Genome-wide association studies of ionomic and agronomic traits in USDA mini core collection of rice and comparative analyses of different mapping methods

Genetic background influences mineral accumulation in rice straw and grains under different soil pH conditions

Mineral element accumulation in plants is influenced by soil conditions and varietal factors. We investigated the dynamic accumulation of 12 elements in straw at the flowering stage and in grains at the mature stage in eight rice varieties with different genetic backgrounds (Japonica, Indica, and admixture) and flowering times (early, middle, and late) grown in soil with various pH levels. In straw, Cd, As, Mn, Zn, Ca, Mg, and Cu accumulation was influenced by both soil pH and varietal factors, whereas P, Mo, and K accumulation was influenced by pH, and Fe and Ni accumulation was affected by varietal factors. In grains, Cd, As, Mn, Cu, Ni, Mo, Ca, and Mg accumulation was influenced by both pH and varietal factors, whereas Zn, Fe, and P accumulation was affected by varietal factors, and K accumulation was not altered. Only As, Mn, Ca and Mg showed similar trends in the straw and grains, whereas the pH responses of Zn, P, K, and Ni differed between them. pH and flowering time had synergistic effects on Cd, Zn, and Mn in straw and on Cd, Ni, Mo, and Mn in grains. Soil pH is a major factor influencing mineral uptake in rice straw and grains, and genetic factors, flowering stage factors, and their interaction with soil pH contribute in a combined manner.

Additive and Dominance Genome-Wide Association Studies Reveal the Genetic Basis of Heterosis Related to Growth Traits of Duhua Hybrid Pigs

Heterosis has been extensively used for pig genetic breeding and production, but the genetic basis of heterosis remains largely elusive. Crossbreeding between commercial and native breeds provides a good model to parse the genetic basis of heterosis. This study uses Duhua hybrid pigs, a crossbreed of Duroc and Liangguang small spotted pigs, as materials to explore the genetic basis underlying heterosis related to growth traits at the genomic level. The mid-parent heterosis (MPH) analysis showed heterosis of this Duhua offspring on growth traits. In this study, we examined the impact of additive and dominance effects on 100 AGE (age adjusted to 100 kg) and 100 BF (backfat thickness adjusted to 100 kg) of Duhua hybrid pigs. Meanwhile, we successfully identified SNPs associated with growth traits through both additive and dominance GWASs (genome-wide association studies). These findings will facilitate the subsequent in-depth studies of heterosis in the growth traits of Duhua pigs.

Genetic analysis of iron, zinc and grain yield in wheat-Aegilops derivatives using multi-locus GWAS

BACKGROUND

Wheat is a major staple crop and helps to reduce worldwide micronutrient deficiency. Investigating the genetics that control the concentrations of iron (Fe) and zinc (Zn) in wheat is crucial. Hence, we undertook a comprehensive study aimed at elucidating the genomic regions linked to the contents of Fe and Zn in the grain.

METHODS AND RESULTS

We performed the multi-locus genome-wide association (ML-GWAS) using a panel of 161 wheat-Aegilops substitution and addition lines to dissect the genomic regions controlling grain iron (GFeC), and grain zinc (GZnC) contents. The wheat panel was genotyped using 10,825 high-quality SNPs and phenotyped in three different environments (E1-E3) during 2017-2019. A total of 111 marker-trait associations (MTAs) (at p-value < 0.001) were detected that belong to all three sub-genomes of wheat. The highest number of MTAs were identified for GFeC (58), followed by GZnC (44) and yield (9). Further, six stable MTAs were identified for these three traits and also two pleiotropic MTAs were identified for GFeC and GZnC. A total of 1291 putative candidate genes (CGs) were also identified for all three traits. These CGs encode a diverse set of proteins, including heavy metal-associated (HMA), bZIP family protein, AP2/ERF, and protein previously associated with GFeC, GZnC, and grain yield.

CONCLUSIONS

The significant MTAs and CGs pinpointed in this current study are poised to play a pivotal role in enhancing both the nutritional quality and yield of wheat, utilizing marker-assisted selection (MAS) techniques.

Genome-Wide Association Studies of Biluochun Tea Plant Populations in Dongting Mountain and Comprehensive Identification of Candidate Genes Associated with Core Agronomic Traits by Four Analysis Models

The elite germplasm resources are key to the beautiful appearance and pleasant flavor of Biluochun tea. We collected and measured the agronomic traits of 95 tea plants to reveal the trait diversity and breeding value of Biluochun tea plant populations. The results revealed that the agronomic traits of Biluochun tea plant populations were diverse and had high breeding value. Additionally, we resequenced these tea plant populations to reveal genetic diversity, population structure, and selection pressure. The Biluochun tea plant populations contained two groups and were least affected by natural selection based on the results of population structure and selection pressure. More importantly, four non-synonymous single nucleotide polymorphisms (nsSNPs) and candidate genes associated with (-)-gallocatechin gallate (GCG), (-)-gallocatechin (GC), and caffeine (CAF) were detected using at least two GWAS models. The results will promote the development and application of molecular markers and the utilization of elite germplasm from Biluochun populations.

E-GWAS: an ensemble-like GWAS strategy that provides effective control over false positive rates without decreasing true positives

BACKGROUND

Genome-wide association studies (GWAS) are an effective way to explore genotype-phenotype associations in humans, animals, and plants. Various GWAS methods have been developed based on different genetic or statistical assumptions. However, no single method is optimal for all traits and, for many traits, the putative single nucleotide polymorphisms (SNPs) that are detected by the different methods do not entirely overlap due to the diversity of the genetic architecture of complex traits. Therefore, multi-tool-based GWAS strategies that combine different methods have been increasingly employed. To take this one step further, we propose an ensemble-like GWAS strategy (E-GWAS) that statistically integrates GWAS results from different single GWAS methods.

RESULTS

E-GWAS was compared with various single GWAS methods using simulated phenotype traits with different genetic architectures. E-GWAS performed stably across traits with different genetic architectures and effectively controlled the number of false positive genetic variants detected without decreasing the number of true positive variants. In addition, its performance could be further improved by using a bin-merged strategy and the addition of more distinct single GWAS methods. Our results show that the numbers of true and false positive SNPs detected by the E-GWAS strategy slightly increased and decreased, respectively, with increasing bin size and when the number and the diversity of individual GWAS methods that were integrated in E-GWAS increased, the latter being more effective than the bin-merged strategy. The E-GWAS strategy was also applied to a real dataset to study backfat thickness in a pig population, and 10 candidate genes related to this trait and expressed in adipose-associated tissues were identified.

CONCLUSIONS

Using both simulated and real datasets, we show that E-GWAS is a reliable and robust strategy that effectively integrates the GWAS results of different methods and reduces the number of false positive SNPs without decreasing that of true positive SNPs.

Genome-wide association study reveals genomic loci influencing agronomic traits in Ethiopian sorghum (Sorghum bicolor (L.) Moench) landraces

Uncovering the genetic basis of agronomic traits in sorghum landraces that have adapted to various agro-climatic conditions would contribute to sorghum improvement efforts around the world. To identify quantitative trait nucleotides (QTNs) associated with nine agronomic traits in a panel of 304 sorghum accessions collected from diverse environments across Ethiopia (considered to be the center of origin and diversity), multi-locus genome-wide association studies (ML-GWAS) were performed using 79,754 high quality single nucleotide polymorphism (SNP) markers. Association analyses using six ML-GWAS models identified a set of 338 significantly (LOD ≥ 3)-associated QTNs for nine agronomic traits of sorghum accessions evaluated in two environments (E1 and E2) and their combined dataset (Em). Of these, 121 reliable QTNs, including 13 for flowering time (DF), 13 for plant height (PH), 9 for tiller number (TN), 15 for panicle weight (PWT), 30 for grain yield per panicle (GYP), 12 for structural panicle mass (SPM), 13 for hundred seed weight (HSW), 6 for grain number per panicle (GNP), and 10 for panicle exertion (PE) were consistently detected by at least three ML-GWAS methods and/or in two different environments. Notably, Ethylene responsive transcription factor gene AP2/ERF, known for regulation of plant growth, and the sorghum Terminal flower1/TF1 gene, which functions in the control of floral architecture, were identified as strong candidate genes associated with PH and HSW, respectively. This study provides an entry point for further validation studies to elucidate complex mechanisms controlling important agronomic traits in sorghum.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01381-5.

A genome-wide association study identifies novel players in Na and Fe homeostasis in Arabidopsis thaliana under alkaline-salinity stress

In nature, multiple stress factors occur simultaneously. The screening of natural diversity panels and subsequent Genome-Wide Association Studies (GWAS) is a powerful approach to identify genetic components of various stress responses. Here, the nutritional status variation of a set of 270 natural accessions of Arabidopsis thaliana grown on a natural saline-carbonated soil is evaluated. We report significant natural variation on leaf Na (LNa) and Fe (LFe) concentrations in the studied accessions. Allelic variation in the NINJA and YUC8 genes is associated with LNa diversity, and variation in the ALA3 is associated with LFe diversity. The allelic variation detected in these three genes leads to changes in their mRNA expression and correlates with plant differential growth performance when plants are exposed to alkaline salinity treatment under hydroponic conditions. We propose that YUC8 and NINJA expression patters regulate auxin and jasmonic signaling pathways affecting plant tolerance to alkaline salinity. Finally, we describe an impairment in growth and leaf Fe acquisition associated with differences in root expression of ALA3, encoding a phospholipid translocase active in plasma membrane and the trans Golgi network which directly interacts with proteins essential for the trafficking of PIN auxin transporters, reinforcing the role of phytohormonal processes in regulating ion homeostasis under alkaline salinity.

Integrated multi-locus genome-wide association studies and transcriptome analysis for seed yield and yield-related traits in Brassica napus

Rapeseed (Brassica napus L.), the third largest oil crop, is an important source of vegetable oil and biofuel for the world. Although the breeding and yield has been improved, rapeseed still has the lowest yield compared with other major crops. Thus, increasing rapeseed yield is essential for the high demand of vegetable oil and high-quality protein for live stocks. Silique number per plant (SN), seed per pod (SP), and 1000-seed weight (SW) are the three important factors for seed yield in rapeseed. Some yield-related traits, including plant height (PH), flowering time (FT), primary branch number (BN) and silique number per inflorescence (SI) also affect the yield per plant (YP). Using six multi-locus genome-wide association study (ML-GWAS) approaches, a total of 908 yield-related quantitative trait nucleotides (QTNs) were identified in a panel consisting of 403 rapeseed core accessions based on whole-genome sequencing. Integration of ML-GWAS with transcriptome analysis, 79 candidate genes, including BnaA09g39790D (RNA helicase), BnaA09g39950D (Lipase) and BnaC09g25980D (SWEET7), were further identified and twelve genes were validated by qRT-PCRs to affect the SW or SP in rapeseed. The distribution of superior alleles from nineteen stable QTNs in 20 elite rapeseed accessions suggested that the high-yielding accessions contained more superior alleles. These results would contribute to a further understanding of the genetic basis of yield-related traits and could be used for crop improvement in B. napus.

Identifying the Genetic Basis of Mineral Elements in Rice Grain Using Genome-Wide Association Mapping

Mineral malnutrition is a major problem in many rice-consuming countries. It is essential to know the genetic mechanisms of accumulation of mineral elements in the rice grain to provide future solutions for this issue. This study was conducted to identify the genetic basis of six mineral elements (Cu, Fe, K, Mg, Mn, and Zn) by using three models for single-locus and six models for multi-locus analysis of a genome-wide association study (GWAS) using 174 diverse rice accessions and 6565 SNP markers. To declare a SNP as significant, -log10(P) ≥ 3.0 and 15% FDR significance cut-off values were used for single-locus models, while LOD ≥ 3.0 was used for multi-locus models. Using these criteria, 147 SNPs were detected by one or two GWAS methods at -log10(P) ≥ 3.0, 48 of which met the 15% FDR significance cut-off value. Single-locus models outperformed multi-locus models before applying multi-test correction, but once applied, multi-locus models performed better. While 14 (~29%) of the identified quantitative trait loci (QTLs) after multiple test correction co-located with previously reported genes/QTLs and marker associations, another 34 trait-associated SNPs were novel. After mining genes within 250 kb of the 48 significant SNP loci, in silico and gene enrichment analyses were conducted to predict their potential functions. These shortlisted genes with their functions could guide future experimental validation, helping us to understand the complex molecular mechanisms controlling rice grain mineral elements.

Temporal and environmental factors interact with rootstock genotype to shape leaf elemental composition in grafted grapevines

Plants take up elements through their roots and transport them to their shoot systems for use in numerous biochemical, physiological, and structural functions. Elemental composition of above-ground plant tissues, such as leaves, reflects both above- and below-ground activities of the plant, as well the local environment. Perennial, grafted plants, where the root system of one individual is fused to the shoot system of a genetically distinct individual, offer a powerful experimental system in which to study how genetically distinct root systems influence the elemental composition of a common shoot system. We measured elemental composition of over 7,000 leaves in the grapevine cultivar "Chambourcin" growing ungrafted and grafted to three rootstock genotypes. Leaves were collected over multiple years and phenological stages (across the season) and along a developmental time series. Temporal components of this study had the largest effect on leaf elemental composition, and rootstock genotype interacted with year, phenological stage, and leaf age to differentially modulate leaf elemental composition. Further, the local, above-ground environment affected leaf elemental composition, an effect influenced by rootstock genotype. This work highlights the dynamic nature by which root systems interact with shoot systems to respond to temporal and environmental variation.

Genetic basis underlying tiller angle in rice (Oryza sativa L.) by genome-wide association study

Novel alleles of two reported tiller angle genes and eleven candidate genes for rice tiller angle were identified by combining GWAS with transcriptomic, qRT-PCR and haplotype analysis. Rice tiller angle is a key agronomic trait determining rice grain yield. Several quantitative trait loci (QTLs) affecting rice tiller angle have been mapped in the past decades. Little is known about the genetic base of tiller angle in rice, because rice tiller angle is a complex polygenic trait. In this study, we performed genome-wide association study (GWAS) on tiller angle in rice using a population of 164 japonica varieties derived from the 3 K Rice Genomes Project (3 K RGP). We detected a total of 18 QTLs using 1135519 single-nucleotide polymorphisms (SNP) based on three GWAS models (GLM, FastLMM and FarmCPU). Among them, two identified QTLs, qTA8.3 and qTA8.4, overlapped with PAY1 and TIG1, respectively, and additional 16 QTLs were identified for the first time. Combined with haplotype and expression analyses, we further revealed that PAY1 harbors one non-synonymous variation at its coding region, likely leading to variable tiller angle in the population, and that nature variations in the promoter of TIG1 significantly affect its expression, closely correlating with tiller angle phenotypes observed. Similarly, using qRT-PCR and haplotype analysis, we identified 1 and 7 candidate genes in qTA6.1 and qTA8.1 that were commonly detected by two GWAS models, respectively. In addition, we identified 3 more candidate genes in the remaining 14 novel QTLs after filtering by transcriptome analysis and qRT-PCR. In summary, this study provides new insights into the genetic architecture of rice tiller angle and candidate genes for rice breeding.

Genome-wide association study of cassava starch paste properties

An understanding of cassava starch paste properties (CSPP) can contribute to the selection of clones with differentiated starches. This study aimed to identify genomic regions associated with CSPP using different genome-wide association study (GWAS) methods (MLM, MLMM, and Farm-CPU). The GWAS was performed using 23,078 single-nucleotide polymorphisms (SNPs). The rapid viscoanalyzer (RVA) parameters were pasting temperature (PastTemp), peak viscosity (PeakVisc), hot-paste viscosity (Hot-PVisc), cool-paste viscosity (Cold-PVisc), final viscosity (FinalVis), breakdown (BreDow), and setback (Setback). Broad phenotypic and molecular diversity was identified based on the genomic kinship matrix. The broad-sense heritability estimates (h²) ranged from moderate to high magnitudes (0.66 to 0.76). The linkage disequilibrium (LD) declined to between 0.3 and 2.0 Mb (r² <0.1) for most chromosomes, except chromosome 17, which exhibited an extensive LD. Thirteen SNPs were found to be significantly associated with CSPP, on chromosomes 3, 8, 17, and 18. Only the BreDow trait had no associated SNPs. The regional marker-trait associations on chromosome 18 indicate a LD block between 2907312 and 3567816 bp and that SNP S18_3081635 was associated with SetBack, FinalVis, and Cold-PVisc (all three GWAS methods) and with Hot-PVisc (MLM), indicating that this SNP can track these four traits simultaneously. The variance explained by the SNPs ranged from 0.13 to 0.18 for SetBack, FinalVis, and Cold-PVisc and from 0.06 to 0.09 for PeakVisc and Hot-PVisc. The results indicated additive effects of the genetic control of Cold-PVisc, FinalVis, Hot-PVisc, and SetBack, especially on the large LD block on chromosome 18. One transcript encoding the glycosyl hydrolase family 35 enzymes on chromosome 17 and one encoding the mannose-p-dolichol utilization defect 1 protein on chromosome 18 were the most likely candidate genes for the regulation of CSPP. These results underline the potential for the assisted selection of high-value starches to improve cassava root quality through breeding programs.

Multi-Locus GWAS for Grain Weight-Related Traits Under Rain-Fed Conditions in Common Wheat (Triticum aestivum L.)

In wheat, a multi-locus genome-wide association study (ML-GWAS) was conducted for the four grain weight-related traits (days to anthesis, grain filling duration, grain number per ear, and grain weight per ear) using data recorded under irrigated (IR) and rain-fed (RF) conditions. Seven stress-related indices were estimated for these four traits: (i) drought resistance index (DI), (ii) geometric mean productivity (GMP), (iii) mean productivity index (MPI), (iv) relative drought index (RDI), (v) stress tolerance index (STI), (vi) yield index, and (vii) yield stability index (YSI). The association panel consisted of a core collection of 320 spring wheat accessions representing 28 countries. The panel was genotyped using 9,627 single nucleotide polymorphisms (SNPs). The genome-wide association (GWA) analysis provided 30 significant marker-trait associations (MTAs), distributed as follows: (i) IR (15 MTAs), (ii) RF (14 MTAs), and (iii) IR+RF (1 MTA). In addition, 153 MTAs were available for the seven stress-related indices. Five MTAs co-localized with previously reported QTLs/MTAs. Candidate genes (CGs) associated with different MTAs were also worked out. Gene ontology (GO) analysis and expression analysis together allowed the selection of the two CGs, which may be involved in response to drought stress. These two CGs included: TraesCS1A02G331000 encoding RNA helicase and TraesCS4B02G051200 encoding microtubule-associated protein 65. The results supplemented the current knowledge on genetics for drought tolerance in wheat. The results may also be used for future wheat breeding programs to develop drought-tolerant wheat cultivars.

Identification of genomic loci regulating grain iron content in aus rice under two irrigation management systems

Iron (Fe) deficiency is one of the common causes of anaemia in humans. Improving grain Fe in rice, therefore, could have a positive impact for humans worldwide, especially for those people who consume rice as a staple food. In this study, 225–269 accessions of the Bengal and Assam Aus Panel (BAAP) were investigated for their accumulation of grain Fe in two consecutive years in a field experiment under alternative wetting and drying (AWD) and continuous flooded (CF) irrigation. AWD reduced straw Fe by 40% and grain Fe by 5.5–13%. Genotype differences accounted for 35% of the variation in grain Fe, while genotype by irrigation interaction accounted for 12% of the variation in straw and grain Fe in year 1, with no significant interactions detected in year 2. Twelve rice accessions were identified as having high grain Fe for both years regardless of irrigation treatment, half of which were from BAAP aus subgroup 3 which prominently comes from Bangladesh. On average, subgroup 3 had higher grain Fe than the other four subgroups of aus. Genome‐wide association mapping identified 6 genomic loci controlling natural variation of grain Fe concentration in plants grown under AWD. For one QTL, nicotianamine synthase OsNAS3 is proposed as candidate for controlling natural variation of grain Fe in rice. The BAAP contains three haplotypes of OsNAS3 where one haplotype (detected in 31% of the individuals) increased grain Fe up to 11%. Haplotype analysis of this gene in rice suggests that the ability to detect the QTL is enhanced in the BAAP because the high Fe allele is balanced in aus, unlike indica and japonica subgroups.

Multi-locus genome-wide association studies for five yield-related traits in rice

BACKGROUND

Improving the overall production of rice with high quality is a major target of breeders. Mining potential yield-related loci have been geared towards developing efficient rice breeding strategies. In this study, one single-locus genome-wide association studies (SL-GWAS) method (MLM) in conjunction with five multi-locus genome-wide association studies (ML-GWAS) approaches (mrMLM, FASTmrMLM, pLARmEB, pKWmEB, and ISIS EM-BLASSO) were conducted in a panel consisting of 529 rice core varieties with 607,201 SNPs.

RESULTS

A total of 152, 106, 12, 111, and 64 SNPs were detected by the MLM model associated with the five yield-related traits, namely grain length (GL), grain width (GW), grain thickness (GT), thousand-grain weight (TGW), and yield per plant (YPP), respectively. Furthermore, 74 significant quantitative trait nucleotides (QTNs) were presented across at least two ML-GWAS methods to be associated with the above five traits successively. Finally, 20 common QTNs were simultaneously discovered by both SL-GWAS and ML-GWAS methods. Based on genome annotation, gene expression analysis, and previous studies, two candidate key genes (LOC_Os09g02830 and LOC_Os07g31450) were characterized to affect GW and TGW, separately.

CONCLUSIONS

These outcomes will provide an indication for breeding high-yielding rice varieties in the immediate future.

Genetic architecture of root and shoot ionomes in rice (Oryza sativa L.)

KEY MESSAGE

Association analysis for ionomic concentrations of 20 elements identified independent genetic factors underlying the root and shoot ionomes of rice, providing a platform for selecting and dissecting causal genetic variants. Understanding the genetic basis of mineral nutrient acquisition is key to fully describing how terrestrial organisms interact with the non-living environment. Rice (Oryza sativa L.) serves both as a model organism for genetic studies and as an important component of the global food system. Studies in rice ionomics have primarily focused on above ground tissues evaluated from field-grown plants. Here, we describe a comprehensive study of the genetic basis of the rice ionome in both roots and shoots of 6-week-old rice plants for 20 elements using a controlled hydroponics growth system. Building on the wealth of publicly available rice genomic resources, including a panel of 373 diverse rice lines, 4.8 M genome-wide single-nucleotide polymorphisms, single- and multi-marker analysis pipelines, an extensive tome of 321 candidate genes and legacy QTLs from across 15 years of rice genetics literature, we used genome-wide association analysis and biparental QTL analysis to identify 114 genomic regions associated with ionomic variation. The genetic basis for root and shoot ionomes was highly distinct; 78 loci were associated with roots and 36 loci with shoots, with no overlapping genomic regions for the same element across tissues. We further describe the distribution of phenotypic variation across haplotypes and identify candidate genes within highly significant regions associated with sulfur, manganese, cadmium, and molybdenum. Our analysis provides critical insight into the genetic basis of natural phenotypic variation for both root and shoot ionomes in rice and provides a comprehensive resource for dissecting and testing causal genetic variants.

Ionomic Approaches for Discovery of Novel Stress-Resilient Genes in Plants

Plants, being sessile, face an array of biotic and abiotic stresses in their lifespan that endanger their survival. Hence, optimized uptake of mineral nutrients creates potential new routes for enhancing plant health and stress resilience. Recently, minerals (both essential and non-essential) have been identified as key players in plant stress biology, owing to their multifaceted functions. However, a realistic understanding of the relationship between different ions and stresses is lacking. In this context, ionomics will provide new platforms for not only understanding the function of the plant ionome during stresses but also identifying the genes and regulatory pathways related to mineral accumulation, transportation, and involvement in different molecular mechanisms under normal or stress conditions. This article provides a general overview of ionomics and the integration of high-throughput ionomic approaches with other "omics" tools. Integrated omics analysis is highly suitable for identification of the genes for various traits that confer biotic and abiotic stress tolerance. Moreover, ionomics advances being used to identify loci using qualitative trait loci and genome-wide association analysis of element uptake and transport within plant tissues, as well as genetic variation within species, are discussed. Furthermore, recent developments in ionomics for the discovery of stress-tolerant genes in plants have also been addressed; these can be used to produce more robust crops with a high nutritional value for sustainable agriculture.

Molecular and genetic dissection of the USDA rice mini-core collection using high-density SNP markers

Molecular tools and knowledge of crop germplasm are vital for their effective utilization. In this study, we developed 40,866 high-quality and well distributed SNPs for a rice mini-core collection (RMC) developed by the United States Department of Agriculture (USDA). The high-quality SNPs clustered the USDA-RMC into five subpopulations (Ind, indica; Aus, aus; Afr, African rice; TeJ, temperate japonica; TrJ, tropical japonica) and one admixture (Adm). This classification was further confirmed by phylogenetic and principal component analyses. The rice ARO (aromatic) subpopulation of previous studies was re-assigned with Adm and the WD (wild-type) subpopulation was re-defined to the Afr subpopulation because most of its accessions are African cultivated rice. The Aus and Ind subpopulations had a substantially wider genetic variation than the TrJ and TeJ subpopulations. The genetic diversities were much larger between the Ind or Aus subpopulation and the TrJ or TeJ subpopulation than between the Afr subpopulation and the Ind, Aus, TrJ or TeJ subpopulation. Comparative agronomic trait analysis between the subpopulations also supported the genetic structure and variation of the RMC, and suggested the existence of extensive variation in the genes controlling agronomic traits among them. Furthermore, analysis of ancestral membership of the RMC accessions revealed that reproductive barrier or wide incompatibility existed between the Indica and Japonica groups, while gene flow occurred between them. These results provide high-quality SNPs and knowledge of genetic structure and diversity of the USDA-RMC necessary for enhanced rice research and breeding.

Global Analysis of UDP Glucose Pyrophosphorylase (UDPGP) Gene Family in Plants: Conserved Evolution Involved in Cell Death

UDP glucose pyrophosphorylase (UDPGP) family genes have been reported to play essential roles in cell death or individual survival. However, a systematic analysis on UDPGP gene family has not been performed yet. In this study, a total of 454 UDPGP proteins from 76 different species were analyzed. The analyses of the phylogenetic tree and orthogroups divided UDPGPs into three clades, including UDP-N-acetylglucosamine pyrophosphorylase (UAP), UDP-glucose pyrophosphorylase (UGP, containing UGP-A and UGP-B), and UDP-sugar pyrophosphorylase (USP). The evolutionary history of the UDPGPs indicated that the members of UAP, USP, and UGP-B were relatively conserved while varied in UGP-A. Homologous sequences of UGP-B and USP were found only in plants. The expression profile of UDPGP genes in Oryza sativa was mainly motivated under jasmonic acid (JA), abscisic acid (ABA), cadmium, and cold treatments, indicating that UDPGPs may play an important role in plant development and environment endurance. The key amino acids regulating the activity of UDPGPs were analyzed, and almost all of them were located in the NB-loop, SB-loop, or conserved motifs. Analysis of the natural variants of UDPGPs in rice revealed that only a few missense mutants existed in coding sequences (CDSs), and most of the resulting variations were located in the non-motif sites, indicating the conserved structure and function of UDPGPs in the evolution. Furthermore, alternative splicing may play a key role in regulating the activity of UDPGPs. The spatial structure prediction, enzymatic analysis, and transgenic verification of UAP isoforms illustrated that the loss of N- and C-terminal sequences did not affect the overall 3D structures, but the N- and C-terminal sequences are important for UAP genes to maintain their enzymatic activity. These results revealed a conserved UDPGP gene family and provided valuable information for further deep functional investigation of the UDPGP gene family in plants.

Uncovering the genetic mechanisms regulating panicle architecture in rice with GPWAS and GWAS

Background

The number of panicles per plant, number of grains per panicle, and 1000-grain weight are important factors contributing to the grain yield per plant in rice. The Rice Diversity Panel 1 (RDP1) contains a total of 421 purified, homozygous rice accessions representing diverse genetic variations within O. sativa. The release of High-Density Rice Array (HDRA, 700 k SNPs) dataset provides a new opportunity to discover the genetic variants of panicle architectures in rice.

Results

In this report, a new method genome-phenome wide association study (GPWAS) was performed with 391 individuals and 27 traits derived from RDP1 to scan the relationship between the genes and multi-traits. A total of 1985 gene models were linked to phenomic variation with a p-value cutoff of 4.49E-18. Besides, 406 accessions derived from RDP1 with 411,066 SNPs were used to identify QTLs associated with the total spikelets number per panicle (TSNP), grain number per panicle (GNP), empty grain number per panicle (EGNP), primary branch number (PBN), panicle length (PL), and panicle number per plant (PN) by GLM, MLM, FarmCPU, and BLINK models for genome-wide association study (GWAS) analyses. A total of 18, 21, 18, 17, 15, and 17 QTLs were identified tightly linked with TSNP, GNP, EGNP, PBN, PL, and PN, respectively. Then, a total of 23 candidate genes were mapped simultaneously using both GWAS and GPWAS methods, composed of 6, 4, 5, 4, and 4 for TSNP, GNP, EGNP, PBN, and PL. Notably, one overlapped gene (Os01g0140100) were further investigated based on the haplotype and gene expression profile, indicating this gene might regulate the TSNP or panicle architecture in rice.

Conclusions

Nearly 30 % (30/106) QTLs co-located with the previous published genes or QTLs, indicating the power of GWAS. Besides, GPWAS is a new method to discover the relationship between genes and traits, especially the pleiotropy genes. Through comparing the results from GWAS and GPWAS, we identified 23 candidate genes related to panicle architectures in rice. This comprehensive study provides new insights into the genetic basis controlling panicle architectures in rice, which lays a foundation in rice improvement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07391-x.