Variable-Selection Emerges on Top in Empirical Comparison of Whole-Genome Complex-Trait Prediction Methods

Accurate prediction of complex traits based on whole-genome data is a computational problem of paramount importance, particularly to plant and animal breeders. However, the number of genetic markers is typically orders of magnitude larger than the number of samples (p >> n), amongst other challenges. We assessed the effectiveness of a diverse set of state-of-the-art methods on publicly accessible real data. The most surprising finding was that approaches with feature selection performed better than others on average, in contrast to the expectation in the community that variable selection is mostly ineffective, i.e. that it does not improve accuracy of prediction, in spite of p >> n. We observed superior performance despite a somewhat simplistic approach to variable selection, possibly suggesting an inherent robustness. This bodes well in general since the variable selection methods usually improve interpretability without loss of prediction power. Apart from identifying a set of benchmark data sets (including one simulated data), we also discuss the performance analysis for each data set in terms of the input characteristics.     

Development of a Quantitative Competitive Reverse Transcription Polymerase Chain Reaction (QC-RT–PCR) for Detection and Quantitation of Chikungunya Virus

Chikungunya is one of the most important emerging arboviral infections of public health significance. Due to lack of a licensed vaccine, rapid diagnosis plays an important role in early management of patients. In this study, a QC-RT–PCR assay was developed to quantify Chikungunya virus (CHIKV) RNA by targeting the conserved region of E1 gene. A competitor molecule containing an internal insertion was generated, which provided a stringent control of the quantification process. The introduction of 10-fold serially diluted competitor in each reaction was further used to determine sensitivity. The applicability of this assay for quantification of CHIKV RNA was evaluated with human clinical samples, and the results were compared with real-time quantitative RT–PCR. The sensitivity of this assay was estimated to be 100 RNA copies per reaction with a dynamic detection range of 10² to 10¹⁰ copies. Specificity was confirmed using closely related alpha and flaviviruses. The comparison of QC-RT–PCR result with real-time RT–PCR revealed 100% concordance for the detection of CHIKV in clinical samples. These findings demonstrated that the reported assay is convenient, sensitive and accurate method and has the potential usefulness for clinical diagnosis due to simultaneous detection and quantification of CHIKV in acute-phase serum samples.     

Distribution of sibling species of Anopheles culicifacies s.l. and Anopheles fluviatilis s.l. and their vectorial capacity in eight different malaria endemic districts of Orissa, India

The study was undertaken in eight endemic districts of Orissa, India, to find the members of the species complexes of Anopheles culicifacies and Anopheles fluviatilis and their distribution patterns. The study area included six forested districts (Keonjhar, Angul, Dhenkanal, Ganjam, Nayagarh and Khurda) and two non-forested coastal districts (Puri and Jagatsingpur) studied over a period of two years (June 2007-May 2009). An. culicifacies A, B, C and D and An. fluviatilis S and T sibling species were reported. The prevalence of An. culicifacies A ranged from 4.2-8.41%, B from 54.96-76.92%, C from 23.08-33.62% and D from 1.85-5.94% (D was reported for the first time in Orissa, except for occurrences in the Khurda and Nayagarh districts). The anthropophilic indices (AI) were 3.2-4.8%, 0.5-1.7%, 0.7-1.37% and 0.91-1.35% for A, B, C and D, respectively, whereas the sporozoite rates (SR) were 0.49-0.54%, 0%, 0.28-0.37% and 0.41-0.46% for A, B, C and D, respectively. An. fluviatilis showed a similarly varied distribution pattern in which S was predominant (84.3% overall); its AI and SR values ranged from 60.7-90.4% and 1.2-2.32%, respectively. The study observed that the co-existence of potential vector sibling species of An. culicifacies (A, C and D) and An. fluviatilis S (> 50%) was responsible for the high endemicity of malaria in forested districts such as Dhenkanal, Keonjhar, Angul, Ganjam, Nayagarh and Khurda (> 5% slide positivity rate). Thus, the epidemiological scenario for malaria is dependent on the distribution of the vector sibling species and their vectorial capacity.     

Tumor necrosis factor is critical to control tuberculosis infection

Tumor necrosis factor (TNF) is critical and non-redundant to control Mycobacterium tuberculosis infection and cannot be replaced by other proinflammatory cytokines. Overproduction of TNF may cause immunopathology, while TNF neutralization reactivates latent and chronic, controlled infection, which is relevant for the use of neutralizing TNF therapies in patients with rheumatoid arthritis.     

Gapped permutation pattern discovery for gene order comparisons.

The list of species whose complete DNA sequence have been read is growing steadily, and it is believed that comparative genomics is in its early days. Permutations patterns (groups of genes in some "close" proximity) on gene sequences of genomes across species is being studied under different models, to cope with this explosion of data. The challenge is to (intelligently and efficiently) analyze the genomes in the context of other genomes. In this paper, we present a generalized model that uses three notions, gapped permutation patterns (with gap g), genome clusters, via quorum, K>1, parameter, and, possible multiplicity in the patterns. The task is to automatically discover all permutation patterns (with possible multiplicity), that occur with gap g in at least K of the given m genomes. We present (log mN (I) + /Sigma/log/Sigma/N (O)) time algorithm where m is the number of sequences, each defined on Sigma, N (I) is the size of the input and N (O) is the size of the maximal gene clusters that appear in at least K of the m genomes.     

Identification of stress-induced genes from the drought-tolerant plant Prosopis juliflora (Swartz) DC. through analysis of expressed sequence tags.

Abiotic stresses such as cold, salinity, drought, wounding, and heavy metal contamination adversely affect crop productivity throughout the world. Prosopis juliflora is a phreatophyte that can tolerate severe adverse environmental conditions such as drought, salinity, and heavy metal contamination. As a first step towards the characterization of genes that contribute to combating abiotic stress, construction and analysis of a cDNA library of P. juliflora genes is reported here. Random expressed sequence tag (EST) sequencing of 1750 clones produced 1467 high-quality reads. These clones were classified into functional categories, and BLAST comparisons revealed that 114 clones were homologous to genes implicated in stress response(s) and included heat shock proteins, metallothioneins, lipid transfer proteins, and late embryogenesis abundant proteins. Of the ESTs analyzed, 26% showed homology to previously uncharacterized genes in the databases. Fifty-two clones from this category were selected for reverse Northern analysis: 21 were shown to be upregulated and 16 downregulated. The results obtained by reverse Northern analysis were confirmed by Northern analysis. Clustering of the 1467 ESTs produced a total of 295 contigs encompassing 790 ESTs, resulting in a 54.2% redundancy. Two of the abundant genes coding for a nonspecific lipid transfer protein and late embryogenesis abundant protein were sequenced completely. Northern analysis (after polyethylene glycol stress) of the 2 genes was carried out. The implications of the analyzed genes in abiotic stress tolerance are also discussed.     

Induction of growth inhibition and differentiation of human leukemia HL-60 cells by a Tunisian gerboui olive leaf extract

Cancer protection associated with the consumption of olive products is well established, but not for leukemia. The protective effects of olive (Olea europaea L.) leaves were investigated by incubating human promyelocytic leukemia HL-60 cells with olive leaf extracts (OLEs) from seven principal Tunisian olive varieties, namely, Chemchali, Chemlali, Chétoui, Gerboui, Sayali, Zalmati and Zarrazi. The results showed significant growth inhibition of HL-60 cells incubated for 48 h with a 100-fold dilution of each OLE which had been obtained by incubating 10 g of dried leaves in 100 ml of 70% ethanol for one week with subsequent ultrafiltration. DNA fragmentation was observed in the cells incubated for 19 h with a 100-fold dilution of the Chemchali, Chemlali and Zalmati extracts. The results of a nitroblue tetrazolium (NBT) assay revealed NBT reduction, a differentiation marker, by the OLE-treated cells after an overnight incubation. The Gerboui extract showed the highest NBT reduction ability at more than 90%. An HPLC analysis revealed the presence of apigenin 7-glucoside in the extract, which was found in subsequent experiments to be responsible for the Gerboui extract-mediated cell differentiation.     

In situ observation of a cell adhesion and metabolism using surface infrared spectroscopy

In this study, we report on an in situ monitoring system of living cultured cells using infrared absorption spectroscopy in the geometry of multiple internal reflections (MIR-IRAS). In order to observe living cultured cells, the temperature in the sample chamber of a FT-IR spectrometer was maintained at 37 °C and a humidified gas mixture containing 5% CO₂ was introduced into the sample chamber. Human breast cell line MCF-7 cultured on Si MIR prisms were placed in the sample chamber and infrared spectra of MCF-7 cells were collected for 5 h. It was found that the adhesion and metabolism of MCF-7 cells could be monitored by the absorption intensity of amide-II protein band (1,545 cm⁻¹) and also by the absorption intensities of CH _x bands (2,700–3,100 cm⁻¹). These results suggest that our system is useful for a nondestructive and non-label monitoring of cell viability. Our method based on infrared absorption spectroscopy has a potential for bioscreening application.     

The DNA Replication,Repair, and Recombination Pathway Genes Modulating Yield and Stress Tolerance Traits in Chickpea

DNA replication, repair, and recombination (DRRR) are the fundamental processes required for faithful transmission of genetic information within and between generations. The DRRR genes protect the cells from potential mutations and damage during the developmental phases and stress conditions. Thus, these genes indirectly regulate diverse important agronomic traits in a crop plant. A genome-wide survey of six DRRR pathway genes, namely, DNA replication, Base Excision Repair, Nucleotide Excision Repair, Homologous Recombination, Mismatch Excision Repair, and Non-Homologous End-Joining, identified 157 DRRR genes in chickpea. Phylogenetic analysis of these genes within the legume clades and model plant Arabidopsis identified 42 conserved DRRR genes exhibiting clade-specific evolutionary patterns. Integrating the gene-based association mapping with differential expression profiling identified the natural alleles of the potential DRRR genes, primarily regulating flowering and maturation time and involved in drought tolerance of chickpea. Identifying and understanding DRRR genes’ roles in regulating yield and stress tolerance traits in a vital grain legume like chickpea is requisite for its future crop improvement endeavors. Manipulation of promising functionally relevant DRRR genes will pave the way for simultaneous improvement in multiple beneficial agronomic traits in chickpea.