Designing a Mini-Core Collection Effectively Representing 3004 Diverse Rice Accessions

Degenerate oligonucleotide primer MIG-seq: an effective PCR-based method for high-throughput genotyping

Next-generation sequencing (NGS) library construction often involves using restriction enzymes to decrease genome complexity, enabling versatile polymorphism detection in plants. However, plant leaves frequently contain impurities, such as polyphenols, necessitating DNA purification before enzymatic reactions. To overcome this problem, we developed a PCR-based method for expeditious NGS library preparation, offering flexibility in number of detected polymorphisms. By substituting a segment of the simple sequence repeat sequence in the MIG-seq primer set (MIG-seq being a PCR method enabling library construction with low-quality DNA) with degenerate oligonucleotides, we introduced variability in detectable polymorphisms across various crops. This innovation, named degenerate oligonucleotide primer MIG-seq (dpMIG-seq), enabled a streamlined protocol for constructing dpMIG-seq libraries from unpurified DNA, which was implemented stably in several crop species, including fruit trees. Furthermore, dpMIG-seq facilitated efficient lineage selection in wheat and enabled linkage map construction and quantitative trait loci analysis in tomato, rice, and soybean without necessitating DNA concentration adjustments. These findings underscore the potential of the dpMIG-seq protocol for advancing genetic analyses across diverse plant species.

Construction of a strawberry breeding core collection to capture and exploit genetic variation

BACKGROUND

Genetic diversity is crucial for the success of plant breeding programs and core collections are important resources to capture this diversity. Many core collections have already been constructed by gene banks, whose main goal is to obtain a panel of a limited number of genotypes to simplify management practices and to improve shareability while retaining as much diversity as possible. However, as gene banks have a different composition and goal than plant breeding programs, constructing a core collection for a plant breeding program should consider different aspects.

RESULTS

In this study, we present a novel approach for constructing a core collection by integrating both genomic and pedigree information to maximize the representation of the breeding germplasm in a minimum subset of genotypes while accounting for future genetic variation within a strawberry breeding program. Our stepwise approach starts with selecting the most important crossing parents of advanced selections and genotypes included for specific traits, to represent also future genetic variation. We then use pedigree-genomic-based relationship coefficients combined with the 'accession to nearest entry' criterion to complement the core collection and maximize its representativeness of the current breeding program. Combined pedigree-genomic-based relationship coefficients allow for accurate relationship estimation without the need to genotype every individual in the breeding program.

CONCLUSIONS

This stepwise construction of a core collection in a strawberry breeding program can be applied in other plant breeding programs to construct core collections for various purposes.

Diversity and genetic architecture of agro-morphological traits in a core collection of European traditional tomato

European traditional tomato varieties have been selected by farmers given their consistent performance and adaptation to local growing conditions. Here we developed a multipurpose core collection, comprising 226 accessions representative of the genotypic, phenotypic, and geographical diversity present in European traditional tomatoes, to investigate the basis of their phenotypic variation, gene×environment interactions, and stability for 33 agro-morphological traits. Comparison of the traditional varieties with a modern reference panel revealed that some traditional varieties displayed excellent agronomic performance and high trait stability, as good as or better than that of their modern counterparts. We conducted genome-wide association and genome-wide environment interaction studies and detected 141 quantitative trait loci (QTLs). Out of those, 47 QTLs were associated with the phenotype mean (meanQTLs), 41 with stability (stbQTLs), and 53 QTL-by-environment interactions (QTIs). Most QTLs displayed additive gene actions, with the exception of stbQTLs, which were mostly recessive and overdominant QTLs. Both common and specific loci controlled the phenotype mean and stability variation in traditional tomato; however, a larger proportion of specific QTLs was observed, indicating that the stability gene regulatory model is the predominant one. Developmental genes tended to map close to meanQTLs, while genes involved in stress response, hormone metabolism, and signalling were found within regions affecting stability. A total of 137 marker-trait associations for phenotypic means and stability were novel, and therefore our study enhances the understanding of the genetic basis of valuable agronomic traits and opens up a new avenue for an exploitation of the allelic diversity available within European traditional tomato germplasm.

Optimizing genomic selection of agricultural traits using K-wheat core collection

The agricultural traits that constitute basic plant breeding information are usually quantitative or complex in nature. This quantitative and complex combination of traits complicates the process of selection in breeding. This study examined the potential of genome-wide association studies (GWAS) and genomewide selection (GS) for breeding ten agricultural traits by using genome-wide SNPs. As a first step, a trait-associated candidate marker was identified by GWAS using a genetically diverse 567 Korean (K)-wheat core collection. The accessions were genotyped using an Axiom^® 35K wheat DNA chip, and ten agricultural traits were determined (awn color, awn length, culm color, culm length, ear color, ear length, days to heading, days to maturity, leaf length, and leaf width). It is essential to sustain global wheat production by utilizing accessions in wheat breeding. Among the traits associated with awn color and ear color that showed a high positive correlation, a SNP located on chr1B was significantly associated with both traits. Next, GS evaluated the prediction accuracy using six predictive models (G-BLUP, LASSO, BayseA, reproducing kernel Hilbert space, support vector machine (SVM), and random forest) and various training populations (TPs). With the exception of the SVM, all statistical models demonstrated a prediction accuracy of 0.4 or better. For the optimization of the TP, the number of TPs was randomly selected (10%, 30%, 50% and 70%) or divided into three subgroups (CC-sub 1, CC-sub 2 and CC-sub 3) based on the subpopulation structure. Based on subgroup-based TPs, better prediction accuracy was found for awn color, culm color, culm length, ear color, ear length, and leaf width. A variety of Korean wheat cultivars were used for validation to evaluate the prediction ability of populations. Seven out of ten cultivars showed phenotype-consistent results based on genomics-evaluated breeding values (GEBVs) calculated by the reproducing kernel Hilbert space (RKHS) predictive model. Our research provides a basis for improving complex traits in wheat breeding programs through genomics assisted breeding. The results of our research can be used as a basis for improving wheat breeding programs by using genomics-assisted breeding.

Restructuring plant types for developing tailor-made crops

Plants have adapted to different environmental niches by fine-tuning the developmental factors working together to regulate traits. Variations in the developmental factors result in a wide range of quantitative variations in these traits that helped plants survive better. The major developmental pathways affecting plant architecture are also under the control of such pathways. Most notable are the CLAVATA-WUSCHEL pathway regulating shoot apical meristem fate, GID1-DELLA module influencing plant height and tillering, LAZY1-TAC1 module controlling branch/tiller angle and the TFL1-FT determining the floral fate in plants. Allelic variants of these key regulators selected during domestication shaped the crops the way we know them today. There is immense yield potential in the 'ideal plant architecture' of a crop. With the available genome-editing techniques, possibilities are not restricted to naturally occurring variations. Using a transient reprogramming system, one can screen the effect of several developmental gene expressions in novel ecosystems to identify the best targets. We can use the plant's fine-tuning mechanism for customizing crops to specific environments. The process of crop domestication can be accelerated with a proper understanding of these developmental pathways. It is time to step forward towards the next-generation molecular breeding for restructuring plant types in crops ensuring yield stability.

Exome-wide variation in a diverse barley panel reveals genetic associations with ten agronomic traits in Eastern landraces

Barley (Hordeum vulgare ssp. vulgare) was one of the first crops to be domesticated and is adapted to a wide range of environments. Worldwide barley germplasm collections possess valuable allelic variations that could further improve barley productivity. Although barley genomics has offered a global picture of allelic variation among varieties and its association with various agronomic traits, polymorphisms from East Asian varieties remain scarce. In this study, we analyzed exome polymorphisms in a panel of 274 barley varieties collected worldwide, including 137 varieties from East Asian countries and Ethiopia. We revealed the underlying population structure and conducted genome-wide association studies for ten agronomic traits. Moreover, we examined genome-wide associations for traits related to grain size such as awn length and glume length. Our results demonstrate the value of diverse barley germplasm panels containing Eastern varieties, highlighting their distinct genomic signatures relative to Western subpopulations.

Genetic diversity of wild rice accessions (Oryza rufipogon Griff.) in Guangdong and Hainan Provinces, China, and construction of a wild rice core collection

Oryza rufipogon Griff. is a valuable germplasm resource for rice genetic improvement. However, natural habitat loss has led to the erosion of the genetic diversity of wild rice populations. Genetic diversity analysis of O. rufipogon accessions and development of the core collection are crucial for conserving natural genetic diversity and providing novel traits for rice breeding. In the present study, we developed 1,592 SNPs by multiplex PCR and next-generation sequencing (NGS) technology and used them to genotype 998 O. rufipogon accessions from 14 agroclimatic zones in Guangdong and Hainan Provinces, China. These SNPs were mapped onto 12 chromosomes, and the average MAF value was 0.128 with a minimum of 0.01 and a maximum of 0.499. The O. rufipogon accessions were classified into ten groups. The mean Nei's diversity index and Shannon-Wiener index (I) were 0.187 and 0.308, respectively, in all populations, indicating that O. rufipogon accessions had rich genetic diversity. There were also differences in the genetic diversity of O. rufipogon resources in the 14 regions. Hainan populations possessed higher levels of genetic diversity, whereas the Guangzhou population had lower levels of genetic diversity than did the other populations. Phylogenetic analysis revealed that the genetic relationship among the distribution sites of O. rufipogon was closely related to geographical location. Based on genetic distance, a core collection of 299 accessions captured more than 99% of the genetic variation in the germplasm. This study provides insights into O. rufipogon conservation, and the constructed core collection provides valuable resources for future research and genomics-assisted breeding of rice.

Genome-Wide Identification of MDH Family Genes and Their Association with Salt Tolerance in Rice

Malate dehydrogenase (MDH) is widely present in nature and regulates plant growth and development, as well as playing essential roles, especially in abiotic stress responses. Nevertheless, there is no comprehensive knowledge to date on MDH family members in rice. In this study, a total of 12 MDH members in rice were identified through genome-wide analysis and divided into three groups on the basis of their phylogenetic relationship and protein-conserved motifs. Evolutionary analysis showed that MDH proteins from rice, maize and wheat shared a close phylogenetic relationship, and the MDH family was conserved in the long-term process of domestication. We identified two segmental duplication events involving four genes, which could be the major force driving the expansion of the OsMDH family. The expression profile, cis-regulatory elements and qRT-PCR results of these genes revealed that a few OsMDH showed high tissue specificity, almost all of which had stress response elements in the promoter region, and ten MDH members were significantly induced by salt stress. Through gene-based association analysis, we found a significant correlation between salt tolerance at the seedling stage and the genetic variation of OsMDH8.1 and OsMDH12.1. Additionally, we found that the polymorphism in the promoter region of OsMDH8.1 might be related to the salt tolerance of rice. This study aimed to provide valuable information on the functional study of the rice MDH gene family related to salt stress response and revealed that OsMDH8.1 might be an important gene for the cultivar improvement of salt tolerance in rice.

Twenty years of rice genomics research: From sequencing and functional genomics to quantitative genomics

Since the completion of the rice genome sequencing project in 2005, we have entered the era of rice genomics, which is still in its ascendancy. Rice genomics studies can be classified into three stages: structural genomics, functional genomics, and quantitative genomics. Structural genomics refers primarily to genome sequencing for the construction of a complete map of rice genome sequence. This is fundamental for rice genetics and molecular biology research. Functional genomics aims to decode the functions of rice genes. Quantitative genomics is large-scale sequence- and statistics-based research to define the quantitative traits and genetic features of rice populations. Rice genomics has been a transformative influence on rice biological research and contributes significantly to rice breeding, making rice a good model plant for studying crop sciences.

Identification of a Diverse Core Set Panel of Rice From the East Coast Region of India Using SNP Markers

In India, rice (Oryza sativa L.) is cultivated under a variety of climatic conditions. Due to the fragility of the coastal ecosystem, rice farming in these areas has lagged behind. Salinity coupled with floods has added to this trend. Hence, to prevent genetic erosion, conserving and characterizing the coastal rice, is the need of the hour. This work accessed the genetic variation and population structure among 2,242 rice accessions originating from India’s east coast comprising Andhra Pradesh, Orissa, and Tamil Nadu, using 36 SNP markers, and have generated a core set (247 accessions) as well as a mini-core set (30 accessions) of rice germplasm. All the 36 SNP loci were biallelic and 72 alleles found with average two alleles per locus. The genetic relatedness of the total collection was inferred using the un-rooted neighbor-joining tree, which grouped all the genotypes (2,242) into three major clusters. Two groups were obtained with a core set and three groups obtained with a mini core set. The mean PIC value of total collection was 0.24, and those of the core collection and mini core collection were 0.27 and 0.32, respectively. The mean heterozygosity and gene diversity of the overall collection were 0.07 and 0.29, respectively, and the core set and mini core set revealed 0.12 and 0.34, 0.20 and 0.40 values, respectively, representing 99% of distinctiveness in the core and mini core sets. Population structure analysis showed maximum population at K = 4 for total collection and core collection. Accessions were distributed according to their population structure confirmed by PCoA and AMOVA analysis. The identified small and diverse core set panel will be useful in allele mining for biotic and abiotic traits and managing the genetic diversity of the coastal rice collection. Validation of the 36-plex SNP assay was done by comparing the genetic diversity parameters across two different rice core collections, i.e., east coast and northeast rice collection. The same set of SNP markers was found very effective in deciphering diversity at different genetic parameters in both the collections; hence, these marker sets can be utilized for core development and diversity analysis studies.

Genomic Selection in Sugarcane: Current Status and Future Prospects

Sugarcane is a C4 and agro-industry-based crop with a high potential for biomass production. It serves as raw material for the production of sugar, ethanol, and electricity. Modern sugarcane varieties are derived from the interspecific and intergeneric hybridization between Saccharum officinarum, Saccharum spontaneum, and other wild relatives. Sugarcane breeding programmes are broadly categorized into germplasm collection and characterization, pre-breeding and genetic base-broadening, and varietal development programmes. The varietal identification through the classic breeding programme requires a minimum of 12-14 years. The precise phenotyping in sugarcane is extremely tedious due to the high propensity of lodging and suckering owing to the influence of environmental factors and crop management practices. This kind of phenotyping requires data from both plant crop and ratoon experiments conducted over locations and seasons. In this review, we explored the feasibility of genomic selection schemes for various breeding programmes in sugarcane. The genetic diversity analysis using genome-wide markers helps in the formation of core set germplasm representing the total genomic diversity present in the Saccharum gene bank. The genome-wide association studies and genomic prediction in the Saccharum gene bank are helpful to identify the complete genomic resources for cane yield, commercial cane sugar, tolerances to biotic and abiotic stresses, and other agronomic traits. The implementation of genomic selection in pre-breeding, genetic base-broadening programmes assist in precise introgression of specific genes and recurrent selection schemes enhance the higher frequency of favorable alleles in the population with a considerable reduction in breeding cycles and population size. The integration of environmental covariates and genomic prediction in multi-environment trials assists in the prediction of varietal performance for different agro-climatic zones. This review also directed its focus on enhancing the genetic gain over time, cost, and resource allocation at various stages of breeding programmes.