Seed Longevity in Legumes: Deeper Insights Into Mechanisms and Molecular Perspectives

Abstract

Sustainable agricultural production largely depends upon the viability and longevity of high-quality seeds during storage. Legumes are considered as rich source of dietary protein that helps to ensure nutritional security, but associated with poor seed longevity that hinders their performance and productivity in farmer's fields. Seed longevity is the key determinant to assure proper seed plant value and crop yield. Thus, maintenance of seed longevity during storage is of prime concern and a pre-requisite for enhancing crop productivity of legumes. Seed longevity is significantly correlated with other seed quality parameters such as germination, vigor, viability and seed coat permeability that affect crop growth and development, consequently distressing crop yield. Therefore, information on genetic basis and regulatory networks associated with seed longevity, as well as molecular dissection of traits linked to longevity could help in developing crop varieties with good storability. Keeping this in view, the present review focuses towards highlighting the molecular basis of seed longevity, with special emphasis on candidate genes and proteins associated with seed longevity and their interplay with other quality parameters. Further, an attempt was made to provide information on 3D structures of various genetic loci (genes/proteins) associated to seed longevity that could facilitate in understanding the interactions taking place within the seed at molecular level. This review compiles and provides information on genetic and genomic approaches for the identification of molecular pathways and key players involved in the maintenance of seed longevity in legumes, in a holistic manner. Finally, a hypothetical fast-forward breeding pipeline has been provided, that could assist the breeders to successfully develop varieties with improved seed longevity in legumes.

Keywords: crop productivity; genes; legumes; molecular pathways; seed longevity.

Figure 1

Schematic representation of interplay between factors determining seed longevity. Seed attains maximum dry weight during mass maturity (MM). Seed vigour and longevity progressively developed during late maturation phase and reaches maximum during harvest maturity (HM). During dry storage, longevity is a result of interaction between various intrinsic and extrinsic factors. Seed longevity is not indefinite; it decreases gradually and lost completely at some point of time. DT: desiccation tolerance; RFOs: raffinose family oligosaccharides; LEA: late embryogenesis abundant; HSPs: heat shock proteins, RH: relative humidity, TAG: triacylglycerol; SMC: seed moisture content, FR: free radicals, ROS: reactive oxygen species.

Figure 2

Molecular mechanisms involved in regulating seed longevity during storage. ABA: abscisic acid, BER: base excision repair, DSB: double strand breaks, HR: homologous repair, SSP: seed storage proteins, HSP: heat shock protein, IAA: indole-3-acetic acid, LEA: late embryogenesis abundant, MSR: methionine sulfoxide reductase, NHEJ: non-homologous end joining, NER: nucleotide excision repair, PIMT: protein L -isoaspartyl methyltransferase, PYR/PYL/RCAR: pyrabactin resistance/PYR1-like/regulatory components of ABA receptors, RFOs: raffinose family oligosaccharides, ROS: reactive oxygen species, snRK2: sucrose non-fermenting 1- related subfamily 2, TIP: tonoplast intrinsic protein, TIR1: transport inhibitor response 1, TF: transcription factor.

Figure 3

3D structure of candidate genes/proteins associated with seed longevity in legumes. (A) GolS1 (Active site residues are Ile107, Lys111, Asp127, Thr158, Trp159, Ser160, Ala222, Glu223, Cys267, Lys272, Phe35, Ala37, Tyr42 (B) ABI5 (Active site residues are Arg298, His301, His302, Lys305, Asn306, Ser309), (C) DOG1 (Active site residues are Phe101, Leu104, Tyr15, Trp18, Met19, Gln22, Ile55, Phe59, Tyr62, Arg66, Tyr77, Asn83, Glu87, Leu90, Trp92, Met93, Gly94, Gly95, Cys96, Pro98).

Figure 4

A hypothetical integrated fast forward breeding pipeline AI: artificial intelligence, IoT: internet of things, GBS: genotyping by sequencing, GWAS: genome wide association study, QTL: quantitative trait loci.