BGLM: big data-guided LOINC mapping with multi-language support.

Motivation: Mapping internal, locally used lab test codes to standardized logical observation identifiers names and codes (LOINC) terminology has become an essential step in harmonizing electronic health record (EHR) data across different institutions. However, most existing LOINC code mappers are based on text-mining technology and do not provide robust multi-language support. Materials and methods: We introduce a simple, yet effective tool called big data-guided LOINC code mapper (BGLM), which leverages the large amount of patient data stored in EHR systems to perform LOINC coding mapping. Distinguishing from existing methods, BGLM conducts mapping based on distributional similarity. Results: We validated the performance of BGLM with real-world datasets and showed that high mapping precision could be achieved under proper false discovery rate control. In addition, we showed that the mapping results of BGLM could be used to boost the performance of Regenstrief LOINC Mapping Assistant (RELMA), one of the most widely used LOINC code mappers. Conclusions: BGLM paves a new way for LOINC code mapping and therefore could be applied to EHR systems without the restriction of languages. BGLM is freely available at https://github.com/Bin-Chen-Lab/BGLM.

Recent selection of candidate genes for mammal domestication in Europeans and language change in Europe: a hypothesis.

BACKGROUND AND AIM: Human evolution resulted from changes in our biology, behaviour, and culture. One source of these changes has been hypothesised to be our self-domestication (that is, the development in humans of features commonly found in domesticated strains of mammals, seemingly as a result of selection for reduced aggression). Signals of domestication, notably brain size reduction, have increased in recent times. METHODS: In this paper, we compare whole-genome data between the Late Neolithic/Bronze Age individuals and modern Europeans. RESULTS: We show that genes associated with mammal domestication and with neural crest development and function are significantly differently enriched in nonsynonymous single nucleotide polymorphisms between these two groups. CONCLUSION: We hypothesise that these changes might account for the increased features of self-domestication in modern humans and, ultimately, for subtle recent changes in human cognition and behaviour, including language.

OCTAD: an open workspace for virtually screening therapeutics targeting precise cancer patient groups using gene expression features.

As the field of precision medicine progresses, treatments for patients with cancer are starting to be tailored to their molecular as well as their clinical features. The emerging cancer subtypes defined by these molecular features require that dedicated resources be used to assist the discovery of drug candidates for preclinical evaluation. Voluminous gene expression profiles of patients with cancer have been accumulated in public databases, enabling the creation of cancer-specific expression signatures. Meanwhile, large-scale gene expression profiles of cellular responses to chemical compounds have also recently became available. By matching the cancer-specific expression signature to compound-induced gene expression profiles from large drug libraries, researchers can prioritize small molecules that present high potency to reverse expression of signature genes for further experimental testing of their efficacy. This approach has proven to be an efficient and cost-effective way to identify efficacious drug candidates. However, the success of this approach requires multiscale procedures, imposing considerable challenges to many labs. To address this, we developed Open Cancer TherApeutic Discovery (OCTAD; http://octad.org ): an open workspace for virtually screening compounds targeting precise groups of patients with cancer using gene expression features. Its database includes 19,127 patient tissue samples covering more than 50 cancer types and expression profiles for 12,442 distinct compounds. The program is used to perform deep-learning-based reference tissue selection, disease gene expression signature creation, drug reversal potency scoring and in silico validation. OCTAD is available as a web portal and a standalone R package to allow experimental and computational scientists to easily navigate the tool.

Positive Selection in Bifidobacterium Genes Drives Species-Specific Host-Bacteria Communication.

Bifidobacteria are commensal microorganisms that inhabit a wide range of hosts, including insects, birds and mammals. The mechanisms responsible for the adaptation of bifidobacteria to various hosts during the evolutionary process remain poorly understood. Previously, we reported that the species-specific PFNA gene cluster is present in the genomes of various species of the Bifidobacterium genus. The cluster contains signal transduction and adhesion genes that are presumably involved in the communication between bifidobacteria and their hosts. The genes in the PFNA cluster show high sequence divergence between bifidobacterial species, which may be indicative of rapid evolution that drives species-specific adaptation to the host organism. We used the maximum likelihood approach to detect positive selection in the PFNA genes. We tested for both pervasive and episodic positive selection to identify codons that experienced adaptive evolution in all and individual branches of the Bifidobacterium phylogenetic tree, respectively. Our results provide evidence that episodic positive selection has played an important role in the divergence process and molecular evolution of sequences of the species-specific PFNA genes in most bifidobacterial species. Moreover, we found the signatures of pervasive positive selection in the molecular evolution of the tgm gene in all branches of the Bifidobacterium phylogenetic tree. These results are consistent with the suggested role of PFNA gene cluster in the process of specific adaptation of bifidobacterial species to various hosts.

Changes in Biological Pathways During 6,000 Years of Civilization in Europe.

The beginning of civilization was a turning point in human evolution. With increasing separation from the natural environment, mankind stimulated new adaptive reactions in response to new environmental factors. In this paper, we describe direct signs of these reactions in the European population during the past 6,000 years. By comparing whole-genome data between Late Neolithic/Bronze Age individuals and modern Europeans, we revealed biological pathways that are significantly differently enriched in nonsynonymous single nucleotide polymorphisms in these two groups and which therefore could be shaped by cultural practices during the past six millennia. They include metabolic transformations, immune response, signal transduction, physical activity, sensory perception, reproduction, and cognitive functions. We demonstrated that these processes were influenced by different types of natural selection. We believe that our study opens new perspectives for more detailed investigations about when and how civilization has been modifying human genomes.

FRA1 mediates the activation of keratinocytes: Implications for the development of psoriatic plaques.

In this study we investigated the role of FRA1, a transcription factor from the AP-1 family, in the regulation of keratinocyte characteristics important for the development of psoriatic plaques. FRA1 is characterized by elevated expression in the skin of psoriasis patients, thus leading us to predict it to be one of the major regulators of keratinocyte phenotype during the development of psoriatic lesions. Pathway analysis of RNAseq data allowed us to identify FRA1-mediated signaling cascades leading to the manifestation of the most prominent skin characteristics of the disease: the development of inflammation, epithelial-mesenchymal transition, activation of metalloproteases, and keratinocyte proliferation and migration. We have confirmed that FRA1-overexpressing keratinocytes produce elevated amounts of proinflammatory cytokines and active matrix metalloproteases, leading to the induction of the autoinflammatory loop and paracrine activation in neighbor cells. Therefore, the elevated expression of FRA1 and its altered transcriptional regulation in the skin of patients with psoriasis is an important driving factor in the development of psoriatic plaques.

Identification of Transcriptional Regulators of Psoriasis from RNA-Seq Experiments.

Psoriasis is a common inflammatory skin disease with complex etiology and chronic progression. To provide novel insights into the molecular mechanisms of regulation of the disease we performed RNA sequencing (RNA-Seq) analysis of 14 pairs of skin samples collected from psoriatic patients. Subsequent pathway analysis and an extraction of transcriptional regulators governing psoriasis-associated pathways was executed using a combination of MetaCore Interactome enrichment tool and cisExpress algorithm, and followed by comparison to a set of previously described psoriasis response elements. A comparative approach has allowed us to identify 42 core transcriptional regulators of the disease associated with inflammation (NFkB, IRF9, JUN, FOS, SRF), activity of T-cells in the psoriatic lesions (STAT6, FOXP3, NFATC2, GATA3, TCF7, RUNX1, etc.), hyperproliferation and migration of keratinocytes (JUN, FOS, NFIB, TFAP2A, TFAP2C), and lipid metabolism (TFAP2, RARA, VDR). After merging the ChIP-seq and RNA-seq data, we conclude that the atypical expression of FOXA1 transcriptional factor is an important player in psoriasis, as it inhibits maturation of naive T cells into this Treg subpopulation (CD4+FOXA1+CD47+CD69+PD-L1(hi)FOXP3-), therefore contributing to the development of psoriatic skin lesions.

Integrated computational approach to the analysis of RNA-seq data reveals new transcriptional regulators of psoriasis.

Psoriasis is a common inflammatory skin disease with complex etiology and chronic progression. To provide novel insights into the regulatory molecular mechanisms of the disease, we performed RNA sequencing analysis of 14 pairs of skin samples collected from patients with psoriasis. Subsequent pathway analysis and extraction of the transcriptional regulators governing psoriasis-associated pathways was executed using a combination of the MetaCore Interactome enrichment tool and the cisExpress algorithm, followed by comparison to a set of previously described psoriasis response elements. A comparative approach allowed us to identify 42 core transcriptional regulators of the disease associated with inflammation (NFκB, IRF9, JUN, FOS, SRF), the activity of T cells in psoriatic lesions (STAT6, FOXP3, NFATC2, GATA3, TCF7, RUNX1), the hyperproliferation and migration of keratinocytes (JUN, FOS, NFIB, TFAP2A, TFAP2C) and lipid metabolism (TFAP2, RARA, VDR). In addition to the core regulators, we identified 38 transcription factors previously not associated with the disease that can clarify the pathogenesis of psoriasis. To illustrate these findings, we analyzed the regulatory role of one of the identified transcription factors (TFs), FOXA1. Using ChIP-seq and RNA-seq data, we concluded that the atypical expression of the FOXA1 TF is an important player in the disease as it inhibits the maturation of naive T cells into the (CD4+FOXA1+CD47+CD69+PD-L1(hi)FOXP3-) regulatory T cell subpopulation, therefore contributing to the development of psoriatic skin lesions.

Nucleotide diversity analysis highlights functionally important genomic regions.

We analyzed functionality and relative distribution of genetic variants across the complete Oryza sativa genome, using the 40 million single nucleotide polymorphisms (SNPs) dataset from the 3,000 Rice Genomes Project (http://snp-seek.irri.org), the largest and highest density SNP collection for any higher plant. We have shown that the DNA-binding transcription factors (TFs) are the most conserved group of genes, whereas kinases and membrane-localized transporters are the most variable ones. TFs may be conserved because they belong to some of the most connected regulatory hubs that modulate transcription of vast downstream gene networks, whereas signaling kinases and transporters need to adapt rapidly to changing environmental conditions. In general, the observed profound patterns of nucleotide variability reveal functionally important genomic regions. As expected, nucleotide diversity is much higher in intergenic regions than within gene bodies (regions spanning gene models), and protein-coding sequences are more conserved than untranslated gene regions. We have observed a sharp decline in nucleotide diversity that begins at about 250 nucleotides upstream of the transcription start and reaches minimal diversity exactly at the transcription start. We found the transcription termination sites to have remarkably symmetrical patterns of SNP density, implying presence of functional sites near transcription termination. Also, nucleotide diversity was significantly lower near 3' UTRs, the area rich with regulatory regions.