Food legumes play an important role in attaining both food and nutritional security along with sustainable agricultural production for the well-being of humans globally. The various traits of economic importance in legume crops are complex and quantitative in nature, which are governed by quantitative trait loci (QTLs). Mapping of quantitative traits is a tedious and costly process, however, a large number of QTLs has been mapped in soybean for various traits albeit their utilization in breeding programmes is poorly reported. For their effective use in breeding programme it is imperative to narrow down the confidence interval of QTLs, to identify the underlying genes, and most importantly allelic characterization of these genes for identifying superior variants. In the field of functional genomics, especially in the identification and characterization of gene responsible for quantitative traits, soybean is far ahead from other legume crops. The availability of genic information about quantitative traits is more significant because it is easy and effective to identify homologs than identifying shared syntenic regions in other crop species. In soybean, genes underlying QTLs have been identified and functionally characterized for phosphorous efficiency, flowering and maturity, pod dehiscence, hard-seededness, α-Tocopherol content, soybean cyst nematode, sudden death syndrome, and salt tolerance. Candidate genes have also been identified for many other quantitative traits for which functional validation is required. Using the sequence information of identified genes from soybean, comparative genomic analysis of homologs in other legume crops could discover novel structural variants and useful alleles for functional marker development. The functional markers may be very useful for molecular breeding in soybean and harnessing benefit of translational research from soybean to other leguminous crops. Thus, soybean crop can act as a model crop for translational genomics and breeding of quantitative traits in legume crops. In this review, we summarize current status of identification and characterization of genes underlying QTLs for various quantitative traits in soybean and their significance in translational genomics and breeding of other legume crops.

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QTLomics in Soybean: A Way Forward for Translational Genomics and Breeding

Shoot architecture is fundamentally crucial to crop growth and productivity. As a key component of shoot architecture, plant height is known to be controlled by both genetic and environmental factors, though specific details remain scarce. In this study, 308 representative soybean lines from a core collection and 168 F9 soybean progeny were planted at distinct field sites. The results demonstrated the presence of significant genotype × environment interaction (G × E) effects on traits associated with plant height in a natural soybean population. In total, 19 loci containing 51 QTLs (quantitative trait locus) for plant height were identified across four environments, with 23, 13 and 15 being QTLs for SH (shoot height), SNN (stem node number) and AIL (average internode length), respectively. Significant LOD ranging from 2.50 to 16.46 explained 2.80–26.10% of phenotypic variation. Intriguingly, only two loci, Loc11 and Loc19–1, containing 20 QTLs, were simultaneously detected across all environments. Results from Pearson correlation analysis and PCA (principal component analysis) revealed that each of the five agro-meteorological factors and four soil properties significantly affected soybean plant height traits, and that the corresponding QTLs had additive effects. Among significant environmental factors, AD (average day-length), AMaT (average maximum temperature), pH, and AN (available nitrogen) had the largest impacts on soybean plant height. Therefore, in spite of uncontrollable agro-meteorological factors, soybean shoot architecture might be remolded through combined efforts to produce superior soybean genetic materials while also optimizing soil properties. Overall, the comprehensive set of relationships outlined herein among environment factors, soybean genotypes and QTLs in effects on plant height opens new avenues to explore in work aiming to increase soybean yield through improvements in shoot architecture.

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Environmental and genetic regulation of plant height in soybean

Flowering time and maturity are important agronomic traits for soybean cultivars to adapt to different latitudes and achieve maximal yield. Genetic studies on genes and quantitative trait loci (QTLs) that control flowering time and maturity are extensive. In particular, the molecular bases of E1-E4, E6, E9, E10, and J have been deciphered. For a better understanding of regulation of flowering time gene networks, we need to understand if more molecular factors carrying different biological functions are also involved in the regulation of flowering time in soybeans. We developed a population derived from a cross between a landrace Jilincailihua (male) and a Chinese cultivar Chongnong16 (female). Both parents carry the same genotypes of E1e2E3HaE4 at E1, E2, E3, and E4 loci. 96 individuals of the F2 population were genotyped with Illumina SoySNP8k iSelect BeadChip. A total of 2407 polymorphic single nucleotide polymorphism (SNP) markers were used to construct a genetic linkage map. One major QTL, qFT12-1, was mapped to an approximately 567kb region on chromosome 12. Using F2 or their progeny plants, which had recombinant events occurring within the QTL region, allowed us to narrow down the QTL region to 56.4kb, in which four genes were annotated. Allelism and associations analysis indicated Glyma. 12G073900, a PRR3 homolog, as the strongest candidate gene for flowering time. The findings of this study disclosed the possible involvement of clock gene to flowering time regulation of soybeans.

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Positional Cloning of the Flowering Time QTL qFT12-1 Reveals the Link Between the Clock Related PRR Homolog With Photoperiodic Response in Soybeans.

A set of 90 Indian soybean landraces were analysed for polymorphism at 43 SSRs and five allele specific markers of four major genes involved in regulating flowering and photoperiod response. A total of 42 polymorphic SSRs had amplified 126 alleles which served as raw data for estimation of genetic relationship and population structure among 90 accessions. Rare alleles of four and three SSRs were detected in accessions IC18768 and IC15089, respectively. Gene diversity in the population ranges from 0.065 to 0.717 with a mean value of 0.411. The polymorphism information content of 42 SSRs varied from 0.063 to 0.668. Hierarchical clustering based on neighbour-joining method identified three major clusters among 90 soybean accessions. Model based population structure analysis divided the 90 soybean accessions into four populations (K = 4). Mean value of Fst for different populations ranged between 0.4143 and 0.7239. Genotyping of 90 accessions with allele specific markers had identified accession IC15089 as triple recessive mutant of flowering genes E1, E2 and photoperiod sensitivity gene E3. The triple mutant IC15089 (e1, e3, e3) had been characterized phenotypically and identified as early maturing (88 days) and photoperiod insensitive genotype under extended photoperiod. The present study characterized genetic relationship among 90 Indian soybean landraces and had identified a few diverse and unique genotypes for utilization in soybean breeding programmes targeting development of short duration and photoperiod insensitive varieties through marker assisted selection.

Genetic relationship, population structure analysis and allelic characterization of flowering and maturity genes E1 , E2 , E3 and E4 among 90 Indian soybean landraces

Natural allelic variation among the genes governing various agronomic and quality traits of plant provides opportunity to develop desirable plant type in crops. In soybean [Glycine max (L.) Merr.], natural allelic variation is known for many functionally characterized genes conferring superior phenotype for their respective governing trait. Exploring this natural allelic variation in germplasm pool through gene based allele specific multiplex marker genotyping is one way to identify and combine the alleles of multiple traits in desired genetic background. Using known alleles of 15 genes governing 10 different agronomic and quality traits, we have developed two multi-trait allele specific genic marker assays of 22-plex and 7-plex alleles. These two multi-trait allele specific genic marker assays were used to genotype a large set of diverse soybean germplasm accessions, which identified several novel genetic sources of rare alleles conferring superior or desirable phenotype. Selected genetic sources of rare alleles for days to flowering and maturity, hard-seededness, pod shattering and oleic acid content were validated phenotypically. Genotyping and phenotyping in a multi-parent advanced generation intercross population validated the utility of multi-trait allele specific genic marker assays in marker assisted selection of multiple traits from multiple parents. The novel genetic sources identified in this study will help in the selection of parents with multiple desirable traits for hybridization. The multi-trait allele specific genic marker assays developed will speed up selection of multiple traits in routine soybean breeding programmes for cultivar development and improvement.

Identification of novel genetic sources for agronomic and quality traits in soybean using multi-trait allele specific genic marker assays

Allelic combinations of major photoperiodic (E1, E3, E4) and maturity (E2) genes have extended the adaptation of quantitative photoperiod sensitive soybean crop from its origin (China ∼35◦N latitude) to both north (up to ∼50◦N) and south (up to 40◦S) latitudes, but their allelic status and role in India (6-35◦N) are unknown. Loss of function and hypoactive alleles of these genes are known to confer photoinsensitivity to long days and early maturity. Early maturity has helped to adapt soybean to short growing season of India. We had earlier found that all the Indian cultivars are sensitive to incandescent long day (ILD) and could identify six insensitive accessions through screening 2071 accessions under ILD. Available models for ILD insensitivity suggested that identified insensitive genotypes should be either e3/e4 or e1 (e1-nl or e1-fs) with either e3 or e4. We found that one of the insensitive accessions (EC 390977) was of e3/e4 genotype and hybridized it with four ILD sensitive cultivars JS 335, JS 95-60, JS 93-05, NRC 37 and an accession EC 538828. Inheritance studies and marker-based cosegregation analyses confirmed the segregation of E3 and E4 genes and identified JS 93-05 and NRC 37 as E3E3E4E4 and EC 538828 as e3e3E4E4. Further, genotyping through sequencing, derived cleaved amplified polymorphic sequences (dCAPS) and cleaved amplified polymorphic sequences (CAPS) markers identified JS 95-60 with hypoactive e1-as and JS 335 with loss of function e3-fs alleles. Presence of photoperiodic recessive alleles in these two most popular Indian cultivars suggested for their role in conferring early flowering and maturity. This observation could be confirmed in F2 population derived from the cross JS 95-60 × EC 390977, where individuals with e1-as e1-as and e4e4 genotypes could flower 7 and 2.4 days earlier, respectively. Possibility of identification of new alleles ormechanism for ILD insensitivity and use of photoinsensitivity in Indian conditions have been discussed.

Devshree Thakur

Papers

Genetic analyses for deciphering the status and role of photoperiodic and maturity genes in major Indian soybean cultivars