WGCNA analysis of the effect of exogenous BR on leaf angle of maize mutant lpa1.

Leaf angle, as one of the important agronomic traits of maize, can directly affect the planting density of maize, thereby affecting its yield. Here we used the ZmLPA1 gene mutant lpa1 to study maize leaf angle and found that the lpa1 leaf angle changed significantly under exogenous brassinosteroid (BR) treatment compared with WT (inbred line B73). Transcriptome sequencing of WT and lpa1 treated with different concentrations of exogenous BR showed that the differentially expressed genes were upregulated with auxin, cytokinin and brassinosteroid; Genes associated with abscisic acid are down-regulated. The differentially expressed genes in WT and lpa1 by weighted gene co-expression network analysis (WGCNA) yielded two gene modules associated with maize leaf angle change under exogenous BR treatment. The results provide a new theory for the regulation of maize leaf angle by lpa1 and exogenous BR.

Identification of Novel Genomic Regions for Bacterial Leaf Pustule (BLP) Resistance in Soybean (Glycine max L.) via Integrating Linkage Mapping and Association Analysis.

Bacterial leaf pustule (BLP), caused by Xanthornonas axonopodis pv. glycines (Xag), is a worldwide disease of soybean, particularly in warm and humid regions. To date, little is known about the underlying molecular mechanisms of BLP resistance. The only single recessive resistance gene rxp has not been functionally identified yet, even though the genotypes carrying the gene have been widely used for BLP resistance breeding. Using a linkage mapping in a recombinant inbred line (RIL) population against the Xag strain Chinese C5, we identified that quantitative trait locus (QTL) qrxp-17-2 accounted for 74.33% of the total phenotypic variations. We also identified two minor QTLs, qrxp-05-1 and qrxp-17-1, that accounted for 7.26% and 22.26% of the total phenotypic variations, respectively, for the first time. Using a genome-wide association study (GWAS) in 476 cultivars of a soybean breeding germplasm population, we identified a total of 38 quantitative trait nucleotides (QTNs) on chromosomes (Chr) 5, 7, 8, 9,15, 17, 19, and 20 under artificial infection with C5, and 34 QTNs on Chr 4, 5, 6, 9, 13, 16, 17, 18, and 20 under natural morbidity condition. Taken together, three QTLs and 11 stable QTNs were detected in both linkage mapping and GWAS analysis, and located in three genomic regions with the major genomic region containing qrxp_17_2. Real-time RT-PCR analysis of the relative expression levels of five potential candidate genes in the resistant soybean cultivar W82 following Xag treatment showed that of Glyma.17G086300, which is located in qrxp-17-2, significantly increased in W82 at 24 and 72 h post-inoculation (hpi) when compared to that in the susceptible cultivar Jack. These results indicate that Glyma.17G086300 is a potential candidate gene for rxp and the QTLs and QTNs identified in this study will be useful for marker development for the breeding of Xag-resistant soybean cultivars.

Study on ZmRPN10 Regulating Leaf Angle in Maize by RNA-Seq.

Ubiquitin/proteasome-mediated proteolysis (UPP) plays a crucial role in almost all aspects of plant growth and development, proteasome subunit RPN10 mediates ubiquitination substrate recognition in the UPP process. The recognition pathway of ubiquitinated UPP substrate is different in different species, which indicates that the mechanism and function of RPN10 are different in different species. However, the homologous ZmRPN10 in maize has not been studied. In this study, the changing of leaf angle and gene expression in leaves in maize wild-type B73 and mutant rpn10 under exogenous brassinosteroids (BRs) were investigated. The regulation effect of BR on the leaf angle of rpn10 was significantly stronger than that of B73. Transcriptome analysis showed that among the differentially expressed genes, CRE1, A-ARR and SnRK2 were significantly up-regulated, and PP2C, BRI1 AUX/IAA, JAZ and MYC2 were significantly down-regulated. This study revealed the regulation mechanism of ZmRPN10 on maize leaf angle and provided a promising gene resource for maize breeding.

Genome-wide association study uncovers major genetic loci associated with seed flooding tolerance in soybean.

BACKGROUND: Seed flooding stress is one of the threatening environmental stressors that adversely limits soybean at the germination stage across the globe. The knowledge on the genetic basis underlying seed-flooding tolerance is limited. Therefore, we performed a genome-wide association study (GWAS) using 34,718 single nucleotide polymorphism (SNPs) in a panel of 243 worldwide soybean collections to identify genetic loci linked to soybean seed flooding tolerance at the germination stage. RESULTS: In the present study, GWAS was performed with two contrasting models, Mixed Linear Model (MLM) and Multi-Locus Random-SNP-Effect Mixed Linear Model (mrMLM) to identify significant SNPs associated with electrical conductivity (EC), germination rate (GR), shoot length (ShL), and root length (RL) traits at germination stage in soybean. With MLM, a total of 20, 40, 4, and 9 SNPs associated with EC, GR, ShL and RL, respectively, whereas in the same order mrMLM detected 27, 17, 13, and 18 SNPs. Among these SNPs, two major SNPs, Gm_08_11971416, and Gm_08_46239716 were found to be consistently connected with seed-flooding tolerance related traits, namely EC and GR across two environments. We also detected two SNPs, Gm_05_1000479 and Gm_01_53535790 linked to ShL and RL, respectively. Based on Gene Ontology enrichment analysis, gene functional annotations, and protein-protein interaction network analysis, we predicted eight candidate genes and three hub genes within the regions of the four SNPs with Cis-elements in promoter regions which may be involved in seed-flooding tolerance in soybeans and these warrant further screening and functional validation. CONCLUSIONS: Our findings demonstrate that GWAS based on high-density SNP markers is an efficient approach to dissect the genetic basis of complex traits and identify candidate genes in soybean. The trait associated SNPs could be used for genetic improvement in soybean breeding programs. The candidate genes could help researchers better understand the molecular mechanisms underlying seed-flooding stress tolerance in soybean.

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.

Genetic Architecture and Candidate Genes for Pubescence Length and Density and Its Relationship With Resistance to Common Cutworm in Soybean.

Soybean pubescence plays an important role in insect resistance, drought tolerance, and other stresses. Hence, a deep understanding of the molecular mechanism underlying pubescence is a prerequisite to a deeper understanding of insect resistance and drought tolerance. In the present study, quantitative trait loci (QTL) mapping of pubescence traits was performed using a high-density inter-specific linkage map of one recombinant inbred line (RIL) population, designated NJRINP. It was observed that pubescence length (PL) was negatively correlated with pubescence density (PD). A total of 10 and 9 QTLs distributed on six and five chromosomes were identified with phenotypic variance (PV) of 3.0-9.9% and 0.8-15.8% for PL and PD, respectively, out of which, eight and five were novel. Most decreased PL (8 of 10) and increased PD (8 of 9) alleles were from the wild soybean PI 342618B. Based on gene annotation, Protein ANalysis THrough Evolutionary Relationships and literature search, 21 and 12 candidate genes were identified related to PL and PD, respectively. In addition, Glyma.12G187200 from major QTLs qPL-12-1 and qPD-12-2, was identified as Ps (sparse pubescence) before, having an expression level of fivefold greater in NN 86-4 than in PI 342618B, hence it might be the candidate gene that is conferring both PL and PD. Based on gene expression and cluster analysis, three and four genes were considered as the important candidate genes of PL and PD, respectively. Besides, leaves with short and dense (SD) pubescence, which are similar to the wild soybean pubescence morphology, had the highest resistance to common cutworm (CCW) in soybean. In conclusion, the findings in the present study provide a better understanding of genetic basis and candidate genes information of PL and PD and the relationship with resistance to CCW in soybean.

Exploring genetic architecture for pod-related traits in soybean using image-based phenotyping.

Mature pod color (PC) and pod size (PS) served as important characteristics are used in the soybean breeding programs. However, manual phenotyping of such complex traits is time-consuming, laborious, and expensive for breeders. Here, we collected pod images from two different populations, namely, a soybean association panel (SAP) consisting of 187 accessions and an inter-specific recombinant inbred line (RIL) population containing 284 RILs. An image-based phenotyping method was developed and used to extract the pod color- and size-related parameters from images. Genome-wide association study (GWAS) and linkage mapping were performed to decipher the genetic control of pod color- and size-related traits across 2 successive years. Both populations exhibited wide phenotypic variations and continuous distribution in pod color- and size-related traits, indicating quantitative polygenic inheritance of these traits. GWAS and linkage mapping approaches identified the two major quantitative trait loci (QTL) underlying the pod color parameters, i.e., qPC3 and qPC19, located to chromosomes 3 and 19, respectively, and 12 stable QTLs for pod size-related traits across nine chromosomes. Several genes residing within the genomic region of stable QTL were identified as potential candidates underlying these pod-related traits based on the gene annotation and expression profiling data. Our results provide the useful information for fine-mapping/map-based cloning of QTL and marker-assisted selection of elite varieties with desirable pod traits. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01223-2.

Identification of QTN and Candidate Gene for Seed-flooding Tolerance in Soybean [Glycine max (L.) Merr.] using Genome-Wide Association Study (GWAS).

Seed-flooding stress is one of the major abiotic constraints severely affecting soybean yield and quality. Understanding the molecular mechanism and genetic basis underlying seed-flooding tolerance will be of greatly importance in soybean breeding. However, very limited information is available about the genetic basis of seed-flooding tolerance in soybean. The present study performed Genome-Wide Association Study (GWAS) to identify the quantitative trait nucleotides (QTNs) associated with three seed-flooding tolerance related traits, viz., germination rate (GR), normal seedling rate (NSR) and electric conductivity (EC), using a panel of 347 soybean lines and the genotypic data of 60,109 SNPs with MAF > 0.05. A total of 25 and 21 QTNs associated with all three traits were identified via mixed linear model (MLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) in three different environments (JP14, HY15, and Combined). Among these QTNs, three major QTNs, viz., QTN13, qNSR-10 and qEC-7-2, were identified through both methods MLM and mrMLM. Interestingly, QTN13 located on Chr.13 has been consistently identified to be associated with all three studied traits in both methods and multiple environments. Within the 1.0 Mb physical interval surrounding the QTN13, nine candidate genes were screened for their involvement in seed-flooding tolerance based on gene annotation information and available literature. Based on the qRT-PCR and sequence analysis, only one gene designated as GmSFT (Glyma.13g248000) displayed significantly higher expression level in all tolerant genotypes compared to sensitive ones under flooding treatment, as well as revealed nonsynonymous mutation in tolerant genotypes, leading to amino acid change in the protein. Additionally, subcellular localization showed that GmSFT was localized in the nucleus and cell membrane. Hence, GmSFT was considered as the most likely candidate gene for seed-flooding tolerance in soybean. In conclusion, the findings of the present study not only increase our knowledge of the genetic control of seed-flooding tolerance in soybean, but will also be of great utility in marker-assisted selection and gene cloning to elucidate the mechanisms of seed-flooding tolerance.

Utilization of Interspecific High-Density Genetic Map of RIL Population for the QTL Detection and Candidate Gene Mining for 100-Seed Weight in Soybean.

Seed-weight is one of the most important traits determining soybean yield. Hence, it is prerequisite to have detailed understanding of the genetic basis regulating seed-weight for the development of improved cultivars. In this regard, the present study used high-density interspecific linkage map of NJIR4P recombinant inbred population evaluated in four different environments to detect stable Quantitative trait loci (QTLs) as well as mine candidate genes for 100-seed weight. In total, 19 QTLs distributed on 12 chromosomes were identified in all individual environments plus combined environment, out of which seven were novel and eight are stable identified in more than one environment. However, all the novel QTLs were minor (R 2 < 10%). The remaining 12 QTLs detected in this study were co-localized with the earlier reported QTLs with narrow genomic regions, and out of these only 2 QTLs were major (R 2 > 10%) viz., qSW-17-1 and qSW-17-4. Beneficial alleles of all identified QTLs were derived from cultivated soybean parent (Nannong493-1). Based on Protein ANalysis THrough Evolutionary Relationships, gene annotation information, and literature search, 29 genes within 5 stable QTLs were predicted to be possible candidate genes that might regulate seed-weight/size in soybean. However, it needs further validation to confirm their role in seed development. In conclusion, the present study provides better understanding of trait genetics and candidate gene information through the use high-density inter-specific bin map, and also revealed considerable scope for genetic improvement of 100-seed weight in soybean using marker-assisted breeding.

Genome-Wide Association Studies for Dynamic Plant Height and Number of Nodes on the Main Stem in Summer Sowing Soybeans.

Plant height (PH) and the number of nodes on the main stem (NN) serve as major plant architecture traits affecting soybean seed yield. Although many quantitative trait loci for the two traits have been reported, their genetic controls at different developmental stages in soybeans remain unclear. Here, 368 soybean breeding lines were genotyped using 62,423 single nucleotide polymorphism (SNP) markers and phenotyped for the two traits at three different developmental stages over two locations in order to identify their quantitative trait nucleotides (QTNs) using compressed mixed linear model (CMLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) approaches. As a result, 11 and 13 QTNs were found by CMLM to be associated with PH and NN, respectively. Among these QTNs, 8, 3, and 4 for PH and 6, 6, and 8 for NN were found at the three stages, and 3 and 6 were repeatedly detected for PH and NN. In addition, 34 and 30 QTNs were found by mrMLM to be associated with PH and NN, respectively. Among these QTNs, 11, 13, and 16 for PH and 11, 15, and 8 for NN were found at the three stages. A majority of these QTNs overlapped with the previously reported loci. Moreover, one QTN within the known E2 locus for flowering time was detected for the two traits at all three stages, and another that overlapped with the Dt1 locus for stem growth habit was also identified for the two traits at the mature stage. This may explain the highly significant correlation between the two traits. Our findings provide evidence for mixed major plus polygenes inheritance for dynamic traits and an extended understanding of their genetic architecture for molecular dissection and breeding utilization in soybeans.

Identification of Major Quantitative Trait Loci for Seed Oil Content in Soybeans by Combining Linkage and Genome-Wide Association Mapping.

Soybean oil is the most widely produced vegetable oil in the world and its content in soybean seed is an important quality trait in breeding programs. More than 100 quantitative trait loci (QTLs) for soybean oil content have been identified. However, most of them are genotype specific and/or environment sensitive. Here, we used both a linkage and association mapping methodology to dissect the genetic basis of seed oil content of Chinese soybean cultivars in various environments in the Jiang-Huai River Valley. One recombinant inbred line (RIL) population (NJMN-RIL), with 104 lines developed from a cross between M8108 and NN1138-2, was planted in five environments to investigate phenotypic data, and a new genetic map with 2,062 specific-locus amplified fragment markers was constructed to map oil content QTLs. A derived F2 population between MN-5 (a line of NJMN-RIL) and NN1138-2 was also developed to confirm one major QTL. A soybean breeding germplasm population (279 lines) was established to perform a genome-wide association study (GWAS) using 59,845 high-quality single nucleotide polymorphism markers. In the NJMN-RIL population, 8 QTLs were found that explained a range of phenotypic variance from 6.3 to 26.3% in certain planting environments. Among them, qOil-5-1, qOil-10-1, and qOil-14-1 were detected in different environments, and qOil-5-1 was further confirmed using the secondary F2 population. Three loci located on chromosomes 5 and 20 were detected in a 2-year long GWAS, and one locus that overlapped with qOil-5-1 was found repeatedly and treated as the same locus. qOil-5-1 was further localized to a linkage disequilibrium block region of approximately 440 kb. These results will not only increase our understanding of the genetic control of seed oil content in soybean, but will also be helpful in marker-assisted selection for breeding high seed oil content soybean and gene cloning to elucidate the mechanisms of seed oil content.