Coherent estimates of genetic effects with missing information

Genetic effect estimates for loci detected in quantitative trait locus (QTL) mapping experiments depend upon two factors. First, they are parameterizations of the genotypic values determined by the model of genetic effects. Second, they are consequently also affected by the regression method used to estimate the genotypic values from the observed marker genotypes and phenotypes. There are two common causes for marker-genotype data to be incomplete in those experiments—missing marker-genotypes and within-interval mapping. Different regression methods tend to differ in how this missing information is represented and handled. In this communication we explain why the estimates of genetic effects of QTL obtained using standard regression methods are not coherent with the model of genetic effects and indeed show intrinsic inconsistencies when there is incomeplete genotype information. We then describe the interval mapping by imputations (IMI) regression method and prove that it overcomes those problems. A numerical example is used to illustrate the use of IMI and the consequences of using current methods of choice. IMI enables researchers to obtain estimates of genetic effects that are coherent with the model of genetic effects used, despite incomplete genotype information. Furthermore, because IMI allows orthogonal estimation of genetic effects, it shows potential performance advantages for being implemented in QTL mapping tools.

Alleviation of nickel toxicity in finger millet(Eleusine coracana L.)germinating seedlings by exogenous application of salicylic acid and nitric oxide

This study investigated the effect of salicylic acid(SA) and sodium nitroprusside(SNP; NO donor) on nickel(Ni) toxicity in germinating finger millet seedlings. Fourteen-day-old finger millet plants were subjected to 0.5 mmol L^(-1) Ni overload and treated with 0.2 mmol L^(-1)salicylic acid and 0.2 mmol L^(-1)sodium nitroprusside to lessen the toxic effect of Ni.The Ni overload led to high accumulation in the roots of growing plants compared to shoots, causing oxidative stress. It further reduced root and shoot length, dry mass,total chlorophyll, and mineral content. Exogenous addition of either 0.2 mmol L^(-1)SA or0.2 mmol L^(-1)SNP reduced the toxic effect of Ni, and supplementation with both SA and SNP significantly reduced the toxic effect of Ni and increased root and shoot length,chlorophyll content, dry mass, and mineral concentration in Ni-treated plants. The results show that oxidative stress can be triggered in finger millet plants by Ni stress by induction of lipoxygenase activity, increase in levels of proline, O_2^(·-) radical, MDA, and H_2O_2, and reduction in the activity of antioxidant enzymes such as CAT, SOD, and APX in shoots and roots. Exogenous application of SA or SNP, specifically the combination of SA + SNP,protects finger millet plants from oxidative stress observed under Ni treatment.

Drought-responsive genes expressed predominantly in root tissues are enriched with homotypic cis-regulatory clusters in promoters of major cereal crops

The root appears to be the most relevant organ for breeding drought stress tolerance.However, our knowledge about temporal and spatial regulation of drought-associated genes in the root remains fragmented, especially in crop plants. We performed a meta-analysis of expression divergence of essential drought-inducible genes and analyzed their association with cis-elements in model crops and major cereal crops. Our analysis of42 selected drought-inducible genes revealed that these are expressed primarily in roots,followed by shoot, leaf, and inflorescence tissues, especially in wheat. Quantitative real-time RT-PCR analysis confirmed higher expression of TaDREB2 and TaAQP7 in roots,correlated with extensive rooting and drought-stress tolerance in wheat. A promoter scan up to 2 kb upstream of the translation start site using phylogenetic footprinting revealed708 transcription factor binding sites, including drought response elements(DREs), auxin response elements(Aux REs), MYCREs/MYBREs, ABAREs, and ERD1 in 19 selected genes.Interestingly, these elements were organized into clusters of overlapping transcription factor binding sites known as homotypic clusters(HCTs), which modulate drought physiology in plants. Taken together, these results revealed the expression preeminence of major drought-inducible genes in the root, suggesting its crucial role in drought adaptation. The occurrence of HCTs in drought-inducible genes highlights the putative evolutionary modifications of crop plants in developing drought adaptation. We propose that these DNA motifs can be used as molecular markers for breeding drought-resilient cultivars, particularly in the cereal crops.

Single-cell trajectories of melanoma cell resistance to targeted treatment

Objective:Cellular heterogeneity is regarded as a major factor affecting treatment response and resistance in malignant melanoma.Recent developments in single-cell sequencing technology have provided deeper insights into these mechanisms.Methods:Here,we analyzed a BRAFV600 E-mutant melanoma cell line by single-cell RNA-seq under various conditions:cells sensitive to BRAF inhibition with BRAF inhibitor vemurafenib and cells resistant to BRAF inhibition with vemurafenib alone or vemurafenib in combination with the MEK1/2 inhibitors cobimetinib or trametinib.Dimensionality reduction by t-distributed stochastic neighbor embedding and self-organizing maps identified distinct trajectories of resistance development clearly separating the 4 treatment conditions in cell and gene state space.Results:Trajectories associated with resistance to single-agent treatment involved cell cycle,extracellular matrix,and de-differentiation programs.In contrast,shifts detected in double-resistant cells primarily affected translation and mitogen-activated protein kinase pathway reactivation,with a small subpopulation showing markers of pluripotency.These findings were validated in pseudotime analyses and RNA velocity measurements.Conclusions:The single-cell transcriptomic analyses reported here employed a spectrum of bioinformatics methods to identify mechanisms of melanoma resistance to single-and double-agent treatments.This study deepens our understanding of treatmentinduced cellular reprogramming and plasticity in melanoma cells and identifies targets of potential relevance to the management of treatment resistance.

Identification of regulatory sequence signatures in microRNA precursors implicated in neurological disorders

MicroRNAs have emerged as one of the major classes of non-coding RNAs. Recent reports have placed them in high abundance in the nervous system, having key roles in development. Neurological disorders such as Parkinson’s disease, Alzheimer’s disease as well as Huntington disease have also been studied and several microRNAs associated with diseases pathogenesis have been identified. Various such findings indicate differential expression levels of many of these microRNAs. Such changes in the expression levels not only indicate towards a control of the biogenesis of these microRNAs but also indicate towards critical yet unelucidated roles of regulatory proteins, which probably act in concert to control the production or maturation of these molecules. In this work, a collection of overrepresented regulatory motif signatures were identified in the DNA and RNA sequences of the precursor microRNAs. The identification of such regulatory sequence signatures promises to provide new insights into many facets of microRNA regulation and neurological disorders.

An Integrated Approach to Comprehend MYMIV-Susceptibility of Blackgram Cv. T9 Possessing Allele of CYR1, the Cognate R-Gene

Blackgram, an important legume crop, faces the constraint of Mungbean yellow mosaic India virus (MYMIV)-stress resulting in severe crop penalty. MYMIV-resistant plants exhibit incompatible response via a cognate CYR1 gene-mediated interaction with virus effector molecule. In this study, we searched for the susceptible allele of the “R” gene in Cv. T9. Southern hybridization study confirmed presence of an allele in Cv. T9. However, transcripts of the CYR1 could not be detected either by RT-PCR or by Northern hybridization in Cv. T9 and also in other susceptible blackgram line. The allele was isolated, sequenced and referred as cyr1. In silico study revealed that cyr1 also encodes a CC-NBS-LRR protein like CYR1. However the CC domain of cyr1 is truncated by 128 amino acid residues indicating functional impairment with respect to the signal transduction after pathogen invasion. Comparative 3D structural modeling, hydrogen bonding and Van der Waals interaction studies revealed differences between CYR1 and cyr1. Lys519 and Thr490 present in the largest pockets of the CYR1 are the key interacting hotspots between CYR1 and MYMIV coat protein (CP). The weak Van der Waals interactions and intermolecular hydrogen bonding between cyr1 and CP confers less stability to the molecular recognition complex, unlike CYR1. Thus, the present investigation revealed Cv. T9 shows compatible interaction with MYMIV due to the truncation in the cyr1 sequence and consequent structural difference in the N-terminal of CC-domain.

Targeting autophagy with small molecules for cancer therapy

Autophagy is a conserved lysosomal-dependent catabolic process that maintains the cellular homeostasis by recycling misfolded proteins and damaged organelles. It involves a series of ordered events (initiation, nucleation, elongation, lysosomal fusion and degradation) that are tightly regulated/controlled by diverse cell signals and stress. It is like a double-edged sword that can play either a protective or destructive role in cancer, by pro-survival or apoptotic cues. Recently, modulating autophagy by pharmacological agents has become an attractive strategy to treat cancer. Currently, a number of small molecules that inhibit autophagy initiation (e.g., ULK kinase inhibitors), nucleation (e.g., Vps34 inhibitors), elongation (e.g., ATG4 inhibitors) and lysosome fusion (e.g., chloroquine, hydroxyl chloroquine,etc.) are reported in pre-clinical and clinical study. Also a number of small molecules reported to induce autophagy by targeting mammalian target of rapamycin (e.g., rapamycin analogs) or adenosine 5'-monophosphate-activated protein kinase (e.g., sulforaphane). The study results suggest that many potential "druggable" targets exist in the autophagy pathway that could be harnessed for developing new cancer therapeutics. In this review, we discuss the reported autophagy modulators (inhibitors and inducers), their molecular mode of action and their applications in cancer therapy.

TrFAST: A Tool to Predict Signaling Pathway-specific Transcription Factor Binding Sites

Recent advances in the development of high-throughput tools have significantly revolutionized our understanding of molecular mech- anisms underlying normal and dysfunctional biological processes. Here we present a novel computational tool, transcription factor search and analysis tool （TrFAST）, which was developed for the in silico analysis of transcription factor binding sites （TFBSs） of sig- naling pathway-specific TFs. TrFAST facilitates searching as well as comparative analysis of regulatory motifs through an exact pattern matching algorithm followed by the graphical representation of matched binding sites in multiple sequences up to 50 kb in length. TrFAST is proficient in reducing the number of comparisons by the exact pattern matching strategy. In contrast to the pre-existing tools that find TFBS in a single sequence, TrFAST seeks out the desired pattern in multiple sequences simultaneously. It counts the GC con- tent within the given multiple sequence data set and assembles the combinational details of consensus sequence（s） located at these regions, thereby generating a visual display based on the abundance of unique pattern. Comparative regulatory region analysis of multi- ple orthologous sequences simultaneously enhances the features of TrFAST and provides a significant insight into study of conservation of non-coding cis-regulatory elements. TrFAST is freely available at http：//www.fi-pk.com/trfast.html.

Integrated transcriptome interactome study of oncogenes and tumor suppressor genes in breast cancer

Breast cancer is the leading cause for mortality among women worldwide.Dysregulation of oncogenes and tumor suppressor genes is the major reason for the cause of cancer.Understanding these genes will provide clues and insights about their regulatory mechanism and their interplay in cancer.In the present study,an attempt is made to compare the functional characteristics and interactions of oncogenes and tumor suppressor genes to understand their biological role.431 breast cancer samples from seven publicly available microarray datasets were collected and analysed using GEO2R tool.The identified 416 differentially expressed genes were classified into five gene sets as oncogenes(OG),tumor suppressor genes(TSG),druggable genes,essential genes and other genes.The gene sets were subjected to various analysis such as enrichment analysis(viz.,GO,Pathways,Diseases and Drugs),network analysis,calculation of mutation frequencies and Guanine-Cytosine(GC)content.From the results,it was observed that the OG were having high GC content as well as high interactions than TSG.Moreover,the OG are found to have frequent mutations than TSG.The enrichment analysis results suggest that the oncogenes are involved in positive regulation of cellular protein metabolic process,macromolecule biosynthetic process and majorly in cell cycle and focal adhesion pathway in cancer.It was also found that these oncogenes are involved in other diseases such as skin diseases and viral infections.Collagenase,paclitaxel and docetaxel are some of the drugs found to be enriched for oncogenes.