Genome-wide association studies reveal novel QTLs, QTL-by-environment interactions and their candidate genes for tocopherol content in soybean seed

Joint GWAS and WGCNA Identify Genes Regulating the Isoflavone Content in Soybean Seeds

Isoflavone is a secondary metabolite of the soybean phenylpropyl biosynthesis pathway with physiological activity and is beneficial to human health. In this study, the isoflavone content of 205 soybean germplasm resources from 3 locations in 2020 showed wide phenotypic variation. A joint genome-wide association study (GWAS) and weighted gene coexpression network analysis (WGCNA) identified 33 single-nucleotide polymorphisms and 11 key genes associated with soybean isoflavone content. Gene ontology enrichment analysis, gene coexpression, and haplotype analysis revealed natural variations in the Glyma.12G109800 (GmOMT7) gene and promoter region, with Hap1 being the elite haplotype. Transient overexpression and knockout of GmOMT7 increased and decreased the isoflavone content, respectively, in hairy roots. The combination of GWAS and WGCNA effectively revealed the genetic basis of soybean isoflavone and identified potential genes affecting isoflavone synthesis and accumulation in soybean, providing a valuable basis for the functional study of soybean isoflavone.

Genome-wide association study and expression of candidate genes for Fe and Zn concentration in sorghum grains

Sorghum germplasm showed grain Fe and Zn genetic variability, but a few varieties were biofortified with these minerals. This work contributes to narrowing this gap. Fe and Zn concentrations along with 55,068 high-quality GBS SNP data from 140 sorghum accessions were used in this study. Both micronutrients exhibited good variability with respective ranges of 22.09-52.55 ppm and 17.92-43.16 ppm. Significant marker-trait associations were identified on chromosomes 1, 3, and 5. Two major effect SNPs (S01_72265728 and S05_58213541) explained 35% and 32% of Fe and Zn phenotypic variance, respectively. The SNP S01_72265728 was identified in the cytochrome P450 gene and showed a positive effect on Fe accumulation in the kernel, while S05_58213541 was intergenic near Sobic.005G134800 (zinc-binding ribosomal protein) and showed negative effect on Zn. Tissue-specific in silico expression analysis resulted in higher levels of Sobic.003G350800 gene product in several tissues such as leaf, root, flower, panicle, and stem. Sobic.005G188300 and Sobic.001G463800 were expressed moderately at grain maturity and anthesis in leaf, root, panicle, and seed tissues. The candidate genes expressed in leaves, stems, and grains will be targeted to improve grain and stover quality. The haplotypes identified will be useful in forward genetics breeding.

Genome-wide association studies using multi-models and multi-SNP datasets provide new insights into pasmo resistance in flax

Introduction

Flax (Linum usitatissimum L.) is an economically important crop due to its oil and fiber. However, it is prone to various diseases, including pasmo caused by the fungus Septoria linicola.

Methods

In this study, we conducted field evaluations of 445 flax accessions over a five-year period (2012-2016) to assess their resistance to pasmo A total of 246,035 single nucleotide polymorphisms (SNPs) were used for genetic analysis. Four statistical models, including the single-locus model GEMMA and the multi-locus models FarmCPU, mrMLM, and 3VmrMLM, were assessed to identify quantitative trait nucleotides (QTNs) associated with pasmo resistance.

Results

We identified 372 significant QTNs or 132 tag QTNs associated with pasmo resistance from five pasmo resistance datasets (PAS2012-PAS2016 and the 5-year average, namely PASmean) and three genotypic datasets (the all SNPs/ALL, the gene-based SNPs/GB and the RGA-based SNPs/RGAB). The tag QTNs had R2 values of 0.66-16.98% from the ALL SNP dataset, 0.68-20.54%from the GB SNP dataset, and 0.52-22.42% from the RGAB SNP dataset. Of these tag QTNs, 93 were novel. Additionally, 37 resistance gene analogs (RGAs)co-localizing with 39 tag QTNs were considered as potential candidates for controlling pasmo resistance in flax and 50 QTN-by-environment interactions(QEIs) were identified to account for genes by environmental interactions. Nine RGAs were predicted as candidate genes for ten QEIs.

Discussion

Our results suggest that pasmo resistance in flax is polygenic and potentially influenced by environmental factors. The identified QTNs provide potential targets for improving pasmo resistance in flax breeding programs. This study sheds light on the genetic basis of pasmo resistance and highlights the importance of considering both genetic and environmental factors in breeding programs for flax.

Genome-wide association study of cooking-caused grain expansion in rice (Oryza sativa L.)

Cooking-caused rice grain expansion (CCRGE) is a critical trait for evaluating the cooking quality of rice. Previous quantitative trait locus (QTL) mapping studies on CCRGE have been limited to bi-parental populations, which restrict the exploration of natural variation and mapping resolution. To comprehensively and precisely dissect the genetic basis of CCRGE, we performed a genome-wide association study (GWAS) on three related indices: grain breadth expansion index (GBEI), grain length expansion index (GLEI), and grain length-breadth ratio expansion index (GREI), using 345 rice accessions grown in two years (environments) and 193,582 SNP markers. By analyzing each environment separately using seven different methods (3VmrMLM, mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, ISIS EM-BLASSO), we identified a total of 32, 19 and 27 reliable quantitative trait nucleotides (QTNs) associated with GBEI, GLEI and GREI, respectively. Furthermore, by jointly analyzing the two environments using 3VmrMLM, we discovered 19, 22 and 25 QTNs, as well as 9, 5 and 7 QTN-by-environment interaction (QEIs) associated with GBEI, GLEI and GREI, respectively. Notably, 12, 9 and 15 QTNs for GBEI, GLEI and GREI were found within the intervals of previously reported QTLs. In the vicinity of these QTNs or QEIs, based on analyses of mutation type, gene ontology classification, haplotype, and expression pattern, we identified five candidate genes that are related to starch synthesis and endosperm development. The five candidate genes, namely, LOC_Os04g53310 (OsSSIIIb, near QTN qGREI-4.5s), LOC_Os05g02070 (OsMT2b, near QTN qGLEI-5.1s), LOC_Os06g04200 (wx, near QEI qGBEI-6.1i and QTNs qGREI-6.1s and qGLEI-6.1t), LOC_Os06g12450 (OsSSIIa, near QTN qGLEI-6.2t), and LOC_Os08g09230 (OsSSIIIa, near QTN qGBEI-8.1t), are predicted to be involved in the process of rice grain starch synthesis and to influence grain expansion after cooking. Our findings provide valuable insights and will facilitate genetic research and improvement of CCRGE.

Genome-Wide Association Studies of Seven Root Traits in Soybean (Glycine max L.) Landraces

Soybean [Glycine max (L.) Merr.], an important oilseed crop, is a low-cost source of protein and oil. In Southeast Asia and Africa, soybeans are widely cultivated for use as traditional food and feed and industrial purposes. Given the ongoing changes in global climate, developing crops that are resistant to climatic extremes and produce viable yields under predicted climatic conditions will be essential in the coming decades. To develop such crops, it will be necessary to gain a thorough understanding of the genetic basis of agronomic and plant root traits. As plant roots generally lie beneath the soil surface, detailed observations and phenotyping throughout plant development present several challenges, and thus the associated traits have tended to be ignored in genomics studies. In this study, we phenotyped 357 soybean landraces at the early vegetative (V2) growth stages and used a 180 K single-nucleotide polymorphism (SNP) soybean array in a genome-wide association study (GWAS) conducted to determine the phenotypic relationships among root traits, elucidate the genetic bases, and identify significant SNPs associated with root trait-controlling genomic regions/loci. A total of 112 significant SNP loci/regions were detected for seven root traits, and we identified 55 putative candidate genes considered to be the most promising. Our findings in this study indicate that a combined approach based on SNP array and GWAS analyses can be applied to unravel the genetic basis of complex root traits in soybean, and may provide an alternative high-resolution marker strategy to traditional bi-parental mapping. In addition, the identified SNPs, candidate genes, and diverse variations in the root traits of soybean landraces will serve as a valuable basis for further application in genetic studies and the breeding of climate-resilient soybeans characterized by improved root traits.