Mapping developmental QTL for plant height in soybean [Glycine max (L.) Merr.] using a four-way recombinant inbred line population

Design principles for synthetic control systems to engineer plants

KEY MESSAGE

Synthetic control systems have led to significant advancement in the study and engineering of unicellular organisms, but it has been challenging to apply these tools to multicellular organisms like plants. The ability to predictably engineer plants will enable the development of novel traits capable of alleviating global problems, such as climate change and food insecurity. Engineering predictable multicellular phenotypes will require the development of synthetic control systems that can precisely regulate how the information encoded in genomes is translated into phenotypes. Many efficient control systems have been developed for unicellular organisms. However, it remains challenging to use such tools to study or engineer multicellular organisms. Plants are a good chassis within which to develop strategies to overcome these challenges, thanks to their capacity to withstand large-scale reprogramming without lethality. Additionally, engineered plants have great potential for solving major societal problems. Here we briefly review the progress of control system development in unicellular organisms, and how that information can be leveraged to characterize control systems in plants. Further, we discuss strategies for developing control systems designed to regulate the expression of transgenes or endogenous loci and generate dosage-dependent or discrete traits. Finally, we discuss the utility that mathematical models of biological processes have for control system deployment.

Genetic Diversity Analysis of Soybean Collection Using Simple Sequence Repeat Markers

Soybean [Glycine max (L.) Merr.] is a nutrient-rich crop that offers a sustainable source of dietary protein and edible oil. Determining the level of genetic diversity and relationships between various genetic resources involved in breeding programs is very important in crop improvement strategies. This study evaluated 100 soybean accessions with diverse origins for 10 important agronomic traits, including plant height (PH), an important plant adaptation-related trait impacting yield, in conditions in southeastern Kazakhstan for 2 years. The comparison of different groups of PH (tall, middle, and short) using a t-test suggested that the group of plants with the tallest PH provided a higher yield (p < 0.001) in relatively dry field conditions. The genetic diversity of the accessions was estimated using 25 simple sequence repeat (SSR) markers previously known to be associated with plant height. The results showed a significant variation among different groups of origin for all measured agronomic traits, as well as high genetic diversity, with the PIC (polymorphism information content) varying from 0.140 to 0.732, with an average of 0.524. Nei's diversity index ranged between 0.152 and 0.747, with an average of 0.526. The principal coordinate analysis (PCoA) of the studied soybean collection showed that Kazakhstan accessions were genetically distant from European, East Asian, and North American cultivars. Twelve out of twenty-five SSR markers demonstrated significant associations with ten studied agronomic traits, including PH (p < 0.05). Six SSRs with pleiotropic effects for studied traits were selected, and their haplotypes with phenotypic effects were generated for each soybean accession. The obtained results can be used in soybean improvement programs, including molecular-assisted breeding projects.

The genetic basis of shoot architecture in soybean

Shoot architecture refers to the three-dimensional body plan of the above ground organs of the plant. The patterning of this body plan results from the tight genetic control of the size and maintenance of meristems, the initiation of axillary growth, and the timing of developmental phase transition. Variation in shoot architecture can result in dramatic differences in plant productivity and/or grain yield due to their effects on light interception, photosynthetic efficiency, response to agronomic inputs, and environmental adaptation. The fine-tuning of shoot architecture has consequently been of great interest to plant breeders, driving the need for deeper understanding of the genes and molecular mechanisms governing these traits. In soybean, the world's most important oil and protein crop, major components of shoot architecture include stem growth habit, plant height, branch angle, branch number, leaf petiole angle, and the size and shape of leaves. Key genes underlying some of these traits have been identified to integrate hormonal, developmental, and environmental signals modulating the growth and orientation of shoot organs. Here we summarize the current knowledge and recent advances in the understanding of the genetic control of these important architectural traits in soybean.

Genome-wide survey identified superior and rare haplotypes for plant height in the north-eastern soybean germplasm of China

The proper and efficient utilization of natural genetic diversity can significantly impact crop improvements. Plant height is a quantitative trait governing the plant type as well as the yield and quality of soybean. Here, we used a combined approach including a genome-wide association study (GWAS) and haplotype and candidate gene analyses to explore the genetic basis of plant height in diverse natural soybean populations. For the GWAS analysis, we used the whole-genome resequencing data of 196 diverse soybean cultivars collected from different accumulated temperature zones of north-eastern China to detect the significant single-nucleotide polymorphisms (SNPs) associated with plant height across three environments (E1, E2, and E3). A total of 33 SNPs distributed on four chromosomes, viz., Chr.02, Chr.04, Chr.06, and Chr.19, were identified to be significantly associated with plant height across the three environments. Among them, 23 were consistently detected in two or more environments and the remaining 10 were identified in only one environment. Interestingly, all the significant SNPs detected on the respective chromosomes fell within the physical interval of linkage disequilibrium (LD) decay (± 38.9 kb). Hence, these genomic regions were considered to be four quantitative trait loci (QTLs), viz., qPH2, qPH4, qPH6, and qPH19, regulating plant height. Moreover, the genomic region flanking all significant SNPs on four chromosomes exhibited strong LD. These significant SNPs thus formed four haplotype blocks, viz., Hap-2, Hap-4, Hap-6, and Hap-19. The number of haplotype alleles underlying each block varied from four to six, and these alleles regulate the different phenotypes of plant height ranging from dwarf to extra-tall heights. Nine candidate genes were identified within the four haplotype blocks, and these genes were considered putative candidates regulating soybean plant height. Hence, these stable QTLs, superior haplotypes, and candidate genes (after proper validation) can be deployed for the development of soybean cultivars with desirable plant heights.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01363-7.

Identification of superior haplotypes in a diverse natural population for breeding desirable plant height in soybean

KEY MESSAGE

Plant height of soybean is associated with a haplotype block on chromosome 19, which classified 211 soybean accessions into five distinct groups showing significant differences for the target trait. Genetic variation is pivotal for crop improvement. Natural populations are precious genetic resources. However, efficient strategies for the targeted utilization of these resources for quantitative traits, such as plant height (PH), are scarce. Being an important agronomic trait associated with soybean yield and quality, it is imperative to unravel the genetic mechanisms underlying PH in soybean. Here, a genome-wide association study (GWAS) was performed to identify single nucleotide polymorphisms (SNPs) significantly associated with PH in a natural population of 211 cultivated soybeans, which was genotyped with NJAU 355 K Soy SNP Array and evaluated across six environments. A total of 128 SNPs distributed across 17 chromosomes were found to be significantly associated with PH across six environments and a combined environment. Three significant SNPs were consistently identified in at least three environments on Chr.02 (AX-93958260), Chr.17 (AX-94154834), and Chr.19 (AX-93897200). Genomic regions of ~ 130 kb flanking these three consistent SNPs were considered as stable QTLs, which included 169 genes. Of these, 22 genes (including Dt1) were prioritized and defined as putative candidates controlling PH. The genomic region flanking 12 most significant SNPs was in strong linkage disequilibrium (LD). These SNPs formed a single haplotype block containing five haplotypes for PH, namely Hap-A, Hap-B, Hap-C, Hap-D, and Hap-E. Deployment of such superior haplotypes in breeding programs will enable development of improved soybean varieties with desirable plant height.

Quantitative Trait Locus Mapping for Drought Tolerance in Soybean Recombinant Inbred Line Population

Improving drought stress tolerance of soybean could be an effective way to minimize the yield reduction in the drought prevailing regions. Identification of drought tolerance-related quantitative trait loci (QTLs) is useful to facilitate the development of stress-tolerant varieties. This study aimed to identify the QTLs for drought tolerance in soybean using a recombinant inbred line (RIL) population developed from the cross between a drought-tolerant ‘PI416937’ and a susceptible ‘Cheonsang’ cultivar. Phenotyping was done with a weighted drought coefficient derived from the vegetative and reproductive traits. The genetic map was constructed using 2648 polymorphic SNP markers that distributed on 20 chromosomes with a mean genetic distance of 1.36 cM between markers. A total of 10 QTLs with 3.52–4.7 logarithm of odds value accounting for up to 12.9% phenotypic variance were identified on seven chromosomes. Five chromosomes—2, 7, 10, 14, and 20—contained one QTL each, and chromosomes 1 and 19 harbored two and three QTLs, respectively. The chromosomal locations of seven QTLs overlapped or located close to the related QTLs and/or potential candidate genes reported earlier. The QTLs and closely linked markers could be utilized in maker-assisted selection to accelerate the breeding for drought tolerance in soybean.

Mapping QTL/QTN and mining candidate genes for plant height and its response to planting densities in soybean [Glycine max (L.) Merr.] through a FW-RIL population

Plant height (PH) determines the morphology and seed yield of soybean, so it is an important breeding target, which is controlled by multiple genes and affected by plant density. In this research, it was used about a four-way recombinant inbred lines (FW-RIL) with 144 families constructed by double cross (Kenfeng 14 × Kenfeng 15) × (Heinong 48 × Kenfeng 19) as experimental materials, with the purpose to map QTL/QTN associated with PH under densities of 2.2×105 plant/ha (D1) and 3×105 plant/ha (D2) in five environments. The results showed that response of PH to densities varied in accordance to genotypes among environments. A total of 26 QTLs and 13 QTNs were identified specifically in D1; 20 QTLs and 21 QTNs were identified specifically in D2. Nine QTLs and one QTN were discovered commonly in two densities. Fifteen QTLs and 9 QTNs were repeatedly detected by multiple statistical methods, densities, or environments, which could be considered stable. Eighteen QTLs were detected, as well as 7 QTNs underlying responses of PH to density increment. Six QTNs, co-located in the interval of QTL, were detected in more than two environments or methods with a longer genome length over 3000 kb. Based on gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, five genes were predicted as candidates, which were likely to be involved in growth and development of PH. The results will help elucidate the genetic basis and improve molecular assistant selection of PH.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01209-0.

Quantitative Trait Locus Analysis of Protein and Oil Content in Response to Planting Density in Soybean (Glycine max [L.] Merri.) Seeds Based on SNP Linkage Mapping

Soybean varieties suitable for high planting density allow greater yields. However, the seed protein and oil contents, which determine the value of this crop, can be influenced by planting density. Thus, it is important to understand the genetic basis of the responses of different soybean genotypes to planting density. In this study, we quantified the protein and oil contents in a four-way recombinant inbred line (FW-RIL) soybean population under two planting densities and the response to density. We performed quantitative trait locus (QTL) mapping using a single nucleotide polymorphism (SNP) linkage map generated by inclusive composite interval mapping. We identified 14 QTLs for protein content and 17 for oil content at a planting density of 2.15 × 10⁵ plant/ha (D1) and 14 QTLs for protein content and 20 for oil content at a planting density 3.0 × 10⁵ plant/ha (D2). Among the QTLs detected, two oil-content QTLs was detected at both plant densities. In addition, we identified 38 QTLs for the responses of protein and oil contents to planting density. Of the QTLs detected, 70 were identified in previous studies, while 33 were newly identified. Fourty-five QTLs accounted for over 10% of the phenotypic variation of the corresponding trait, based on 23 QTLs at a marker interval distance of ~600 kb detected under different densities and with the responses to density difference. Pathway analysis revealed four candidate genes involved in protein and oil biosynthesis/metabolism. These results improve our understanding of the genetic underpinnings of protein and oil biosynthesis in soybean, laying the foundation for enhancing protein and oil contents and increasing yields in soybean.