Synthetic biology for plant genetic engineering and molecular farming.

This review aims to provide a framework for categorizing the different components of synthetic gene circuits, thus facilitating the exchange of DNA parts and information in plant synthetic biology.

/pdf/the-design-of-synthetic-gene-circuits-in-plants-new-2jhuolmd.pdf

The design of synthetic gene circuits in plants: new components, old challenges

Advances in plant synthetic biology approaches to control expression of gene circuits.

Temperature stress is a factor limiting agricultural production in many regions. High and low temperatures can cause irreversible damage to plants, affecting the development and profitability of crops, and are a threat to national and global food security. Raising agricultural outputs by developing elite crop cultivars capable of coping with damaging environmental temperatures is a primary objective of plant breeders. Gene editing systems offer opportunities to rapidly develop improved cultivars. Gene editing has already been applied to several species to improve valuable traits, including yield, quality, nutritional values and tolerance to abiotic and biotic stresses. This review focuses on the recent progress and future potential of gene editing in developing new cultivars with greater heat and cold stress tolerance. 

Gene editing for tolerance to temperature stress in plants: A review

Artificial neural networks, inspired by the biological networks of the human brain, have become game-changing computing models in modern computer science. Inspired by their wide scope of applications, synthetic biology strives to create their biological counterparts, which we denote synthetic biological neural networks (SYNBIONNs). Their use in the fields of medicine, biosensors, biotechnology, and many more shows great potential and presents exciting possibilities. So far, many different synthetic biological networks have been successfully constructed, however, SYNBIONN implementations have been sparse.The latter are mostly based on neural networks pretrained in silico and being heavily dependent on extensive human input. In this paper, we review current implementations and models of SYNBIONNs. We briefly present the biological platforms that show potential for designing and constructing perceptrons and/or multilayer SYNBIONNs. We explore their future possibilities along with the challenges that must be overcome to successfully implement a scalable in vivo biological neural network capable of online learning. 

Synthetic biological neural networks: From current implementations to future perspectives.

CRISPRi-based circuits to control gene expression in plants.

Synthetic gene circuits can enable new cellular behaviours by integrating multiple input signals into customisable genetic programs. However, gene circuit development in plants has been limited by a lack of orthogonal and modular parts required for their construction. Here, we present a tool-kit of reversible CRISPRi-based gene circuits for use in plants. First, we created a range of engineered repressible promoters of different strengths and used them as integrators for the construction of NOT and NOR gates in Arabidopsis cells. Next, we determined the optimal processing system to express sgRNAs from RNA Pol II promoters to introduce NOR gate programmability and interface it with host regulatory sequences. Finally, we connected multiple NOR gates together in layered arrangements to create OR, NIMPLY, and AND logic functions. Our CRISPRi circuits are orthogonal, compact, reversible, programmable, and modular, providing a new platform for sophisticated and deliberate spatio-temporal control of gene expression in plants.

CRISPRi-based circuits for genetic computation in plants

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Gabrielle Herring

Author Tools

Chat about Author

Papers

CRISPRi-based circuits to control gene expression in plants.

CRISPRi-based circuits for genetic computation in plants