Plant Proteomics in Crop Improvement

PROTEOMICS ◽  
2013 ◽  
Vol 13 (12-13) ◽  
pp. 1771-1771 ◽  
Author(s):  
Rainer Cramer ◽  
Laurence Bindschedler ◽  
Ganesh Agrawal
Keyword(s):  
Crop Improvement ◽  
Plant Proteomics

Molecular Biology and Crop Improvement

1986 ◽  
Author(s):  
R. B. Austin ◽  
R. B. Flavell ◽  
I. E. Henson ◽  
H. J. B. Lowe
Keyword(s):  
Molecular Biology ◽  
Crop Improvement

Evaluation of Gloriosa superba for Yield Attributing Characters and Quantification of Colchicine Originated from Different Agro Climatic Zones of Tamil Nadu and Andhra Pradesh

2017 ◽  
Vol 9 (3) ◽  
Author(s):  
Arun Kumar P. ◽  
Elangaimannan R.
Keyword(s):  
Seed Yield ◽  
Tamil Nadu ◽  
High Performance ◽  
Andhra Pradesh ◽  
Crop Improvement ◽  
Mean Value ◽  
Hplc Method ◽  
Gloriosa Superba ◽  
Climatic Zones ◽  
Colchicine Alkaloid

The study was conducted to evolve Gloriosa superba for yield characters and alkalodi content for selecting elite genotypes for comercial exploitatio n. The genotypes were sowm in Variyankaval village, Udayarpalayam taluk of Ariyalur district, Tamil Nadu. The highest mean value for fresh and dry seed yield was observed in Chittor local. The genotype Mulanur local has recorded the highest mean value for number of pods per plant and number of seeds per pod and Arupukotai local excelled the general mean for the traits seeds per pod, fresh and dry seed yield and also for tuber characters. An investigation was carried out to quantify the colchicine (alkaloid) present in tubers by High Performance Liquid Chromatography (HPLC) method. The genotypes collected from Arupukotai recorded the highest colchicine content (0.760 mg/g) followed by Chittoor (0.578 mg/g) and Mulanur (0.496 mg/g) and there by these three genotypes were utilized for further crop improvement.

Microsatellite Marker: Importance and Implications of Cross-genome Analysis for Finger Millet (Eleusine coracana (L.) Gaertn)

2020 ◽  
Vol 9 (3) ◽  
pp. 160-170
Author(s):  
Thumadath P.A. Krishna ◽  
Maharajan Theivanayagam ◽  
Gurusunathan V. Roch ◽  
Veeramuthu Duraipandiyan ◽  
Savarimuthu Ignacimuthu
Keyword(s):  
Molecular Marker ◽  
Microsatellite Markers ◽  
Ssr Markers ◽  
Genome Analysis ◽  
Related Species ◽  
Finger Millet ◽  
Crop Improvement ◽  
Human Beings ◽  
Closely Related Species ◽  
Genome Amplification

Finger millet is a superior staple food for human beings. Microsatellite or Simple Sequence Repeat (SSR) marker is a powerful tool for genetic mapping, diversity analysis and plant breeding. In finger millet, microsatellites show a higher level of polymorphism than other molecular marker systems. The identification and development of microsatellite markers are extremely expensive and time-consuming. Only less than 50% of SSR markers have been developed from microsatellite sequences for finger millet. Therefore, it is important to transfer SSR markers developed for related species/genus to finger millet. Cross-genome transferability is the easiest and cheapest method to develop SSR markers. Many comparative mapping studies using microsatellite markers clearly revealed the presence of synteny within the genomes of closely related species/ genus. Sufficient homology exists among several crop plant genomes in the sequences flanking the SSR loci. Thus, the SSR markers are beneficial to amplify the target regions in the finger millet genome. Many SSR markers were used for the analysis of cross-genome amplification in various plants such as Setaria italica, Pennisetum glaucum, Oryza sativa, Triticum aestivum, Zea mays and Hordeum vulgare. However, there is very little information available about cross-genome amplification of these markers in finger millet. The only limited report is available for the utilization of cross-genome amplified microsatellite markers in genetic analysis, gene mapping and other applications in finger millet. This review highlights the importance and implication of microsatellite markers such as genomic SSR (gSSR) and Expressed Sequence Tag (EST)-SSR in cross-genome analysis in finger millet. Nowadays, crop improvement has been one of the major priority areas of research in agriculture. The genome assisted breeding and genetic engineering plays a very crucial role in enhancing crop productivity. The rapid advance in molecular marker technology is helpful for crop improvement. Therefore, this review will be very helpful to the researchers for understanding the importance and implication of SSR markers in closely related species.

Abiotic Stress Tolerance in Soybean : Regulated by ncRNA

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
YASIN JESHIMA KHAN ◽  
HUSNARA Tyagi ◽  
Anil kumar Singh ◽  
Santosh kumar. Magadum
Keyword(s):  
Abiotic Stresses ◽  
Target Genes ◽  
Abiotic Stress Tolerance ◽  
Crop Improvement ◽  
Vital Role ◽  
Grain Legume ◽  
Biological Processes ◽  
Small Interfering Rnas ◽  
Cellular Environment ◽  
Non Coding Rnas

Plants respond through a cascade of reactions resulting in varied cellular environment leading to alterations in the patterns of protein expression resulting in phonotypic changes. Single cell genomics and global proteomics came out to be powerful tools and efficient techniques in studying stress tolerant plants. Non-coding RNAs are a distinct class of regulatory RNAs in plants and animals that control a variety of biological processes. Small ncRNAs play a vital role in post transcriptional gene regulation by either translational repression or by inducing mRNA cleavage. The major classes of small RNAs include microRNAs (miRNAs) and small interfering RNAs (siRNAs), which differ in their biogenesis. miRNAs control the expression of cognate target genes by binding to complementary sequences, resulting in cleavage or translational inhibition of the target RNAs. siRNAs too have a similar structure, function, and biogenesis like miRNAs but are derived from long double-stranded RNAs and can often direct DNA methylation at target sequences.In this review, we focus on the involvement of ncRNAs in comabting abiotic stresses of soybean. This review emphasis on previously known miRNAs as they play important role in several abiotic stresses like drought, salinity, chilling and heat stress by their diverse roles in mediating biological processes like gene expression, chromatin formation, defense of genome against invading viruses. This review attempts to elucidate the various kinds of non-coding RNAs explored, their discovery, biogenesis, functions, and response for different type of abiotic stresses and future aspects for crop improvement in the context of soybean, a representative grain legume.

scholarly journals Tackling G × E × M interactions to close on-farm yield-gaps: creating novel pathways for crop improvement by predicting contributions of genetics and management to crop productivity

2021 ◽  
Author(s):  
Mark Cooper ◽  
Kai P. Voss-Fels ◽  
Carlos D. Messina ◽  
Tom Tang ◽  
Graeme L. Hammer
Keyword(s):  
Climate Change ◽  
Crop Improvement ◽  
Target Population ◽  
Crop Productivity ◽  
Climate Change Scenarios ◽  
Global Food Security ◽  
Genotype By Environment ◽  
Improvement Strategies ◽  
Yield Gaps ◽  
On Farm

Abstract Key message Climate change and Genotype-by-Environment-by-Management interactions together challenge our strategies for crop improvement. Research to advance prediction methods for breeding and agronomy is opening new opportunities to tackle these challenges and overcome on-farm crop productivity yield-gaps through design of responsive crop improvement strategies. Abstract Genotype-by-Environment-by-Management (G × E × M) interactions underpin many aspects of crop productivity. An important question for crop improvement is “How can breeders and agronomists effectively explore the diverse opportunities within the high dimensionality of the complex G × E × M factorial to achieve sustainable improvements in crop productivity?” Whenever G × E × M interactions make important contributions to attainment of crop productivity, we should consider how to design crop improvement strategies that can explore the potential space of G × E × M possibilities, reveal the interesting Genotype–Management (G–M) technology opportunities for the Target Population of Environments (TPE), and enable the practical exploitation of the associated improved levels of crop productivity under on-farm conditions. Climate change adds additional layers of complexity and uncertainty to this challenge, by introducing directional changes in the environmental dimension of the G × E × M factorial. These directional changes have the potential to create further conditional changes in the contributions of the genetic and management dimensions to future crop productivity. Therefore, in the presence of G × E × M interactions and climate change, the challenge for both breeders and agronomists is to co-design new G–M technologies for a non-stationary TPE. Understanding these conditional changes in crop productivity through the relevant sciences for each dimension, Genotype, Environment, and Management, creates opportunities to predict novel G–M technology combinations suitable to achieve sustainable crop productivity and global food security targets for the likely climate change scenarios. Here we consider critical foundations required for any prediction framework that aims to move us from the current unprepared state of describing G × E × M outcomes to a future responsive state equipped to predict the crop productivity consequences of G–M technology combinations for the range of environmental conditions expected for a complex, non-stationary TPE under the influences of climate change.

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