RESUMO
Genetic analysis of copy number variations (CNVs), especially in complex regions, is challenging due to reference bias and ambiguous alignment of Next-Generation Sequencing (NGS) reads to repetitive DNA. Consequently, aggregate copy numbers are typically analyzed, overlooking variation between gene copies. Pangenomes contain diverse sequences of gene copies and enable the study of sequence-resolved CNVs. We developed a method, ctyper, to discover sequence-resolved CNVs in NGS data by leveraging CNV genes from pangenomes. From 118 public assemblies, we constructed a database of 3,351 CNV genes, distinguishing each gene copy as a resolved allele. We used phylogenetic trees to organize alleles into highly similar allele-types that revealed events of linked small variants due to stratification, structural variation, conversion, and duplication. Saturation analysis showed that new samples share an average of 97.8% CNV alleles with the database. The ctyper method traces individual gene copies in NGS data to their nearest alleles in the database and identifies allele-specific copy numbers using multivariate linear regression on k-mer counts and phylogenetic clustering. Applying ctyper to 1000 Genomes Project (1kgp) samples showed Hardy-Weinberg Equilibrium on 99.3% of alleles and a 97.6% F1 score on genotypes based on 641 1kgp trios. Leave-one-out analysis on 39 assemblies matched to 1kgp samples showed that 96.5% of variants in query sequences match the genotyped allele. Genotyping 1kgp data revealed 226 population-specific CNVs, including a conversion on SMN2 to SMN1, potentially impacting Spinal Muscular Atrophy diagnosis in Africans. Our results revealed two models of CNV: recent CNVs due to ongoing duplications and polymorphic CNVs from ancient paralogs missing from the reference. To measure the functional impact of CNVs, after merging allele-types, we conducted genome-wide Quantitative Trait Locus analysis on 451 1kgp samples with Geuvadis rRNA-seqs. Using a linear mixed model, our genotyping enables the inference of relative expression levels of paralogs within a gene family. In a global evolutionary context, 150 out of 1,890 paralogs (7.94%) and 546 out of 16,628 orthologs (3.28%) had significantly different expression levels, suggesting divergent expression from original genes. Specific examples include lower expression on the converted SMN and increased expression on translocated AMY2B (GTEx pancreas data). Our method enables large cohort studies on complex CNVs to uncover hidden health impacts and overcome reference bias.
RESUMO
The current human reference genome is predominantly derived from a single individual and it does not adequately reflect human genetic diversity. Here, we analyze 338 high-quality human assemblies of genetically divergent human populations to identify missing sequences in the human reference genome with breakpoint resolution. We identify 127,727 recurrent non-reference unique insertions spanning 18,048,877 bp, some of which disrupt exons and known regulatory elements. To improve genome annotations, we linearly integrate these sequences into the chromosomal assemblies and construct a Human Diversity Reference. Leveraging this reference, an average of 402,573 previously unmapped reads can be recovered for a given genome sequenced to ~40X coverage. Transcriptomic diversity among these non-reference sequences can also be directly assessed. We successfully map tens of thousands of previously discarded RNA-Seq reads to this reference and identify transcription evidence in 4781 gene loci, underlining the importance of these non-reference sequences in functional genomics. Our extensive datasets are important advances toward a comprehensive reference representation of global human genetic diversity.
Assuntos
Variação Genética , Genoma Humano , População/genética , Mapeamento Cromossômico , Biologia Computacional , Expressão Gênica , Genômica , Técnicas de Genotipagem , Humanos , Anotação de Sequência Molecular , RNA-Seq , Análise de Sequência de DNA , Transcriptoma , Sequenciamento Completo do GenomaRESUMO
Sequences encoding Olduvai protein domains (formerly DUF1220) show the greatest human lineage-specific increase in copy number of any coding region in the genome and have been associated, in a dosage-dependent manner, with brain size, cognitive aptitude, autism, and schizophrenia. Tandem intragenic duplications of a three-domain block, termed the Olduvai triplet, in four NBPF genes in the chromosomal 1q21.1-0.2 region, are primarily responsible for the striking human-specific copy number increase. Interestingly, most of the Olduvai triplets are adjacent to, and transcriptionally coregulated with, three human-specific NOTCH2NL genes that have been shown to promote cortical neurogenesis. Until now, the underlying genomic events that drove the Olduvai hyperamplification in humans have remained unexplained. Here, we show that the presence or absence of an alternative first exon of the Olduvai triplet perfectly discriminates between amplified (58/58) and unamplified (0/12) triplets. We provide sequence and breakpoint analyses that suggest the alternative exon was produced by an nonallelic homologous recombination-based mechanism involving the duplicative transposition of an existing Olduvai exon found in the CON3 domain, which typically occurs at the C-terminal end of NBPF genes. We also provide suggestive in vitro evidence that the alternative exon may promote instability through a putative G-quadraplex (pG4)-based mechanism. Lastly, we use single-molecule optical mapping to characterize the intragenic structural variation observed in NBPF genes in 154 unrelated individuals and 52 related individuals from 16 families and show that the presence of pG4-containing Olduvai triplets is strongly correlated with high levels of Olduvai copy number variation. These results suggest that the same driver of genomic instability that allowed the evolutionarily recent, rapid, and extreme human-specific Olduvai expansion remains highly active in the human genome.
Assuntos
Proteínas de Transporte/genética , Genoma Humano , Expansão das Repetições de Trinucleotídeos , Animais , Sequência de Bases , Variações do Número de Cópias de DNA , Evolução Molecular , Quadruplex G , Amplificação de Genes , Dosagem de Genes , Instabilidade Genômica , Recombinação Homóloga , Humanos , Primatas , Domínios Proteicos , Homologia de SequênciaRESUMO
BACKGROUND: Homozygous Familial Hypercholesterolemia (HoFH) is an inherited recessive condition associated with extremely high levels of low-density lipoprotein (LDL) cholesterol in affected individuals. It is usually caused by homozygous or compound heterozygous functional mutations in the LDL receptor (LDLR). A number of mutations causing FH have been reported in literature and such genetic heterogeneity presents great challenges for disease diagnosis. OBJECTIVE: We aim to determine the likely genetic defects responsible for three cases of pediatric HoFH in two kindreds. METHODS: We applied whole exome sequencing (WES) on the two probands to determine the likely functional variants among candidate FH genes. We additionally applied 10x Genomics (10xG) Linked-Reads whole genome sequencing (WGS) on one of the kindreds to identify potentially deleterious structural variants (SVs) underlying HoFH. A PCR-based screening assay was also established to detect the LDLR structural variant in a cohort of 641 patients with elevated LDL. RESULTS: In the Caucasian kindred, the FH homozygosity can be attributed to two compound heterozygous LDLR damaging variants, an exon 12 p.G592E missense mutation and a novel 3kb exon 1 deletion. By analyzing the 10xG phased data, we ascertained that this deletion allele was most likely to have originated from a Russian ancestor. In the Mexican kindred, the strikingly elevated LDL cholesterol level can be attributed to a homozygous frameshift LDLR variant p.E113fs. CONCLUSIONS: While the application of WES can provide a cost-effective way of identifying the genetic causes of FH, it often lacks sensitivity for detecting structural variants. Our finding of the LDLR exon 1 deletion highlights the broader utility of Linked-Read WGS in detecting SVs in the clinical setting, especially when HoFH patients remain undiagnosed after WES.
Assuntos
LDL-Colesterol/genética , Hiperlipoproteinemia Tipo II/genética , Receptores de LDL/genética , Sequência de Bases/genética , Pré-Escolar , Mapeamento Cromossômico/métodos , Estudos de Coortes , Mutação da Fase de Leitura/genética , Variação Genética/genética , Genoma Humano/genética , Heterozigoto , Homozigoto , Humanos , Lactente , Lipoproteínas LDL/genética , Linhagem , Fenótipo , Análise de Sequência de DNA/métodos , Sequenciamento do Exoma/métodosRESUMO
Large structural variants (SVs) in the human genome are difficult to detect and study by conventional sequencing technologies. With long-range genome analysis platforms, such as optical mapping, one can identify large SVs (>2 kb) across the genome in one experiment. Analyzing optical genome maps of 154 individuals from the 26 populations sequenced in the 1000 Genomes Project, we find that phylogenetic population patterns of large SVs are similar to those of single nucleotide variations in 86% of the human genome, while ~2% of the genome has high structural complexity. We are able to characterize SVs in many intractable regions of the genome, including segmental duplications and subtelomeric, pericentromeric, and acrocentric areas. In addition, we discover ~60 Mb of non-redundant genome content missing in the reference genome sequence assembly. Our results highlight the need for a comprehensive set of alternate haplotypes from different populations to represent SV patterns in the genome.