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44,516
result(s) for
"chromosome mapping"
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Intronic ATTTC repeat expansions in STARD7 in familial adult myoclonic epilepsy linked to chromosome 2
Familial Adult Myoclonic Epilepsy (FAME) is characterised by cortical myoclonic tremor usually from the second decade of life and overt myoclonic or generalised tonic-clonic seizures. Four independent loci have been implicated in FAME on chromosomes (chr) 2, 3, 5 and 8. Using whole genome sequencing and repeat primed PCR, we provide evidence that chr2-linked FAME (FAME2) is caused by an expansion of an ATTTC pentamer within the first intron of
STARD7
. The ATTTC expansions segregate in 158/158 individuals typically affected by FAME from 22 pedigrees including 16 previously reported families recruited worldwide. RNA sequencing from patient derived fibroblasts shows no accumulation of the AUUUU or AUUUC repeat sequences and
STARD7
gene expression is not affected. These data, in combination with other genes bearing similar mutations that have been implicated in FAME, suggest ATTTC expansions may cause this disorder, irrespective of the genomic locus involved.
Familial cortical myoclonic tremor (FAME) has so far been mapped to regions on chromosome 2, 3, 5 and 8 and pentameric repeat expansions in
SAMD12
were identified as cause of FAME1. Here, Corbett
et al
. identify ATTTT/ATTTC repeat expansions in intron 1 of STARD7 in individuals with FAME2.”
Journal Article
Functional mapping and annotation of genetic associations with FUMA
A main challenge in genome-wide association studies (GWAS) is to pinpoint possible causal variants. Results from GWAS typically do not directly translate into causal variants because the majority of hits are in non-coding or intergenic regions, and the presence of linkage disequilibrium leads to effects being statistically spread out across multiple variants. Post-GWAS annotation facilitates the selection of most likely causal variant(s). Multiple resources are available for post-GWAS annotation, yet these can be time consuming and do not provide integrated visual aids for data interpretation. We, therefore, develop FUMA: an integrative web-based platform using information from multiple biological resources to facilitate functional annotation of GWAS results, gene prioritization and interactive visualization. FUMA accommodates positional, expression quantitative trait loci (eQTL) and chromatin interaction mappings, and provides gene-based, pathway and tissue enrichment results. FUMA results directly aid in generating hypotheses that are testable in functional experiments aimed at proving causal relations.
Prioritizing genetic variants is a major challenge in genome-wide association studies. Here, the authors develop FUMA, a web-based bioinformatics tool that uses a combination of positional, eQTL and chromatin interaction mapping to prioritize likely causal variants and genes.
Journal Article
Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics
Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes.
Phenotypic variation and diseases are influenced by factors such as genetic variants and gene expression. Here, Barbeira et al. develop S-PrediXcan to compute PrediXcan results using summary data, and investigate the effects of gene expression variation on human phenotypes in 44 GTEx tissues and >100 phenotypes.
Journal Article
Piercing the dark matter: bioinformatics of long-range sequencing and mapping
Several new genomics technologies have become available that offer long-read sequencing or long-range mapping with higher throughput and higher resolution analysis than ever before. These long-range technologies are rapidly advancing the field with improved reference genomes, more comprehensive variant identification and more complete views of transcriptomes and epigenomes. However, they also require new bioinformatics approaches to take full advantage of their unique characteristics while overcoming their complex errors and modalities. Here, we discuss several of the most important applications of the new technologies, focusing on both the currently available bioinformatics tools and opportunities for future research.
Journal Article
Probabilistic fine-mapping of transcriptome-wide association studies
Transcriptome-wide association studies using predicted expression have identified thousands of genes whose locally regulated expression is associated with complex traits and diseases. In this work, we show that linkage disequilibrium induces significant gene–trait associations at non-causal genes as a function of the expression quantitative trait loci weights used in expression prediction. We introduce a probabilistic framework that models correlation among transcriptome-wide association study signals to assign a probability for every gene in the risk region to explain the observed association signal. Importantly, our approach remains accurate when expression data for causal genes are not available in the causal tissue by leveraging expression prediction from other tissues. Our approach yields credible sets of genes containing the causal gene at a nominal confidence level (for example, 90%) that can be used to prioritize genes for functional assays. We illustrate our approach by using an integrative analysis of lipid traits, where our approach prioritizes genes with strong evidence for causality.
FOCUS (fine-mapping of causal gene sets) models correlation among TWAS signals to assign a probability for every gene in the risk region to explain the observed association signal while controlling for pleiotropic SNP effects and unmeasured causal expression.
Journal Article
Whole-exome imputation within UK Biobank powers rare coding variant association and fine-mapping analyses
Exome association studies to date have generally been underpowered to systematically evaluate the phenotypic impact of very rare coding variants. We leveraged extensive haplotype sharing between 49,960 exome-sequenced UK Biobank participants and the remainder of the cohort (total
n
≈ 500,000) to impute exome-wide variants with accuracy
R
2
> 0.5 down to minor allele frequency (MAF) ~0.00005. Association and fine-mapping analyses of 54 quantitative traits identified 1,189 significant associations (
P
< 5 × 10
−8
) involving 675 distinct rare protein-altering variants (MAF < 0.01) that passed stringent filters for likely causality. Across all traits, 49% of associations (578/1,189) occurred in genes with two or more hits; follow-up analyses of these genes identified allelic series containing up to 45 distinct ‘likely-causal’ variants. Our results demonstrate the utility of within-cohort imputation in population-scale genome-wide association studies, provide a catalog of likely-causal, large-effect coding variant associations and foreshadow the insights that will be revealed as genetic biobank studies continue to grow.
Imputation of rare coding variants in the UK Biobank enables association and fine-mapping analyses of rare (minor allele frequency (MAF) = 0.00005) genotypes, identifying 600 new variant–trait associations, including long allelic series in individual genes.
Journal Article
Mapping the genomic landscape of CRISPR–Cas9 cleavage
SITE-Seq probes Cas9 cleavage sites
in vitro
and returns a comprehensive list of off-target sites at different Cas9–sgRNA concentrations.
RNA-guided CRISPR–Cas9 endonucleases are widely used for genome engineering, but our understanding of Cas9 specificity remains incomplete. Here, we developed a biochemical method (SITE-Seq), using Cas9 programmed with single-guide RNAs (sgRNAs), to identify the sequence of cut sites within genomic DNA. Cells edited with the same Cas9–sgRNA complexes are then assayed for mutations at each cut site using amplicon sequencing. We used SITE-Seq to examine Cas9 specificity with sgRNAs targeting the human genome. The number of sites identified depended on sgRNA sequence and nuclease concentration. Sites identified at lower concentrations showed a higher propensity for off-target mutations in cells. The list of off-target sites showing activity in cells was influenced by sgRNP delivery, cell type and duration of exposure to the nuclease. Collectively, our results underscore the utility of combining comprehensive biochemical identification of off-target sites with independent cell-based measurements of activity at those sites when assessing nuclease activity and specificity.
Journal Article
Mapping and phasing of structural variation in patient genomes using nanopore sequencing
Despite improvements in genomics technology, the detection of structural variants (SVs) from short-read sequencing still poses challenges, particularly for complex variation. Here we analyse the genomes of two patients with congenital abnormalities using the MinION nanopore sequencer and a novel computational pipeline—NanoSV. We demonstrate that nanopore long reads are superior to short reads with regard to detection of de novo chromothripsis rearrangements. The long reads also enable efficient phasing of genetic variations, which we leveraged to determine the parental origin of all de novo chromothripsis breakpoints and to resolve the structure of these complex rearrangements. Additionally, genome-wide surveillance of inherited SVs reveals novel variants, missed in short-read data sets, a large proportion of which are retrotransposon insertions. We provide a first exploration of patient genome sequencing with a nanopore sequencer and demonstrate the value of long-read sequencing in mapping and phasing of SVs for both clinical and research applications.
The detection of structural variants can be difficult with short-read sequencing technology, especially when variants are highly complex. Here, the authors use a MinION nanopore sequencer to analyse two patient genomes and develop NanoSV to map known and novel structural variants in long read data.
Journal Article
Identification and characterization of a new stripe rust resistance gene Yr83 on rye chromosome 6R in wheat
Key messageA physical map of Secale cereale chromosome 6R was constructed using deletion mapping, and a new stripe rust resistance gene Yr83 was mapped to the deletion bin of FL 0.73–1.00 of 6RL.Rye (Secale cereale L., RR) possesses valuable genes for wheat improvement. In the current study, we report a resistance gene conferring stripe rust resistance effective from seedling to adult plant stages located on chromosome 6R. This chromosome was derived from triticale line T-701 and also carries highly effective resistance to the cereal cyst nematode species Heterodera avenae Woll. A wheat-rye 6R(6D) disomic substitution line exhibited high levels of seedling resistance to Australian pathotypes of the stripe rust (Puccinia striiformis f. sp. tritici; Pst) pathogen and showed an even greater resistance to the Chinese Pst pathotypes in the field. Ten chromosome 6R deletion lines and five wheat-rye 6R translocation lines were developed earlier in the attempt to transfer the nematode resistance gene to wheat and used herein to map the stripe rust resistance gene. These lines were subsequently characterized by sequential multicolor fluorescence in situ hybridization (mc-FISH), genomic in situ hybridization (GISH), mc-GISH, PCR-based landmark unique gene (PLUG), and chromosome 6R-specific length amplified fragment sequencing (SLAF-Seq) marker analyses to physically map the stripe rust resistance gene. The new stripe rust resistance locus was located in a chromosomal bin with fraction length (FL) 0.73–1.00 on 6RL and was named Yr83. A wheat-rye translocation line T6RL (#5) carrying the stripe rust resistance gene will be useful as a new germplasm in breeding for resistance.
Journal Article