Grain protein content (GPC) affects rice nutrition quality. Here, we identify two stable quantitative trait loci (QTLs), qGPC-1 and qGPC-10, controlling GPC in a mapping population derived from ...indica and japonica cultivars crossing. Map-based cloning reveals that OsGluA2, encoding a glutelin type-A2 precursor, is the candidate gene underlying qGPC-10. It functions as a positive regulator of GPC and has a pleiotropic effect on rice grain quality. One SNP located in OsGluA2 promoter region is associated with its transcript expression level and GPC diversity. Polymorphisms of this nucleotide can divide all haplotypes into low (OsGluA2
) and high (OsGluA2
) expression types. Population genetic and evolutionary analyses reveal that OsGluA2
, mainly present in japonica accessions, originates from wild rice. However, OsGluA2
, the dominant type in indica, is acquired through mutation of OsGluA2
. Our results shed light on the understanding of natural variations of GPC between indica and japonica subspecies.
Dissecting the genetic architecture of complex traits is an ongoing challenge for geneticists. Two complementary approaches for genetic mapping, linkage mapping and association mapping have led to ...successful dissection of complex traits in many crop species. Both of these methods detect quantitative trait loci (QTL) by identifying marker–trait associations, and the only fundamental difference between them is that between mapping populations, which directly determine mapping resolution and power. Based on this difference, we first summarize in this review the advances and limitations of family-based mapping and natural population-based mapping instead of linkage mapping and association mapping. We then describe statistical methods used for improving detection power and computational speed and outline emerging areas such as large-scale meta-analysis for genetic mapping in crops. In the era of next-generation sequencing, there has arisen an urgent need for proper population design, advanced statistical strategies, and precision phenotyping to fully exploit high-throughput genotyping.
Key message
GWAS identified 559 significant SNPs associated with the remodelling of the root architecture in response to salt, and 168 candidate genes were prioritized by integrating RNA-seq, DEG and ...WGCNA data.
Salinity is a major environmental factor limiting crop growth and productivity. The root is the first plant organ to encounter salt stress, yet the effects of salinity on maize root development remain unclear. In this study, the natural variations in 14 root and 4 shoot traits were evaluated in 319 maize inbred lines under control and saline conditions. Considerable phenotypic variations were observed for all traits, with high salt concentrations decreasing the root length, but increasing the root diameter. A genome-wide association study was conducted to analyse these traits and their plasticity (relative variation). We detected 559 significant single nucleotide polymorphisms, of which 125, 181 and 253 were associated with the control condition, stress condition and trait plasticity, respectively. A total of 168 of 587 candidate genes identified by genome-wide association study were supported by the differentially expressed genes or co-expression networks. Two candidate genes
ZmIAA1
and
ZmGRAS43
were validated by resequencing. Among these genes, 130 were detected under stress condition or trait plasticity that involved in diverse biological processes including plant hormone signal transduction, phenylpropanoid biosynthesis and fatty acid biosynthesis. Our findings clarify the root remodelling to salinity, and the identified loci and candidate genes may be important for the genetic improvement of root traits and salt tolerance in maize.
Maize starch plays a critical role in food processing and industrial application. The pasting properties, the most important starch characteristics, have enormous influence on fabrication property, ...flavor characteristics, storage, cooking, and baking. Understanding the genetic basis of starch pasting properties will be beneficial for manipulation of starch properties for a given purpose. Genome-wide association studies (GWAS) are becoming a powerful tool for dissecting the complex traits. Here, we carried out GWAS for seven pasting properties of maize starch with a panel of 230 inbred lines and 145,232 SNPs using one single-locus method, genome-wide efficient mixed model association (GEMMA), and three multi-locus methods, FASTmrEMMA, FarmCPU, and LASSO. We totally identified 60 quantitative trait nucleotides (QTNs) for starch pasting properties with these four GWAS methods. FASTmrEMMA detected the most QTNs (29), followed by FarmCPU (19) and LASSO (12), GEMMA detected the least QTNs (7). Of these QTNs, seven QTNs were identified by more than one method simultaneously. We further investigated locations of these significantly associated QTNs for possible candidate genes. These candidate genes and significant QTNs provide the guidance for further understanding of molecular mechanisms of starch pasting properties. We also compared the statistical powers and Type I errors of the four GWAS methods using Monte Carlo simulations. The results suggest that the multi-locus method is more powerful than the single-locus method and a combination of these multi-locus methods could help improve the detection power of GWAS.
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.
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.
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.
Background
Hybrid breeding is an effective tool to improve yield in rice, while parental selection remains the key and difficult issue. Genomic selection (GS) provides opportunities to predict the ...performance of hybrids before phenotypes are measured. However, the application of GS is influenced by several genetic and statistical factors. Here, we used a rice North Carolina II (NC II) population constructed by crossing 115 rice varieties with five male sterile lines as a model to evaluate effects of statistical methods, heritability, marker density and training population size on prediction for hybrid performance.
Results
From the comparison of six GS methods, we found that predictabilities for different methods are significantly different, with genomic best linear unbiased prediction (GBLUP) and least absolute shrinkage and selection operation (LASSO) being the best, support vector machine (SVM) and partial least square (PLS) being the worst. The marker density has lower influence on predicting rice hybrid performance compared with the size of training population. Additionally, we used the 575 (115 × 5) hybrid rice as a training population to predict eight agronomic traits of all hybrids derived from 120 (115 + 5) rice varieties each mating with 3023 rice accessions from the 3000 rice genomes project (3 K RGP). Of the 362,760 potential hybrids, selection of the top 100 predicted hybrids would lead to 35.5%, 23.25%, 30.21%, 42.87%, 61.80%, 75.83%, 19.24% and 36.12% increase in grain yield per plant, thousand-grain weight, panicle number per plant, plant height, secondary branch number, grain number per panicle, panicle length and primary branch number, respectively.
Conclusions
This study evaluated the factors affecting predictabilities for hybrid prediction and demonstrated the implementation of GS to predict hybrid performance of rice. Our results suggest that GS could enable the rapid selection of superior hybrids, thus increasing the efficiency of rice hybrid breeding.
Carbon graphite materials inevitably produce more internal microcracks and pores during the carbonization process, which makes the materials have lower mechanical properties and poor frictional ...properties, limiting their applications. In this paper, the modification of coal tar pitch using oleic acid modified multi-walled carbon nanotubes (MWCNTs) can increase the dispersion of MWCNTs, change the carbonization process of the pitch and optimize the microstructure of the composite. The results showed that the dispersibility of oleic acid modified MWCNTs was significantly improved, and they could act as nucleating agents in the carbonization process of coal tar pitch to improve the graphitization degree and carbonization yield of the pitch. When the content of oleic acid modified MWCNTs was 0.1%, the compressive and flexural strengths of the modified carbon graphite material reached the maximum, which increased by 54.81% and 64.43%, respectively, compared with the pristine material, and led to a 46.47% reduction in wear rate. This work provides a new idea for the development of higher performance electrical contact materials.
The primary root is the first organ to perceive the stress signals for abiotic stress. In this study, maize plants subjected to drought, heat and combined stresses displayed a significantly reduced ...primary root length. Metabolic and transcriptional analyses detected 72 and 5,469 differentially expressed metabolites and genes in response to stress conditions, respectively. The functional annotation of differentially expressed metabolites and genes indicated that primary root development was mediated by pathways involving phenylalanine metabolism, hormone metabolism and signaling under stress conditions. Furthermore, we found that the concentration of salicylic acid and two precursors, shikimic acid and phenylalanine, showed rapid negative accumulation after all three stresses. The expression levels of some key genes involved in salicylic acid metabolism and signal transduction were differentially expressed under stress conditions. This study extends our understanding of the mechanism of primary root responses to abiotic stress tolerance in maize.
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