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.

Linking immune receptor sequence to transcriptional states with clonotype neighbor graph analysis (CoNGA)

Recent advances now allow for deep simultaneous profiling of T cell clonotypes, defined by T cell receptor (TCR) sequence, and phenotype, as reflected in gene expression (GEX) profile, surface protein expression, and epitope binding at the single-cell-level. However, there currently few tools available for unsupervised discovery of relationships between TCR sequence and cell phenotype. We hypothesized that by identifying correlations between “TCR neighborhoods”, defined by shared TCR sequence and GEX features, we could move beyond simply measuring GEX variation within clonal descendants and identify novel associations between T cell specificities and states. Previously, we introduced TCRdist, a measure for assessing inter-TCR similarity capable of identifying closely related clonotypes based on shared sequence features. Using TCRdist to quantify TCR similarity, we developed a graph-theoretic approach—clonotype neighbor-graph analysis or “CoNGA”—that identifies correlations between GEX profile and TCR sequence in an unbiased and automated manner through statistical analysis of GEX and TCR similarity graphs. Applying CoNGA, we uncovered novel associations between TCR and GEX space including a previously undescribed “natural lymphocyte” population of human blood CD8+ T cells; an association between TRBV gene usage and EPHB6 expression; and TCR sequence determinants of differentiation in thymocytes. These examples demonstrate that CoNGA is able to effectively deconvolve complex relationships between TCR sequence and cellular state. Conceptually, CoNGA could be extended to other clonally-related populations (e.g. B cells, tumors), and can easily incorporate other measurable features (e.g. ATAC-Seq).

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.

The genomic footprint of sexual conflict

Genes with sex-biased expression show a number of unique properties and this has been seen as evidence for conflicting selection pressures in males and females, forming a genetic ‘tug-of-war’ between the sexes. However, we lack studies of taxa where an understanding of conflicting phenotypic selection in the sexes has been linked with studies of genomic signatures of sexual conflict. Here, we provide such a link. We used an insect where sexual conflict is unusually well understood, the seed beetle Callosobruchus maculatus, to test for molecular genetic signals of sexual conflict across genes with varying degrees of sex-bias in expression. We sequenced, assembled and annotated its genome and performed population resequencing of three divergent populations. Sex-biased genes showed increased levels of genetic diversity and bore a remarkably clear footprint of relaxed purifying selection. Yet, segregating genetic variation was also affected by balancing selection in weakly female-biased genes, while male-biased genes showed signs of overall purifying selection. Female-biased genes contributed disproportionally to shared polymorphism across populations, while male-biased genes, male seminal fluid protein genes and sex-linked genes did not. Genes showing genomic signatures consistent with sexual conflict generally matched life-history phenotypes known to experience sexually antagonistic selection in this species. Our results highlight metabolic and reproductive processes, confirming the key role of general life-history traits in sexual conflict.

Scalable and comprehensive characterization of antigen-specific CD8 T cells using multi-omics single cell analysis

Understanding the antigen binding specificities of lymphocytes is key to the development of effective therapeutics for cancers and infectious diseases. Recent technological advancements have enabled the integration of simultaneous cell-surface protein, transcriptome, immune repertoire and antigen specificity measurements at single cell resolution, providing comprehensive, scalable, high-throughput characterization of immune cells.

Using the 10x Genomics Single Cell Immune Profiling Solution with Feature Barcoding technology with 14 oligo-conjugated antibodies and 50 Immudex peptide-MHC I Dextramer reagents (pMHC) panels spanning different CMV, EBV, Influenza, HIV and Cancer antigens, we performed multi-omic characterization of ~100,000 CD8+ T cells from four MHC-matched donors. The multi-omic combination of gene expression, paired alpha/beta T cell receptor (TCR) repertoire, cell surface proteins and pMHC binding specificity allowed the identification of CD8+ T cell subpopulations with specificity for pMHCs within our panel. We observed multiple TCRs that bound the same pMHC and identified enriched amino acid motifs within TCR sequences that shared specificities. We compared the CDR3 amino acid sequences of the pMHC-specific TCR clonotypes with previously reported sequences with the same binding specificities to show that we could identify new and known CDR3 sequences. This analytical framework provides a systematic and scalable method for deciphering TCR–pMHC specificity combined with cellular phenotype identity which is critical for developing a better understanding of the adaptive immune response to cancer and infectious diseases and will be key in the development of successful immunotherapies.

An advancement in single cell genomics allows for T cell population analysis at high resolution

Progress in our understanding of immunology and cancer immunotherapies requires a comprehensive view of immune cell behavior and the interactions of these cells with their environment. Recent technological innovations have facilitated the combination of cell-surface protein, transcriptome, immune repertoire, and antigen specificity measurements from the same single cells, providing thorough and high-throughput lymphocyte characterization.

Using the 10x Genomics Single Cell Immune Profiling Solution with Feature Barcoding technology along with oligo-conjugated antibodies and peptide-MHC (pMHC) Dextramers®, we performed multi-omic characterization of PBMCs from cytomegalovirus (CMV) seronegative and seropositive patients. Next generation sequencing libraries were made following the 10x Genomics workflows, where transcriptome and immune repertoire libraries are generated alongside libraries from DNA barcodes conjugated to antibodies or pMHC.

Full length, paired TCRα/β sequences with specificity to known CMV antigens were identified in the seropositive donor, but not in the seronegative donor. Interestingly, a large Epstein Barr Virus (EBV) pMHC specific T cell expansion was identified in the CMV seronegative donor, suggesting an active EBV response. Moreover, the combination of transcriptomic and cell surface protein information resulted in an increase in resolution of cell type identification. This multi-omic workflow allowed the identification of enriched amino acid motifs within the TCR sequences that contained novel and known CDR3 amino acid sequences specific to CMV.

These technological advancements provide new biological insights that are critical for progress in the field.

Deep characterization of tumor microenvironments using single cell multi-omics analysis

Understanding the complexity of cell interactions in the tumor microenvironment (TME) requires the ability to distinguish each cell type, and is a prerequisite of personalized cancer treatments. Here, we use a fully integrated system for single cell RNA sequencing, to simultaneously profile the transcriptome, cell surface proteins and immune repertoire of cells from primary colorectal cancer (CRC), non-small cell lung cancer (NSCLC), and mucosa-associated lymphoid tissue (MALT) lymphoma. Each tumor varied in type and proportion of its cellular components, and in particular in the proportion of immune cells. The CRC tumor consisted of T (3% CD4+, 3% CD8+), B lymphocytes (5% CD79A+) and plasma B cells (11% IGH high). Repertoire sequencing identified a clonal expansion (>4% of B cell clonotypes) suggesting a strong B cell response in this tumor. The NSCLC tumor displayed a marked immune cell infiltration containing predominantly B cells (30% CD79A+ and 8% IGH high plasma B) with a very limited clonal expansion. The MALT lymphoma consisted of only T and B lymphocytes (31% CD4+, 8% CD8+, 57% CD79A+). In addition to the activated CD4+ and CD8+ T cells, Tfh and Treg cells were clearly identified as well as two distinct large B cell populations showing plasmacytic differentiation. Analysis of the B cell repertoire revealed a large expanded clone bearing an IGHV segment associated with parotid MALT lymphoma. These findings emphasize the importance of combining repertoire and gene expression sequencing data to determine the nature and clonality of an immune response. This method enables full characterization of tumor heterogeneity and the adaptive immune response to the TME and will be key in the development of successful immunotherapies.

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.

The genetic basis for ecological adaptation of the Atlantic herring revealed by genome sequencing

Ecological adaptation is of major relevance to speciation and sustainable population management, but the underlying genetic factors are typically hard to study in natural populations due to genetic differentiation caused by natural selection being confounded with genetic drift in subdivided populations. Here, we use whole genome population sequencing of Atlantic and Baltic herring to reveal the underlying genetic architecture at an unprecedented detailed resolution for both adaptation to a new niche environment and timing of reproduction. We identify almost 500 independent loci associated with a recent niche expansion from marine (Atlantic Ocean) to brackish waters (Baltic Sea), and more than 100 independent loci showing genetic differentiation between spring- and autumn-spawning populations irrespective of geographic origin. Our results show that both coding and non-coding changes contribute to adaptation. Haplotype blocks, often spanning multiple genes and maintained by selection, are associated with genetic differentiation.

Rabbit genome analysis reveals a polygenic basis for phenotypic change during domestication

The genetic changes underlying the initial steps of animal domestication are still poorly understood. We generated a high-quality reference genome for the rabbit and compared it to resequencing data from populations of wild and domestic rabbits. We identified more than 100 selective sweeps specific to domestic rabbits but only a relatively small number of fixed (or nearly fixed) single-nucleotide polymorphisms (SNPs) for derived alleles. SNPs with marked allele frequency differences between wild and domestic rabbits were enriched for conserved noncoding sites. Enrichment analyses suggest that genes affecting brain and neuronal development have often been targeted during domestication. We propose that because of a truly complex genetic background, tame behavior in rabbits and other domestic animals evolved by shifts in allele frequencies at many loci, rather than by critical changes at only a few domestication loci.

Targeted resequencing and analysis of the Diamond-Blackfan anemia disease locus RPS19

Background

The Ribosomal protein S19 gene locus (RPS19) has been linked to two kinds of red cell aplasia, Diamond-Blackfan Anemia (DBA) and Transient Erythroblastopenia in Childhood (TEC). Mutations in RPS19 coding sequences have been found in 25% of DBA patients, but not in TEC patients. It has been suggested that non-coding RPS19 sequence variants contribute to the considerable clinical variability in red cell aplasia. We therefore aimed at identifying non-coding variations associated with DBA or TEC phenotypes.

Methodology/Principal Findings

We targeted a region of 19'980 bp encompassing the RPS19 gene in a cohort of 89 DBA and TEC patients for resequencing. We provide here a catalog of the considerable, previously unrecognized degree of variation in this region. We identified 73 variations (65 SNPs, 8 indels) that all are located outside of the RPS19 open reading frame, and of which 67.1% are classified as novel. We hypothesize that specific alleles in non-coding regions of RPS19 could alter the binding of regulatory proteins or transcription factors. Therefore, we carried out an extensive analysis to identify transcription factor binding sites (TFBS). A series of putative interaction sites coincide with detected variants. Sixteen of the corresponding transcription factors are of particular interest, as they are housekeeping genes or show a direct link to hematopoiesis, tumorigenesis or leukemia (e.g. GATA-1/2, PU.1, MZF-1).

Conclusions

Specific alleles at predicted TFBSs may alter the expression of RPS19, modify an important interaction between transcription factors with overlapping TFBS or remove an important stimulus for hematopoiesis. We suggest that the detected interactions are of importance for hematopoiesis and could provide new insights into individual response to treatment.

EVALLER: a web server for in silico assessment of potential protein allergenicity

Bioinformatics testing approaches for protein allergenicity, involving amino acid sequence comparisons, have evolved appreciably over the last several years to increased sophistication and performance. EVALLER, the web server presented in this article is based on our recently published 'Detection based on Filtered Length-adjusted Allergen Peptides' (DFLAP) algorithm, which affords in silico determination of potential protein allergenicity of high sensitivity and excellent specificity. To strengthen bioinformatics risk assessment in allergology EVALLER provides a comprehensive outline of its judgment on a query protein's potential allergenicity. Each such textual output incorporates a scoring figure, a confidence numeral of the assignment and information on high- or low-scoring matches to identified allergen-related motifs, including their respective location in accordingly derived allergens. The interface, built on a modified Perl Open Source package, enables dynamic and color-coded graphic representation of key parts of the output. Moreover, pertinent details can be examined in great detail through zoomed views. The server can be accessed at http://bioinformatics.bmc.uu.se/evaller.html.

Diagnosis of tuberculosis in children using a polymerase chain reaction

We investigated the value of the polymerase chain reaction (PCR) in the diagnosis of active tuberculosis in children and evaluated the relationship between PCR results in children with tuberculous infections and mediastinal adenopathies detected by computerized tomography (CT-Scan). This was a controlled, blinded, prospective study comparing nested PCR, mycobacterial cultures and the clinical diagnosis based on 350 clinical specimens from 117 children referred for evaluation of suspected pulmonary tuberculosis. All children with tuberculous infection but without active disease underwent a chest CT-scan to detect the presence of mediastinal adenopathies not evident on chest x-ray. The sensitivity of PCR was 56.8% in children with clinically active disease (culture: 37.8%; smears: 13.5%). A major advantage of PCR over cultures was noted when there was no parenchymal involvement on chest radiograph and when the patient was undergoing anti-tuberculous treatment. There were nine specimens with false-negative PCR results due to the presence of amplification reaction inhibitors. PCR was positive in five children with tuberculous infection without active disease and these children presented mediastinal adenopathies on the CT-scan that were not evident on chest radiography. There were no false-positive PCR results in the control groups of children. We conclude that nested PCR is a rapid and sensitive method for the early diagnosis of tuberculosis in children. It is especially useful when the diagnosis of active tuberculosis is difficult. In our study children with tuberculous infection without apparent disease who have positive PCR results have mediastinal adenopathies on CT-scan.