Molecular pixelation: spatial proteomics of single cells by sequencing.

The spatial distribution of cell surface proteins governs vital processes of the immune system such as intercellular communication and mobility. However, fluorescence microscopy has limited scalability in the multiplexing and throughput needed to drive spatial proteomics discoveries at subcellular level. We present Molecular Pixelation (MPX), an optics-free, DNA sequence-based method for spatial proteomics of single cells using antibody-oligonucleotide conjugates (AOCs) and DNA-based, nanometer-sized molecular pixels. The relative locations of AOCs are inferred by sequentially associating them into local neighborhoods using the sequence-unique DNA pixels, forming >1,000 spatially connected zones per cell in 3D. For each single cell, DNA-sequencing reads are computationally arranged into spatial proteomics networks for 76 proteins. By studying immune cell dynamics using spatial statistics on graph representations of the data, we identify known and new patterns of spatial organization of proteins on chemokine-stimulated T cells, highlighting the potential of MPX in defining cell states by the spatial arrangement of proteins.

Resolving the full spectrum of human genome variation using Linked-Reads.

Large-scale population analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. To date, this diversity has largely been uncovered using short-read whole-genome sequencing. However, these short-read approaches fail to give a complete picture of a genome. They struggle to identify structural events, cannot access repetitive regions, and fail to resolve the human genome into haplotypes. Here, we describe an approach that retains long range information while maintaining the advantages of short reads. Starting from ∼1 ng of high molecular weight DNA, we produce barcoded short-read libraries. Novel informatic approaches allow for the barcoded short reads to be associated with their original long molecules producing a novel data type known as "Linked-Reads". This approach allows for simultaneous detection of small and large variants from a single library. In this manuscript, we show the advantages of Linked-Reads over standard short-read approaches for reference-based analysis. Linked-Reads allow mapping to 38 Mb of sequence not accessible to short reads, adding sequence in 423 difficult-to-sequence genes including disease-relevant genes STRC, SMN1, and SMN2 Both Linked-Read whole-genome and whole-exome sequencing identify complex structural variations, including balanced events and single exon deletions and duplications. Further, Linked-Reads extend the region of high-confidence calls by 68.9 Mb. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone.

Integrating T cell receptor sequences and transcriptional profiles by clonotype neighbor graph analysis (CoNGA).

Links between T cell clonotypes, as defined by T cell receptor (TCR) sequences, and phenotype, as reflected in gene expression (GEX) profiles, surface protein expression and peptide:major histocompatibility complex binding, can reveal functional relationships beyond the features shared by clonally related cells. Here we present clonotype neighbor graph analysis (CoNGA), a graph theoretic approach that identifies correlations between GEX profile and TCR sequence through statistical analysis of GEX and TCR similarity graphs. Using CoNGA, we uncovered associations between TCR sequence and GEX profiles that include a previously undescribed 'natural lymphocyte' population of human circulating CD8+ T cells and a set of TCR sequence determinants of differentiation in thymocytes. These examples show that CoNGA might help elucidate complex relationships between TCR sequence and T cell phenotype in large, heterogeneous, single-cell datasets.

Benchmarking challenging small variants with linked and long reads.

Genome in a Bottle benchmarks are widely used to help validate clinical sequencing pipelines and develop variant calling and sequencing methods. Here we use accurate linked and long reads to expand benchmarks in 7 samples to include difficult-to-map regions and segmental duplications that are challenging for short reads. These benchmarks add more than 300,000 SNVs and 50,000 insertions or deletions (indels) and include 16% more exonic variants, many in challenging, clinically relevant genes not covered previously, such as PMS2. For HG002, we include 92% of the autosomal GRCh38 assembly while excluding regions problematic for benchmarking small variants, such as copy number variants, that should not have been in the previous version, which included 85% of GRCh38. It identifies eight times more false negatives in a short read variant call set relative to our previous benchmark. We demonstrate that this benchmark reliably identifies false positives and false negatives across technologies, enabling ongoing methods development.

A diploid assembly-based benchmark for variants in the major histocompatibility complex.

Most human genomes are characterized by aligning individual reads to the reference genome, but accurate long reads and linked reads now enable us to construct accurate, phased de novo assemblies. We focus on a medically important, highly variable, 5 million base-pair (bp) region where diploid assembly is particularly useful - the Major Histocompatibility Complex (MHC). Here, we develop a human genome benchmark derived from a diploid assembly for the openly-consented Genome in a Bottle sample HG002. We assemble a single contig for each haplotype, align them to the reference, call phased small and structural variants, and define a small variant benchmark for the MHC, covering 94% of the MHC and 22368 variants smaller than 50 bp, 49% more variants than a mapping-based benchmark. This benchmark reliably identifies errors in mapping-based callsets, and enables performance assessment in regions with much denser, complex variation than regions covered by previous benchmarks.

Author Correction: A robust benchmark for detection of germline large deletions and insertions.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A robust benchmark for detection of germline large deletions and insertions.

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution and comprehensiveness. To help translate these methods to routine research and clinical practice, we developed a sequence-resolved benchmark set for identification of both false-negative and false-positive germline large insertions and deletions. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle Consortium integrated 19 sequence-resolved variant calling methods from diverse technologies. The final benchmark set contains 12,745 isolated, sequence-resolved insertion (7,281) and deletion (5,464) calls ≥50 base pairs (bp). The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.51 Gbp and 5,262 insertions and 4,095 deletions supported by ≥1 diploid assembly. We demonstrate that the benchmark set reliably identifies false negatives and false positives in high-quality SV callsets from short-, linked- and long-read sequencing and optical mapping.

Annotation and visualization of endogenous retroviral sequences using the Distributed Annotation System (DAS) and eBioX.

BACKGROUND: The Distributed Annotation System (DAS) is a widely used network protocol for sharing biological information. The distributed aspects of the protocol enable the use of various reference and annotation servers for connecting biological sequence data to pertinent annotations in order to depict an integrated view of the data for the final user. RESULTS: An annotation server has been devised to provide information about the endogenous retroviruses detected and annotated by a specialized in silico tool called RetroTector. We describe the procedure to implement the DAS 1.5 protocol commands necessary for constructing the DAS annotation server. We use our server to exemplify those steps. Data distribution is kept separated from visualization which is carried out by eBioX, an easy to use open source program incorporating multiple bioinformatics utilities. Some well characterized endogenous retroviruses are shown in two different DAS clients. A rapid analysis of areas free from retroviral insertions could be facilitated by our annotations. CONCLUSION: The DAS protocol has shown to be advantageous in the distribution of endogenous retrovirus data. The distributed nature of the protocol is also found to aid in combining annotation and visualization along a genome in order to enhance the understanding of ERV contribution to its evolution. Reference and annotation servers are conjointly used by eBioX to provide visualization of ERV annotations as well as other data sources. Our DAS data source can be found in the central public DAS service repository, http://www.dasregistry.org, or at http://loka.bmc.uu.se/das/sources.

The first sequenced carnivore genome shows complex host-endogenous retrovirus relationships.

Host-retrovirus interactions influence the genomic landscape and have contributed substantially to mammalian genome evolution. To gain further insights, we analyzed a female boxer (Canis familiaris) genome for complexity and integration pattern of canine endogenous retroviruses (CfERV). Intriguingly, the first such in-depth analysis of a carnivore species identified 407 CfERV proviruses that represent only 0.15% of the dog genome. In comparison, the same detection criteria identified about six times more HERV proviruses in the human genome that has been estimated to contain a total of 8% retroviral DNA including solitary LTRs. These observed differences in man and dog are likely due to different mechanisms to purge, restrict and protect their genomes against retroviruses. A novel group of gammaretrovirus-like CfERV with high similarity to HERV-Fc1 was found to have potential for active retrotransposition and possibly lateral transmissions between dog and human as a result of close interactions during at least 10.000 years. The CfERV integration landscape showed a non-uniform intra- and inter-chromosomal distribution. Like in other species, different densities of ERVs were observed. Some chromosomal regions were essentially devoid of CfERVs whereas other regions had large numbers of integrations in agreement with distinct selective pressures at different loci. Most CfERVs were integrated in antisense orientation within 100 kb from annotated protein-coding genes. This integration pattern provides evidence for selection against CfERVs in sense orientation relative to chromosomal genes. In conclusion, this ERV analysis of the first carnivorous species supports the notion that different mammals interact distinctively with endogenous retroviruses and suggests that retroviral lateral transmissions between dog and human may have occurred.