bluuebunny/crossref_metadata_2025_split huggingface dataset:
PROMO: an interactive tool for analyzing clinically-labeled multi-omic cancer datasets
Authors: Netanely Dvir , Stern Neta , Laufer Itay , Shamir Ron 
Published: December 2019

AbstractBackgroundAnalysis of large genomic datasets along with their accompanying clinical information has shown great promise in cancer research over the last decade. Such datasets typically include thousands of samples, each measured by one or several high-throughput technologies (‘omics’) and annotated with extensive clinical information. While instrumental for fulfilling the promise of personalized medicine, the analysis and visualization of such large datasets is challenging and necessitates programming skills and familiarity with a large array of software tools to be used for the various steps of the analysis.ResultsWe developed PROMO (Profiler of Multi-Omic data), a friendly, fully interactive stand-alone software for analyzing large genomic cancer datasets together with their associated clinical information. The tool provides an array of built-in methods and algorithms for importing, preprocessing, visualizing, clustering, clinical label enrichment testing, and survival analysis that can be performed on a single or multi-omic dataset. The tool can be used for quick exploration and stratification of tumor samples taken from patients into clinically significant molecular subtypes. Identification of prognostic biomarkers and generation of simple subtype classifiers are additional important features. We review PROMO’s main features and demonstrate its analysis capabilities on a breast cancer cohort from TCGA.ConclusionsPROMO provides a single integrated solution for swiftly performing a complete analysis of cancer genomic data for subtype discovery and biomarker identification without writing a single line of code, and can, therefore, make the analysis of these data much easier for cancer biologists and biomedical researchers. PROMO is freely available for download athttp://acgt.cs.tau.ac.il/promo/.
ICGRM: integrative construction of genomic relationship matrix combining multiple genomic regions for big dataset
Authors: Jiang Dan , Xin Cong , Ye Jinhua , Yuan Yingbo , Fang Ming 
Published: December 2019

AbstractBackgroundGenomic prediction is an advanced method for estimating genetic values, which has been widely accepted for genetic evaluation in animal and disease-risk prediction in human. It estimates genetic values with genome-wide distributed SNPs instead of pedigree. The key step of it is to construct genomic relationship matrix (GRM) via genome-wide SNPs; however, usually the calculation of GRM needs huge computer memory especially when the SNP number and sample size are big, so that sometimes it will become computationally prohibitive even for super computer clusters. We herein developed an integrative algorithm to compute GRM. To avoid calculating GRM for the whole genome, ICGRM freely divides the genome-wide SNPs into several segments and computes the summary statistics related to GRM for each segment that requires quite few computer RAM; then it integrates these summary statistics to produce GRM for whole genome.ResultsIt showed that the computer memory of ICGRM was reduced by 15 times (from 218Gb to 14Gb) after the genome SNPs were split into 5 to 200 parts in terms of the number of SNPs in our simulation dataset, making it computationally feasible for almost all kinds of computer servers. ICGRM is implemented in C/C++ and freely available viahttps://github.com/mingfang618/CLGRM.ConclusionsICGRM is computationally efficient software to build GRM and can be used for big dataset.
Exploring the changing landscape of cell-to-cell variation after CTCF knockdown via single cell RNA-seq
Authors: Wang Wei , Ren Gang , Hong Ni , Jin Wenfei 
Published: December 2019

Abstract
Background
CCCTC-Binding Factor (CTCF), also known as 11-zinc finger protein, participates in many cellular processes, including insulator activity, transcriptional regulation and organization of chromatin architecture. Based on single cell flow cytometry and single cell RNA-FISH analyses, our previous study showed that deletion of CTCF binding site led to a significantly increase of cellular variation of its target gene. However, the effect of CTCF on genome-wide landscape of cell-to-cell variation remains unclear.

Results
We knocked down CTCF in EL4 cells using shRNA, and conducted single cell RNA-seq on both wild type (WT) cells and CTCF-Knockdown (CTCF-KD) cells using Fluidigm C1 system. Principal component analysis of single cell RNA-seq data showed that WT and CTCF-KD cells concentrated in two different clusters on PC1, indicating that gene expression profiles of WT and CTCF-KD cells were systematically different. Interestingly, GO terms including regulation of transcription, DNA binding, zinc finger and transcription factor binding were significantly enriched in CTCF-KD-specific highly variable genes, implying tissue-specific genes such as transcription factors were highly sensitive to CTCF level. The dysregulation of transcription factors potentially explains why knockdown of CTCF leads to systematic change of gene expression. In contrast, housekeeping genes such as rRNA processing, DNA repair and tRNA processing were significantly enriched in WT-specific highly variable genes, potentially due to a higher cellular variation of cell activity in WT cells compared to CTCF-KD cells. We further found that cellular variation-increased genes were significantly enriched in down-regulated genes, indicating CTCF knockdown simultaneously reduced the expression levels and increased the expression noise of its regulated genes.

Conclusions
To our knowledge, this is the first attempt to explore genome-wide landscape of cellular variation after CTCF knockdown. Our study not only advances our understanding of CTCF function in maintaining gene expression and reducing expression noise, but also provides a framework for examining gene function.
PaCBAM: fast and scalable processing of whole exome and targeted sequencing data
Authors: Valentini Samuel , Fedrizzi Tarcisio , Demichelis Francesca , Romanel Alessandro 
Published: December 2019

Abstract
Background
Interrogation of whole exome and targeted sequencing NGS data is rapidly becoming a preferred approach for the exploration of large cohorts in the research setting and importantly in the context of precision medicine. Single-base and genomic region level data retrieval and processing still constitute major bottlenecks in NGS data analysis. Fast and scalable tools are hence needed.

Results
PaCBAM is a command line tool written in C and designed for the characterization of genomic regions and single nucleotide positions from whole exome and targeted sequencing data. PaCBAM computes depth of coverage and allele-specific pileup statistics, implements a fast and scalable multi-core computational engine, introduces an innovative and efficient on-the-fly read duplicates filtering strategy and provides comprehensive text output files and visual reports. We demonstrate that PaCBAM exploits parallel computation resources better than existing tools, resulting in important reductions of processing time and memory usage, hence enabling an efficient and fast exploration of large datasets.

Conclusions
PaCBAM is a fast and scalable tool designed to process genomic regions from NGS data files and generate coverage and pileup comprehensive statistics for downstream analysis. The tool can be easily integrated in NGS processing pipelines and is available from Bitbucket and Docker/Singularity hubs.
Transcriptome analysis of the fungal pathogen Rosellinia necatrix during infection of a susceptible avocado rootstock identifies potential mechanisms of pathogenesis
Authors: Zumaquero A. , Kanematsu S. , Nakayashiki H. , Matas A. , Martínez-Ferri E. , Barceló-Muñóz A. , Pliego-Alfaro F. , López-Herrera C. , Cazorla F. M. , Pliego C. 
Published: December 2019

Abstract
Background
White root rot disease caused by Rosellinia necatrix is one of the most important threats affecting avocado productivity in tropical and subtropical climates. Control of this disease is complex and nowadays, lies in the use of physical and chemical methods, although none have proven to be fully effective. Detailed understanding of the molecular mechanisms underlying white root rot disease has the potential of aiding future developments in disease resistance and management. In this regard, this study used RNA-Seq technology to compare the transcriptomic profiles of R. necatrix during infection of susceptible avocado ‘Dusa’ roots with that obtained from the fungus cultured in rich medium.

Results
The transcriptomes from three biological replicates of R. necatrix colonizing avocado roots (RGA) and R. necatrix growing on potato dextrose agar media (RGPDA) were analyzed using Illumina sequencing. A total of 12,104 transcripts were obtained, among which 1937 were differentially expressed genes (DEG), 137 exclusively expressed in RGA and 160 in RGPDA. During the root infection process, genes involved in the production of fungal toxins, detoxification and transport of toxic compounds, hormone biosynthesis, gene silencing and plant cell wall degradation were overexpressed. Interestingly, 24 out of the 137 contigs expressed only during R. necatrix growth on avocado roots, were predicted as candidate effector proteins (CEP) with a probability above 60%. The PHI (Pathogen Host Interaction) database revealed that three of the R. necatrix CEP showed homology with previously annotated effectors, already proven experimentally via pathogen-host interaction.

Conclusions
The analysis of the full-length transcriptome of R. necatrix during the infection process is suggesting that the success of this fungus to infect roots of diverse crops might be attributed to the production of different compounds which, singly or in combination, interfere with defense or signaling mechanisms shared among distinct plant families. The transcriptome analysis of R. necatrix during the infection process provides useful information and facilitates further research to a more in -depth understanding of the biology and virulence of this emergent pathogen. In turn, this will make possible to evolve novel strategies for white root rot management in avocado.
Archaic mitochondrial DNA inserts in modern day nuclear genomes
Authors: Bücking Robert , Cox Murray P , Hudjashov Georgi , Saag Lauri , Sudoyo Herawati , Stoneking Mark 
Published: December 2019

Abstract
Background
Traces of interbreeding of Neanderthals and Denisovans with modern humans in the form of archaic DNA have been detected in the genomes of present-day human populations outside sub-Saharan Africa. Up to now, only nuclear archaic DNA has been detected in modern humans; we therefore attempted to identify archaic mitochondrial DNA (mtDNA) residing in modern human nuclear genomes as nuclear inserts of mitochondrial DNA (NUMTs).

Results
We analysed 221 high-coverage genomes from Oceania and Indonesia using an approach which identifies reads that map both to the nuclear and mitochondrial DNA. We then classified reads according to the source of the mtDNA, and found one NUMT of Denisovan mtDNA origin, present in 15 analysed genomes; analysis of the flanking region suggests that this insertion is more likely to have happened in a Denisovan individual and introgressed into modern humans with the Denisovan nuclear DNA, rather than in a descendant of a Denisovan female and a modern human male.

Conclusions
Here we present our pipeline for detecting introgressed NUMTs in next generation sequencing data that can be used on genomes sequenced in the future. Further discovery of such archaic NUMTs in modern humans can be used to detect interbreeding between archaic and modern humans and can reveal new insights into the nature of such interbreeding events.
Network analysis exposes core functions in major lifestyles of fungal and oomycete plant pathogens
Authors: Pandaranayaka Eswari PJ , Frenkel Omer , Elad Yigal , Prusky Dov , Harel Arye 
Published: December 2019

Abstract
Background
Genomic studies demonstrate that components of virulence mechanisms in filamentous eukaryotic pathogens (FEPs, fungi and oomycetes) of plants are often highly conserved, or found in gene families that include secreted hydrolytic enzymes (e.g., cellulases and proteases) and secondary metabolites (e.g., toxins), central to the pathogenicity process. However, very few large-scale genomic comparisons have utilized complete proteomes from dozens of FEPs to reveal lifestyle-associated virulence mechanisms. Providing a powerful means for exploration, and the discovery of trends in large-scale datasets, network analysis has been used to identify core functions of the primordial cyanobacteria, and ancient evolutionary signatures in oxidoreductases.

Results
We used a sequence-similarity network to study components of virulence mechanisms of major pathogenic lifestyles (necrotroph (ic), N; biotroph (ic), B; hemibiotroph (ic), H) in complete pan-proteomes of 65 FEPs and 17 saprobes. Our comparative analysis highlights approximately 190 core functions found in 70% of the genomes of these pathogenic lifestyles. Core functions were found mainly in: transport (in H, N, B cores); carbohydrate metabolism, secondary metabolite synthesis, and protease (H and N cores); nucleic acid metabolism and signal transduction (B core); and amino acid metabolism (H core). Taken together, the necrotrophic core contains functions such as cell wall-associated degrading enzymes, toxin metabolism, and transport, which are likely to support their lifestyle of killing prior to feeding. The biotrophic stealth growth on living tissues is potentially controlled by a core of regulatory functions, such as: small G-protein family of GTPases, RNA modification, and cryptochrome-based light sensing. Regulatory mechanisms found in the hemibiotrophic core contain light- and CO2-sensing functions that could mediate important roles of this group, such as transition between lifestyles.

Conclusions
The selected set of enriched core functions identified in our work can facilitate future studies aimed at controlling FEPs. One interesting example would be to facilitate the identification of the pathogenic potential of samples analyzed by metagenomics. Finally, our analysis offers potential evolutionary scenarios, suggesting that an early-branching saprobe (identified in previous studies) has probably evolved a necrotrophic lifestyle as illustrated by the highest number of shared gene families between saprobes and necrotrophs.
Variation of growth characteristics of pneumococcus with environmental conditions
Authors: Tóthpál Adrienn , Desobry Katherine , Joshi Shreyas S. , Wyllie Anne L. , Weinberger Daniel M. 
Published: December 2019

Abstract
Background
Pneumococcus is exposed to a variety of temperature and oxygen levels in the upper respiratory tract and as it invades the lung, tissues, and blood. We sought to determine the effect of environmental variability on growth in vitro and to assess variability between strains. We evaluated the effect of temperature and oxygen on the growth of 256 isolates representing 53 serotypes, recovered from healthy carriers and disease patients. Strains were grown at a range of temperatures, anaerobically or in ambient air with catalase, and were monitored by reading the optical density. Regression models evaluated variation in the characteristics of the growth curves.

Results
Most isolates grew to the maximal density at low temperatures (~33C) and under aerobic conditions. There was considerable variability between strains, and some of this variability was linked to serotype. However, capsule-switch experiments suggest that the production of different capsules might not be sufficient to explain this variation, suggesting there could be interactions between the capsule and genetic background.

Conclusions
Pneumococcal strains vary in how they respond to environmental variations, some of this variation can be explained by the capsule type being produced, but capsule production itself is not sufficient to explain the variability. This variability could help to explain why different lineages of pneumococcus are more common in carriage or disease.
Comparative physiological, metabolomic, and transcriptomic analyses reveal developmental stage-dependent effects of cluster bagging on phenolic metabolism in Cabernet Sauvignon grape berries
Authors: Sun Run-Ze , Cheng Guo , Li Qiang , Zhu Yan-Rong , Zhang Xue , Wang Yu , He Yan-Nan , Li Si-Yu , He Lei , Chen Wu , Pan Qiu-Hong , Duan Chang-Qing , Wang Jun 
Published: December 2019

AbstractBackgroundLight conditions significantly influence grape berry ripening and the accumulation of phenolic compounds, but the underlying molecular basis remains partially understood. Here, we applied integrated transcriptomics and pathway-level metabolomics analyses to investigate the effect of cluster bagging during various developmental stages on phenolic metabolism in Cabernet Sauvignon grapes.ResultsBagging treatments had limited effects on berry quality attributes at harvest and did not consistently affect phenolic acid biosynthesis between seasons. Significantly elevated flavan-3-ol and flavonol contents were detected in re-exposed berries after bagging during early-developmental stages, while bagging after véraison markedly inhibited skin anthocyanin accumulation. Several anthocyanin derivatives and flavonol glycosides were identified as marker phenolic metabolites for distinguishing bagged and non-bagged grapes. Coordinated transcriptional changes in the light signaling components CRY2 and HY5/HYHs, transcription regulator MYBA1, and enzymes LAR, ANR, UFGT and FLS4, coincided well with light-responsive biosynthesis of the corresponding flavonoids. The activation of multiple hormone signaling pathways after both light exclusion and re-exposure treatments was inconsistent with the changes in phenolic accumulation, indicating a limited role of plant hormones in mediating light/darkness-regulated phenolic biosynthesis processes. Furthermore, gene-gene and gene-metabolite network analyses discovered that the light-responsive expression of genes encoding bHLH, MYB, WRKY, NAC, and MADS-box transcription factors, and proteins involved in genetic information processing and epigenetic regulation such as nucleosome assembly and histone acetylation, showed a high positive correlation with grape berry phenolic accumulation in response to different light regimes.ConclusionsAltogether, our findings provide novel insights into the understanding of berry phenolic biosynthesis under light/darkness and practical guidance for improving grape features.
Integrated analyses of miRNAome and transcriptome reveal zinc deficiency responses in rice seedlings
Authors: Zeng Houqing , Zhang Xin , Ding Ming , Zhu Yiyong 
Published: December 2019

Abstract
Background
Zinc (Zn) deficiency is one of the most widespread soil constraints affecting rice productivity, but the molecular mechanisms underlying the regulation of Zn deficiency response is still limited. Here, we aim to understand the molecular mechanisms of Zn deficiency response by integrating the analyses of the global miRNA and mRNA expression profiles under Zn deficiency and resupply in rice seedlings by integrating Illumina’s high-throughput small RNA sequencing and transcriptome sequencing.

Results
The transcriptome sequencing identified 360 genes that were differentially expressed in the shoots and roots of Zn-deficient rice seedlings, and 97 of them were recovered after Zn resupply. A total of 68 miRNAs were identified to be differentially expressed under Zn deficiency and/or Zn resupply. The integrated analyses of miRNAome and transcriptome data showed that 12 differentially expressed genes are the potential target genes of 10 Zn-responsive miRNAs such as miR171g-5p, miR397b-5p, miR398a-5p and miR528-5p. Some miRNA genes and differentially expressed genes were selected for validation by quantitative RT-PCR, and their expressions were similar to that of the sequencing results.

Conclusion
These results provide insights into miRNA-mediated regulatory pathways in Zn deficiency response, and provide candidate genes for genetic improvement of Zn deficiency tolerance in rice.
Transcriptome analysis of Pueraria candollei var. mirifica for gene discovery in the biosyntheses of isoflavones and miroestrol
Authors: Suntichaikamolkul Nithiwat , Tantisuwanichkul Kittitya , Prombutara Pinidphon , Kobtrakul Khwanlada , Zumsteg Julie , Wannachart Siriporn , Schaller Hubert , Yamazaki Mami , Saito Kazuki , De-eknamkul Wanchai , Vimolmangkang Sornkanok , Sirikantaramas Supaart 
Published: December 2019

Abstract
Background
Pueraria candollei var. mirifica, a Thai medicinal plant used traditionally as a rejuvenating herb, is known as a rich source of phytoestrogens, including isoflavonoids and the highly estrogenic miroestrol and deoxymiroestrol. Although these active constituents in P. candollei var. mirifica have been known for some time, actual knowledge regarding their biosynthetic genes remains unknown.

Results
Miroestrol biosynthesis was reconsidered and the most plausible mechanism starting from the isoflavonoid daidzein was proposed. A de novo transcriptome analysis was conducted using combined P. candollei var. mirifica tissues of young leaves, mature leaves, tuberous cortices, and cortex-excised tubers. A total of 166,923 contigs was assembled for functional annotation using protein databases and as a library for identification of genes that are potentially involved in the biosynthesis of isoflavonoids and miroestrol. Twenty-one differentially expressed genes from four separate libraries were identified as candidates involved in these biosynthetic pathways, and their respective expressions were validated by quantitative real-time reverse transcription polymerase chain reaction. Notably, isoflavonoid and miroestrol profiling generated by LC-MS/MS was positively correlated with expression levels of isoflavonoid biosynthetic genes across the four types of tissues. Moreover, we identified R2R3 MYB transcription factors that may be involved in the regulation of isoflavonoid biosynthesis in P. candollei var. mirifica. To confirm the function of a key-isoflavone biosynthetic gene, P. candollei var. mirifica isoflavone synthase identified in our library was transiently co-expressed with an Arabidopsis MYB12 transcription factor (AtMYB12) in Nicotiana benthamiana leaves. Remarkably, the combined expression of these proteins led to the production of the isoflavone genistein.

Conclusions
Our results provide compelling evidence regarding the integration of transcriptome and metabolome as a powerful tool for identifying biosynthetic genes and transcription factors possibly involved in the isoflavonoid and miroestrol biosyntheses in P. candollei var. mirifica.
A case presentation of patient from northern China with endomyocardial fibrosis
Authors: Yuan Yonggang , Li Yingkai , Xu Zesheng 
Published: December 2019

Abstract
Background
Endomyocardial fibrosis (EMF) is a rare condition and a major cause of death in tropical countries. The etiology of EMF remains elusive, and no specific treatment has been developed yet, therefore it carries poor prognosis.

Case presentation
An 81-year-old male Chinese patient with a history of long-standing exertional breathlessness, presented with worsening symptoms rapidly evolving to orthopnea. A proper specific treatment was prescribed to the patient in the following days, including diuretics, angiotensin-converting-enzyme inhibitor and beta blockers. The patient died of progressive multiple organ failure.

Conclusion
Echocardiography is technically limited due to the acoustic shadowing as a result of the calcification. Chest computed tomography is a more accurate diagnostic tool to examine the anatomic distribution and extent of endomyocardial calcification in this rare case.