Meta-analysis of gene expression in mouse models of neurodegenerative disorders

There is intense interest in understanding the molecular mechanisms that contribute to neurodegenerative disorders (NDs), which involve complex interplays of genetic and environmental factors. To catch early events involved in disease initiation requires investigation on pre-symptomatic brain samples. It is difficult to capture early molecular events using post-mortem human brain samples since these samples represent the late phase of the disorder with progressive brain damage and neurodegeneration. Disease mouse models are developed to study disease progression and pathophysiology. Here, I focus on two of the most studied NDs: Alzheimer’s disease (AD) and Huntington’s disease (HD). Mouse models developed for the disease (AD or HD) often share similar phenotypes mimicking human disease symptoms, which suggest potential common underlying mechanisms of disease initiation and progression across mouse models of the same disease. Investigation of gene expression profiles of pre-symptomatic animals from different mouse models may shed light on the mechanisms occurred in the early disease phase. Gene expression profiling analyses have been performed on mouse models and some of the studies investigate the molecular changes in pre-symptomatic phase of AD and HD respectively. However, their findings have not reached a clear consensus. To identify shared molecular changes across mouse models, I conducted a systematic meta-analysis of gene expression in mouse models of AD and HD, consisted of 369 gene expression profiles from 23 independent studies. The goal of this project is to identify transcriptional alterations shared among different mouse models of each disease respectively, especially changes during early disease phase that may link to disease-causing mechanisms, and potential common cross-disease changes. For both of the disorders, the results showed subtle but biologically interpretable changes shared across mouse models in the early disease phase that may contribute to the early disease progression: dysregulation of genes involved in cholesterol biosynthesis and complement system in AD mouse models and genes encoding mitochondrial respiratory chain complexes in HD mouse models. Cross-disease similarities in the late phase suggested that different brain regions may share mechanisms in response to neuronal loss and toxic protein aggregates.Science, Faculty ofGraduat

The Annona montana genome reveals the development and flavor formation in mountain soursop fruit

Annona is a genus of family Annonaceae within the magnoliids and plays a crucial role in revealing the evolution of magnolias. Annona species provide important fruit resources. Here, we report a chromosome-level genome assembly of A. montana, an edible and ornamental fruit species. Integration with other genomes provides clear evidence that the magnoliids were sisters to eudicots, and the ASTRAL trees showed discordance in the phylogenetic position of magnoliids, which might be caused by incomplete lineage sorting (ILS). Whole genome duplication (WGD) analysis showed that the common ancestor of A. montana and Liriodendron chinense experienced a WGD event, and this WGD event occurred after the splitting of Magnoliales and Laurales. We identified the gene family expansions and contractions in Annonaceae. Based on the identification of MADS-box gene families, we inferred the pathway integrators of morphological regulation, the occurrence of florescence and the development of fruit in A. montana. In addition, we identified key sugar transporter genes and the key enzyme genes related to sugar accumulation in A. montana fruit. The gene function analysis indicated that starch and cell wall degradation might be the main reasons for the softening of A. montana fruit. Furthermore, aromatic alcohols were suggested be the main volatile aromatic compounds in A. montana fruit. Our results provide the genetic basis of fruit development, softening, aroma, and sugar accumulation in A. montana and the evolution and diversification of Annonaceae

One thousand plant transcriptomes and the phylogenomics of green plants

Abstract: Green plants (Viridiplantae) include around 450,000–500,000 species1, 2 of great diversity and have important roles in terrestrial and aquatic ecosystems. Here, as part of the One Thousand Plant Transcriptomes Initiative, we sequenced the vegetative transcriptomes of 1,124 species that span the diversity of plants in a broad sense (Archaeplastida), including green plants (Viridiplantae), glaucophytes (Glaucophyta) and red algae (Rhodophyta). Our analysis provides a robust phylogenomic framework for examining the evolution of green plants. Most inferred species relationships are well supported across multiple species tree and supermatrix analyses, but discordance among plastid and nuclear gene trees at a few important nodes highlights the complexity of plant genome evolution, including polyploidy, periods of rapid speciation, and extinction. Incomplete sorting of ancestral variation, polyploidization and massive expansions of gene families punctuate the evolutionary history of green plants. Notably, we find that large expansions of gene families preceded the origins of green plants, land plants and vascular plants, whereas whole-genome duplications are inferred to have occurred repeatedly throughout the evolution of flowering plants and ferns. The increasing availability of high-quality plant genome sequences and advances in functional genomics are enabling research on genome evolution across the green tree of life