Whole plant response of Pongamia pinnata to drought stress tolerance revealed by morpho-physiological,biochemical and transcriptome analysis

Molecular Biology Reports - Pongamia is considered an important biofuel species worldwide. Drought stress in the early growth stages of Pongamia influences negatively on the germination and...     

Predicting breast cancer using an expression values weighted clinical classifier

Background

Clinical data, such as patient history, laboratory analysis, ultrasound parameters-which are the basis of day-to-day clinical decision support-are often used to guide the clinical management of cancer in the presence of microarray data. Several data fusion techniques are available to integrate genomics or proteomics data, but only a few studies have created a single prediction model using both gene expression and clinical data. These studies often remain inconclusive regarding an obtained improvement in prediction performance. To improve clinical management, these data should be fully exploited. This requires efficient algorithms to integrate these data sets and design a final classifier.LS-SVM classifiers and generalized eigenvalue/singular value decompositions are successfully used in many bioinformatics applications for prediction tasks. While bringing up the benefits of these two techniques, we propose a machine learning approach, a weighted LS-SVM classifier to integrate two data sources: microarray and clinical parameters.

Results

We compared and evaluated the proposed methods on five breast cancer case studies. Compared to LS-SVM classifier on individual data sets, generalized eigenvalue decomposition (GEVD) and kernel GEVD, the proposed weighted LS-SVM classifier offers good prediction performance, in terms of test area under ROC Curve (AUC), on all breast cancer case studies.

Conclusions

Thus a clinical classifier weighted with microarray data set results in significantly improved diagnosis, prognosis and prediction responses to therapy. The proposed model has been shown as a promising mathematical framework in both data fusion and non-linear classification problems.     

Segregation for fertility and meiotic stability in novel <Emphasis Type="Italic">Brassica</Emphasis> allohexaploids

Key message

Allohexaploid Brassica populations reveal ongoing segregation for fertility, while genotype influences fertility and meiotic stability.

Abstract

Creation of a new Brassica allohexaploid species is of interest for the development of a crop type with increased heterosis and adaptability. At present, no naturally occurring, meiotically stable Brassica allohexaploid exists, with little data available on chromosome behaviour and meiotic control in allohexaploid germplasm. In this study, 100 plants from the cross B. carinata?×?B. rapa (A2 allohexaploid population) and 69 plants from the cross (B. napus?×?B. carinata)?×?B. juncea (H2 allohexaploid population) were assessed for fertility and meiotic behaviour. Estimated pollen viability, self-pollinated seed set, number of seeds on the main shoot, number of pods on the main shoot, seeds per ten pods and plant height were measured for both the A2 and H2 populations and for a set of reference control cultivars. The H2 population had high segregation for pollen viability and meiotic stability, while the A2 population was characterised by low pollen fertility and a high level of chromosome loss. Both populations were taller, but had lower average fertility trait values than the control cultivar samples. The study also characterises fertility and meiotic chromosome behaviour in genotypes and progeny sets in heterozygous allotetraploid Brassica derived lines, and indicates that genotypes of the parents and H1 hybrids are affecting chromosome pairing and fertility phenotypes in the H2 population. The identification and characterisation of factors influencing stability in novel allohexaploid Brassica populations will assist in the development of this as a new crop species for food and agricultural benefit.

     

A cloud-based enhanced differential evolution algorithm for parameter estimation problems in computational systems biology

Metaheuristics are gaining increasing recognition in many research areas, computational systems biology among them. Recent advances in metaheuristics can be helpful in locating the vicinity of the global solution in reasonable computation times, with Differential Evolution (DE) being one of the most popular methods. However, for most realistic applications, DE still requires excessive computation times. With the advent of Cloud Computing effortless access to large number of distributed resources has become more feasible, and new distributed frameworks, like Spark, have been developed to deal with large scale computations on commodity clusters and cloud resources. In this paper we propose a parallel implementation of an enhanced DE using Spark. The proposal drastically reduces the execution time, by means of including a selected local search and exploiting the available distributed resources. The performance of the proposal has been thoroughly assessed using challenging parameter estimation problems from the domain of computational systems biology. Two different platforms have been used for the evaluation, a local cluster and the Microsoft Azure public cloud. Additionally, it has been also compared with other parallel approaches, another cloud-based solution (a MapReduce implementation) and a traditional HPC solution (a MPI implementation)     

Alternaria incidence in some alloplasmic lines of Indian mustard (Brassica juncea (L.) Coss.)

Summary The cytoplasmic substitution lines of Brassica juncea (L.) Coss were evaluated for their field resistance to Alternaria blight (Alternaria brassicae). The euplasmic B. juncea cv. RLM 198 had a mesothetic reaction while alloplasmic B. juncea lines with cytoplasms of B. campestris, B. chinensis, and B. japonica were highly susceptible. B. nigra cytoplasm did not have any effect on the disease reaction of the B. juncea genome. However, the alloplasmic lines with the cytoplasm of B. napus and B. carinata revealed a comparatively higher degree of resistance. The study underlined the utility of cytoplasmic manipulations in modifying the phenotypic expression of nuclear genes.     

Functional evaluation of murine allogeneic T lymphoblasts separated by Vicia villosa lectin positivity

Mixed-lymphocyte culture-stimulated cells have been fractionated by their ability to bind the lectin Vicia villosa (Vv) and assessed for their cytolytic and suppressor activity in vitro. Vv positive and negative cells were separated either by cell affinity chromatography using Vv-Sepharose 6MB chromatography or by electronic cell sorting with FITC-Vv. Both populations expressed marked cytolytic and suppressor cell activity. Thus this lectin cannot be used to discriminate between these and other functional lymphoid cell population of blastoid cells binding the FITC-Vv appears following allogeneic stimulation; treatment with the immunosuppressive drug cyclosporin A, which affects cytotoxic cells preferentially, results in a considerable reduction of the Vv positive blastoid cells.     

Prediction of domain organisation and secondary structure of thyroid peroxidase, a human autoantigen involved in destructive thyroiditis

Organ specific autoimmune diseases are relatively common immunological disorders in man which include thyroid autoimmune disease, insulin-dependent diabetes mellitus and myasthenia gravis. The target autoantigens in some of these diseases have recently been characterised. In thyroid autoimmune disease this includes the key enzyme, thyroid peroxidase (TPO), which is involved in the generation of thyroid hormone. Structural knowledge about autoantigens such as thyroid peroxidase will allow a greater understanding of the interaction between autoantigens and the aberrant immune response, and facilitate the development of strategies for antigen-specific therapeutic manipulation. We report here a prediction of the secondary structure of thyroid peroxidase, together with the results of circular dichroic spectroscopy of a homologous purified enzyme. A combination of 3 secondary structure prediction programs has been used, following multiple sequence alignment, and TPO has been found to consist mainly of alpha-helical conformation, with little beta-sheet present. This structure prediction, together with knowledge of the exon-intron boundaries allows a model for the domain organisation of the TPO molecule to be proposed.     

Separation of membrane proteins in an undenatured form by isoelectric focusing

Conditions are described which allow good resolution of membrane proteins in an undenatured form by isoelectric focusing in thin polyacrylamide gels in Triton X-100. High voltages and deionization of the acrylamide are essential. Streaking is grossly reduced by sample application in Bio-Gel P-60, by deionization of the Triton, and dialysis of membrane samples against low ionic strength buffer at slightly alkaline pH. The latter step also greatly improves solubilization of the membrane components. Reproducible isoelectric focusing patterns of proteins from red cell, thyroid, and lymphocyte membrane are presented.     

Dynamic optimization of bioprocesses: efficient and robust numerical strategies

The dynamic optimization (open loop optimal control) of non-linear bioprocesses is considered in this contribution. These processes can be described by sets of non-linear differential and algebraic equations (DAEs), usually subject to constraints in the state and control variables. A review of the available solution techniques for this class of problems is presented, highlighting the numerical difficulties arising from the non-linear, constrained and often discontinuous nature of these systems. In order to surmount these difficulties, we present several alternative stochastic and hybrid techniques based on the control vector parameterization (CVP) approach. The CVP approach is a direct method which transforms the original problem into a non-linear programming (NLP) problem, which must be solved by a suitable (efficient and robust) solver. In particular, a hybrid technique uses a first global optimization phase followed by a fast second phase based on a local deterministic method, so it can handle the nonconvexity of many of these NLPs. The efficiency and robustness of these techniques is illustrated by solving several challenging case studies regarding the optimal control of fed-batch bioreactors and other bioprocesses. In order to fairly evaluate their advantages, a careful and critical comparison with several other direct approaches is provided. The results indicate that the two-phase hybrid approach presents the best compromise between robustness and efficiency.     

A mass mortality of fishes caused by receding water levels in the vegetated littoral zone of the West Kleinemonde Estuary,South Africa

On 15 November 2017 the mouth of the West Kleinemonde Estuary breached following heavy catchment rains and increased river flow. The water level in the estuary following mouth opening decreased by 1.65 m within 24 h, resulting in an almost complete draining of the littoral zone where large beds of the aquatic macrophyte Ruppia cirrhosa and mats of the associated filamentous algae were present. As the water depth within the plant beds decreased, the macrophytes, together with the algal filaments, created an increasingly dense mat, trapping fish that were resident, foraging or passing through the littoral zone. By 16 November 2017 large numbers of fishes belonging to at least 20 species were trapped in pools and depressions within the littoral, as well as within the R. cirrhosa beds and filamentous algal mats in the lower reaches of this system. Other affected taxa included crustaceans, especially isopods, and large numbers of small bivalves attached to macrophyte vegetation. Beneficiaries of the fish kill, in terms of unexpected food availability, included a variety of piscivorous bird species and the Cape clawless otter Aonyx capensis. This is the first documented account of a diverse species fish kill associated with estuary mouth breaching.