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The second ISCB-Asia conference of the International Society for Computational Biology took place December 17-19, 2012, in Shenzhen, China. The conference was co-hosted by BGI as the first Shenzhen Conference on Computational Genomics (SCCG). 45 talks were presented at ISCB-Asia/SCCG 2012. The topics covered included software tools, reproducible computing, next-generation sequencing data analysis, transcription and mRNA regulation, protein structure and function, cancer genomics and personalized medicine. Nine of the proceedings track talks are included as full papers in this supplement. In this report we first give a short overview of the conference by listing some statistics and visualizing the talk abstracts as word clouds. Then we group the talks by topic and briefly summarize each one, providing references to related publications whenever possible. Finally, we close with a few comments on the success of this conference [ABSTRACT FROM AUTHOR]

There is an ongoing process in which mitochondrial sequences are being integrated into the nuclear genome. The importance of these sequences has already been revealed in cancer biology, forensic, phylogenetic studies and in the evolution of the eukaryotic genetic information. Human and numerous model organisms' genomes were described from those sequences point of view. Furthermore, recent studies were published on the patterns of these nuclear localised mitochondrial sequences in different taxa. However, the results of the previously released studies are difficult to compare due to the lack of standardised methods and/or using few numbers of genomes. Therefore, in this paper our primary goal is to establish a uniform mining pipeline to explore these nuclear localised mitochondrial sequences. Our results show that the frequency of several repetitive elements is higher in the flanking regions of these sequences than expected. A machine learning model reveals that the flanking regions' repetitive elements and different structural characteristics are highly influential during the integration process. In this paper, we introduce a general mining pipeline for all mammalian genomes. The workflow is publicly available and is believed to serve as a validated baseline for future research in this field. We confirm the widespread opinion, on - as to our current knowledge - the largest dataset, that structural circumstances and events corresponding to repetitive elements are highly significant. An accurate model has also been trained to predict these sequences and their corresponding flanking regions. [ABSTRACT FROM AUTHOR]

Plant genomics plays a pivotal role in enhancing global food security and sustainability by offering innovative solutions for improving crop yield, disease resistance, and stress tolerance. As the number of sequenced genomes grows and the accuracy and contiguity of genome assemblies improve, structural annotation of plant genomes continues to be a significant challenge due to their large size, polyploidy, and rich repeat content. In this paper, we present an overview of the current landscape in crop genomics research, highlighting the diversity of genomic characteristics across various crop species. We also assessed the accuracy of popular gene prediction tools in identifying genes within crop genomes and examined the factors that impact their performance. Our findings highlight the strengths and limitations of BRAKER2 and Helixer as leading structural genome annotation tools and underscore the impact of genome complexity, fragmentation, and repeat content on their performance. Furthermore, we evaluated the suitability of the predicted proteins as a reliable search space in proteomics studies using mass spectrometry data. Our results provide valuable insights for future efforts to refine and advance the field of structural genome annotation. [ABSTRACT FROM AUTHOR]

Background: Anamika et al[1] recently published in this journal a sequence alignment analysis of protein kinases encoded by the chimpanzee genome in comparison to those in the human genome. From this analysis they concluded that several chimpanzee kinases have unusual domain arrangements. Results: Re-examination of these kinases reveals claimed novel arrangements cannot withstand scrutiny; each is either not novel or represents over-analysis of weakly confident computer generated gene models. Additional sequence evidence available at the time of the paper's submission either directly contradict the gene models or suggest alternate gene models. These alternate models would minimize or eliminate the observed differences between human and chimp kinases. Conclusion: None of the proposed novel chimpanzee kinase architectures are supported by experiment evidence. Guidelines to prevent such erroneous conclusions in similar papers are proposed. [ABSTRACT FROM AUTHOR]

The sixth International Conference on Intelligent Biology and Medicine (ICIBM) took place in Los Angeles, California, USA on June 10–12, 2018. This conference featured eleven regular scientific sessions, four tutorials, one poster session, four keynote talks, and four eminent scholar talks. The scientific program covered a wide range of topics from bench to bedside, including 3D Genome Organization, reconstruction of large scale evolution of genomes and gene functions, artificial intelligence in biological and biomedical fields, and precision medicine. Both method development and application in genomic research continued to be a main component in the conference, including studies on genetic variants, regulation of transcription, genetic-epigenetic interaction at both single cell and tissue level and artificial intelligence. Here, we write a summary of the conference and also briefly introduce the four high quality papers selected to be published in BMC Genomics that cover novel methodology development or innovative data analysis. [ABSTRACT FROM AUTHOR]

Background: Proteins are a kind of macromolecules and the main component of a cell, and thus it is the most essential and versatile material of life. The research of protein functions is of great significance in decoding the secret of life. In recent years, researchers have introduced multi-label supervised topic model such as Labeled Latent Dirichlet Allocation (Labeled-LDA) into protein function prediction, which can obtain more accurate and explanatory prediction. However, the topic-label corresponding way of Labeled-LDA is associating each label (GO term) with a corresponding topic directly, which makes the latent topics to be completely degenerated, and ignores the differences between labels and latent topics. Result: To achieve more accurate probabilistic modeling of function label, we propose a Partially Function-to-Topic Prediction (PFTP) model for introducing the local topics subset corresponding to each function label. Meanwhile, PFTP not only supports latent topics subset within a given function label but also a background topic corresponding to a 'fake' function label, which represents common semantic of protein function. Related definitions and the topic modeling process of PFTP are described in this paper. In a 5-fold cross validation experiment on yeast and human datasets, PFTP significantly outperforms five widely adopted methods for protein function prediction. Meanwhile, the impact of model parameters on prediction performance and the latent topics discovered by PFTP are also discussed in this paper. Conclusion: All of the experimental results provide evidence that PFTP is effective and have potential value for predicting protein function. Based on its ability of discovering more-refined latent sub-structure of function label, we can anticipate that PFTP is a potential method to reveal a deeper biological explanation for protein functions. [ABSTRACT FROM AUTHOR]

Background: Genome-wide association studies (GWAS) have identified many individual genes associated with brain imaging quantitative traits (QTs) in Alzheimer's disease (AD). However single marker level association discovery may not be able to address the underlying biological interactions with disease mechanism. Results: In this paper, we used the MGAS (Multivariate Gene-based Association test by extended Simes procedure) tool to perform multivariate GWAS on eight AD-relevant subcortical imaging measures. We conducted multiple iPINBPA (integrative Protein-Interaction-Network-Based Pathway Analysis) network analyses on MGAS findings using protein-protein interaction (PPI) data, and identified five Consensus Modules (CMs) from the PPI network. Functional annotation and network analysis were performed on the identified CMs. The MGAS yielded significant hits within APOE, TOMM40 and APOC1 genes, which were known AD risk factors, as well as a few new genes such as LAMA1, XYLB, HSD17B7P2, and NPEPL1. The identified five CMs were enriched by biological processes related to disorders such as Alzheimer's disease, Legionellosis, Pertussis, and Serotonergic synapse. Conclusions: The statistical power of coupling MGAS with iPINBPA was higher than traditional GWAS method, and yielded new findings that were missed by GWAS. This study provides novel insights into the molecular mechanism of Alzheimer's Disease and will be of value to novel gene discovery and functional genomic studies. [ABSTRACT FROM AUTHOR]

The advent of high-throughput next generation sequencing technologies have fostered enormous potential applications of supercomputing techniques in genome sequencing, epi-genetics, metagenomics, personalized medicine, discovery of non-coding RNAs and protein-binding sites. To this end, the 2008 International Conference on Bioinformatics and Computational Biology (Biocomp) - 2008 World Congress on Computer Science, Computer Engineering and Applied Computing (Worldcomp) was designed to promote synergistic inter/multidisciplinary research and education in response to the current research trends and advances. The conference attracted more than two thousand scientists, medical doctors, engineers, professors and students gathered at Las Vegas, Nevada, USA during July 14-17 and received great success. Supported by International Society of Intelligent Biological Medicine (ISIBM), International Journal of Computational Biology and Drug Design (IJCBDD), International Journal of Functional Informatics and Personalized Medicine (IJFIPM) and the leading research laboratories from Harvard, M.I.T., Purdue, UIUC, UCLA, Georgia Tech, UT Austin, U. of Minnesota, U. of Iowa etc, the conference received thousands of research papers. Each submitted paper was reviewed by at least three reviewers and accepted papers were required to satisfy reviewers' comments. Finally, the review board and the committee decided to select only 19 high-quality research papers for inclusion in this supplement to BMC Genomics based on the peer reviews only. The conference committee was very grateful for the Plenary Keynote Lectures given by: Dr. Brian D. Athey (University of Michigan Medical School), Dr. Vladimir N. Uversky (Indiana University School of Medicine), Dr. David A. Patterson (Member of United States National Academy of Sciences and National Academy of Engineering, University of California at Berkeley) and Anousheh Ansari (Prodea Systems, Space Ambassador). The theme of the conference to promote synergistic research and education has been achieved successfully. [ABSTRACT FROM AUTHOR]

Background: Graph-based reference genomes have become popular as they allow read mapping and follow-up analyses in settings where the exact haplotypes underlying a high-throughput sequencing experiment are not precisely known. Two recent papers show that mapping to graph-based reference genomes can improve accuracy as compared to methods using linear references. Both of these methods index the sequences for most paths up to a certain length in the graph in order to enable direct mapping of reads containing common variants. However, the combinatorial explosion of possible paths through nearby variants also leads to a huge search space and an increased chance of false positive alignments to highly variable regions. Results: We here assess three prominent graph-based read mappers against a hybrid baseline approach that combines an initial path determination with a tuned linear read mapping method. We show, using a previously proposed benchmark, that this simple approach is able to improve overall accuracy of read-mapping to graph-based reference genomes. Conclusions: Our method is implemented in a tool Two-step Graph Mapper, which is available at https://github.com/uio-bmi/two%5fstep%5fgraph%5fmapperalong with data and scripts for reproducing the experiments. Our method highlights characteristics of the current generation of graph-based read mappers and shows potential for improvement for future graph-based read mappers. [ABSTRACT FROM AUTHOR]

Background: Annotating genomes remains an hazardous task. Mistakes or gaps in such a complex process may occur when relevant knowledge is ignored, whether lost, forgotten or overlooked. This paper exemplifies an approach which could help to ressucitate such meaningful data. Results: We show that a set of closely related sequences which have been annotated as ornithine carbamoyltransferases are actually putrescine carbamoyltransferases. This demonstration is based on the following points : (i) use of enzymatic data which had been overlooked, (ii) rediscovery of a short NH2-terminal sequence allowing to reannotate a wrongly annotated ornithine carbamoyltransferase as a putrescine carbamoyltransferase, (iii) identification of conserved motifs allowing to distinguish unambiguously between the two kinds of carbamoyltransferases, and (iv) comparative study of the gene context of these different sequences. Conclusions: We explain why this specific case of misannotation had not yet been described and draw attention to the fact that analogous instances must be rather frequent. We urge to be especially cautious when high sequence similarity is coupled with an apparent lack of biochemical information. Moreover, from the point of view of genome annotation, proteins which have been studied experimentally but are not correlated with sequence data in current databases qualify as "orphans", just as unassigned genomic open reading frames do. The strategy we used in this paper to bridge such gaps in knowledge could work whenever it is possible to collect a body of facts about experimental data, homology, unnoticed sequence data, and accurate informations about gene context. [ABSTRACT FROM AUTHOR]

Background: Topological association domains (TADs) are chromosomal domains characterised by frequent internal DNA-DNA interactions. The transcription factor CTCF binds to conserved DNA sequence patterns called CTCF binding motifs to either prohibit or facilitate chromosomal interactions. TADs and CTCF binding motifs control gene expression, but they are not yet well defined in the bovine genome. In this paper, we sought to improve the annotation of bovine TADs and CTCF binding motifs, and assess whether the new annotation can reduce the search space for cis-regulatory variants. Results: We used genomic synteny to map TADs and CTCF binding motifs from humans, mice, dogs and macaques to the bovine genome. We found that our mapped TADs exhibited the same hallmark properties of those sourced from experimental data, such as housekeeping genes, transfer RNA genes, CTCF binding motifs, short interspersed elements, H3K4me3 and H3K27ac. We showed that runs of genes with the same pattern of allele-specific expression (ASE) (either favouring paternal or maternal allele) were often located in the same TAD or between the same conserved CTCF binding motifs. Analyses of variance showed that when averaged across all bovine tissues tested, TADs explained 14% of ASE variation (standard deviation, SD: 0.056), while CTCF explained 27% (SD: 0.078). Furthermore, we showed that the quantitative trait loci (QTLs) associated with gene expression variation (eQTLs) or ASE variation (aseQTLs), which were identified from mRNA transcripts from 141 lactating cows' white blood and milk cells, were highly enriched at putative bovine CTCF binding motifs. The linearly-furthermost, and most-significant aseQTL and eQTL for each genic target were located within the same TAD as the gene more often than expected (Chi-Squared test P-value < 0.001). Conclusions: Our results suggest that genomic synteny can be used to functionally annotate conserved transcriptional components, and provides a tool to reduce the search space for causative regulatory variants in the bovine genome. [ABSTRACT FROM AUTHOR]

Background: It has been suggested that the high phospholipid (PL) requirement in Atlantic salmon (Salmo salar) fry is due to insufficient intestinal de-novo synthesis causing low lipoprotein (LP) production and reduced transport capacity of dietary lipids. However, in-depth ontogenetic analysis of intestinal PL and LP synthesis with the development of salmon has yet to be performed. Therefore, in this paper we used RNA-Seq technology to investigate the expression of genes involved in PL synthesis and LP formation throughout early developmental stages and associate insufficient expression of synthesis pathways in salmon fry with its higher dietary PL requirement. There was a special focus on the understanding homologous genes, especially those from salmonid-specific fourth vertebrate whole-genome duplication (Ss4R), and their contribution to salmonid specific features of regulation of PL metabolic pathways. Salmon fry were sampled at 0.16 g (1 day before first-feeding), 2.5 and 10 g stages of development and transcriptomic analysis was applied separately on stomach, pyloric caeca and hindgut of the fish. Results: In general, we found up-regulated pathways involved in synthesis of phosphatidylcholine (PtdCho), phosphatidylethanolamine (PtdEtn), and LP in pyloric caeca of salmon between 0.16 and 10 g. Thirteen differentially expressed genes (q < 0.05) in these pathways were highly up-regulated in 2.5 g salmon compared to 0.16 g, while only five more differentially expressed (q < 0.05) genes were found when the fish grew up to 10 g. Different homologous genes were found dominating in stomach, pyloric caeca and hindgut. However, the expression of dominating genes in pathways of PL and LP synthesis were much higher in pyloric caeca than stomach and hindgut. Salmon-specific homologous genes (Ss4R) had similar expression during development, while other homologs had more diverged expression. Conclusions: The up-regulation of the de-novo PtdCho and PtdEtn pathways confirm that salmon have decreasing requirement for dietary PL as the fish develops. The similar expressions between Ss4R homologous genes suggest that the functional divergence of these genes was incomplete compared to homologs derived from other genome duplication. The results of the present study have provided new information on the molecular mechanisms of phospholipid synthesis and lipoprotein formation in fish. [ABSTRACT FROM AUTHOR]

Background: Whole-genome sequencing (WGS) plays an increasingly important role in clinical practice and public health. Due to the big data size, WGS data analysis is usually compute-intensive and IO-intensive. Currently it usually takes 30 to 40 h to finish a 50× WGS analysis task, which is far from the ideal speed required by the industry. Furthermore, the high-end infrastructure required by WGS computing is costly in terms of time and money. In this paper, we aim to improve the time efficiency of WGS analysis and minimize the cost by elastic cloud computing. Results: We developed a distributed system, GT-WGS, for large-scale WGS analyses utilizing the Amazon Web Services (AWS). Our system won the first prize on the Wind and Cloud challenge held by Genomics and Cloud Technology Alliance conference (GCTA) committee. The system makes full use of the dynamic pricing mechanism of AWS. We evaluate the performance of GT-WGS with a 55× WGS dataset (400GB fastq) provided by the GCTA 2017 competition. In the best case, it only took 18.4 min to finish the analysis and the AWS cost of the whole process is only 16.5 US dollars. The accuracy of GT-WGS is 99.9% consistent with that of the Genome Analysis Toolkit (GATK) best practice. We also evaluated the performance of GT-WGS performance on a real-world dataset provided by the XiangYa hospital, which consists of 5× whole-genome dataset with 500 samples, and on average GT-WGS managed to finish one 5× WGS analysis task in 2.4 min at a cost of $3.6. Conclusions: WGS is already playing an important role in guiding therapeutic intervention. However, its application is limited by the time cost and computing cost. GT-WGS excelled as an efficient and affordable WGS analyses tool to address this problem. The demo video and supplementary materials of GT-WGS can be accessed at https://github.com/Genetalks/wgs_analysis_demo. [ABSTRACT FROM AUTHOR]

Background: Adenosine-to-inosine (A-to-I) RNA editing is a co-/post-transcriptional modification introducing A-to-G variations in RNAs. There is extensive discussion on whether the flexibility of RNA editing exerts a proteomic diversification role, or it just acts like hardwired mutations to correct the genomic allele. Eusocial insects evolved the ability to generate phenotypically differentiated individuals with the same genome, indicating the involvement of epigenetic/transcriptomic regulation. Methods: We obtained the genomes of 104 Hymenoptera insects and the transcriptomes of representative species. Comparative genomic analysis was performed to parse the evolutionary trajectory of a regulatory Ile > Met auto-recoding site in Adar gene. Results: At genome level, the pre-editing Ile codon is conserved across a node containing all eusocial hymenopterans. At RNA level, the editing events are confirmed in representative species and shows considerable condition-specificity. Compared to random expectation, the editable Ile codon avoids genomic substitutions to Met or to uneditable Ile codons, but does not avoid mutations to other unrelated amino acids. Conclusions: The flexibility of Adar auto-recoding site in Hymenoptera is selectively maintained, supporting the flexible RNA editing hypothesis. We proposed a new angle to view the adaptation of RNA editing, providing another layer to explain the great phenotypical plasticity of eusocial insects. [ABSTRACT FROM AUTHOR]

Background: Nitzschia closterium f. minutissima is a commonly available diatom that plays important roles in marine aquaculture. It was originally classified as Nitzschia (Bacillariaceae, Bacillariophyta) but is currently regarded as a heterotypic synonym of Phaeodactylum tricornutum. The aim of this study was to obtain the draft genome of the marine microalga N. closterium f. minutissima to understand its phylogenetic placement and evolutionary specialization. Given that the ornate hierarchical silicified cell walls (frustules) of diatoms have immense applications in nanotechnology for biomedical fields, biosensors and optoelectric devices, transcriptomic data were generated by using reference genome-based read mapping to identify significantly differentially expressed genes and elucidate the molecular processes involved in diatom biosilicification. Results: In this study, we generated 13.81 Gb of pass reads from the PromethION sequencer. The draft genome of N. closterium f. minutissima has a total length of 29.28 Mb, and contains 28 contigs with an N50 value of 1.23 Mb. The GC content was 48.55%, and approximately 18.36% of the genome assembly contained repeat sequences. Gene annotation revealed 9,132 protein-coding genes. The results of comparative genomic analysis showed that N. closterium f. minutissima was clustered as a sister lineage of Phaeodactylum tricornutum and the divergence time between them was estimated to be approximately 17.2 million years ago (Mya). CAFF analysis demonstrated that 220 gene families that significantly changed were unique to N. closterium f. minutissima and that 154 were specific to P. tricornutum, moreover, only 26 gene families overlapped between these two species. A total of 818 DEGs in response to silicon were identified in N. closterium f. minutissima through RNA sequencing, these genes are involved in various molecular processes such as transcription regulator activity. Several genes encoding proteins, including silicon transporters, heat shock factors, methyltransferases, ankyrin repeat domains, cGMP-mediated signaling pathways-related proteins, cytoskeleton-associated proteins, polyamines, glycoproteins and saturated fatty acids may contribute to the formation of frustules in N. closterium f. minutissima. Conclusions: Here, we described a draft genome of N. closterium f. minutissima and compared it with those of eight other diatoms, which provided new insight into its evolutionary features. Transcriptome analysis to identify DEGs in response to silicon will help to elucidate the underlying molecular mechanism of diatom biosilicification in N. closterium f. minutissima. [ABSTRACT FROM AUTHOR]

Background: Detecting the borders between coding and non-coding regions is an essential step in the genome annotation. And information entropy measures are useful for describing the signals in genome sequence. However, the accuracies of previous methods of finding borders based on entropy segmentation method still need to be improved. Methods: In this study, we first applied a new recursive entropic segmentation method on DNA sequences to get preliminary significant cuts. A 22-symbol alphabet is used to capture the differential composition of nucleotide doublets and stop codon patterns along three phases in both DNA strands. This process requires no prior training datasets. Results: Comparing with the previous segmentation methods, the experimental results on three bacteria genomes, Rickettsia prowazekii, Borrelia burgdorferi and E.coli, show that our approach improves the accuracy for finding the borders between coding and non-coding regions in DNA sequences. Conclusions: This paper presents a new segmentation method in prokaryotes based on Jensen-Rényi divergence with a 22-symbol alphabet. For three bacteria genomes, comparing to A12 JR method, our method raised the accuracy of finding the borders between protein coding and non-coding regions in DNA sequences. [ABSTRACT FROM AUTHOR]

Background: Proximity-based methods and co-evolution-based phylogenetic profiles methods have been successfully used for the identification of functionally related genes. Proximity-based methods are effective for physically clustered genes while the phylogenetic profiles method is effective for co-occurring gene sets. However, both methods predict many false positives and false negatives. In this paper, we propose the Gene Cluster Profile Vector (GCPV) method, which combines these two methods by using phylogenetic profiles of whole gene clusters. The GCPV method is, currently, the only genome comparison based method that allows for the characterization of relationships between gene clusters based profiles of individual genes in clusters. Results: The GCPV method groups together reasonably related operons in E. coli about 60% of the time. The method is not sensitive to the choice of a reference genome set used and it outperforms the conventional phylogenetic profiles method. Finally, we show that the method works well for predicted gene clusters from C. crescentus and can serve as an important tool not only for understanding gene function, but also for elucidating mechanisms of general biological processes. Conclusions: The GCPV method has shown to be an effective and robust approach to the prediction of functionally related gene sets from proximity-based gene clusters or operons. [ABSTRACT FROM AUTHOR]

Significant interest exists in establishing synergistic research in bioinformatics, systems biology and intelligent computing. Supported by the United States National Science Foundation (NSF), International Society of Intelligent Biological Medicine (http://www.ISIBM.org), International Journal of Computational Biology and Drug Design (IJCBDD) and International Journal of Functional Informatics and Personalized Medicine, the ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing (ISIBM IJCBS 2009) attracted more than 300 papers and 400 researchers and medical doctors world-wide. It was the only inter/multidisciplinary conference aimed to promote synergistic research and education in bioinformatics, systems biology and intelligent computing. The conference committee was very grateful for the valuable advice and suggestions from honorary chairs, steering committee members and scientific leaders including Dr. Michael S. Waterman (USC, Member of United States National Academy of Sciences), Dr. Chih-Ming Ho (UCLA, Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Wing H. Wong (Stanford, Member of United States National Academy of Sciences), Dr. Ruzena Bajcsy (UC Berkeley, Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Qu Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Andrzej Niemierko (Harvard), Dr. A. Keith Dunker (Indiana), Dr. Brian D. Athey (Michigan), Dr. Weida Tong (FDA, United States Department of Health and Human Services), Dr. Cathy H. Wu (Georgetown), Dr. Dong Xu (Missouri), Drs. Arif Ghafoor and Okan K Ersoy (Purdue), Dr. Mark Borodovsky (Georgia Tech, President of ISIBM), Dr. Hamid R. Arabnia (UGA, Vice-President of ISIBM), and other scientific leaders. The committee presented the 2009 ISIBM Outstanding Achievement Awards to Dr. Joydeep Ghosh (UT Austin), Dr. Aidong Zhang (Buffalo) and Dr. Zhi-Hua Zhou (Nanjing) for their significant contributions to the field of intelligent biological medicine. [ABSTRACT FROM AUTHOR]

Background: Efforts using computational algorithms towards the enumeration of the full set of miRNAs of an organism have been limited by strong reliance on arguments of precursor conservation and feature similarity. However, miRNA precursors may arise anew or be lost across the evolutionary history of a species and a newly sequenced genome may be evolutionarily too distant from other genomes for an adequate comparative analysis. In addition, the learning of intricate classification rules based purely on features shared by miRNA precursors that are currently known may reflect a perpetuating identification bias rather than a sound means to tell true miRNAs from other genomic stem-loops. Results: We show that there is a strong bias amongst annotated pre-miRNAs towards robust stem-loops in the genomes of Drosophila melanogaster and Anopheles gambiae and we propose a scoring scheme for precursor candidates which combines four robustness measures. Additionally, we identify several known pre-miRNA homologs in the newly sequenced Anopheles darlingi and show that most are found amongst the top-scoring precursor candidates. Furthermore, a comparison of the performance of our approach is made against two single-genome pre-miRNA classification methods. Conclusions: In this paper we present a strategy to sieve through the vast amount of stem-loops found in metazoan genomes in search of pre-miRNAs, significantly reducing the set of candidates while retaining most known miRNA precursors. This approach makes no use of conservation data and relies solely on properties derived from our knowledge of miRNA biogenesis. [ABSTRACT FROM AUTHOR]

Background: The pig genome is being sequenced and characterised under the auspices of the Swine Genome Sequencing Consortium. The sequencing strategy followed a hybrid approach combining hierarchical shotgun sequencing of BAC clones and whole genome shotgun sequencing. Results: Assemblies of the BAC clone derived genome sequence have been annotated using the Pre-Ensembl and Ensembl automated pipelines and made accessible through the Pre-Ensembl/Ensembl browsers. The current annotated genome assembly (Sscrofa9) was released with Ensembl 56 in September 2009. A revised assembly (Sscrofa10) is under construction and will incorporate whole genome shotgun sequence (WGS) data providing > 30× genome coverage. The WGS sequence, most of which comprise short Illumina/Solexa reads, were generated from DNA from the same single Duroc sow as the source of the BAC library from which clones were preferentially selected for sequencing. In accordance with the Bermuda and Fort Lauderdale agreements and the more recent Toronto Statement the data have been released into public sequence repositories (Genbank/EMBL, NCBI/Ensembl trace repositories) in a timely manner and in advance of publication. Conclusions: In this marker paper, the Swine Genome Sequencing Consortium (SGSC) sets outs its plans for analysis of the pig genome sequence, for the application and publication of the results. [ABSTRACT FROM AUTHOR]

Background: Insertional mutagenesis is an effective method for functional genomic studies in various organisms. It can rapidly generate easily tractable mutations. A large-scale insertional mutagenesis with the piggyBac (PB) transposon is currently performed in mice at the Institute of Developmental Biology and Molecular Medicine (IDM), Fudan University in Shanghai, China. This project is carried out via collaborations among multiple groups overseeing interconnected experimental steps and generates a large volume of experimental data continuously. Therefore, the project calls for an efficient database system for recording, management, statistical analysis, and information exchange. Results: This paper presents a database application called MP-PBmice (insertional mutation mapping system of PB Mutagenesis Information Center), which is developed to serve the on-going large-scale PB insertional mutagenesis project. A lightweight enterprise-level development framework Struts-Spring-Hibernate is used here to ensure constructive and flexible support to the application. The MP-PBmice database system has three major features: strict access-control, efficient workflow control, and good expandability. It supports the collaboration among different groups that enter data and exchange information on daily basis, and is capable of providing real time progress reports for the whole project. MP-PBmice can be easily adapted for other large-scale insertional mutation mapping projects and the source code of this software is freely available at http://www.idmshanghai.cn/PBmice. Conclusion: MP-PBmice is a web-based application for large-scale insertional mutation mapping onto the mouse genome, implemented with the widely used framework Struts-Spring-Hibernate. This system is already in use by the on-going genome-wide PB insertional mutation mapping project at IDM, Fudan University. [ABSTRACT FROM AUTHOR]

Background: Gene order changes, under rearrangements, insertions, deletions and duplications, have been used as a new type of data source for phylogenetic reconstruction. Because these changes are rare compared to sequence mutations, they allow the inference of phylogeny further back in evolutionary time. There exist many computational methods for the reconstruction of gene-order phylogenies, including widely used maximum parsimonious methods and maximum likelihood methods. However, both methods face challenges in handling large genomes with many duplicated genes, especially in the presence of whole genome duplication. Methods: In this paper, we present three simple yet powerful methods based on maximum-likelihood (ML) approaches that encode multiplicities of both gene adjacency and gene content information for phylogenetic reconstruction. Results: Extensive experiments on simulated data sets show that our new method achieves the most accurate phylogenies compared to existing approaches. We also evaluate our method on real whole-genome data from eleven mammals. The package is publicly accessible at http://www.geneorder.org. Conclusions: Our new encoding schemes successfully incorporate the multiplicity information of gene adjacencies and gene content into an ML framework, and show promising results in reconstruct phylogenies for whole-genome data in the presence of massive duplications. [ABSTRACT FROM AUTHOR]

Background: Studying genetic variation distribution in proteins containing charged regions, called charge clusters (CCs), is of great interest to unravel their functional role. Charge clusters are 20 to 75 residue segments with high net positive charge, high net negative charge, or high total charge relative to the overall charge composition of the protein. We previously developed a bioinformatics tool (FCCP) to detect charge clusters in proteomes and scanned the human proteome for the occurrence of CCs. In this paper we investigate the genetic variations in the human proteins harbouring CCs. Results: We studied the coding regions of 317 positively charged clusters and 1020 negatively charged ones previously detected in human proteins. Results revealed that coding parts of CCs are richer in sequence variants than their corresponding genes, full mRNAs, and exonic + intronic sequences and that these variants are predominately rare (Minor allele frequency < 0.005). Furthermore, variants occurring in the coding parts of positively charged regions of proteins are more often pathogenic than those occurring in negatively charged ones. Classification of variants according to their types showed that substitution is the major type followed by Indels (Insertions-deletions). Concerning substitutions, it was found that within clusters of both charges, the charged amino acids were the greatest loser groups whereas polar residues were the greatest gainers. Conclusions: Our findings highlight the prominent features of the human charged regions from the DNA up to the protein sequence which might provide potential clues to improve the current understanding of those charged regions and their implication in the emergence of diseases. [ABSTRACT FROM AUTHOR]

Background: The recent advancement of whole genome alignment software has made it possible to align two genomes very efficiently and with only a small sacrifice in sensitivity. Yet it becomes very slow if the extra sensitivity is needed. This paper proposes a simple but effective method to improve the sensitivity of existing whole-genome alignment software without paying much extra running time. Results and conclusions: We have applied our method to a popular whole genome alignment tool LAST, and we called the resulting tool LASTM. Experimental results showed that LASTM could find more high quality alignments with a little extra running time. For example, when comparing human and mouse genomes, to produce the similar number of alignments with similar average length and similarity, LASTM was about three times faster than LAST. We conclude that our method can be used to improve the sensitivity, and the extra time it takes is small, and thus it is worthwhile to be implemented in existing tools. [ABSTRACT FROM AUTHOR]

Advancing the production efficiency and profitability of aquaculture is dependent upon the ability to utilize a diverse array of genetic resources. The ultimate goals of aquaculture genomics, genetics and breeding research are to enhance aquaculture production efficiency, sustainability, product quality, and profitability in support of the commercial sector and for the benefit of consumers. In order to achieve these goals, it is important to understand the genomic structure and organization of aquaculture species, and their genomic and phenomic variations, as well as the genetic basis of traits and their interrelationships. In addition, it is also important to understand the mechanisms of regulation and evolutionary conservation at the levels of genome, transcriptome, proteome, epigenome, and systems biology. With genomic information and information between the genomes and phenomes, technologies for marker/causal mutation-assisted selection, genome selection, and genome editing can be developed for applications in aquaculture. A set of genomic tools and resources must be made available including reference genome sequences and their annotations (including coding and non-coding regulatory elements), genome-wide polymorphic markers, efficient genotyping platforms, highdensity and high-resolution linkage maps, and transcriptome resources including non-coding transcripts. Genomic and genetic control of important performance and production traits, such as disease resistance, feed conversion efficiency, growth rate, processing yield, behaviour, reproductive characteristics, and tolerance to environmental stressors like low dissolved oxygen, high or low water temperature and salinity, must be understood. QTL need to be identified, validated across strains, lines and populations, and their mechanisms of control understood. Causal gene(s) need to be identified. Genetic and epigenetic regulation of important aquaculture traits need to be determined, and technologies for marker-assisted selection, causal gene/mutation-assisted selection, genome selection, and genome editing using CRISPR and other technologies must be developed, demonstrated with applicability, and application to aquaculture industries. Major progress has been made in aquaculture genomics for dozens of fish and shellfish species including the development of genetic linkage maps, physical maps, microarrays, single nucleotide polymorphism (SNP) arrays, transcriptome databases and various stages of genome reference sequences. This paper provides a general review of the current status, challenges and future research needs of aquaculture genomics, genetics, and breeding, with a focus on major aquaculture species in the United States: catfish, rainbow trout, Atlantic salmon, tilapia, striped bass, oysters, and shrimp. While the overall research priorities and the practical goals are similar across various aquaculture species, the current status in each species should dictate the next priority areas within the species. This paper is an output of the USDA Workshop for Aquaculture Genomics, Genetics, and Breeding held in late March 2016 in Auburn, Alabama, with participants from all parts of the United States. [ABSTRACT FROM AUTHOR]

Morchella spongiola is a highly prized mushroom for its delicious flavor and medical value and is one of the most flourishing, representative, and dominant macrofungi in the Qilian Mountains of the Qinghai-Tibet Plateau subkingdoms (QTPs). However, the understanding of M. spongiola remains largely unknown, and its taxonomy is ambiguous. In this study, we redescribed a unique species of M. spongiola, i.e., micromorphology, molecular data, genomics, and comparative genomics, and the historical biogeography of M. spongiola were estimated for 182 single-copy homologous genes. A high-quality chromosome-level reference genome of M. spongiola M12-10 was obtained by combining PacBio HiFi data and Illumina sequencing technologies; it was approximately 57.1 Mb (contig N50 of 18.14 Mb) and contained 9775 protein-coding genes. Comparative genome analysis revealed considerable conservation and unique characteristics between M. spongiola M12-10 and 32 other Morchella species. Molecular phylogenetic analysis indicated that M. spongiola M12-10 is similar to the M. prava/Mes-7 present in sandy soil near rivers, differentiating from black morels ~ 43.06 Mya (million years ago), and diverged from M. parva/Mes-7 at approximately 12.85 Mya (in the Miocene epoch), which is closely related to the geological activities in the QTPs (in the Neogene). Therefore, M. spongiola is a unique species rather than a synonym of M. vulgaris/Mes-5, which has a distinctive grey-brown sponge-like ascomata. This genome of M. spongiola M12-10 is the first published genome sequence of the species in the genus Morchella from the QTPs, which could aid future studies on functional gene identification, germplasm resource management, and molecular breeding efforts, as well as evolutionary studies on the Morchella taxon in the QTPs. [ABSTRACT FROM AUTHOR]

Assessing the genetic structure of local varieties and understanding their genetic data are crucial for effective management and preservation. However, the genetic differences among local breeds require further explanation. To enhance our understanding of their population structure and genetic diversity, we conducted a genome-wide comparative study of Chaohu and Ji'an Red ducks using genome sequence and restriction site-associated DNA sequencing technology. Our analysis revealed a distinct genetic distinction between the two breeds, leading to divided groups. The phylogenetic tree for Chaohu duck displayed two branches, potentially indicating minimal impact from artificial selection. Additionally, our ROH (runs of homozygosity) analysis revealed that Chaohu ducks had a lower average inbreeding coefficient than Ji'an Red ducks. We identified several genomic regions with high genetic similarity in these indigenous duck breeds. By conducting a selective sweep analysis, we identified 574 candidate genes associated with muscle growth (BMP2, ITGA8, MYLK, and PTCH1), fat deposits (ELOVL1 and HACD2), and pigmentation (ASIP and LOC101797494). These results offer valuable insights for the further enhancement and conservation of Chinese indigenous duck breeds. [ABSTRACT FROM AUTHOR]

Background: The growth and development of organism were dependent on the effect of genetic, environment, and their interaction. In recent decades, lots of candidate additive genetic markers and genes had been detected by using genome-widely association study (GWAS). However, restricted to computing power and practical tool, the interactive effect of markers and genes were not revealed clearly. And utilization of these interactive markers is difficult in the breeding and prediction, such as genome selection (GS). Results: Through the Power-FDR curve, the GbyE algorithm can detect more significant genetic loci at different levels of genetic correlation and heritability, especially at low heritability levels. The additive effect of GbyE exhibits high significance on certain chromosomes, while the interactive effect detects more significant sites on other chromosomes, which were not detected in the first two parts. In prediction accuracy testing, in most cases of heritability and genetic correlation, the majority of prediction accuracy of GbyE is significantly higher than that of the mean method, regardless of whether the rrBLUP model or BGLR model is used for statistics. The GbyE algorithm improves the prediction accuracy of the three Bayesian models BRR, BayesA, and BayesLASSO using information from genetic by environmental interaction (G × E) and increases the prediction accuracy by 9.4%, 9.1%, and 11%, respectively, relative to the Mean value method. The GbyE algorithm is significantly superior to the mean method in the absence of a single environment, regardless of the combination of heritability and genetic correlation, especially in the case of high genetic correlation and heritability. Conclusions: Therefore, this study constructed a new genotype design model program (GbyE) for GWAS and GS using Kronecker product. which was able to clearly estimate the additive and interactive effects separately. The results showed that GbyE can provide higher statistical power for the GWAS and more prediction accuracy of the GS models. In addition, GbyE gives varying degrees of improvement of prediction accuracy in three Bayesian models (BRR, BayesA, and BayesCpi). Whatever the phenotype were missed in the single environment or multiple environments, the GbyE also makes better prediction for inference population set. This study helps us understand the interactive relationship between genomic and environment in the complex traits. The GbyE source code is available at the GitHub website (https://github.com/liu-xinrui/GbyE). [ABSTRACT FROM AUTHOR]

Pseudoalteromonas viridis strain BBR56 was isolated from seawater at Dutungan Island, South Sulawesi, Indonesia. Bacterial DNA was isolated using Promega Genomic DNA TM050. DNA purity and quantity were assessed using NanoDrop spectrophotometers and Qubit fluorometers. The DNA library and sequencing were prepared using Oxford Nanopore Technology GridION MinKNOW 20.06.9 with long read, direct, and comprehensive analysis. High accuracy base calling was assessed with Guppy version 4.0.11. Filtlong and NanoPlot were used for filtering and visualizing the FASTQ data. Flye (2.8.1) was used for de novo assembly analysis. Variant calls and consensus sequences were created using Medaka. The annotation of the genome was elaborated by DFAST. The assembled genome and annotation were tested using Busco and CheckM. Herein, we found that the highest similarity of the BBR56 isolate was 98.37% with the 16 S rRNA gene sequence of P. viridis G-1387. The genome size was 5.5 Mb and included chromosome 1 (4.2 Mbp) and chromosome 2 (1.3 Mbp), which encoded 61 pseudogenes, 4 noncoding RNAs, 113 tRNAs, 31 rRNAs, 4,505 coding DNA sequences, 4 clustered regularly interspaced short palindromic repeats, 4,444 coding genes, and a GC content of 49.5%. The sequence of the whole genome of P. viridis BBR56 was uploaded to GenBank under the accession numbers CP072425–CP072426, biosample number SAMN18435505, and bioproject number PRJNA716373. The sequence read archive (SRR14179986) was successfully obtained from NCBI for BBR56 raw sequencing reads. Digital DNA–DNA hybridization results showed that the genome of BBR56 had the potential to be a new species because no other bacterial genomes were similar to the sample. Biosynthetic gene clusters (BGCs) were assessed using BAGEL4 and the antiSMASH bacterial version. The genome harbored diverse BGCs, including genes that encoded polyketide synthase, nonribosomal peptide synthase, RiPP-like, NRP-metallophore, hydrogen cyanide, betalactone, thioamide-NRP, Lant class I, sactipeptide, and prodigiosin. Thus, BBR56 has considerable potential for further exploration regarding the use of its secondary metabolite products in the human and fisheries sectors. [ABSTRACT FROM AUTHOR]

Background: Genetically modified (GM) crop plants with transgenic expression of Bacillus thuringiensis (Bt) pesticidal proteins are used to manage feeding damage by pest insects. The durability of this technology is threatened by the selection for resistance in pest populations. The molecular mechanism(s) involved in insect physiological response or evolution of resistance to Bt is not fully understood. Results: To investigate the response of a susceptible target insect to Bt, the soybean pod borer, Leguminivora glycinivorella (Lepidoptera: Tortricidae), was exposed to soybean, Glycine max, expressing Cry1Ac pesticidal protein or the non-transgenic parental cultivar. Assessment of larval changes in gene expression was facilitated by a third-generation sequenced and scaffolded chromosome-level assembly of the L. glycinivorella genome (657.4 Mb; 27 autosomes + Z chromosome), and subsequent structural annotation of 18,197 RefSeq gene models encoding 23,735 putative mRNA transcripts. Exposure of L. glycinivorella larvae to transgenic Cry1Ac G. max resulted in prediction of significant differential gene expression for 204 gene models (64 up- and 140 down-regulated) and differential splicing among isoforms for 10 genes compared to unexposed cohorts. Differentially expressed genes (DEGs) included putative peritrophic membrane constituents, orthologs of Bt receptor-encoding genes previously linked or associated with Bt resistance, and those involved in stress responses. Putative functional Gene Ontology (GO) annotations assigned to DEGs were significantly enriched for 36 categories at GO level 2, respectively. Most significantly enriched cellular component (CC), biological process (BP), and molecular function (MF) categories corresponded to vacuolar and microbody, transport and metabolic processes, and binding and reductase activities. The DEGs in enriched GO categories were biased for those that were down-regulated (≥ 0.783), with only MF categories GTPase and iron binding activities were bias for up-regulation genes. Conclusions: This study provides insights into pathways and processes involved larval response to Bt intoxication, which may inform future unbiased investigations into mechanisms of resistance that show no evidence of alteration in midgut receptors. [ABSTRACT FROM AUTHOR]

Background: The spread of Popillia japonica in non-native areas (USA, Canada, the Azores islands, Italy and Switzerland) poses a significant threat to agriculture and horticulture, as well as to endemic floral biodiversity, entailing that appropriate control measures must be taken to reduce its density and limit its further spread. In this context, the availability of a high quality genomic sequence for the species is liable to foster basic research on the ecology and evolution of the species, as well as on possible biotechnologically-oriented and genetically-informed control measures. Results: The genomic sequence presented and described here is an improvement with respect to the available draft sequence in terms of completeness and contiguity, and includes structural and functional annotations. A comparative analysis of gene families of interest, related to the species ecology and potential for polyphagy and adaptability, revealed a contraction of gustatory receptor genes and a paralogous expansion of some subgroups/subfamilies of odorant receptors, ionotropic receptors and cytochrome P450s. Conclusions: The new genomic sequence as well as the comparative analyses data may provide a clue to explain the staggering invasive potential of the species and may serve to identify targets for potential biotechnological applications aimed at its control. [ABSTRACT FROM AUTHOR]

Background: Ampelopsideae J. Wen & Z.L. Nie is a small-sized tribe of Vitaceae Juss., including ca. 47 species from four genera showing a disjunct distribution worldwide across all the continents except Antarctica. There are numerous species from the tribe that are commonly used as medicinal plants with immune-modulating, antimicrobial, and anti-hypertensive properties. The tribe is usually recognized into three clades, i.e., Ampelopsis Michx., Nekemias Raf., and the Southern Hemisphere clade. However, the relationships of the three clades differ greatly between the nuclear and the plastid topologies. There has been limited exploration of the chloroplast phylogenetic relationships within Ampelopsideae, and studies on the chloroplast genome structure of this tribe are only available for a few individuals. In this study, we aimed to investigate the evolutionary characteristics of plastid genomes of the tribe, including their genome structure and evolutionary insights. Results: We sequenced, assembled, and annotated plastid genomes of 36 species from the tribe and related taxa in the family. Three main clades were recognized within Ampelopsideae, corresponding to Ampelopsis, Nekemias, and the Southern Hemisphere lineage, respectively, and all with 100% bootstrap supports. The genome sequences and content of the tribe are highly conserved. However, comparative analyses suggested that the plastomes of Nekemias demonstrate a contraction in the large single copy region and an expansion in the inverted repeat region, and possess a high number of forward and palindromic repeat sequences distinct from both Ampelopsis and the Southern Hemisphere taxa. Conclusions: Our results highlighted plastome variations in genome length, expansion or contraction of the inverted repeat region, codon usage bias, and repeat sequences, are corresponding to the three lineages of the tribe, which probably faced with different environmental selection pressures and evolutionary history. This study provides valuable insights into understanding the evolutionary patterns of plastid genomes within the Ampelopsideae of Vitaceae. [ABSTRACT FROM AUTHOR]

Background: Patagonian toothfish (Dissostichus eleginoides) is an economically and ecologically important fish species in the family Nototheniidae. Juveniles occupy progressively deeper waters as they mature and grow, and adults have been caught as deep as 2500 m, living on or in just above the southern shelves and slopes around the sub-Antarctic islands of the Southern Ocean. As apex predators, they are a key part of the food web, feeding on a variety of prey, including krill, squid, and other fish. Despite its importance, genomic sequence data, which could be used for more accurate dating of the divergence between Patagonian and Antarctic toothfish, or establish whether it shares adaptations to temperature with fish living in more polar or equatorial climes, has so far been limited. Results: A high-quality D. eleginoides genome was generated using a combination of Illumina, PacBio and Omni-C sequencing technologies. To aid the genome annotation, the transcriptome derived from a variety of toothfish tissues was also generated using both short and long read sequencing methods. The final genome assembly was 797.8 Mb with a N50 scaffold length of 3.5 Mb. Approximately 31.7% of the genome consisted of repetitive elements. A total of 35,543 putative protein-coding regions were identified, of which 50% have been functionally annotated. Transcriptomics analysis showed that approximately 64% of the predicted genes (22,617 genes) were found to be expressed in the tissues sampled. Comparative genomics analysis revealed that the anti-freeze glycoprotein (AFGP) locus of D. eleginoides does not contain any AFGP proteins compared to the same locus in the Antarctic toothfish (Dissostichus mawsoni). This is in agreement with previously published results looking at hybridization signals and confirms that Patagonian toothfish do not possess AFGP coding sequences in their genome. Conclusions: We have assembled and annotated the Patagonian toothfish genome, which will provide a valuable genetic resource for ecological and evolutionary studies on this and other closely related species. [ABSTRACT FROM AUTHOR]

Background: Orchardgrass (Dactylis glomerata L.), a perennial forage, has the advantages of rich leaves, high yield, and good quality and is one of the most significant forage for grassland animal husbandry and ecological management in southwest China. Mitochondrial (mt) genome is one of the major genetic systems in plants. Studying the mt genome of the genus Dactylis could provide more genetic information in addition to the nuclear genome project of the genus. Results: In this study, we sequenced and assembled two mitochondrial genomes of Dactylis species of D. glomerata (597, 281 bp) and D. aschersoniana (613, 769 bp), based on a combination of PacBio and Illumina. The gene content in the mitochondrial genome of D. aschersoniana is almost identical to the mitochondrial genome of D. glomerata, which contains 22–23 protein-coding genes (PCGs), 8 ribosomal RNAs (rRNAs) and 30 transfer RNAs (tRNAs), while D. glomerata lacks the gene encoding the Ribosomal protein (rps1) and D. aschersoniana contains one pseudo gene (atp8). Twenty-three introns were found among eight of the 30 protein-coding genes, and introns of three genes (nad 1, nad2, and nad5) were trans-spliced in Dactylis aschersoniana. Further, our mitochondrial genome characteristics investigation of the genus Dactylis included codon usage, sequences repeats, RNA editing and selective pressure. The results showed that a large number of short repetitive sequences existed in the mitochondrial genome of D. aschersoniana, the size variation of two mitochondrial genomes is due largely to the presence of a large number of short repetitive sequences. We also identified 52–53 large fragments that were transferred from the chloroplast genome to the mitochondrial genome, and found that the similarity was more than 70%. ML and BI methods used in phylogenetic analysis revealed that the evolutionary status of the genus Dactylis. Conclusions: Thus, this study reveals the significant rearrangements in the mt genomes of Pooideae species. The sequenced Dactylis mt genome can provide more genetic information and improve our evolutionary understanding of the mt genomes of gramineous plants. [ABSTRACT FROM AUTHOR]

Background: De novo genome assembly using NGS data remains a computation-intensive task especially for large genomes. In practice, efficiency is often a primary concern and favors using a more efficient assembler like SOAPdenovo2. Yet SOAPdenovo2, based on de Bruijn graph, fails to take full advantage of longer NGS reads (say, 150 bp to 250 bp from Illumina HiSeq and MiSeq). Assemblers that are based on string graphs (e.g., SGA), though less popular and also very slow, are more favorable for longer reads. Methods: This paper shows a new de novo assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs. Results: Experiments on two bacteria and four human datasets shows the advantage of BASE in both contig quality and speed in dealing with longer reads. In the experiment on bacteria, two datasets with read length of 100 bp and 250 bp were used.. Especially for the 250 bp dataset, BASE gives much better quality than SOAPdenovo2 and SGA and is simlilar to SPAdes. Regarding speed, BASE is consistently a few times faster than SPAdes and SGA, but still slower than SOAPdenovo2. BASE and Soapdenov2 are further compared using human datasets with read length 100 bp, 150 bp and 250 bp. BASE shows a higher N50 for all datasets, while the improvement becomes more significant when read length reaches 250 bp. Besides, BASE is more-meory efficent than SOAPdenovo2 when sequencing data with error rate. Conclusions: BASE is a practically efficient tool for constructing contig, with significant improvement in quality for long NGS reads. It is relatively easy to extend BASE to include scaffolding. [ABSTRACT FROM AUTHOR]

Background: The identification of genes and uncovering the role they play in diseases is an important and complex challenge. Genome-wide linkage and association studies have made advancements in identifying genetic variants that underpin human disease. An important challenge now is to identify meaningful disease-associated genes from a long list of candidate genes implicated by these analyses. The application of gene prioritization can enhance our understanding of disease mechanisms and aid in the discovery of drug targets. The integration of protein-protein interaction networks along with disease datasets and contextual information is an important tool in unraveling the molecular basis of diseases. Results: In this paper we propose a computational pipeline for the prioritization of disease-gene candidates. Diverse heterogeneous data including: gene-expression, protein-protein interaction network, ontology-based similarity and topological measures and tissue-specific are integrated. The pipeline was applied to prioritize Alzheimer's Disease (AD) genes, whereby a list of 32 prioritized genes was generated. This approach correctly identified key AD susceptible genes: PSEN1 and TRAF1. Biological process enrichment analysis revealed the prioritized genes are modulated in AD pathogenesis including: regulation of neurogenesis and generation of neurons. Relatively high predictive performance (AUC: 0.70) was observed when classifying AD and normal gene expression profiles from individuals using leave-one-out cross validation. Conclusions: This work provides a foundation for future investigation of diverse heterogeneous data integration for disease-gene prioritization. [ABSTRACT FROM AUTHOR]

Background: Strand specific RNAseq data is now more common in RNAseq projects. Visualizing RNAseq data has become an important matter in Analysis of sequencing data. The most widely used visualization tool is the UCSC genome browser that introduced the custom track concept that enabled researchers to simultaneously visualize gene expression at a particular locus from multiple experiments. Our objective of the software tool is to provide friendly interface for visualization of RNAseq datasets. Results: This paper introduces a visualization tool (RNASeqBrowser) that incorporates and extends the functionality of the UCSC genome browser. For example, RNASeqBrowser simultaneously displays read coverage, SNPs, InDels and raw read tracks with other BED and wiggle tracks - all being dynamically built from the BAM file. Paired reads are also connected in the browser to enable easier identification of novel exon/intron borders and chimaeric transcripts. Strand specific RNAseq data is also supported by RNASeqBrowser that displays reads above (positive strand transcript) or below (negative strand transcripts) a central line. Finally, RNASeqBrowser was designed for ease of use for users with few bioinformatic skills, and incorporates the features of many genome browsers into one platform. Conclusions: The features of RNASeqBrowser: (1) RNASeqBrowser integrates UCSC genome browser and NGS visualization tools such as IGV. It extends the functionality of the UCSC genome browser by adding several new types of tracks to show NGS data such as individual raw reads, SNPs and InDels. (2) RNASeqBrowser can dynamically generate RNA secondary structure. It is useful for identifying non-coding RNA such as miRNA. (3) Overlaying NGS wiggle data is helpful in displaying differential expression and is simple to implement in RNASeqBrowser. (4) NGS data accumulates a lot of raw reads. Thus, RNASeqBrowser collapses exact duplicate reads to reduce visualization space. Normal PC's can show many windows of NGS individual raw reads without much delay. (5) Multiple popup windows of individual raw reads provide users with more viewing space. This avoids existing approaches (such as IGV) which squeeze all raw reads into one window. This will be helpful for visualizing multiple datasets simultaneously. RNASeqBrowser and its manual are freely available at http://www.australianprostatecentre.org/research/software/ rnaseqbrowser or http://sourceforge.net/projects/rnaseqbrowser/ [ABSTRACT FROM AUTHOR]

Background: RNA-Seq has become increasingly popular in transcriptome profiling. One aspect of transcriptome research is to quantify the expression levels of genomic elements, such as genes, their transcripts and exons. Acquiring a transcriptome expression profile requires genomic elements to be defined in the context of the genome. Multiple human genome annotation databases exist, including RefGene (RefSeq Gene), Ensembl, and the UCSC annotation database. The impact of the choice of an annotation on estimating gene expression remains insufficiently investigated. Results: In this paper, we systematically characterized the impact of genome annotation choice on read mapping and transcriptome quantification by analyzing a RNA-Seq dataset generated by the Human Body Map 2.0 Project. The impact of a gene model on mapping of non-junction reads is different from junction reads. For the RNA-Seq dataset with a read length of 75 bp, on average, 95% of non-junction reads were mapped to exactly the same genomic location regardless of which gene models was used. By contrast, this percentage dropped to 53% for junction reads. In addition, about 30% of junction reads failed to align without the assistance of a gene model, while 10-15% mapped alternatively. There are 21,958 common genes among RefGene, Ensembl, and UCSC annotations. When we compared the gene quantification results in RefGene and Ensembl annotations, 20% of genes are not expressed, and thus have a zero count in both annotations. Surprisingly, identical gene quantification results were obtained for only 16.3% (about one sixth) of genes. Approximately 28.1% of genes' expression levels differed by 5% or higher, and of those, the relative expression levels for 9.3% of genes (equivalent to 2038) differed by 50% or greater. The case studies revealed that the gene definition differences in gene models frequently result in inconsistency in gene quantification. Conclusions: We demonstrated that the choice of a gene model has a dramatic effect on both gene quantification and differential analysis. Our research will help RNA-Seq data analysts to make an informed choice of gene model in practical RNA-Seq data analysis. [ABSTRACT FROM AUTHOR]

Background: Transcription factors (TF) regulate gene expression by binding DNA regulatory regions. Transcription factor binding sites (TFBSs) are conserved not only in primary DNA sequences but also in DNA structures. However, the global relationship between TFs and their preferred DNA structures remains to be elucidated. Results: In this paper, we have developed a computational method to generate a genome-wide landscape of TFs and their characteristic binding DNA structures in Saccharomyces cerevisiae. We revealed DNA structural features for different TFs. The structural conservation shows positional preference in TFBSs. Structural levels of DNA sequences are correlated with TF-DNA binding affinities. Conclusions: We provided the genome-wide correspondences of TFs to DNA structures. Our findings will have implications in understanding TF regulatory mechanisms. [ABSTRACT FROM AUTHOR]

Essential proteins are vitally important for cellular survival and development, and identifying essential proteins is very meaningful research work in the post-genome era. Rapid increase of available protein-protein interaction (PPI) data has made it possible to detect protein essentiality at the network level. A series of centrality measures have been proposed to discover essential proteins based on the PPI networks. However, the PPI data obtained from large scale, high-throughput experiments generally contain false positives. It is insufficient to use original PPI data to identify essential proteins. How to improve the accuracy, has become the focus of identifying essential proteins. In this paper, we proposed a framework for identifying essential proteins from active PPI networks constructed with dynamic gene expression. Firstly, we process the dynamic gene expression profiles by using time-dependent model and time-independent model. Secondly, we construct an active PPI network based on co-expressed genes. Lastly, we apply six classical centrality measures in the active PPI network. For the purpose of comparison, other prediction methods are also performed to identify essential proteins based on the active PPI network. The experimental results on yeast network show that identifying essential proteins based on the active PPI network can improve the performance of centrality measures considerably in terms of the number of identified essential proteins and identification accuracy. At the same time, the results also indicate that most of essential proteins are active. [ABSTRACT FROM AUTHOR]

Background: With the development of several new technologies using synthetic biology, it is possible to engineer genetically intractable organisms including Mycoplasma mycoides subspecies capri (Mmc), by cloning the intact bacterial genome in yeast, using the host yeast's genetic tools to modify the cloned genome, and subsequently transplanting the modified genome into a recipient cell to obtain mutant cells encoded by the modified genome. The recently described tandem repeat coupled with endonuclease cleavage (TREC) method has been successfully used to generate seamless deletions and point mutations in the mycoplasma genome using the yeast DNA repair machinery. But, attempts to knock-in genes in some cases have encountered a high background of transformation due to maintenance of unwanted circularization of the transforming DNA, which contains possible autonomously replicating sequence (ARS) activity. To overcome this issue, we incorporated a split marker system into the TREC method, enabling seamless gene knock-in with high efficiency. The modified method is called TREC-assisted gene knock-in (TREC-IN). Since a gene to be knocked-in is delivered by a truncated non-functional marker, the background caused by an incomplete integration is essentially eliminated. Results: In this paper, we demonstrate applications of the TREC-IN method in gene complementation and genome minimization studies in Mmc. In the first example, the Mmc dnaA gene was seamlessly replaced by an orthologous gene, which shares a high degree of identity at the nucleotide level with the original Mmc gene, with high efficiency and low background. In the minimization example, we replaced an essential gene back into the genome that was present in the middle of a cluster of non-essential genes, while deleting the non-essential gene cluster, again with low backgrounds of transformation and high efficiency. Conclusion: Although we have demonstrated the feasibility of TREC-IN in gene complementation and genome minimization studies in Mmc, the applicability of TREC-IN ranges widely. This method proves to be a valuable genetic tool that can be extended for genomic engineering in other genetically intractable organisms, where it may be implemented in elucidating specific metabolic pathways and in rationale vaccine design. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via the original article. [ABSTRACT FROM AUTHOR]

Background: Sect. Tuberculata belongs to Camellia, and its members are characterized by a wrinkled pericarp and united filaments. All the plants in this group, which are endemic to China, are highly valuable for exploring the evolution of Camellia and have great potential for use as an oil source. However, due to the complex and diverse phenotypes of these species and the difficulty of investigating them in the field, their complex evolutionary history and interspecific definitions have remained largely unelucidated. Results: Therefore, we newly sequenced and annotated 12 chloroplast (cp) genomes and retrieved the published cp genome of Camellia anlungensis Chang in sect. Tuberculata. In this study, comparative analysis of the cp genomes of the thirteen sect. Tuberculata species revealed a typical quadripartite structure characterized by a total sequence length ranging from 156,587 bp to 157,068 bp. The cp.genome arrangement is highly conserved and moderately differentiated. A total of 130 to 136 genes specific to the three types were identified by annotation, including protein-coding genes (coding sequences (CDSs)) (87–91), tRNA genes (35–37), and rRNA genes (8). The total observed frequency ranged from 23,045 (C. lipingensis) to 26,557 (C. anlungensis). IR region boundaries were analyzed to show that the ycf1 gene of C. anlungensis is located in the IRb region, while the remaining species are present only in the IRa region. Sequence variation in the SSC region is greater than that in the IR region, and most protein-coding genes have high codon preferences. Comparative analyses revealed six hotspot regions (tRNA-Thr(GGT)-psbD, psbE-petL, ycf15-tRNA-Leu(CAA), ndhF-rpl32, ndhD, and trnL(CAA)-ycf15) in the cp genomes that could serve as potential molecular markers. In addition, the results of phylogenetic tree construction based on the cp genomes showed that the thirteen sect. Tuberculata species formed a monophyletic group and were divided into two evolutionarily independent clades, confirming the independence of the section. Conclusions: In summary, we obtained the cp genomes of thirteen sect. Tuberculata plants and performed the first comparative analysis of this group. These results will help us better characterize the plants in this section, deepen our understanding of their genetic characteristics and phylogenetic relationships, and lay the theoretical foundation for their accurate classification, elucidation of their evolutionary changes, and rational development and utilization of this section in the future. [ABSTRACT FROM AUTHOR]

Background: Despite the many cheap and fast ways to generate genomic data, good and exact genome assembly is still a problem, with especially the repeats being vastly underrepresented and often misassembled. As short reads in low coverage are already sufficient to represent the repeat landscape of any given genome, many read cluster algorithms were brought forward that provide repeat identification and classification. But how can trustworthy, reliable and representative repeat consensuses be derived from unassembled genomes? Results: Here, we combine methods from repeat identification and genome assembly to derive these robust consensuses. We test several use cases, such as (1) consensus building from clustered short reads of non-model genomes, (2) from genome-wide amplification setups, and (3) specific repeat-centred questions, such as the linked vs. unlinked arrangement of ribosomal genes. In all our use cases, the derived consensuses are robust and representative. To evaluate overall performance, we compare our high-fidelity repeat consensuses to RepeatExplorer2-derived contigs and check, if they represent real transposable elements as found in long reads. Our results demonstrate that it is possible to generate useful, reliable and trustworthy consensuses from short reads by a combination from read cluster and genome assembly methods in an automatable way. Conclusion: We anticipate that our workflow opens the way towards more efficient and less manual repeat characterization and annotation, benefitting all genome studies, but especially those of non-model organisms. [ABSTRACT FROM AUTHOR]

Background: Spodoptera litura is a harmful pest that feeds on more than 80 species of plants, and can be infected and killed by Spodoptera litura nucleopolyhedrovirus (SpltNPV). SpltNPV-C3 is a type C SpltNPV clone, that was observed and collected in Japan. Compared with type A or type B SpltNPVs, SpltNPV-C3 can cause the rapid mortality of S. litura larvae. Methods: In this study, occlusion bodies (OBs) and occlusion-derived viruses (ODVs) of SpltNPV-C3 were purified, and OBs were observed by scanning electron microscopy (SEM). ODVs were observed under a transmission electron microscope (TEM). Results: Both OBs and ODVs exhibit morphological characteristics typical of nucleopolyhedroviruses (NPVs).The genome of SpltNPV-C3 was sequenced and analyzed; the total length was 148,634 bp (GenBank accession 780,426,which was submitted as SpltNPV-II), with a G + C content of 45%. A total of 149 predicted ORFs were found. A phylogenetic tree of 90 baculoviruses was constructed based on core baculovirus genes. LC‒MS/MS was used to analyze the proteins of SpltNPV-C3; 34 proteins were found in the purified ODVs, 15 of which were core proteins. The structure of the complexes formed by per os infectivity factors 1, 2, 3 and 4 (PIF-1, PIF-2, PIF-3 and PIF-4) was predicted with the help of the AlphaFold multimer tool and predicted conserved sequences in PIF-3. SpltNPV-C3 is a valuable species because of its virulence, and the analysis of its genome and proteins in this research will be beneficial for pest control efforts. [ABSTRACT FROM AUTHOR]

Background: Beyond the massive amounts of DNA and genes transferred from the protoorganelle genome to the nucleus during the endosymbiotic event that gave rise to the plastids, stretches of plastid DNA of varying size are still being copied and relocated to the nuclear genome in a process that is ongoing and does not result in the concomitant shrinking of the plastid genome. As a result, plant nuclear genomes feature small, but variable, fraction of their genomes of plastid origin, the so-called nuclear plastid DNA sequences (NUPTs). However, the mechanisms underlying the origin and fixation of NUPTs are not yet fully elucidated and research on the topic has been mostly focused on a limited number of species and of plastid DNA. Results: Here, we leveraged a chromosome-scale version of the genome of the orphan crop Moringa oleifera, which features the largest fraction of plastid DNA in any plant nuclear genome known so far, to gain insights into the mechanisms of origin of NUPTs. For this purpose, we examined the chromosomal distribution and arrangement of NUPTs, we explicitly modeled and tested the correlation between their age and size distribution, we characterized their sites of origin at the chloroplast genome and their sites of insertion at the nuclear one, as well as we investigated their arrangement in clusters. We found a bimodal distribution of NUPT relative ages, which implies NUPTs in moringa were formed through two separate events. Furthermore, NUPTs from every event showed markedly distinctive features, suggesting they originated through distinct mechanisms. Conclusions: Our results reveal an unanticipated complexity of the mechanisms at the origin of NUPTs and of the evolutionary forces behind their fixation and highlight moringa species as an exceptional model to assess the impact of plastid DNA in the evolution of the architecture and function of plant nuclear genomes. [ABSTRACT FROM AUTHOR]

Databases of genome sequences are growing exponentially, but, in some cases, assembly is incomplete and genes are poorly annotated. For evolutionary studies, it is important to identify all members of a given gene family in a genome. We developed a method for identifying most, if not all, members of a gene family from raw genomes in which assembly is of low quality, using the P-type ATPase superfamily as an example. The method is based on the translation of an entire genome in all six reading frames and the co-occurrence of two family-specific sequence motifs that are in close proximity to each other. To test the method's usability, we first used it to identify P-type ATPase members in the high-quality annotated genome of barley (Hordeum vulgare). Subsequently, after successfully identifying plasma membrane H+-ATPase family members (P3A ATPases) in various plant genomes of varying quality, we tested the hypothesis that the number of P3A ATPases correlates with the ability of the plant to tolerate saline conditions. In 19 genomes of glycophytes and halophytes, the total number of P3A ATPase genes was found to vary from 7 to 22, but no significant difference was found between the two groups. The method successfully identified P-type ATPase family members in raw genomes that are poorly assembled. [ABSTRACT FROM AUTHOR]

Background: Chiloschista (Orchidaceae, Aeridinae) is an epiphytic leafless orchid that is mainly distributed in tropical or subtropical forest canopies. This rare and threatened orchid lacks molecular resources for phylogenetic and barcoding analysis. Therefore, we sequenced and assembled seven complete plastomes of Chiloschista to analyse the plastome characteristics and phylogenetic relationships and conduct a barcoding investigation. Results: We are the first to publish seven Chiloschista plastomes, which possessed the typical quadripartite structure and ranged from 143,233 bp to 145,463 bp in size. The plastomes all contained 120 genes, consisting of 74 protein-coding genes, 38 tRNA genes and eight rRNA genes. The ndh genes were pseudogenes or lost in the genus, and the genes petG and psbF were under positive selection. The seven Chiloschista plastomes displayed stable plastome structures with no large inversions or rearrangements. A total of 14 small inversions (SIs) were identified in the seven Chiloschista plastomes but were all similar within the genus. Six noncoding mutational hotspots (trnNGUU–rpl32 > rpoB–trnCGCA > psbK–psbI > psaC–rps15 > trnEUUC–trnTGGU > accD–psaI) and five coding sequences (ycf1 > rps15 > matK > psbK > ccsA) were selected as potential barcodes based on nucleotide diversity and species discrimination analysis, which suggested that the potential barcode ycf1 was most suitable for species discrimination. A total of 47–56 SSRs and 11–14 long repeats (> 20 bp) were identified in Chiloschista plastomes, and they were mostly located in the large single copy intergenic region. Phylogenetic analysis indicated that Chiloschista was monophyletic. It was clustered with Phalaenopsis and formed the basic clade of the subtribe Aeridinae with a moderate support value. The results also showed that seven Chiloschista species were divided into three major clades with full support. Conclusion: This study was the first to analyse the plastome characteristics of the genus Chiloschista in Orchidaceae, and the results showed that Chiloschista plastomes have conserved plastome structures. Based on the plastome hotspots of nucleotide diversity, several genes and noncoding regions are suitable for phylogenetic and population studies. Chiloschista may provide an ideal system to investigate the dynamics of plastome evolution and DNA barcoding investigation for orchid studies. [ABSTRACT FROM AUTHOR]

Terpenoids are important compounds associated with the pest and herbivore resistance mechanisms of plants; consequently, it is essential to identify and explore terpene synthase (TPS) genes in maize. In the present study, we identified 31 TPS genes based on a pan-genome of 26 high-quality maize genomes containing 20 core genes (present in all 26 lines), seven dispensable genes (present in 2 to 23 lines), three near-core genes (present in 24 to 25 lines), and one private gene (present in only 1 line). Evaluation of ka/ks values of TPS in 26 varieties revealed that TPS25 was subjected to positive selection in some varieties. Six ZmTPS had ka/ks values less than 1, indicating that they were subjected to purifying selection. In 26 genomes, significant differences were observed in ZmTPS25 expression between genes affected by structural variation (SV) and those not affected by SV. In some varieties, SV altered the conserved structural domains resulting in a considerable number of atypical genes. The analysis of RNA-seq data of maize Ostrinia furnacalis feeding revealed 10 differentially expressed ZmTPS, 9 of which were core genes. However, many atypical genes for these responsive genes were identified in several genomes. These findings provide a novel resource for functional studies of ZmTPS. [ABSTRACT FROM AUTHOR]

Background Oil palm is an important perennial oil crop with an extremely long selection cycle of 10 to 12 years. As such, any tool that speeds up its genetic improvement process, such as markerassisted breeding is invaluable. Previously, genetic linkage maps based on AFLP, RFLP and SSR markers were developed and QTLs for fatty acid composition and yield components identified. High density genetic maps of crosses of different genetic backgrounds are indispensable tools for investigating oil palm genetics. They are also useful for comparative mapping analyses to identify markers closely linked to traits of interest. Results A 4.5 K customized oil palm SNP array was developed using the Illumina Infinium platform. The SNPs and 252 SSRs were genotyped on two mapping populations, an intraspecific cross with 87 palms and an interspecific cross with 108 palms. Parental maps with 16 (LGs) linkage groups were constructed for the three fruit forms of E. guineensis (dura, pisifera and tenera). Map resolution was further increased by integrating the dura and pisifera maps into an intraspecific integrated map with 1,331 markers spanning 1,867 cM. We also report the first map of a Colombian E. oleifera, comprising 10 LGs with 65 markers spanning 471 cM. Although not very dense due to the high level of homozygosity in E. oleifera, the LGs were successfully integrated with the LGs of the tenera map. Direct comparison between the parental maps identified 603 transferable markers polymorphic in at least two of the parents. Further analysis revealed a high degree of marker transferability covering 1,075 cM, between the intra- and interspecific integrated maps. The interspecific cross displayed higher segregation distortion than the intraspecific cross. However, inclusion of distorted markers in the genetic maps did not disrupt the marker order and no map expansion was observed. Conclusions The high density SNP and SSR-based genetic maps reported in this paper have greatly improved marker density and genome coverage in comparison with the first reference map based on AFLP and SSR markers. Therefore, it is foreseen that they will be more useful for fine mapping of QTLs and whole genome association mapping studies in oil palm. [ABSTRACT FROM AUTHOR]