Extensive Annotation Research Articles

Reptilian Transcriptomes v2.0: An Extensive Resource for Sauropsida Genomics and Transcriptomics.

Despite the availability of deep-sequencing techniques, genomic and transcriptomic data remain unevenly distributed across phylogenetic groups. For example, reptiles are poorly represented in sequence databases, hindering functional evolutionary and developmental studies in these lineages substantially more diverse than mammals. In addition, different studies use different assembly and annotation protocols, inhibiting meaningful comparisons. Here, we present the “Reptilian Transcriptomes Database 2.0,” which provides extensive annotation of transcriptomes and genomes from species covering the major reptilian lineages. To this end, we sequenced normalized complementary DNA libraries of multiple adult tissues and various embryonic stages of the leopard gecko and the corn snake and gathered published reptilian sequence data sets from representatives of the four extant orders of reptiles: Squamata (snakes and lizards), the tuatara, crocodiles, and turtles. The LANE runner 2.0 software was implemented to annotate all assemblies within a single integrated pipeline. We show that this approach increases the annotation completeness of the assembled transcriptomes/genomes. We then built large concatenated protein alignments of single-copy genes and inferred phylogenetic trees that support the positions of turtles and the tuatara as sister groups of Archosauria and Squamata, respectively. The Reptilian Transcriptomes Database 2.0 resource will be updated to include selected new data sets as they become available, thus making it a reference for differential expression studies, comparative genomics and transcriptomics, linkage mapping, molecular ecology, and phylogenomic analyses involving reptiles. The database is available at www.reptilian-transcriptomes.org and can be enquired using a wwwblast server installed at the University of Geneva.

Marine systems biology.

EDITORIAL article Front. Genet., 13 May 2015Sec. Systems Biology Archive Volume 6 - 2015 | https://doi.org/10.3389/fgene.2015.00181

Bad Latin, Bad Manners: Giovanni Battista Doni, Marin Mersenne, and Literary Style in Seventeenth-Century Music Theory

An overlooked copy of Marin Mersenne’s Harmonicorum libri (1636) with extensive annotations by theorist Giovanni Battista Doni offers a glimpse of how early modern music scholars assessed each other’s work behind closed doors. Although Doni treated Mersenne courteously in more public settings, his private marginalia reveal an overwhelmingly negative assessment of Mersenne and his work. Doni bypassed matters of contemporary musical practice and instead criticized Mersenne’s Latin, his prose style, his manners, and his failure to meet (Doni’s) standards for humanistic scholarship. Doni’s preoccupation with literary style and his discretion in not airing his criticisms publicly illuminate the social and professional worlds where musical knowledge was generated. Doni showed good courtly taste in valuing eloquence as much as (or more than) technical precision, even in music-theoretical writing. Moreover, it would have been impolitic for a courtier such as Doni to reveal his full judgement of Mersenne in the greater Republic of Letters, where complex political and institutional networks intersected.

The Power of Gene-Based Rare Variant Methods to Detect Disease-Associated Variation and Test Hypotheses About Complex Disease

Genome and exome sequencing in large cohorts enables characterization of the role of rare variation in complex diseases. Success in this endeavor, however, requires investigators to test a diverse array of genetic hypotheses which differ in the number, frequency and effect sizes of underlying causal variants. In this study, we evaluated the power of gene-based association methods to interrogate such hypotheses, and examined the implications for study design. We developed a flexible simulation approach, using 1000 Genomes data, to (a) generate sequence variation at human genes in up to 10K case-control samples, and (b) quantify the statistical power of a panel of widely used gene-based association tests under a variety of allelic architectures, locus effect sizes, and significance thresholds. For loci explaining ~1% of phenotypic variance underlying a common dichotomous trait, we find that all methods have low absolute power to achieve exome-wide significance (~5-20% power at α=2.5×10-6) in 3K individuals; even in 10K samples, power is modest (~60%). The combined application of multiple methods increases sensitivity, but does so at the expense of a higher false positive rate. MiST, SKAT-O, and KBAC have the highest individual mean power across simulated datasets, but we observe wide architecture-dependent variability in the individual loci detected by each test, suggesting that inferences about disease architecture from analysis of sequencing studies can differ depending on which methods are used. Our results imply that tens of thousands of individuals, extensive functional annotation, or highly targeted hypothesis testing will be required to confidently detect or exclude rare variant signals at complex disease loci.

Genome-wide identification and characterization of MADS-box family genes related to organ development and stress resistance in Brassica rapa.

BackgroundMADS-box transcription factors (TFs) are important in floral organ specification as well as several other aspects of plant growth and development. Studies on stress resistance-related functions of MADS-box genes are very limited and no such functional studies in Brassica rapa have been reported. To gain insight into this gene family and to elucidate their roles in organ development and stress resistance, we performed genome-wide identification, characterization and expression analysis of MADS-box genes in B. rapa.ResultsWhole-genome survey of B. rapa revealed 167 MADS-box genes, which were categorized into type I (Mα, Mβ and Mγ) and type II (MIKCc and MIKC*) based on phylogeny, protein motif structure and exon-intron organization. Expression analysis of 89 MIKCc and 11 MIKC* genes was then carried out. In addition to those with floral and vegetative tissue expression, we identified MADS-box genes with constitutive expression patterns at different stages of flower development. More importantly, from a low temperature-treated whole-genome microarray data set, 19 BrMADS genes were found to show variable transcript abundance in two contrasting inbred lines of B. rapa. Among these, 13 BrMADS genes were further validated and their differential expression was monitored in response to cold stress in the same two lines via qPCR expression analysis. Additionally, the set of 19 BrMADS genes was analyzed under drought and salt stress, and 8 and 6 genes were found to be induced by drought and salt, respectively.ConclusionThe extensive annotation and transcriptome profiling reported in this study will be useful for understanding the involvement of MADS-box genes in stress resistance in addition to their growth and developmental functions, which ultimately provides the basis for functional characterization and exploitation of the candidate genes for genetic engineering of B. rapa.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1349-z) contains supplementary material, which is available to authorized users.

Splicing landscape of the eight collaborative cross founder strains.

BackgroundThe Collaborative Cross (CC) is a large panel of genetically diverse recombinant inbred mouse strains specifically designed to provide a systems genetics resource for the study of complex traits. In part, the utility of the CC stems from the extensive genome-wide annotations of founder strain sequence and structural variation. Still missing, however, are transcriptome-specific annotations of the CC founder strains that could further enhance the utility of this resource.ResultsWe provide a comprehensive survey of the splicing landscape of the 8 CC founder strains by leveraging the high level of alternative splicing within the brain. Using deep transcriptome sequencing, we found that a majority of the splicing landscape is conserved among the 8 strains, with ~65% of junctions being shared by at least 2 strains. We, however, found a large number of potential strain-specific splicing events as well, with an average of ~3000 and ~500 with ≥3 and ≥10 sequence read coverage, respectively, within each strain. To better understand strain-specific splicing within the CC founder strains, we defined criteria for and identified high-confidence strain-specific splicing events. These splicing events were defined as exon-exon junctions 1) found within only one strain, 2) with a read coverage ≥10, and 3) defined by a canonical splice site. With these criteria, a total of 1509 high-confidence strain-specific splicing events were identified, with the majority found within two of the wild-derived strains, CAST and PWK. Strikingly, the overwhelming majority, 94%, of these strain-specific splicing events are not yet annotated. Strain-specific splicing was also located within genomic regions recently reported to be over- and under-represented within CC populations.ConclusionsPhenotypic characterization of CC populations is increasing; thus these results will not only aid in further elucidating the transcriptomic architecture of the individual CC founder strains, but they will also help in guiding the utilization of the CC populations in the study of complex traits. This report is also the first to establish guidelines in defining and identifying strain-specific splicing across different mouse strains.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1267-0) contains supplementary material, which is available to authorized users.

Localization and abundance analysis of human lncRNAs at single-cell and single-molecule resolution.

BackgroundLong non-coding RNAs (lncRNAs) have been implicated in diverse biological processes. In contrast to extensive genomic annotation of lncRNA transcripts, far fewer have been characterized for subcellular localization and cell-to-cell variability. Addressing this requires systematic, direct visualization of lncRNAs in single cells at single-molecule resolution.ResultsWe use single-molecule RNA-FISH to systematically quantify and categorize the subcellular localization patterns of a representative set of 61 lncRNAs in three different cell types. Our survey yields high-resolution quantification and stringent validation of the number and spatial positions of these lncRNA, with an mRNA set for comparison. Using this highly quantitative image-based dataset, we observe a variety of subcellular localization patterns, ranging from bright sub-nuclear foci to almost exclusively cytoplasmic localization. We also find that the low abundance of lncRNAs observed from cell population measurements cannot be explained by high expression in a small subset of ‘jackpot’ cells. Additionally, nuclear lncRNA foci dissolve during mitosis and become widely dispersed, suggesting these lncRNAs are not mitotic bookmarking factors. Moreover, we see that divergently transcribed lncRNAs do not always correlate with their cognate mRNA, nor do they have a characteristic localization pattern.ConclusionsOur systematic, high-resolution survey of lncRNA localization reveals aspects of lncRNAs that are similar to mRNAs, such as cell-to-cell variability, but also several distinct properties. These characteristics may correspond to particular functional roles. Our study also provides a quantitative description of lncRNAs at the single-cell level and a universally applicable framework for future study and validation of lncRNAs.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0586-4) contains supplementary material, which is available to authorized users.

Spanish change of state verbs in composition with atypical theme arguments: Clarifying the meaning shifts

For many instances of verb-object combinations involving change of state verbs, different kinds of internal arguments seem to trigger distinct interpretations of the verb phrase. These are usually divided into literal uses, such as romper la ventana ‘break the window’ or cortar el papel ‘cut the paper’ and figurative uses such as romper el desarrollo ‘interrupt the development’ or cortar la circulación ‘cut off the circulation’.Based on an extensive manual annotation of corpus (the used corpus is the El País Corpus consisting of all the El País newspaper issues from 1976 to 2007 and is hosted at the Insitut Universitari de Linguistica Aplicada (IULA) at the University Pompeu Fabra) data involving verb-object combinations with Spanish change of state verbs, I argue that combinations like romper el desarrollo or cortar la circulación, far from representing frozen idiom chunks, exemplify very productive compositional patterns. The frequency and naturalness with which change of state verbs take both physical and abstract entities as objects raises the question of how verbs express their meaning and makes this kind of data especially relevant for a theory of the lexicon as well as of composition.I provide a clear inventory of the typical combinatorial patterns of romper and cortar and I show that their combinatorial behaviour is much more diverse than usually acknowledged. I then argue that these facts need to be addressed by the compositional system, rather than by postulating homophonic lexical entires (Dowty, 1979; Alonso Ramos, 2011) or contextualist accounts (Recanati, 2005).For a proposal I turn to Modern Type Theories, which allow me to incorporate a richer notion of lexical semantics within compositional semantics. These theories thus allow me provide an insightful compositional account of what has long been considered non-compositional, namely combinations of change of state verbs with objects denoting abstract entities.

A New Approach to Identify Pathogenic Mutations and Inherited Variants By Exome Sequencing – Using a Pair of Identical Twins with Monoclonal Lymphosis As Case Model

Genome-wide association studies (GWAS) have identified common susceptibility loci in developing chronic lymphocytic leukemia (CLL). As the price on whole exome and genome sequencing continues to drop, large sequencing studies become more feasible and will change our understanding of the biological fundament of malignancy - and of the premalignant state of monoclonal lymphocytosis toward leukemic status. However, CLL is heterogeneous and, while co-inheritance of multiple low-risk variants govern predisposition, GWAS cannot yet be expected to contribute sufficiently in delineating individual molecular drivers. There is a need to be able to determine likely drivers in single patients, while GWAS continue to add information to draw from. We hypothesized that with the right tool much information can be extracted from the patient specific analysis - with direct implications in the clinic. The production cost is already within range of other lab analyses, but the interpretative work is still in its infancy in the clinical settings.AIM: We set out to engineer a method to automatically rank and annotate whole exome data efficiently, pointing to most likely contributing variants in the development of MBL and CLL - with direct practical implications for the clinic and research.METHODS: As testing ground and model for the tool we analysed a pair of identical twins in whom one had developed B-CLL and the other monoclonal lymphocytosis (notably with different clonal usage of light chains). In this setting extensive variant and mutation annotation, filtering, analysis and ranking were carried out through variant calling and MuTect output post-processing tool written in the versatile Wolfram programming language (Mathematica 9, Wolfram Research, Oxfordshire, UK) tied to external data sources (Fig. 1). Variants are automatically evaluated and ranked on the basis of 1) allele frequency, predicted damage, non-synonymous change (e.g. charge or polarity change), affected region or predicted size of frameshift, 2) functional annotation of gene and 3) automated literature search and gene-disease association. 4) Querying COSMIC database determines calculated mutational frequency (normalized to size) of the affected gene in human cancers and whether the gene is known to be involved in oncogenesis. 5) Finally, graphical representation of expected expression is provided to assist interpretation.RESULTS: Rare inherited variants in the B-Cell Receptor and Wnt/beta-catenin Signaling Pathway and tumor suppressors were found in the germline set (Fig. 1). These results also showed IRF8 mutation, recently linked to CLL susceptibility loci, and a reported susceptibility loci (rs17246404). Twin A could be distinguished from B by a series of high-ranked mutations with myeloid association (RUNX1, TET2, PLCB1 and ELF4 etc, fig. 1C), a nonsense mutation affecting MAP2K3 and a frameshifting indel in CHST15 - a gene suggested to act as a B-cell receptor important for B-cell development. Also, a missense mutation with altered charge in the helicase domain of CLL-associated CHD2 was found. Twin B was found to have a different set of relevant mutations that may also be drivers in inducing a proliferative disorder (e.g. ABL2 SH2 domain, MYH1 motor domain, TNFAIP6 CUB domain, NOTCH4 EGF-like calcium-binding domain). Twin B, although following a benign course, had an overall higher number of mutations was backed by affected genes involved in DNA repair response (TOPBP1 and DNMT1). Also a key feature was chromatin, histone and DNA modifiers (CHD7, SETD1B and likewise DNMT1).DISCUSSION: The use of a new set of scripts allowed for the easy interpretation of variants in these twins, in whom it can be surmised that master genes underlying the B-cell proliferation in B-CLL can be found. We suggest that this analysis method can be used for individual assessment in close collaboration or directly by the clinician. As example, primary refractoriness to chemotherapy is an evident problem, but much data is already at hand to evaluate potential problematic variants. In our case doxorubicin and imatinib influx transporters were reported as possibly affected. There is a need for constructing analysis methods that assist the clinician in evaluating the disease on a genomic level. Hopefully, this kind of approach will make similar ventures in the single patient a clinical reality within a short span of time - benefitting patient and clinics. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

SNiPA: an interactive, genetic variant-centered annotation browser.

Motivation: Linking genes and functional information to genetic variants identified by association studies remains difficult. Resources containing extensive genomic annotations are available but often not fully utilized due to heterogeneous data formats. To enhance their accessibility, we integrated many annotation datasets into a user-friendly webserver.Availability and implementation: http://www.snipa.org/Contact: g.kastenmueller@helmholtz-muenchen.deSupplementary information: Supplementary data are available at Bioinformatics online.

SMART: recent updates, new developments and status in 2015.

SMART (Simple Modular Architecture Research Tool) is a web resource (http://smart.embl.de/) providing simple identification and extensive annotation of protein domains and the exploration of protein domain architectures. In the current version, SMART contains manually curated models for more than 1200 protein domains, with ∼200 new models since our last update article. The underlying protein databases were synchronized with UniProt, Ensembl and STRING, bringing the total number of annotated domains and other protein features above 100 million. SMART's ‘Genomic’ mode, which annotates proteins from completely sequenced genomes was greatly expanded and now includes 2031 species, compared to 1133 in the previous release. SMART analysis results pages have been completely redesigned and include links to several new information sources. A new, vector-based display engine has been developed for protein schematics in SMART, which can also be exported as high-resolution bitmap images for easy inclusion into other documents. Taxonomic tree displays in SMART have been significantly improved, and can be easily navigated using the integrated search engine.

Abstract 367: Tumorigenesis: an investigation by network evolution and perturbations of somatic mutations in cancer interactome

Abstract Cells govern biological actions through highly complex biological networks. Perturbations to the complex molecular network due to driver mutations may transit cells to new phenotypic states, e.g., tumorigenesis. Identifying how genetic lesions such as somatic mutations perturb these networks is a fundamental challenge in cancer biology. The recent TCGA studies revealed that a typical tumor contains two to as many as eight of driver mutations while the numerous remaining somatic mutations are passenger mutations. So far, it remains largely unknown what evolutionary forces and how the genetic lesions disrupt cancer interactome that leads to tumorigenesis. In this study, we systematically investigated the relationship among the network topology, evolutionary rates, and evolutionary origins of somatic and germline mutation driven disease genes in the large context of the protein-protein interaction (PPI) networks by utilizing recently released extensive somatic mutations and gene annotation data. We aimed to address two fundamental questions. (1) Whether cancer genes display a distinct network topology from Mendelian disease genes, and why? (2) From a network biology perspective, how the transition occurs from a normal cell to a tumor cell as initiated by a few driver genetic mutations? We collected the largest ever cancer gene list and five comprehensive networks. We found evolutionary origin is the main determinant of the unique network centrality of cancer proteins. We further investigated the perturbations of network topology by somatic mutations that were identified from 3268 tumors across 12 cancer types in TCGA. We revealed that the network-attacking perturbation of somatic mutations on central hubs of cancer interactome is a main feature of tumor emergence and evolution. This finding elucidates the high efficiency of the transition during tumorigenesis as initiated by a few driver mutations. This work improves our understanding of dynamic network-attacking perturbation by somatic mutations during tumorigenesis, and, in turn, of the implications for both basic cancer biology and the development of personalized antitumor therapy. Citation Format: Feixiong Cheng, Peilin Jia, Quan Wang, Chen-Ching Lin, Zhongming Zhao. Tumorigenesis: an investigation by network evolution and perturbations of somatic mutations in cancer interactome. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 367. doi:10.1158/1538-7445.AM2014-367

Evaluation of stromal HGF immunoreactivity as a biomarker for melanoma response to RAF inhibitors

Of more than 150 000 published studies evaluating new biomarkers, fewer than 100 biomarkers have been implemented for patient care. One reason for this is lack of rigorous testing by the medical community to validate claims for biomarker clinical relevance, and potential reluctance to publish negative results when confirmation is not obtained. Here we sought to determine the utility and reproducibility of immunohistochemical detection of hepatocyte growth factor (HGF) in melanoma tissue, an approach of potential assistance in defining patients with innate resistance to BRAF inhibitor therapy. To this end, a published and a revised method that retained sensitivity but with greater specificity for HGF detection, were evaluated in cells known to endogenously express HGF, and in models where HGF is upregulated via cytokine induction and via overexpression by gene transfection. Consequent patient evaluation in collaboration with the Melanoma Institute Australia of a cohort of 41 melanoma specimens with extensive clinical annotation failed to validate HGF immunohistochemistry as a predictor of response to BRAF inhibitors. Targeted therapies for advanced melanoma and other cancers show great promise, and rigorous validation studies are thus indicated for approaches that seek to personalize such therapies to maximize therapeutic efficacy.

STATdb: a specialised resource for the STATome.

Signal transducers and activators of transcription (STAT) proteins are key signalling molecules in metazoans, implicated in various cellular processes. Increased research in the field has resulted in the accumulation of STAT sequence and structure data, which are scattered across various public databases, missing extensive functional annotations, and prone to effort redundancy because of the dearth of community sharing. Therefore, there is a need to integrate the existing sequence, structure and functional data into a central repository, one that is enriched with annotations and provides a platform for community contributions. Herein, we present STATdb (publicly available at http://statdb.bic.nus.edu.sg/), the first integrated resource for STAT sequences comprising 1540 records representing the known STATome, enriched with existing structural and functional information from various databases and literature and including manual annotations. STATdb provides advanced features for data visualization, analysis and prediction, and community contributions. A key feature is a meta-predictor to characterise STAT sequences based on a novel classification that integrates STAT domain architecture, lineage and function. A curation policy workflow has been devised for regulated and structured community contributions, with an update policy for the seamless integration of new data and annotations.

Draft genome sequence of Rhodomicrobium udaipurense JA643T with special reference to hopanoid biosynthesis.

Hopanoids are present in vast amounts as integral components of bacteria and plants with their primary function to strengthen rigidity of the plasma membrane. To establish their roles more precisely, we conducted sequencing of the whole genome of Rhodomicrobium udaipurense JA643T isolated from a fresh water stream of Udaipur in Himachal Pradesh, India, by using the Illumina HiSeq pair end chemistry of 2 × 100 bp platform. Determined genome showed a high degree of similarity to the genome of R. vannielii ATCC17100T and the 13.7 million reads generated a sequence of 3,649,277 bp possessing 3,611 putative genes. The genomic data were subsequently investigated with respect to genes involved in various features. The machinery required for the degradation of aromatic compounds and resistance to solvents as well as all that required for photosynthesis are present in this organism. Also, through extensive functional annotation, 18 genes involved in the biosynthesis of hopanoids are predicted, namely those responsible for the synthesis of diploptene, diplopterol, adenosylhopane, ribosylhopane, aminobacteriohopanetriol, glycosyl group containing hopanoids and unsaturated hopanoids. The hopanoid biosynthetic pathway was then inferred based on the genes identified and through experimental validation of individual hopanoid molecules. The genome data of R. udaipurense JA643T will be useful in understanding the functional features of hopanoids in this bacterium.

'RetinoGenetics': a comprehensive mutation database for genes related to inherited retinal degeneration.

Inherited retinal degeneration (IRD), a leading cause of human blindness worldwide, is exceptionally heterogeneous with clinical heterogeneity and genetic variety. During the past decades, tremendous efforts have been made to explore the complex heterogeneity, and massive mutations have been identified in different genes underlying IRD with the significant advancement of sequencing technology. In this study, we developed a comprehensive database, ‘RetinoGenetics’, which contains informative knowledge about all known IRD-related genes and mutations for IRD. ‘RetinoGenetics’ currently contains 4270 mutations in 186 genes, with detailed information associated with 164 phenotypes from 934 publications and various types of functional annotations. Then extensive annotations were performed to each gene using various resources, including Gene Ontology, KEGG pathways, protein–protein interaction, mutational annotations and gene–disease network. Furthermore, by using the search functions, convenient browsing ways and intuitive graphical displays, ‘RetinoGenetics’ could serve as a valuable resource for unveiling the genetic basis of IRD. Taken together, ‘RetinoGenetics’ is an integrative, informative and updatable resource for IRD-related genetic predispositions.Database URL: http://www.retinogenetics.org/.

Genome-guided transcript assembly by integrative analysis of RNA sequence data.

The identification of full length transcripts entirely from short-read RNA sequencing data (RNA-seq) remains a challenge in genome annotation pipelines. Here we describe an automated pipeline for genome annotation that integrates RNA-seq and gene-boundary data sets, which we call generalized RNA integration tool, or GRIT. By applying GRIT to Drosophila melanogaster short-read RNA-seq, cap analysis of gene expression (CAGE) and poly(A)-site-seq data collected for the modENCODE project, we recover the vast majority of previously annotated transcripts and double the total number of transcripts cataloged. We find that 20% of protein coding genes encode multiple protein-localization signals, and that, in 20 day old adult fly heads, genes with multiple poly-adenylation sites are more common than genes with alternate splicing or alternate promoters. When compared to the most widely used transcript assembly tools, GRIT recovers a larger fraction of annotated transcripts at higher precision. GRIT will enable the automated generation of high-quality genome annotations without necessitating extensive manual annotation.

Emplacement Algorithm for Extensive Geographical Annotation Based on Voronoi K-Order Adjacency

In terms of the issue of the geographical annotation estimation on the condition of network map service environment, the content of traditional geographic annotation with the unstructured text formation is extended in this paper; meanwhile an extensive geographic annotation is defined. The emplacement process is applied to model the geographic annotation behavior. First and foremost, according to the frequency class, need confirm the geographic annotation text classification need confirming and establishing a quantitative convergence description about the spatial self-correlation in the emplacement adjacency based on Voronoi k order vicinity relationship. Proceeding further, an emplacement algorithm for the types of geographical annotation and transformative type is built in combination with the geographic text annotation and the de facto geographical annotation neighborhood. Lastly, through empirical results, in the practical situation of two typological geographic annotation sets having been known already, emplacement algorithm can come to be effective appraisal about the newly augmented geographic annotation in a practicable way.

Evolutionary Interrogation of Human Biology in Well-Annotated Genomic Framework of Rhesus Macaque

With genome sequence and composition highly analogous to human, rhesus macaque represents a unique reference for evolutionary studies of human biology. Here, we developed a comprehensive genomic framework of rhesus macaque, the RhesusBase2, for evolutionary interrogation of human genes and the associated regulations. A total of 1,667 next-generation sequencing (NGS) data sets were processed, integrated, and evaluated, generating 51.2 million new functional annotation records. With extensive NGS annotations, RhesusBase2 refined the fine-scale structures in 30% of the macaque Ensembl transcripts, reporting an accurate, up-to-date set of macaque gene models. On the basis of these annotations and accurate macaque gene models, we further developed an NGS-oriented Molecular Evolution Gateway to access and visualize macaque annotations in reference to human orthologous genes and associated regulations (www.rhesusbase.org/molEvo). We highlighted the application of this well-annotated genomic framework in generating hypothetical link of human-biased regulations to human-specific traits, by using mechanistic characterization of the DIEXF gene as an example that provides novel clues to the understanding of digestive system reduction in human evolution. On a global scale, we also identified a catalog of 9,295 human-biased regulatory events, which may represent novel elements that have a substantial impact on shaping human transcriptome and possibly underpin recent human phenotypic evolution. Taken together, we provide an NGS data-driven, information-rich framework that will broadly benefit genomics research in general and serves as an important resource for in-depth evolutionary studies of human biology.

Human Transporter Database: Comprehensive Knowledge and Discovery Tools in the Human Transporter Genes

Transporters are essential in homeostatic exchange of endogenous and exogenous substances at the systematic, organic, cellular, and subcellular levels. Gene mutations of transporters are often related to pharmacogenetics traits. Recent developments in high throughput technologies on genomics, transcriptomics and proteomics allow in depth studies of transporter genes in normal cellular processes and diverse disease conditions. The flood of high throughput data have resulted in urgent need for an updated knowledgebase with curated, organized, and annotated human transporters in an easily accessible way. Using a pipeline with the combination of automated keywords query, sequence similarity search and manual curation on transporters, we collected 1,555 human non-redundant transporter genes to develop the Human Transporter Database (HTD) (http://htd.cbi.pku.edu.cn). Based on the extensive annotations, global properties of the transporter genes were illustrated, such as expression patterns and polymorphisms in relationships with their ligands. We noted that the human transporters were enriched in many fundamental biological processes such as oxidative phosphorylation and cardiac muscle contraction, and significantly associated with Mendelian and complex diseases such as epilepsy and sudden infant death syndrome. Overall, HTD provides a well-organized interface to facilitate research communities to search detailed molecular and genetic information of transporters for development of personalized medicine.