Plants are frequently exposed to limitations in oxygen availability during their lifetime. During evolution, they have developed a number of physiological and morphological adaptations to tolerate oxygen and other stress conditions. These include regulation of growth by gene expression and ATP generation. The regulation of nuclear genes after hypoxia and anoxia is well studied; however, the regulation of mitochondrial genes in response to oxygen stress has not been characterized to date. Therefore, we have established an Arabidopsis mitochondrial genome-specific microarray that accommodates probes for all mitochondrial DNA-encoded genes and conserved open reading frames. Our analysis showed an up-regulation of mitochondrial transcripts in Arabidopsis roots after 48 h of hypoxia. Since no significant difference was detected in the expression of mitochondrial RNA polymerases or the mitochondrial DNA content per cell, we propose a transcriptional mode of induction of mitochondrial gene expression under hypoxia.
Fetal alcohol syndrome (FAS) is a condition resulting from excessive drinking by pregnant women. Symptoms of FAS include abnormal facial features, stunted growth, intellectual deficits and attentional dysfunction. Many studies have investigated FAS, but its underlying mechanisms remain unknown. This study evaluated the relationship between alcohol exposure during the synaptogenesis period in postnatal mice and subsequent cognitive function in adult mice. We delivered two injections, separated by 2 h, of ethanol (3 g/kg, ethanol/saline, 20% v/v) to ICR mice on postnatal day 7. After 10 weeks, we conducted a behavioral test, sacrificed the animals, harvested brain tissue and analyzed hippocampal gene expression using a microarray. In ethanol-treated mice, there was a reduction in brain size and decreased neuronal cell number in the cortex, and also cognitive impairment. cDNA microarray results indicated that 1,548 genes showed a > 2-fold decrease in expression relative to control, whereas 974 genes showed a > 2-fold increase in expression relative to control. Many of these genes were related to signal transduction, synaptogenesis and cell membrane formation, which are highlighted in our findings.
Facioscapulohumeral muscular dystrophy (FSHD) is a neuromuscular disorder that shows a preference for the facial, shoulder and upper arm muscles. FSHD affects about one in 20-400,000 people, and no effective therapeutic strategies are known to halt disease progression or reverse muscle weakness or atrophy. Many genes may be incorrectly regulated in affected muscle tissue, but the mechanisms responsible for the progressive muscle weakness remain largely unknown. Although machine learning (ML) has made significant inroads in biomedical disciplines such as cancer research, no reports have yet addressed FSHD analysis using ML techniques. This study explores a specific FSHD data set from a ML perspective. We report results showing a very promising small group of genes that clearly separates FSHD samples from healthy samples. In addition to numerical prediction figures, we show data visualizations and biological evidence illustrating the potential usefulness of these results.