Genomics-based plant germplasm research (GPGR)

A Pathway to Assess Genetic Variation of Wheat Germplasm by Multidimensional Traits with Digital Images

In this paper, a new pathway was proposed to assess the germplasm genetic variation by multidimensional traits of wheat seeds generated from digital images. A machine vision platform was first established to reconstruct wheat germplasm 3D model from omnidirectional image sequences of wheat seeds. Then, multidimensional traits were conducted from the wheat germplasm 3D model, including seed length, width, thickness, surface area, volume, maximum projection area, roundness, and 2 new defined traits called cardioid-derived area and the index of adjustment (J index). To assess genetic variation of wheat germplasm, phenotypic coefficients of variation (PCVs), analysis of variance (ANOVA), clustering, and the defined genetic variation factor (GVF) were calculated using the extracted morphological traits of 15 wheat accessions comprising 13 offspring and 2 parents. The measurement accuracy of 3D reconstruction model is demonstrated by the correlation coefficient (R) and root mean square errors (RMSEs). Results of PCVs among all the traits show importance of multidimensional traits, as seed volume (22.4%), cardioid-derived area (16.97%), and maximum projection area (14.67%). ANOVA shows a highly significance difference among all accessions. The results of GVF innovatively reflect the connection between genotypic variance and phenotypic traits from parents to offspring. Our results confirmed that extracting multidimensional traits from digital images is a promising high-throughput and cost-efficient pathway that can be included as a valuable approach in genetic variation assessment, and it can provide useful information for genetic improvement, preservation, and evaluation of wheat germplasm.

Deciphering the evolution and complexity of wheat germplasm from a genomic perspective

Bread wheat provides an essential fraction of the daily calorific intake for humanity. Due to its huge and complex genome, progress in studying on the wheat genome is substantially trailed behind those of the other two major crops, rice and maize, for at least a decade. With rapid advances in genome assembling and reduced cost of high-throughput sequencing, emerging de novo genome assemblies of wheat and whole-genome sequencing data are leading to a paradigm shift in wheat research. Here, we review recent progress in dissecting the complex genome and germplasm evolution of wheat since the release of the first high-quality wheat genome. New insights have been gained in the evolution of wheat germplasm during domestication and modern breeding progress, genomic variations at multiple scales contributing to the diversity of wheat germplasm, and complex transcriptional and epigenetic regulations of functional genes in polyploid wheat. Genomics databases and bioinformatics tools meeting the urgent needs of wheat genomics research are also summarized. The ever-increasing omics data, along with advanced tools and well-structured databases, are expected to accelerate deciphering the germplasm and gene resources in wheat for future breeding advances.

Next-generation bulked segregant analysis for Breeding 4.0

Functional cloning and manipulation of genes controlling various agronomic traits are important for boosting crop production. Although bulked segregant analysis (BSA) is an efficient method for functional cloning, its low throughput cannot satisfy the current need for crop breeding and food security. Here, we review the rationale and development of conventional BSA and discuss its strengths and drawbacks. We then propose next-generation BSA (NG-BSA) integrating multiple cutting-edge technologies, including high-throughput phenotyping, biological big data, and the use of machine learning. NG-BSA increases the resolution of genetic mapping and throughput for cloning quantitative trait genes (QTGs) and optimizes candidate gene selection while providing a means to elucidate the interaction network of QTGs. The ability of NG-BSA to efficiently batch-clone QTGs makes it an important tool for dissecting molecular mechanisms underlying various traits, as well as for the improvement of Breeding 4.0 strategy, especially in targeted improvement and population improvement of crops.

Genetic and molecular dissection of ginseng (Panax ginseng Mey.) germplasm using high-density genic SNP markers, secondary metabolites, and gene expressions

Genetic and molecular knowledge of a species is crucial to its gene discovery and enhanced breeding. Here, we report the genetic and molecular dissection of ginseng, an important herb for healthy food and medicine. A mini-core collection consisting of 344 cultivars and landraces was developed for ginseng that represents the genetic variation of ginseng existing in its origin and diversity center. We sequenced the transcriptomes of all 344 cultivars and landraces; identified over 1.5 million genic SNPs, thereby revealing the genic diversity of ginseng; and analyzed them with 26,600 high-quality genic SNPs or a selection of them. Ginseng had a wide molecular diversity and was clustered into three subpopulations. Analysis of 16 ginsenosides, the major bioactive components for healthy food and medicine, showed that ginseng had a wide variation in the contents of all 16 ginsenosides and an extensive correlation of their contents, suggesting that they are synthesized through a single or multiple correlated pathways. Furthermore, we pair-wisely examined the relationships between the cultivars and landraces, revealing their relationships in gene expression, gene variation, and ginsenoside biosynthesis. These results provide new knowledge and new genetic and genic resources for advanced research and breeding of ginseng and related species.

Crop germplasm: Current challenges, physiological-molecular perspective, and advance strategies towards development of climate-resilient crops

Germplasm is a long-term resource management mission and investment for civilization. An estimated ∼7.4 million accessions are held in 1750 plant germplasm centres around the world; yet, only 2% of these assets have been utilized as plant genetic resources (PGRs). According to recent studies, the current food yield trajectory will be insufficient to feed the world's population in 2050. Additionally, possible negative effects in terms of crop failure because of climate change are already being experienced across the world. Therefore, it is necessary to reconciliation of research advancement and innovation of practices for further exploration of the potential of crop germplasm especially for the complex traits associated with yield such as water- and nitrogen use efficiency. In this review, we tried to address current challenges, research gaps, physiological and molecular aspects of two broad spectrum complex traits such as water- and nitrogen-use efficiency, and advanced integrated strategies that could provide a platform for combined stress management for climate-smart crop development. Additionally, recent development in technologies that are directly related to germplasm characterization was highlighted for further molecular utilization towards the development of elite varieties.

ggComp enables dissection of germplasm resources and construction of a multiscale germplasm network in wheat

Accurate germplasm characterization is a vital step for accelerating crop genetic improvement, which remains largely infeasible for crops such as bread wheat (Triticum aestivum L.), which has a complex genome that undergoes frequent introgression and contains many structural variations. Here, we propose a genomic strategy called ggComp, which integrates resequencing data with copy number variations and stratified single-nucleotide polymorphism densities to enable unsupervised identification of pairwise germplasm resource-based Identity-By-Descent (gIBD) blocks. The reliability of ggComp was verified in wheat cultivar Nongda5181 by dissecting parental-descent patterns represented by inherited genomic blocks. With gIBD blocks identified among 212 wheat accessions, we constructed a multi-scale genomic-based germplasm network. At the whole-genome level, the network helps to clarify pedigree relationship, demonstrate genetic flow, and identify key founder lines. At the chromosome level, we were able to trace the utilization of 1RS introgression in modern wheat breeding by hitchhiked segments. At the single block scale, the dissected germplasm-based haplotypes nicely matched with previously identified alleles of "Green Revolution" genes and can guide allele mining and dissect the trajectory of beneficial alleles in wheat breeding. Our work presents a model-based framework for precisely evaluating germplasm resources with genomic data. A database, WheatCompDB (http://wheat.cau.edu.cn/WheatCompDB/), is available for researchers to exploit the identified gIBDs with a multi-scale network.

DArT-based evaluation of soybean germplasm from Polish Gene Bank

OBJECTIVE

Soybean is an important plant used for food, feed and many industrial purposes. Interest in soybean breeding is growing in Central Europe, including Poland. A very large number of soybean accessions are stored in gene banks, but less than 1% of them have been used for breeding. Here, we present genotypic data as well as phenotypic data on plant and seed performance, including seed chlorophyll fluorescence traits, and on yield components within a collection of soybean accessions that are conserved in the Polish Gene Bank at the Plant Breeding and Acclimatization Institute-National Research Institute.

RESULTS

The materials used consisted of sub-collections: 79 Polish genotypes, including old traditional cultivars, 24 Canadian, 21 American, 21 Swedish and 31 from Central and Eastern European Countries, 9 from France and 6 from Japan. In total, 9602 high quality SNPs were derived from DArTseq, a method utilising GBS technology. GWAS, performed with the BLINK model, revealed that a total of 41 significant SNPs were mapped for days to flowering, flower colour, plant height, days to pod formation, 100 seed weight, pod colour, seeds and hilum colour and steady-state chlorophyll fluorescence under light (Ft_Lss). This is the first report about the diversity of traditional old Polish soybean cultivars.

Whole-Genome Sequencing of the NARO World Rice Core Collection (WRC) as the Basis for Diversity and Association Studies

Genebanks provide access to diverse materials for crop improvement. To utilize and evaluate them effectively, core collections, such as the World Rice Core Collection (WRC) in the Genebank at the National Agriculture and Food Research Organization, have been developed. Because the WRC consists of 69 accessions with a high degree of genetic diversity, it has been used for >300 projects. To allow deeper investigation of existing WRC data and to further promote research using Genebank rice accessions, we performed whole-genome resequencing of these 69 accessions, examining their sequence variation by mapping against the Oryza sativa ssp. japonica Nipponbare genome. We obtained a total of 2,805,329 single nucleotide polymorphisms (SNPs) and 357,639 insertion-deletions. Based on the principal component analysis and population structure analysis of these data, the WRC can be classified into three major groups. We applied TASUKE, a multiple genome browser to visualize the different WRC genome sequences, and classified haplotype groups of genes affecting seed characteristics and heading date. TASUKE thus provides access to WRC genotypes as a tool for reverse genetics. We examined the suitability of the compact WRC population for genome-wide association studies (GWASs). Heading date, affected by a large number of quantitative trait loci (QTLs), was not associated with known genes, but several seed-related phenotypes were associated with known genes. Thus, for QTLs of strong effect, the compact WRC performed well in GWAS. This information enables us to understand genetic diversity in 37,000 rice accessions maintained in the Genebank and to find genes associated with different phenotypes. The sequence data have been deposited in DNA Data Bank of Japan Sequence Read Archive (DRA) (Supplementary Table S1).

The USDA cucumber (Cucumis sativus L.) collection: genetic diversity, population structure, genome-wide association studies, and core collection development

Germplasm collections are a crucial resource to conserve natural genetic diversity and provide a source of novel traits essential for sustained crop improvement. Optimal collection, preservation and utilization of these materials depends upon knowledge of the genetic variation present within the collection. Here we use the high-throughput genotyping-by-sequencing (GBS) technology to characterize the United States National Plant Germplasm System (NPGS) collection of cucumber (Cucumis sativus L.). The GBS data, derived from 1234 cucumber accessions, provided more than 23 K high-quality single-nucleotide polymorphisms (SNPs) that are well distributed at high density in the genome (~1 SNP/10.6 kb). The SNP markers were used to characterize genetic diversity, population structure, phylogenetic relationships, linkage disequilibrium, and population differentiation of the NPGS cucumber collection. These results, providing detailed genetic analysis of the U.S. cucumber collection, complement NPGS descriptive information regarding geographic origin and phenotypic characterization. We also identified genome regions significantly associated with 13 horticulturally important traits through genome-wide association studies (GWAS). Finally, we developed a molecularly informed, publicly accessible core collection of 395 accessions that represents at least 96% of the genetic variation present in the NPGS. Collectively, the information obtained from the GBS data enabled deep insight into the diversity present and genetic relationships among accessions within the collection, and will provide a valuable resource for genetic analyses, gene discovery, crop improvement, and germplasm preservation.

Assessing and Exploiting Functional Diversity in Germplasm Pools to Enhance Abiotic Stress Adaptation and Yield in Cereals and Food Legumes

There is a need to accelerate crop improvement by introducing alleles conferring host plant resistance, abiotic stress adaptation, and high yield potential. Elite cultivars, landraces and wild relatives harbor useful genetic variation that needs to be more easily utilized in plant breeding. We review genome-wide approaches for assessing and identifying alleles associated with desirable agronomic traits in diverse germplasm pools of cereals and legumes. Major quantitative trait loci and single nucleotide polymorphisms (SNPs) associated with desirable agronomic traits have been deployed to enhance crop productivity and resilience. These include alleles associated with variation conferring enhanced photoperiod and flowering traits. Genetic variants in the florigen pathway can provide both environmental flexibility and improved yields. SNPs associated with length of growing season and tolerance to abiotic stresses (precipitation, high temperature) are valuable resources for accelerating breeding for drought-prone environments. Both genomic selection and genome editing can also harness allelic diversity and increase productivity by improving multiple traits, including phenology, plant architecture, yield potential and adaptation to abiotic stresses. Discovering rare alleles and useful haplotypes also provides opportunities to enhance abiotic stress adaptation, while epigenetic variation has potential to enhance abiotic stress adaptation and productivity in crops. By reviewing current knowledge on specific traits and their genetic basis, we highlight recent developments in the understanding of crop functional diversity and identify potential candidate genes for future use. The storage and integration of genetic, genomic and phenotypic information will play an important role in ensuring broad and rapid application of novel genetic discoveries by the plant breeding community. Exploiting alleles for yield-related traits would allow improvement of selection efficiency and overall genetic gain of multigenic traits. An integrated approach involving multiple stakeholders specializing in management and utilization of genetic resources, crop breeding, molecular biology and genomics, agronomy, stress tolerance, and reproductive/seed biology will help to address the global challenge of ensuring food security in the face of growing resource demands and climate change induced stresses.