Spatial distribution and influencing factors analysis of national key rural tourism villages in the Yangtze River Delta region based on geographically weighted regression.

National key rural tourism villages (NKRTVs) can lead to the high-quality development of rural tourism, and their spatial distribution is influenced by a variety of factors. However, existing studies have neglected the fact that influencing factors can have different directions and effects in different geographic spaces. This study investigates 156 NKRTVs in the Yangtze River Delta region of China as the research object and employs ArcGIS spatial analysis technology to examine their spatial distribution characteristics. Additionally, two new indicators of land and culture are introduced to enhance the index system of influencing factors. A geographically weighted regression model is utilized to identify the spatial heterogeneity of various factors that affect the spatial distribution of NKRTVs. The results of this study indicate the following: (1) The spatial distribution of NKRTVs in the Yangtze River Delta region is characterized by "small clustering and large dispersion." The spatial distribution exhibits strong spatial correlation, with Shanghai serving as the primary spatial clustering core and Huangshan city forming a secondary spatial clustering subcore. The distribution of NKRTVs is relatively scattered in other areas, with obvious differences in the spatial distribution of cold and hot spots. (2) The results of the geographically weighted regression model show that with the change in spatial location, the influence effect of each influencing factor on the spatial distribution of NKRTVs has obvious spatial differences. Based on the spatial heterogeneity of the influencing factors, this study proposes targeted suggestions for the development of rural tourism in different regions.

Genetic Mapping and QTL Analysis of Fruit Traits in Melon (Cucumis melo L.).

Melon (Cucumis melo L.) is an important horticultural cash crop and its quality traits directly affect consumer choice and market price. These traits are controlled by genetic as well as environmental factors. In this study, a quantitative trait locus (QTL) mapping strategy was used to identify the potential genetic loci controlling quality traits of melons (i.e., exocarp and pericarp firmness and soluble solid content) based on newly derived whole-genome single nucleotide polymorphism-based cleaved amplified polymorphic sequence (SNP-CAPS) markers. Specifically, SNPs of two melon varieties, M4-5 and M1-15, as revealed by whole-genome sequencing, were converted to the CAPS markers, which were used to construct a genetic linkage map comprising 12 chromosomes with a total length of 1414.88 cM, in the F2 population of M4-5 and M1-15. The six identified QTLs included: SSC6.1 and SSC11.1 related to soluble solid content; EF12.1 associated with exocarp firmness; and EPF3.1, EPF3.2 and EPF7.1 related to edible pericarp firmness. These genes were located on five chromosomes (3, 6, 7, 11, and 12) in the flanking regions of the CAPS markers. Moreover, the newly developed CAPS markers will be useful in guiding genetic engineering and molecular breeding in melon.

CNV-FB: A Feature bagging strategy-based approach to detect copy number variants from NGS data.

Copy number variation (CNV), as a type of genomic structural variation, accounts for a large proportion of structural variation and is related to the pathogenesis and susceptibility to some human diseases, playing an important role in the development and change of human diseases. The development of next-generation sequencing technology (NGS) provides strong support for the design of CNV detection algorithms. Although a large number of methods have been developed to detect CNVs using NGS data, it is still considered a difficult problem to detect CNVs with low purity and coverage. In this paper, a new calculation method CNV-FB is proposed to detect CNVs from NGS data. The core idea of CNV-FB is to randomly sample the read depth values of the genome fragment, and then each sample is individually detected for outliers, and finally combined into a final outlier score. The CNV-FB method was applied to simulation data and real data experiments and compared with the other five methods of the same type. The results show that the CNV-FB method has a better detection effect than other methods. Therefore, the CNV-FB method may be an effective algorithm for detecting genomic mutations.

svBreak: A New Approach for the Detection of Structural Variant Breakpoints Based on Convolutional Neural Network.

Structural variation (SV) is an important type of genome variation and confers susceptibility to human cancer diseases. Systematic analysis of SVs has become a crucial step for the exploration of mechanisms and precision diagnosis of cancers. The central point is how to accurately detect SV breakpoints by using next-generation sequencing (NGS) data. Due to the cooccurrence of multiple types of SVs in the human genome and the intrinsic complexity of SVs, the discrimination of SV breakpoint types is a challenging task. In this paper, we propose a convolutional neural network- (CNN-) based approach, called svBreak, for the detection and discrimination of common types of SV breakpoints. The principle of svBreak is that it extracts a set of SV-related features for each genome site from the sequencing reads aligned to the reference genome and establishes a data matrix where each row represents one site and each column represents one feature and then adopts a CNN model to analyze such data matrix for the prediction of SV breakpoints. The performance of the proposed approach is tested via simulation studies and application to a real sequencing sample. The experimental results demonstrate the merits of the proposed approach when compared with existing methods. Thus, svBreak can be expected to be a supplementary approach in the field of SV analysis in human tumor genomes.

CIRCNV: Detection of CNVs Based on a Circular Profile of Read Depth from Sequencing Data.

Copy number variation (CNV) is a common type of structural variation in the human genome. Accurate detection of CNVs from tumor genomes can provide crucial information for the study of tumor genesis and cancer precision diagnosis. However, the contamination of normal genomes in tumor genomes and the crude profiles of the read depth make such a task difficult. In this paper, we propose an alternative approach, called CIRCNV, for the detection of CNVs from sequencing data. CIRCNV is an extension of our previously developed method CNV-LOF, which uses local outlier factors to predict CNVs. Comparatively, CIRCNV can be performed on individual tumor samples and has the following two new features: (1) it transfers the read depth profile from a line shape to a circular shape via a polar coordinate transformation, in order to improve the efficiency of the read depth (RD) profile for the detection of CNVs; and (2) it performs a second round of CNV declaration based on the truth circular RD profile, which is recovered by estimating tumor purity. We test and validate the performance of CIRCNV based on simulation and real sequencing data and perform comparisons with several peer methods. The results demonstrate that CIRCNV can obtain superior performance in terms of sensitivity and precision. We expect that our proposed method will be a supplement to existing methods and become a routine tool in the field of variation analysis of tumor genomes.

A comprehensive evaluation of the potential of semiterrestrial isopods, Ligia exotica, as a new animal food.

The semiterrestrial isopod, Ligia exotica represents one of the oldest documented species introductions of marine organisms and is known as an intermediate form between marine and strictly terrestrial isopods. In order to explore the potential value of Ligia as an animal food source, this study focused on the growth rate under laboratory rearing conditions and conducted a detailed analysis of the overall nutrient content of the species in comparison to two other marine food media (krill and fish meal). Evaluation of the growth rate of juveniles suggests it is a relatively fast-growing species of the Ligiidae family. The essential amino acids content Ligia meal is the lowest amongst the three studied media but the proportion of flavor amino acids, and in particular taurine, was higher. The most restricted amino acids of isopod meal are methionine and cysteine. The significantly unbalanced amino acid composition of Ligia meal may affect the absorption and utilization by consumers. In terms of fatty acids, the total polyunsaturated fatty acids in the isopod is very low. A total of 12 vitamins were examined. The VK1, VE, VB2, VB3, VB5 content of isopod meal were significantly higher than those of krill meal and fish meal. Similarly, most of the 11 mineral elements are highest in the isopod meal. Ligia therefore offers potential as an alternative natural food source in animal given the growth rate under culture and the overall nutrient content. But Ligia collected in most of the field would be deemed unfit for human consumption because of the relatively low nutritional value and heavy metal content exceeding the provided standard. Further study is warranted to elucidate the biological characteristics of isopods and how its diet is reflected in its nutritional value to consumers.

STIC: Predicting Single Nucleotide Variants and Tumor Purity in Cancer Genome.

Single nucleotide variant (SNV) plays an important role in cellular proliferation and tumorigenesis in various types of human cancer. Next-generation sequencing (NGS) has provided high-throughput data at an unprecedented resolution to predict SNVs. Currently, there exist many computational methods for either germline or somatic SNV discovery from NGS data, but very few of them are versatile enough to adapt to any situations. In the absence of matched normal samples, the prediction of somatic SNVs from single-tumor samples becomes considerably challenging, especially when the tumor purity is unknown. Here, we propose a new approach, STIC, to predict somatic SNVs and estimate tumor purity from NGS data without matched normal samples. The main features of STIC include: (1) extracting a set of SNV-relevant features on each site and training the BP neural network algorithm on the features to predict SNVs; (2) creating an iterative process to distinguish somatic SNVs from germline ones by disturbing allele frequency; and (3) establishing a reasonable relationship between tumor purity and allele frequencies of somatic SNVs to accurately estimate the purity. We quantitatively evaluate the performance of STIC on both simulation and real sequencing datasets, the results of which indicate that STIC outperforms competing methods.

ERINS: Novel Sequence Insertion Detection by Constructing an Extended Reference.

Next generation sequencing technology has led to the development of methods for the detection of novel sequence insertions (nsINS). Multiple signatures from short reads are usually extracted to improve nsINS detection performance. However, characterization of nsINSs larger than the mean insert size is still challenging. This article presents a new method, ERINS, to detect nsINS contents and genotypes of full spectrum range size. It integrates the features of structural variations and mapping states of split reads to find nsINS breakpoints, and then adopts a left-most mapping strategy to infer nsINS content by iteratively extending the standard reference at each breakpoint. Finally, it realigns all reads to the extended reference and infers nsINS genotypes through statistical testing on read counts. We test and validate the performance of ERINS on simulation and real sequencing datasets. The simulation experimental results demonstrate that it outperforms several peer methods with respect to sensitivity and precision. The real data application indicates that ERINS obtains high consistent results with those of previously reported and detects nsINSs over 200 base pairs that many other methods fail. In conclusion, ERINS can be used as a supplement to existing tools and will become a routine approach for characterizing nsINSs.

Detection of Pathogenic Microbe Composition Using Next-Generation Sequencing Data.

Next-generation sequencing (NGS) technologies have provided great opportunities to analyze pathogenic microbes with high-resolution data. The main goal is to accurately detect microbial composition and abundances in a sample. However, high similarity among sequences from different species and the existence of sequencing errors pose various challenges. Numerous methods have been developed for quantifying microbial composition and abundance, but they are not versatile enough for the analysis of samples with mixtures of noise. In this paper, we propose a new computational method, PGMicroD, for the detection of pathogenic microbial composition in a sample using NGS data. The method first filters the potentially mistakenly mapped reads and extracts multiple species-related features from the sequencing reads of 16S rRNA. Then it trains an Support Vector Machine classifier to predict the microbial composition. Finally, it groups all multiple-mapped sequencing reads into the references of the predicted species to estimate the abundance for each kind of species. The performance of PGMicroD is evaluated based on both simulation and real sequencing data and is compared with several existing methods. The results demonstrate that our proposed method achieves superior performance. The software package of PGMicroD is available at https://github.com/BDanalysis/PGMicroD.

Requisite Chromatin Remodeling for Myeloid and Erythroid Lineage Differentiation from Erythromyeloid Progenitors.

The mammalian SWitch/Sucrose Non-Fermentable (SWI/SNF) chromatin-remodeling BAF (BRG1/BRM-associated factor) complex plays an essential role in developmental and pathological processes. We show that the deletion of Baf155, which encodes a subunit of the BAF complex, in the Tie2(+) lineage (Baf155 (CKO) leads to defects in yolk sac myeloid and definitive erythroid (EryD) lineage differentiation from erythromyeloid progenitors (EMPs). The chromatin of myeloid gene loci in Baf155 CKO EMPs is mostly inaccessible and enriched mainly by the ETS binding motif. BAF155 interacts with PU.1 and is recruited to PU.1 target gene loci together with p300 and KDM6a. Treatment of Baf155 CKO embryos with GSK126, an H3K27me2/3 methyltransferase EZH2 inhibitor, rescues myeloid lineage gene expression. This study uncovers indispensable BAF-mediated chromatin remodeling of myeloid gene loci at the EMP stage. Future studies exploiting epigenetics in the generation and application of EMP derivatives for tissue repair, regeneration, and disease are warranted.

MFCNV: A New Method to Detect Copy Number Variations From Next-Generation Sequencing Data.

Copy number variation (CNV) is a very important phenomenon in tumor genomes and plays a significant role in tumor genesis. Accurate detection of CNVs has become a routine and necessary procedure for a deep investigation of tumor cells and diagnosis of tumor patients. Next-generation sequencing (NGS) technique has provided a wealth of data for the detection of CNVs at base-pair resolution. However, such task is usually influenced by a number of factors, including GC-content bias, sequencing errors, and correlations among adjacent positions within CNVs. Although many existing methods have dealt with some of these artifacts by designing their own strategies, there is still a lack of comprehensive consideration of all the factors. In this paper, we propose a new method, MFCNV, for an accurate detection of CNVs from NGS data. Compared with existing methods, the characteristics of the proposed method include the following: (1) it makes a full consideration of the intrinsic correlations among adjacent positions in the genome to be analyzed, (2) it calculates read depth, GC-content bias, base quality, and correlation value for each genome bin and combines them as multiple features for the evaluation of genome bins, and (3) it addresses the joint effect among the factors via training a neural network algorithm for the prediction of CNVs. We test the performance of the MFCNV method by using simulation and real sequencing data and make comparisons with several peer methods. The results demonstrate that our method is superior to other methods in terms of sensitivity, precision, and F1-score and can detect many CNVs that other methods have not discovered. MFCNV is expected to be a complementary tool in the analysis of mutations in tumor genomes and can be extended to be applied to the analysis of single-cell sequencing data.

Accurate Inference of Tumor Purity and Absolute Copy Numbers From High-Throughput Sequencing Data.

Inference of absolute copy numbers in tumor genomes is one of the key points in the study of tumor genesis. However, the mixture of tumor and normal cells poses a big challenge to this task. Accurate estimation of tumor purity (i.e., the fraction of tumor cells) is a necessary step to solve this problem. In this paper, we propose a new approach, AITAC, to accurately infer tumor purity and absolute copy numbers in a tumor sample by using high-throughput sequencing (HTS) data. In contrast to many existing algorithms for estimating tumor purity, which usually rely on pre-detected mutation genotypes (heterogeneity and homogeneity), AITAC just requires read depths (RDs) observed at the regions with copy number losses. AITAC creates a non-linear model to correlate tumor purity, observed and expected RDs. It adopts an exhaustive search strategy to scan tumor purity in a wide range, and chooses the tumor purity that minimizes the deviation between observed RDs and expected ones as the optimal solution. We apply the proposed approach to both simulation and real sequencing data sets and demonstrate its performance by comparing with two classical approaches. AITAC is freely available at https://github.com/BDanalysis/aitac and can be expected to become a useful approach for researchers to analyze copy numbers in cancer genome.

Single cell transcriptome dynamics from pluripotency to FLK1+ mesoderm.

Hemangiogenic progenitors generating blood and endothelial cells are specified from FLK1-expressing (FLK1+) mesoderm by the transcription factor ETV2. FLK1+ mesoderm also contributes to smooth muscle and cardiomyocytes. However, the developmental process of FLK1+ mesoderm generation and its allocation to various cell fates remain obscure. Recent single cell RNA-sequencing studies of early embryos or in vitro-differentiated human embryonic stem (ES) cells have provided unprecedented information on the spatiotemporal resolution of cells in embryogenesis. These snapshots, however, lack information on continuous dynamic developmental processes. Here, we performed single cell RNA sequencing of in vitro-differentiated mouse ES cells to capture the continuous developmental process leading to hemangiogenesis. We found that hemangiogenic progenitors from ES cells develop through intermediate gastrulation stages, which are gradually specified by 'relay'-like highly overlapping transcription factor modules. Moreover, the transcriptional program of the Flk1+ mesoderm was maintained in the smooth muscle lineage, suggesting that smooth muscle is the default fate of Flk1+ mesoderm. We also identified the SRC kinase contributing to ETV2-mediated activation of the hemangiogenic program. This continuous transcriptome map will facilitate both basic and applied studies of mesoderm development.

A CRISPR screen identifies genes controlling Etv2 threshold expression in murine hemangiogenic fate commitment.

The ETS transcription factor Etv2 is necessary and sufficient for the generation of hematopoietic and endothelial cells. However, upstream regulators of Etv2 in hemangiogenesis, generation of hematopoietic and endothelial cells, have not been clearly addressed. Here we track the developmental route of hemangiogenic progenitors from mouse embryonic stem cells, perform genome-wide CRISPR screening, and transcriptome analysis of en route cell populations by utilizing Brachyury, Etv2, or Scl reporter embryonic stem cell lines to further understand the mechanisms that control hemangiogenesis. We identify the forkhead transcription factor Foxh1, in part through Eomes, to be critical for the formation of FLK1+ mesoderm, from which the hemangiogenic fate is specified. Importantly, hemangiogenic fate is specified not simply by the onset of Etv2 expression, but by a threshold-dependent mechanism, in which VEGF-FLK1 signaling plays an instructive role by promoting Etv2 threshold expression. These studies reveal comprehensive cellular and molecular pathways governing the hemangiogenic cell lineage development.How haematopoietic and endothelial cell lineages are specified is unclear. Here, the authors identify the forkhead transcription factor Foxh1 as regulating FLK1+ mesoderm formation in mouse embryonic stem cells, which in turn specifies hemangiogenic fate via Etv2.

ETS transcription factor ETV2/ER71/Etsrp in hematopoietic and vascular development, injury, and regeneration.

The major goal in regenerative medicine is to repair and restore injured, diseased or aged tissue function, thereby promoting general health. As such, the field of regenerative medicine has great translational potential in undertaking many of the health concerns and needs that we currently face. In particular, hematopoietic and vascular systems supply oxygen and nutrients and thus play critical roles in tissue development and tissue regeneration. Additionally, tissue vasculature serves as a tissue stem cell niche and thus contributes to tissue homeostasis. Notably, hematopoietic and vascular systems are sensitive to injury and subject to regeneration. As such, successful hematopoietic and vascular regeneration is prerequisite for efficient tissue repair and organismal survival and health. Recent studies have established that the interplay among the ETS transcription factor ETV2, vascular endothelial growth factor, and its receptor VEGFR2/FLK1 is essential for hematopoietic and vascular development. Emerging studies also support the role of these three factors and possible interplay in hematopoietic and vascular regeneration. Comprehensive understanding of the molecular mechanisms involved in the regulation and function of these three factors may lead to more effective approaches in promoting tissue repair and regeneration. Developmental Dynamics 246:318-327, 2017. © 2016 Wiley Periodicals, Inc.

An increase in the incidence of hip fractures in Tangshan, China.

UNLABELLED: We determined the number and incidence of hip fractures in Tangshan, China, in 2010. Compared with data we reported in Tangshan from 1994, the crude and age-specific incidence increased significantly for both sexes, especially in women. Strategies are needed for effective fracture prevention in the future. INTRODUCTION: The aims of the study were to determine the incidence of cervical and trochanteric fractures of the proximal femur in Tangshan, China, in 2010 and to compare the incidence with data from 1994. METHODS: The orthopedic departments of 15 hospitals in Tangshan were visited in 2010; the medical records and radiographs of patients who had sustained cervical and trochanteric fractures were reviewed. The absolute number of admissions was collated and the incidence rate per 100,000 person years was calculated, adjusted by different age ranges, and gender. We then calculated the age-standardized incidence in 2010 as compared with those from 1994. RESULTS: The population of Tangshan in 2010 was determined to be 3,075,382 (1,558,173 males; 1,517,209 females); there were 1,509 cervical and trochanteric fractures (in 745 males and 764 females). The overall incidence was 47.8 and 50.4 fractures per 100,000 per year for men and women, respectively. Females showed a higher fracture incidence than males in those aged 55 years and over. Comparing the 2010 data with the 1994 findings, the incidence increased by 85% in men and by 306% in women; age-specific increases were observed in all female and male groups (except the 55-59 years age group). CONCLUSIONS: Compared with the results in 1994, the incidence of hip fracture has markedly increased in 2010 in Tangshan, China. It is necessary to implement a comprehensive policy for hip fracture prevention in our communities.

The impact of R213 mutation on p53-mediated p21 activity.

p53 is a transcriptional regulator in the nucleus that functions as a tumor suppressor and its mutations are frequently found in human tumors. It has been reported that p53 with R213Q mutation is exist in certain tumor cell lines and its methylation on R213 as well. However, the mechanisms and consequences of these modifications on p53 function are not fully understood. Mutations of p53 at R213Q (R/Q) and R213K (R/K) were respectively constructed and transfected into the p53 null H1299 cells. As shown in luciferase reporter assays, either R/Q or R/K disrupted the efficiency of p53 transactivation. EMSA and ChIP assays revealed that these mutants were less efficient in targeting the consensus binding sequences of p53 in the regulatory region of p21 gene. In addition, R/Q and R/K mutants attenuated the expression of p21 gene and counteracted the p53 mediated G1/S arrest to deliver a normal cell cycle progression as in the mock H1299 cells. Through this study, we have provided the first evidence on the pivotal role of arginine 213 that determines the p53 mediated functions of p21 in human cancer cells.

H3.3 actively marks enhancers and primes gene transcription via opening higher-ordered chromatin.

The histone variants H3.3 and H2A.Z have recently emerged as two of the most important features in transcriptional regulation, the molecular mechanism of which still remains poorly understood. In this study, we investigated the regulation of H3.3 and H2A.Z on chromatin dynamics during transcriptional activation. Our in vitro biophysical and biochemical investigation showed that H2A.Z promoted chromatin compaction and repressed transcriptional activity. Surprisingly, with only four to five amino acid differences from the canonical H3, H3.3 greatly impaired higher-ordered chromatin folding and promoted gene activation, although it has no significant effect on the stability of mononucleosomes. We further demonstrated that H3.3 actively marks enhancers and determines the transcriptional potential of retinoid acid (RA)-regulated genes via creating an open chromatin signature that enables the binding of RAR/RXR. Additionally, the H3.3-dependent recruitment of H2A.Z on promoter regions resulted in compaction of chromatin to poise transcription, while RA induction results in the incorporation of H3.3 on promoter regions to activate transcription via counteracting H2A.Z-mediated chromatin compaction. Our results provide key insights into the mechanism of how histone variants H3.3 and H2A.Z function together to regulate gene transcription via the modulation of chromatin dynamics over the enhancer and promoter regions.

Differential effects of AdOx on gene expression in P19 embryonal carcinoma cells.

BACKGROUND: Pluripotent cells maintain a unique gene expression pattern and specific chromatin signature. In this study, we explored the effect of the methyltransferase inhibitor adenosine dialdehyde (AdOx) on pluripotency maintenance and gene expression in P19 embryonal carcinoma cells. RESULTS: After AdOx treatment, the pluripotency-related gene network became disordered, and the early developmental genes were released from the repression. Remarkably, AdOx caused contrasting effects on the expression of two key pluripotency genes, nanog and oct3/4, with the reduction of the repressive histone marks H3K27me3, H3K9me3 and H3K9me2 only in the nanog gene. CONCLUSIONS: Key pluripotency genes were controlled by different mechanisms, including the differential enrichment of repressive histone methylation marks. These data provided novel clues regarding the critical role of histone methylation in the maintenance of pluripotency and the determination of cell fate in P19 pluripotent cells.