RNA clay offers green alternative to plant pesticides

By Neena Bhandari

A nano-sized bio-degradable clay-comprising double stranded ribonucleic acid (dsRNA) could offer a cost-effective, clean and green alternative to chemical-based plant pesticides.

Australian researchers from the University of Queensland have successfully used a gene-silencing spray, named BioClay, a combination of biomolecules and clay, to protect tobacco plants from a virus for 20 days with a single application. Their study has been published in Nature Plants.

“When BioClay is sprayed onto a plant, the virus-specific dsRNA is slowly released from the clay nanosheets into the plant. This activates a pathway in the plant that is a natural defence mechanism. The dsRNA is chopped up into small bits of RNA by enzymes of this pathway. These small bits attack the virus when it infects the plant without altering the plant genome,” explains lead researcher, Neena Mitter.

“Even with current pesticides, we lose up to 40 per cent of our crop productivity because of pests and pathogens. We are hoping that having BioClay in the mix as an environmentally friendly, sustainable crop protection measure will reduce crop losses,” Mitter adds.

“The clay-based delivery technology could represent a positive inflection point in the progress towards commercialisation of topical RNAi. This is a non-GM, environmentally benign and very specific technology.”

 John Killmer, APSE

While chemical-based pesticides kill the targeted insect, they can also affect a range of other insects that are beneficial. Mitter says, “BioClay is specific and it only kills the pathogen being targeted. Currently farmers use insecticides to kill the vector that comes with the viruses, but with BioClay we can target the virus itself.”

BioClay field trials may begin in Australia by year-end. “The first test will be on a virus that infects vegetable crops — capsicum, tomato, chilli,” Mitter tells SciDev.Net.

Farmers can use the existing equipment to deliver BioClay and the researchers are hopeful that it will be a commercially viable product for farmers everywhere. The clay component is cheap to make, but not the RNA.

Several companies like APSE, a US based startup, are working on the mass production of RNAs. APSE is developing RNA manufacturing technology for RNA interference (RNAi) or gene silencing applications.

“Our technology for RNA production should be ready in 2-3 years. We are targeting US$2 per gram,” APSE’s John Killmer tells SciDev.Net.

Killmer says, “The clay-based delivery technology could represent a positive inflection point in the progress towards commercialisation of topical RNAi. This is a non-GM, environmentally benign and very specific technology.”

RNAi technology is being used by many in the agriculture industry including the biotech firm Monsanto. The company’s BioDirect technology is focused on applications of RNAi directly onto the leaves of a plant.

Monsanto’s spokesperson John Combest tells SciDev.Net, “As insects develop resistance to certain classes of pesticides, giving farmers another option to control these pests is critical. The idea is not to replace any given system of farming, whether modern GM systems or others — it’s to provide farmers with products that can complement or replace agricultural chemical products.”

This piece was produced by SciDev.Net’s Asia & Pacific desk.

 

This article was originally published on SciDev.Net. Read the original article.

Mother grain genome: insights into quinoa

Sales of quinoa (Chenopodium quinoa) have exploded in the last decade, with prices more than tripling between 2008 and 2014. The popularity of this pseudocereal comes from its highly nutritious seeds, which resemble grains and contain a good balance of protein, vitamins, and minerals. The nourishing nature of quinoa meant it was prized by the Incas, who called it the “Mother grain”.

Quinoa

Quinoa is a popular ‘grain’, but it is more closely related to spinach and beetroot than cereals like wheat or barley. Image credit: Flickr user. Used under license: CC BY 2.0.

Quinoa is native to the Andes of South America, where it thrives in a range of conditions from coastal regions to alpine regions of up to 4000 m above sea level. Its resilience and nutritious seeds means that quinoa has been identified as a key crop for enhancing food security, but there are currently very few breeding programs targeting this species.

The challenge of improving the efficiency and sustainability of quinoa production has so far been restricted by the lack of a reference genome. This week, a team of researchers led by Professor Mark Tester (King Abdullah University of Science & Technology; KAUST) addressed this issue, publishing a high-quality genome sequence for quinoa in Nature. They compared the genome with that of related species to characterize the evolution and domestication of the crop, and investigated the genetic diversity of economically important traits.

 

The evolution of quinoa

Tester and colleagues used an array of genomics techniques to assemble 1.39 Gb of the estimated 1.45-1.50 Gb full length of quinoa’s genome. Quinoa is a tetraploid, meaning it has four copies of each chromosome. The researchers shed light on the evolutionary history of this crop by sequencing descendants of the two diploid species (each containing two sets of chromosomes) that hybridized to generate quinoa; kañiwa (Chenopodium pallidicaule) and Swedish goosefoot (Chenopodium suecicum). Comparing these sequences to quinoa and other relatives, the team showed that the hybridization event likely occurred between 3.3 and 6.3 million years ago. A comparison with other closely related Chenopodium species also suggested that, contrary to previous predictions, quinoa may have been domesticated twice, both in highland and coastal environments.

Quinoa field

Quinoa field. Image credit: LID. Used under license: CC BY-SA 2.0.

 

Washing away quinoa’s bitter taste

Quinoa seeds are coated with soap-like chemicals called saponins, which have a bitter taste that deters herbivores. Saponins can disrupt the cell membranes of red blood cells, so they have to be removed before human consumption, but this process is costly, so quinoa breeders are always looking for varieties that produce lower levels of saponins.

Sweet (low-saponin) quinoa strains do occur naturally, but the genes that regulate this phenotype were previously unknown. Tester and colleagues investigated sweet and bitter quinoa strains and discovered that a single gene (TRITERPENE SAPONIN BIOSYNTHESIS ACTIVATING REGULATOR-LIKE 1 [TSARL1]) controls the amount of saponins produced in the seeds. The low-saponin quinoa strains contained mutations in TSARL1 that prevented it from functioning properly. This is a key target for the improvement of quinoa in the future, although farmers will have to find new ways to protect their crops from birds and other seed predators!

Quinoa flowers

Quinoa flowers. Image credit: Alan Cann. Used under license: CC BY-SA 2.0.

 

Quality quinoa

The high-quality reference genome for quinoa generated by Tester and colleagues is likely to be vital for allowing many exciting improvements in the future. Breeders hoping to improve the yield, ease of harvest, stress tolerance, and saponin content of quinoa can develop genetic markers to speed up breeding for these key traits, improving the productivity of quinoa varieties and enhancing future food security.

 


Read the paper in Nature: Jarvis et al., 2017. The genome of Chenopodium quinoa. Nature. DOI: 10.1038/nature21370

Thank you to Professor Mark Tester (KAUST) for providing information used in this post!

The future of phenotyping

This week’s post was written by Dr Kasra Sabermanesh, Rothamsted Research.

I am a post-doctoral research scientist within Rothamsted Research’s BBSRC-funded 20:20 Wheat® program, which aims to provide the knowledge base and tools to increase the UK wheat yield potential from 8.4 to 20 tons of wheat per hectare within the next 20 years. Field phenotyping is one component of this program and facilitates the non-destructive monitoring of field-grown crops. Traditional methods of field phenotyping require huge human effort, which consequently limits the accuracy, frequency, and number of different measurements that can be taken at one time. Fortunately, Rothamsted has an exciting solution to this problem.

The Field Scanalyzer

Kasra Sabermanesh

Dr Kasra Sabermanesh shows off the Field Scanalyzer. Image credit: Rothamsted Research

Our field phenotyping platform, the Field Scanalyzer (constructed by LemnaTec GmbH and being further developed by ourselves), supports a motorized measuring platform with multiple sensors that can be accurately positioned anywhere within a dedicated field. The sensor array comprises a high-definition RGB camera, two hyperspectral cameras, a thermal infrared camera, a system for imaging chlorophyll fluorescence and twin scanning lasers for 3D information capture. Together, these sensors generate a wealth of data about crop growth, architecture, performance, and health. The Field Scanalyzer operates autonomously and in high-throughput, meaning it can take a lot of non-destructive measurements without human supervision, throughout the crops lifecycle, with high-accuracy and reproducibility. (You can read more about the Field Scanalyzer in our recent paper: http://www.publish.csiro.au/FP/pdf/FP16163).

We are currently using the Field Scanalyzer to identify new characteristics of crops that relate to performance, as well as identifying new genetic diversity for existing traits. Outputs from either of these research components can be delivered to breeders. We are screening approximately 400 wheat varieties, but also imaging some oilseed rape and oat plants.

Rothamsted Research

The scanalyzer. Image credit: Rothamsted Research

The big data problem

The Field Scanalyzer at Rothamsted is a world first, so we initially had to develop all the necessary image acquisition protocols and image processing tools, in order to exploit its full capabilities. A number of image processing tools are available; however, they are not suitable for field-grown crops, as they were not developed for complex canopies consisting of hundreds of plants in highly dynamic ambient conditions. The platform can generate up to 100 TB data with a year’s continuous operation (using all of the sensors). That’s why I work with two other post-docs to develop robust computer vision tools to automate the way we extracting quantitative image datasets. We are also validating the accuracy of the values extracted from our images by comparing them with measurements obtained manually.

Approximately 1.5 years have passed since we first began operating the Field Scanalyzer, and we have now optimized all of our image acquisition protocols and have collected a full seasonal dataset. With the good quality images stored in our database, we have developed some robust tools to automatically extract the information about some key growth stages (ear emergence and flowering), as well as quantifying height and the number of some plant organs. We are still just scraping the surface though, and have a list of traits for which we want to develop computer vision tools, in order to automatically analyze them.

Take to the skies: Drones for data collection

Some of my colleagues work with drones (UAVs) to capture information about crop height, plant density (Normalized Difference Vegetation Index), and canopy temperature from large-scale field trials containing 5000 plots. They also fly the UAVs over our Field Scanalyzer site, so we can compare data collected from the higher flying UAV with those collected from the Field Scanalyzer at close proximity. The way we see it, UAVs can image large fields in a very short time (15 min), so if we notice something interesting using the UAV at the large plot-scale, we can put the material under the Field Scanalyzer for high-resolution phenotyping. On the other hand, with the Field Scanalyzer, once we gain a better understanding of which trait/s we need to focus on, when we should be looking at them, and exactly which sensor/s are required to quantify the trait, we can deploy drones with the necessary sensors (once the sensors are portable enough) to collect this information at field-scale and at the appropriate time.

Drones at Rothamsted

Taking to the skies: Drones are used for large-scale phenotyping at Rothamsted. Credit: Rothamsted Research.

The future of phenotyping

I envision that the future of phenotyping technology will focus on reducing the cost and size of cameras/sensors, ultimately increasing their portability and accessibility. This will result in more sophisticated cameras being attached to UAVs (as many of sensors we currently use far out-weigh a UAV’s payload). Parallel to this, research efforts are focusing on developing image processing systems that efficiently extract quantitative information about the crops from acquired images. Together, phenotyping systems such as low-flying UAVs that generate easily interpreted data outputs could be developed, which may be more widely adopted by breeders and farmers to get a deeper insight into their crop’s health and performance.