We present an open-source web platform, Ginkgo (http://qb.cshl.edu/ginkgo), for the analysis and assessment of single-cell copy-number variations (CNVs). Ginkgo automatically constructs copy-number profiles of cells from mapped reads and constructs phylogenetic trees of related cells. We validate Ginkgo by reproducing the results of five major studies and examine the characteristics of three commonly used single-cell amplification techniques to conclude degenerate oligonucleotide-primed PCR to be the most consistent for CNV analysis.
BackgroundParrots belong to a group of behaviorally advanced vertebrates and have an advanced ability of vocal learning relative to other vocal-learning birds. They can imitate human speech, synchronize their body movements to a rhythmic beat, and understand complex concepts of referential meaning to sounds. However, little is known about the genetics of these traits. Elucidating the genetic bases would require whole genome sequencing and a robust assembly of a parrot genome.FindingsWe present a genomic resource for the budgerigar, an Australian Parakeet (Melopsittacus undulatus) -- the most widely studied parrot species in neuroscience and behavior. We present genomic sequence data that includes over 300× raw read coverage from multiple sequencing technologies and chromosome optical maps from a single male animal. The reads and optical maps were used to create three hybrid assemblies representing some of the largest genomic scaffolds to date for a bird; two of which were annotated based on similarities to reference sets of non-redundant human, zebra finch and chicken proteins, and budgerigar transcriptome sequence assemblies. The sequence reads for this project were in part generated and used for both the Assemblathon 2 competition and the first de novo assembly of a giga-scale vertebrate genome utilizing PacBio single-molecule sequencing.ConclusionsAcross several quality metrics, these budgerigar assemblies are comparable to or better than the chicken and zebra finch genome assemblies built from traditional Sanger sequencing reads, and are sufficient to analyze regions that are difficult to sequence and assemble, including those not yet assembled in prior bird genomes, and promoter regions of genes differentially regulated in vocal learning brain regions. This work provides valuable data and material for genome technology development and for investigating the genomics of complex behavioral traits.
Summary Ribbon is an alignment visualization tool that shows how alignments are positioned within both the reference and read contexts, giving an intuitive view that enables a better understanding of structural variants and the read evidence supporting them. Ribbon was born out of a need to curate complex structural variant calls and determine whether each was well supported by long-read evidence, and it uses the same intuitive visualization method to shed light on contig alignments from genome-to-genome comparisons. Availability and Implementation Ribbon is freely available online at http://genomeribbon.com/ and is open-source at https://github.com/marianattestad/ribbon. Supplementary information Supplementary data are available at Bioinformatics online.
Big science is on the rise. Recent endeavors, such as the Large Hadron Collider and the Human Genome Project, illustrate the rise in large-scale scientific inquiries. To assess whether big science is part of a general trend towards increased authorship, we queried the publicly available database Pubmed and measured the trend in number of authors per paper over the last century. Here we show that authorship has increased five-fold since 1913 and predict that by 2034, publications will boast an average of 8 authors.
A central challenge in sequencing single-cell genomes is the accurate determination of point mutations, phasing of these mutations, and identifying copy number variations with few assumptions. Ideally, this is accomplished under as low sequencing coverage as possible. Here we report our attempt to meet these goals with a novel library construction and library amplification methodology. In our approach, single-cell genomic DNA is first fragmented with saturated transposition to make a primary library that uniformly covers the whole genome by short fragments. The library is then amplified by a carefully optimized PCR protocol in a uniform and synchronized fashion for next-generation sequencing. Each step of the protocol can be quantitatively characterized. Our shallow sequencing data show that the library is tightly distributed and is useful for the determination of copy number variations.
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