18 research outputs found
Inheritance of Resistance to Sorghum Shoot Fly, Atherigona soccata in Sorghum, Sorghum bicolor (L.) Moench
Inheritance of Resistance to Sorghum Shoot Fly, Atherigona soccata in Sorghum, Sorghum bicolor (L.) Moench
Sorghum production is affected by a wide array of biotic constraints, of which sorghum shoot fly, Atherigona soccata is the most important pest, which severely damages the sorghum crop during the seedling stage. Host plant resistance is one of the major components to control sorghum shoot fly, A. soccata. To understand the nature of gene action for inheritance of shoot fly resistance, we evaluated 10 parents, 45 F1's and their reciprocals in replicated trials during the rainy and postrainy seasons. The genotypes ICSV 700, Phule Anuradha, ICSV 25019, PS 35805, IS 2123, IS 2146, and IS 18551 exhibited resistance to shoot fly damage across seasons. Crosses between susceptible parents were preferred for egg laying by the shoot fly females, resulting in a susceptible reaction. ICSV 700, ICSV 25019, PS 35805, IS 2123, IS 2146, and IS 18551 exhibited significant and negative general combining ability (gca) effects for oviposition, deadheart incidence, and overall resistance score. The plant morphological traits associated with expression of resistance/susceptibility to shoot fly damage such as leaf glossiness, plant vigor, and leafsheath pigmentation also showed significant gca effects by these genotypes, suggesting the potential for use as a selection criterion to breed for resistance to shoot fly, A. soccata. ICSV 700, Phule Anuradha, IS 2146 and IS 18551 with significant positive gca effects for trichome density can also be utilized in improving sorghums for shoot fly resistance. The parents involved in hybrids with negative specific combining ability (sca) effects for shoot fly resistance traits can be used in developing sorghum hybrids with adaptation to postrainy season. The significant reciprocal effects of combining abilities for oviposition, leaf glossy score and trichome density suggested the influence of cytoplasmic factors in inheritance of shoot fly resistance. Higher values of variance due to specific combining ability (σ2s), dominance variance (σ2d), and lower predictability ratios than the variance due to general combining ability (σ2g) and additive variance (σ2a) for shoot fly resistance traits indicated the predominance of dominance type of gene action, whereas trichome density, leaf glossy score, and plant vigor score with high σ2g, additive variance, predictability ratio, and the ratio of general combining ability to the specific combining ability showed predominance of additive type of gene action indicating importance of heterosis breeding followed by simple selection in breeding shoot fly-resistant sorghums. Most of the traits exhibited high broadsense heritability, indicating high inheritance of shoot fly resistance traits
Machine Learning Heuristics on Gingivobuccal Cancer Gene Datasets Reveals Key Candidate Attributes for Prognosis
Delayed cancer detection is one of the common causes of poor prognosis in the case of many cancers, including cancers of the oral cavity. Despite the improvement and development of new and efficient gene therapy treatments, very little has been carried out to algorithmically assess the impedance of these carcinomas. In this work, from attributes or NCBI’s oral cancer datasets, viz. (i) name, (ii) gene(s), (iii) protein change, (iv) condition(s), clinical significance (last reviewed). We sought to train the number of instances emerging from them. Further, we attempt to annotate viable attributes in oral cancer gene datasets for the identification of gingivobuccal cancer (GBC). We further apply supervised and unsupervised machine learning methods to the gene datasets, revealing key candidate attributes for GBC prognosis. Our work highlights the importance of automated identification of key genes responsible for GBC that could perhaps be easily replicated in other forms of oral cancer detection.publishedVersionPeer reviewe
Role of proline in cell wall synthesis and plant development and its implications in plant ontogeny
Abscisic acid and its role in the modulation of plant growth, development, and yield stability
Abscisic acid (ABA) is known to confer stress tolerance; however, at elevated levels it impairs plant growth under prolonged stress. Paradoxically, at its basal level, ABA plays many vital roles in promoting plant growth and development, including modulation of tillering, flowering, and seed development, as well as seed maturation. In this review, we provide insight into novel discoveries of ABA fluxes, ABA signaling responses, and their impact on yield stability. We discuss ABA homeostasis implicated under pre- and postanthesis drought and its impact on productive tillers, grain number determination, and seed development to address yield stability in cereal crops while considering the new knowledge that emerged from the model plant systems
Unraveling regulation of the small heat shock proteins by the heat shock factor HvHsfB2c in barley: its implications in drought stress response and seed development.
The rapid increase in heat shock proteins upon exposure to damaging stresses and during plant development related to desiccation events reveal their dual importance in plant development and stress tolerance. Genome-wide sequence survey identified 20 non-redundant small heat shock proteins (sHsp) and 22 heat shock factor (Hsf) genes in barley. While all three major classes (A, B, C) of Hsfs are localized in nucleus, the 20 sHsp gene family members are localized in different cell organelles like cytoplasm, mitochondria, plastid and peroxisomes. Hsf and sHsp members are differentially regulated during drought and at different seed developmental stages suggesting the importance of chaperone role under drought as well as seed development. In silico cis-regulatory motif analysis of Hsf promoters showed an enrichment with abscisic acid responsive cis-elements (ABRE), implying regulatory role of ABA in mediating transcriptional response of HvsHsf genes. Gene regulatory network analysis identified HvHsfB2c as potential central regulator of the seed-specific expression of several HvsHsps including 17.5CI sHsp. These results indicate that HvHsfB2c is co-expressed in the central hub of small Hsps and therefore it may be regulating the expression of several HvsHsp subclasses HvHsp16.88-CI, HvHsp17.5-CI and HvHsp17.7-CI. The in vivo relevance of binding specificity of HvHsfB2C transcription factor to HSE-element present in the promoter of HvSHP17.5-CI under heat stress exposure is confirmed by gel shift and LUC-reporter assays. Further, we isolated 477 bp cDNA from barley encoding a 17.5 sHsp polypeptide, which was predominantly upregulated under drought stress treatments and also preferentially expressed in developing seeds. Recombinant HvsHsp17.5-CI protein was expressed in E. coli and purified to homogeneity, which displayed in vitro chaperone activity. The predicted structural model of HvsHsp-17.5-CI protein suggests that the α-crystallin domain is evolutionarily highly conserved
Gene network analysis.
<p>Gene co-expression network of <i>HvHsfB2c/HvHsp17.5-CI</i>, is derived from Plant Network using Heuristic Cluster Chiseling Algorithm based on genome-wide plant ontology high throughput gene expression data. Meta-network containing genes of <i>HvHsfB2c</i> cluster are enriched for several sHsps (highlighted in yellow colour) and also enriched Hsp class in the MapMan functional categories are represented (see table). For further details refer <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089125#pone.0089125.s006" target="_blank">Table S1</a>.</p
Expression profiles of sHsp and Hsf family genes during various stages of plant ontogeny analyzed by the Affymetrix 22K barley gene chip.
<p>Horizontal rows represent expression patterns of individual gene. Trivial names of genes as well as the corresponding Affymetrix IDs are given. Vertical lines represent the developmental stages and investigated tissues. Signal intensities: red, high expression; yellow, moderate expression; blue, low expression. Represented cultivars are named as M, ‘Morex’; Mo, ‘Morocco’, Ma ‘Martin’, B, ‘Barke’; GP, ‘Golden Promise’. Quantile normalized expression values are given as log2.</p
Expression, purification and chaperone activity of recombinant <i>Hv</i>sHsp17.5-CI.
<p>A) Expression of recombinant <i>Hv</i>sHsp17.5-CI in <i>E. coli</i>. Lane M, molecular weight marker; lane 1, uninduced; lane 2, induced; lane 3, purified recombinant <i>Hv</i>sHsp17.5-CI protein. Figures on the left indicate molecular weight in kDa. B) Prevention of thermal inactivation of <i>Swa</i>I restriction enzyme by recombinant <i>Hv</i>sHsp17.5-CI. The <i>Swa</i>I restriction enzyme was preincubated at 25, 30, 35, 40, 45 or 50°C in the presence of either BSA or recombinant <i>Hv</i>sHsp17.5-CI for 60 min. Residual activity of <i>Swa</i>I was determined by incubation with 300 ng plasmid at 25°C for 60 min, followed by electrophoresis on a 1% agarose gel. Lane M, 1-Kb DNA ladder; lane 1, plasmid DNA control (without <i>Swa</i>I digestion); lane 2, plasmid DNA digested with the <i>Swa</i>I restriction enzyme; lanes 3, 5, 7, 9, 11, and 13, plasmid DNA digested with <i>Swa</i>I after preincubation at 25, 30, 35, 40, 45 and 50°C, respectively, in the presence of BSA; lanes 4, 6, 8, 10, 12, and 14, plasmid DNA digested with <i>Swa</i>I after preincubation at 25, 30, 35, 40, 45 and 50°C, respectively, in the presence of recombinant <i>Hv</i>sHsp17.5-CI. SC, supercoiled plasmid; OC, open circular plasmid; L, linear plasmid. The numbers on the left represent the DNA markers in kb.</p
Expression profiles of barley genes responsive to drought.
<p>Expression ratios (drought vs control) are calculated based 3 replications. Fold change values are colour-coded: dark yellow >6 fold up-regulated, black no change, violet >6 fold down-regulated. Horizontal rows represent gene expression patterns. Vertical lines represent different stress treatments. Gene expression data refers to cvs. Brenda (B), Morex (M), Morocco (Mo), Martin (Ma), Oregon Wolf Barley-Dominant (OWB-D), Oregon Wolf Barley-Recessive (OWB-R), Hs (<i>H. spontaneum</i> HS584).</p