Modernising breeding for orphan crops: tools, methodologies, and beyond

Integrating genomics and genome editing for orphan crop improvement: a bridge between orphan crops and modern agriculture system

Domestication of orphan crops could be explored by editing their genomes. Genome editing has a lot of promise for enhancing agricultural output, and there is a lot of interest in furthering breeding in orphan crops, which are sometimes plagued with unwanted traits that resemble wild cousins. Consequently, applying model crop knowledge to orphan crops allows for the rapid generation of targeted allelic diversity and innovative breeding germplasm. We explain how plant breeders could employ genome editing as a novel platform to accelerate the domestication of semi-domesticated or wild plants, resulting in a more diversified base for future food and fodder supplies. This review emphasizes both the practicality of the strategy and the need to invest in research that advances our understanding of plant genomes, genes, and cellular systems. Planting more of these abandoned orphan crops could help alleviate food scarcities in the challenge of future climate crises.

Mainstreaming orphan millets for advancing climate smart agriculture to secure nutrition and health

The ever-changing climate and the current COVID-19 pandemic compound the problems and seriously impact agriculture production, resulting in socio-economic insecurities and imposing health implications globally. Most of the poor and malnourished population in the developing countries depends on agriculture for food, income, and employment. Impact of climate change together with the COVID-19 outbreak revealed immense problems highlighting the importance of mainstreaming climate-resilient and low input crops with more contemporary agriculture practices. Orphan millets play a vital role in the poor and malnourished population's livelihood, food and nutrition security. Recognizing their unique potential, the United Nations-Food and Agriculture Organization has announced the year 2023 as the "International Year of Millets". However, despite the unique properties for present and future agriculture of orphan millets, their cultivation is declining in many countries. As a result, millets have gained attention from researchers which eventually decelerated "multi-omics" resource generation. This review summarizes the benefits of millets and major barriers/ bottlenecks in their improvement. We also discuss the pre- and post-harvest technologies; policies required to introduce and establish millets in mainstream agriculture. To improve and ensure the livelihood of the poor/malnourished population, intensive efforts are urgently needed in advancing the research and development, implementing pre- and post-harvest technological intervention strategies, and making favorable policies for orphan crops to accomplish food and nutrition security. National and international collaborations are also indispensable to address the uncertain effects of climate change and COVID-19.

Population-tailored mock genome enables genomic studies in species without a reference genome

Based on molecular markers, genomic prediction enables us to speed up breeding schemes and increase the response to selection. There are several high-throughput genotyping platforms able to deliver thousands of molecular markers for genomic study purposes. However, even though its widely applied in plant breeding, species without a reference genome cannot fully benefit from genomic tools and modern breeding schemes. We used a method to assemble a population-tailored mock genome to call single-nucleotide polymorphism (SNP) markers without an available reference genome, and for the first time, we compared the results with standard genotyping platforms (array and genotyping-by-sequencing (GBS) using a reference genome) for performance in genomic prediction models. Our results indicate that using a population-tailored mock genome to call SNP delivers reliable estimates for the genomic relationship between genotypes. Furthermore, genomic prediction estimates were comparable to standard approaches, especially when considering only additive effects. However, mock genomes were slightly worse than arrays at predicting traits influenced by dominance effects, but still performed as well as standard GBS methods that use a reference genome. Nevertheless, the array-based SNP markers methods achieved the best predictive ability and reliability to estimate variance components. Overall, the mock genomes can be a worthy alternative for genomic selection studies, especially for those species where the reference genome is not available.

Subsampling and DNA pooling can increase gains through genomic selection in switchgrass

Genomic selection (GS) can accelerate breeding cycles in perennial crops such as the bioenergy grass switchgrass (Panicum virgatum L.). The sequencing costs of GS can be reduced by pooling DNA samples in the training population (TP), only sequencing TP phenotypic outliers, or pooling candidate population (CP) samples. These strategies were simulated for two traits (spring vigor and anthesis date) in three breeding populations. Sequencing only the outlier 50% of the TP phenotype distribution resulted in a penalty of <5% of the predictive ability, measured using cross-validation. Predictive ability also decreased when sequencing progressively fewer TP DNA pools, but TPs constructed from only two phenotypically contrasting DNA samples retained a mean of >80% predictive ability relative to individual TP sequencing. Novel group testing methods allowed greater than one CP individual to be screened per sequenced DNA sample but resulted in a predictive ability penalty. To determine the impact of reduced sequencing, genetic gain was calculated for seven GS scenarios with variable sequencing budgets. Reduced TP sequencing and most CP pooling methods were superior to individual sequence-based GS when sequencing resources were restricted (2,000 DNA samples per 5-yr cycle). Only one scenario was superior to individual sequencing when sequencing budgets were large (8,000 DNA samples per 5-yr cycle). This study highlights multiple routes for reduced sequencing costs in GS.

Bambara Groundnut (Vigna subterranea L. Verdc): A Crop for the New Millennium, Its Genetic Diversity, and Improvements to Mitigate Future Food and Nutritional Challenges

The world’s food and agricultural schemes have gradually fallen into an alarming state due to challenges such as high population birth rates, diverse agro-climatic zones, a lack of measures to counter global warming, severe practices of sole-culture cultivation, and asset reduction. A very high dependency on limited staple food crops is associated with repetitious diets, deprivation of food, and shortages of trace minerals, which often causes dietary sicknesses. To ensure nutritious diets worldwide, a real-world and justifiable scheme is provided to garner extra attention towards variation in both agriculture/farming approaches and food habits. The EAT-Lancet statement emphasized an increase in agri-based diets as a way of attaining global generational health. Enlarging neglected crops with plenty of genomic stocks and potentially profitable attributes is a solution that could address food and nutritional security concerns. Bambara groundnut is one such imperative and neglected legume crop that contributes positively to improving global food and nutrient safety. As a “complete food”, this crop has recently been treated as a new millennium crop, and furthermore, it is more adjusted to poor soil and climatic conditions than other dominant crops. Bambara groundnut is a repository of vital nutrients that provides carbohydrates, crucial amino acids, proteins, and energy as well as minerals and vitamins to developed and low-income countries where animal proteins are not readily available. This review explores the potential of Bambara groundnut in ensuring food and nutrient security; its variables, production, processing, nutrient values, role in reducing the nutritional gap, and diverse uses; and attempts in improving its traits. To strengthen food production, an agricultural revolution is required for underutilized crop species to feed the ever-expanding population in the world. Henceforth, advanced plant-breeding procedures, such as next-generation breeding techniques, various molecular tools, TILLING, Eco-TILLING, proteomics, genomics, and transcriptomics (which has been used for major crops), also need to be practiced to intensify production. To boost productivity and to feed the most starved and malnourished populations of the world, it is assumed that the application of modern techniques will play a vital role in the advancement of the underutilized Bambara groundnut.

Orphan Crops and their Wild Relatives in the Genomic Era

More than half of the calories consumed by humans are provided by three major cereal crops (rice, maize, and wheat). Orphan crops are usually well adapted to low-input agricultural conditions, and they not only play vital roles in local areas but can also contribute to food and nutritional needs worldwide. Interestingly, many wild relatives of orphan crops are important weeds of major crops. Although orphan crops and their wild relatives have received little attentions from researchers for many years, genomic studies have recently been performed on these plants. Here, we provide an overview of genomic studies on orphan crops, with a focus on orphan cereals and their wild relatives. The genomes of at least 12 orphan cereals and/or their wild relatives have been sequenced. In addition to genomic benefits for orphan crop breeding, we discuss the potential ways for mutual utilization of genomic data from major crops, orphan crops, and their wild relatives (including weeds) and provide perspectives on genetic improvement of both orphan and major crops (including de novo domestication of orphan crops) in the coming genomic era.

COPO: a metadata platform for brokering FAIR data in the life sciences

Scientific innovation is increasingly reliant on data and computational resources. Much of today’s life science research involves generating, processing, and reusing heterogeneous datasets that are growing exponentially in size. Demand for technical experts (data scientists and bioinformaticians) to process these data is at an all-time high, but these are not typically trained in good data management practices. That said, we have come a long way in the last decade, with funders, publishers, and researchers themselves making the case for open, interoperable data as a key component of an open science philosophy. In response, recognition of the FAIR Principles (that data should be Findable, Accessible, Interoperable and Reusable) has become commonplace. However, both technical and cultural challenges for the implementation of these principles still exist when storing, managing, analysing and disseminating both legacy and new data. COPO is a computational system that attempts to address some of these challenges by enabling scientists to describe their research objects (raw or processed data, publications, samples, images, etc.) using community-sanctioned metadata sets and vocabularies, and then use public or institutional repositories to share them with the wider scientific community. COPO encourages data generators to adhere to appropriate metadata standards when publishing research objects, using semantic terms to add meaning to them and specify relationships between them. This allows data consumers, be they people or machines, to find, aggregate, and analyse data which would otherwise be private or invisible, building upon existing standards to push the state of the art in scientific data dissemination whilst minimising the burden of data publication and sharing.

Strategies for Effective Use of Genomic Information in Crop Breeding Programs Serving Africa and South Asia

Much of the world's population growth will occur in regions where food insecurity is prevalent, with large increases in food demand projected in regions of Africa and South Asia. While improving food security in these regions will require a multi-faceted approach, improved performance of crop varieties in these regions will play a critical role. Current rates of genetic gain in breeding programs serving Africa and South Asia fall below rates achieved in other regions of the world. Given resource constraints, increased genetic gain in these regions cannot be achieved by simply expanding the size of breeding programs. New approaches to breeding are required. The Genomic Open-source Breeding informatics initiative (GOBii) and Excellence in Breeding Platform (EiB) are working with public sector breeding programs to build capacity, develop breeding strategies, and build breeding informatics capabilities to enable routine use of new technologies that can improve the efficiency of breeding programs and increase genetic gains. Simulations evaluating breeding strategies indicate cost-effective implementations of genomic selection (GS) are feasible using relatively small training sets, and proof-of-concept implementations have been validated in the International Maize and Wheat Improvement Center (CIMMYT) maize breeding program. Progress on GOBii, EiB, and implementation of GS in CIMMYT and International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) breeding programs are discussed, as well as strategies for routine implementation of GS in breeding programs serving Africa and South Asia.