The combination of high-density transposon-mediated mutagenesis and high-throughput sequencing has led to significant advancements in research on essential genes, resulting in a dramatic increase in the number of identified prokaryotic essential genes under diverse conditions and a revised essential-gene concept that includes all essential genomic elements, rather than focusing on protein-coding genes only. DEG 10, a new release of the Database of Essential Genes (available at http://www.essentialgene.org), has been developed to accommodate these quantitative and qualitative advancements. In addition to increasing the number of bacterial and archaeal essential genes determined by genome-wide gene essentiality screens, DEG 10 also harbors essential noncoding RNAs, promoters, regulatory sequences and replication origins. These essential genomic elements are determined not only in vitro, but also in vivo, under diverse conditions including those for survival, pathogenesis and antibiotic resistance. We have developed customizable BLAST tools that allow users to perform species- and experiment-specific BLAST searches for a single gene, a list of genes, annotated or unannotated genomes. Therefore, DEG 10 includes essential genomic elements under different conditions in three domains of life, with customizable BLAST tools.

Chromosomal replication is the central event in the bacterial cell cycle. Identification of replication origins (oriC s) is necessary for almost all newly sequenced bacterial genomes. Given the increasing pace of genome sequencing, the current available software for predicting oriC s, however, still leaves much to be desired. Therefore, the increasing availability of genome sequences calls for improved software to identify oriC s in newly sequenced and unannotated bacterial genomes. We have developed Ori-Finder, an online system for finding oriC s in bacterial genomes based on an integrated method comprising the analysis of base composition asymmetry using the Z-curve method, distribution of DnaA boxes, and the occurrence of genes frequently close to oriC s. The program can also deal with unannotated genome sequences by integrating the gene-finding program ZCURVE 1.02. Output of the predicted results is exported to an HTML report, which offers convenient views on the results in both graphical and tabular formats. A web-based system to predict replication origins of bacterial genomes has been presented here. Based on this system, oriC regions have been predicted for the bacterial genomes available in GenBank currently. It is hoped that Ori-Finder will become a useful tool for the identification and analysis of oriC s in both bacterial and archaeal genomes.

Essential genes refer to genes that are required by an organism to survive under specific conditions. Studies of the minimal-gene-set for bacteria have elucidated fundamental cellular processes that sustain life. The past five years have seen a significant progress in identifying human essential genes, primarily due to the successful use of CRISPR/Cas9 in various types of human cells. DEG 15, a new release of the Database of Essential Genes (www.essentialgene.org), has provided major advancements, compared to DEG 10. Specifically, the number of eukaryotic essential genes has increased by more than fourfold, and that of prokaryotic ones has more than doubled. Of note, the human essential-gene number has increased by more than tenfold. Moreover, we have developed built-in analysis modules by which users can perform various analyses, such as essential-gene distributions between bacterial leading and lagging strands, sub-cellular localization distribution, enrichment analysis of gene ontology and KEGG pathways, and generation of Venn diagrams to compare and contrast gene sets between experiments. Additionally, the database offers customizable BLAST tools for performing species- and experiment-specific BLAST searches. Therefore, DEG comprehensively harbors updated human-curated essential-gene records among prokaryotes and eukaryotes with built-in tools to enhance essential-gene analysis.

INTRODUCTION: Design and construction of an extensively modified yeast genome is a direct means to interrogate the integrity, comprehensiveness, and accuracy of the knowledge amassed by the yeast community to date. The international synthetic yeast genome project (Sc2.0) aims to build an entirely designer, synthetic Saccharomyces cerevisiae genome. The synthetic genome is designed to increase genome stability and genetic flexibility while maintaining cell fitness near that of the wild type. A major challenge for a genome synthesis lies in identifying and eliminating fitness-reducing sequence variants referred to as “bugs.” RATIONALE: Debugging is imperative for successfully building a fit strain encoding a synthetic genome. However, it is time-consuming and laborious to replace wild-type genes and measure strain fitness systematically. The Sc2.0 PCRTag system, which specifies recoded sequences within open reading frames (ORFs), is designed to distinguish synthetic from wild-type DNA in a simple polymerase chain reaction (PCR) assay. This system provides an opportunity to efficiently map bugs to the related genes by using a pooling strategy and subsequently correct them. Further, as we identify bugs in designer sequences, we will identify gaps in our knowledge and gain a deeper understanding of genome biology, allowing refinement of future design strategies. RESULTS: We chemically synthesized yeast chromosome X, synX, designed to be 707,459 base pairs. A high-throughput mapping strategy called pooled PCRTag mapping (PoPM) was developed to identify unexpected bugs during chromosome assembly. With this method, the genotypes of pools of colonies with normal or defective fitness are assessed by PCRTag analysis. The PoPM method exploits the patchwork structure of synthetic and wild-type sequences observed in the majority of putative synthetic DNA integrants or meiotic progeny derived from synthetic/wild-type strain backcross. PCRTag analysis with both synthetic and wild-type specific primers, carried out with genomic DNA extracted from the two pools of clones (normal fitness versus a specific growth defect), can be used to identify regions of synthetic DNA missing from the normal fitness pool and, analogously, sections of wild-type DNA absent from the specific growth-defect pool. In this way, the defect can be efficiently mapped to a very small overlapping region, and subsequent systematic analysis of designed changes in that region can be used to identify the bug. Several bugs were identified and corrected, including a growth defect mapping to a specific synonymously recoded PCRTag sequence in the essential FIP1 ORF and the effect of introducing a loxPsym site that unexpectedly altered the the promoter function of a nearby gene, ATP2. In addition, meiotic crossover was employed to repair the massive duplications and rearrangements in the synthetic chromosome. The debugged synX strain exhibited high fitness under a variety of conditions tested and in competitive growth with the wild-type strain. CONCLUSION: Synthetic yeast chromosome X was chemically synthesized from scratch, a rigorous, incremental step toward complete synthesis of the whole yeast genome. Thousands of designer modifications in synX revealed extensive flexibility of the yeast genome. We developed an efficient mapping method, PoPM, to identify bugs during genome synthesis, generalizable to any watermarked synthetic chromosome, and several details of yeast biology were uncovered by debugging. Considering the numerous gene-associated PCRTags available in the synthetic chromosomes, PoPM may represent a powerful tool to map interesting phenotypes of mutated synthetic strains or even mutated wild-type strains to the relevant genes. It may also be useful to study yeast genetic interactions when an unexpected phenotype is generated by alterations in two or more genes, substantially expanding understanding of yeast genomic and cellular functions. The PoPM method is also likely to be useful for mapping phenotype(s) resulting from the genome SCRaMbLE system. Characterization of synX and debugging by pooled PCRTag mapping.: ( Top ) Design overview of synthetic chromosome X. ( Bottom ) Flow diagram of pooled PCRTag mapping (PoPM).

The National Genomics Data Center (NGDC) provides a suite of database resources to support worldwide research activities in both academia and industry. With the rapid advancements in higher-throughput and lower-cost sequencing technologies and accordingly the huge volume of multi-omics data generated at exponential scales and rates, NGDC is continually expanding, updating and enriching its core database resources through big data integration and value-added curation. In the past year, efforts for update have been mainly devoted to BioProject, BioSample, GSA, GWH, GVM, NONCODE, LncBook, EWAS Atlas and IC4R. Newly released resources include three human genome databases (PGG.SNV, PGG.Han and CGVD), eLMSG, EWAS Data Hub, GWAS Atlas, iSheep and PADS Arsenal. In addition, four web services, namely, eGPS Cloud, BIG Search, BIG Submission and BIG SSO, have been significantly improved and enhanced. All of these resources along with their services are publicly accessible at https://bigd.big.ac.cn.

In order to understand the evolution, structure and function of genomes, it is important to know the general compositional features of DNA sequences. Based on the quadratic divergence, a new segmentation algorithm to partition a given genome or DNA sequence into compositionally distinct domains has been put forward. With the aid of the technique of cumulative GC profile, the distribution of segmentation points can be displayed intuitively. We have therefore developed them into GC-Profile, an interactive web-based software system, which can be used to segment prokaryotic and eukaryotic genomes. GC-Profile provides a quantitative and qualitative view of genome organization. Based on the obtained results, the relationships between the G+C content and other genomic features, such as distributions of genes and CpG islands, can be analyzed in a perceivable manner. It shows that GC-Profile would be an appropriate starting point for analyzing the isochore structure of higher eukaryotic genomes, and an intuitive tool for identifying genomic islands in prokaryotic genomes. GC-Profile is freely available at the website http://tubic.tju.edu.cn/GC-Profile/ . In addition, precompiled binaries, together with examples and documentation, can also be freely downloaded for a local execution.