May 13, 2013
Source: National University of Ireland, Galway via AlphaGalileo
Scientists have developed techniques for the genetic improvement of sunflowers using a non-GMO based approach. The new technology platform can harness the plant’s own genes to improve characteristics of sunflower, develop genetic traits, which will improve its role as an important oilseed crop. The work was led by Dr Manash Chatterjee, an Adjunct Faculty member of Botany and Plant Science at NUI Galway, and has been published in the journal BMC Plant Biology.
Among oilseed crops, sunflowers are one of the most important sources of edible vegetable oil for human consumption worldwide. Sunflower and other oilseed crops are the source of the vast majority of vegetable oil used for cooking and food processing. The oils are also for industrial processes such as making soaps, cosmetics, perfumes, paints and biofuels.
Dr Chatterjee is currently a Science Foundation Ireland (SFI) ETS Walton Fellow at NUI Galway, collaborating with the SFI Genetics and Biotechnology Lab of Professor Charles Spillane. Dr Chatterjee’s research uses an approach called TILLING (Targeting Induced Lesions In The Genome), an established non-GM method for creating and discovering new traits in plants.
According to Dr Chatterjee: “Over the centuries, the sunflower has been cultivated for traits such as yield. However, along the way many useful genetic variations have been lost. This new technology allows us to pinpoint key genetic information relating to various useful traits in the sunflower, including wild sunflower species. It gives us a method to quickly create variability for further breeding to enhance the quantity, quality and natural performance of the crop. In this era of increasing global food crisis and changing climatic regimes, such ability is highly desirable.”
The research breakthrough was part of a collaborative project between Bench Bio (India), URGV Lab INRA (France), NUI Galway Plant and AgriBiosciences Research Centre (Ireland) and Advanta Seeds Argentina. NUI Galway PhD student Anish PK Kumar has been working on the technology platform development as a component of his PhD research studies.
Dr Chatterjee is also involved in research in the NUI Galway Plant and AgriBiosciences Research Centre (PABC) to improve the bioenergy crop Miscanthus. Also known as elephant grass, miscanthus is one of a new generation of renewable energy crops that can be converted into renewable energy by being burned in biomass power stations.
SMART – Sunflower Mutant population And Reverse genetic Tool for crop improvement
Anish PK Kumar, Adnane Boualem, Anjanabha Bhattacharya, Seema Parikh, Nirali Desai, Andres Zambelli, Alberto Leon, Manash Chatterjee, Abdelhafid Bendahmane
BMC Plant Biology 2013, 13:38 (5 March 2013)
Sunflower (Helianthus annuus L.) is an important oilseed crop grown widely in various areas of the world. Classical genetic studies have been extensively undertaken for the improvement of this particular oilseed crop. Pertaining to this endeavor, we developed a “chemically induced mutated genetic resource for detecting SNP by TILLING” in sunflower to create new traits.
To optimize the EMS mutagenesis, we first conducted a “kill curve” analysis with a range of EMS dose from 0.5% to 3%. Based on the observed germination rate, a 50% survival rate i.e. LD50, treatment with 0.6% EMS for 8 hours was chosen to generate 5,000 M2 populations, out of which, 4,763 M3 plants with fertile seed set. Phenotypic characterization of the 5,000 M2 mutagenised lines were undertaken to assess the mutagenesis quality and to identify traits of interest. In the M2 population, about 1.1% of the plants showed phenotypic variations. The sunflower TILLING platform was setup using Endo-1-nuclease as mismatch detection system coupled with an eight fold DNA pooling strategy. As proof-of-concept, we screened the M2 population for induced mutations in two genes related to fatty acid biosynthesis, FatA an acyl-ACP thioesterase and SAD the stearoyl-ACP desaturase and identified a total of 26 mutations.
Based on the TILLING of FatA and SAD genes, we calculated the overall mutation rate to one mutation every 480 kb, similar to other report for this crop so far. As sunflower is a plant model for seed oil biosynthesis, we anticipate that the developed genetic resource will be a useful tool to identify novel traits for sunflower crop improvement.