AMBER: Assessment of Metagenome BinnERs

Meyer F, Hofmann P, Belmann P, et al. AMBER: Assessment of Metagenome BinnERs. GigaScience. 2018;7(6): giy069

Predicting tissue specific cis-regulatory modules in the human genome using pairs of co-occurring motifs

<p>Abstract</p> <p>Background</p> <p>Researchers seeking to unlock the genetic basis of human physiology and diseases have been studying gene transcription regulation. The temporal and spatial patterns of gene expression are controlled by mainly non-coding elements known as cis-regulatory modules (CRMs) and epigenetic factors. CRMs modulating related genes share the regulatory signature which consists of transcription factor (TF) binding sites (TFBSs). Identifying such CRMs is a challenging problem due to the prohibitive number of sequence sets that need to be analyzed.</p> <p>Results</p> <p>We formulated the challenge as a supervised classification problem even though experimentally validated CRMs were not required. Our efforts resulted in a software system named CrmMiner. The system mines for CRMs in the vicinity of related genes. CrmMiner requires two sets of sequences: a mixed set and a control set. Sequences in the vicinity of the related genes comprise the mixed set, whereas the control set includes random genomic sequences. CrmMiner assumes that a large percentage of the mixed set is made of background sequences that do not include CRMs. The system identifies pairs of closely located motifs representing vertebrate TFBSs that are enriched in the training mixed set consisting of 50% of the gene loci. In addition, CrmMiner selects a group of the enriched pairs to represent the tissue-specific regulatory signature. The mixed and the control sets are searched for candidate sequences that include any of the selected pairs. Next, an optimal Bayesian classifier is used to distinguish candidates found in the mixed set from their control counterparts. Our study proposes 62 tissue-specific regulatory signatures and putative CRMs for different human tissues and cell types. These signatures consist of assortments of ubiquitously expressed TFs and tissue-specific TFs. Under controlled settings, CrmMiner identified known CRMs in noisy sets up to 1:25 signal-to-noise ratio. CrmMiner was 21-75% more precise than a related CRM predictor. The sensitivity of the system to locate known human heart enhancers reached up to 83%. CrmMiner precision reached 82% while mining for CRMs specific to the human CD4⁺T cells. On several data sets, the system achieved 99% specificity.</p> <p>Conclusion</p> <p>These results suggest that CrmMiner predictions are accurate and likely to be tissue-specific CRMs. We expect that the predicted tissue-specific CRMs and the regulatory signatures broaden our knowledge of gene transcription regulation.</p

Anthropometric measurements and dental caries in children: A systematic review of longitudinal studies

There is growing interest in the association between anthropometric measurements and dental caries in childhood over time (life-course studies). The aim of this review was to identify and systematically review the evidence of the association between anthropometric measurements and dental caries in childhood over time. PubMed, Institute for Scientific Information (ISI) Web of Knowledge, the Cochrane Library, and 6 other databases were searched to identify effective articles. A systematic approach involving critical appraisal was conducted to examine the relation between anthropometric measurements and dental caries in preschool- and school-aged populations from longitudinal studies. An initial search identified 1338 studies, with 59 potentially effective studies (κ = 0.82) and 17 effective studies (κ = 0.88). The quality of reporting among the studies ranged from 19.5 to 30.0 according to the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) criteria. Among the effective studies, 2 studies in which caries was used to predict anthropometric measurements consistently found an inverse association and 15 studies in which anthropometric measurements were used to predict caries were inconsistent, with results appearing to be influenced by nonuniformity of assessments, setting, and procedure of measurements; age and ethnicity of participants; and confounders of dental caries. In conclusion, among >1000 studies identified, 17 informed this systematic review. The quality of reporting of these studies varied considerably. Evidence of the association between anthropometric measurements and dental caries is conflicting and remains inconclusive