Quantifying cell-type proportions and their corresponding gene expression profiles in tissue samples would enhance understanding of the contributions of individual cell types to the physiological states of the tissue. Current approaches that address tissue heterogeneity have drawbacks. Experimental techniques, such as fluorescence-activated cell sorting, and single cell RNA sequencing are expensive. Computational approaches that use expression data from heterogeneous samples are promising, but most of the current methods estimate either cell-type proportions or cell-type-specific expression profiles by requiring the other as input. Although such partial deconvolution methods have been successfully applied to tumor samples, the additional input required may be unavailable. We introduce a novel complete deconvolution method, CDSeq, that uses only RNA-Seq data from bulk tissue samples to simultaneously estimate both cell-type proportions and cell-type-specific expression profiles. Using several synthetic and real experimental datasets with known cell-type composition and cell-type-specific expression profiles, we compared CDSeq’s complete deconvolution performance with seven other established deconvolution methods. Complete deconvolution using CDSeq represents a substantial technical advance over partial deconvolution approaches and will be useful for studying cell mixtures in tissue samples. CDSeq is available at GitHub repository (MATLAB and Octave code): https://github.com/kkang7/CDSeq.

Ophiocordyceps sinensis (Berk.) is an entomopathogenic fungus endemic to the Qinghai-Tibet Plateau. It parasitizes and mummifies the underground ghost moth larvae, then produces a fruiting body. The fungus-insect complex, called Chinese cordyceps or "DongChongXiaCao", is not only a valuable traditional Chinese medicine, but also a major source of income for numerous Himalayan residents. Here, taking advantage of rapid advances in single-molecule sequencing, we assembled a highly contiguous genome assembly of O. sinensis. The assembly of 23 contigs was ∼ 110.8 Mb with a N50 length of 18.2 Mb. We used RNA-seq and homologous protein sequences to identify 8916 protein-coding genes in the IOZ07 assembly. Moreover, 63 secondary metabolite gene clusters were identified in the improved assembly. The improved assembly and genome features described in this study will further inform the evolutionary study and resource utilization of Chinese cordyceps.

BackgroundThis study aimed to validate the effectiveness of the Osteoporosis Self-assessment Tool for Asians (OSTA) in identifying postmenopausal women at increased risk of primary osteoporosis and painful new osteoporotic vertebral fractures in a large selected Han Chinese population in Beijing.MethodsWe assessed the performance of the OSTA in 1201 women. Subjects with an OSTA index > -1 were classified as the low risk group, and those with an index ≤ -1 were classified as the increased risk group. Osteoporosis is defined by a T-score ≤ 2.5 standard deviations according to the WHO criteria. All painful, new vertebral fractures were identified by X-ray and MRI scans with correlating clinical signs and symptoms. We determined the sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve for correctly selecting women with osteoporosis and painful new vertebral fractures.ResultsOf the study subjects, 29.3% had osteoporosis, and the prevalence of osteoporosis increased progressively with age. The areas under the ROC curves of the OSTA index (cutoff = -1) to identify osteoporosis in the femoral neck, total hip, and lumbar spine were 0.824, 0.824, and 0.776, respectively. The sensitivity and specificity of the OSTA index (cutoff = -1) to identify osteoporosis in healthy women were 66% and 76%, respectively. With regard to painful new vertebral fractures, the area under the ROC curve relating the OSTA index (cutoff = -1) to new vertebral fractures was 0.812.ConclusionsThe OSTA may be a simple and effective tool for identifying the risk of osteoporosis and new painful osteoporotic vertebral fractures in Han Chinese women.