Mechanisms of Stress Tolerance in Xerophyte \u3cem\u3eZygophyllum xanthoxylum\u3c/em\u3e and Their Application in Genetic Improvement of Legume Forages

Xerophytes, naturally growing in desert areas, have evolved multiple protective mechanisms to survive and grow well in harsh environments. Zygophyllum xanthoxylum, a succulent xerophyte with excellent adaptability to adverse arid environments and a fodder shrub with high palatability and nutrient value, colonizes arid areas in China and Mongolia. In this study, we found that Z. xanthoxylum grew better responding to salt condition with a typical feature for halophytes and became more tolerant to drought in the presence of moderate salinity (50 mM NaCl); 50 mM NaCl alleviated deleterious impacts of drought on the growth of Z. xanthoxylum by improving the relative water content, inducing a significant drop in leaf water potential and, concomitantly, increasing leaf turgor pressure and chlorophyll concentrations resulting in an enhancement of overall plant photosynthetic activity. Subsequently, co-expression of genes encoding the tonoplast Na+/H+ antiporter (ZxNHX) and H+-PPase (ZxVP1-1) which involve in leaf Na+ accumulation under stress condition by compartmentalizing Na+ into vacuoles in Z. xanthoxylum significantly improved both drought and salt tolerance in legume forages, Lotus corniculatus L. and Medicago sativa L

Histone modification profiling in breast cancer cell lines highlights commonalities and differences among subtypes

Abstract Background Epigenetic regulators are frequently mutated or aberrantly expressed in a variety of cancers, leading to altered transcription states that result in changes in cell identity, behavior, and response to therapy. Results To define alterations in epigenetic landscapes in breast cancers, we profiled the distributions of 8 key histone modifications by ChIP-Seq, as well as primary (GRO-seq) and steady state (RNA-Seq) transcriptomes, across 13 distinct cell lines that represent 5 molecular subtypes of breast cancer and immortalized human mammary epithelial cells. Discussion Using combinatorial patterns of distinct histone modification signals, we defined subtype-specific chromatin signatures to nominate potential biomarkers. This approach identified AFAP1-AS1 as a triple negative breast cancer-specific gene associated with cell proliferation and epithelial-mesenchymal-transition. In addition, our chromatin mapping data in basal TNBC cell lines are consistent with gene expression patterns in TCGA that indicate decreased activity of the androgen receptor pathway but increased activity of the vitamin D biosynthesis pathway. Conclusions Together, these datasets provide a comprehensive resource for histone modification profiles that define epigenetic landscapes and reveal key chromatin signatures in breast cancer cell line subtypes with potential to identify novel and actionable targets for treatment

Histone modification profiling in breast cancer cell lines highlights commonalities and differences among subtypes

Abstract Background Epigenetic regulators are frequently mutated or aberrantly expressed in a variety of cancers, leading to altered transcription states that result in changes in cell identity, behavior, and response to therapy. Results To define alterations in epigenetic landscapes in breast cancers, we profiled the distributions of 8 key histone modifications by ChIP-Seq, as well as primary (GRO-seq) and steady state (RNA-Seq) transcriptomes, across 13 distinct cell lines that represent 5 molecular subtypes of breast cancer and immortalized human mammary epithelial cells. Discussion Using combinatorial patterns of distinct histone modification signals, we defined subtype-specific chromatin signatures to nominate potential biomarkers. This approach identified AFAP1-AS1 as a triple negative breast cancer-specific gene associated with cell proliferation and epithelial-mesenchymal-transition. In addition, our chromatin mapping data in basal TNBC cell lines are consistent with gene expression patterns in TCGA that indicate decreased activity of the androgen receptor pathway but increased activity of the vitamin D biosynthesis pathway. Conclusions Together, these datasets provide a comprehensive resource for histone modification profiles that define epigenetic landscapes and reveal key chromatin signatures in breast cancer cell line subtypes with potential to identify novel and actionable targets for treatment.https://deepblue.lib.umich.edu/bitstream/2027.42/142394/1/12864_2018_Article_4533.pd

Cellular Heterogeneity-Adjusted cLonal Methylation (CHALM) improves prediction of gene expression.

Promoter DNA methylation is a well-established mechanism of transcription repression, though its global correlation with gene expression is weak. This weak correlation can be attributed to the failure of current methylation quantification methods to consider the heterogeneity among sequenced bulk cells. Here, we introduce Cell Heterogeneity-Adjusted cLonal Methylation (CHALM) as a methylation quantification method. CHALM improves understanding of the functional consequences of DNA methylation, including its correlations with gene expression and H3K4me3. When applied to different methylation datasets, the CHALM method enables detection of differentially methylated genes that exhibit distinct biological functions supporting underlying mechanisms

Cellular Heterogeneity-Adjusted cLonal Methylation (CHALM) improves prediction of gene expression.

Promoter DNA methylation is a well-established mechanism of transcription repression, though its global correlation with gene expression is weak. This weak correlation can be attributed to the failure of current methylation quantification methods to consider the heterogeneity among sequenced bulk cells. Here, we introduce Cell Heterogeneity-Adjusted cLonal Methylation (CHALM) as a methylation quantification method. CHALM improves understanding of the functional consequences of DNA methylation, including its correlations with gene expression and H3K4me3. When applied to different methylation datasets, the CHALM method enables detection of differentially methylated genes that exhibit distinct biological functions supporting underlying mechanisms