As next-generation sequencing projects generate massive genome-wide sequence variation data, bioinformatics tools are being developed to provide computational predictions on the functional effects of sequence variations and narrow down the search of casual variants for disease phenotypes. Different classes of sequence variations at the nucleotide level are involved in human diseases, including substitutions, insertions, deletions, frameshifts, and non-sense mutations. Frameshifts and non-sense mutations are likely to cause a negative effect on protein function. Existing prediction tools primarily focus on studying the deleterious effects of single amino acid substitutions through examining amino acid conservation at the position of interest among related sequences, an approach that is not directly applicable to insertions or deletions. Here, we introduce a versatile alignment-based score as a new metric to predict the damaging effects of variations not limited to single amino acid substitutions but also in-frame insertions, deletions, and multiple amino acid substitutions. This alignment-based score measures the change in sequence similarity of a query sequence to a protein sequence homolog before and after the introduction of an amino acid variation to the query sequence. Our results showed that the scoring scheme performs well in separating disease-associated variants (n = 21,662) from common polymorphisms (n = 37,022) for UniProt human protein variations, and also in separating deleterious variants (n = 15,179) from neutral variants (n = 17,891) for UniProt non-human protein variations. In our approach, the area under the receiver operating characteristic curve (AUC) for the human and non-human protein variation datasets is ∼0.85. We also observed that the alignment-based score correlates with the deleteriousness of a sequence variation. In summary, we have developed a new algorithm, PROVEAN (Protein Variation Effect Analyzer), which provides a generalized approach to predict the functional effects of protein sequence variations including single or multiple amino acid substitutions, and in-frame insertions and deletions. The PROVEAN tool is available online at http://provean.jcvi.org.

Supplementary data are available at Bioinformatics online.

The flowering plant Arabidopsis thaliana is a dicot model organism for research in many aspects of plant biology. A comprehensive annotation of its genome paves the way for understanding the functions and activities of all types of transcripts, including mRNA, the various classes of non-coding RNA, and small RNA. The TAIR10 annotation update had a profound impact on Arabidopsis research but was released more than 5 years ago. Maintaining the accuracy of the annotation continues to be a prerequisite for future progress. Using an integrative annotation pipeline, we assembled tissue-specific RNA-Seq libraries from 113 datasets and constructed 48 359 transcript models of protein-coding genes in eleven tissues. In addition, we annotated various classes of non-coding RNA including microRNA, long intergenic RNA, small nucleolar RNA, natural antisense transcript, small nuclear RNA, and small RNA using published datasets and in-house analytic results. Altogether, we identified 635 novel protein-coding genes, 508 novel transcribed regions, 5178 non-coding RNAs, and 35 846 small RNA loci that were formerly unannotated. Analysis of the splicing events and RNA-Seq based expression profiles revealed the landscapes of gene structures, untranslated regions, and splicing activities to be more intricate than previously appreciated. Furthermore, we present 692 uniformly expressed housekeeping genes, 43% of whose human orthologs are also housekeeping genes. This updated Arabidopsis genome annotation with a substantially increased resolution of gene models will not only further our understanding of the biological processes of this plant model but also of other species.

Castor bean (Ricinus communis) is an oil crop that belongs to the spurge (Euphorbiaceae) family. Its seeds are the source of castor oil, used for the production of high-quality lubricants due to its high proportion of the unusual fatty acid ricinoleic acid. Castor bean seeds also produce ricin, a highly toxic ribosome inactivating protein, making castor bean relevant for biosafety. We report here the 4.6X draft genome sequence of castor bean, representing the first reported Euphorbiaceae genome sequence. Our analysis shows that most key castor oil metabolism genes are single-copy while the ricin gene family is larger than previously thought. Comparative genomics analysis suggests the presence of an ancient hexaploidization event that is conserved across the dicotyledonous lineage.

Approximately 80% of the maize genome comprises highly repetitive sequences interspersed with single-copy, gene-rich sequences, and standard genome sequencing strategies are not readily adaptable to this type of genome. Methodologies that enrich for genic sequences might more rapidly generate useful results from complex genomes. Equivalent numbers of clones from maize selected by techniques called methylation filtering and High C0t selection were sequenced to generate approximately 200,000 reads (approximately 132 megabases), which were assembled into contigs. Combination of the two techniques resulted in a sixfold reduction in the effective genome size and a fourfold increase in the gene identification rate in comparison to a nonenriched library.

Humans are a diploid species that inherit one set of chromosomes paternally and one homologous set of chromosomes maternally. Unfortunately, most human sequencing initiatives ignore this fact in that they do not directly delineate the nucleotide content of the maternal and paternal copies of the 23 chromosomes individuals possess (i.e., they do not ‘phase’ the genome) often because of the costs and complexities of doing so. We compared 11 different widely-used approaches to phasing human genomes using the publicly available ‘Genome-In-A-Bottle’ (GIAB) phased version of the NA12878 genome as a gold standard. The phasing strategies we compared included laboratory-based assays that prepare DNA in unique ways to facilitate phasing as well as purely computational approaches that seek to reconstruct phase information from general sequencing reads and constructs or population-level haplotype frequency information obtained through a reference panel of haplotypes. To assess the performance of the 11 approaches, we used metrics that included, among others, switch error rates, haplotype block lengths, the proportion of fully phase-resolved genes, phasing accuracy and yield between pairs of SNVs. Our comparisons suggest that a hybrid or combined approach that leverages: 1. population-based phasing using the SHAPEIT software suite, 2. either genome-wide sequencing read data or parental genotypes, and 3. a large reference panel of variant and haplotype frequencies, provides a fast and efficient way to produce highly accurate phase-resolved individual human genomes. We found that for population-based approaches, phasing performance is enhanced with the addition of genome-wide read data; e.g., whole genome shotgun and/or RNA sequencing reads. Further, we found that the inclusion of parental genotype data within a population-based phasing strategy can provide as much as a ten-fold reduction in phasing errors. We also considered a majority voting scheme for the construction of a consensus haplotype combining multiple predictions for enhanced performance and site coverage. Finally, we also identified DNA sequence signatures associated with the genomic regions harboring phasing switch errors, which included regions of low polymorphism or SNV density.

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The TIGR Plant Transcript Assemblies (TA) database () uses expressed sequences collected from the NCBI GenBank Nucleotide database for the construction of transcript assemblies. The sequences collected include expressed sequence tags (ESTs) and full-length and partial cDNAs, but exclude computationally predicted gene sequences. The TA database includes all plant species for which more than 1000 EST or cDNA sequences are publicly available. The EST and cDNA sequences are first clustered based on an all-versus-all pairwise sequence comparison, followed by the generation of consensus sequences (TAs) from individual clusters. The clustering and assembly procedures use the TGICL tool, Megablast and the CAP3 assembler. The UniProt Reference Clusters (UniRef100) protein database is used as the reference database for the functional annotation of the assemblies. The transcription orientation of each TA is determined based on the orientation of the alignment with the best protein hit. The TA sequences and annotation are available via web interfaces and FTP downloads. Assemblies can be retrieved by a text-based keyword search or a sequence-based BLAST search. The current version of the TA database is Release 2 (July 17, 2006) and includes a total of 215 plant species.