Yifang Hu

Bio: Yifang Hu is an academic researcher from Walter and Eliza Hall Institute of Medical Research. The author has contributed to research in topics: Haematopoiesis & Progenitor cell. The author has an hindex of 23, co-authored 34 publications receiving 16561 citations. Previous affiliations of Yifang Hu include University of Melbourne.

Author Correction: Increased autophagy in EphrinB2-deficient osteocytes is associated with elevated secondary mineralization and brittle bone.

Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Identifying low-grade cellular rejection after heart transplantation in children by using gene expression profiling.

Abstract: Endomyocardial biopsy (EMB) remains the gold standard for detecting rejection after heart transplantation but is costly and invasive. This study aims to distinguish no rejection (0R) from low-grade...

Increased autophagy in ephrinB2 deficient osteocytes is associated with hypermineralized, brittle bones

Abstract: Mineralized bone forms when collagen-containing osteoid accrues hydroxyapatite crystals. This process has two phases: a rapid initiation (primary mineralization), followed by slower accrual of mineral (secondary mineralization) that continues until that portion of bone is renewed by remodelling. Within the bone matrix is an interconnected network of cells termed osteocytes. These cells are derived from bone-forming osteoblasts. This cellular transition requires expression of ephrinB2, and we were intrigued about why ephrinB2 continues to be expressed at high levels in mature osteocytes. To determine its function in osteocytes, we developed an osteocyte-specific ephrinB2 null mouse and found they exhibited a brittle bone phenotype. This was not caused by a change in bone mass, but by an intrinsic defect in the strength of the bone material. Although the initiation of osteoid mineralization occurred at a normal rate, the process of secondary mineralization was accelerated in these mice. The maturing mineralized bone matrix incorporated mineral and carbonate more rapidly than controls, indicating that osteocytic ephrinB2 suppresses mineral accumulation in bone. No known regulators of mineralization were modified in the bone of these mice. However, RNA sequencing showed differential expression of a group of autophagy-associated genes, and increased autophagic flux was confirmed in ephrinB2 knockdown osteocytes. This indicates that the process of secondary mineralization in bone makes use of autophagic machinery in a manner that is limited by ephrinB2 in osteocytes, and that this process may be disrupted in conditions of bone fragility.

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

Integrating single-cell transcriptomic data across different conditions, technologies, and species.

Abstract: Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.

Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown

Abstract: High-throughput sequencing of mRNA (RNA-seq) has become the standard method for measuring and comparing the levels of gene expression in a wide variety of species and conditions. RNA-seq experiments generate very large, complex data sets that demand fast, accurate and flexible software to reduce the raw read data to comprehensible results. HISAT (hierarchical indexing for spliced alignment of transcripts), StringTie and Ballgown are free, open-source software tools for comprehensive analysis of RNA-seq experiments. Together, they allow scientists to align reads to a genome, assemble transcripts including novel splice variants, compute the abundance of these transcripts in each sample and compare experiments to identify differentially expressed genes and transcripts. This protocol describes all the steps necessary to process a large set of raw sequencing reads and create lists of gene transcripts, expression levels, and differentially expressed genes and transcripts. The protocol's execution time depends on the computing resources, but it typically takes under 45 min of computer time. HISAT, StringTie and Ballgown are available from http://ccb.jhu.edu/software.shtml.

Dimensionality reduction for visualizing single-cell data using UMAP.

Abstract: Advances in single-cell technologies have enabled high-resolution dissection of tissue composition. Several tools for dimensionality reduction are available to analyze the large number of parameters generated in single-cell studies. Recently, a nonlinear dimensionality-reduction technique, uniform manifold approximation and projection (UMAP), was developed for the analysis of any type of high-dimensional data. Here we apply it to biological data, using three well-characterized mass cytometry and single-cell RNA sequencing datasets. Comparing the performance of UMAP with five other tools, we find that UMAP provides the fastest run times, highest reproducibility and the most meaningful organization of cell clusters. The work highlights the use of UMAP for improved visualization and interpretation of single-cell data.