scholarly journals BRS 500 B2RF: transgenic cotton cultivar expressing Cry1Ac, Cry2Ab, and CP4-EPSPS with multiple disease resistance

2021 ◽  
Vol 21 (2) ◽  
Author(s):  
Nelson Dias Suassuna ◽  
Camilo de Lelis Morello ◽  
Fabiano José Perina ◽  
João Luís da Silva Filho ◽  
Murilo Barros Pedrosa ◽  
...  
2008 ◽  
Vol 117 (4) ◽  
pp. 531-543 ◽  
Author(s):  
Young-Ki Jo ◽  
Reed Barker ◽  
William Pfender ◽  
Scott Warnke ◽  
Sung-Chur Sim ◽  
...  

Crop Science ◽  
2010 ◽  
Vol 50 (2) ◽  
pp. 458-466 ◽  
Author(s):  
Peter J. Balint-Kurti ◽  
Junyun Yang ◽  
George Van Esbroeck ◽  
Janelle Jung ◽  
Margaret E. Smith

2021 ◽  
Author(s):  
Dinesh Kumar Saini ◽  
Amneek Chahal ◽  
Neeraj Pal ◽  
Puja Srivast ◽  
Pushpendra Kumar Gupta

Abstract In wheat, meta-QTLs (MQTLs), and candidate genes (CGs) were identified for multiple disease resistance (MDR). For this purpose, information was collected from 58 studies for mapping QTLs for resistance to one or more of the five diseases. As many as 493 QTLs were available from these studies, which were distributed in five diseases as follows: septoria tritici blotch (STB) 126 QTLs; septoria nodorum blotch (SNB), 103; fusarium head blight (FHB), 184; karnal bunt (KB), 66, and loose smut (LS), 14. Of these 493 QTLs, only 291 QTLs could be projected onto a consensus genetic map, giving 63 MQTLs. The CI of the MQTLs ranged from 0.04 to 15.31 cM with an average of 3.09 cM per MQTL. This is a ~ 4.39 fold reduction from the CI of initial QTLs, which ranged from 0 to 197.6 cM, with a mean of 13.57 cM. Of 63 MQTLs, 60 were anchored to the reference physical map of wheat (the physical interval of these MQTLs ranged from 0.30 to 726.01 Mb with an average of 74.09 Mb). Thirty-eight (38) of these MQTLs were verified using marker-trait associations (MTAs) derived from genome-wide association studies. As many as 874 CGs were also identified which were further investigated for differential expression using data from five transcriptome studies, resulting in 194 differentially expressed genes (DEGs). Among the DEGs, 85 genes had functions previously reported to be associated with disease resistance. These results should prove useful for fine mapping of MDR genes and marker-assisted breeding.


2012 ◽  
Vol 6 (4) ◽  
pp. 182-194 ◽  
Author(s):  
D. Nyadanu ◽  
R. Akromah ◽  
B. Adomako ◽  
H. Dzahini-Ob ◽  
A.Y. Akrofi ◽  
...  

2019 ◽  
Vol 9 (9) ◽  
pp. 2905-2912 ◽  
Author(s):  
Lais B. Martins ◽  
Elizabeth Rucker ◽  
Wade Thomason ◽  
Randall J. Wisser ◽  
James B. Holland ◽  
...  

2017 ◽  
Vol 107 (9) ◽  
pp. 1055-1061 ◽  
Author(s):  
Katherine Drake-Stowe ◽  
Nicolas Bakaher ◽  
Simon Goepfert ◽  
Berangere Philippon ◽  
Regis Mark ◽  
...  

Phytophthora nicotianae and Ralstonia solanacearum are two of the most important pathogens affecting tobacco worldwide. Greater insight regarding genetic systems controlling resistance to these two soilborne pathogens, as well as identification of DNA markers associated with genomic regions controlling this resistance, could aid in variety development. An evaluation of 50 historical tobacco lines revealed a high positive correlation between resistances to the two pathogens, preliminarily suggesting that some genomic regions may confer resistance to both pathogens. A quantitative trait loci (QTL) mapping experiment designed to investigate the genetic control of soilborne disease resistance of highly resistant ‘K346’ tobacco identified four QTL significantly associated with resistance to P. nicotianae (explaining 60.0% of the observed phenotypic variation) and three QTL to be associated with R. solanacearum resistance (explaining 50.3% of the observed variation). The two QTL with the largest effect on Phytophthora resistance were also found to be the QTL with the greatest effects on resistance to Ralstonia. This finding partially explains previously observed associations between resistances to these two pathogens among U.S. current cultivars and within breeding populations. Further study is needed to determine whether these relationships are due to the same genes (i.e., pleiotropy) or favorable coupling-phase linkages that have been established over time.


Sign in / Sign up

Export Citation Format

Share Document