Single-copy gene based 50 K SNP chip for genetic studies and molecular breeding in rice

Discovering New QTNs and Candidate Genes Associated with Rice-Grain-Related Traits within a Collection of Northeast Core Set and Rice Landraces

Grain-related traits are pivotal in rice cultivation, influencing yield and consumer preference. The complex inheritance of these traits, involving multiple alleles contributing to their expression, poses challenges in breeding. To address these challenges, a multi-locus genome-wide association study (ML-GWAS) utilizing 35,286 high-quality single-nucleotide polymorphisms (SNPs) was conducted. Our study utilized an association panel comprising 483 rice genotypes sourced from a northeast core set and a landraces set collected from various regions in India. Forty quantitative trait nucleotides (QTNs) were identified, associated with four grain-related traits: grain length (GL), grain width (GW), grain aroma (Aro), and length-width ratio (LWR). Notably, 16 QTNs were simultaneously identified using two ML-GWAS methods, distributed across multiple chromosomes. Nearly 258 genes were found near the 16 significant QTNs. Gene annotation study revealed that sixty of these genes exhibited elevated expression levels in specific tissues and were implicated in pathways influencing grain quality. Gene ontology (GO), trait ontology (TO), and enrichment analysis pinpointed 60 candidate genes (CGs) enriched in relevant GO terms. Among them, LOC_Os05g06470, LOC_Os06g06080, LOC_Os08g43470, and LOC_Os03g53110 were confirmed as key contributors to GL, GW, Aro, and LWR. Insights from QTNs and CGs illuminate rice trait regulation and genetic connections, offering potential targets for future studies.

Development of Novel KASP Markers for Improved Germination in Deep-Sown Direct Seeded Rice

BACKGROUND

The lack of stable-high yielding and direct-seeded adapted varieties with better germination ability from deeper soil depth and availability of molecular markers are major limitation in achieving the maximum yield potential of rice under water and resource limited conditions. Development of high-throughput and trait-linked markers are of great interest in genomics-assisted breeding. The aim of present study was to develop and validate novel KASP (Kompetitive Allele-Specific PCR) markers associated with traits improving germination and seedling vigor of deep sown direct seeded rice (DSR).

RESULTS

Out of 58 designed KASP assays, four KASP assays did not show any polymorphism in any of the eleven genetic backgrounds considered in the present study. The 54 polymorphic KASP assays were then validated for their robustness and reliability on the F1s plants developed from eight different crosses considered in the present study. The third next validation was carried out on 256 F3:F4 and 713 BC3F2:3 progenies. Finally, the reliability of the KASP assays was accessed on a set of random 50 samples from F3:F4 and 80-100 samples from BC3F2:3 progenies using the 10 random markers. From the 54 polymorphic KASP, based on the false positive rate, false negative rate, KASP utility in different genetic backgrounds and significant differences in the phenotypic values of the positive (desirable) and negative (undesirable) traits, a total of 12 KASP assays have been selected. These 12 KASP include 5 KASP on chromosome 3, 1 on chromosome 4, 3 on chromosome 7 and 3 on chromosome 8. The two SNPs lying in the exon regions of LOC_Os04g34290 and LOC_Os08g32100 led to non-synonymous mutations indicating a possible deleterious effect of the SNP variants on the protein structure.

CONCLUSION

The present research work will provide trait-linked KASP assays, improved breeding material possessing favourable alleles and breeding material in form of expected pre-direct-seeded adapted rice varieties. The marker can be utilized in introgression program during pyramiding of valuable QTLs/genes providing adaptation to rice under DSR. The functional studies of the genes LOC_Os04g34290 and LOC_Os08g32100 possessing two validated SNPs may provide valuable information about these genes.

Development of early maturing salt-tolerant rice variety KKL(R) 3 using a combination of conventional and molecular breeding approaches

Introduction: Soil salinity poses a severe threat to rice production, resulting in stunted growth, leaf damage, and substantial yield losses. This study focuses on developing an early maturing seedling stage salinity tolerant rice variety by integrating conventional breeding methods with marker assisted breeding (MAB) approaches. Methods: Seedling-stage salinity tolerance Quantitative Trait Locus (QTL) "Saltol" from the salt-tolerant parent FL478 was introduced into the high-yielding but salt-sensitive rice variety ADT 45. This was achieved through a combination of conventional breeding and MAB. The breeding process involved rigorous selection, screening, and physiological parameter assessments. Results: KKL(R) 3 (KR 15066) identified as the top performing Recombinant Inbred Line (RIL), consistently demonstrating maximum mean grain yields under both salinity (3435.6 kg/ha) and normal (6421.8 kg/ha) conditions. In comparison to the early maturing, salt-tolerant national check variety CSR 10, KKL(R) 3 exhibited a substantial yield increase over 50%. Discussion: The notable improvement observed in KKL(R) 3 positions it as a promising variety for release, offering a reliable solution to maximize yields, ensure food security, and promote agricultural sustainability in both saline and non-saline environments. The study highlights the effectiveness of MAB in developing salt-tolerant rice varieties and emphasizes the significance of the Saltol QTL in enhancing seedling stage salinity tolerance. The potential release of KKL(R) 3 has the capacity to revolutionize rice production in salt affected regions, providing farmers with a reliable solution to maximize yields and contribute to food security while ensuring agricultural sustainability.

Physiological Analysis of Source-Sink Relationship in Rice Genotypes with Contrasting Grain Yields

Rice is a major staple food, and, hence, doubling its productivity is critical to sustain future food security. Improving photosynthesis, source-sink relationships and grain-filling mechanisms are promising traits for improvement in grain yield. To understand the source-sink relationship and grain yield, a set of contrasting rice genotypes differing in yield and biomass were studied for physiological, biochemical and gene-expression differences. The physiological and yield component traits of selected rice genotypes were analyzed in 2016 and 2017 under field conditions. This led to the categorization of genotypes as high yielding (HY) and high biomass, viz., Dular, Gontra Bidhan 3, Way Rarem, Patchai Perumal, Sahbhagi Dhan, Indira Barani Dhan-1, MTU1010, and Maudamani; while, low yielding (LY) and low biomass, viz. Anjali, Ghanteswari, Parijat, Khao Daw Tai, RKVY-104, Ghati Kamma Nangarhar, BAM4510 and BAM5850. The HY genotypes in general had relatively better values of yield component traits, higher photosynthetic rate (Pn) and chlorophyll (Chl) content. The study revealed that leaf area per plant and whole plant photosynthesis are the key traits contributing to high biomass production. We selected two good-performing (Sahbhagi Dhan and Maudamani) and two poor-performing (Ghanteswari and Parijat) rice genotypes for a detailed expression analysis of selected genes involved in photosynthesis, sucrose synthesis, transport, and starch synthesis in the leaf and starch metabolism in grain. Some of the HY genotypes had a relatively high level of expression of key photosynthesis genes, such as RbcS, RCA, FBPase, and ZEP over LY genotypes. This study suggests that traits, such as leaf area, photosynthesis and grain number, contribute to high grain yield in rice. These good-performing genotypes can be used as a donor in a breeding program aimed at high yields in rice.

Functional role of microRNA in the regulation of biotic and abiotic stress in agronomic plants

The increasing demand for food is the result of an increasing population. It is crucial to enhance crop yield for sustainable production. Recently, microRNAs (miRNAs) have gained importance because of their involvement in crop productivity by regulating gene transcription in numerous biological processes, such as growth, development and abiotic and biotic stresses. miRNAs are small, non-coding RNA involved in numerous other biological functions in a plant that range from genomic integrity, metabolism, growth, and development to environmental stress response, which collectively influence the agronomic traits of the crop species. Additionally, miRNA families associated with various agronomic properties are conserved across diverse plant species. The miRNA adaptive responses enhance the plants to survive environmental stresses, such as drought, salinity, cold, and heat conditions, as well as biotic stresses, such as pathogens and insect pests. Thus, understanding the detailed mechanism of the potential response of miRNAs during stress response is necessary to promote the agronomic traits of crops. In this review, we updated the details of the functional aspects of miRNAs as potential regulators of various stress-related responses in agronomic plants.

On the usefulness of mock genomes to define heterotic pools, testers, and hybrid predictions in orphan crops

The advances in genomics in recent years have increased the accuracy and efficiency of breeding programs for many crops. Nevertheless, the adoption of genomic enhancement for several other crops essential in developing countries is still limited, especially for those that do not have a reference genome. These crops are more often called orphans. This is the first report to show how the results provided by different platforms, including the use of a simulated genome, called the mock genome, can generate in population structure and genetic diversity studies, especially when the intention is to use this information to support the formation of heterotic groups, choice of testers, and genomic prediction of single crosses. For that, we used a method to assemble a reference genome to perform the single-nucleotide polymorphism (SNP) calling without needing an external genome. Thus, we compared the analysis results using the mock genome with the standard approaches (array and genotyping-by-sequencing (GBS)). The results showed that the GBS-Mock presented similar results to the standard methods of genetic diversity studies, division of heterotic groups, the definition of testers, and genomic prediction. These results showed that a mock genome constructed from the population's intrinsic polymorphisms to perform the SNP calling is an effective alternative for conducting genomic studies of this nature in orphan crops, especially those that do not have a reference genome.

Flooding tolerance in Rice: adaptive mechanism and marker-assisted selection breeding approaches

Natural and man-made ecosystems worldwide are subjected to flooding, which is a form of environmental stress. Genetic variability in the plant response to flooding involves variations in metabolism, architecture, and elongation development that are related with a low oxygen escape strategy and an opposing quiescence scheme that enables prolonged submergence endurance. Flooding is typically associated with a decrease in O₂ in the cells, which is especially severe when photosynthesis is absent or limited, leading to significant annual yield losses globally. Over the past two decades, considerable advancements have been made in understanding of mechanisms of rice adaptation and tolerance to flooding/submergence. The mapping and identification of Sub1 QTL have led to the development of marker-assisted selection (MAS) breeding approach to improve flooding-tolerant rice varieties in submergence-prone ecosystems. The Sub1 incorporated in rice varieties showed tolerance during flash flood, but not during stagnant conditions. Hence, gene pyramiding techniques can be applied to combine/stack multiple resistant genes for developing flood-resilient rice varieties for different types of flooding stresses. This review contains an update on the latest advances in understanding the molecular mechanisms, metabolic adaptions, and genetic factors governing rice flooding tolerance. A better understanding of molecular genetics and adaptation mechanisms that enhance flood-tolerant varieties under different flooding regimes was also discussed.

Rice Pangenome Genotyping Array: an efficient genotyping solution for pangenome-based accelerated genetic improvement in rice

The advent of the pangenome era has unraveled previously unknown genetic variation existing within diverse crop plants, including rice. This untapped genetic variation is believed to account for a major portion of phenotypic variation existing in crop plants. However, the use of conventional single reference-guided genotyping often fails to capture a large portion of this genetic variation leading to a reference bias. This makes it difficult to identify and utilize novel population/cultivar-specific genes for crop improvement. Thus, we developed a Rice Pangenome Genotyping Array (RPGA) harboring probes assaying 80K single-nucleotide polymorphisms (SNPs) and presence-absence variants spanning the entire 3K rice pangenome. This array provides a simple, user-friendly and cost-effective (60-80 USD per sample) solution for rapid pangenome-based genotyping in rice. The genome-wide association study (GWAS) conducted using RPGA-SNP genotyping data of a rice diversity panel detected a total of 42 loci, including previously known as well as novel genomic loci regulating grain size/weight traits in rice. Eight of these identified trait-associated loci (dispensable loci) could not be detected with conventional single reference genome-based GWAS. A WD repeat-containing PROTEIN 12 gene underlying one of such dispensable locus on chromosome 7 (qLWR7) along with other non-dispensable loci were subsequently detected using high-resolution quantitative trait loci mapping confirming authenticity of RPGA-led GWAS. This demonstrates the potential of RPGA-based genotyping to overcome reference bias. The application of RPGA-based genotyping for population structure analysis, hybridity testing, ultra-high-density genetic map construction and chromosome-level genome assembly, and marker-assisted selection was also demonstrated. A web application (http://www.rpgaweb.com) was further developed to provide an easy to use platform for the imputation of RPGA-based genotyping data using 3K rice reference panel and subsequent GWAS.

Integrated genetic analysis of leaf blast resistance in upland rice: QTL mapping, bulked segregant analysis and transcriptome sequencing

Elite upland rice cultivars have the advantages of less water requirement along with high yield but are usually susceptible to various diseases. Rice blast caused by Magnaporthe oryzae is the most devastating disease in rice. Identification of new sources of resistance and the introgression of major resistance genes into elite cultivars are required for sustainable rice production. In this study, an upland rice genotype UR0803 was considered an emerging source of blast resistance. An F₂ mapping population was developed from a cross between UR0803 and a local susceptible cultivar Lijiang Xintuan Heigu. The individuals from the F₂ population were evaluated for leaf blast resistance in three trials 7 days after inoculation. Bulked segregant analysis (BSA) by high-throughput sequencing and SNP-index algorithm was performed to map the candidate region related to disease resistance trait. A major quantitative trait locus (QTL) for leaf blast resistance was identified on chromosome 11 in an interval of 1.61-Mb genomic region. The candidate region was further shortened to a 108.9-kb genomic region by genotyping the 955 individuals with 14 SNP markers. Transcriptome analysis was further performed between the resistant and susceptible parents, yielding a total of 5044 differentially expressed genes (DEGs). There were four DEGs in the candidate QTL region, of which, two (Os11g0700900 and Os11g0704000) were upregulated and the remaining (Os11g0702400 and Os11g0703600) were downregulated in the susceptible parent after inoculation. These novel candidate genes were functionally annotated to catalytic response against disease stimulus in cellular membranes. The results were further validated by a quantitative real-time PCR analysis. The fine-mapping of a novel QTL for blast resistance by integrative BSA mapping and transcriptome sequencing enhanced the genetic understanding of the mechanism of blast resistance in upland rice. The most suitable genotypes with resistance alleles would be useful genetic resources in rice blast resistance breeding.

Development of an inclusive 580K SNP array and its application for genomic selection and genome-wide association studies in rice

Rice is a globally cultivated crop and is primarily a staple food source for more than half of the world's population. Various single-nucleotide polymorphism (SNP) arrays have been developed and utilized as standard genotyping methods for rice breeding research. Considering the importance of SNP arrays with more inclusive genetic information for GWAS and genomic selection, we integrated SNPs from eight different data resources: resequencing data from the Korean World Rice Collection (KRICE) of 475 accessions, 3,000 rice genome project (3 K-RGP) data, 700 K high-density rice array, Affymetrix 44 K SNP array, QTARO, Reactome, and plastid and GMO information. The collected SNPs were filtered and selected based on the breeder's interest, covering all key traits or research areas to develop an integrated array system representing inclusive genomic polymorphisms. A total of 581,006 high-quality SNPs were synthesized with an average distance of 200 bp between adjacent SNPs, generating a 580 K Axiom Rice Genotyping Chip (580 K _ KNU chip). Further validation of this array on 4,720 genotypes revealed robust and highly efficient genotyping. This has also been demonstrated in genome-wide association studies (GWAS) and genomic selection (GS) of three traits: clum length, heading date, and panicle length. Several SNPs significantly associated with cut-off, -log₁₀ p-value >7.0, were detected in GWAS, and the GS predictabilities for the three traits were more than 0.5, in both rrBLUP and convolutional neural network (CNN) models. The Axiom 580 K Genotyping array will provide a cost-effective genotyping platform and accelerate rice GWAS and GS studies.

DRR Dhan 58, a Seedling Stage Salinity Tolerant NIL of Improved Samba Mahsuri Shows Superior Performance in Multi-location Trials

BACKGROUND

Improved Samba Mahsuri (ISM) is an elite, high-yielding, bacterial blight resistant, fine-grained rice variety with low glycaemic index. It is highly sensitive to salt stress, particularly at seedling stage, which significantly reduces its yield potential in coastal areas. A salinity tolerant QTL, Saltol, associated with seedling stage tolerance was previously mapped on chromosome 1 (10.6-11.5 Mb) from the Indian landrace, Pokkali and is effective in different genetic backgrounds. The objective of this study was to enhance salinity tolerance of ISM by incorporating the Saltol QTL through marker-assisted backcross breeding using the breeding line, FL478 (Pokkali/IR29).

RESULTS

Foreground selection was carried out at each generation using five Saltol-specific markers and three bacterial blight resistance genes, Xa21, xa13 and xa5. Background selection was conducted using 66 well distributed polymorphic SSR markers and at the BC₃F₂ generation, a single plant with maximum recurrent parent genome recovery (95.3%) was identified and advanced to the BC₃F₄ generation. Based on bacterial blight resistance, seedling stage salinity tolerance and resemblance to ISM, four advanced breeding lines were selected for testing in replicated experiments near Hyderabad, India. A promising near-isogenic line, DRR Dhan 58, was evaluated in multi-location trials-coastal salinity and it showed significant salinity tolerance, resistance to bacterial blight disease, high yield and excellent grain quality during the 2019 and 2020 trials. DRR Dhan 58 was 95.1% similar to ISM based on genotyping with the 90 K SNP chip. Whole genome resequencing analysis of Pokkali and FL478 which were salinity tolerant checks, ISM and DRR Dhan 58 showed a high degree of relatedness with respect to the candidate gene loci for Saltol and OsSKC1 (Shoot K⁺ Concentration 1).

CONCLUSION

DRR Dhan 58, possessing Saltol and three bacterial blight resistance genes (Xa21, xa13 and xa5) in the genetic background of the Indian mega-variety of rice, Samba Mahsuri, was developed for potential cultivation in areas prone to seedling stage salinity, as well as areas with endemic bacterial blight disease. This entry had a 24% yield advantage over the recurrent parent ISM under coastal saline conditions in multi-location trials and was recently released for commercial cultivation in India.

Genome-Wide Association Mapping Reveals Novel Putative Gene Candidates Governing Reproductive Stage Heat Stress Tolerance in Rice

Temperature rise predicted for the future will severely affect rice productivity because the crop is highly sensitive to heat stress at the reproductive stage. Breeding tolerant varieties is an economically viable option to combat heat stress, for which the knowledge of target genomic regions associated with the reproductive stage heat stress tolerance (RSHT) is essential. A set of 192 rice genotypes of diverse origins were evaluated under natural field conditions through staggered sowings for RSHT using two surrogate traits, spikelet fertility and grain yield, which showed significant reduction under heat stress. These genotypes were genotyped using a 50 k SNP array, and the association analysis identified 10 quantitative trait nucleotides (QTNs) for grain yield, of which one QTN (qHTGY8.1) was consistent across the different models used. Only two out of 10 MTAs coincided with the previously reported QTLs, making the remaing eight novel. A total of 22 QTNs were observed for spikelet fertility, among which qHTSF5.1 was consistently found across three models. Of the QTNs identified, seven coincided with previous reports, while the remaining QTNs were new. The genes near the QTNs were found associated with the protein–protein interaction, protein ubiquitination, stress signal transduction, and so forth, qualifying them to be putative for RSHT. An in silico expression analysis revealed the predominant expression of genes identified for spikelet fertility in reproductive organs. Further validation of the biological relevance of QTNs in conferring heat stress tolerance will enable their utilization in improving the reproductive stage heat stress tolerance in rice.

Genetic Analysis of a Collection of Rice Germplasm (Oryza sativa L.) through High-Density SNP Array Provides Useful Information for Further Breeding Practices

Traditional breeding strategies mainly focus on the evaluation of trait performance, but pay less attention to the changing genetic background. A comprehensive understanding of the genetic diversity of germplasms is crucial for the deliberate improvement of specific traits. A collection of 154 highland rice varieties were collected as the initial genetic resource in our breeding program to improve the pathogen resistance and eating and cooking qualities. These varieties were analyzed using a whole-genome SNP array and were clustered into three groups. Further analysis revealed that the favorable alleles of pathogen resistance genes are mostly absent in our collected varieties. However, it showed that most varieties possess favorable alleles of Waxy (Wx) and ALKALI DEGENERATION (ALK), which are able to enhance the eating and cooking qualities. Moreover, only about one fifth of all varieties harbors favorable the allele of fragrance gene Betainealdehyde dehydrogenase (BADH2). Together, these results give an overall view of the genetic constitution of the target traits, which provide useful information for future genetic improvement in breeding practices.

Current Research Trends and Prospects for Yield and Quality Improvement in Sesame, an Important Oilseed Crop

Climate change is shifting agricultural production, which could impact the economic and cultural contexts of the oilseed industry, including sesame. Environmental threats (biotic and abiotic stresses) affect sesame production and thus yield (especially oil content). However, few studies have investigated the genetic enhancement, quality improvement, or the underlying mechanisms of stress tolerance in sesame. This study reveals the challenges faced by farmers/researchers growing sesame crops and the potential genetic and genomic resources for addressing the threats, including: (1) developing sesame varieties that tolerate phyllody, root rot disease, and waterlogging; (2) investigating beneficial agro-morphological traits, such as determinate growth, prostrate habit, and delayed response to seed shattering; (3) using wild relatives of sesame for wide hybridization; and (4) advancing existing strategies to maintain sesame production under changing climatic conditions. Future research programs need to add technologies and develop the best research strategies for economic and sustainable development.

Development and Application of a Target Capture Sequencing SNP-Genotyping Platform in Rice

The development of efficient, robust, and high-throughput SNP genotyping platforms is pivotal for crop genetics and breeding. Recently, SNP genotyping platforms based on target capture sequencing, which is very flexible in terms of the number of SNP markers, have been developed for maize, cassava, and fava bean. We aimed to develop a target capture sequencing SNP genotyping platform for rice. A target capture sequencing panel containing 2565 SNPs, including 1225 SNPs informative for japonica and 1339 SNPs informative for indica, was developed. This platform was used in diversity analysis of 50 rice varieties. Of the 2565 SNP markers, 2341 (91.3%) produced useful polymorphic genotype data, enabling the production of a phylogenetic tree of the 50 varieties. The mean number of markers polymorphic between any two varieties was 854. The platform was used for QTL mapping of preharvest sprouting (PHS) resistance in an F₈ recombinant inbred line population derived from the cross Odae × Joun. A genetic map comprising 475 markers was constructed, and two QTLs for PHS resistance were identified on chromosomes 4 and 11. This system is a powerful tool for rice genetics and breeding and will facilitate QTL studies and gene mapping, germplasm diversity analysis, and marker-assisted selection.

Applications of Genomic Tools in Plant Breeding: Crop Biofortification

Crop breeding has mainly been focused on increasing productivity, either directly or by decreasing the losses caused by biotic and abiotic stresses (that is, incorporating resistance to diseases and enhancing tolerance to adverse conditions, respectively). Quite the opposite, little attention has been paid to improve the nutritional value of crops. It has not been until recently that crop biofortification has become an objective within breeding programs, through either conventional methods or genetic engineering. There are many steps along this long path, from the initial evaluation of germplasm for the content of nutrients and health-promoting compounds to the development of biofortified varieties, with the available and future genomic tools assisting scientists and breeders in reaching their objectives as well as speeding up the process. This review offers a compendium of the genomic technologies used to explore and create biodiversity, to associate the traits of interest to the genome, and to transfer the genomic regions responsible for the desirable characteristics into potential new varieties. Finally, a glimpse of future perspectives and challenges in this emerging area is offered by taking the present scenario and the slow progress of the regulatory framework as the starting point.

Identification of Heterotic Groups and Patterns Based on Genotypic and Phenotypic Characteristics Among Rice Accessions of Diverse Origins

Identification of the right parental combinations to maximize heterosis is the major goal of hybrid breeding, which could be achieved through identification of heterotic groups. The main objective of this study was to identify promising heterotic groups for future rice breeding programs. A collection of 359 rice genotypes of diverse origins of China and abroad, composed of inbreds, maintainers, restorers, and temperature-sensitive genic male sterile (TGMS) lines were genotyped using 10K SNP chips. The SNP data set was subjected to genomic analyses for estimation of genetic divergence and diversity. Significant variations were observed in the germplasm with the identification of six different genetic groups. These lines were assigned to the genetic groups independent of their origin. Taking an account of commercially used heterotic groups present in each cluster, three cytoplasmic male sterile (CMS) lines and 14 inbred and restorer lines with moderate to high genetic distances selected from five heterotic patterns were crossed and obtained 42 F1 hybrids. A total of 14 hybrids were found with significant maximum mid- and better-parent heterosis, namely, TaifengA × Guang122, TaifengA × Wushansimiao, and TaifengA × Minghui63 for earliness; Guang8A × Huazhan for dwarf stature; and Guang8A × Huanghuzhan-1, TaifengA × Yuexiangzhan, Guang8A × Minhui3301, TianfengA × Guang122, Guang8A × Yahui2115, TianfengA × Huanghuazhan, TianfengA × Minghui63, TianfengA × Minhui3301, TaifengA × Gui99, and Guang8A × Yuenongsimiao for yield and yield-related traits. Mid-parent and better-parent heterotic F1 hybrids were in positive correlation with the genetic distances as that manifested by commercially used heterotic groups, encouraging the use of genotypic data for identification of heterotic groups. Our study provides an informative strategy for the development of early maturing, lodging resistant and high-yielding commercial hybrids and cultivars in future heterosis breeding programs.

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.

Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing

Forest tree breeding efforts have focused mainly on improving traits of economic importance, selecting trees suited to new environments or generating trees that are more resilient to biotic and abiotic stressors. This review describes various methods of forest tree selection assisted by genomics and the main technological challenges and achievements in research at the genomic level. Due to the long rotation time of a forest plantation and the resulting long generation times necessary to complete a breeding cycle, the use of advanced techniques with traditional breeding have been necessary, allowing the use of more precise methods for determining the genetic architecture of traits of interest, such as genome-wide association studies (GWASs) and genomic selection (GS). In this sense, main factors that determine the accuracy of genomic prediction models are also addressed. In turn, the introduction of genome editing opens the door to new possibilities in forest trees and especially clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). It is a highly efficient and effective genome editing technique that has been used to effectively implement targetable changes at specific places in the genome of a forest tree. In this sense, forest trees still lack a transformation method and an inefficient number of genotypes for CRISPR/Cas9. This challenge could be addressed with the use of the newly developing technique GRF-GIF with speed breeding.

Plant Variety Protection: Current Practices and Insights

Breeders persistently supply farmers with the best varieties in order to exceed consumer demand through plant-breeding processes that are resource-intensive. In order to motivate continuous innovation in variety development, a system needs to provide incentives for plant breeders to develop superior varieties, for example, exclusive ownership to produce and market those varieties. The most common system is the acquisition of intellectual property protection through plant variety protection, also known as the breeder’s right. Most countries have adopted the system established by the International Union for the Protection of New Varieties of Plants (UPOV). To be granted plant variety protection, the variety should prove to be unique by meeting three requirements: distinctness, uniformity, and stability. This review summarizes (1) the plant variety protection via UPOV convention, (2) technical methods for distinctness, uniformity, and stability testing via phenotype, molecular markers, and sequencing as well as their challenges and potentiality, and (3) additional discussions in essentially derived variety, value for cultivation and use testing, and open source seed initiative.

Genetic relationships and identification of core germplasm among rice photoperiod- and thermo-sensitive genic male sterile lines

BACKGROUND

Harnessing heterosis is one of the major approaches to increase rice yield and has made a great contribution to food security. The identification and selection of outstanding parental genotypes especially among male sterile lines is a key step for exploiting heterosis. Two-line hybrid system is based on the discovery and application of photoperiod- and thermo-sensitive genic sensitive male sterile (PTGMS) materials. The development of wide-range of male sterile lines from a common gene pool leads to a narrower genetic diversity, which is vulnerable to biotic and abiotic stress. Hence, it is valuable to ascertain the genetic background of PTGMS lines and to understand their relationships in order to select and design a future breeding strategy.

RESULTS

A collection of 118 male sterile rice lines and 13 conventional breeding lines from the major rice growing regions of China was evaluated and screened against the photosensitive (pms3) and temperature sensitive male sterility (tms5) genes. The total gene pool was divided into four major populations as P1 possessing the pms3, P2 possessing tms5, P3 possessing both pms3 and tms5 genes, and P4 containing conventional breeding lines without any male sterility allele. The high genetic purity was revealed by homozygous alleles in all populations. The population admixture, principle components and the phylogenetic analysis revealed the close relations of P2 and P3 with P4. The population differentiation analysis showed that P1 has the highest differentiation coefficient. The lines from P1 were observed as the ancestors of other three populations in a phylogenetic tree, while the lines in P2 and P3 showed a close genetic relation with conventional lines. A core collection of top 10% lines with maximum within and among populations genetic diversity was constructed for future research and breeding efforts.

CONCLUSION

The low genetic diversity and close genetic relationship among PTGMS lines in P2, P3 and P4 populations suggest a selection sweep and they might result from a backcrossing with common ancestors including the pure lines of P1. The core collection from PTGMS panel updated with new diverse germplasm will serve best for further two-line hybrid breeding.

Designing Future Crops: Genomics-Assisted Breeding Comes of Age

Over the past decade, genomics-assisted breeding (GAB) has been instrumental in harnessing the potential of modern genome resources and characterizing and exploiting allelic variation for germplasm enhancement and cultivar development. Sustaining GAB in the future (GAB 2.0) will rely upon a suite of new approaches that fast-track targeted manipulation of allelic variation for creating novel diversity and facilitate their rapid and efficient incorporation in crop improvement programs. Genomic breeding strategies that optimize crop genomes with accumulation of beneficial alleles and purging of deleterious alleles will be indispensable for designing future crops. In coming decades, GAB 2.0 is expected to play a crucial role in breeding more climate-smart crop cultivars with higher nutritional value in a cost-effective and timely manner.

Emerging Molecular Strategies for Improving Rice Drought Tolerance

Rice occupies a pre-eminent position as a food crop in the world. Its production, how- ever, entails up to 3000 liters of water per kilogram of grain produced. Such high demand makes rice prone to drought easily. Sustainable rice cultivation with limited water resources requires the deployment of a suitable strategy for better water use efficiency and improved drought tolerance. Several drought-related genes have been evaluated in rice for their mode of action in conferring drought tolerance. Manipulation of components of abscisic acid signal transduction, stomatal density, deposition of cuticular wax, and protein modification pathways are emerging as priority targets. Gene reprogramming by microRNAs is also being explored to achieve drought tolerance. Genetically dissected Quantitative Trait Loci (QTLs) and their constituent genes are being deployed to develop drought-tolerant rice varieties. Progressive research and challenges include a better understanding of crucial components of drought response and search for new targets and the deployment of improved varieties in the field.

Recent Advances of Genetic Resources, Genes and Genetic Approaches for Flooding Tolerance in Rice

Flooding is one of the most hazardous natural disasters and a major stress constraint to rice production throughout the world, which results in huge economic losses. The frequency and duration of flooding is predicted to increase in near future as a result of global climate change. Breeding of flooding tolerance in rice is a challenging task because of the complexity of the component traits, screening technique, environmental factors and genetic interactions. A great progress has been made during last two decades to find out the flooding tolerance mechanism in rice. An important breakthrough in submergence research was achieved by the identification of major quantitative trait locus (QTL) SUB1 in rice chromosomes that acts as the primary contributor for tolerance. This enabled the use of marker-assisted backcrossing (MABC) to transfer SUB1 QTL into popular varieties which showed yield advantages in flood prone areas. However, SUB1 varieties are not always tolerant to stagnant flooding and flooding during germination stage. So, gene pyramiding approach can be used by combining several important traits to develop new breeding rice lines that confer tolerances to different types of flooding. This review highlights the important germplasm/genetic resources of rice to different types of flooding stress. A brief discussion on the genes and genetic mechanism in rice exhibited to different types of flooding tolerance was discussed for the development of flood tolerant rice variety. Further research on developing multiple stresses tolerant rice can be achieved by combining SUB1 with other tolerance traits/genes for wider adaptation in the rain-fed rice ecosystems.

How array design creates SNP ascertainment bias

Single nucleotide polymorphisms (SNPs), genotyped with arrays, have become a widely used marker type in population genetic analyses over the last 10 years. However, compared to whole genome re-sequencing data, arrays are known to lack a substantial proportion of globally rare variants and tend to be biased towards variants present in populations involved in the development process of the respective array. This affects population genetic estimators and is known as SNP ascertainment bias. We investigated factors contributing to ascertainment bias in array development by redesigning the Axiom^™ Genome-Wide Chicken Array in silico and evaluating changes in allele frequency spectra and heterozygosity estimates in a stepwise manner. A sequential reduction of rare alleles during the development process was shown. This was mainly caused by the identification of SNPs in a limited set of populations and a within-population selection of common SNPs when aiming for equidistant spacing. These effects were shown to be less severe with a larger discovery panel. Additionally, a generally massive overestimation of expected heterozygosity for the ascertained SNP sets was shown. This overestimation was 24% higher for populations involved in the discovery process than not involved populations in case of the original array. The same was observed after the SNP discovery step in the redesign. However, an unequal contribution of populations during the SNP selection can mask this effect but also adds uncertainty. Finally, we make suggestions for the design of specialized arrays for large scale projects where whole genome re-sequencing techniques are still too expensive.

Genome-Wide Association Study Reveals Marker-Trait Associations for Early Vegetative Stage Salinity Tolerance in Rice

Rice germplasm is a rich resource for discovering genes associated with salt tolerance. In the current study, a set of 96 accessions were evaluated for seedling stage salinity tolerance and its component traits. Significant phenotypic variation was observed among the genotypes for all the measured traits and eleven accessions with high level of salt tolerance at seedling stage were identified. The germplasm set comprised of three sub-populations and genome-wide association study (GWAS) identified a total of 23 marker-trait associations (MTAs) for traits studied. These MTAs were located on rice chromosomes 1, 2, 5, 6, 7, 9, and 12 and explained the trait phenotypic variances ranging from 13.98 to 29.88 %. Twenty-one MTAs identified in this study were located either in or near the previously reported quantitative trait loci (QTLs), while two MTAs namely, qSDW2.1 and qSNC5 were novel. A total of 18 and 13 putative annotated candidate genes were identified in a genomic region spanning ~200 kb around the MTAs qSDW2.1 and qSNC5, respectively. Some of the important genes underlying the novel MTAs were OsFBA1,OsFBL7, and mTERF which are known to be associated with salinity tolerance in crops. These MTAs pave way for combining salinity tolerance with high yield in rice genotypes through molecular breeding.

Genomic resources in plant breeding for sustainable agriculture

Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, conventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965-85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker-assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture.

Development of a highly efficient 50K single nucleotide polymorphism genotyping array for the large and complex genome of Norway spruce (Picea abies L. Karst) by whole genome resequencing and its transferability to other spruce species

Norway spruce (Picea abies L. Karst) is one of the most important forest tree species with significant economic and ecological impact in Europe. For decades, genomic and genetic studies on Norway spruce have been challenging due to the large and repetitive genome (19.6 Gb with more than 70% being repetitive). To accelerate genomic studies, including population genetics, genome‐wide association studies (GWAS) and genomic selection (GS), in Norway spruce and related species, we here report on the design and performance of a 50K single nucleotide polymorphism (SNP) genotyping array for Norway spruce. The array is developed based on whole genome resequencing (WGS), making it the first WGS‐based SNP array in any conifer species so far. After identifying SNPs using genome resequencing data from 29 trees collected in northern Europe, we adopted a two‐step approach to design the array. First, we built a 450K screening array and used this to genotype a population of 480 trees sampled from both natural and breeding populations across the Norway spruce distribution range. These samples were then used to select high‐confidence probes that were put on the final 50K array. The SNPs selected are distributed over 45,552 scaffolds from the P. abies version 1.0 genome assembly and target 19,954 unique gene models with an even coverage of the 12 linkage groups in Norway spruce. We show that the array has a 99.5% probe specificity, >98% Mendelian allelic inheritance concordance, an average sample call rate of 96.30% and an SNP call rate of 98.90% in family trios and haploid tissues. We also observed that 23,797 probes (50%) could be identified with high confidence in three other spruce species (white spruce [Picea glauca], black spruce [P. mariana] and Sitka spruce [P. sitchensis]). The high‐quality genotyping array will be a valuable resource for genetic and genomic studies in Norway spruce as well as in other conifer species of the same genus.

A genome-wide association study in Indian wild rice accessions for resistance to the root-knot nematode Meloidogyne graminicola

Rice root-knot nematode (RRKN), Meloidogyne graminicola is one of the major biotic constraints in rice-growing countries of Southeast Asia. Host plant resistance is an environmentally-friendly and cost-effective mean to mitigate RRKN damage to rice. Considering the limited availability of genetic resources in the Asian rice (Oryza sativa) cultivars, exploration of novel sources and genetic basis of RRKN resistance is necessary. We screened 272 diverse wild rice accessions (O. nivara, O. rufipogon, O. sativa f. spontanea) to identify genotypes resistant to RRKN. We dissected the genetic basis of RRKN resistance using a genome-wide association study with SNPs (single nucleotide polymorphism) genotyped by 50K "OsSNPnks" genic Affymetrix chip. Population structure analysis revealed that these accessions were stratified into three major sub-populations. Overall, 40 resistant accessions (nematode gall number and multiplication factor/MF < 2) were identified, with 17 novel SNPs being significantly associated with phenotypic traits such as number of galls, egg masses, eggs/egg mass and MF per plant. SNPs were localized to the quantitative trait loci (QTL) on chromosome 1, 2, 3, 4, 6, 10 and 11 harboring the candidate genes including NBS-LRR, Cf2/Cf5 resistance protein, MYB, bZIP, ARF, SCARECROW and WRKY transcription factors. Expression of these identified genes was significantly (P < 0.01) upregulated in RRKN-infected plants compared to mock-inoculated plants at 7 days after inoculation. The identified SNPs enrich the repository of candidate genes for future marker-assisted breeding program to alleviate the damage of RRKN in rice.

Development of a single nucleotide polymorphism array for population genomic studies in four European pine species

Pines are some of the most ecologically and economically important tree species in the world, and many have enormous natural distributions or have been extensively planted. However, a lack of rapid genotyping capability is hampering progress in understanding the molecular basis of genetic variation in these species. Here, we deliver an efficient tool for genotyping thousands of single nucleotide polymorphism (SNP) markers across the genome that can be applied to genetic studies in pines. Polymorphisms from resequenced candidate genes and transcriptome sequences of P. sylvestris, P. mugo, P. uncinata, P. uliginosa and P. radiata were used to design a 49,829 SNP array (Axiom_PineGAP, Thermo Fisher). Over a third (34.68%) of the unigenes identified from the P. sylvestris transcriptome were represented on the array, which was used to screen samples of four pine species. The conversion rate for the array on all samples was 42% (N = 20,795 SNPs) and was similar for SNPs sourced from resequenced candidate gene and transcriptome sequences. The broad representation of gene ontology terms by unigenes containing converted SNPs reflected their coverage across the full transcriptome. Over a quarter of successfully converted SNPs were polymorphic among all species, and the data were successful in discriminating among the species and some individual populations. The SNP array provides a valuable new tool to advance genetic studies in these species and demonstrates the effectiveness of the technology for rapid genotyping in species with large and complex genomes.

Role of NGS and SNP genotyping methods in sugarcane improvement programs

Sugarcane (Saccharum spp.) is one of the most economically significant crops because of its high sucrose content and it is a promising biomass feedstock for biofuel production. Sugarcane genome sequencing and analysis is a difficult task due to its heterozygosity and polyploidy. Long sequence read technologies, PacBio Single-Molecule Real-Time (SMRT) sequencing, the Illumina TruSeq, and the Oxford Nanopore sequencing could solve the problem of genome assembly. On the applications side, next generation sequencing (NGS) technologies played a major role in the discovery of single nucleotide polymorphism (SNP) and the development of low to high throughput genotyping platforms. The two mainstream high throughput genotyping platforms are the SNP microarray and genotyping by sequencing (GBS). This paper reviews the NGS in sugarcane genomics, genotyping methodologies, and the choice of these methods. Array-based SNP genotyping is robust, provides consistent SNPs, and relatively easier downstream data analysis. The GBS method identifies large scale SNPs across the germplasm. A combination of targeted GBS and array-based genotyping methods should be used to increase the accuracy of genomic selection and marker-assisted breeding.

Genome-wide association studies using 50 K rice genic SNP chip unveil genetic architecture for anaerobic germination of deep-water rice population of Assam, India

North Eastern part of India such as Assam is inundated by flood every year where the farmers are forced to grow the traditional tall deep-water rice. Genetic improvement of this type of rice is slow because of insufficient knowledge about their genetic architecture and population structure. In the present investigation, the genetic diversity architecture of 94 deep-water rice genotypes of Assam and association mapping strategy was, for the first time, applied to determine the significant SNPs and genes for deep-water rice. These genotypes are known for their unique elongation ability under deep-water condition. The anaerobic germination (AG) related trait-associated genes identified here can provide affluent resources for rice breeding especially in flood-prone areas. We investigated the genome-wide association studies (GWAS) using 50 K rice genic SNP chip across 94 deep-water rice genotypes collected from different flood-prone districts/villages of Assam. Population structure and diversity analysis revealed that these genotypes were stratified into four sub-populations. Using GWAS approach, 20 significant genes were identified and found to be associated with AG-related traits. Of them, two most relevant genes (OsXDH1and SSXT) have been identified which explain phenotypic variability (R² > 20%) in the population. These genes were located in Chr 3 (LOC_Os03g31550) which encodes for enzyme xanthine dehydrogenase 1(OsXDH1) and in Chr 12 (LOC_Os12g31350) which encodes for SSXT family protein. Both of these genes were found to be associated with anaerobic response index (increase in the coleoptile length under water in anaerobic condition with respect to control), respectively. Interestingly, OsXDH1is involved in purine catabolism pathway and acts as a scavenger of reactive oxygen species in plants, whereas SSXT is GRF1-interacting factor 3. These two candidate genes associated with AG of deep-water rice have been found to be reported for the first time. Thus, this study provides a greater resource for breeders not only for improvement of deep-water rice, but also for AG tolerant variety useful for direct-seeded rice in flood-affected areas.

Recommendations for Choosing the Genotyping Method and Best Practices for Quality Control in Crop Genome-Wide Association Studies

High-throughput genotyping boosts genome-wide association studies (GWAS) in crop species, leading to the identification of single-nucleotide polymorphisms (SNPs) associated with economically important traits. Choosing a cost-effective genotyping method for crop GWAS requires careful examination of several aspects, namely, the purpose and the scale of the study, crop-specific genomic features, and technical and economic matters associated with each genotyping option. Once genotypic data have been obtained, quality control (QC) procedures must be applied to avoid bias and false signals in genotype–phenotype association tests. QC for human GWAS has been extensively reviewed; however, QC for crop GWAS may require different actions, depending on the GWAS population type. Here, we review most popular genotyping methods based on next-generation sequencing (NGS) and array hybridization, and report observations that should guide the investigator in the choice of the genotyping method for crop GWAS. We provide recommendations to perform QC in crop species, and deliver an overview of bioinformatics tools that can be used to accomplish all needed tasks. Overall, this work aims to provide guidelines to harmonize those procedures leading to SNP datasets ready for crop GWAS.

Improving nutritional quality of rice for human health

This review surveys rice nutritional value, mainly focusing on breeding achievements via adoption of both genetic engineering and non-transgenic strategies to improve key nutrients associated with human health. Rice (Oryza sativa) is an essential component of the diets and livelihoods of over 3.5 billion people. Polished rice is mostly consumed as staple food, fulfilling daily energy demands and part of the protein requirement. Brown rice is comparatively more nutritious, containing more lipids, minerals, vitamins, dietary fiber, micronutrients, and bioactive compounds. In this article, we review the nutritional facts about rice including the level of γ-aminobutyric acid, resistant starch, lysine, iron, zinc, β-carotene, folate, anthocyanin, various carotenoids, and flavonoids, focusing on their synthesis and metabolism and the advances in their biofortification via adoption of both conventional and genetic engineering strategies. We conclude that besides representing a staple food, rice has the potential to become a source of various essential nutrients or bioactive compounds through appropriate genetic improvements to benefit human health and prevent certain chronic diseases. Finally, we discuss the available, non-genetically engineering strategies for the nutritional improvement of rice, including their main strengths and constraints.

Genome-Wide Association Study Reveals Novel Marker-Trait Associations (MTAs) Governing the Localization of Fe and Zn in the Rice Grain

Micronutrient malnutrition due to Fe and Zn, affects around two billion people globally particularly in the developing countries. More than 90% of the Asian population is dependent on rice-based diets, which is low in these micronutrients. In the present study, a set of 192 Indian rice germplasm accessions, grown at two locations, were evaluated for Fe and Zn in brown rice (BR) and milled rice (MR). A significant variation was observed in the rice germplasm for these micronutrients. The grain Fe concentration was in the range of 6.2–23.1 ppm in BR and 0.8–12.3 ppm in MR, while grain Zn concentration was found to be in the range of 11.0–47.0 ppm and 8.2–40.8 ppm in the BR and MR, respectively. Grain Fe exhibited maximum loss upon milling with a mean retention of 24.9% in MR, while Zn showed a greater mean retention of 74.2% in MR. A genome-wide association study (GWAS) was carried out implementing the FarmCPU model to control the population structure and kinship, and resulted in the identification of 29 marker-trait associations (MTAs) with significant associations for traits viz. FeBR (6 MTAs), FeMR (7 MTAs), ZnBR (11 MTAs), and ZnMR (5 MTAs), which could explain the phenotypic variance from 2.1 to as high as 53.3%. The MTAs governing the correlated traits showed co-localization, signifying the possibility of their simultaneous improvement. The robust MTAs identified in the study could be valuable resource for enhancing Fe and Zn concentration in the rice grain and addressing the problem of Fe and Zn malnutrition among rice consumers.

A 62K genic-SNP chip array for genetic studies and breeding applications in pigeonpea (Cajanus cajan L. Millsp.)

Pigeonpea is the second most important pulse legume crop for food and nutritional security of South Asia that requires accelerated breeding using high throughput genomic tools. Single nucleotide polymorphisms (SNPs) are highly suitable markers for this purpose because of their bi-allelic nature, reproducibility and high abundance in the genome. Here we report on development and use of a pigeonpea 62 K SNP chip array ‘CcSNPnks’ for Affymetrix GeneTitan^® platform. The array was designed after filtering 645,662 genic-SNPs identified by re-sequencing of 45 diverse genotypes and has 62,053 SNPs from 9629 genes belonging to five different categories, including 4314 single-copy genes unique to pigeonpea, 4328 single-copy genes conserved between soybean and pigeonpea, 156 homologs of agronomically important cloned genes, 746 disease resistance and defense response genes and 85 multi-copy genes of pigeonpea. This fully genic chip has 28.94% exonic, 33.04% intronic, 27.56% 5′UTR and 10.46% 3′UTR SNPs and incorporates multiple SNPs per gene allowing gene haplotype network analysis. It was used successfully for the analysis of genetic diversity and population structure of 95 pigeonpea varieties and high resolution mapping of 11 yield related QTLs for number of branches, pod bearing length and number of seeds per pod in a biparental RIL population. As an accurate high-density genotyping tool, ‘CcSNPnks’ chip array will be useful for high resolution fingerprinting, QTL mapping and genome wide as well as gene-based association studies in pigeonpea.

Population genetic structure and maternal lineage of South African crossbred Nguni cattle using the cytochrome b gene in mtDNA

The Nguni cattle breed predominates South Africa and is endowed with traits favourable against environmental stressors such as heat stress and resistance to diseases. Interventions to improve production have led to the erosion of the genetic integrity of local breeds and the introduction of exotic breeds has proved ineffective as they fail to perform well due to different climatic conditions and production systems. In this study, the genetic structure and genetic lineage of Nguni crossbreds from 6 populations were assessed using the mitochondrial cytochrome b gene. Twelve polymorphic sites were detected resulting in 11 haplotypes with haplotype and nucleotide diversities of 0.550 ± 0.135 and 0.0019 ± 0.0011, respectively. Only 2 of the 6 populations displayed recent population expansion events, whereas the majority adhered to neutral evolution. The basal haplotype contained approximately 60% of the studied populations and there were four unique haplotypes that were revealed. A possible Nguni descript haplotype was uncovered, and this haplotype was found in all populations but was however devoid of individuals from around the world. The genetic structure of the populations was rather low (average pairwise F_ST = 0.066 and Slatkins F_ST = 0.094), and approximately 96% of the total genetic variation was accounted for by differences within populations. Phylogenetic analyses supported the clustering of all the samples within the Bos taurus clade and no Bos indicus haplotype was detected. Furthermore, no intermediate haplotype of taurine and indicine was detected. Overall, the maternal lineage of the crossbreds points to a taurine origin and the low genetic diversity depicts the retention of the Nguni genetic pool and possibly its superior adaptive traits.

In Silico Identification of QTL-Based Polymorphic Genes as Salt-Responsive Potential Candidates through Mapping with Two Reference Genomes in Rice

Recent advances in next generation sequencing have created opportunities to directly identify genetic loci and candidate genes for abiotic stress responses in plants. With the objective of identifying candidate genes within the previously identified QTL-hotspots, the whole genomes of two divergent cultivars for salt responses, namely At 354 and Bg 352, were re-sequenced using Illumina Hiseq 2500 100PE platform and mapped to Nipponbare and R498 genomes. The sequencing results revealed approximately 2.4 million SNPs and 0.2 million InDels with reference to Nipponbare while 1.3 million and 0.07 million with reference to R498 in two parents. In total, 32,914 genes were reported across all rice chromosomes of this study. Gene mining within QTL hotspots revealed 1236 genes, out of which 106 genes were related to abiotic stress. In addition, 27 abiotic stress-related genes were identified in non-QTL regions. Altogether, 32 genes were identified as potential genes containing polymorphic non-synonymous SNPs or InDels between two parents. Out of 10 genes detected with InDels, tolerant haplotypes of Os01g0581400, Os10g0107000, Os11g0655900, Os12g0622500, and Os12g0624200 were found in the known salinity tolerant donor varieties. Our findings on different haplotypes would be useful in developing resilient rice varieties for abiotic stress by haplotype-based breeding studies.

An Axiom SNP genotyping array for Douglas-fir

BACKGROUND

In forest trees, genetic markers have been used to understand the genetic architecture of natural populations, identify quantitative trait loci, infer gene function, and enhance tree breeding. Recently, new, efficient technologies for genotyping thousands to millions of single nucleotide polymorphisms (SNPs) have finally made large-scale use of genetic markers widely available. These methods will be exceedingly valuable for improving tree breeding and understanding the ecological genetics of Douglas-fir, one of the most economically and ecologically important trees in the world.

RESULTS

We designed SNP assays for 55,766 potential SNPs that were discovered from previous transcriptome sequencing projects. We tested the array on ~ 2300 related and unrelated coastal Douglas-fir trees (Pseudotsuga menziesii var. menziesii) from Oregon and Washington, and 13 trees of interior Douglas-fir (P. menziesii var. glauca). As many as ~ 28 K SNPs were reliably genotyped and polymorphic, depending on the selected SNP call rate. To increase the number of SNPs and improve genome coverage, we developed protocols to 'rescue' SNPs that did not pass the default Affymetrix quality control criteria (e.g., 97% SNP call rate). Lowering the SNP call rate threshold from 97 to 60% increased the number of successful SNPs from 20,669 to 28,094. We used a subset of 395 unrelated trees to calculate SNP population genetic statistics for coastal Douglas-fir. Over a range of call rate thresholds (97 to 60%), the median call rate for SNPs in Hardy-Weinberg equilibrium ranged from 99.2 to 99.7%, and the median minor allele frequency ranged from 0.198 to 0.233. The successful SNPs also worked well on interior Douglas-fir.

CONCLUSIONS

Based on the original transcriptome assemblies and comparisons to version 1.0 of the Douglas-fir reference genome, we conclude that these SNPs can be used to genotype about 10 K to 15 K loci. The Axiom genotyping array will serve as an excellent foundation for studying the population genomics of Douglas-fir and for implementing genomic selection. We are currently using the array to construct a linkage map and test genomic selection in a three-generation breeding program for coastal Douglas-fir.

Introgressed Saltol QTL Lines Improves the Salinity Tolerance in Rice at Seedling Stage

Rice is a staple food crop in Asia and plays a crucial role in the economy of this region. However, production of rice and its cultivating areas are under constant threat of soil salinity. A major QTL, Saltol, responsible for salinity tolerance at seedling stage has been mapped on chromosome 1 using Pokkali/IR29 Recombinant Inbred Lines (RIL) population. The present study was aimed to incorporate Saltol Quantitative Trait Loci (QTL) in two high yielding mega rice varieties i.e. Pusa44 and Sarjoo52 through Marker Assisted Backcross Breeding (MABB). To improve the seedling stage salinity tolerance in these cultivars, we introgressed the Saltol QTL from donor parent FL478 a derivative of Pokkali. A total of three backcrosses (BC₃) followed by selfing have led to successful introgression of Saltol QTL. Foreground selection at each breeding cycle was done using micro-satellite markers RM3412 and AP3206 to confirm Saltol QTL. The precise transfer of Saltol region was established using recombinant selection through flanking markers RM493 and G11a. Finally, 10 Saltol near isogenic lines (NILs) of Pusa44 and eight NILs of Sarjoo52 were successfully developed. These NILs (BC₃F₄) were evaluated for seedling stage salinity under hydroponic system. The NILs PU99, PU176, PU200, PU215, PU229, PU240, PU241, PU244, PU252, PU263 of Pusa44 and SAR17, SAR23, SAR35, SAR39, SAR77, SAR87, SAR123, SAR136 NILs of Sarjoo52 confirmed tolerance to salinity with low salt injury score of 3 or 5. Ratio of Na⁺/K⁺ content of Saltol NILs ranged from 1.26 to 1.85 in Pusa44 and 1.08 to 1.69 in Sarjoo52. The successfully developed NILs were further phenotyped stringently for morphological traits to estimate Phenotypic Recovery. Background selection of NILs along with parents was carried out with 50K SNP chip and recovered 94.83-98.38% in Pusa44 NILs and 94.51 to 98.31% in Sarjoo52 NILs of recurrent genome. The present study of MAB has accelerated the development of salt tolerant lines in the genetic background of Pusa44 and Sarjoo52. These NILs could be used for commercial cultivation in saline affected area.

Genotyping-by-sequencing based QTL mapping for rice grain yield under reproductive stage drought stress tolerance

QTLs for rice grain yield under reproductive stage drought stress (qDTY) identified earlier with low density markers have shown linkage drag and need to be fine mapped before their utilization in breeding programs. In this study, genotyping-by-sequencing (GBS) based high-density linkage map of rice was developed using two BC₁F₃ mapping populations namely Swarna*2/Dular (3929 SNPs covering 1454.68 cM) and IR11N121*2/Aus196 (1191 SNPs covering 1399.68 cM) with average marker density of 0.37 cM to 1.18 cM respectively. In total, six qDTY QTLs including three consistent effect QTLs were identified in Swarna*2/Dular while eight qDTY QTLs including two consistent effect QTLs were identified in IR11N121*2/Aus 196 mapping population. Comparative analysis revealed four stable and novel QTLs (qDTY_2.4, qDTY_3.3, qDTY_6.3, and qDTY_11.2) which explained 8.62 to 14.92% PVE. However, one of the identified stable grain yield QTL qDTY_1.1 in both the populations was located nearly at the same physical position of an earlier mapped major qDTY QTL. Further, the effect of the identified qDTY_1.1 was validated in a subset of lines derived from five mapping populations confirming robustness of qDTY_1.1 across various genetic backgrounds/seasons. The study successfully identified stable grain yield QTLs free from undesirable linkages of tall plant height/early maturity utilizing high density linkage maps.

1k-RiCA (1K-Rice Custom Amplicon) a novel genotyping amplicon-based SNP assay for genetics and breeding applications in rice

BACKGROUND

While a multitude of genotyping platforms have been developed for rice, the majority of them have not been optimized for breeding where cost, turnaround time, throughput and ease of use, relative to density and informativeness are critical parameters of their utility. With that in mind we report the development of the 1K-Rice Custom Amplicon, or 1k-RiCA, a robust custom sequencing-based amplicon panel of ~ 1000-SNPs that are uniformly distributed across the rice genome, designed to be highly informative within indica rice breeding pools, and tailored for genomic prediction in elite indica rice breeding programs.

RESULTS

Empirical validation tests performed on the 1k-RiCA showed average marker call rates of 95% with marker repeatability and concordance rates of 99%. These technical properties were not affected when two common DNA extraction protocols were used. The average distance between SNPs in the 1k-RiCA was 1.5 cM, similar to the theoretical distance which would be expected between 1,000 uniformly distributed markers across the rice genome. The average minor allele frequencies on a panel of indica lines was 0.36 and polymorphic SNPs estimated on pairwise comparisons between indica by indica accessions and indica by japonica accessions were on average 430 and 450 respectively. The specific design parameters of the 1k-RiCA allow for a detailed view of genetic relationships and unambiguous molecular IDs within indica accessions and good cost vs. marker-density balance for genomic prediction applications in elite indica germplasm. Predictive abilities of Genomic Selection models for flowering time, grain yield, and plant height were on average 0.71, 0.36, and 0.65 respectively based on cross-validation analysis. Furthermore the inclusion of important trait markers associated with 11 different genes and QTL adds value to parental selection in crossing schemes and marker-assisted selection in forward breeding applications.

CONCLUSIONS

This study validated the marker quality and robustness of the 1k-RiCA genotypic platform for genotyping populations derived from indica rice subpopulation for genetic and breeding purposes including MAS and genomic selection. The 1k-RiCA has proven to be an alternative cost-effective genotyping system for breeding applications.

The rice genome revolution: from an ancient grain to Green Super Rice

Rice is a staple crop for half the world's population, which is expected to grow by 3 billion over the next 30 years. It is also a key model for studying the genomics of agroecosystems. This dual role places rice at the centre of an enormous challenge facing agriculture: how to leverage genomics to produce enough food to feed an expanding global population. Scientists worldwide are investigating the genetic variation among domesticated rice species and their wild relatives with the aim of identifying loci that can be exploited to breed a new generation of sustainable crops known as Green Super Rice.

Detection of stable QTLs for grain protein content in rice (Oryza sativa L.) employing high throughput phenotyping and genotyping platforms

Lack of appropriate donors, non-utilization of high throughput phenotyping and genotyping platforms with high genotype × environment interaction restrained identification of robust QTLs for grain protein content (GPC) in rice. In the present investigation a  BC₃F₄ mapping population was developed using grain protein donor, ARC10075 and high-yielding cultivar Naveen and 190 lines were genotyped using 40 K Affimetrix custom SNP array with the objective to identify stable QTLs for protein content. Three of the identified QTLs, one for GPC (qGPC1.1) and the other two for single grain protein content (qSGPC2.1, qSGPC7.1) were stable over the environments explaining  13%, 14% and 7.8% of the phenotypic variances, respectively. Stability and repeatability of these additive QTLs were supported by the synergistic additive effects of multi-environmental-QTLs. One epistatic-QTL, independent of  the  main effect QTL was detected over the environment for SGPC. A few functional genes governing seed storage protein were hypothesised inside these identified QTLs. The qGPC1.1 was validated by NIR Spectroscopy-based high throughput phenotyping in BC₃F₅ population. Higher glutelin content was estimated in high-protein lines with the introgression of qGPC1.1 in telomeric region of short arm of chromosome 1. This was supported by the postulation of probable candidate gene inside this QTL region encoding glutelin family proteins.

Multi-omics approaches for strategic improvement of stress tolerance in underutilized crop species: A climate change perspective

For several decades, researchers are working toward improving the "major" crops for better adaptability and tolerance to environmental stresses. However, little or no research attention is given toward neglected and underutilized crop species (NUCS) which hold the potential to ensure food and nutritional security among the ever-growing global population. NUCS are predominantly climate resilient, but their yield and quality are compromised due to selective breeding. In this context, the importance of omics technologies namely genomics, transcriptomics, proteomics, phenomics and ionomics in delineating the complex molecular machinery governing growth, development and stress responses of NUCS is underlined. However, gaining insights through individual omics approaches will not be sufficient to address the research questions, whereas integrating these technologies could be an effective strategy to decipher the gene function, genome structures, biological pathways, metabolic and regulatory networks underlying complex traits. Given this, the chapter enlists the importance of NUCS in food and nutritional security and provides an overview of deploying omics approaches to study the NUCS. Also, the chapter enumerates the status of crop improvement programs in NUCS and suggests implementing "integrating omics" for gaining a better understanding of crops' response to abiotic and biotic stresses.

Development and use of chromosome segment substitution lines as a genetic resource for crop improvement

CSSLs are a complete library of introgression lines with chromosomal segments of usually a distant genotype in an adapted background and are valuable genetic resources for basic and applied research on improvement of complex traits. Chromosome segment substitution lines (CSSLs) are genetic stocks representing the complete genome of any genotype in the background of a cultivar as overlapping segments. Ideally, each CSSL has a single chromosome segment from the donor with a maximum recurrent parent genome recovered in the background. CSSL development program requires population-wide backcross breeding and genome-wide marker-assisted selection followed by selfing. Each line in a CSSL library has a specific marker-defined large donor segment. CSSLs are evaluated for any target phenotype to identify lines significantly different from the parental line. These CSSLs are then used to map quantitative trait loci (QTLs) or causal genes. CSSLs are valuable prebreeding tools for broadening the genetic base of existing cultivars and harnessing the genetic diversity from the wild- and distant-related species. These are resources for genetic map construction, mapping QTLs, genes or gene interactions and their functional analysis for crop improvement. In the last two decades, the utility of CSSLs in identification of novel genomic regions and QTL hot spots influencing a wide range of traits has been well demonstrated in food and commercial crops. This review presents an overview of how CSSLs are developed, their status in major crops and their use in genomic studies and gene discovery.

Development and Application of High-Density Axiom Cajanus SNP Array with 56K SNPs to Understand the Genome Architecture of Released Cultivars and Founder Genotypes

As one of the major outputs of next-generation sequencing (NGS), a large number of genome-wide single-nucleotide polymorphisms (SNPs) have been developed in pigeonpea [ (L.) Huth.]. However, SNPs require a genotyping platform or assay to be used in different evolutionary studies or in crop improvement programs. Therefore, we developed an Axiom SNP array with 56K SNPs uniformly distributed across the genome and assessed its utility in a genetic diversity study. From the whole-genome resequencing (WGRS) data on 104 pigeonpea lines, ∼2 million sequence variations (SNPs and insertion-deletions [InDels]) were identified, from which a subset of 56,512 unique and informative sequence variations were selected to develop the array. The Axiom SNP array developed was used for genotyping 103 pigeonpea lines encompassing 63 cultivars released between 1960 and 2014 and 40 breeding, germplasm, and founder lines. Genotyping data thus generated on 103 pigeonpea lines provided 51,201 polymorphic SNPs and InDels. Genetic diversity analysis provided in-depth insights into the genetic architecture and trends in temporal diversity in pigeonpea cultivars. Therefore, the continuous use of the high-density Axiom SNP array developed will accelerate high-resolution trait mapping, marker-assisted breeding, and genomic selection efforts in pigeonpea.

DNA fingerprinting at farm level maps rice biodiversity across Bangladesh and reveals regional varietal preferences

The development, dissemination, and adoption of improved rice varieties are imperative for global food and nutritional security. Knowledge of the crop's distribution across agro-ecologies is important for impact assessment studies, varietal replacement strategies, and the development and implementation of agricultural policies. Bangladesh is the world's 4th largest rice producer. Though traditional varieties (TVs) are abundant and valued throughout Bangladesh, population growth and vulnerability to climate change, necessitate efficient deployment of high-yielding stress-tolerant modern varieties (MVs). To aid agricultural policy and strategy this study aimed to accurately assess the distribution of MVs and TVs across Bangladesh during the rainfed rice-growing season. Information derived from a survey of rice production areas were compared and combined with DNA fingerprinting information from the same locations. Biodiversity of Bangladesh rice remained high. While TVs and first generation MVs of Bangladeshi and Indian origin were still commonly grown, recently released stress-tolerant MVs were adopted in large proportions in several districts. Although farmers successfully distinguished TVs from MVs grown in their fields, a considerable lack of authenticity among MVs was observed, pinpointing shortcomings in the seed supply chain. This study identifies focal points for extension work and validates DNA fingerprinting as reliable method for impact assessment studies.

Wild Relatives of Maize, Rice, Cotton, and Soybean: Treasure Troves for Tolerance to Biotic and Abiotic Stresses

Global food demand is expected to nearly double by 2050 due to an increase in the world's population. The Green Revolution has played a key role in the past century by increasing agricultural productivity worldwide, however, limited availability and continued depletion of natural resources such as arable land and water will continue to pose a serious challenge for global food security in the coming decades. High yielding varieties with proven tolerance to biotic and abiotic stresses, superior nutritional profiles, and the ability to adapt to the changing environment are needed for continued agricultural sustainability. The narrow genetic base of modern cultivars is becoming a major bottleneck for crop improvement efforts and, therefore, the use of crop wild relatives (CWRs) is a promising approach to enhance genetic diversity of cultivated crops. This article provides a review of the efforts to date on the exploration of CWRs as a source of tolerance to multiple biotic and abiotic stresses in four global crops of importance; maize, rice, cotton, and soybean. In addition to the overview of the repertoire and geographical spread of CWRs in each of the respective crops, we have provided a comprehensive discussion on the morphological and/or genetic basis of the traits along with some examples, when available, of the research in the transfer of traits from CWRs to cultivated varieties. The emergence of modern molecular and genomic technologies has not only accelerated the pace of dissecting the genetics underlying the traits found in CWRs, but also enabled rapid and efficient trait transfer and genome manipulation. The potential and promise of these technologies has also been highlighted in this review.