Bản tin chủ nhật 4-9-2022
Bản tin chủ nhật 4-9-2022
Bản tin số 1
Enhanced Green Fluorescent Marker Effective in Transforming Grapes Using CRISPR
CRISPR-Cas9-mediated genome editing in grapes was first reported in 2016. With the increasing interest in using this new breeding technique in grapes, scientists from the Chinese Academy of Sciences evaluated genome editing in grapes using newly developed CRISPR-based tools such as the CRISPR/LbCpf1 system to increase existing evidence that gene editing tools are useful in improving the crop.
The scientists evaluated four different markers and found that the Enhanced Green Fluorescent Protein  (EGFP) was not harmful to grape cells, but its signal was not easily detected. Scientists then used EGFP and RUBY, another marker, to help screen transformed grape cells based on fluorescence and red betalain. They then tested the activities of CRISPR/LbCpf1, CRISPR-Cas9, and cytidine base editor. Further examination revealed that using the CRISPR/LbCpf1 with the aid of the EGFP marker is effective in generating targeted mutagenesis in grapes and is capable of editing multiple targets simultaneously using only a single crRNA array. The scientists also noted that elevated temperature could improve the activity of the CRISPR/LbCpf1 in grapes.
The study provides evidence that can be used for further gene editing research on grapes.
Read the pre-print of the publication in bioRxiv.
Bản tin số 2
CRISPR Market Size to Reach US$3.73B by 2032
In 2021, the CRISPR/CRISPR-associated genes market was valued at US$1.56 billion. With a compound annual growth rate (CAGR) of 16.67%, the market is expected to reach US$3.73 billion by 2032, reported.
CRISPR has a wide array of applications, particularly for genome editing. Its popularity has increased over the years since its discovery as a tool in genetics. Since then, CRISPR has been driving developments in genome editing across medicine and biotechnology.
The market growth is attributed to the increasing investments by biotechnology companies and non-profit entities in research and developmental initiatives. The primary drivers are the pharmaceutical and biopharmaceutical industries.
Read the original article from Eturbo or download the report from to know more.
Assessing the response to genomic selection by simulation
Theoretical and Applied Genetics August 2022; vol. 135: 2891–2905
Key message
We propose a simulation approach to compute response to genomic selection on a multi-environment framework to provide breeders the number of entries that need to be selected from the population to have a defined probability of selecting the truly best entry from the population and the probability of obtaining the truly best entries when some top-ranked entries are selected.Abstract
The goal of any plant breeding program is to maximize genetic gain for traits of interest. In classical quantitative genetics, the genetic gain can be obtained from what is known as “Breeder’s equation”. In the past, only phenotypic data were used to compute the genetic gain. The advent of genomic prediction (GP) has opened the door to the utilization of dense markers for estimating genomic breeding values or GBV. The salient feature of GP is the possibility to carry out genomic selection with the assistance of the kinship matrix, hence improving the prediction accuracy and accelerating the breeding cycle. However, estimates of GBV as such do not provide the full information on the number of entries to be selected as in the classical response to selection. In this paper, we use simulation, based on a fitted mixed model for GP in a multi-environmental framework, to answer two typical questions of a plant breeder: (1) How many entries need to be selected to have a defined probability of selecting the truly best entry from the population; (2) what is the probability of obtaining the truly best entries when some top-ranked entries are selected.
Figure 1: The structure of selection cycles in the rye hybrid breeding program. The number of entries decreases due to selection in each GCA trial. In each cycle, inbred lines are crossed with two testers of the opposite gene pool
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