Genome-wide association studies of 14 agronomic traits in rice landraces

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.

Genome-wide association of single nucleotide polymorphism loci and candidate genes for frogeye leaf spot (Cercospora sojina) resistance in soybean

BACKGROUND

Frogeye leaf spot (FLS) is a destructive fungal disease that affects soybean production. The most economical and effective strategy to control FLS is the use of resistant cultivars. However, the use of a limited number of resistant loci in FLS management will be countered by the emergence of new high-virulence Cercospora sojina races. Therefore, we identified quantitative trait loci (QTL) that control resistance to FLS and identified novel resistant genes using a genome-wide association study (GWAS) on 234 Chinese soybean cultivars.

RESULTS

A total of 30,890 single nucleotide polymorphism (SNP) markers were used to estimate linkage disequilibrium (LD) and population structure. The GWAS results showed four loci (p < 0.0001) distributed over chromosomes (Chr.) 5 and 20, that are significantly associated with FLS resistance. No previous studies have reported resistance loci in these regions. Subsequently, 45 genes in the two resistance-related haplotype blocks were annotated. Among them, Glyma20g31630 encoding pyruvate dehydrogenase (PDH), Glyma05g28980, which encodes mitogen-activated protein kinase 7 (MPK7), and Glyma20g31510, Glyma20g31520 encoding calcium-dependent protein kinase 4 (CDPK4) in the haplotype blocks deserves special attention.

CONCLUSIONS

This study showed that GWAS can be employed as an effective strategy for identifying disease resistance traits in soybean and narrowing SNPs and candidate genes. The prediction of candidate genes in the haplotype blocks identified by disease resistance loci can provide a useful reference to study systemic disease resistance.

Rice functional genomics: decades' efforts and roads ahead

Rice (Oryza sativa L.) is one of the most important crops in the world. Since the completion of rice reference genome sequences, tremendous progress has been achieved in understanding the molecular mechanisms on various rice traits and dissecting the underlying regulatory networks. In this review, we summarize the research progress of rice biology over past decades, including omics, genome-wide association study, phytohormone action, nutrient use, biotic and abiotic responses, photoperiodic flowering, and reproductive development (fertility and sterility). For the roads ahead, cutting-edge technologies such as new genomics methods, high-throughput phenotyping platforms, precise genome-editing tools, environmental microbiome optimization, and synthetic methods will further extend our understanding of unsolved molecular biology questions in rice, and facilitate integrations of the knowledge for agricultural applications.

Goyal A, Chaudhury A. Molecular and Transcriptional Regulation of Seed Development in Cereals: Present Status and Future Prospects

Cereals are a rich source of vitamins, minerals, carbohydrates, fats, oils and protein, making them the world’s most important source of nutrition. The influence of rising global population, as well as the emergence and spread of disease, has the major impact on cereal production. To meet the demand, there is a pressing need to increase cereal production. Optimal seed development is a key agronomical trait that contributes to crop yield. The seed development and maturation is a complex process that includes not only embryo and endosperm development, but also accompanied by huge physiological, biochemical, metabolic, molecular and transcriptional changes. This chapter discusses the growth of cereal seed and highlights the novel biological insights, with a focus on transgenic and new molecular breeding, as well as biotechnological intervention strategies that have improved crop yield in two major cereal crops, primarily wheat and rice, over the last 21 years (2000–2021).

The Genetic Landscape of Fiber Flax

Genetic diversity in a breeding program is essential to overcome modern-day environmental challenges faced by humanity and produce robust, resilient crop cultivars with improved agronomic characteristics, as well as to trace crop domestication history. Flax (Linum usitatissimum), one of the first crops domesticated by mankind, has been traditionally cultivated for fiber as well as for medicinal purposes and as a nutritional product. The origins of fiber flax are hidden in the mists of time and can be hypothetically traced back to either the Indo-Afghan region or Fertile Crescent. To shed new light on fiber flax genetic diversity and breeding history, in this study, we presented a comprehensive analysis of the core collection of flax (306 accessions) of different morphotypes and geographic origins maintained by the Russian Federal Research Center for Bast Fiber Crops. We observed significant population differentiation between oilseed and fiber morphotypes, as well as mapped genomic regions affected by recent breeding efforts. We also sought to unravel the origins of kryazhs, Russian heritage landraces, and their genetic relatedness to modern fiber flax cultivars. For the first time, our results provide strong genetic evidence in favor of the hypothesis on kryazh's mixed origin from both the Indo-Afghan diversity center and Fertile Crescent. Finally, we showed predominant contribution from Russian landraces and kryazhs into the ancestry of modern fiber flax varieties. Taken together, these findings may have practical implications on the development of new improved flax varieties with desirable traits that give farmers greater choice in crop management and meet the aspirations of breeders.

Natural variation in the fast phase of chlorophyll a fluorescence induction curve (OJIP) in a global rice minicore panel

Photosynthesis can be probed through Chlorophyll a fluorescence induction (FI), which provides detailed insight into the electron transfer process in Photosystem II, and beyond. Here, we have systematically studied the natural variation of the fast phase of the FI, i.e. the OJIP phase, in rice. The OJIP phase of the Chl a fluorescence induction curve is referred to as "fast transient" lasting for less than a second; it is obtained after a dark-adapted sample is exposed to saturating light. In the OJIP curve, "O" stands for "origin" (minimal fluorescence), "P" for "peak" (maximum fluorescence), and J and I for inflection points between the O and P levels. Further, F_o is the fluorescence intensity at the "O" level, whereas F_m is the intensity at the P level, and F_v (= F_m - F_o) is the variable fluorescence. We surveyed a set of quantitative parameters derived from the FI curves of 199 rice accessions, grown under both field condition (FC) and growth room condition (GC). Our results show a significant variation between Japonica (JAP) and Indica (IND) subgroups, under both the growth conditions, in almost all the parameters derived from the OJIP curves. The ratio of the variable to the maximum (F_v/F_m) and of the variable to the minimum (F_v/F_o) fluorescence, the performance index (PI_abs), as well as the amplitude of the I-P phase (A_I-P) show higher values in JAP compared to that in the IND subpopulation. In contrast, the amplitude of the O-J phase (A_O-J) and the normalized area above the OJIP curve (S_m) show an opposite trend. The performed genetic analysis shows that plants grown under GC appear much more affected by environmental factors than those grown in the field. We further conducted a genome-wide association study (GWAS) using 11 parameters derived from plants grown in the field. In total, 596 non-unique significant loci based on these parameters were identified by GWAS. Several photosynthesis-related proteins were identified to be associated with different OJIP parameters. We found that traits with high correlation are usually associated with similar genomic regions. Specifically, the thermal phase of FI, which includes the amplitudes of the J-I and I-P subphases (A_J-I and A_I-P) of the OJIP curve, is, in turn, associated with certain common genomic regions. Our study is the first one dealing with the natural variations in rice, with the aim to characterize potential candidate genes controlling the magnitude and half-time of each of the phases in the OJIP FI curve.

Genetic architecture of photosynthesis energy partitioning as revealed by a genome-wide association approach

The photosynthesis process is determined by the intensity level and spectral quality of the light; therefore, leaves need to adapt to a changing environment. The incident energy absorbed can exceed the sink capability of the photosystems, and, in this context, photoinhibition may occur in both photosystem II (PSII) and photosystem I (PSI). Quantum yield parameters analyses reveal how the energy is managed. These parameters are genotype-dependent, and this genotypic variability is a good opportunity to apply mapping association strategies to identify genomic regions associated with photosynthesis energy partitioning. An experimental and mathematical approach is proposed for the determination of an index which estimates the energy per photon flux for each spectral bandwidth (Δ_λ) of the light incident (QI index). Based on the QI, the spectral quality of the plant growth, environmental lighting, and the actinic light of PAM were quantitatively very similar which allowed an accurate phenotyping strategy of a rice population. A total of 143 genomic single regions associated with at least one trait of chlorophyll fluorescence were identified. Moreover, chromosome 5 gathers most of these regions indicating the importance of this chromosome in the genetic regulation of the photochemistry process. Through a GWAS strategy, 32 genes of rice genome associated with the main parameters of the photochemistry process of photosynthesis in rice were identified. Association between light-harvesting complexes and the potential quantum yield of PSII, as well as the relationship between coding regions for PSI-linked proteins in energy distribution during the photochemical process of photosynthesis is analyzed.

Identification and verification of grain shape QTLs by SNP array in rice

Grain shape strongly influences the economic value and grain yield of rice. Thus, identifying quantitative trait loci (QTLs) for grain shape has been a longstanding goal in rice genetic research and breeding programs. Single nucleotide polymorphism (SNP) markers are ubiquitous in the rice genome and are more abundant and evenly distributed on the 12 rice chromosomes than traditional markers. An F₂ population was genotyped using the RICE6K SNP array to elucidate the mechanisms governing grain shape. Thirty-five QTLs for grain shape were detected on 11 of 12 chromosomes over 2 years. The major QTL cluster qGS7 was detected in both years and displayed strong genetic effects on grain length and width, showing consistency with GL7/GW7. Some minor QTLs were also detected, and the effects of four QTLs on seed size were then validated using BC₁F₆ populations with residual heterozygous lines in each QTL region. Our findings provide insights into the molecular basis of grain shape as well as additional resources and approaches for producing hybrid high-yield rice varieties.

High-Quality Genomes and High-Density Genetic Map Facilitate the Identification of Genes From a Weedy Rice

Genes have been lost or weakened from cultivated rice during rice domestication and breeding. Weedy rice (Oryza sativa f. spontanea) is usually recognized as the progeny between cultivated rice and wild rice and is also known to harbor an gene pool for rice breeding. Therefore, identifying genes from weedy rice germplasms is an important way to break the bottleneck of rice breeding. To discover genes from weedy rice germplasms, we constructed a genetic map based on w-hole-genome sequencing of a F₂ population derived from the cross between LM8 and a cultivated rice variety. We further identified 31 QTLs associated with 12 important agronomic traits and revealed that ORUFILM03g000095 gene may play an important role in grain length regulation and participate in grain formation. To clarify the genomic characteristics from weedy rice germplasms of LM8, we generated a high-quality genome assembly using single-molecule sequencing, Bionano optical mapping, and Hi-C technologies. The genome harbored a total size of 375.8 Mb, a scaffold N50 of 24.1 Mb, and originated approximately 0.32 million years ago (Mya) and was more closely related to Oryza sativa ssp. japonica. and contained 672 unique genes. It is related to the formation of grain shape, heading date and tillering. This study generated a high-quality reference genome of weedy rice and high-density genetic map that would benefit the analysis of genome evolution for related species and suggested an effective way to identify genes related to important agronomic traits for further rice breeding.

Resequencing of 388 cassava accessions identifies valuable loci and selection for variation in heterozygosity

Background

Heterozygous genomes are widespread in outcrossing and clonally propagated crops. However, the variation in heterozygosity underlying key agronomic traits and crop domestication remains largely unknown. Cassava is a staple crop in Africa and other tropical regions and has a highly heterozygous genome.

Results

We describe a genomic variation map from 388 resequenced genomes of cassava cultivars and wild accessions. We identify 52 loci for 23 agronomic traits through a genome-wide association study. Eighteen allelic variations in heterozygosity for nine candidate genes are significantly associated with seven key agronomic traits. We detect 81 selective sweeps with decreasing heterozygosity and nucleotide diversity, harboring 548 genes, which are enriched in multiple biological processes including growth, development, hormone metabolisms and responses, and immune-related processes. Artificial selection for decreased heterozygosity has contributed to the domestication of the large starchy storage root of cassava. Selection for homozygous GG allele in MeTIR1 during domestication contributes to increased starch content. Selection of homozygous AA allele in MeAHL17 is associated with increased storage root weight and cassava bacterial blight (CBB) susceptibility. We have verified the positive roles of MeTIR1 in increasing starch content and MeAHL17 in resistance to CBB by transient overexpression and silencing analysis. The allelic combinations in MeTIR1 and MeAHL17 may result in high starch content and resistance to CBB.

Conclusions

This study provides insights into allelic variation in heterozygosity associated with key agronomic traits and cassava domestication. It also offers valuable resources for the improvement of cassava and other highly heterozygous crops.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-021-02524-7.

Novel QTLs for salinity tolerance revealed by genome-wide association studies of biomass, chlorophyll and tissue ion content in 176 rice landraces from Bangladesh

Farmland is on the decline and worldwide food security is at risk. Rice is the staple of choice for over half the Earth's people. To sustain current demands and ascertain a food secure future, substandard farmland affected by abiotic stresses must be utilized. For rapid crop improvement, a broader understanding of polygenic traits like stress tolerance and crop yield is indispensable. To this end, the hidden diversity of resilient and neglected wild varieties must be traced back to their genetic roots. In this study, we separately assayed 11 phenotypes in a panel of 176 diverse accessions predominantly comprised of local landraces from Bangladesh. We compiled high resolution sequence data for these accessions. We collectively studied the ties between the observed phenotypic differences and the examined additive genetic effects underlying these variations. We applied a fixed effect model to associate phenotypes with genotypes on a genomic scale. Discovered QTLs were mapped to known genes. Our explorations yielded 13 QTLs related to various traits in multiple trait classes. 10 identified QTLs were equivalent to findings from previous studies. Integrative analysis assumes potential novel functionality for a number of candidate genes. These findings will usher novel avenues for the bioengineering of high yielding crops of the future fortified with genetic defenses against abiotic stressors.

A global alfalfa diversity panel reveals genomic selection signatures in Chinese varieties and genomic associations with root development

Alfalfa (Medicago sativa L.) is an important forage crop worldwide. However, little is known about the effects of breeding status and different geographical populations on alfalfa improvement. Here, we sequenced 220 alfalfa core germplasms and determined that Chinese alfalfa cultivars form an independent group, as evidenced by comparisons of F_ST values between different subgroups, suggesting that geographical origin plays an important role in group differentiation. By tracing the influence of geographical regions on the genetic diversity of alfalfa varieties in China, we identified 350 common candidate genetic regions and 548 genes under selection. We also defined 165 loci associated with 24 important traits from genome-wide association studies. Of those, 17 genomic regions closely associated with a given phenotype were under selection, with the underlying haplotypes showing significant differences between subgroups of distinct geographical origins. Based on results from expression analysis and association mapping, we propose that 6-phosphogluconolactonase (MsPGL) and a gene encoding a protein with NHL domains (MsNHL) are critical candidate genes for root growth. In conclusion, our results provide valuable information for alfalfa improvement via molecular breeding.

Genome-wide association study reveals genetic variations associated with ocean acidification resilience in Yesso scallop Patinopecten yessoensis

Ocean acidification (OA), which refers to a gradual decrease in seawater pH due to the absorption of atmospheric carbon dioxide, profoundly affects the growth, development and survival of bivalves. Relatively limited studies have assessed the resilience of bivalve to OA. In the present study, Patinopecten yessoensis, an economically and ecologically significant species, were exposed to low pH (pH = 7.5) for 4 weeks. Forty-seven scallops that died in the first week were considered pH-sensitive population, and 20 that were alive at the end of the experiment were considered pH-tolerant population. A genome-wide association study was conducted to identify the genomic loci associated the resilience of P. yessoensis to OA. Twenty-one single nucleotide polymorphisms were significantly associated with resilience, which were distributed in 11 linkage groups. Within the linkage disequilibrium block region (± 300 kb) surrounding the 21 SNPs, 193 candidate genes were successfully identified. Particularly, five associated SNPs were directly located on five genes, including SP24, CFDH, 5HTR3, HSDL1 and ZFP346. The GO enrichment and KEGG pathway analyses showed that the molecular response of P. yessoensis to OA mainly involved neural signal transmission, energy metabolism and redox reaction. Candidate genes were expressed during larval development and in adult tissues. Furthermore, the expression of 30 candidate genes changed significantly under low pH stress in the mantle. Our results reveal certain SNPs and candidate genes that could elucidate the different responses of P. yessoensis to OA. The genetic variations indicated molecular resilience in P. yessoensis populations, which may enable adaptation to future acidification stress.

Integrating GWAS and transcriptomics to identify genes involved in seed dormancy in rice

Several QTLs and genes responsible for seed dormancy were detected and SNP candidates were shown to cause changes in seed germination. Seed dormancy is a key agricultural trait to prevent pre-harvest sprouting in crop plants such as rice (Oryza sativa L.), wheat (Triticum aestivum), and barley (Hordeum vulgare L.). However, our knowledge of seed dormancy is hampered by the complexities of studying a trait that changes over time after seed harvest, and is complicated by interactions between phytohormones, seed coat components and the environment. Here, we have conducted a genome-wide association study using a panel of 311 natural accessions of cultivated rice, examining a total of 519,158 single nucleotide polymorphisms (SNPs). Eight quantitative trait loci (QTLs) were found to associate with seed dormancy in the whole panel and five in the Japonica and Indica subpanel; expression of candidate genes within 100 kb of each QTL was examined in two published, germination-specific transcriptomic datasets. Ten candidate genes, differentially expressed within the first four days post-imbibition, were identified. Five of these genes had previously been associated with awn length, heading date, yield, and spikelet length phenotypes. Two candidates were validated using Quantitative Reverse Transcription (qRT)-PCR. In addition, previously identified genes involved in hormone signaling during germination were found to be differentially expressed between a japonica and an indica line; SNPs in the promoter of Os9BGlu33 were associated with germination index, with qRT-PCR validation. Collectively, our results are useful for future characterization of seed dormancy mechanism and crop improvement, and suggest haplotypes for further analysis that may be of use to boost PHS resistance in rice.

An OsKala3, R2R3 MYB TF, Is a Common Key Player for Black Rice Pericarp as Main Partner of an OsKala4, bHLH TF

Rice (Oryza sativa) pericarp exhibits various colors due to the accumulation of anthocyanins and/or proanthocyanidins. Previous work revealed that the two basic helix-loop-helix (bHLH) transcription factors OsKala4 and OsRc are key regulators for the black and red pericarp traits, respectively, and their inactivation results in rice with white pericarp. However, their pericarp-specific R2R3 MYB partner remained unknown. Here, we characterized the role of the R2R3 MYB gene OsKala3 in rice pericarp pigmentation through genetic and molecular approaches. A rice protoplast transfection assay showed that OsKala3 is a nuclear-localized protein. Furthermore, OsKala3 physically interacted with OsKala4 in a yeast two-hybrid analysis. Co-transfection assays in rice protoplasts revealed that OsKala3 and OsKala4 mediate the activation of anthocyanin biosynthetic genes. Notably, the OsKala3 promoter region exhibited an insertion polymorphism specifically in rice cultivars with black pericarp, creating two tandem repeats while red and white varieties harbor only one. The number of repeats within the OsKala3 promoter correlated with increased transactivation by OsKala3, thus providing a rationale for the black pericarp characteristic of cultivars with two repeats. These results thus provide evidence for the molecular basis of anthocyanin biosynthesis in rice pericarp and may facilitate the introduction of this beneficial trait to other rice cultivars through marker-assisted breeding.

Gene Mapping, Cloning and Association Analysis for Salt Tolerance in Rice

Soil salinization caused by the accumulation of sodium can decrease rice yield and quality. Identification of rice salt tolerance genes and their molecular mechanisms could help breeders genetically improve salt tolerance. We studied QTL mapping of populations for rice salt tolerance, period and method of salt tolerance identification, salt tolerance evaluation parameters, identification of salt tolerance QTLs, and fine-mapping and map cloning of salt tolerance QTLs. We discuss our findings as they relate to other genetic studies of salt tolerance association.

Global Genetic Heterogeneity in Adaptive Traits

Understanding the genetic architecture of complex traits is a major objective in biology. The standard approach for doing so is genome-wide association studies (GWAS), which aim to identify genetic polymorphisms responsible for variation in traits of interest. In human genetics, consistency across studies is commonly used as an indicator of reliability. However, if traits are involved in adaptation to the local environment, we do not necessarily expect reproducibility. On the contrary, results may depend on where you sample, and sampling across a wide range of environments may decrease the power of GWAS because of increased genetic heterogeneity. In this study, we examine how sampling affects GWAS in the model plant species Arabidopsis thaliana. We show that traits like flowering time are indeed influenced by distinct genetic effects in local populations. Furthermore, using gene expression as a molecular phenotype, we show that some genes are globally affected by shared variants, whereas others are affected by variants specific to subpopulations. Remarkably, the former are essentially all cis-regulated, whereas the latter are predominately affected by trans-acting variants. Our result illustrate that conclusions about genetic architecture can be extremely sensitive to sampling and population structure.

Association mapping of drought tolerance and agronomic traits in rice (Oryza sativa L.) landraces

BACKGROUND

Asian cultivars were predominantly represented in global rice panel selected for sequencing and to identify novel alleles for drought tolerance. Diverse genetic resources adapted to Indian subcontinent were not represented much in spite harboring useful alleles that could improve agronomic traits, stress resilience and productivity. These rice accessions are valuable genetic resource in developing rice varieties suited to different rice ecosystem that experiences varying drought stress level, and at different crop stages. A core collection of rice germplasm adapted to Southwestern Indian peninsular genotyped using SSR markers and characterized by contrasting water regimes to associate genomic regions for physiological, root traits and yield related traits. Genotyping-By-Sequencing of selected accessions within the diverse panel revealed haplotype variation in genic content within genomic regions mapped for physiological, morphological and root traits.

RESULTS

Diverse rice panel (99 accessions) were evaluated in field and measurements on plant physiological, root traits and yield related traits were made over five different seasons experiencing varying drought stress intensity at different crop stages. Traits like chlorophyll stability index, leaf rolling, days to 50% flowering, chlorophyll content, root volume and root biomass were identified as best predictors of grain yield under stress. Association mapping revealed genetic variation among accessions and revealed 14 genomic targets associated with different physiological, root and plant production traits. Certain accessions were found to have beneficial allele to improve traits, plant height, root length and spikelet fertility, that contribute to the grain yield under stress. Genomic characterization of eleven accessions revealed haplotype variation within key genomic targets on chromosomes 1, 4, 6 and 11 for potential use as molecular markers to combine drought avoidance and tolerance traits. Genes mined within the genomic QTL intervals identified were prioritized based on tissue specific expression level in publicly available rice transcriptome data.

CONCLUSION

The genetic and genomic resources identified will enable combining traits with agronomic value to optimize yield under stress and hasten trait introgression into elite cultivars. Alleles associated with plant height, specific leaf area, root length from PTB8 and spikelet fertility and grain weight from PTB26 can be harnessed in future rice breeding program.

Mapping causal genes and genetic interactions for agronomic traits using a large F2 population in rice

Dissecting the genetic mechanisms underlying agronomic traits is of great importance for crop breeding. Agronomic traits are usually controlled by multiple quantitative trait loci (QTLs) and genetic interactions, and mapping the underlying causal genes is still labor-intensive and time-consuming. Here, we present a genetic tool for directly targeting the specific causal genes by using a single-gene resolution linkage map that was constructed from 3756 F2 rice plants via targeted sequencing technology and Tukey-Kramer multiple comparisons test. Three large- and moderate-effect QTLs, qHD6-2, qGL3-1, and qGW5-2, were successfully mapped to their specific causal genes, Hd1, GS3, and GW5, respectively. A complex genetic interaction network containing 30 QTL-QTL interactions was constructed, revealing that the alternative allele of hub QTL, qHD6-2, can hide or release the genetic contributions of the alleles at interacting loci. Moreover, arranging genetic interactions in the models lead to more accurate phenotypic predictions. These results provide a community resource and new feasible strategy for deciphering the genetic mechanisms of complex agronomic traits and accelerating crop breeding.

Advances and Challenges for QTL Analysis and GWAS in the Plant-Breeding of High-Yielding: A Focus on Rapeseed

Yield is one of the most important agronomic traits for the breeding of rapeseed (Brassica napus L), but its genetic dissection for the formation of high yield remains enigmatic, given the rapid population growth. In the present review, we review the discovery of major loci underlying important agronomic traits and the recent advancement in the selection of complex traits. Further, we discuss the benchmark summary of high-throughput techniques for the high-resolution genetic breeding of rapeseed. Biparental linkage analysis and association mapping have become powerful strategies to comprehend the genetic architecture of complex agronomic traits in crops. The generation of improved crop varieties, especially rapeseed, is greatly urged to enhance yield productivity. In this sense, the whole-genome sequencing of rapeseed has become achievable to clone and identify quantitative trait loci (QTLs). Moreover, the generation of high-throughput sequencing and genotyping techniques has significantly enhanced the precision of QTL mapping and genome-wide association study (GWAS) methodologies. Furthermore, this study demonstrates the first attempt to identify novel QTLs of yield-related traits, specifically focusing on ovule number per pod (ON). We also highlight the recent breakthrough concerning single-locus-GWAS (SL-GWAS) and multi-locus GWAS (ML-GWAS), which aim to enhance the potential and robust control of GWAS for improved complex traits.

Ca2+ sensor-mediated ROS scavenging suppresses rice immunity and is exploited by a fungal effector

Plant immunity is activated upon pathogen perception and often affects growth and yield when it is constitutively active. How plants fine-tune immune homeostasis in their natural habitats remains elusive. Here, we discover a conserved immune suppression network in cereals that orchestrates immune homeostasis, centering on a Ca²⁺-sensor, RESISTANCE OF RICE TO DISEASES1 (ROD1). ROD1 promotes reactive oxygen species (ROS) scavenging by stimulating catalase activity, and its protein stability is regulated by ubiquitination. ROD1 disruption confers resistance to multiple pathogens, whereas a natural ROD1 allele prevalent in indica rice with agroecology-specific distribution enhances resistance without yield penalty. The fungal effector AvrPiz-t structurally mimics ROD1 and activates the same ROS-scavenging cascade to suppress host immunity and promote virulence. We thus reveal a molecular framework adopted by both host and pathogen that integrates Ca²⁺ sensing and ROS homeostasis to suppress plant immunity, suggesting a principle for breeding disease-resistant, high-yield crops.

Genome-wide association study revealed genetic variations of ABA sensitivity controlled by multiple stress-related genes in rice

Abscisic acid (ABA) is a critical phytohormone that regulates multiple physiological processes including plant growth and stress tolerance. The core ABA signaling pathway has been well established, but genetic variations mediating ABA responses remain largely unknown. In this study, we performed genome-wide association study (GWAS) to identify loci and genes associated with ABA sensitivity (reflected by seed germination inhibition by ABA) in a panel of 425 rice accessions. The seed germination assay revealed that Aus and indica rice had stronger ABA sensitivity than japonica rice. A total of 48 non-redundant association loci were detected in the indica subpopulation and whole population, and 386 genes in these loci were responsive to ABA or abiotic stresses. Eight association loci were overlapped with previously reported loci for yield under drought stress or for drought-indicative image traits. Haplotype analyses of important candidate genes such as OsSAPK6, a key component in the ABA signaling core, were performed to identify key SNPs/InDels that may affect gene functions through promoter activity regulation, amino acid variation, or gene splicing. These results provide insights into the genetic basis of ABA sensitivity related to stress responses.

Genomic insight into balancing high yield, good quality, and blast resistance of japonica rice

BACKGROUND

Balancing the yield, quality and resistance to disease is a daunting challenge in crop breeding due to the negative relationship among these traits. Large-scale genomic landscape analysis of germplasm resources is considered to be an efficient approach to dissect the genetic basis of the complex traits. Central China is one of the main regions where the japonica rice is produced. However, dozens of high-yield rice varieties in this region still exist with low quality or susceptibility to blast disease, severely limiting their application in rice production.

RESULTS

Here, we re-sequence 200 japonica rice varieties grown in central China over the past 30 years and analyze the genetic structure of these cultivars using 2.4 million polymorphic SNP markers. Genome-wide association mapping and selection scans indicate that strong selection for high-yield and taste quality associated with low-amylose content may have led to the loss of resistance to the rice blast fungus Magnaporthe oryzae. By extensive bioinformatic analyses of yield components, resistance to rice blast, and taste quality, we identify several superior alleles for these traits in the population. Based on this information, we successfully introduce excellent taste quality and blast-resistant alleles into the background of two high-yield cultivars and develop two elite lines, XY99 and JXY1, with excellent taste, high yield, and broad-spectrum of blast resistance.

CONCLUSIONS

This is the first large-scale genomic landscape analysis of japonica rice varieties grown in central China and we demonstrate a balancing of multiple agronomic traits by genomic-based strategy.

Genome-wide association studies of yield-related traits in high-latitude japonica rice

BACKGROUND

Heilongjiang Province is a high-quality japonica rice cultivation area in China. One in ten bowls of Chinese rice is produced here. Increasing yield is one of the main aims of rice production in this area. However, yield is a complex quantitative trait composed of many factors. The purpose of this study was to determine how many genetic loci are associated with yield-related traits. Genome-wide association studies (GWAS) were performed on 450 accessions collected from northeast Asia, including Russia, Korea, Japan and Heilongjiang Province of China. These accessions consist of elite varieties and landraces introduced into Heilongjiang Province decade ago.

RESULTS

After resequencing of the 450 accessions, 189,019 single nucleotide polymorphisms (SNPs) were used for association studies by two different models, a general linear model (GLM) and a mixed linear model (MLM), examining four traits: days to heading (DH), plant height (PH), panicle weight (PW) and tiller number (TI). Over 25 SNPs were found to be associated with each trait. Among them, 22 SNPs were selected to identify candidate genes, and 2, 8, 1 and 11 SNPs were found to be located in 3' UTR region, intron region, coding region and intergenic region, respectively.

CONCLUSIONS

All SNPs detected in this research may become candidates for further fine mapping and may be used in the molecular breeding of high-latitude rice.

Genome-Wide Association Study to Map Genomic Regions Related to the Initiation Time of Four Growth Stage Traits in Soybean

The time to flowering (DF), pod beginning (DPB), seed formation (DSF), and maturity initiation (DMI) in soybean (Glycine max [L.] Merr) are important characteristics of growth stage traits (GSTs) in Chinese summer-sowing soybean, and are influenced by genetic as well as environmental factors. To better understand the molecular mechanism underlying the initiation times of GSTs, we investigated four GSTs of 309 diverse soybean accessions in six different environments and Best Linear Unbiased Prediction values. Furthermore, the genome-wide association study was conducted by a Fixed and random model Circulating Probability Unification method using over 60,000 single nucleotide polymorphism (SNP) markers to identify the significant quantitative trait nucleotide (QTN) regions with phenotypic data. As a result, 212 SNPs within 102 QTN regions were associated with four GSTs. Of which, eight stable regions were repeatedly detected in least three datasets for one GST. Interestingly, half of the QTN regions overlapped with previously reported quantitative trait loci or well-known soybean growth period genes. The hotspots associated with all GSTs were concentrated on chromosome 10. E2 (Glyma10g36600), a gene with a known function in regulating flowering and maturity in soybean, is also found on this chromosome. Thus, this genomic region may account for the strong correlation among the four GSTs. All the significant SNPs in the remaining 7 QTN regions could cause the significant phenotypic variation with both the major and minor alleles. Two hundred and seventy-five genes in soybean and their homologs in Arabidopsis were screened within ± 500 kb of 7 peak SNPs in the corresponding QTN regions. Most of the genes are involved in flowering, response to auxin stimulus, or regulation of seed germination, among others. The findings reported here provide an insight for genetic improvement which will aid in breeding of soybean cultivars that can be adapted to the various summer sowing areas in China and beyond.

Balancing selection and wild gene pool contribute to resistance in global rice germplasm against planthopper

Interactions and co-evolution between plants and herbivorous insects are critically important in agriculture. Brown planthopper (BPH) is the most severe insect of rice, and the biotypes adapt to feed on different rice genotypes. Here, we present genomics analyses on 1,520 global rice germplasms for resistance to three BPH biotypes. Genome-wide association studies identified 3,502 single nucleotide polymorphisms (SNPs) and 59 loci associated with BPH resistance in rice. We cloned a previously unidentified gene Bph37 that confers resistance to BPH. The associated loci showed high nucleotide diversity. Genome-wide scans for trans-species polymorphisms revealed ancient balancing selection at the loci. The secondarily evolved insect biotypes II and III exhibited significantly higher virulence and overcame more rice varieties than the primary biotype I. In response, more SNPs and loci evolved in rice for resistance to biotypes II and III. Notably, three exceptional large regions with high SNP density and resistance-associated loci on chromosomes 4 and 6 appear distinct between the resistant and susceptible rice varieties. Surprisingly, these regions in resistant rice might have been retained from wild species Oryza nivara. Our findings expand the understanding of long-term interactions between rice and BPH and provide resistance genes and germplasm resources for breeding durable BPH-resistant rice varieties.

Molecular dissection of maize seedling salt tolerance using a genome-wide association analysis method

Salt stress is a major devastating abiotic factor that affects the yield and quality of maize. However, knowledge of the molecular mechanisms of the responses to salt stress in maize is limited. To elucidate the genetic basis of salt tolerance traits, a genome-wide association study was performed on 348 maize inbred lines under normal and salt stress conditions using 557 894 single nucleotide polymorphisms (SNPs). The phenotypic data for 27 traits revealed coefficients of variation of >25%. In total, 149 significant SNPs explaining 6.6%-11.2% of the phenotypic variation for each SNP were identified. Of the 104 identified quantitative trait loci (QTLs), 83 were related to salt tolerance and 21 to normal traits. Additionally, 13 QTLs were associated with two to five traits. Eleven and six QTLs controlling salt tolerance traits and normal root growth, respectively, co-localized with QTL intervals reported previously. Based on functional annotations, 13 candidate genes were predicted. Expression levels analysis of 12 candidate genes revealed that they were all responsive to salt stress. The CRISPR/Cas9 technology targeting three sites was applied in maize, and its editing efficiency reached 70%. By comparing the biomass of three CRISPR/Cas9 mutants of ZmCLCg and one zmpmp3 EMS mutant with their wild-type plants under salt stress, the salt tolerance function of candidate genes ZmCLCg and ZmPMP3 were confirmed. Chloride content analysis revealed that ZmCLCg regulated chloride transport under sodium chloride stress. These results help to explain genetic variations in salt tolerance and provide novel loci for generating salt-tolerant maize lines.

Development and application of the Faba_bean_130K targeted next-generation sequencing SNP genotyping platform based on transcriptome sequencing

KEY MESSAGE

Large-scale faba bean transcriptome data are available, and the first genotyping platform based on liquid-phase probe targeted capture technology was developed for genetic and molecular breeding studies. Faba bean (Vicia faba L., 2n = 12) is an important food legume crop that is widely grown for multiple uses worldwide. However, no reference genome is currently available due to its very large genome size (approximately 13 Gb) and limited single nucleotide polymorphism (SNP) markers as well as highly efficient genotyping tools have been reported for faba bean. In this study, 16.7 billion clean reads were obtained from transcriptome libraries of flowers and leaves of 102 global faba bean accessions. A total of 243,120 unigenes were de novo assembled and functionally annotated. Moreover, a total of 1,579,411 SNPs were identified and further filtered according to a selection pipeline to develop a high-throughput, flexible, low-cost Faba_bean_130K targeted next-generation sequencing (TNGS) genotyping platform. A set of 69 Chinese faba bean accessions were genotyped with the TNGS genotyping platform, and the average mapping rate of captured reads to reference transcripts was 93.14%, of which 53.23% were located in the targeted regions. The TNGS genotyping results were validated by Sanger sequencing and the average consistency rate reached 93.6%. Comprehensive population genetic analysis was performed on the 69 Chinese faba bean accessions and identified four genetic subgroups correlated with the geographic distribution. This study provides valuable genomic resources and a reliable genotyping tool that could be implemented in genetic and molecular breeding studies to accelerate new cultivar development and improvement in faba bean.

Genome-Wide Association Study of QTLs Conferring Resistance to Bacterial Leaf Streak in Rice

Bacterial leaf streak (BLS) is a devastating rice disease caused by the bacterial pathogen, Xanthomonas oryzae pv. oryzicola (Xoc), which can result in severe damage to rice production worldwide. Based on a total of 510 rice accessions, trialed in two seasons and using six different multi-locus GWAS methods (mrMLM, ISIS EM-BLASSO, pLARmEB, FASTmrMLM, FASTmrEMMA and pKWmEB), 79 quantitative trait nucleotides (QTNs) reflecting 69 QTLs for BLS resistance were identified (LOD > 3). The QTNs were distributed on all chromosomes, with the most distributed on chromosome 11, followed by chromosomes 1 and 5. Each QTN had an additive effect of 0.20 (cm) and explained, on average, 2.44% of the phenotypic variance, varying from 0.00–0.92 (cm) and from 0.00–9.86%, respectively. Twenty-five QTNs were detected by at least two methods. Among them, qnBLS11.17 was detected by as many as five methods. Most of the QTNs showed a significant interaction with their environment, but no QTNs were detected in both seasons. By defining the QTL range for each QTN according to the LD half-decay distance, a total of 848 candidate genes were found for nine top QTNs. Among them, more than 10% were annotated to be related to biotic stress resistance, and five showed a significant response to Xoc infection. Our results could facilitate the in-depth study and marker-assisted improvement of rice resistance to BLS.

Genetic Dissection of Grain Yield Component Traits Under High Nighttime Temperature Stress in a Rice Diversity Panel

To dissect the genetic complexity of rice grain yield (GY) and quality in response to heat stress at the reproductive stage, a diverse panel of 190 rice accessions in the United States Department of Agriculture (USDA) rice mini-core collection (URMC) diversity panel were treated with high nighttime temperature (HNT) stress at the reproductive stage of panicle initiation. The quantifiable yield component response traits were then measured. The traits, panicle length (PL), and number of spikelets per panicle (NSP) were evaluated in subsets of the panel comprising the rice subspecies Oryza sativa ssp. Indica and ssp. Japonica. Under HNT stress, the Japonica ssp. exhibited lower reductions in PL and NSP and a higher level of genetic variation compared with the other subpopulations. Whole genome sequencing identified 6.5 million single nucleotide polymorphisms (SNPs) that were used for the genome-wide association studies (GWASs) of the PL and NSP traits. The GWAS analysis in the Combined, Indica, and Japonica populations under HNT stress identified 83, 60, and 803 highly significant SNPs associated with PL, compared to the 30, 30, and 11 highly significant SNPs associated with NSP. Among these trait-associated SNPs, 140 were coincident with genomic regions previously reported for major GY component quantitative trait loci (QTLs) under heat stress. Using extents of linkage disequilibrium in the rice populations, Venn diagram analysis showed that the highest number of putative candidate genes were identified in the Japonica population, with 20 putative candidate genes being common in the Combined, Indica and Japonica populations. Network analysis of the genes linked to significant SNPs associated with PL and NSP identified modules that were involved in primary and secondary metabolisms. The findings in this study could be useful to understand the pathways/mechanisms involved in rice GY and its components under HNT stress for the acceleration of rice-breeding programs and further functional analysis by molecular geneticists.

Introgression of Maize Diversity for Drought Tolerance: Subtropical Maize Landraces as Source of New Positive Variants

Current climate change models predict an increased frequency and intensity of drought for much of the developing world within the next 30 years. These events will negatively affect maize yields, potentially leading to economic and social instability in many smallholder farming communities. Knowledge about the genetic resources available for traits related to drought tolerance has great importance in developing breeding program strategies. The aim of this research was to study a maize landrace introgression panel to identify chromosomal regions associated with a drought tolerance index. For that, we performed Genome-Wide Association Study (GWAS) on 1326 landrace progenies developed by the CIMMYT Genetic Resources Program, originating from 20 landraces populations collected in arid regions. Phenotypic data were obtained from early testcross trials conducted in three sites and two contrasting irrigation environments, full irrigation (well-watered) and reduced irrigation (drought). The populations were genotyped using the DArTSeq^® platform, and a final set of 5,695 SNPs markers was used. The genotypic values were estimated using spatial adjustment in a two-stage analysis. First, we performed the individual analysis for each site/irrigation treatment combination. The best linear unbiased estimates (BLUEs) were used to calculate the Harmonic Mean of Relative Performance (HMRP) as a drought tolerance index for each testcross. The second stage was a joint analysis, which was performed using the HMRP to obtain the best linear unbiased predictions (BLUPs) of the index for each genotype. Then, GWAS was performed to determine the marker-index associations and the marker-Grain Yield (GY) associations for the two irrigation treatments. We detected two significant markers associated with the drought-tolerance index, four associated with GY in drought condition, and other four associated with GY in irrigated conditions each. Although each of these markers explained less than 0.1% of the phenotypic variation for the index and GY, we found two genes likely related to the plant response to drought stress. For these markers, alleles from landraces provide a slightly higher yield under drought conditions. Our results indicate that the positive diversity delivered by landraces are still present on the backcrosses and this is a potential breeding strategy for improving maize for drought tolerance and for trait introgression bringing new superior allelic diversity from landraces to breeding populations.

Genetic characterization of melon accessions in the U.S. National Plant Germplasm System and construction of a melon core collection

Melon (C. melo L.) is an economically important vegetable crop cultivated worldwide. The melon collection in the U.S. National Plant Germplasm System (NPGS) is a valuable resource to conserve natural genetic diversity and provide novel traits for melon breeding. Here we use the genotyping-by-sequencing (GBS) technology to characterize 2083 melon accessions in the NPGS collected from major melon production areas as well as regions where primitive melons exist. Population structure and genetic diversity analyses suggested that C. melo ssp. melo was firstly introduced from the centers of origin, Indian and Pakistan, to Central and West Asia, and then brought to Europe and Americas. C. melo ssp. melo from East Asia was likely derived from C. melo ssp. agrestis in India and Pakistan and displayed a distinct genetic background compared to the rest of ssp. melo accessions from other geographic regions. We developed a core collection of 383 accessions capturing more than 98% of genetic variation in the germplasm, providing a publicly accessible collection for future research and genomics-assisted breeding of melon. Thirty-five morphological characters investigated in the core collection indicated high variability of these characters across accessions in the collection. Genome-wide association studies using the core collection panel identified potentially associated genome regions related to fruit quality and other horticultural traits. This study provides insights into melon origin and domestication, and the constructed core collection and identified genome loci potentially associated with important traits provide valuable resources for future melon research and breeding.

An inferred functional impact map of genetic variants in rice

Interpreting the functional impacts of genetic variants (GVs) is an important challenge for functional genomic studies in crops and next-generation breeding. Previous studies in rice (Oryza sativa) have focused mainly on the identification of GVs, whereas systematic functional annotation of GVs has not yet been performed. Here, we present a functional impact map of GVs in rice. We curated haplotype information for 17 397 026 GVs from sequencing data of 4726 rice accessions. We quantitatively evaluated the effects of missense mutations in coding regions in each haplotype based on the conservation of amino acid residues and obtained the effects of 918 848 non-redundant missense GVs. Furthermore, we generated high-quality chromatin accessibility (CA) data from six representative rice tissues and used these data to train deep convolutional neural network models to predict the impacts of 5 067 405 GVs for CA in regulatory regions. We characterized the functional properties and tissue specificity of the GV effects and found that large-effect GVs in coding and regulatory regions may be subject to selection in different directions. Finally, we demonstrated how the functional impact map could be used to prioritize causal variants in mapping populations. This impact map will be a useful resource for accelerating gene cloning and functional studies in rice, and can be freely queried in RiceVarMap V2.0 (http://ricevarmap.ncpgr.cn).

Dissection of the Genetic Basis of Rice Panicle Architecture Using a Genome-wide Association Study

Panicle architecture is one of the major factors influencing productivity of rice crops. The regulatory mechanisms underlying this complex trait are still unclear and genetic resources for rice breeders to improve panicle architecture are limited. Here, we have performed a genome-wide association study (GWAS) to analyze and identify genetic determinants underlying three panicle architecture traits. A population of 340 rice accessions from the 3000 Rice Genomes Project was phenotyped for panicle length, primary panicle number and secondary branch number over two years; GWAS was performed across the whole panel, and also across the japonica and indica sub-panels. A total of 153 quantitative trait loci (QTLs) were detected, of which 5 were associated with multiple traits, 8 were unique to either indica or japonica sub-panels, while 37 QTLs were stable across both years. Using haplotype and expression analysis, we reveal that genetic variations in the OsSPL18 promoter significantly affect gene expression and correlate with panicle length phenotypes. Three new candidate genes with putative roles in determining panicle length were also identified. Haplotype analysis of OsGRRP and LOC_Os03g03480 revealed high association with panicle length variation. Gene expression of DSM2, involved in abscisic acid biosynthesis, was up-regulated in long panicle accessions. Our results provide valuable information and resources for further unravelling the genetic basis determining rice panicle architecture. Identified candidate genes and molecular markers can be used in marker-assisted selection to improve rice panicle architecture through molecular breeding.

Lime and Organic Manure Amendment: A Potential Approach for Sustaining Crop Productivity of the T. Aman-Maize-Fallow Cropping Pattern in Acidic Piedmont Soils

Acid soil is a hindrance to agricultural productivity and a threat to food and environmental security. Research was carried out to assess the impact of lime and organic manure (OM) amendments on yield and nutrient uptake by using the T. Aman-Maize-Fallow cropping pattern in acid soils. The experiment was set up in an RCBD design and used nine treatments and three replications. The treatments, comprising of various doses of lime, OM (cow dung and poultry manure), and a lime-OM combination, were applied to the first crop, T. Aman (Binadhan 7), and in the next crop, maize (BARI Hybrid Maize-9), the residual impacts of the treatments were assessed. Results demonstrate that the highest grain yield, 4.84 t ha−1 (13.61% increase over control) was recorded for T. Aman and 8.38 t ha−1 (58.71% increase over control) for maize, was achieved when dololime was applied in combination with poultry manure. The total rice equivalent yield increase over the control ranged from 20.5% to 66.1%. The application of lime with cow dung or poultry manure considerably enhanced N, P, K, and S content and uptake in both crops, compared to the control. Thus, it may be inferred that using dololime in association with poultry manure can increase crop productivity in acid soils.

Revisiting a GWAS peak in Arabidopsis thaliana reveals possible confounding by genetic heterogeneity

Genome-wide association studies (GWAS) have become a standard approach for exploring the genetic basis of phenotypic variation. However, correlation is not causation, and only a tiny fraction of all associations have been experimentally confirmed. One practical problem is that a peak of association does not always pinpoint a causal gene, but may instead be tagging multiple causal variants. In this study, we reanalyze a previously reported peak associated with flowering time traits in Swedish Arabidopsis thaliana population. The peak appeared to pinpoint the AOP2/AOP3 cluster of glucosinolate biosynthesis genes, which is known to be responsible for natural variation in herbivore resistance. Here we propose an alternative hypothesis, by demonstrating that the AOP2/AOP3 flowering association can be wholly accounted for by allelic variation in two flanking genes with clear roles in regulating flowering: NDX1, a regulator of the main flowering time controller FLC, and GA1, which plays a central role in gibberellin synthesis and is required for flowering under some conditions. In other words, we propose that the AOP2/AOP3 flowering-time association may be yet another example of a spurious, "synthetic" association, arising from trying to fit a single-locus model in the presence of two statistically associated causative loci. We conclude that caution is needed when using GWAS for fine-mapping.

Recent advancements in molecular marker-assisted selection and applications in plant breeding programmes

Background

DNA markers improved the productivity and accuracy of classical plant breeding by means of marker-assisted selection (MAS). The enormous number of quantitative trait loci (QTLs) mapping read for different plant species have given a plenitude of molecular marker-gene associations.

Main body of the abstract

In this review, we have discussed the positive aspects of molecular marker-assisted selection and its precise applications in plant breeding programmes. Molecular marker-assisted selection has considerably shortened the time for new crop varieties to be brought to the market. To explore the information about DNA markers, many reviews have been published in the last few decades; all these reviews were intended by plant breeders to obtain information on molecular genetics. In this review, we intended to be a synopsis of recent developments of DNA markers and their application in plant breeding programmes and devoted to early breeders with little or no knowledge about the DNA markers. The progress made in molecular plant breeding, plant genetics, genomics selection, and editing of genome contributed to the comprehensive understanding of DNA markers and provides several proofs on the genetic diversity available in crop plants and greatly complemented plant breeding devices.

Short conclusion

MAS has revolutionized the process of plant breeding with acceleration and accuracy, which is continuously empowering plant breeders around the world.

Loci and natural alleles for cadmium-mediated growth responses revealed by a genome wide association study and transcriptome analysis in rice

BACKGROUND

Cadmium (Cd) is a toxic heavy metal that is harmful to the environment and human health. Cd pollution threatens the cultivation of rice (Oryza sativa L.) in many countries. Improving rice performance under Cd stress could potentially improve rice productivity.

RESULTS

In this study, 9 growth traits of 188 different cultivated rice accessions under normal and Cd stress conditions were found to be highly variable during the seedling stage. Based on ~3.3 million single nucleotide polymorphisms (SNPs), 119 Cd-mediated growth response (CGR) quantitative trait loci (QTL) were identified by a genome-wide association study (GWAS), 55 of which have been validated by previously reported QTL and 64 were new CGR loci. Combined with the data from the GWAS, transcriptome analysis, gene annotations from the gene ontology (GO) Slim database, and annotations and functions of homologous genes, 148 CGR candidate genes were obtained. Additionally, several reported genes have been found to play certain roles in CGRs. Seven Cd-related cloned genes were found among the CGR genes. Natural elite haplotypes/alleles in these genes that increased Cd tolerance were identified by a haplotype analysis of a diverse mini core collection. More importantly, this study was the first to uncover the natural variations of 5 GST genes that play important roles in CGRs.

CONCLUSION

The exploration of Cd-resistant rice germplasm resources and the identification of elite natural variations related to Cd-resistance will help improve the tolerance of current major rice varieties to Cd, as well as provide raw materials and new genes for breeding Cd-resistant varieties.

Loci and natural alleles for cadmium-mediated growth responses revealed by a genome wide association study and transcriptome analysis in rice

BACKGROUND

Cadmium (Cd) is a toxic heavy metal that is harmful to the environment and human health. Cd pollution threatens the cultivation of rice (Oryza sativa L.) in many countries. Improving rice performance under Cd stress could potentially improve rice productivity.

RESULTS

In this study, 9 growth traits of 188 different cultivated rice accessions under normal and Cd stress conditions were found to be highly variable during the seedling stage. Based on ~3.3 million single nucleotide polymorphisms (SNPs), 119 Cd-mediated growth response (CGR) quantitative trait loci (QTL) were identified by a genome-wide association study (GWAS), 55 of which have been validated by previously reported QTL and 64 were new CGR loci. Combined with the data from the GWAS, transcriptome analysis, gene annotations from the gene ontology (GO) Slim database, and annotations and functions of homologous genes, 148 CGR candidate genes were obtained. Additionally, several reported genes have been found to play certain roles in CGRs. Seven Cd-related cloned genes were found among the CGR genes. Natural elite haplotypes/alleles in these genes that increased Cd tolerance were identified by a haplotype analysis of a diverse mini core collection. More importantly, this study was the first to uncover the natural variations of 5 GST genes that play important roles in CGRs.

CONCLUSION

The exploration of Cd-resistant rice germplasm resources and the identification of elite natural variations related to Cd-resistance will help improve the tolerance of current major rice varieties to Cd, as well as provide raw materials and new genes for breeding Cd-resistant varieties.

Identification and allele mining of new candidate genes underlying rice grain weight and grain shape by genome-wide association study

BACKGROUND

Grain weight and grain shape are important agronomic traits that affect the grain yield potential and grain quality of rice. Both grain weight and grain shape are controlled by multiple genes. The 3,000 Rice Genomes Project (3 K RGP) greatly facilitates the discovery of agriculturally important genetic variants and germplasm resources for grain weight and grain shape.

RESULTS

Abundant natural variations and distinct phenotic differentiation among the subgroups in grain weight and grain shape were observed in a large population of 2,453 accessions from the 3 K RGP. A total of 21 stable quantitative trait nucleotides (QTNs) for the four traits were consistently identified in at least two of 3-year trials by genome-wide association study (GWAS), including six new QTNs (qTGW3.1, qTGW9, qTGW11, qGL4/qRLW4, qGL10, and qRLW1) for grain weight and grain shape. We further predicted seven candidate genes (Os03g0186600, Os09g0544400, Os11g0163600, Os04g0580700, Os10g0399700, Os10g0400100 and Os01g0171000) for the six new QTNs by high-density association and gene-based haplotype analyses. The favorable haplotypes of the seven candidate genes and five previously cloned genes in elite accessions with high TGW and RLW are also provided.

CONCLUSIONS

Our results deepen the understanding of the genetic basis of grain weight and grain shape in rice and provide valuable information for improving rice grain yield and grain quality through molecular breeding.

Favorable pleiotropic loci for fiber yield and quality in upland cotton (Gossypium hirsutum)

Upland cotton (Gossypium hirsutum L.) is an important economic crop for renewable textile fibers. However, the simultaneous improvement of yield and fiber quality in cotton is difficult as the linkage drag. Compared with breaking the linkage drag, identification of the favorable pleiotropic loci on the genome level by genome-wide association study (GWAS) provides a new way to improve the yield and fiber quality simultaneously. In our study restriction-site-associated DNA sequencing (RAD-seq) was used to genotype 316 cotton accessions. Eight major traits in three categories including yield, fiber quality and maturation were investigated in nine environments (3 sites × 3 years). 231 SNPs associated with these eight traits (− log₁₀(P) > 5.27) were identified, located in 27 genomic regions respectively by linkage disequilibrium analysis. Further analysis showed that four genomic regions (the region 1, 6, 8 and 23) held favorable pleiotropic loci and 6 candidate genes were identified. Through genotyping, 14 elite accessions carrying the favorable loci on four pleiotropic regions were identified. These favorable pleiotropic loci and elite genotypes identified in this study will be utilized to improve the yield and fiber quality simultaneously in future cotton breeding.

Potential of rice landraces with strong culms as genetic resources for improving lodging resistance against super typhoons

It is generally believed that rice landraces with long culms are susceptible to lodging, and have not been utilized for breeding to improve lodging resistance. However, little is known about the structural culm strength of landraces and their beneficial genetic loci. Therefore, in this study, genome-wide association studies (GWAS) were performed using a rice population panel including Japanese rice landraces to identify beneficial loci associated with strong culms. As a result, the landraces were found to have higher structural culm strength and greater diversity than the breeding varieties. Genetic loci associated with strong culms were identified, and it was demonstrated that haplotypes with positive effects of those loci were present in a high proportion of these landraces. These results indicated that the utilization of the strong culm-associated loci present in Japanese rice landraces may further improve the lodging resistance of modern breeding varieties that have relied on semi-dwarfism.

Genome-wide association study reveals the genetic architecture of 27 agronomic traits in tomato

Tomato (Solanum lycopersicum) is a highly valuable fruit crop, and yield is one of the most important agronomic traits. However, the genetic architecture underlying tomato yield-related traits has not been fully addressed. Based on ∼4.4 million single nucleotide polymorphisms obtained from 605 diverse accessions, we performed a comprehensive genome-wide association study for 27 agronomic traits in tomato. A total of 239 significant associations corresponding to 129 loci, harboring many previously reported and additional genes related to vegetative and reproductive development, were identified, and these loci explained an average of ∼8.8% of the phenotypic variance. A total of 51 loci associated with 25 traits have been under selection during tomato domestication and improvement. Furthermore, a candidate gene, Sl-ACTIVATED MALATE TRANSPORTER15, that encodes an aluminum-activated malate transporter was functionally characterized and shown to act as a pivotal regulator of leaf stomata formation, thereby affecting photosynthesis and drought resistance. This study provides valuable information for tomato genetic research and breeding.

GmST1, which encodes a sulfotransferase, confers resistance to soybean mosaic virus strains G2 and G3

Soybean mosaic virus (SMV) is one of the most widespread and devastating viral diseases worldwide. The genetic architecture of qualitative resistance to SMV in soybean remains unclear. Here, the Rsvg2 locus was identified as underlying soybean resistance to SMV by genome-wide association and linkage analyses. Fine mapping results showed that soybean resistance to SMV strains G2 and G3 was controlled by a single dominant gene, GmST1, on chromosome 13, encoding a sulfotransferase (SOT). A key variation at position 506 in the coding region of GmST1 associated with the structure of the encoded SOT and changed SOT activity levels between RSVG2-S and RSVG2-R alleles. In RSVG2-S allele carrier "Hefeng25", the overexpression of GmST1 carrying the RSVG2-R allele from the SMV-resistant line "Dongnong93-046" conferred resistance to SMV strains G2 and G3. Compared to Hefeng25, the accumulation of SMV was decreased in transgenic plants carrying the RSVG2-R allele. SMV infection differentiated both the accumulation of jasmonates and expression patterns of genes involved in jasmonic acid (JA) signalling, biosynthesis and catabolism in RSVG2-R and RSVG2-S allele carriers. This characterization of GmST1 suggests a new scenario explaining soybean resistance to SMV.

Identification of rice (Oryza sativa L.) genes involved in sheath blight resistance via a genome-wide association study

Rice sheath blight (RSB) is an economically significant disease affecting rice yield worldwide. Genetic resistance to RSB is associated with multiple minor genes, with each providing a minor phenotypic effect, but the underlying dominant resistance genes remain unknown. A genome-wide association study (GWAS) of 259 diverse rice varieties, with genotypes based on a single nucleotide polymorphism (SNP) and haplotype, was conducted to assess their sheath blight reactions at three developmental stages (seedlings, tillering and booting). A total of 653 genes were correlated with sheath blight resistance, of which the disease resistance protein RPM1 (OsRSR1) and protein kinase domain-containing protein (OsRLCK5) were validated by overexpression and knockdown assays. We further found that the coiled-coil (CC) domain of OsRSR1 (OsRSR1-CC) and full-length OsRLCK5 interacted with serine hydroxymethyltransferase 1 (OsSHM1) and glutaredoxin (OsGRX20), respectively. It was found that OsSHM1, which has a role in the reactive oxygen species (ROS) burst, and OsGRX20 enhanced the antioxidation ability of plants. A regulation model of the new RSB resistance though the glutathione (GSH)-ascorbic acid (AsA) antioxidant system was therefore revealed. These results enhance our understanding of RSB resistance mechanisms and provide better gene resources for the breeding of disease resistance in rice.

Accelerated deciphering of the genetic architecture of agricultural economic traits in pigs using a low-coverage whole-genome sequencing strategy

BACKGROUND

Uncovering the genetic architecture of economic traits in pigs is important for agricultural breeding. However, high-density haplotype reference panels are unavailable in most agricultural species, limiting accurate genotype imputation in large populations. Moreover, the infinitesimal model of quantitative traits implies that weak association signals tend to be spread across most of the genome, further complicating the genetic analysis. Hence, there is a need to develop new methods for sequencing large cohorts without large reference panels.

RESULTS

We describe a Tn5-based highly accurate, cost- and time-efficient, low-coverage sequencing method to obtain 11.3 million whole-genome single-nucleotide polymorphisms in 2,869 Duroc boars at a mean depth of 0.73×. On the basis of these single-nucleotide polymorphisms, a genome-wide association study was performed, resulting in 14 quantitative trait loci (QTLs) for 7 of 21 important agricultural traits in pigs. These QTLs harbour genes, such as ABCD4 for total teat number and HMGA1 for back fat thickness, and provided a starting point for further investigation. The inheritance models of the different traits varied greatly. Most follow the minor-polygene model, but this can be attributed to different reasons, such as the shaping of genetic architecture by artificial selection for this population and sufficiently interconnected minor gene regulatory networks.

CONCLUSIONS

Genome-wide association study results for 21 important agricultural traits identified 14 QTLs/genes and showed their genetic architectures, providing guidance for genetic improvement harnessing genomic features. The Tn5-based low-coverage sequencing method can be applied to large-scale genome studies for any species without a good reference panel and can be used for agricultural breeding.

Genome-Wide Association Study Reveals PC4 as the Candidate Gene for Thermal Tolerance in Bay Scallop (Argopecten irradians irradians)

The increasing sea temperature caused by global warming has resulted in severe mortalities in maricultural scallops. Therefore, improving thermal tolerance has become an active research area in the scallop farming industry. Bay scallop (Argopecten irradians irradians) was introduced into China in 1982 and has developed into a vast aquaculture industry in northern China. To date, genetic studies on thermal tolerance in bay scallops are limited, and no systematic screening of thermal tolerance-related loci or genes has been conducted in this species. In the present study, we conducted a genome-wide association study (GWAS) for thermal tolerance using the Arrhenius break temperature (ABT) indicators of 435 bay scallops and 38,011 single nucleotide polymorphism (SNP) markers. The GWAS identified 1,906 significant thermal tolerance-associated SNPs located in 16 chromosomes of bay scallop. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that 638 genes were enriched in 42 GO terms, while 549 annotated genes were enriched in aggregation pathways. Additionally, the SNP (15-5091-20379557-1) with the lowest P value was located in the transcriptional coactivator p15 (PC4) gene, which is involved in regulating DNA damage repair and stabilizing genome functions. Further analysis in another population identified two new thermal tolerance-associated SNPs in the first coding sequence of PC4 in bay scallops (AiPC4). Moreover, AiPC4 expression levels were significantly correlated (r = 0.675–0.962; P < 0.05) with the ABT values of the examined bay scallops. Our data suggest that AiPC4 might be a positive regulator of thermal tolerance and a potential candidate gene for molecular breeding in bay scallop aiming at thermal tolerance improvement.

Hyperspectral reflectance-based phenotyping for quantitative genetics in crops: Progress and challenges

Many biochemical and physiological properties of plants that are of interest to breeders and geneticists have extremely low throughput and/or can only be measured destructively. This has limited the use of information on natural variation in nutrient and metabolite abundance, as well as photosynthetic capacity in quantitative genetic contexts where it is necessary to collect data from hundreds or thousands of plants. A number of recent studies have demonstrated the potential to estimate many of these traits from hyperspectral reflectance data, primarily in ecophysiological contexts. Here, we summarize recent advances in the use of hyperspectral reflectance data for plant phenotyping, and discuss both the potential benefits and remaining challenges to its application in plant genetics contexts. The performances of previously published models in estimating six traits from hyperspectral reflectance data in maize were evaluated on new sample datasets, and the resulting predicted trait values shown to be heritable (e.g., explained by genetic factors) were estimated. The adoption of hyperspectral reflectance-based phenotyping beyond its current uses may accelerate the study of genes controlling natural variation in biochemical and physiological traits.

PIP-SNP: a pipeline for processing SNP data featured as linkage disequilibrium bin mapping, genotype imputing and marker synthesizing

Genome-wide association study data analyses often face two significant challenges: (i) high dimensionality of single-nucleotide polymorphism (SNP) genotypes and (ii) imputation of missing values. SNPs are not independent due to physical linkage and natural selection. The correlation of nearby SNPs is known as linkage disequilibrium (LD), which can be used for LD conceptual SNP bin mapping, missing genotype inferencing and SNP dimension reduction. We used a stochastic process to describe the SNP signals and proposed two types of autocorrelations to measure nearby SNPs' information redundancy. Based on the calculated autocorrelation coefficients, we constructed LD bins. We adopted a k-nearest neighbors algorithm (kNN) to impute the missing genotypes. We proposed several novel methods to find the optimal synthetic marker to represent the SNP bin. We also proposed methods to evaluate the information loss or information conservation between using the original genome-wide markers and using dimension-reduced synthetic markers. Our performance assessments on the real-life SNP data from a rice recombinant inbred line (RIL) population and a rice HapMap project show that the new methods produce satisfactory results. We implemented these functional modules in C/C++ and streamlined them into a web-based pipeline named PIP-SNP (https://bioinfo.noble.org/PIP_SNP/) for processing SNP data.