Key message
Integration of genomic technologies with breeding efforts have been used in recent years for chickpea improvement. Modern breeding along with low cost genotyping platforms have potential ...to further accelerate chickpea improvement efforts.
The implementation of novel breeding technologies is expected to contribute substantial improvements in crop productivity. While conventional breeding methods have led to development of more than 200 improved chickpea varieties in the past, still there is ample scope to increase productivity. It is predicted that integration of modern genomic resources with conventional breeding efforts will help in the delivery of climate-resilient chickpea varieties in comparatively less time. Recent advances in genomics tools and technologies have facilitated the generation of large-scale sequencing and genotyping data sets in chickpea. Combined analysis of high-resolution phenotypic and genetic data is paving the way for identifying genes and biological pathways associated with breeding-related traits. Genomics technologies have been used to develop diagnostic markers for use in marker-assisted backcrossing programmes, which have yielded several molecular breeding products in chickpea. We anticipate that a sequence-based holistic breeding approach, including the integration of functional omics, parental selection, forward breeding and genome-wide selection, will bring a paradigm shift in development of superior chickpea varieties. There is a need to integrate the knowledge generated by modern genomics technologies with molecular breeding efforts to bridge the genome-to-phenome gap. Here, we review recent advances that have led to new possibilities for developing and screening breeding populations, and provide strategies for enhancing the selection efficiency and accelerating the rate of genetic gain in chickpea.
Artificially improving traits of cultivated alfalfa (Medicago sativa L.), one of the most important forage crops, is challenging due to the lack of a reference genome and an efficient genome editing ...protocol, which mainly result from its autotetraploidy and self-incompatibility. Here, we generate an allele-aware chromosome-level genome assembly for the cultivated alfalfa consisting of 32 allelic chromosomes by integrating high-fidelity single-molecule sequencing and Hi-C data. We further establish an efficient CRISPR/Cas9-based genome editing protocol on the basis of this genome assembly and precisely introduce tetra-allelic mutations into null mutants that display obvious phenotype changes. The mutated alleles and phenotypes of null mutants can be stably inherited in generations in a transgene-free manner by cross pollination, which may help in bypassing the debate about transgenic plants. The presented genome and CRISPR/Cas9-based transgene-free genome editing protocol provide key foundations for accelerating research and molecular breeding of this important forage crop.
Key message
We describe the development and application of the Sorghum QTL Atlas, a high-resolution, open-access research platform to facilitate candidate gene identification across three cereal ...species, sorghum, maize and rice.
The mechanisms governing the genetic control of many quantitative traits are only poorly understood and have yet to be fully exploited. Over the last two decades, over a thousand QTL and GWAS studies have been published in the major cereal crops including sorghum, maize and rice. A large body of information has been generated on the genetic basis of quantitative traits, their genomic location, allelic effects and epistatic interactions. However, such QTL information has not been widely applied by cereal improvement programs and genetic researchers worldwide. In part this is due to the heterogeneous nature of QTL studies which leads QTL reliability variation from study to study. Using approaches to adjust the QTL confidence interval, this platform provides access to the most updated sorghum QTL information than any database available, spanning 23 years of research since 1995. The QTL database provides information on the predicted gene models underlying the QTL CI, across all sorghum genome assembly gene sets and maize and rice genome assemblies and also provides information on the diversity of the underlying genes and information on signatures of selection in sorghum. The resulting high-resolution, open-access research platform facilitates candidate gene identification across 3 cereal species, sorghum, maize and rice. Using a number of trait examples, we demonstrate the power and resolution of the resource to facilitate comparative genomics approaches to provide a bridge between genomics and applied breeding.
Genomic selection (GS) models have been validated for many quantitative traits in wheat (
Triticum aestivum
L.) breeding. However, those models are mostly constrained within the same growing cycle ...and the extension of GS to the case of across cycles has been a challenge, mainly due to the low predictive accuracy resulting from two factors: reduced genetic relationships between different families and augmented environmental variances between cycles. Using the data collected from diverse field conditions at the International Wheat and Maize Improvement Center, we evaluated GS for grain yield in three elite yield trials across three wheat growing cycles. The objective of this project was to employ the secondary traits, canopy temperature, and green normalized difference vegetation index, which are closely associated with grain yield from high-throughput phenotyping platforms, to improve prediction accuracy for grain yield. The ability to predict grain yield was evaluated reciprocally across three cycles with or without secondary traits. Our results indicate that prediction accuracy increased by an average of 146% for grain yield across cycles with secondary traits. In addition, our results suggest that secondary traits phenotyped during wheat heading and early grain filling stages were optimal for enhancing the prediction accuracy for grain yield.
Efficiency of breeding programs of legume crops such as chickpea, pigeonpea and groundnut has been considerably improved over the past decade through deployment of modern genomic tools and ...technologies. For instance, next-generation sequencing technologies have facilitated availability of genome sequence assemblies, re-sequencing of several hundred lines, development of HapMaps, high-density genetic maps, a range of marker genotyping platforms and identification of markers associated with a number of agronomic traits in these legume crops. Although marker-assisted backcrossing and marker-assisted selection approaches have been used to develop superior lines in several cases, it is the need of the hour for continuous population improvement after every breeding cycle to accelerate genetic gain in the breeding programs. In this context, we propose a sequence-based breeding approach which includes use of independent or combination of parental selection, enhancing genetic diversity of breeding programs, forward breeding for early generation selection, and genomic selection using sequencing/genotyping technologies. Also, adoption of speed breeding technology by generating 4–6 generations per year will be contributing to accelerate genetic gain. While we see a huge potential of the sequence-based breeding to revolutionize crop improvement programs in these legumes, we anticipate several challenges especially associated with high-quality and precise phenotyping at affordable costs, data analysis and management related to improving breeding operation efficiency. Finally, integration of improved seed systems and better agronomic packages with the development of improved varieties by using sequence-based breeding will ensure higher genetic gains in farmers’ fields.
Bandwagons I, too, have known Bernardo, Rex
Theoretical and applied genetics,
12/2016, Volume:
129, Issue:
12
Journal Article
Peer reviewed
Key message
Bandwagons come in waves. A plant breeder, just like a surfer, needs to carefully choose which waves to be on.
A bandwagon is an idea, activity, or cause that becomes increasingly ...fashionable as more and more people adopt it. In a 1991 article entitled
Bandwagons I Have Known
, Professor N. W. Simmonds described several bandwagons that he encountered in his career, beginning with induced polyploidy and mutation breeding and ending with the then-new field of biotechnology. This article reviews and speculates about post-1990 bandwagons in plant improvement, including transgenic cultivars, quantitative trait locus (QTL) mapping, association mapping, genomewide (or genomic) selection, phenomics, envirotyping, and genome editing. The life cycle of a bandwagon includes an excitement phase of hype and funding; a realization phase when the initial hype is either tempered or the initial expectations are found to have been too low; and a reality phase when the useful aspects of a bandwagon become part of mainstream thinking and practice, or when an unsuccessful bandwagon is largely abandoned. During the realization phase, a new bandwagon that draws our attention and gives us renewed optimism typically arises. The most popular bandwagons, such as QTL mapping, are those for which the needed experimental resources are accessible, the required technical knowledge and skills can be easily learned, and the outputs can almost always be reported. The favorite bandwagon of any plant breeder has, in one way or another, resulted from Mendel’s seminal discoveries 150 years ago. Our community of plant breeders needs to be continually diligent in welcoming new bandwagons, but also in hopping off from those that do not prove useful.
Polyploid organisms carry more than two copies of each chromosome, a condition rarely tolerated in animals but which occurs relatively frequently in the plant kingdom. One of the principal challenges ...faced by polyploid organisms is to evolve stable meiotic mechanisms to faithfully transmit genetic information to the next generation upon which the study of inheritance is based. In this review we look at the tools available to the research community to better understand polyploid inheritance, many of which have only recently been developed. Most of these tools are intended for experimental populations (rather than natural populations), facilitating genomics-assisted crop improvement and plant breeding. This is hardly surprising given that a large proportion of domesticated plant species are polyploid. We focus on three main areas: (1) polyploid genotyping; (2) genetic and physical mapping; and (3) quantitative trait analysis and genomic selection. We also briefly review some miscellaneous topics such as the mode of inheritance and the availability of polyploid simulation software. The current polyploid analytic toolbox includes software for assigning marker genotypes (and in particular, estimating the dosage of marker alleles in the heterozygous condition), establishing chromosome-scale linkage phase among marker alleles, constructing (short-range) haplotypes, generating linkage maps, performing genome-wide association studies (GWAS) and quantitative trait locus (QTL) analyses, and simulating polyploid populations. These tools can also help elucidate the mode of inheritance (disomic, polysomic or a mixture of both as in segmental allopolyploids) or reveal whether double reduction and multivalent chromosomal pairing occur. An increasing number of polyploids (or associated diploids) are being sequenced, leading to publicly available reference genome assemblies. Much work remains in order to keep pace with developments in genomic technologies. However, such technologies also offer the promise of understanding polyploid genomes at a level which hitherto has remained elusive.
Key message
Safeguarding crop yields in a changing climate requires bioinformatics advances in harnessing data from vast phenomics and genomics datasets to translate research findings into climate ...smart crops in the field.
Climate change and an additional 3 billion mouths to feed by 2050 raise serious concerns over global food security. Crop breeding and land management strategies will need to evolve to maximize the utilization of finite resources in coming years. High-throughput phenotyping and genomics technologies are providing researchers with the information required to guide and inform the breeding of climate smart crops adapted to the environment. Bioinformatics has a fundamental role to play in integrating and exploiting this fast accumulating wealth of data, through association studies to detect genomic targets underlying key adaptive climate-resilient traits. These data provide tools for breeders to tailor crops to their environment and can be introduced using advanced selection or genome editing methods. To effectively translate research into the field, genomic and phenomic information will need to be integrated into comprehensive clade-specific databases and platforms alongside accessible tools that can be used by breeders to inform the selection of climate adaptive traits. Here we discuss the role of bioinformatics in extracting, analysing, integrating and managing genomic and phenomic data to improve climate resilience in crops, including current, emerging and potential approaches, applications and bottlenecks in the research and breeding pipeline.
Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of ...quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.
•A shift in breeding mentality is needed to realise improved varieties’ potential to increase food security.•Information on markets, environment and climate, pre-breeding research and effective ...dissemination methods are needed too.•Rapid generation advance has the highest adoption potential of all the accelerated breeding methods in the public sector.•Foregone benefits from earlier adoption could have mitigated the long-term negative impact of hunger on human development.•Postponing accelerated breeding technologies makes no economic sense and immediate adoption is economically optimal.
With an expected 9 billion people by 2050 and average income on the rise in the developing world, meeting future food demand will be a challenge. Climate change, urbanisation and land degradation are putting further pressure on the food supply. The multifaceted and self-reinforcing nature of these challenges calls for a fundamental transformation of the food system. In the past, crop improvement through breeding has been the major tool to lift people out of poverty and increase global food supply. To adequately address these food security challenges, new improved crop varieties need to be developed and reach farmers sooner as a partial solution. In this review, we focus on various proven conventional and biotechnological accelerating plant breeding methods that do not require genetic engineering or gene editing. We pay specific attention to the feasibility for implementation by national agricultural research systems in developing countries in the short term. We argue that postponing technologies that can accelerate breeding makes no economic sense and justify immediate adoption of accelerated breeding practices in the public sector. Considering a wide range of factors including the economics of accelerated breeding, we advocate the use of a method called rapid generation advance (RGA) as the most feasible method for accelerating breeding in the public sector.
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