Marco Papageorgiou

2016 involving the public sector on improved crop varieties, and supporting local, and private seed companies that spans markets and value chains. Genomics-Centric Approach: An Insight into the Role of Genomics in Assisting GM-rice Varieties. Cultivated rice (Oryza sativa) (Caicedo et al., 2007), as one crucial crop responsible for feeding around 50% of the population (Wang et al., 2016), and providing 20% of the worlds caloric intake and over 50% in Asian countries (Caicedo et al., 2007), is cultivated across the world on available arable land (Cao et al., 2016). It has been calculated that by 2035, 116 million tons of rice production, globally, will need to be met (Yamano et al., 2016). This increase will need to be from smallholder farmers in developing countries. Currently, there exists two cultivated species of rice, along with 22 wild species (Anacleto et al., 2015). Authors: Marco Papageorgiou Introduction With an increasing demand for food throughout the developed and developing world improved approaches of identifying and utilising rice genes, along with modifying existing ones involved in abiotic stress, should be more associated to a reliance of genomic tools. This demand for applying improved, and better resolving, genomic tools will need to coincide with an unprecedented population growth to 9 billion people (Schaart et al., 2016), which will also signal a need to produce 70-100% more food by 2050 (Schaart et al., 2016). In particular, the FAO in their recent 2016 report developed a likelihood of scenario outcomes (FAO, 2016) based on food price increases. In four climate change scenarios of low population growth and high income, it was predicted that by 2050 projected mean price increase of 31% for rice alone (FAO, 2016). The presently occurring shift in global climate will undoubtedly impact agriculture (Batley et al., 2016). The relationship between relevant climate-linked traits and crop diversity can be adequately linked to genomics (Edwards 2016). Additionally, the mapping and characterisation of eventual SNPs in rice climatelinked QTL regions can allow an insight into the molecular and biochemical basis of their expression profiles (Edwards 2016), which can be used to predict phenotype. Overall, the essential mapping of rice genes modelled within future climatic shifts, can prime genetic engineering approaches which can produce GM-rice varieties with strengthened traits to cope with an everchanging global environment. These climate impacts, namely abiotic stresses, pest and disease outbreaks, from the overall affect of climate change, projected to considerably effect rice yields in tropical regions than temperate regions (FAO, 2016), will require careful stitching of new rice crop varieties (Batley et al., 2016). The FAO: Save and Grow guidelines detail, and address, the need of improved crop varieties. Looking specifically at Chatter 4, Crops and varieties, the report clearly highlights the need to prioritise sustainable crop production intensification (SCRI). They report stresses the need to increase genetic diversity of crop species in order to evade climate change outcomes such as those posing abiotic stresses, whilst at the same time improving adaptability. What is interesting is that the Save and Grow guidelines for improving crop varieties is also geared towards increasing farmer participation, 1! of 17 ! 2016 One goal of abiotic stress research in rice is to improve its characteristics via the method of diversification (Brozynska et al., 2016). It has been suggested that the use of crop wild relatives (CWRs) can support the building strengthened rice varieties (Brozynska et al. 2016). Since crop wild-relatives might be less variable from a lack of human selection parameters, they nonetheless contain a broad range of exploitable traits (Hamblin et al., 2011) which can be screened using GWAS and GS. harmonise aspects of current rice genomics with food security/guidelines outlined in the recent 2016 FAO report, The State of Food and Agriculture, will also be discussed. This section will also bring into light the issues surrounding trade, commercialisation, policy, and industry relevance and responsibility, from a postgenomics era viewpoint. Along with these insights, the review suggests a genomic-centric perspective that seeks to recommend strategies to appropriately consider GM-rice varieties, and the paramount adaption to future shifting climate, that will lead to strengthened food security. Genomics is leading the way in rice crop research, by: a) Providing a platform to discover the ongoing effects of climate change on rice varieties through re-sequencing; b) Enabling a larger pool of genes from CWR to be determined, and utilised, in downstream genetic engineering processes; c) Providing a strong scientific knowledge-base for the seed industry (SMEs and government agencies) that can also assist in developing new agricultural guidelines catering for GM-rice, and, d) Efficiently storing and re-using known rice germplasm/genotypes which can efficiently streamline the processes of creating new GM-rice varieties which can withstand predicted climate shifts; shortening the lag time between climate-induced abiotic stress to elite rice variety engineering. This perspective and mini-review will firstly explain the brief background of some NGS-genomics strategies, discussing their likely impacts on creating new rice varieties. Genomics will then be explained within a context of climate change and food security, exemplified from using the major staple crop, rice. Lastly, a discussion on the aspects and difficulties of commercialising new elite GM-rice varieties along with the inclusion and discussion of current FAO assessments, and other authorised agricultural documents will be mentioned. Frameworks that 2! of 17 ! 2016 Genomic tools used in rice Improvement Thus, NGS technologies have allowed entire genomes to be annotated for agronomically-valuable traits based on precise nucleotide positions. Additionally, reverse genetics techniques such as Eco-TILLING have also been developed for use in discovering drought and salinity tolerant genes (Varshney et al., 2014) in economically important crops, such as rice. Precise selection of multiple traits can be uncovered using present day genomics (Godfray et al., 2010). Uncovering such genetic information relating to agronomically important crop traits represents a critical step in understanding phenotypic variation which can lead to improving crops (Yano et al., 2016), along with a better understanding of abiotic stress effects on developing varieties well-suited to handle difficult environments (Godfray et al., 2010). With widely-used Next Generation Sequencing (NGS) approaches and its association with sequencing large populations, heightening the resolution of QTL discovery, and uncovering SNP markers for plant crop analysis (Varshney et al., 2014), many biological hypotheses have nowadays become open for further investigation (Rossetto et al., 2014). Genomics-assisted breeding represents a a range of holistic approaches (Varshney et al., 2009) wherein a phenotype can be predicted from a genotype from the incorporation of genomic analysis. Furthermore, the application of a GWAS (genome-wide association studies) (Hamblin et al., 2011) and Genome-sequencing (GS) will greatly improve mapping resolution and genetic diversity data, as it efficiently identifies a magnitude of allelic variations (Yano et al., 2016) through nucleotide polymorphisms, and the subsequent variability in phenotypes (Yano et al., 2016). Genotyping-by-Sequencing (GBS) is an offshoot of NGS wherein plant populations can be genotyped for their SNP attributes (Edwards 2016). Zhao et al., (2010) used a genome-wide SNP analysis to study polymorphism patterns in 395 rice accessions. The study analysed amylose content and grain length to uncover complex traits, and genetic elements that were functionally important, based on their population genetics approaches using the SNPs (Zhao et al., 2010). Marker-assisted selection (MAS) tools that can specifically investigate the basis of genetic variations in rice (Wang et al., 2016) will require further application in order to characterise the other >37, 000 protein coding genes in its genome (Wang et al., 2016). Genomics-assisted breeding (Varshney et al., 2014) represents an effective approach that can decode rice crop traits from seedling stage, and potentially eliminate multi-location trials, without the lengthy process of phenotypic evaluation over stretches of time. Wedged between full-length cDNA sequence data and functional genomics is the highly crucial role of DNA microarray technology (Rabbani et al., 2003). The imperativeness of DNA microarray applications lies in its utilisation in comparative experimentation. Its yielding transcript data reveals vital information that can indicate gene expression (Rabbani et al., 2003) based upon the experimental/abiotic pressure in question. Discrepancies between microarray data and gel-based analyses is a major drawback to the validity and accuracy of applying this approach to derive plant transcriptomic data. Prior to the popularity of NGS technologies, a limitation with the number of available markers necessary for marker-breeding strategies was a barricade that disqualified the identification of valuable agronomic traits outside continuously utilised genomic regions (Varshney et al., 2014). 3! of 17 ! 2016 investigated, and exploited, through the use of genomics approaches. The overall adoption of genomics to its application within a crop improving context will open new pathways which will lead to discoveries and produce data based on; 1) Screening crop communities from varying environmental climates; 2) Comparing the results of improved heterozygosity, heterosis, and its impacts on crop domestication; 3) Developing new, or improving existing molecular, techniques that can derive important patterns and processes at the plant- and community-level which can subsequently provide relevant bio-marker data (Rossetto et al., 2014). Genomics offers the capacity to not only uncover these unknown genes and/or gene regions, but also to facilitate further downstream developmental processes that could determine physiological traits for improved crop resilience to abiotic stresses, at the whole crop level. Thus, the aim of research in this post-genomic era is to identify the functions of these unknown genes (Rabbani et al., 2003) that could further be available throughout online public databases. By assessing SNPs conferring changes at the gene level from external pressures such as drought and/or heat stress, a gradual building of enhanced holistic crop-models can be developed fusing biological changes happening at the gene/biochemical level to providing detailed information on rice-climate interactive responses at the whole-crop level. In a study that utilised chloroplast sequence data, Brozynska et al., (2014) were able to uncover 122 polymorphisms in a wild rice relative, matching this to a reference cultivated rice genome. This chloroplast barcoding approach can be further applied to GM-rice varieties, which will be discussed in the next section accordingly, along with possibly eliminating amplification steps that would otherwise interfere with genotypes (Brozynska et al., 2014) from different plants. Another example of whole chloroplast gene sequencing is described by Wambugu et al., 2015. In their study, the evolutionary and phylogenetic relationships of the AA Oryza genome generated a primary gene pool that allowed the authors to conclude relationships between cultivated and wild rice relatives, and potentially exploit these wild genetic resources for rice improvement (Wambugu et al., 2015). In order to mine for existing and new functional traits in rice, which can be utilised in cultivar improvement such as improving yield, drought tolerance, and/or synthesising heat tolerant lines, statistical models used in GWAS and GS would be required to explain, for example, population history more accurately. Genomic resources that pertain to QTL linked to drought-tolerant rice are crucial in climate-resilient lines (Vikram et al., 2016), however their trait complexities are hampered by genetic linkages and interactions. Vikram et al., (2016) described the possibility of linkages between QTLs from flowering and plant height, to drought-grain QTLs. They subsequently utilised a marker-assisted approach to infer improve grain yield under drought street conditions. These approaches should also screen for consumerfriendly factors/genes such as those associated with sensory attributes (Anacleto et al., 2015), for example fragrance, along with cooking characteristics, such as the amylose content (Bradbury et al., 2008). Both fragrance and amylose content are also important characteristics which influence consumer choice. Depending on the consumer preference in question, selecting sensory and physical attributes is an interesting aspect of rice quality that can be 4! of 17 ! 2016 Exploratory genomic techniques applied to rice draft genomes can help identify functional elements in noncoding DNA regions (Joly-Lopez et al., 2016), along with characterising genome-wide SNPs in rice. Fitness maps (Joly-Lopez et al., 2016) provide mutationvariation data and estimate probability functions which help determine the effect of that mutation within a crop-genome context. Continually working towards, and within, a bioinformational framework of uncovering genetic data will nonetheless facilitate a growing number of virtuallaboratory based scientists that will need to better handle this incoming informatic data. This can only occur if genomics-based approaches can simultaneously manage and interpret incoming genomic datasets. Genomics based breeding is becoming more popular as ongoing genomic discoveries are made. The ability to genotype an abundance of SNPs, in breeding new rice varieties, has led to more accurate marker-assisted trait selection providing improved genome coverage of commercially vital stable crops, such as rice. If a more defined genomics pipeline is applied, identifying consumer-/climate- important traits for consumer preference and climate mitigation, a reduction in rice breeding costs will be apparent in the near future. Overall, the continuing use of NGS technologies, especially those associated with genomics data mining and processing, will allow for a much better characterised trait-pool from crop gene resources. For example, the application of NGS to sequence total plant DNA can lead to chloroplast barcoding (Brozynska et al., 2014), which can in turn accommodate the streamlined plant identification from an apparent diversity-lacking across closely related plant species (Li et al., 2014). Table 1: Save and Grow recommended measures (SCPI) taken from Chapter 4 of the Save and Grow guidelines, with relevant genomics inputs aligned. Sustainable crop production intensification NGS technologies will also permit perviously undefined and neglected gene banks to become utilised by plant breeders. This should be aligned with the FAO’s Save and Grow guidelines, mentioned in the beginning of this article. Table 1 describes this alignment through matching genomics approaches with the Save and Grow: The Way Forward key points of consideration. These genomics-FAO matches could support further policy formulation by interested policymakers. 5! of 17 ! Measures Genomics-derived approaches Strengthening linkages between the conservation of PGR and the use of diversity in plant breeding Providing genomics databases to store and utilise large datasets Increasing the participation of farmers in conservation, crop improvement and seed supply Educating smallholder farmers in genomic-platform technologies and opportunities with communication of riskassessments Improving policies and legislation for variety development and release, and seed supply Integrating genomics technologies into policy-maker decisions that can rationally lead legislation into adopting NGS approaches as standardised methods for developing elite varieties; based on the intended design and its purpose within a climate-mitigating context. Strengthening capacity: creating skill workers to assist enhanced breeding Training skilled workers in matters regarding land intensification and additional benefits of using GM-varieties from genomics-derived been pools. Revitalising public sector: expanding its roles in developing new crop varieties Investing into the development of improved NGS platforms; funding research centres into NGS research. Supporting the emergence of local, private sector seed enterprises Using genomics-based modelling, from a climatechange perspective, to explain economical advantages, ROI, and human well-being, from developing SME opportunities. 2016 Coordinating linkages with other essential components of SCPI stress environments (Cao et al., 2016), and use this data to design abiotic-tolerant rice varieties. Since drought stress involves molecular, cellular, and physiological level changes (Barnabas et al., 2008), genomics can help reveal small individual changes across a large number of genes. Genomic information can uncover the combined traits leading to drought-stress crop changes and conclude a map of QTL. Nonetheless, a more holistic approach (Varshney et al., 2009) is needed in order to combine abiotic-stress genomics data (Barnabas et al., 2008) to other equally important approaches such as understanding complex regulatory networks using metabolomics (Okazaki et al., 2016), proteomics and transcriptomics (Urano et al., 2010), and crop phenotyping. An additional approach utilised in rice studies, phytochemical genomics, seeks to uncover metabolites pertaining to biosynthetic enzymes (Okazaki et al., 2016). These combined approaches can provide the elementary and necessary datasets needed to design improved agriculture production systems which can then feedback to engineering GM-rice varieties which can both be productive and provide a platform for investigating SNPs information, also based upon stress conditions. Implementing a reasonable model that incorporates, economics, climate-change science, sociological and geographical factors, and regulation/IP to further enhance the SCPI approach. Genomics: adapting, or diversifying, new and existing crop species to climate change The FAOs recent report outlines several strategies to mitigate climate change through improved agricultural practices, and also through enabling genetic diversity (FAO, 2016). Climate change influences and modifies agriculture both directly and indirectly upon society (Schmidhuber et al., 2007). These effects can be modelled from the IPCC’s Special Report on Emissions Scenarios (SRES), which include four families of socio-economic development. Aligned it these SRES’s is the FAO’s food security dimensions (Schmidhuber et al., 2007), which focuses on the monetary and nonmonetary resources of current food insecurity; seeking to avoid an inadequacy of food supplies as its overall goal. The rapidity of designing cultivars with enhanced tolerance to abiotic stresses and/or improving rice varieties with stably agronomic performance (Varshney et al., 2009) is becoming increasingly important in designing climate-resilient rice crops. The importance of breeding climate-resilient (Kissoudis et al., 2016) rice is globally imperative in order to counteract the effects of this growing climate danger. In line with this, the adaption of crops to this climatic shift, namely heat and drought, will be an essential element to maintaining rice quality (Henry et al., 2016). Since crop-stress environments are highly variable (Kissoudis et al., 2016), the incorporation of a plantresponse to its stress-mediated environment would involve a series of changes at the DNA level which follow on to non-specific changes at the expression level. There is still a persisting problem of addressing abiotic stresses such as drought exposure (Leurenco et al., 2016), salinity stress (Ghosh et al., 2016), and temperature stress (Martinez, 2016). Genomics can help inform on past trends of extreme climate events (ECEs) on crop populations and demographics (Leurenco et al., 2016). What is of equal importance is the need to finely describe gene-expression data resulting from abiotic6! of 17 ! 2016 For example, Oryza sativa (rice) can be rearranged if rapid adaption to abiotic stresses is necessary by employing genomics to map the 155 CWRs (Bradbury et al., 2008) associated within its predefined group (Bradbury et al., 2008). This would assist by discovering possible abiotic-stress related genes that can recover a specific abiotic stress phenotype, depending of course on the environmental stress in question. Aligned to this, NGS technologies (Varshney et al., 2009) can provide the necessary genomic information which could assist in developing available genomic resources for improving existing domesticated rice varieties. This includes developing drought-tolerant lines This will also strengthen food security (Henry et al., 2016) as it alleviates reliance on the current major rice varieties, increasing the likelihood of securing rice for further generations, through diversification with CWR versions. The following example explains an abiotic-stress adaption of staple food crops, for example rice in a drought-context, to better understand such impacts through such adverse conditions: 1) Defining regional climate, based on establishing criteria: In the case of drought-tolerance or water deficiency, a short-term and gradual, water shortage will cause physiological changes to the plant crop: a) Shortening life-cycle b) Optimising resources c) Metabolic protection d) Maintaining high tissue water potential. 2) Characterising plant crop genes/alleles changes (SNPs); from (1), 3) Mapping genes, using genomics, which are upregulated and favoured from conditions within a (1) scenario, The combination and implementation of crop adaption strategies and/or new crops species management can only be directed by modelling climate change behaviour with a readily available genetic resource of engineered rice varieties. Efforts should also be guided towards population characteristics; i.e. how rice is consumed in society, and the various physical and nutritional preferences that humans may have. This presents an additional layer of consumer-information which might suggest that along with climate change, the likely change(s) in human response(s) to available functional foods may need to be concurrently taken into consideration, based on key cultural and sociological indicators. Together, a clearer picture of changing climatic events can be aligned to better understanding climate responses in rice species. Mitigating undesirable climate change effects in this major staple crop, for example, should encompass adaption strategies (Fitzgerald 2016), not only focused on agricultural systems but also geographic indicators. 4) Excising candidate gene(s) from (2,3) for strengthened crop variety, gene engineering approaches, and phenotyping in field studies to preclude the damage from severe drought events. 5) Using genome data from (3) and improved crop varieties from (4) to develop new production systems which positively support physiological and phenological responses from plants in a (1) scenario. Another possible strategy which could be independent or dependent on currently utilised crop improvements, is the idea of domesticating new rice species (Henry et al., 2016) under diversification programs. This approach makes use of Crop Wild Relatives (CWRs), which can provide a future safety-net and readilyexploitable (Godfray et al., 2010) genetic resource for phylogentically similar crops. 7! of 17 ! 2016 The FAO has established a Save and Grow setup for addressing crop management practices (FAO, 2016). Unfavourable climatic conditions driven by climate change will hamper, and decrease (Kissoudis et al., 2016), the productivity of economically important agricultural crops, which have only a short production opportunity to thrive in a given climatic window. Conclusively, genomics technologies and genomicbased crop improvements (Abberton et al., 2016) will provide identification of a larger gene pool, for plant breeders, to create elite crops that can greatly assist future food supply and security. Kole et al., 2015 described three important challenges which must be circumvented in regard to gene loss; 1) Shifting focus on a selection criteria which accounts for stress adaption; 2) Confirming the existence, through genomics, of stress-related genes which can be utilised for further breeding programs; and, 3) Accounting for minor rice crops, along with major ones, which might have already-adapted characteristics which will require less inputs. Genomics leading to secure food supplies A combination of sufficient food availability, an economically feasible access to food, and an appropriate and adequate nutritional content (Qaim 2011) from consumed foods, are all relevant to ensuring food security. Food security and genomics Food security, represented in this case by agricultural productivity and food pricing (Kole et al., 2015; FAO, 2016), will be subsequently affected by climate change, which sit within the four FAO elements of food security. Food security can be maintained from the indirect action of appropriately applying NGS-genomic studies, which can tackle food insecurity as is being faced by those in developing countries. Food insecurity is nonetheless a serious problem, with the FAO identifying the need for agricultural biotechnology implementation to address this growing issue (Smyth et al., 2016). Therefore, the importance of commercialising new rice crop innovations, usually GM, will assist developing countries and their desire to shift into, and maintain, a nutritionally sustainable diet. Referring back to the Save and Grow guidelines, and also the Hague conference climate-Smart report (2010); in both instances policies and institutions are described (FAO, 2011; FAO 2010). The Climate-Smart approach, with regards to enabling food security, proposes that a significant transformation must be initiated to address food security challenges. Additionally, their key findings suggest that investment in developing technologies and methodologies to fill present research knowledge gaps, is mandatory to fully enable the proposed climate-smart approach. (FAO, 2010). Genomics can assist efforts in researching into knowledge gaps, such that the climate-smart approach can account for scientific platforms, offered by NGS. FAO’s Save and Grow guidelines, also addressing policies and institutions, base their outcomes on their developed Sustainable crop production intensification (SCPI) goal. (FAO, 2011). It interprets seed sector regulation, plant genetic resources, technologies and information, and agricultural investments as key factors An increase in rice crop productivity has been the resulting trend from the ongoing operation of traditional production systems, namely the unchanged farming simplification and intensification procedures. It is now acceptable to assume that changes in how current rice crop harvesting strategies are approached should be remodelled accordingly. 8! of 17 ! 2016 that will support their SCPI intentions. Enabling institutions, as an additional SCPI function, presents two main functions: 1) Ensuring key resources (natural, inputs, knowledge, financial, and, 2) ensuring small farmers can access those resources. Genomics technologies can adequately support the Save and Grow SCPI program, through providing accessible crop genetic data that can be disseminated appropriately to smallholder farmers, provided knowledge is also communicated. varieties with subsequent improved phenotypes to farm-scale. An appropriate commercialisation platform must be set-up and readily implemented. Commercialising GM-rice varieties will require a strict approach to detecting GM events (Broeders et al., 2012). A high-throughput system, such as genomics, will lead to an advanced system wherein UGM can be detected, and conformation of authorised GM traits are mapped. Minor differences in GM-non-GM crops will become increasingly difficult to identify (Broeders et al., 2012), and so NGS technologies-genomics platforms will better handle this growing GM complexity in the future. GM-Rice commercialisation GM-rice has been mentioned as a new-comer in the GM-market (Parisi et al., 2016), which will no doubt yield some interesting products for both industry and community. The reasons for this emergence into cultivating GM-rice varieties is from the simultaneous problems affected rice yields and a need to manage abiotic-stresses more readily. Huang et al., (2010) identified some 3.6 million SNPs from the sequencing of 517 rice landraces, using GWAS on 14 agronomic traits in a subspecies of O. sativa indica. The same authors concluded that such a GWAS approach showcases the possibility of uncovering complex traits in rice, where this strategy can be used as a resource for further, and alongside, breeding strategies (Huang et al., 2010). Commercialisation strategies have previously approved crops which contain minor modifications that provide resistance against herbicides and pesticides (Godfray et al., 2010). A current dilemma exists within the relationship between IP rights, biotechnology, and public discourse on matters relating to GM crops. The interrelationship of trust and public perception must be aligned to an overall agreement if genomic technologies can start exploiting large pools of genetic data and material, and use these in a context of developing drought- and/or -temperature resilient rice varieties. Overall, a lengthy and usually expensive process (Fischhoff and Cline, 2009), is required to bring a GM-product from lab to shelf. If improved GM-rice varieties are to be invested and sold within this paradigm of biotechnology regulation, then it is of equal importance to develop and include existing genomics protocols/techniques which can lead to a better defined agricultural development plan, for both policy and industry. Inclusively, policy-makers must also ensure that GM technologies are suitable for those nations in need of poverty reduction, and, consider the potential of GM crops (Qaim 2011), such as GM-rice varieties. Qaim (2011) outlined that the several opportunities from utilising GM techniques/ technologies can enable improved GM crops based on a Consumer preferences are also leaking into R&D pipelines, hence affecting how new GM-rice varieties could be marketed (Huffman, 2011). An effective approach could be to design and market nutritional traits. These modifications to the nutritional profile of rice would require public opinion and a disclosure of the technology used, to gain mainstream community acceptance. Genomics-based trait identification as a means to identify resilient-genes and QTL regions in rice cannot be the end-all-be-all to progress these engineered 9! of 17 ! 2016 3 dimensional framework consisting of, Physical, Economical, and Food safety attributes. (Qaim 2011). Importantly, GM technologies can help raise small farmer incomes. An improvement in food safety from genomics adaptions will also need to overcome regulatory obstacles. This is contrary to the intended purposes of applying genomics, for example resequencing and WGS, as their purpose is to provide precise mapping of genetic changes. Therefore, these approaches would depend on institute and policy elements, rather than on their benefits of speeding-up commercialisation, and simultaneously strengthening regulation of high-risk labelled GM. transcripts indicating a time-, geographical- scale change in GM-rice varieties. Due to the large dataset generated from genomics/NGS technologies, there is currently no application of genomics approaches in GMs (Fraiture et al., 2016). If genomics were applied, however, then it would require an improvement in the NGS analysis, along with a complete assessment of the currently used GM detection method, using qPCR (Fraiture et al., 2016). Therefore, the way in which GM detection laboratories assess GM-derived products could be tightened by using genomics technologies. Genomics will also assist plant breeders. A plant breeder can utilise, with increased confidence, genomewide datasets of known rice varieties/species to understand which chromosomal fragment(s) might be involved in cross-over events, thereby increasing confidence of their marker-placement along genetic maps. This approach also enables the more precise transfer of QTL or chromosome regions from one cultivar to another. Additionally, if specific QTLs are involved in metabolic engineering pathways, then genomics will paint a clearer picture of which genes should be excised and transferred to produce strengthened varieties. Genomics-assisted breeding, in this regard, might utilise rice CWRs. Markets, trade, and genomics approaches There is however another aspect of commercialising new GM-rice varieties that will curtail such adverse effects from climate change; that is, investment options and opportunities. Market size is crucial in this regard, and only sustainable markets will be appealing to those large companies that can maintain their position within their existing position within such markets. Market size, in the context of GM-approved rice varieties that will mitigate climatic change effects, will also depends on the risk(s), regulatory position of importing/exporting countries, and public perception, or a lack thereof, associated with continuing with pipeline processes, from lab GM-trait development to supply-chain. Trade is a critical aspect of agriculture. Using genomics-based methods might also lower the risk of GM-rice trade, i.e. import/export. This stage relates to the necessary regulatory framework that ensures access to genetic resources (Roa et al., 2016), derived from MAB and/or WGS data, which should be communicated and provided between trading nations. Additionally, policy frameworks should be developed; regulating access to these genetic resources. Currently, the EU member states (MS) have complicated this trade process by their decision to take a zero-tolerance approach to trading partners exporting GM-traits (Smyth et al., 2016). In doing so, those countries, such as within sub-saharan Africa, may lose their market- How will genomics assist in this overall process involving the many risk-associated steps of commercialising GM-rice varieties? Genomics approaches can lower the risk level when designing GM-rice varieties by providing sufficient genetic resources for the regulator and investor. The precision of NGS technologies can also provide a model-simulated approach that can help explain spatial and temporal consequences by mapping RNA ! of 17 10 ! 2016 positions from investments into GM-based productive crops. non-GM varieties, ensuring trade isn't hampered and further investment decisions are not affected. Although the examples provided signify a much longerterm strategy for GM-rice varieties, it is still important that policy-makers and state GM regulators are aware of the challenges that lie ahead regarding abiotic-stress traits in rice, heralded from climate change events. Genomics-based approaches can avoid the stigma surrounding GM-crops in certain EU MS. If policymakers and regulators of the EU formulate a collaborative effort to provide its public groups and government access to interpreted, user-friendly, genomics data and/or knowledge courses, outlining associated benefits, then perhaps genomics could lead the way in lowering risks associated with GM-rice varieties in the future, especially alleviating perceived risks involved in investing into adaption of GM-crops varieties. Regulation would then be an appropriate measure in the detection of GMO traces in GM-crops (Fraiture et al., 2015). Fraiture et al., (2015) described the additional advantage of implementing NGS, targeting sequencing and WGS, in GM traceability, as one that allows new PCR markers to be synthesised, however is based on an unknown a priori GM sequence. This study noted that difficulties in adopting NGS in enforcement laboratories relates to high-costs and inadequacies in computer and expertise infrastructures (Fraiture et al., 2015). Nonetheless, the high-throughout of NGS can be applied to GM varieties via the screening of unique barcodes. Secondly, can genomics-assisted technology applied to producing GM-rice cultivar development increase the amount of positive investment in these carefully constructed varieties? In the long-term, genomics mapping of GM-rice of economically traits will greatly assist and enable stronger agricultural productivity in developing nations where food insecurity persists. This will serve as a basis for, and feed into, policy-maker decisions, which will in turn affect country-to-country legislation on GM related decisions. New breeding outcomes, from adopting genomicsbased methodologies, will only be accepted in mainstream perception when food and agricultural authorities, such as the FAO, can realise their ambitions of eliminating food insecurity by challenging current viewpoints, such as those currently harboured by the EU (Smyth et al., 2016). The FAO might also enlist as part of its objectives and mission to tackle global food insecurity the growing genomics revolution, in progress, with already published results that will greatly enhance confidence in WGS-based studies, and resolve a greater number of genetic resources/markers. This leads into another aspect of the genomics revolution; sharing genetic resource information. Extending the aforementioned example, a GM-riceadopting country in Asia, such as in China or India (R), will be better-equipped to share NGS data: WGS and/or MAS information, to its export GM-allowing countries, in the foreseeable future. The additional commercial advantage of combining traits from genomics technologies is of particular interest. Not only will genomics, and its complementary holistic approaches, provide appropriate genetic and chromosomal maps for industry to exploit and design, with improved resolution, elite rice varieties; but genomics-assisted breeding strategies can work within a paradigm of selecting and combining traits that can overcome complicated farming By enforcing adequate guidelines and monitoring systems from GM-adapting states to non-GM allowing states (Broeders et al., 2012), and for SMEs to remain viable within their markets, the use of a re-sequencing approach, for example, should be a mandatory element of quality assurance (QA) in order to segregate GM and ! of !17 11 2016 environments (Ronald 2014). This should be viewed as a significant subset of mitigating climate-change. golden-rice, would have resulted in millions of damaged eyesights. The authors concluded that it is unjustified to delay GM technologies if their adoption is greater than the expected damages. From a social welfare perspective, GM technology adaption can improve social standing (Zilberman et al., 2015). What this suggests is that an additional economical limiting factor, that is economical benefits from GM technologies, could also influence government decision towards being more precaution-orientated rather than accepting the economical- social and -agricultural rewards with accepting NGS-genomics technologies. Scientific publications from genomics studies should be transcribed for public readability, and disclosed accordingly, to trigger public-GM acceptance (Hallerman et al., 2016) that is malleable to rational suggestion upon anticipated public discourse. GM-trust concerns, perhaps relating to longterm GM-rice cultivation, should also account for the need to protect and improve global food production and security. A skilful approach from policy and private agrocompanies should span the science, in this case NGSgenomics, the need for climate adaptive GM-crops, an education on climate change effects on crops such as rice, and a focus on the benefits to the local farm-owner (R); so that farmer advantages outweigh the benefits yielded from private and public organisations. State and Federal government should work to reformat and redefine key terminologies to the relevant food standards, for example FSANZ (Food Standards Australia and New Zealand 2016), and GM consultancy, for example with the OGTR (Office of the Gene Regulator), in an Australian context. This could adequately characterise and define new GM-rice varieties projected to mitigate climate change effects, based on IPCC and FAO objectives (IPCC 2014;FAO 2016), and summaries for policy makers. Large and SME agri-businesses should also work collaboratively (Hallerman et al., 2016) and incorporate developing nations/rural farmers into their strategic ventures in order to communicate the use of genomic technologies and methodologies and associated outputs based on gene bank databases, for example. In unison, governments should position themselves towards reviewing regulation, educating public to ensure confidence in their perception(s), and working with large and SME organisations to evolve policy and incentives that favours food security, through a new agricultural model; that should incorporate NGS genomics to generate public interest in biotechnology. This will ensure the local farmer is considered, educated, and well-informed of, climate-mitigated GMapproved crop varieties which can only be effective if their socio-cultural factors are considered in governmentally regulated frameworks and policies. Private sector stakes in GM-initiated rice projects should not be monopolised solely towards their own commercial interests, and should allow room for other agri-startups and SMEs to innovate. State governance remains the key limiting factor in these scenarios, who must encourage and support innovative genomic technologies/methodologies, and their application, that complement production systems and which can harmonise these in favour of providing suitable return on investments for private players. A simulated study of GM economics conducted by Zilberman et al., (2015) revealed that a loss of 10 years from not applying Parisi et al. described the concerns associated with commercialisation barriers. In their study, they pointed out that other factors such as market availability and viability, regulatory systems, and economic aspects of commercialisation are fundamental for companies to understand if they are to continue investing into their R&D agricultural products (Parisi et al., 2016). The same study addresses products, GM traits in staple crops, and explains their barriers to commercialisation ! of 17 12 ! 2016 which might be due to unfavourable market platforms, the failure to transition GM events to a large-scale and/ or under-performing, and the discouragement from public consensus that offsets further progression towards commercialisation. account the potential of NGS technologies that can offer a valid rationale for their ‘agricultural transformation’ ambitions. These new advances in NGS, and biotechnology, must be considered by regulators in order to account for the many more GM events that will undoubtably occur. These regulatory concerns should keep up with the growing number of molecular markers, for example, which will explain the complexity of stress-related traits, and which will require GM to address climate-change effects. Furthermore, risks of investing large sums of money into product pipelines can be, depending on the R&D stage, associated with stringent and expensive regulatory outlines. From a large business perspective the costs may seem manageable; conversely, a SME or public organisation would need to invest more during the early stages of their R&D pipeline. In the case of a long-term SME with promising GM-rice variety cultivars that can tolerate drought and temperature stress, initiating the genomics-driven results to largescale trials might seem feasible and within budget, however this could breakdown at regulatory step(s) where over-spending might become an apparent issue. Together, these strategies will pave a way forward for new agricultural systems from GM-crop genome to farmer satisfaction, that should only be marketed and sold to farmers based on their needs, not for the purpose of stand-alone profitability. Chapter five of the 2016 FAO has listed an ‘inefficient use of resources’ as a prime concern influencing productivity and climate change, and resilience. It could well be the role of genomics, such as WGS, GS, GWAS, and/or re-sequencing, that can fill certain ‘knowledge gaps’ which can provide the initial data surrounding the development of climate-resilient rice varieties. By improving this knowledge base using a genomic-derived platform, a more scientificallydefined approach to establishing relevant policy can be materialised and implemented. The example of FAOs Save and Grow approach provides a well-developed paradigm that also includes several suggested strategies that address the need of improved and adapted varieties. Agricultural assessment will need to address not only the implementation of the improvement in rice phenotypes to its transfer to food security and policy, but also to maintain a focus on what consumers desire, i.e. nutritional content. Modifying the existing framework of how rice varieties become commercially sold and grown, by industry to farmers, consequently to consumer, will explicitly call in strict food safety criteria that will need to address, and meet, end-use quality processes in a globallydemanding food outlook. Conclusions The obvious relationship between existing and emerging genomics approaches, climate change outlooks, and their translational output in designing GM-rice varieties which can withstand changing socioeconomic and climatic terrain, will represent the next phase in rice research. Problems currently exist within managing a suitable agricultural development plan which accounts for the improved genomics approaches that can mitigate human-induced environmental threats in most staple crops across the globe. The Save and Grow, and Hague conference reports both offer suitable plans that address climate change, and agricultural intensification processes; however they do not take into ! of 17 13 ! 2016 The challenge in the near future is not only developing more resilient rice varieties that can mitigate abiotic effects, but also managing and implementing a minimally-timed process of commercialising elite rice varieties with functional traits that don't run the risk of a lengthy time-to-market pipeline. Thus it is necessary that GM regulation is properly educated to avoid a further politicisation of the GM debate. Developing nations will be the beneficiaries in genomics-applied GM-rice varieties, and so major reform is required. 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