ABSTRACT
The challenge of decoding information about complex diseases hidden in huge number of single nucleotide polymorphism (SNP) genotypes is undertaken based on five dbGaP studies. Current genome-wide association studies have successfully identified many high-risk SNPs associated with diseases, but precise diagnostic models for complex diseases by these or more other SNP genotypes are still unavailable in the literature. We report that lung cancer, breast cancer and prostate cancer as the first three top cancers worldwide can be predicted precisely via 240-370 SNPs with accuracy up to 99% according to leave-one-out and 10-fold cross-validation. Our findings (1) confirm an early guess of Dr. Mitchell H. Gail that about 300 SNPs are needed to improve risk forecasts for breast cancer, (2) reveal an incredible fact that SNP genotypes may contain almost all information that one wants to know, and (3) show a hopeful possibility that complex diseases can be precisely diagnosed by means of SNP genotypes without using phenotypical features. In short words, information hidden in SNP genotypes can be extracted in efficient ways to make precise diagnoses for complex diseases.
Subject(s)
Breast Neoplasms/diagnosis , Lung Neoplasms/diagnosis , Prostatic Neoplasms/diagnosis , Algorithms , Breast Neoplasms/genetics , Computational Biology , Computer Simulation , Databases, Genetic , Female , Genome-Wide Association Study/methods , Genotype , Humans , Lung Neoplasms/genetics , Male , Phenotype , Polymorphism, Single Nucleotide , Prostatic Neoplasms/geneticsABSTRACT
Considerable progresses have taken place both in the methodology available to study changes in intracellular cytosolic calcium and in our understanding of calcium signaling cascades. It is generally accepted that the global calcium signal system functions importantly in coping with plant abiotic stresses, especially drought stress, which has been proved further by the recent transgenic and molecular breeding reports under soil water deficits. In plant cells, calcium plays roles as a universal transducer coupling a wide range of extracellular stimuli with intracellular responses. Different extracellular stimuli trigger specific calcium signatures: dynamics, amplitude and duration of calcium transients specify the nature, implication and intensity of stimuli. Calcium-binding proteins (sensors) play a critical role in decoding calcium signatures and transducing signals by activating specific targets and corresponding metabolic pathways. Calmodulin (CAM) is a calcium sensor known to regulate the activity of many mammalian proteins, whose targets in plants are now being identified. Higher plants possess a rapidly growing list of CAM targets with a variety of cellular functions. Nevertheless, many targets appear to be unique to higher plant cells and remain characterized, calling for a concerted effort from plant and animal scientists to elucidate their functions. To date, three major classes of plant calcium signals encoding elements in the calcium signal system, including calcium-permeable ion channels,Ca(2)+/ H(+) antiporters and Ca(2)+-ATPases, are responsible for drought stress signal transduction directly or indirectly. This review summarizes the current knowledge of calcium signals involved in plant abiotic stresses and presents suggestions for future focus areas of study.