quantitative trait loci (QTL) detection and parental effect estimation. We extended our model to estimate QTL effect sensitivity to environmental covariates, which facilitated the integration of envirotyping data. Our models allowed spatial projections of the QTL effects in agro-ecologies of interest. We utilized this strategy to analyze the genetic architecture of flowering time and plant height, which represents key adaptation mechanisms in environments like West Africa. Our results allowed a better characterization of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod-sensitive and the region of possible candidate gene Elf3 being photoperiod-insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology-dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the West and Central Africa-back-cross nested association mapping and the presented analytical approach constitute unique resources to better understand adaptation in sorghum with direct application to develop climate-smart varieties.
Agronomy Department University of Wisconsin Madison WI 53705 WI USA
CIRAD UMR AGAP Institut Montpellier F 34398 France
Institut d'Economie Rurale Bamako BP 262 Mali
Sorghum Program International Crops Research Institute for the Semi Arid Tropics Bamako BP 320 Mali
UMR AGAP Institut Univ Montpellier CIRAD INRAE Institut Agro Montpellier F 34398 France
Citace poskytuje Crossref.org
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