Identification of SSR markers associated with saccharification yield using pool-based genome-wide association mapping in sorghum

Genome ◽  
2011 ◽  
Vol 54 (11) ◽  
pp. 883-889 ◽  
Author(s):  
Yi-Hong Wang ◽  
Durga D. Poudel ◽  
Karl H. Hasenstein

Saccharification describes the conversion of plant biomass by cellulase into glucose. Because plants have never been selected for high saccharification yield, cellulosic ethanol production faces a significant bottleneck. To improve saccharification yield, it is critical to identify the genes that affect this process. In this study, we used pool-based genome-wide association mapping to identify simple sequence repeat (SSR) markers associated with saccharification yield. Screening of 703 SSR markers against the low and high saccharification pools identified two markers on the sorghum chromosomes 2 (23-1062) and 4 (74-508c) associated with saccharification yield. The association was significant at 1% using either general or mixed linear models. Localization of these markers based on the whole genome sequence indicates that 23-1062 is 223 kb from a β–glucanase (Bg) gene and 74-508c is 81 kb from a steroid-binding protein (Sbp) gene. Bg is critical for cell wall assembly and degradation, but Sbp can suppress the expression of Bg as demonstrated in Arabidopsis (Yang et al. 2005). These markers are found physically close to genes encoding plant cell wall synthesis enzymes such as xyloglucan fucosyltransferase (149 kb from 74-508c) and UDP-d-glucose 4-epimerase (46 kb from 23-1062). Genetic transformation of selected candidate genes is in progress to examine their effect on saccharification yield in plants.

2011 ◽  
Vol 30 (1) ◽  
pp. 281-292 ◽  
Author(s):  
Yi-Hong Wang ◽  
Paul Bible ◽  
Rasiah Loganantharaj ◽  
Hari D. Upadhyaya

PLoS ONE ◽  
2017 ◽  
Vol 12 (3) ◽  
pp. e0173313 ◽  
Author(s):  
Andrea Bellucci ◽  
Alessandro Tondelli ◽  
Jonatan U. Fangel ◽  
Anna Maria Torp ◽  
Xin Xu ◽  
...  

3 Biotech ◽  
2021 ◽  
Vol 11 (5) ◽  
Author(s):  
Kumari Shikha ◽  
J. P. Shahi ◽  
M. T. Vinayan ◽  
P. H. Zaidi ◽  
A. K. Singh ◽  
...  

2017 ◽  
Vol 77 ◽  
pp. 211-218 ◽  
Author(s):  
Jieyun Li ◽  
Awais Rasheed ◽  
Qi Guo ◽  
Yan Dong ◽  
Jindong Liu ◽  
...  

Genomics ◽  
2019 ◽  
Vol 111 (6) ◽  
pp. 1794-1801 ◽  
Author(s):  
Nathanael Fickett ◽  
Andres Gutierrez ◽  
Mohit Verma ◽  
Michael Pontif ◽  
Anna Hale ◽  
...  

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Susan R. McCouch ◽  
Mark H. Wright ◽  
Chih-Wei Tung ◽  
Lyza G. Maron ◽  
Kenneth L. McNally ◽  
...  

Abstract Increasing food production is essential to meet the demands of a growing human population, with its rising income levels and nutritional expectations. To address the demand, plant breeders seek new sources of genetic variation to enhance the productivity, sustainability and resilience of crop varieties. Here we launch a high-resolution, open-access research platform to facilitate genome-wide association mapping in rice, a staple food crop. The platform provides an immortal collection of diverse germplasm, a high-density single-nucleotide polymorphism data set tailored for gene discovery, well-documented analytical strategies, and a suite of bioinformatics resources to facilitate biological interpretation. Using grain length, we demonstrate the power and resolution of our new high-density rice array, the accompanying genotypic data set, and an expanded diversity panel for detecting major and minor effect QTLs and subpopulation-specific alleles, with immediate implications for rice improvement.


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