Linkage QTL Mapping and Genome-Wide Association Study on Resistance in Chickpea to Pythium ultimum

The soilborne oomycete plant pathogen Pythium ultimum causes seed rot and pre-emergence damping-off of chickpea (Cicer arietinum L.). The pathogen has been controlled for several decades using the fungicide metalaxyl as seed treatment but has re-emerged as a severe problem with the detection of metalaxyl-resistant isolates of the pathogen from infested fields in the United States Pacific Northwest. The objective of this study was to identify genetic markers and candidate genes associated with resistance to P. ultimum in an interspecific recombinant inbred line population (CRIL-7) derived from a cross between C. reticulatum (PI 599072) x C. arietinum (FLIP 84-92C) and conduct genome-wide association studies (GWAS) for disease resistance using a chickpea diversity panel consisting of 184 accessions. CRIL-7 was examined using 1029 SNP markers spanning eight linkage groups. A major QTL, “qpsd4-1,” was detected on LG 4 that explained 41.8% of phenotypic variance, and a minor QTL, “qpsd8-1,” was detected on LG8 that explained 4.5% of phenotypic variance. Seven candidate genes were also detected using composite interval mapping including several genes previously associated with disease resistance in other crop species. A total of 302,902 single nucleotide polymorphic (SNP) markers were used to determine population structure and kinship of the diversity panel. Marker–trait associations were established by employing different combinations of principal components (PC) and kinships (K) in the FarmCPU model. Genome-wide association studies detected 11 significant SNPs and seven candidate genes associated with disease resistance. SNP Ca4_1765418, detected by GWAS on chromosome 4, was located within QTL qpsd4-1 that was revealed in the interspecific CRIL-7 population. The present study provides tools to enable MAS for resistance to P. ultimum and identified genomic domains and candidate genes involved in the resistance of chickpea to soilborne diseases

Prediction of mitochondrial proteins of malaria parasite using split amino acid composition and PSSM profile

The rate of human death due to malaria is increasing day-by-day. Thus the malaria causing parasite Plasmodium falciparum (PF) remains the cause of concern. With the wealth of data now available, it is imperative to understand protein localization in order to gain deeper insight into their functional roles. In this manuscript, an attempt has been made to develop prediction method for the localization of mitochondrial proteins. In this study, we describe a method for predicting mitochondrial proteins of malaria parasite using machine-learning technique. All models were trained and tested on 175 proteins (40 mitochondrial and 135 non-mitochondrial proteins) and evaluated using five-fold cross validation. We developed a Support Vector Machine (SVM) model for predicting mitochondrial proteins of P. falciparum, using amino acids and dipeptides composition and achieved maximum MCC 0.38 and 0.51, respectively. In this study, split amino acid composition (SAAC) is used where composition of N-termini, C-termini, and rest of protein is computed separately. The performance of SVM model improved significantly from MCC 0.38 to 0.73 when SAAC instead of simple amino acid composition was used as input. In addition, SVM model has been developed using composition of PSSM profile with MCC 0.75 and accuracy 91.38%. We achieved maximum MCC 0.81 with accuracy 92% using a hybrid model, which combines PSSM profile and SAAC. When evaluated on an independent dataset our method performs better than existing methods. A web server PFMpred has been developed for predicting mitochondrial proteins of malaria parasites (http://www.imtech.res.in/raghava/pfmpred/)

An Evolutionary Multi-Objective Crowding Algorithm (EMOCA): Benchmark Test Function Results

A new evolutionary multi-objective crowding algorithm (EMOCA) is evaluated using nine benchmark multiobjective optimization problems, and shown to produce non-dominated solutions with significant diversity, outperforming state-of-the-art multi-objective evolutionary algorithms viz., Non-dominated Sorting Genetic Algorithm – II (NSGA-II), Strength Pareto Evolutionary algorithm II (SPEA-II) and Pareto Archived Evolution Strategy (PAES) on most of the test problems. The key new approach in EMOCA is to use a diversity-emphasizing probabilistic approach in determining whether an offspring individual is considered in the replacement selection phase, along with the use of a non-domination ranking scheme. This approach appears to provide a useful compromise between the two concerns of dominance and diversity in the evolving population

Mapping out market drivers of improved variety seed use: The case of sorghum in Tanzania

It is understood that the grain market pulls the seed market. The problem of low quality prompted failure of traders and processors to purchase most of the farmers' grain to subsequently drive the use of improved variety seed. The aim of this study is to identify drivers that persuade farmers to use improved variety seeds for grain production. It also assesses factors affecting market participation among small-scale farmers. Descriptive analysis, Binary Logistic model, Probit model and gross margin analysis was conducted from random selected sample of 212 individual farmers, 63 grain off-takers, 3 extension officers and 7 seeds producers through structured interviews. In additional, 80 farmers were interviewed through 10 focus group discussion. The results showed that taste, preferences and price difference between grain and seed were significant and positive drivers that influenced the decision of farmers to use improved varieties at 47% and 0.007%, respectively. Factors such as group membership and farm size were significantly positive affecting farmer's market participation while age was negatively significant affecting farmer's market participation. Gross margin was computed to compare the profit margin between users and non-users of improved variety seeds, where users had high profit margin (530 979.89Tsh/Ha) compared to non-users (472 885.94Tsh/Ha), because non-users incurred high seed cost (54 504.84Tsh/15kg) compared to users of improved variety seeds (39 329.94Tsh/kg). Also, users obtained high grain revenue compared to non-user at 1 353 268.37Tsh and 848 249.11Tsh, respectively. Efforts should be made by value chain actors and other agricultural actors to support farmers based on market demand so they could benefit from high grain quality, quantity and promising grain market

HaptenDB: a comprehensive database of haptens, carrier proteins and anti-hapten antibodies

The key requirement for successful immunochemical assay is the availability of antibodies with high specificity and desired affinity. Small molecules, when used as haptens, are not immunogenic. However, on conjugating with carrier molecule they elicit antibody response. The production of anti-hapten antibodies of desired specificity largely depends on the hapten design (preserving greatly the chemical structure and spatial conformation of target compound), selection of the appropriate carrier protein and the conjugation method. This manuscript describes a curated database HaptenDB, where information is collected from published literature and web resources. The current version of the database has 2021 entries for 1087 haptens and 25 carrier proteins, where each entry provides comprehensive details about (1) nature of the hapten, (2) 2D and 3D structures of haptens, (3) carrier proteins, (4) coupling method, (5) method of anti-hapten antibody production, (6) assay method (used for characterization) and (7) specificities of antibodies. The current version of HaptenDB covers a wide array of haptens including pesticides, herbicides, insecticides, drugs, vitamins, steroids, hormones, toxins, dyes, explosives, etc. It provides internal and external links to various databases/resources to obtain further information about the nature of haptens, carriers and respective antibodies. For structure similarity comparison of haptens, the database also integrates tools like JME Editor and JMOL for sketching, displaying and manipulating hapten 2D/3D structures online. So the database would be of great help in identifying functional group(s) in smaller molecules using antibodies as well as for the development of immunodiagnostics/therapeutics by providing data and procedures available so far for the generation of specific or cross-reactive antibodies. Availability: HaptenDB is available on http://www.imtech.res.in/raghava/haptendb/ and http://bioinformatics.uams.edu/raghava/haptendb/ (Mirror site)

CicArMiSatDB: the chickpea microsatellite database

Background Chickpea (Cicer arietinum) is a widely grown legume crop in tropical, sub-tropical and temperate regions. Molecular breeding approaches seem to be essential for enhancing crop productivity in chickpea. Until recently, limited numbers of molecular markers were available in the case of chickpea for use in molecular breeding. However, the recent advances in genomics facilitated the development of large scale markers especially SSRs (simple sequence repeats), the markers of choice in any breeding program. Availability of genome sequence very recently opens new avenues for accelerating molecular breeding approaches for chickpea improvement. Description In order to assist genetic studies and breeding applications, we have developed a user friendly relational database named the Chickpea Microsatellite Database (CicArMiSatDB http://cicarmisatdb.icrisat.org). This database provides detailed information on SSRs along with their features in the genome. SSRs have been classified and made accessible through an easy-to-use web interface. Conclusions This database is expected to help chickpea community in particular and legume community in general, to select SSRs of particular type or from a specific region in the genome to advance both basic genomics research as well as applied aspects of crop improvement

Legume seed production for sustainable seed supply and crop productivity: case of groundnut in Tanzania and Uganda

Improvingagriculturalproductivityandproductionisaprerequisite to sustain rural livelihoods in developing countries of sub-Saharan Africa SSA).Thisrequiresincreaseduseofqualityseedofimproved and well-adapted crop varieties. Legumes are particularly critical in ensuring food and nutritional securities of the majority of farming households. However, their productivity has been constrained because of limited availability of quality seed, jeopardizing henceforth food security and rural livelihoods. The lack of interest in productionoflegumeseedsbypotentialseedproducers,especially the private sector, is attributable to limited information on the cost and profitability of producing these seeds. Using primary data collectedfromTanzaniaandUganda,weanalyzedthecoststructureof improved groundnut (Arachis hypogaea L.) seed production to assess viability. We adopted cost-benefit analysis framework to evaluate different seed production models. Results showed that groundnutseedpricevariedbetween1and2US$kg−1 forcertified andqualitydeclaredseedandbetween2and3.5US$kg−1 forearly generationseed.Overall,upto50%increaseintotalseedproduction costsresultedinreduceddropinthegrossmarginearned.However, when production costs increased by 75–100%, the gross margin droppedbyabout18%and50%inTanzaniaandinUganda,respectively. These findings indicated that groundnut seed could be providedtofarmersinremotecommunitiesatanaffordablepricewhile still keeping seed producers profitably in business. Availing these seeds to smallholder producers is a major step in achieving food securityandnutritionalhealthindevelopingcountries inSSA

Energy-efficient Decision Fusion for Distributed Detection in Wireless Sensor Networks

This paper proposes an energy-efficient counting rule for distributed detection by ordering sensor transmissions in wireless sensor networks. In the counting rule-based detection in an $N-$sensor network, the local sensors transmit binary decisions to the fusion center, where the number of all $N$ local-sensor detections are counted and compared to a threshold. In the ordering scheme, sensors transmit their unquantized statistics to the fusion center in a sequential manner; highly informative sensors enjoy higher priority for transmission. When sufficient evidence is collected at the fusion center for decision making, the transmissions from the sensors are stopped. The ordering scheme achieves the same error probability as the optimum unconstrained energy approach (which requires observations from all the $N$ sensors) with far fewer sensor transmissions. The scheme proposed in this paper improves the energy efficiency of the counting rule detector by ordering the sensor transmissions: each sensor transmits at a time inversely proportional to a function of its observation. The resulting scheme combines the advantages offered by the counting rule (efficient utilization of the network's communication bandwidth, since the local decisions are transmitted in binary form to the fusion center) and ordering sensor transmissions (bandwidth efficiency, since the fusion center need not wait for all the $N$ sensors to transmit their local decisions), thereby leading to significant energy savings. As a concrete example, the problem of target detection in large-scale wireless sensor networks is considered. Under certain conditions the ordering-based counting rule scheme achieves the same detection performance as that of the original counting rule detector with fewer than $N/2$ sensor transmissions; in some cases, the savings in transmission approaches $(N-1)$.Comment: 7 pages, 3 figures. Proceedings of FUSION 2018, Cambridge, U

Left ventricle hydatid cyst of heart removed under cardiopulmonary bypass: anesthesia management

Hydatid cyst uncommon in heart, echinococcosis is endemine in our country. Hydatid cyst in a heart may causes disturbances in conducting system, Pericarditis congestive cardiac failure. The surgery and anesthetic management become very challenging in this case. We are describing the successful management of such a case of left ventricle hydatid cyst remove under cardio pulmonary bypass in a middle age female