Association analysis of the amino acid contents in rice

Knocking out isopropylmalate synthase simultaneously improves grain appearance and nutritional quality in rice

Grain appearance and nutritional quality are critical traits for rice marketing. However, how to simultaneously improve grain appearance (slender grain and low chalkiness) and nutritional quality (improved protein and amino acid contents) in rice remains a major challenge. Here, we show that knocking out rice isopropylmalate synthase genes OsIPMS1 and OsIPMS2 can improve both grain appearance and nutritional quality. We find that OsIPMS1 directly interacts with OsIPMS2 to form heterodimers. Meanwhile, we observe that OsIPMS1 and OsIPMS2 influence the expression of genes previously reported to be involved in the determination of grain size and nutritional quality in the developing panicles and grains. Furthermore, we show that Osipms1/2 double mutants exhibit significantly improved grain appearance and nutritional quality in polished rice in both the japonica (Wuyungeng 23) and indica (Huanghuazhan) varieties. Our findings indicate that OsIPMS is a useful target gene for breeding of rice varieties appealing for marketing and with health-benefiting properties.

Genome-wide SNPs and candidate genes underlying the genetic variations for protein and amino acids in pearl millet (Pennisetum glaucum) germplasm

MAIN CONCLUSION

A total of 544 significant marker-trait associations and 286 candidate genes associated with total protein and 18 amino acids were identified. Thirty-three candidate genes were found near the strong marker trait associations (- log10P ≥ 5.5). Pearl millet (Pennisetum glaucum) is largely grown as a subsistence crop in South Asia and sub-Saharan Africa. It serves as a major source of daily protein intake in these regions. Despite its importance, no systematic effort has been made to study the genetic variations of protein and amino acid content in pearl millet germplasm. The present study was undertaken to dissect the global genetic variations of total protein and 18 essential and non-essential amino acids in pearl millet, using a set of 435 K Single Nucleotide Polymorphisms (SNPs) and 161 genotypes of the Pearl Millet Inbred Germplasm Association Panel (PMiGAP). A total of 544 significant marker-trait associations (at P < 0.0001; - log10P ≥ 4) were detected and 23 strong marker-trait associations were identified using Bonferroni's correction method. Forty-eight pleiotropic loci were found in the genome for the studied traits. In total, 286 candidate genes associated with total protein and 18 amino acids were identified. Thirty-three candidate genes were found near strongly associated SNPs. The associated markers and the candidate genes provide an insight into the genetic architecture of the traits studied and are going to be useful in breeding improved pearl millet varieties in the future. Availabilities of improved pearl millet varieties possessing higher protein and amino acid compositions will help combat the rising malnutrition problem via diet.

The differences in metabolites, starch structure, and physicochemical properties of rice were related to the decrease in taste quality under high nitrogen fertilizer application

Nitrogen fertilizer application is one of the key cultivation practices to improve rice yields. However, the application of high nitrogen fertilizers often leads to a reduction in the stickiness of the rice after cooking, thus reducing the taste quality of rice. Moreover, there are differences in taste quality among rice varieties, and the mechanism has not been studied in depth. In this study, two rice varieties (Meixiangzhan2hao and Exiang2hao) were planted under two nitrogen fertilizer levels. The physicochemical properties and taste quality of the rice were determined after maturity. Our results showed that high nitrogen fertilizer level alters tryptophan metabolism in rice, increasing most amino acid content and protein content in rice. The high content of protein and the higher short-range ordered structure of starch inhibited the gelatinization characteristics of starch and reduced the taste quality of rice. Under high nitrogen fertilizer application, Exiang2hao showed smaller increases in protein content, lower level of amylose and relative crystallinity, and higher content of lipid metabolites. These differences in chemical substances resulted in a less pronounced reduction in the taste quality of Exiang2hao. In this study, the taste quality of different rice varieties under different levels of nitrogen fertilizer application was analyzed, providing new ideas for future improvement of rice taste quality.

Genome-wide association study reveals that different pathways contribute to grain quality variation in sorghum (Sorghum bicolor)

BACKGROUND

In sorghum (Sorghum bicolor), one paramount breeding objective is to increase grain quality. The nutritional quality and end use value of sorghum grains are primarily influenced by the proportions of tannins, starch and proteins, but the genetic basis of these grain quality traits remains largely unknown. This study aimed to dissect the natural variation of sorghum grain quality traits and identify the underpinning genetic loci by genome-wide association study.

RESULTS

Levels of starch, tannins and 17 amino acids were quantified in 196 diverse sorghum inbred lines, and 44 traits based on known metabolic pathways and biochemical interactions amongst the 17 amino acids calculated. A Genome-wide association study (GWAS) with 3,512,517 SNPs from re-sequencing data identified 14, 15 and 711 significant SNPs which represented 14, 14, 492 genetic loci associated with levels of tannins, starch and amino acids in sorghum grains, respectively. Amongst these significant SNPs, two SNPs were associated with tannin content on chromosome 4 and colocalized with three previously identified loci for Tannin1, and orthologs of Zm1 and TT16 genes. One SNP associated with starch content colocalized with sucrose phosphate synthase gene. Furthermore, homologues of opaque1 and opaque2 genes associated with amino acid content were identified. Using the KEGG pathway database, six and three candidate genes of tannins and starch were mapped into 12 and 3 metabolism pathways, respectively. Thirty-four candidate genes were mapped into 16 biosynthetic and catabolic pathways of amino acids. We finally reconstructed the biosynthetic pathways for aspartate and branched-chain amino acids based on 15 candidate genes identified in this study.

CONCLUSION

Promising candidate genes associated with grain quality traits have been identified in the present study. Some of them colocalized with previously identified genetic regions, but novel candidate genes involved in various metabolic pathways which influence grain quality traits have been dissected. Our study acts as an entry point for further validation studies to elucidate the complex mechanisms controlling grain quality traits such as tannins, starch and amino acids in sorghum.

A Genome-Wide Association Study Reveals Candidate Genes Related to Salt Tolerance in Rice (Oryza sativa) at the Germination Stage

Salt toxicity is the major factor limiting crop productivity in saline soils. In this paper, 295 accessions including a heuristic core set (137 accessions) and 158 bred varieties were re-sequenced and ~1.65 million SNPs/indels were used to perform a genome-wide association study (GWAS) of salt-tolerance-related phenotypes in rice during the germination stage. A total of 12 associated peaks distributed on seven chromosomes using a compressed mixed linear model were detected. Determined by linkage disequilibrium (LD) blocks analysis, we finally obtained a total of 79 candidate genes. By detecting the highly associated variations located inside the genic region that overlapped with the results of LD block analysis, we characterized 17 genes that may contribute to salt tolerance during the seed germination stage. At the same time, we conducted a haplotype analysis of the genes with functional variations together with phenotypic correlation and orthologous sequence analyses. Among these genes, OsMADS31, which is a MADS-box family transcription factor, had a down-regulated expression under the salt condition and it was predicted to be involved in the salt tolerance at the rice germination stage. Our study revealed some novel candidate genes and their substantial natural variations in the rice genome at the germination stage. The GWAS in rice at the germination stage would provide important resources for molecular breeding and functional analysis of the salt tolerance during rice germination.

Association between SSR markers and fibre traits in sea island cotton (Gossypium barbadense) germplasm resources

Identification of molecular markers associated with fibre traits can accelerate cotton marker-assisted selection (MAS) programmes. In this study, Gossypium barbadense germplasm accessions with diverse origins (n = 123) were used to perform association analysis of fibre traits with 120 polymorphic simple sequence repeat (SSR) markers. In total, 120 polymorphic primer pairs amplified 258 loci with a mean of 2.15 loci per primer. Population structure analysis identified three main clusters for the accessions, which indicated agreement of genetic and predefined populations. Marker-trait associations (n = 58) were detected for 10 fibre traits with 26 SSR markers located on 15 chromosomes. The R² (phenotypic variation explained) ranged from 3.19 to 15.21%. Two markers (NAU5465 and NAU3013) were found to be stably associated with boll number per plant (BNP) and fibre uniformity (UI), respectively. Four markers (BNL252, NAU3424,NAU3324 and CGR5202) associated with fibre quality traits preferentially clustered on the D8 chromosome, which was thus identified as an important candidate region for study molecular mechanisms underlying fibre quality and for use in breeding cotton cultivars for improving fibre quality. This study generated molecular data with a potential for better understanding of the genetic basis of the fibre traits and provided new markers for MAS in G. barbadense breeding programmes.

Genome-wide association study and gene set analysis for understanding candidate genes involved in salt tolerance at the rice seedling stage

Salt is the major factor limiting crop productivity in saline soils and is controlled by various genes. The development of salt-tolerant rice through molecular breeding methods is important to meet the needs of rice breeding. We used 295 accessions to perform a genome-wide association study (GWAS) of salt tolerance-related phenotypes in rice at the seedling stage and obtained 93 candidate genes with high association peaks across six phenotypes. We constructed a protein interaction network using the candidate genes identified here, and 33 genes were associated. Based on the expression patterns, we found that most of these genes showed a different expression level under control and salt stress conditions. In addition, haplotype network and sequence analysis of one 'key' gene, a transcription factor (Os12g0176700) encoding a SWIRM domain-containing protein, in the interaction network was investigated to explore its possible role in the network. Our study revealed candidate salt tolerance-related genes in rice at the seedling stage, and demonstrated the feasibility of using GWAS to identify genetic architecture underlying salt tolerance. The data generated here may provide resources for molecular breeding and functional analysis of salt tolerance in rice seedlings.

The Transcript Profile of a Traditional Chinese Medicine, Atractylodes lancea, Revealing Its Sesquiterpenoid Biosynthesis of the Major Active Components

Atractylodes lancea (Thunb.) DC., named “Cangzhu” in China, which belongs to the Asteraceae family. In some countries of Southeast Asia (China, Thailand, Korea, Japan etc.) its rhizome, commonly called rhizoma atractylodis, is used to treat many diseases as it contains a variety of sesquiterpenoids and other components of medicinal importance. Despite its medicinal value, the information of the sesquiterpenoid biosynthesis is largely unknown. In this study, we investigated the transcriptome analysis of different tissues of non-model plant A. lancea by using short read sequencing technology (Illumina). We found 62,352 high quality unigenes with an average sequence length of 913 bp in the transcripts of A. Lancea. Among these, 43,049 (69.04%), 30,264 (48.53%), 26,233 (42.07%), 17,881 (28.67%) and 29,057(46.60%) unigenes showed significant similarity (E-value<1e^-5) to known proteins in Nr, KEGG, SWISS-PROT, GO, and COG databases, respectively. Of the total 62,352 unigenes, 43,049 (Nr Database) open reading frames were predicted. On the basis of different bioinformatics tools we identify all the enzymes that take part in the terpenoid biosynthesis as well as five different known sesquiterpenoids via cytosolic mevalonic acid (MVA) pathway and plastidal methylerythritol phosphate (MEP) pathways. In our study, 6, 864 Simple Sequence Repeats (SSRs) were also found as great potential markers in A. lancea. This transcriptomic resource of A. lancea provides a great contribution in advancement of research for this specific medicinal plant and more specifically for the gene mining of different classes of terpenoids and other chemical compounds that have medicinal as well as economic importance.

Association Analysis in Rice: From Application to Utilization

Association analysis based on linkage disequilibrium (LD) is an efficient way to dissect complex traits and to identify gene functions in rice. Although association analysis is an effective way to construct fine maps for quantitative traits, there are a few issues which need to be addressed. In this review, we will first summarize type, structure, and LD level of populations used for association analysis of rice, and then discuss the genotyping methods and statistical approaches used for association analysis in rice. Moreover, we will review current shortcomings and benefits of association analysis as well as specific types of future research to overcome these shortcomings. Furthermore, we will analyze the reasons for the underutilization of the results within association analysis in rice breeding.

Comparative transcriptome analysis of aboveground and underground tissues of Rhodiola algida, an important ethno-medicinal herb endemic to the Qinghai-Tibetan Plateau

Transcriptome sequencing is a powerful tool for the assessment of gene expression and the identification and characterization of molecular markers in non-model organisms. Rhodiola algida L. (Crassulaceae), endemic to the Qinghai-Tibetan Plateau, has long been used in traditional Chinese medicine to prevent altitude sickness and eliminate fatigue. Illumina-based high-throughput transcriptome sequencing of aboveground and underground tissues of R. algida respectively yielded 5.40 million and 5.18 million clean reads. A total of 82,664 unigenes averaging 577 bp in length were generated from the aboveground clean reads, with 86,237 unigenes of 502-bp mean length obtained from the underground tissues. Of 55,028 unigenes compared with sequences in UniProt databases, 20,413 unigenes had significant similarities with existing sequences in NR, NT, Swiss-Prot, GO, KEGG, and COG databases. Single nucleotide polymorphism (SNP) analysis identified 237,294 SNPs from 154,636 contigs of aboveground tissues and 197,540 SNPs from 144,963 underground-derived contigs. The information uncovered in this study should serve as a valuable resource for the characterization of important traits related to secondary metabolite formation and for the identification of associated molecular mechanisms.

Evolution and association analysis of GmCYP78A10 gene with seed size/weight and pod number in soybean

Seed-size/weight traits, controlled by multiple genes in soybean, play an important role in determining seed yield. However, the molecular mechanisms controlling the seed size and weight in soybean remain unclear. In Arabidopsis, P450/CYP78A gene family has been proved extremely relevant to seed size (such as AtCYP78A5, AtCYP78A6 and AtCYP78A9). We found that a soybean GmCYP78A10 gene underwent artificial selection during soybean breeding. The GmCYP78A10a allele mainly distributed in wild soybean (Glycine soja), but has been eliminated in the cultivars during early stage of soybean breeding, while the GmCYP78A10b allele has been accumulated and become the predominant allele in cultivated soybean (G. max). ANOVA analysis showed that the mean seed weight, seed width and seed thickness of soybean varieties with GmCYP78A10b allele was significantly heavier/bigger than those with GmCYP78A10a allele (P < 0.01). The allele could explain 7.2 % variation in seed weight. The pod number of the soybeans with GmCYP78A10b allele significantly decreased compared to those with GmCYP78A10a allele (P < 0.01, R(2) = 5.8 %), while other agronomic traits including seed weight/plant were not significantly affected by these two alleles. We speculated that during the early stage of soybean breeding, breeders selected big seed carrying GmCYP78A10b allele, but lowered pod number simultaneously. Overall, the selection did not cause the significantly change in soybean seed yield. Our results suggests that the soybean GmCYP78A10 gene may have a similar function to those genes belonging to P450/CYP78A subfamily in Arabidopsis and provides new information for the genetic control of seed size in soybean.

Diversity characterization and association analysis of agronomic traits in a Chinese peanut (Arachis hypogaea L.) mini-core collection

Association mapping is a powerful approach for exploring the molecular basis of phenotypic variations in plants. A peanut (Arachis hypogaea L.) mini-core collection in China comprising 298 accessions was genotyped using 109 simple sequence repeat (SSR) markers, which identified 554 SSR alleles and phenotyped for 15 agronomic traits in three different environments, exhibiting abundant genetic and phenotypic diversity within the panel. A model-based structure analysis assigned all accessions to three groups. Most of the accessions had the relative kinship of less than 0.05, indicating that there were no or weak relationships between accessions of the mini-core collection. For 15 agronomic traits in the peanut panel, generally the Q + K model exhibited the best performance to eliminate the false associated positives compared to the Q model and the general linear model-simple model. In total, 89 SSR alleles were identified to be associated with 15 agronomic traits of three environments by the Q + K model-based association analysis. Of these, eight alleles were repeatedly detected in two or three environments, and 15 alleles were commonly detected to be associated with multiple agronomic traits. Simple sequence repeat allelic effects confirmed significant differences between different genotypes of these repeatedly detected markers. Our results demonstrate the great potential of integrating the association analysis and marker-assisted breeding by utilizing the peanut mini-core collection.

Association analysis for quality traits in a diverse panel of Chinese sesame (Sesamum indicum L.) germplasm

The main objective of this study was to evaluate the potential of a sesame (Sesamum indicum L.) panel for association analysis, and investigate the genetic basis of oil content (OC), protein content, oleic acid concentration, and linoleic acid concentration using association mapping. A panel of 216 sesame accessions was phenotyped in a multi-environment trial and fingerprinted with 608 polymorphic loci produced by 79 primers, including simple sequence repeats (SSRs), sequence-related amplified polymorphisms (SRAPs), and amplified fragment length polymorphisms (AFLPs). Population structure analysis revealed two subgroups in the population. The Q model performed better for its ability to re-identify associations for the four traits at highly significant P-values compared to the other three mixed models. And a total of 35 and 25 associations for the four traits in 2010 and 2011 were identified, respectively, with the Q model after Bonferroni correction. Among those associations, only one for OC was re-identified in two environments, and several markers associated simultaneously with multiple traits were discovered. These results suggest the power and stability of the Q model for association analysis of nutritional traits in this sesame panel for its slight population stratification and familial relationship, which could aid in dissecting complex traits, and could help to develop strategies for improving nutritional quality.