scholarly journals Development of whole‐genome prediction models to increase the rate of genetic gain in intermediate wheatgrass (Thinopyrum intermedium) breeding

2021 ◽  
Author(s):  
Jared Crain ◽  
Atena Haghighattalab ◽  
Lee DeHaan ◽  
Jesse Poland
2016 ◽  
Vol 38 (4) ◽  
pp. 447 ◽  
Author(s):  
Abbas Atefi ◽  
Abdol Ahad Shadparvar ◽  
Navid Ghavi Hossein-Zadeh

2018 ◽  
Vol 9 ◽  
Author(s):  
Saad Haider ◽  
Michael B. Black ◽  
Bethany B. Parks ◽  
Briana Foley ◽  
Barbara A. Wetmore ◽  
...  

2021 ◽  
Author(s):  
Helgi Hilmarsson ◽  
Arvind S. Kumar ◽  
Richa Rastogi ◽  
Carlos D. Bustamante ◽  
Daniel Mas Montserrat ◽  
...  

ABSTRACTAs genome-wide association studies and genetic risk prediction models are extended to globally diverse and admixed cohorts, ancestry deconvolution has become an increasingly important tool. Also known as local ancestry inference (LAI), this technique identifies the ancestry of each region of an individual’s genome, thus permitting downstream analyses to account for genetic effects that vary between ancestries. Since existing LAI methods were developed before the rise of massive, whole genome biobanks, they are computationally burdened by these large next generation datasets. Current LAI algorithms also fail to harness the potential of whole genome sequences, falling well short of the accuracy that such high variant densities can enable. Here we introduce Gnomix, a set of algorithms that address each of these points, achieving higher accuracy and swifter computational performance than any existing LAI method, while also enabling portable models that are particularly useful when training data are not shareable due to privacy or other restrictions. We demonstrate Gnomix (and its swift phase correction counterpart Gnofix) on worldwide whole-genome data from both humans and canids and utilize its high resolution accuracy to identify the location of ancient New World haplotypes in the Xoloitzcuintle, dating back over 100 generations. Code is available at https://github.com/AI-sandbox/gnomix.


2019 ◽  
Vol 230 ◽  
pp. 103817 ◽  
Author(s):  
Ning Gao ◽  
Jinyan Teng ◽  
Rongyang Pan ◽  
Xiujin Li ◽  
Shaopan Ye ◽  
...  

2019 ◽  
Vol 96 (5) ◽  
pp. 927-936
Author(s):  
Yingxin Zhong ◽  
Juan Mogoginta ◽  
Joseph Gayin ◽  
George Amponsah Annor

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Sophie Held ◽  
Catrin E. Tyl ◽  
George A. Annor

Cold plasma is an emerging technology to improve microbiological safety as well as functionality of foods. This study compared the effect of radio frequency cold plasma on flour and dough properties of three members of the Triticeae tribe, soft as well as hard wheat (Triticum aestivum L.) and intermediate wheatgrass (Thinopyrum intermedium, IWG). These three flour types differ in their protein content and composition and were evaluated for their solubility, solvent retention capacity, starch damage, GlutoPeak and Farinograph profiles, and protein secondary structures. Plasma treatment resulted in dehydration of flours but did not change protein content or solubility. Farinograph water absorption increased for all flours after plasma treatment (from 56.5–61.1 before to 71.0–81.6%) and coincided with higher solvent retention capacity for water and sodium carbonate. Plasma treatment under our conditions was found to cause starch damage to the extent of 3.46–6.62% in all samples, explaining the higher solvent retention capacity for sodium carbonate. However, Farinograph properties were changed differently in each flour type: dough development time and stability time decreased for hard wheat and increased for soft wheat but remained unchanged in intermediate wheatgrass. GlutoPeak parameters were also affected differently: peak torque for intermediate wheatgrass increased from 32 to 39.5 GlutoPeak units but was not different for the other two flours. Soft wheat did not always aggregate after plasma treatment, i.e., did not aggregate within the measurement time. It was also the only flour where protein secondary structures were changed after plasma treatment, exhibiting an increase from 15.2 to 27.9% in β-turns and a decrease from 59.4 to 47.9% in β-sheets. While this could be indicative of a better hydrated gluten network, plasma-treated soft wheat was the only flour where viscoelastic properties were changed and extensibility decreased. Further research is warranted to elucidate molecular changes underlying these effects.


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