Differential Response of Peanut Genotypes to Water Stress

Differential expression of leaf proteins in four cultivars of peanut (Arachis hypogaea L.) under water stress

Drought is a major constraint to the productivity of many crops affecting various physiological and biochemical processes. Seventy percent of the peanuts are grown in semiarid tropics that are frequently prone to drought stress. So, we analyzed its effect in 4 cultivars of peanut, with different degrees of drought tolerance, under 10 and 20 days of water stress using two-dimensional gel electrophoresis and mass spectrometry. A total of 189 differentially expressed protein spots were identified in the leaf proteome of all the 4 cultivars using PD Quest Basic software; 74 in ICGV 91114, 41 in ICGS 76, 44 in J 11 and 30 in JL 24. Of these, 30 protein spots were subjected to in-gel trypsin digestion followed by MALDI-TOF that are functionally categorized into 5 groups: molecular chaperones, signal transducers, photosynthetic proteins, defense proteins and detoxification proteins. Of these, 12 proteins were sequenced. Late embryogenesis abundant protein, calcium ion binding protein, sucrose synthase isoform-1, 17.3 kDa heat shock protein and structural maintenance of chromosome proteins were overexpressed only in the 15 and 20 days stressed plants of ICGV 91114 cultivar while cytosolic ascorbate peroxidase was expressed with varying levels in the 10 and 20 days stressed plants of all the 4 cultivars. Signaling protein like 14-3-3 and defense proteins like alpha-methyl-mannoside-specific lectin and mannose/glucose-binding lectins were differentially expressed in the 4 cultivars. Photosynthetic protein like Rubisco was down-regulated in the stressed plants of all 4 cultivars while Photosystem-I reaction center subunit-II of chloroplast precursor protein was overexpressed in only 20 days stressed plants of ICGV 91114, ICGS 76 and J11 cultivars. These differentially expressed proteins could potentially be used as protein markers for screening the peanut germplasm and further crop improvement.

Annotation of Stress-Responsive Candidate Genes in Peanut ESTs

Peanut (Arachis hypogaea L.) is an internationally important crop for human consumption as a good source of protein and vegetable oil. Peanut is widely cultivated around the world in tropical, subtropical and warm temperate climate. Because of its huge genome size (2.8 Gb) and unsequenced genome, studies on genomics and genetic modification of peanut are less as compared to other model crops. As peanut can be cultivated in arid and semiarid regions, its growth is drastically affected by various stresses that reduce the yield. Therefore, study on stress-responsive genes and its regulation is very much important. Here we report about the identification and annotation of some stress-responsive candidate genes using peanut expressed sequence tags (ESTs). The selection of genes was based on the publically available expression data. Due to good expression data and lack of available literature in peanut, some of the stress-responsive genes were screened. Individual EST of the said group was further searched in peanut ESTs (1,78,490 whole EST sequences) using computational approach. Various tools like VecScreen, RepeatMasker, EST trimmer, DNA Baser and Wise2 were being used for stress-responsive gene identification and annotation. Research progress made toward contig assembly, determination of biological function of genes, and prediction of domain as well as 3D structure for related protein are included.

Identification of peanut seed prolamins with an antifungal role by 2D-GE and drought treatment

This work revealed peanut seed prolamins likely displaying a defensive role besides the known nitrogen storage. Drought stress and proteomic approaches were used in varieties of peanuts to explore the prolamin member in association with a test against Aspergillus flavus spore germination. The stress effect was showed by aerial biomass, leaf content of malondialdehyde, and seed contamination by A. flavus. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis profiles were not informative for the antifungal polypeptides. From two-dimensional gel electrophoresis, the suspected polypeptides were those with pI 5.45-5.75 and sizes of 22.0-30.5 kDa specifically in Spanish-type peanuts. Regarding to the drought effect in most of these peanuts, the spot peak volume analysis deduced three novel prolamin-related antifungal polypeptides at pI 5.75-5.8 with 30.5, 27.5-28.5, and 22.0-22.5 kDa, which was confirmed after isoelectric purification at pH 5.60. The data could not yet conclude their correlation with resistance to drought and to seed infection by A. flavus.

Annotation of stress responsive candidate genes in peanut ESTs

Peanut (Arachis hypogaea L.) is an internationally important crop for human consumption as a good source of protein and vegetable oil. Peanut is widely cultivated around the world in tropical, sub-tropical and warm temperate climate. Because of its huge genome size (2.8 Gb) and unsequenced genome, studies on genomics and genetic modification of peanut are less as compared to other model crops. As peanut can be cultivated in arid and semi-arid regions, and its growth is drastically affected by various stresses that reduces the yield. Therefore, study on stress responsive genes and its regulation are very much important. Here we report about the identification and annotation of some stress responsive candidate genes using peanut Expressed Sequences Tags (ESTs). The selection of genes was based on the publically available expression data. Due to good expression data and lack of available literature in peanut some of the stress responsive genes were screened. Individual EST of the said group were further searched in peanut ESTs (1, 78,490 whole EST sequences) using computational approach. Various tools like Vec-Screen, Repeat Masker, EST Trimmer, DNA Baser and WISE2 were being used for stress responsive gene identification and annotation. Research progress made towards contigs assembly, determination of biological function of genes, and prediction of domain as well as 3D structure for related protein are included.