Abstract

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.

Highlights

  • Soybean [Glycine max (L.) Merr.] is a major crop used for food, feed, and biofuel on the globe

  • While traits like plant architecture, seed yield components, nutrient use efficiency, photosynthetic efficiency, abiotic and biotic stress tolerance are desirable for sustainable higher productivity, traits like protein content, oil content and quality, fragrance, sweetness, tocopherols, and secondary metabolites are desirable for producing good quality consumer products

  • Characterized genes are those which have been functionally validated by gain of function experiments such as genetic transformation, transient gene expression or phenotypic validation in near isogenic lines (NILs), while others identified based on homology and expression analysis were considered as candidate genes for respective QTLs

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Summary

INTRODUCTION

Soybean [Glycine max (L.) Merr.] is a major crop used for food, feed, and biofuel on the globe. The main reasons for poor utilization of QTLs in soybean breeding programme are; the large size of the mapped genomic regions, small contribution to phenotypic variation, and genetic background effect of recipient parent which demands further validation (Collard and Mackill, 2008; Ratnaparkhe et al, 2014.) For their effective use in breeding programme it is required to narrow down the confidence intervals of QTLs, identify the underlying genes and the most important is allelic characterization of these genes for identifying superior variants. QTL mapping is performed using bi-parental mapping populations with low density marker coverage This results in poor resolution of QTLs, identifying large genomic regions with limited information on gene(s) underlying important agronomic traits (Sonah et al, 2015).

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Findings
CONCLUSION AND FUTURE PERSPECTIVES
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