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Recent advancement in modern genomic tools for adaptation of Lablab purpureus L to biotic and abiotic stresses: present mechanisms and future adaptations

Abstract

Hyacinth bean is an important traditional plant with substantial medicinal value. Being imperative, it is still less explored crop on genomic and transcriptomic scale that has indexed it as an “orphan” crop for its genome revolution. Among different crop legumes such as pigeon pea, chickpea, cowpea, soybean and common bean, hyacinth bean also serves as a significant source of nutrition for both tropical and temperate regions and execute an imperative function in fixing biological nitrogen in agriculture. Nonetheless, the productivity of hyacinth bean is restrained due to environmental and biotic cues. Thus, understanding of the genomic functions and identification of probable genes/proteins for major agronomic traits through transcriptomic approaches has become imperative to improve stress tolerance in hyacinth bean. For understanding the plant stress tolerance mechanisms, the deployment of functional genomics approaches viz., proteomics and metabolomics have become imperious in breeding programs in developing countries. These approaches have been successfully used in other legume crops to create protein reference maps and their exploitation through comparative approaches can greatly enhance the research and understanding of hyacinth bean biological processes to changing environmental conditions. In this review, emerging epigenomics, proteomics, metabolomics and phenomics approaches and their achievements both in model/crop legumes are discussed. Additionally, the review also provides an overview of the applications of advanced proteomics, metabolomics and next-generation sequencing technologies in the discovery of candidate biomarkers for the development of agronomically refined hyacinth bean which may further ensure food and nutritional security under adverse climacteric conditions in developing countries.

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Abbreviations

NGS:

Next-generation sequencing

QTLs:

Quantitative trait loci

ALS:

Angular leaf spot

MABC:

Marker-assisted backcrossing

DYMV:

Dolichos yellow mosaic virus

MAS:

Marker-assisted selection

YMD:

Yellow mosaic disease

SNP:

Single nucleotide polymorphisms

Indels:

Insertion and deletions

RAPD:

Random amplified polymorphic DNA

SCAR:

Sequenced characterized amplified region

AFLP:

Amplified fragment length polymorphisms

RFLP:

Restriction fragment length polymorphisms

SSR:

Simple sequence repeat

ISSR:

Inter-simple sequence repeat

CBB:

Common bacterial blight

ABA:

Abscisic acid

JA:

Jasmonic acid

SA:

Salicylic acid

NO:

Nitric oxide

GB:

Glycine betaine

miRNA:

MicroRNA

ROS:

Reactive oxygen species

H2O2 :

Hydrogen peroxide

O2 ·− :

Superoxide radical

HO· :

Hydroxyl radical

HO2 :

Perhydroxy radical

1O2 :

Singlet oxygen

PS I:

Photosystem I

PS II:

Photosystem II

CAT:

Catalase

SOD:

Superoxide dismutase

APX:

Ascorbate peroxidase

GPX:

Guaiacol peroxidase

GR:

Glutathione reductase

ASH:

Ascorbate

DHAR:

Dehydro ascorbate reductase

MDHAR:

Monodehydro ascorbate reductase

MDA:

Malondialdehyde

GSH:

Reduced glutathione

GSSG:

Oxidized glutathione

MB:

Molecular biotechnology

GE:

Genetic engineering

NAM:

Nested association mapping

MARS:

Marker-assisted recurrent selection

GWS:

Genome-wide selection

GEBVs:

Genomic-estimated breeding values

GBS:

Genotyping by sequencing

GWAS:

Genome-wide association studies

QTL-Seq:

Quantitative trait loci sequencing

BSA-Seq:

Bulked segregant analysis sequencing

BSR-Seq:

Bulked segregant RNA sequencing

Indel-Seq:

Insertion and deletion sequencing

cDNA:

Complementary DNA

EST:

Expressed sequence tag

MS:

Mass spectrometry

2D-GE:

Two-dimensional gel electrophoresis

2D-DIGE:

Two-dimensional differential gel electrophoresis

LC–MS/MS:

Liquid chromatography–tandem mass spectrometry

GC–MS:

Gas chromatography–mass spectrometry

GC-TOF-MS:

Gas chromatography–time of flight mass spectrometry

EAB:

Epigenomics-assisted breeding

WGBS:

Whole-genome bisulphite sequencing

ChIp-Seq:

Chromatin immunoprecipitation sequencing

epiRILS:

Epigenetic inbred lines

QTLepi :

Epigenetic quantitative trait loci

siRNA:

Small interfering RNA

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Acknowledgements

The authors are thankful to the Director, Indian Institute of Vegetable Research, Varanasi for providing necessary funds and facilities for conducting the research. The authors are highly grateful to Department of Biotechnology (DBT), Govt. of India, for the financial support (Grant No. BT/PR10067/AGR/02/554/2007). The authors are also thankful to Department of Science and Technology (DST), Promotion of University Research and Scientific Excellence (PURSE), Fund for Improvement of S&T Infrastructure (FIST) program for financial support and central facility of the Department of Botany BHU, Varanasi.

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Communicated by M. Stobiecki.

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Rai, K.K., Rai, N. & Rai, S.P. Recent advancement in modern genomic tools for adaptation of Lablab purpureus L to biotic and abiotic stresses: present mechanisms and future adaptations. Acta Physiol Plant 40, 164 (2018). https://doi.org/10.1007/s11738-018-2740-6

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Keywords

  • Hyacinth bean
  • Abiotic/biotic stresses
  • Epigenomics
  • Trait mapping
  • Phenomics