The functional impact of structural variation in humans

afila, the origin and nature of a major innovation in the history of pea breeding

The afila (af) mutation causes the replacement of leaflets by a branched mass of tendrils in the compound leaves of pea - Pisum sativum L. This mutation was first described in 1953, and several reports of spontaneous af mutations and induced mutants with a similar phenotype exist. Despite widespread introgression into breeding material, the nature of af and the origin of the alleles used remain unknown. Here, we combine comparative genomics with reverse genetic approaches to elucidate the genetic determinants of af. We also investigate haplotype diversity using a set of AfAf and afaf cultivars and breeding lines and molecular markers linked to seven consecutive genes. Our results show that deletion of two tandemly arranged genes encoding Q-type Cys(2)His(2) zinc finger transcription factors, PsPALM1a and PsPALM1b, is responsible for the af phenotype in pea. Eight haplotypes were identified in the af-harbouring genomic region on chromosome 2. These haplotypes differ in the size of the deletion, covering more or less genes. Diversity at the af locus is valuable for crop improvement and sheds light on the history of pea breeding for improved standing ability. The results will be used to understand the function of PsPALM1a/b and to transfer the knowledge for innovation in related crops.

High-depth whole-genome sequencing identifies structure variants, copy number variants and short tandem repeats associated with Parkinson's disease

While numerous single nucleotide variants and small indels have been identified in Parkinson's disease (PD), the contribution of structural variants (SVs), copy number variants (CNVs), and short tandem repeats (STRs) remains poorly understood. Here we investigated the association using the high-depth whole-genome sequencing data from 466 Chinese PD patients and 513 controls. Totally, we identified 29,561 SVs, 32,153 CNVs, and 174,905 STRs, and found that CNV deletions were significantly enriched in the end-proportion of autosomal chromosomes in PD. After genome-wide association analysis and replication in an external cohort of 352 cases and 547 controls, we validated that the 1.6 kb-deletion neighboring MUC19, 12.4kb-deletion near RXFP1 and GGGAAA repeats in SLC2A13 were significantly associated with PD. Moreover, the MUC19 deletion and the SLC2A13 5-copy repeat reduced the penetrance of the LRRK2 G2385R variant. Moreover, genes with these variants were dosage-sensitive. These data provided novel insights into the genetic architecture of PD.

Large-scale genomic rearrangements boost SCRaMbLE in Saccharomyces cerevisiae

Synthetic Chromosome Rearrangement and Modification by LoxP-mediated Evolution (SCRaMbLE) is a promising tool to study genomic rearrangements. However, the potential of SCRaMbLE to study genomic rearrangements is currently hindered, because a strain containing all 16 synthetic chromosomes is not yet available. Here, we construct SparLox83R, a yeast strain containing 83 loxPsym sites distributed across all 16 chromosomes. SCRaMbLE of SparLox83R produces versatile genome-wide genomic rearrangements, including inter-chromosomal events. Moreover, when combined with synthetic chromosomes, SCRaMbLE of hetero-diploids with SparLox83R leads to increased diversity of genomic rearrangements and relatively faster evolution of traits compared to hetero-diploids only with wild-type chromosomes. Analysis of the SCRaMbLEd strain with increased tolerance to nocodazole demonstrates that genomic rearrangements can perturb the transcriptome and 3D genome structure and consequently impact phenotypes. In summary, a genome with sparsely distributed loxPsym sites can serve as a powerful tool for studying the consequence of genomic rearrangements and accelerating strain engineering in Saccharomyces cerevisiae.

Modification of Huntington's disease by short tandem repeats

Expansions of glutamine-coding CAG trinucleotide repeats cause a number of neurodegenerative diseases, including Huntington's disease and several of spinocerebellar ataxias. In general, age-at-onset of the polyglutamine diseases is inversely correlated with the size of the respective inherited expanded CAG repeat. Expanded CAG repeats are also somatically unstable in certain tissues, and age-at-onset of Huntington's disease corrected for individual HTT CAG repeat length (i.e. residual age-at-onset), is modified by repeat instability-related DNA maintenance/repair genes as demonstrated by recent genome-wide association studies. Modification of one polyglutamine disease (e.g. Huntington's disease) by the repeat length of another (e.g. ATXN3, CAG expansions in which cause spinocerebellar ataxia 3) has also been hypothesized. Consequently, we determined whether age-at-onset in Huntington's disease is modified by the CAG repeats of other polyglutamine disease genes. We found that the CAG measured repeat sizes of other polyglutamine disease genes that were polymorphic in Huntington's disease participants but did not influence Huntington's disease age-at-onset. Additional analysis focusing specifically on ATXN3 in a larger sample set (n = 1388) confirmed the lack of association between Huntington's disease residual age-at-onset and ATXN3 CAG repeat length. Additionally, neither our Huntington's disease onset modifier genome-wide association studies single nucleotide polymorphism data nor imputed short tandem repeat data supported the involvement of other polyglutamine disease genes in modifying Huntington's disease. By contrast, our genome-wide association studies based on imputed short tandem repeats revealed significant modification signals for other genomic regions. Together, our short tandem repeat genome-wide association studies show that modification of Huntington's disease is associated with short tandem repeats that do not involve other polyglutamine disease-causing genes, refining the landscape of Huntington's disease modification and highlighting the importance of rigorous data analysis, especially in genetic studies testing candidate modifiers.

Exploring quantitative traits-associated copy number deletions through reanalysis of UK10K consortium whole genome sequencing cohorts

OBJECTIVES

We performed comprehensive association analyses of common high-confidence gnomAD-reported copy number deletions (CNDs) with 60 quantitative traits from UK10K consortium WGS data.

METHODS

The study made use of data generated by the UK10K Consortium. UK10K consortium WGS data consist of TwinsUK (n = 1754, middle-aged females) and ALSPAC (n = 1867, birth to adolescence) cohorts. UK10K consortium called 18,739 CNDs (hg19) with GenomeSTRiP software. After filtering out variants with minor allele frequency < 0.05 or HWE P < 1.0 × 10- 6, 1222 (TwinsUK) and 1211 (ALSPAC) CNDs remained for association analyses with 60 normalized quantitative traits.

RESULTS

We identified 23 genome-wide significant associations at 13 loci, among which 2 associations reached experiment-wide significance. We found that two common deletions in chromosome 4, located between WDR1 and ZNF518B (23.3 kb, dbVar ID:nssv15888957, 4:10211262-10,234,569 and 9.8 kb, dbVar ID:nssv15888975, 4:10392422-10,402,191), were associated with uric acid levels (P = 5.23 × 10- 11 and 2.29 × 10- 8, respectively). We also discovered a novel deletion spanning chromosome 18 (823 bp, dbVar ID: nssv15841628, 8:74347187-74,348,010) associated with low HDL cholesterol levels (P = 4.15 × 10- 7). Additionally, we observed two red blood cell traits-associated loci with genome-wide significance, a 13.2 kb deletion in 7q22.1 (nssv15922542) and a 3.7 kb deletion in 12q24.12 (nssv15813226), both of which were located in regions previously reported to be associated with red blood cell traits. Two deletions in 11q11 (nssv15803200 and nssv15802240), where clusters of multiple olfactory receptor genes exist, and a deletion (nssv15929560) upstream to DOCK5 were associated with childhood obesity. Finally, when defining Trait-Associated copy number Deletions (TADs) as CNDs with phenotype associations at sub-threshold significance (P < 10- 3), we identified 157 (97.5%) out of 161 TADs in non-coding regions, with a mean size of 4 kb (range: 209 - 47,942 bp).

CONCLUSION

We conducted a reanalysis of the UK10K Whole Genome Sequencing cohort, which led to the identification of multiple high confidence copy number deletions associated with quantitative traits. These deletions have standard dbVar IDs and replicate previous findings, as well as reveal novel loci that require further replication studies.

Comprehensive detection of structural variation and transposable element differences between wild type laboratory lineages of C. elegans

Genomic structural variations (SVs) and transposable elements (TEs) can be significant contributors to genome evolution, altered gene expression, and risk of genetic diseases. Recent advancements in long-read sequencing have greatly improved the quality of de novo genome assemblies and enhanced the detection of sequence variants at the scale of hundreds or thousands of bases. Comparisons between two diverged wild isolates of Caenorhabditis elegans, the Bristol and Hawaiian strains, have been widely utilized in the analysis of small genetic variations. Genetic drift, including SVs and rearrangements of repeated sequences such as TEs, can occur over time from long-term maintenance of wild type isolates within the laboratory. To comprehensively detect both large and small structural variations as well as TEs due to genetic drift, we generated de novo genome assemblies and annotations for each strain from our lab collection using both long- and short-read sequencing and compared our assemblies and annotations with that of other lab wild type strains. Within our lab assemblies, we annotate over 3.1Mb of sequence divergence between the Bristol and Hawaiian isolates: 337,584 SNPs, 94,503 small insertion-deletions (<50bp), and 4,334 structural variations (>50bp). Further, we define the location and movement of specific DNA TEs between N2 Bristol and CB4856 Hawaiian wild type isolates. Specifically, we find the N2 Bristol genome has 20.6% more TEs from the Tc1/mariner family than the CB4856 Hawaiian genome. Moreover, we identified Zator elements as the most abundant and mobile TE family in the genome. Using specific TE sequences with unique SNPs, we also identify 38 TEs that moved intrachromosomally and 9 TEs that moved interchromosomally between the N2 Bristol and CB4856 Hawaiian genomes. By comparing the de novo genome assembly of our lab collection Bristol isolate to the VC2010 Bristol assembly, we also reveal that lab lineages display over 2 Mb of total variation: 1,162 SNPs, 1,528 indels, and 897 SVs with 95% of the variation due to SVs. Overall, our work demonstrates the unique contribution of SVs and TEs to variation and genetic drift between wild type laboratory strains assumed to be isogenic despite growing evidence of genetic drift and phenotypic variation.

FADS2 function at the major cancer hotspot 11q13 locus alters fatty acid metabolism in cancer

Dysregulation of fatty acid metabolism and de novo lipogenesis is a key driver of several cancer types through highly unsaturated fatty acid (HUFA) signaling precursors such as arachidonic acid. The human chromosome 11q13 locus has long been established as the most frequently amplified in a variety of human cancers. The fatty acid desaturase genes (FADS1, FADS2 and FADS3) responsible for HUFA biosynthesis localize to the 11q12-13.1 region. FADS2 activity is promiscuous, catalyzing biosynthesis of several unsaturated fatty acids by Δ6, Δ8, and Δ4 desaturation. Our main aim here is to review known and putative consequences of FADS2 dysregulation due to effects on the 11q13 locus potentially driving various cancer types. FADS2 silencing causes synthesis of sciadonic acid (5Z,11Z,14Z-20:3) in MCF7 cells and breast cancer in vivo. 5Z,11Z,14Z-20:3 is structurally identical to arachidonic acid (5Z,8Z,11Z,14Z-20:4) except it lacks the internal Δ8 double bond required for prostaglandin and leukotriene synthesis, among other eicosanoids. Palmitic acid has substrate specificity for both SCD and FADS2. Melanoma, prostate, liver and lung cancer cells insensitive to SCD inhibition show increased FADS2 activity and sapienic acid biosynthesis. Elevated serum mead acid levels found in hepatocellular carcinoma patients suggest an unsatisfied demand for arachidonic acid. FADS2 circular RNAs are at high levels in colorectal and lung cancer tissues. FADS2 circular RNAs are associated with shorter overall survival in colorectal cancer patients. The evidence thusfar supports an effort for future research on the role of FADS2 as a tumor suppressor in a range of neoplastic disorders.

Structural variation of the coding and non-coding human pharmacogenome

Genetic variants in drug targets and genes encoding factors involved in drug absorption, distribution, metabolism and excretion (ADME) can have pronounced impacts on drug pharmacokinetics, response, and toxicity. While the landscape of genetic variability at the level of single nucleotide variants (SNVs) has been extensively studied in these pharmacogenetic loci, their structural variation is only poorly understood. Thus, we systematically analyzed the genetic structural variability across 908 pharmacogenes (344 ADME genes and 564 drug targets) based on publicly available whole genome sequencing data from 10,847 unrelated individuals. Overall, we extracted 14,984 distinct structural variants (SVs) ranging in size from 50 bp to 106 Mb. Each individual harbored on average 10.3 and 1.5 SVs with putative functional effects that affected the coding regions of ADME genes and drug targets, respectively. In addition, by cross-referencing pharmacogenomic SVs with experimentally determined binding data of 224 transcription factors across 130 cell types, we identified 1276 non-coding SVs that overlapped with gene regulatory elements. Based on these data, we estimate that non-coding structural variants account for 22% of the genetically encoded pharmacogenomic variability. Combined, these analyses provide the first comprehensive map of structural variability across pharmacogenes, derive estimates for the functional impact of non-coding SVs and incentivize the incorporation of structural genomic data into personalized drug response predictions.

Population history modulates the fitness effects of Copy Number Variation in the Roma

We provide the first whole genome Copy Number Variant (CNV) study addressing Roma, along with reference populations from South Asia, the Middle East and Europe. Using CNV calling software for short-read sequence data, we identified 3171 deletions and 489 duplications. Taking into account the known population history of the Roma, as inferred from whole genome nucleotide variation, we could discern how this history has shaped CNV variation. As expected, patterns of deletion variation, but not duplication, in the Roma followed those obtained from single nucleotide polymorphisms (SNPs). Reduced effective population size resulting in slightly relaxed natural selection may explain our observation of an increase in intronic (but not exonic) deletions within Loss of Function (LoF)-intolerant genes. Over-representation analysis for LoF-intolerant gene sets hosting intronic deletions highlights a substantial accumulation of shared biological processes in Roma, intriguingly related to signaling, nervous system and development features, which may be related to the known profile of private disease in the population. Finally, we show the link between deletions and known trait-related SNPs reported in the genome-wide association study (GWAS) catalog, which exhibited even frequency distributions among the studied populations. This suggests that, in general human populations, the strong association between deletions and SNPs associated to biomedical conditions and traits could be widespread across continental populations, reflecting a common background of potentially disease/trait-related CNVs.

Genetic variation in the immunoglobulin heavy chain locus shapes the human antibody repertoire

Variation in the antibody response has been linked to differential outcomes in disease, and suboptimal vaccine and therapeutic responsiveness, the determinants of which have not been fully elucidated. Countering models that presume antibodies are generated largely by stochastic processes, we demonstrate that polymorphisms within the immunoglobulin heavy chain locus (IGH) impact the naive and antigen-experienced antibody repertoire, indicating that genetics predisposes individuals to mount qualitatively and quantitatively different antibody responses. We pair recently developed long-read genomic sequencing methods with antibody repertoire profiling to comprehensively resolve IGH genetic variation, including novel structural variants, single nucleotide variants, and genes and alleles. We show that IGH germline variants determine the presence and frequency of antibody genes in the expressed repertoire, including those enriched in functional elements linked to V(D)J recombination, and overlapping disease-associated variants. These results illuminate the power of leveraging IGH genetics to better understand the regulation, function, and dynamics of the antibody response in disease.

Dam Assisted Fluorescent Tagging of Chromatin Accessibility (DAFCA) for Optical Genome Mapping in Nanochannel Arrays

Proteins and enzymes in the cell nucleus require physical access to their DNA target sites in order to perform genomic tasks such as gene activation and transcription. Hence, chromatin accessibility is a central regulator of gene expression, and its genomic profile holds essential information on the cell type and state. We utilized the E. coli Dam methyltransferase in combination with a fluorescent cofactor analogue to generate fluorescent tags in accessible DNA regions within the cell nucleus. The accessible portions of the genome are then detected by single-molecule optical genome mapping in nanochannel arrays. This method allowed us to characterize long-range structural variations and their associated chromatin structure. We show the ability to create whole-genome, allele-specific chromatin accessibility maps composed of long DNA molecules extended in silicon nanochannels.

Identification of complex and cryptic chromosomal rearrangements by optical genome mapping

BACKGROUND

Optical genome mapping (OGM) has developed into a highly promising method for detecting structural variants (SVs) in human genomes. Complex chromosomal rearrangements (CCRs) and cryptic translocations are rare events that are considered difficult to detect by routine cytogenetic methods. In this study, OGM was applied to delineate the precise chromosomal rearrangements in three cases with uncertain or unconfirmed CCRs detected by conventional karyotyping and one case with a cryptic translocation suggested by fetal chromosomal microarray analysis (CMA).

RESULTS

In the three cases with CCRs, OGM not only confirmed or revised the original karyotyping results but also refined the precise chromosomal structures. In the case with a suspected translocation not detected by karyotyping, OGM efficiently identified the cryptic translocation and defined the genomic breakpoints with relatively high accuracy.

CONCLUSIONS

Our study confirmed OGM as a robust alternative approach to karyotyping for the detection of chromosomal structural rearrangements, including CCRs and cryptic translocations.

Novel gene-intergenic fusion involving ubiquitin E3 ligase UBE3C causes distal hereditary motor neuropathy

Distal hereditary motor neuropathies (dHMNs) are a group of inherited diseases involving the progressive, length-dependent axonal degeneration of the lower motor neurons. There are currently 29 reported causative genes and four disease loci implicated in dHMN. Despite the high genetic heterogeneity, mutations in the known genes account for less than 20% of dHMN cases, with the mutations identified predominantly being point mutations or indels. We have expanded the spectrum of dHMN mutations with the identification of a 1.35 Mb complex structural variation (SV) causing a form of autosomal dominant dHMN (DHMN1 OMIM %182906). Given the complex nature of SV mutations and the importance of studying pathogenic mechanisms in a neuronal setting, we generated a patient-derived DHMN1 motor neuron model harbouring the 1.35 Mb complex insertion. The DHMN1 complex insertion creates a duplicated copy of the first 10 exons of the ubiquitin-protein E3 ligase gene (UBE3C) and forms a novel gene-intergenic fusion sense transcript by incorporating a terminal pseudo-exon from intergenic sequence within the DHMN1 locus. The UBE3C intergenic fusion (UBE3C-IF) transcript does not undergo nonsense-mediated decay and results in a significant reduction of wild-type full-length UBE3C (UBE3C-WT) protein levels in DHMN1 iPSC-derived motor neurons. An engineered transgenic Caenorhabditis elegans model expressing the UBE3C-IF transcript in GABA-ergic motor neurons shows neuronal synaptic transmission deficits. Furthermore, the transgenic animals are susceptible to heat stress, which may implicate defective protein homeostasis underlying DHMN1 pathogenesis. Identification of the novel UBE3C-IF gene-intergenic fusion transcript in motor neurons highlights a potential new disease mechanism underlying axonal and motor neuron degeneration. These complementary models serve as a powerful paradigm for studying the DHMN1 complex SV and an invaluable tool for defining therapeutic targets for DHMN1.

Comprehensive variant discovery in the era of complete human reference genomes

Advances in long-read sequencing technologies have broadened our understanding of genetic variation in the human population, uncovered new complex structural variants and offered an opportunity to elucidate new variant associations with disease.

Different structural variant prediction tools yield considerably different results in Caenorhabditis elegans

The accurate characterization of structural variation is crucial for our understanding of how large chromosomal alterations affect phenotypic differences and contribute to genome evolution. Whole-genome sequencing is a popular approach for identifying structural variants, but the accuracy of popular tools remains unclear due to the limitations of existing benchmarks. Moreover, the performance of these tools for predicting variants in non-human genomes is less certain, as most tools were developed and benchmarked using data from the human genome. To evaluate the use of long-read data for the validation of short-read structural variant calls, the agreement between predictions from a short-read ensemble learning method and long-read tools were compared using real and simulated data from Caenorhabditis elegans. The results obtained from simulated data indicate that the best performing tool is contingent on the type and size of the variant, as well as the sequencing depth of coverage. These results also highlight the need for reference datasets generated from real data that can be used as 'ground truth' in benchmarks.

Chromosome-level genome and recombination map of the male buffalo

BACKGROUND

The swamp buffalo (Bubalus bubalis carabanesis) is an economically important livestock supplying milk, meat, leather, and draft power. Several female buffalo genomes have been available, but the lack of high-quality male genomes hinders studies on chromosome evolution, especially Y, as well as meiotic recombination.

RESULTS

Here, a chromosome-level genome with a contig N50 of 72.2 Mb and a fine-scale recombination map of male buffalo were reported. We found that transposable elements (TEs) and structural variants (SVs) may contribute to buffalo evolution by influencing adjacent gene expression. We further found that the pseudoautosomal region (PAR) of the Y chromosome is subject to stronger purification selection. The meiotic recombination map showed that there were 2 obvious recombination hotspots on chromosome 8, and the genes around them were mainly related to tooth development, which may have helped to enhance the adaption of buffalo to inferior feed. Among several genomic features, TE density has the strongest correlation with recombination rates. Moreover, the TE subfamily, SINE/tRNA, is likely to play a role in driving recombination into SVs.

CONCLUSIONS

The male genome and sperm sequencing will facilitate the understanding of the buffalo genomic evolution and functional research.

Genomic imbalance in euploid pregnancy loss

PURPOSE

This study aims to investigate genomic imbalance in euploid products of conceptions (POCs) detected by chromosomal microarray analysis (CMA) and its association with clinical characteristics.

METHODS

In a retrospective cohort study where all women with singleton pregnancy losses underwent CMA detection of POCs, only patients with euploid POCs were included in the analysis. The clinical features were compared between those with and without a copy number variant (CNV). The pathogenic CNVs and the variant of uncertain significance (VOUS) were analyzed, and the common pathogenic CNVs and uniparental disomy (UPD) were investigated.

RESULTS

A total of 610 POCs were detected as chromosomal euploid, of which 176 were euploid with CNVs and 434 were euploid without CNVs. Regarding maternal age, gestational age, and history of pregnancy loss, no significant differences were found between the two groups. Furthermore, 104 pathogenic CNVs were identified in 93 POCs, and the deletion of 8p23.3 was found in 10 subjects. All CNVs greater than 3 Mb and 39.5% of CNVs ranging from 1 to 2 Mb were pathogenic, and only 3 CNVs < 1 Mb were pathogenic. UPD was detected in 12 POCs.

CONCLUSION

Besides aneuploidy, 15.24% pregnancy loss might have an association with pathogenic genomic imbalance, and the occurrence of genomic imbalance is not related to clinical characteristics. CNVs greater than 3 Mb in pregnancy losses have a high probability to be pathogenic, and approximately 40% of CNVs ranging from 1 to 2 Mb are pathogenic. The deletion of 8p23.3 is the most common pathogenic CVN in POCs of Chinese-Han women. The clinical significance of UPD in pregnancy loss needs further study.

A cross-disorder dosage sensitivity map of the human genome

Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics.

Copy Number Variant Risk Scores Associated With Cognition, Psychopathology, and Brain Structure in Youths in the Philadelphia Neurodevelopmental Cohort

Importance

Psychiatric and cognitive phenotypes have been associated with a range of specific, rare copy number variants (CNVs). Moreover, IQ is strongly associated with CNV risk scores that model the predicted risk of CNVs across the genome. But the utility of CNV risk scores for psychiatric phenotypes has been sparsely examined.

Objective

To determine how CNV risk scores, common genetic variation indexed by polygenic scores (PGSs), and environmental factors combine to associate with cognition and psychopathology in a community sample.

Design, Setting, and Participants

The Philadelphia Neurodevelopmental Cohort is a community-based study examining genetics, psychopathology, neurocognition, and neuroimaging. Participants were recruited through the Children's Hospital of Philadelphia pediatric network. Participants with stable health and fluency in English underwent genotypic and phenotypic characterization from November 5, 2009, through December 30, 2011. Data were analyzed from January 1 through July 30, 2021.

Exposures

The study examined (1) CNV risk scores derived from models of burden, predicted intolerance, and gene dosage sensitivity; (2) PGSs from genomewide association studies related to developmental outcomes; and (3) environmental factors, including trauma exposure and neighborhood socioeconomic status.

Main Outcomes and Measures

The study examined (1) neurocognition, with the Penn Computerized Neurocognitive Battery; (2) psychopathology, with structured interviews based on the Schedule for Affective Disorders and Schizophrenia for School-Age Children; and (3) brain volume, with magnetic resonance imaging.

Results

Participants included 9498 youths aged 8 to 21 years; 4906 (51.7%) were female, and the mean (SD) age was 14.2 (3.7) years. After quality control, 18 185 total CNVs greater than 50 kilobases (10 517 deletions and 7668 duplications) were identified in 7101 unrelated participants genotyped on Illumina arrays. In these participants, elevated CNV risk scores were associated with lower overall accuracy on cognitive tests (standardized β = 0.12; 95% CI, 0.10-0.14; P = 7.41 × 10-26); lower accuracy across a range of cognitive subdomains; increased overall psychopathology; increased psychosis-spectrum symptoms; and higher deviation from a normative developmental model of brain volume. Statistical models of developmental outcomes were significantly improved when CNV risk scores were combined with PGSs and environmental factors.

Conclusions and Relevance

In this study, elevated CNV risk scores were associated with lower cognitive ability, higher psychopathology including psychosis-spectrum symptoms, and greater deviations from normative magnetic resonance imaging models of brain development. Together, these results represent a step toward synthesizing rare genetic, common genetic, and environmental factors to understand clinically relevant outcomes in youth.

The third international hackathon for applying insights into large-scale genomic composition to use cases in a wide range of organisms

In October 2021, 59 scientists from 14 countries and 13 U.S. states collaborated virtually in the Third Annual Baylor College of Medicine & DNANexus Structural Variation hackathon. The goal of the hackathon was to advance research on structural variants (SVs) by prototyping and iterating on open-source software. This led to nine hackathon projects focused on diverse genomics research interests, including various SV discovery and genotyping methods, SV sequence reconstruction, and clinically relevant structural variation, including SARS-CoV-2 variants. Repositories for the projects that participated in the hackathon are available at https://github.com/collaborativebioinformatics.

Copy Number Variation Analysis of Euploid Pregnancy Loss

Objectives: Copy number variant (CNV) is believed to be the potential genetic cause of pregnancy loss. However, CNVs less than 3 Mb in euploid products of conceptions (POCs) remain largely unexplored. The aim of this study was to investigate the features of CNVs less than 3 Mb in POCs and their potential clinical significance in pregnancy loss/fetal death. Methods: CNV data were extracted from a cohort in our institution and 19 peer-reviewed publications, and only those CNVs less than 3 Mb detected in euploid pregnancy loss/fetal death were included. We conducted a CNV map to analyze the distribution of CNVs in chromosomes using R packages karyoploteR_1.10.5. Gene names and annotated gene types covered by those CNVs were mined from the human Release 19 reference genome file and GENECODE database. We assessed the expression patterns and the consequences of murine knock-out of those genes using TiGER and Mouse Genome Informatics (MGI) databases. Functional enrichment and pathway analysis for genes in CNVs were performed using clusterProfiler V3.12.0. Result: Breakpoints of 564 CNVs less than 3 Mb were obtained from 442 euploid POCs, with 349 gains and 185 losses. The CNV map showed that CNVs were distributed in all chromosomes, with the highest frequency detected in chromosome 22 and the lowest frequency in chromosome Y, and CNVs showed a higher density in the pericentromeric and sub-telomeric regions. A total of 5,414 genes mined from the CNV regions (CNVRs), Gene Ontology (GO), and pathway analysis showed that the genes were significantly enriched in multiple terms, especially in sensory perception, membrane region, and tight junction. A total of 995 protein-coding genes have been reported to present mammalian phenotypes in MGI, and 276 of them lead to embryonic lethality or abnormal embryo/placenta in knock-out mouse models. CNV located at 19p13.3 was the most common CNV of all POCs. Conclusion: CNVs less than 3 Mb in euploid POCs distribute unevenly in all chromosomes, and a higher density was seen in the pericentromeric and sub-telomeric regions. The genes in those CNVRs are significantly enriched in biological processes and pathways that are important to embryonic/fetal development. CNV in 19p13.3 and the variations of ARID3A and FSTL3 might contribute to pregnancy loss.

Pierre CL, Williams A, Sohni A, Wilkinson MF, Gymrek M, Sebat J, Palmer AA. SNPs, short tandem repeats, and structural variants are responsible for differential gene expression across C57BL/6 and C57BL/10 substrains

Mouse substrains are an invaluable model for understanding disease. We compared C57BL/6J, which is the most commonly used inbred mouse strain, with eight C57BL/6 and five C57BL/10 closely related inbred substrains. Whole-genome sequencing and RNA-sequencing analysis yielded 352,631 SNPs, 109,096 indels, 150,344 short tandem repeats (STRs), 3,425 structural variants (SVs), and 2,826 differentially expressed genes (DE genes) among these 14 strains; 312,981 SNPs (89%) distinguished the B6 and B10 lineages. These SNPs were clustered into 28 short segments that are likely due to introgressed haplotypes rather than new mutations. Outside of these introgressed regions, we identified 53 SVs, protein-truncating SNPs, and frameshifting indels that were associated with DE genes. Our results can be used for both forward and reverse genetic approaches and illustrate how introgression and mutational processes give rise to differences among these widely used inbred substrains.

Similarity-Based Analysis of Allele Frequency Distribution among Multiple Populations Identifies Adaptive Genomic Structural Variants

Structural variants have a considerable impact on human genomic diversity. However, their evolutionary history remains mostly unexplored. Here, we developed a new method to identify potentially adaptive structural variants based on a similarity-based analysis that incorporates genotype frequency data from 26 populations simultaneously. Using this method, we analyzed 57,629 structural variants and identified 576 structural variants that show unusual population differentiation. Of these putatively adaptive structural variants, we further showed that 24 variants are multiallelic and overlap with coding sequences, and 20 variants are significantly associated with GWAS traits. Closer inspection of the haplotypic variation associated with these putatively adaptive and functional structural variants reveals deviations from neutral expectations due to: 1) population differentiation of rapidly evolving multiallelic variants, 2) incomplete sweeps, and 3) recent population-specific negative selection. Overall, our study provides new methodological insights, documents hundreds of putatively adaptive variants, and introduces evolutionary models that may better explain the complex evolution of structural variants.

Xq27.1 palindrome mediated interchromosomal insertion likely causes familial congenital bilateral laryngeal abductor paralysis (Plott syndrome)

Bilateral laryngeal abductor paralysis is a rare entity and the second most common cause of stridor in newborns. So far, no conclusive genetic or chromosomal aberration has been reported for X-linked isolated bilateral vocal cord paralysis, also referred to as Plott syndrome. Via whole genome sequencing (WGS), we identified a complex interchromosomal insertion in a large family with seven affected males. The 404 kb inserted fragment originates from chromosome 10q21.3, contains no genes and is inserted inversionally into the intergenic chromosomal region Xq27.1, 82 kb centromeric to the nearest gene SOX3. The patterns found at the breakpoint junctions resemble typical characteristics that arise in replication-based mechanisms with long-distance template switching. Non protein-coding insertions into the same genomic region have been described to result in different phenotypes, indicating that the phenotypic outcome likely depends on the introduction of regulatory elements. In conclusion, our data adds Plott syndrome as another entity, likely caused by the insertion of non-coding DNA into the intergenic chromosomal region Xq27.1. In this regard, we demonstrate the importance of WGS as a powerful diagnostic test in unsolved genetic diseases, as this genomic rearrangement has not been detected by current first-line diagnostic tests, i.e., exome sequencing and chromosomal microarray analysis.

BRCA1 gene polymorphism and finger dermatoglyphic patterns in Ghanaian breast cancer patients: a quantitative cross-sectional approach

Introduction

breast cancer development is linked to mutant single nucleotide polymorphism of breast cancer type 1 (BRCA1) gene usually harboured within exon 11. It has also been linked to finger dermatoglyphics where certain patterns have been associated with breast cancer. This study suggests a possible relationship between finger dermatoglyphic patterns and single nucleotide polymorphism of BRCA1 gene.

Methods

in a quantitative cross-sectional approach, finger dermatoglyphic patterns were obtained using the ink method from 70 female breast cancer patients and 70 age-matched apparently healthy females. Approximately 5 ml of venous blood was obtained from each participant from which DNA was extracted from the white blood cells collected after centrifugation. DNA was amplified and sequenced and the data aligned with the wildtype template of BRCA1 gene. Fingerprint patterns were analyzed with Chi-square. Mean frequency of fingerprint patterns was analyzed with independent student's t-test. Differences in data set with p<0.05 were statistically significant.

Results

luminal B was the predominant breast cancer molecular subtype among the patients. The predominant fingerprint pattern among breast cancer participants was the loop. Six or more loops had higher frequency among breast cancer females. The predominant BRCA1 gene variant locations were c.34311, c.34320, and c.34321 with c.34311A>C being the predominant variant. Higher percentage frequency of six or more loops in relation to c.34311A>C was observed in apparently healthy females compared to breast cancer females.

Conclusion

the study reports for the very first time in Ghana, BRCA1 gene variants and finger dermatoglyphics among breast cancer patients. Although the results are preliminary and inconclusive it creates an avenue for extended studies.

Transcriptomic profiling of whole blood in 22q11.2 reciprocal copy number variants reveals that cell proportion highly impacts gene expression

22q11.2 reciprocal copy number variants (CNVs) offer a powerful quasi-experimental "reverse-genetics" paradigm to elucidate how gene dosage (i.e., deletions and duplications) disrupts the transcriptome to cause further downstream effects. Clinical profiles of 22q11.2 CNV carriers indicate that disrupted gene expression causes alterations in neuroanatomy, cognitive function, and psychiatric disease risk. However, interpreting transcriptomic signal in bulk tissue requires careful consideration of potential changes in cell composition. We first characterized transcriptomic dysregulation in peripheral blood from reciprocal 22q11.2 CNV carriers using differential expression analysis and weighted gene co-expression network analysis (WGCNA) to identify modules of co-expressed genes. We also assessed for group differences in cell composition and re-characterized transcriptomic differences after accounting for cell type proportions and medication usage. Finally, to explore whether CNV-related transcriptomic changes relate to downstream phenotypes associated with 22q11.2 CNVs, we tested for associations of gene expression with neuroimaging measures and behavioral traits, including IQ and psychosis or ASD diagnosis. 22q11.2 deletion carriers (22qDel) showed widespread expression changes at the individual gene as well as module eigengene level compared to 22q11.2 duplication carriers (22qDup) and controls. 22qDup showed increased expression of 5 genes within the 22q11.2 locus, and CDH6 located outside of the locus. Downregulated modules in 22qDel implicated altered immune and inflammatory processes. Celltype deconvolution analyses revealed significant differences between CNV and control groups in T-cell, mast cell, and macrophage proportions; differential expression of individual genes between groups was substantially attenuated after adjusting for cell composition. Individual gene, module eigengene, and cell proportions were not significantly associated with psychiatric or neuroanatomic traits. Our findings suggest broad immune-related dysfunction in 22qDel and highlight the importance of understanding differences in cell composition when interpreting transcriptomic changes in clinical populations. Results also suggest novel directions for future investigation to test whether 22q11.2 CNV effects on macrophages have implications for brain-related microglial function that may contribute to psychiatric phenotypes in 22q11.2 CNV carriers.

Genome Structural Variation Landscape and Its Selection Signatures in the Fast-growing Strains of the Pacific Oyster, Crassostrea gigas

The Pacific oyster (Crassostrea gigas) genome is highly polymorphic and affluent in structural variations (SVs), a significant source of genetic variation underlying inter-individual differences. Here, we used two genome assemblies and 535 individuals of genome re-sequencing data to construct a comprehensive landscape of structural variations in the Pacific oyster. Through whole-genome alignment, 11,087 short SVs and 11,561 copy number variations (CNVs) were identified. While analysis of re-sequencing data revealed 511,170 short SVs and 979,486 CNVs, a total of 63,100 short SVs and 58,182 CNVs were identified in at least 20 samples and regarded as common variations. Based on the common short SVs, both Fst and Pi ratio statistical methods were employed to detect the selective sweeps between 20 oyster individuals from the fast-growing strain and 20 individuals from their corresponding wild population. A total of 514 overlapped regions (8.76 Mb), containing 746 candidate genes, were identified by both approaches, in addition with 103 genes within 61 common CNVs only detected in the fast-growing strains. The GO enrichment and KEGG pathway analysis indicated that the identified candidate genes were mostly associated with apical part of cell and were significantly enriched in several metabolism-related pathways, including tryptophan metabolism and histidine metabolism. This work provided a comprehensive landscape of SVs and revealed their responses to selection, which will be valuable for further investigations on genome evolution under selection in the oysters.

From DNA human sequence to the chromatin higher order organisation and its biological meaning: Using biomolecular interaction networks to understand the influence of structural variation on spatial genome organisation and its functional effect

The three-dimensional structure of the human genome has been proven to have a significant functional impact on gene expression. The high-order spatial chromatin is organised first by looping mediated by multiple protein factors, and then it is further formed into larger structures of topologically associated domains (TADs) or chromatin contact domains (CCDs), followed by A/B compartments and finally the chromosomal territories (CTs). The genetic variation observed in human population influences the multi-scale structures, posing a question regarding the functional impact of structural variants reflected by the variability of the genes expression patterns. The current methods of evaluating the functional effect include eQTLs analysis which uses statistical testing of influence of variants on spatially close genes. Rarely, non-coding DNA sequence changes are evaluated by their impact on the biomolecular interaction network (BIN) reflecting the cellular interactome that can be analysed by the classical graph-theoretic algorithms. Therefore, in the second part of the review, we introduce the concept of BIN, i.e. a meta-network model of the complete molecular interactome developed by integrating various biological networks. The BIN meta-network model includes DNA-protein binding by the plethora of protein factors as well as chromatin interactions, therefore allowing connection of genomics with the downstream biomolecular processes present in a cell. As an illustration, we scrutinise the chromatin interactions mediated by the CTCF protein detected in a ChIA-PET experiment in the human lymphoblastoid cell line GM12878. In the corresponding BIN meta-network the DNA spatial proximity is represented as a graph model, combined with the Proteins-Interaction Network (PIN) of human proteome using the Gene Association Network (GAN). Furthermore, we enriched the BIN with the signalling and metabolic pathways and Gene Ontology (GO) terms to assert its functional context. Finally, we mapped the Single Nucleotide Polymorphisms (SNPs) from the GWAS studies and identified the chromatin mutational hot-spots associated with a significant enrichment of SNPs related to autoimmune diseases. Afterwards, we mapped Structural Variants (SVs) from healthy individuals of 1000 Genomes Project and identified an interesting example of the missing protein complex associated with protein Q6GYQ0 due to a deletion on chromosome 14. Such an analysis using the meta-network BIN model is therefore helpful in evaluating the influence of genetic variation on spatial organisation of the genome and its functional effect in a cell.

Application of long-read sequencing to the detection of structural variants in human cancer genomes

In recent years, the so-called long-read sequencing technology has had a substantial impact on various aspects of genome sciences. Here, we introduce recent studies of cancerous structural variants (SVs) using long-read sequencing technologies, namely Pacific Biosciences (PacBio) sequencers, Oxford Nanopore Technologies (ONT) sequencers, and linked-read methods. By taking advantage of long-read lengths, these technologies have enabled the precise detection of SVs, including long insertions by transposable elements, such as LINE-1. In addition to SV detection, the epigenome status (including DNA methylation and haplotype information) surrounding SV loci has also been unveiled by long-read sequencing technologies, to identify the effects of SVs. Among the various research fields in which long-read sequencing has been applied, cancer genomics has shown the most remarkable advances. In fact, many studies are beginning to shed light on the detection of SVs and the elucidation of their complex structures in various types of cancer. In the particular case of cancers, we summarize the technical limitations of the application of this technology to the analysis of clinical samples. We will introduce recent achievements from this viewpoint. However, a similar approach will be started for other applications in the near future. Therefore, by complementing the current short-read sequencing analysis, long-read sequencing should reveal the complex nature of human genomes in their healthy and disease states, which will open a new opportunity for a better understanding of disease development and for a novel strategy for drug development.

SVNN: an efficient PacBio-specific pipeline for structural variations calling using neural networks

Background

Once aligned, long-reads can be a useful source of information to identify the type and position of structural variations. However, due to the high sequencing error of long reads, long-read structural variation detection methods are far from precise in low-coverage cases. To be accurate, they need to use high-coverage data, which in turn, results in an extremely time-consuming pipeline, especially in the alignment phase. Therefore, it is of utmost importance to have a structural variation calling pipeline which is both fast and precise for low-coverage data.

Results

In this paper, we present SVNN, a fast yet accurate, structural variation calling pipeline for PacBio long-reads that takes raw reads as the input and detects structural variants of size larger than 50 bp. Our pipeline utilizes state-of-the-art long-read aligners, namely NGMLR and Minimap2, and structural variation callers, videlicet Sniffle and SVIM. We found that by using a neural network, we can extract features from Minimap2 output to detect a subset of reads that provide useful information for structural variation detection. By only mapping this subset with NGMLR, which is far slower than Minimap2 but better serves downstream structural variation detection, we can increase the sensitivity in an efficient way. As a result of using multiple tools intelligently, SVNN achieves up to 20 percentage points of sensitivity improvement in comparison with state-of-the-art methods and is three times faster than a naive combination of state-of-the-art tools to achieve almost the same accuracy.

Conclusion

Since prohibitive costs of using high-coverage data have impeded long-read applications, with SVNN, we provide the users with a much faster structural variation detection platform for PacBio reads with high precision and sensitivity in low-coverage scenarios.

reconCNV: interactive visualization of copy number data from high-throughput sequencing

SUMMARY

Copy number variation (CNV) is an important category of unbalanced structural rearrangement. While methods for detecting CNV in high-throughput targeted sequencing have become increasingly sophisticated, dedicated tools for interactive and dynamic visualization of CNV from these data are still lacking. We describe reconCNV, a tool that produces an interactive and annotated web-based dashboard for viewing and summarizing CNVs detected in next-generation sequencing (NGS) data. reconCNV is designed to work with delimited result files from most NGS CNV callers with minor adjustments to the configuration file. The reconCNV output is an HTML file that is viewable on any modern web browser, requires no backend server, and can be readily appended to existing analysis pipelines. In addition to a standard CNV track for visualizing relative fold change and absolute copy number, the tool includes an auxiliary variant allele fraction track for visualizing underlying allelic imbalance and loss of heterozygosity. A feature to mask assay-specific technical artifacts and a direct HTML link out to the UCSC Genome Browser are also included to augment the reviewer experience. By providing a light-weight plugin for interactive visualization to existing NGS CNV pipelines, reconCNV can facilitate efficient NGS CNV visualization and interpretation in both research and clinical settings.

AVAILABILITY AND IMPLEMENTATION

The source code and documentation including a tutorial can be accessed at https://github.com/rghu/reconCNV as well as a Docker image at https://hub.docker.com/repository/docker/raghuc1990/reconcnv.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

2-kupl: mapping-free variant detection from DNA-seq data of matched samples

BACKGROUND

The detection of genome variants, including point mutations, indels and structural variants, is a fundamental and challenging computational problem. We address here the problem of variant detection between two deep-sequencing (DNA-seq) samples, such as two human samples from an individual patient, or two samples from distinct bacterial strains. The preferred strategy in such a case is to align each sample to a common reference genome, collect all variants and compare these variants between samples. Such mapping-based protocols have several limitations. DNA sequences with large indels, aggregated mutations and structural variants are hard to map to the reference. Furthermore, DNA sequences cannot be mapped reliably to genomic low complexity regions and repeats.

RESULTS

We introduce 2-kupl, a k-mer based, mapping-free protocol to detect variants between two DNA-seq samples. On simulated and actual data, 2-kupl achieves higher accuracy than other mapping-free protocols. Applying 2-kupl to prostate cancer whole exome sequencing data, we identify a number of candidate variants in hard-to-map regions and propose potential novel recurrent variants in this disease.

CONCLUSIONS

We developed a mapping-free protocol for variant calling between matched DNA-seq samples. Our protocol is suitable for variant detection in unmappable genome regions or in the absence of a reference genome.

Characterization of structural variation in Tibetans reveals new evidence of high-altitude adaptation and introgression

BACKGROUND

Structural variation (SV) acts as an essential mutational force shaping the evolution and function of the human genome. However, few studies have examined the role of SVs in high-altitude adaptation and little is known of adaptive introgressed SVs in Tibetans so far.

RESULTS

Here, we generate a comprehensive catalog of SVs in a Chinese Tibetan (n = 15) and Han (n = 10) population using nanopore sequencing technology. Among a total of 38,216 unique SVs in the catalog, 27% are sequence-resolved for the first time. We systematically assess the distribution of these SVs across repeat sequences and functional genomic regions. Through genotyping in additional 276 genomes, we identify 69 Tibetan-Han stratified SVs and 80 candidate adaptive genes. We also discover a few adaptive introgressed SV candidates and provide evidence for a deletion of 335 base pairs at 1p36.32.

CONCLUSIONS

Overall, our results highlight the important role of SVs in the evolutionary processes of Tibetans' adaptation to the Qinghai-Tibet Plateau and provide a valuable resource for future high-altitude adaptation studies.

Genomic Variation, Evolvability, and the Paradox of Mental Illness

Twentieth-century genetics was hard put to explain the irregular behavior of neuropsychiatric disorders. Autism and schizophrenia defy a principle of natural selection; they are highly heritable but associated with low reproductive success. Nevertheless, they persist. The genetic origins of such conditions are confounded by the problem of variable expression, that is, when a given genetic aberration can lead to any one of several distinct disorders. Also, autism and schizophrenia occur on a spectrum of severity, from mild and subclinical cases to the overt and disabling. Such irregularities reflect the problem of missing heritability; although hundreds of genes may be associated with autism or schizophrenia, together they account for only a small proportion of cases. Techniques for higher resolution, genomewide analysis have begun to illuminate the irregular and unpredictable behavior of the human genome. Thus, the origins of neuropsychiatric disorders in particular and complex disease in general have been illuminated. The human genome is characterized by a high degree of structural and behavioral variability: DNA content variation, epistasis, stochasticity in gene expression, and epigenetic changes. These elements have grown more complex as evolution scaled the phylogenetic tree. They are especially pertinent to brain development and function. Genomic variability is a window on the origins of complex disease, neuropsychiatric disorders, and neurodevelopmental disorders in particular. Genomic variability, as it happens, is also the fuel of evolvability. The genomic events that presided over the evolution of the primate and hominid lineages are over-represented in patients with autism and schizophrenia, as well as intellectual disability and epilepsy. That the special qualities of the human genome that drove evolution might, in some way, contribute to neuropsychiatric disorders is a matter of no little interest.

Integrative analysis of structural variations using short-reads and linked-reads yields highly specific and sensitive predictions

Genetic diseases are driven by aberrations of the human genome. Identification of such aberrations including structural variations (SVs) is key to our understanding. Conventional short-reads whole genome sequencing (cWGS) can identify SVs to base-pair resolution, but utilizes only short-range information and suffers from high false discovery rate (FDR). Linked-reads sequencing (10XWGS) utilizes long-range information by linkage of short-reads originating from the same large DNA molecule. This can mitigate alignment-based artefacts especially in repetitive regions and should enable better prediction of SVs. However, an unbiased evaluation of this technology is not available. In this study, we performed a comprehensive analysis of different types and sizes of SVs predicted by both the technologies and validated with an independent PCR based approach. The SVs commonly identified by both the technologies were highly specific, while validation rate dropped for uncommon events. A particularly high FDR was observed for SVs only found by 10XWGS. To improve FDR and sensitivity, statistical models for both the technologies were trained. Using our approach, we characterized SVs from the MCF7 cell line and a primary breast cancer tumor with high precision. This approach improves SV prediction and can therefore help in understanding the underlying genetics in various diseases.

Cancer and many other diseases are often driven by structural rearrangements in the patients. Their precise identification is necessary to understand evolution and cure for the disease. In this study, we have compared two sequencing technologies for the identification of structural variations i.e. Illumina’s short-reads and 10X Genomics linked-reads sequencing. Short-reads sequencing is already known to have high false discovery rate for structural variations, while, an unbiased performance evaluation of linked-reads sequencing is missing. Hence, we evaluate the performance of these two technologies using computational and PCR based methodologies. Moreover, we also present a statistical approach to increase their performance, supporting better detection of structural variations and thus further research into disease biology.

Polyunsaturated fatty acid biosynthesis pathway and genetics. implications for interindividual variability in prothrombotic, inflammatory conditions such as COVID-19✰,✰✰,★,★★

COVID-19 symptoms vary from silence to rapid death, the latter mediated by both a cytokine storm and a thrombotic storm. SARS-CoV (2003) induces Cox-2, catalyzing the synthesis, from highly unsaturated fatty acids (HUFA), of eicosanoids and docosanoids that mediate both inflammation and thrombosis. HUFA balance between arachidonic acid (AA) and other HUFA is a likely determinant of net signaling to induce a healthy or runaway physiological response. AA levels are determined by a non-protein coding regulatory polymorphisms that mostly affect the expression of FADS1, located in the FADS gene cluster on chromosome 11. Major and minor haplotypes in Europeans, and a specific functional insertion-deletion (Indel), rs66698963, consistently show major differences in circulating AA (>50%) and in the balance between AA and other HUFA (47-84%) in free living humans; the indel is evolutionarily selective, probably based on diet. The pattern of fatty acid responses is fully consistent with specific genetic modulation of desaturation at the FADS1-mediated 20:3→20:4 step. Well established principles of net tissue HUFA levels indicate that the high linoleic acid and low alpha-linoleic acid in populations drive the net balance of HUFA for any individual. We predict that fast desaturators (insertion allele at rs66698963; major haplotype in Europeans) are predisposed to higher risk and pathological responses to SARS-CoV-2 could be reduced with high dose omega-3 HUFA.

Cas9 Cuts and Consequences; Detecting, Predicting, and Mitigating CRISPR/Cas9 On- and Off-Target Damage: Techniques for Detecting, Predicting, and Mitigating the On- and off-target Effects of Cas9 Editing

Large deletions and genomic re-arrangements are increasingly recognized as common products of double-strand break repair at Clustered Regularly Interspaced, Short Palindromic Repeats - CRISPR associated protein 9 (CRISPR/Cas9) on-target sites. Together with well-known off-target editing products from Cas9 target misrecognition, these are important limitations, that need to be addressed. Rigorous assessment of Cas9-editing is necessary to ensure validity of observed phenotypes in Cas9-edited cell-lines and model organisms. Here the mechanisms of Cas9 specificity, and strategies to assess and mitigate unwanted effects of Cas9 editing are reviewed; covering guide-RNA design, RNA modifications, Cas9 modifications, control of Cas9 activity; computational prediction for off-targets, and experimental methods for detecting Cas9 cleavage. Although recognition of the prevalence of on- and off-target effects of Cas9 editing has increased in recent years, broader uptake across the gene editing community will be important in determining the specificity of Cas9 across diverse applications and organisms.

Prenatal Diagnosis of a De Novo Partial Trisomy 6q and Partial Monosomy 18p Associated with Cephalocele: A Case Report

A 28-year-old woman underwent amniocentesis at 18 weeks’ gestation upon detection of increased fetal nuchal fold and parietal cephalocele on the second trimester ultrasound examination. Prenatal microarray showed a de novo unbalanced translocation resulting in a gain in 6q and loss in 18p. A female infant was delivered at 38 weeks’ gestation. At birth, cephalocele and webbed neck were noted as major dysmorphic features. The case presented here shows how a combination of different genetic studies is used to accurately elucidate a chromosomal anomaly in a prenatal setting.

A structural variation reference for medical and population genetics

Structural variants (SVs) rearrange large segments of DNA¹ and can have profound consequences in evolution and human disease^2,3. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)⁴ have become integral in the interpretation of single-nucleotide variants (SNVs)⁵. However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25–29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage⁶. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings⁷. This SV resource is freely distributed via the gnomAD browser⁸ and will have broad utility in population genetics, disease-association studies, and diagnostic screening.

A large empirical assessment of sequence-resolved structural variants from 14,891 genomes across diverse global populations in the Genome Aggregation Database (gnomAD) provides a reference map for disease-association studies, population genetics, and diagnostic screening.

NanoVar: accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing

The recent advent of third-generation sequencing technologies brings promise for better characterization of genomic structural variants by virtue of having longer reads. However, long-read applications are still constrained by their high sequencing error rates and low sequencing throughput. Here, we present NanoVar, an optimized structural variant caller utilizing low-depth (8X) whole-genome sequencing data generated by Oxford Nanopore Technologies. NanoVar exhibits higher structural variant calling accuracy when benchmarked against current tools using low-depth simulated datasets. In patient samples, we successfully validate structural variants characterized by NanoVar and uncover normal alternative sequences or alleles which are present in healthy individuals.

Genome analysis and knowledge-driven variant interpretation with TGex

BACKGROUND

The clinical genetics revolution ushers in great opportunities, accompanied by significant challenges. The fundamental mission in clinical genetics is to analyze genomes, and to identify the most relevant genetic variations underlying a patient's phenotypes and symptoms. The adoption of Whole Genome Sequencing requires novel capacities for interpretation of non-coding variants.

RESULTS

We present TGex, the Translational Genomics expert, a novel genome variation analysis and interpretation platform, with remarkable exome analysis capacities and a pioneering approach of non-coding variants interpretation. TGex's main strength is combining state-of-the-art variant filtering with knowledge-driven analysis made possible by VarElect, our highly effective gene-phenotype interpretation tool. VarElect leverages the widely used GeneCards knowledgebase, which integrates information from > 150 automatically-mined data sources. Access to such a comprehensive data compendium also facilitates TGex's broad variant annotation, supporting evidence exploration, and decision making. TGex has an interactive, user-friendly, and easy adaptive interface, ACMG compliance, and an automated reporting system. Beyond comprehensive whole exome sequence capabilities, TGex encompasses innovative non-coding variants interpretation, towards the goal of maximal exploitation of whole genome sequence analyses in the clinical genetics practice. This is enabled by GeneCards' recently developed GeneHancer, a novel integrative and fully annotated database of human enhancers and promoters. Examining use-cases from a variety of TGex users world-wide, we demonstrate its high diagnostic yields (42% for single exome and 50% for trios in 1500 rare genetic disease cases) and critical actionable genetic findings. The platform's support for integration with EHR and LIMS through dedicated APIs facilitates automated retrieval of patient data for TGex's customizable reporting engine, establishing a rapid and cost-effective workflow for an entire range of clinical genetic testing, including rare disorders, cancer predisposition, tumor biopsies and health screening.

CONCLUSIONS

TGex is an innovative tool for the annotation, analysis and prioritization of coding and non-coding genomic variants. It provides access to an extensive knowledgebase of genomic annotations, with intuitive and flexible configuration options, allows quick adaptation, and addresses various workflow requirements. It thus simplifies and accelerates variant interpretation in clinical genetics workflows, with remarkable diagnostic yield, as exemplified in the described use cases. TGex is available at http://tgex.genecards.org/.

The X chromosome and male infertility

The X chromosome is a key player in germ cell development, as has been highlighted for males in previous studies revealing that the mammalian X chromosome is enriched in genes expressed in early spermatogenesis. In this review, we focus on the X chromosome’s unique biology as associated with human male infertility. Male infertility is most commonly caused by spermatogenic defects to which X chromosome dosage is closely linked; for example, any supernumerary X chromosome as in Klinefelter syndrome will lead to male infertility. Furthermore, because males normally only have a single X chromosome and because X-linked genetic anomalies are generally only present in a single copy in males, any loss-of-function mutations in single-copy X-chromosomal genes cannot be compensated by a normal allele. These features make X-linked genes particularly attractive for studying male spermatogenic failure. However, to date, only very few genetic causes have been identified as being definitively responsible for male infertility in humans. Although genetic studies of germ cell-enriched X-chromosomal genes in mice suggest a role of certain human orthologs in infertile men, these genes in mice and humans have striking evolutionary differences. Furthermore, the complexity and highly repetitive structure of the X chromosome hinder the mutational analysis of X-linked genes in humans. Therefore, we conclude that additional methodological approaches are urgently warranted to advance our understanding of the genetics of X-linked male infertility.

Progress in finding pathogenic DNA copy number variations in dyslipidemia

PURPOSE OF REVIEW

DNA copy number variations (CNVs) are large-scale mutations that include deletions and duplications larger than 50 bp in size. In the era when single-nucleotide variations were the major focus of genetic technology and research, CNVs were largely overlooked. However, CNVs clearly underlie a substantial proportion of clinical disorders. Here, we update recent progress in identifying CNVs in dyslipidemias.

RECENT FINDINGS

Until last year, only the LDLR and LPA genes were appreciated as loci within which clinically relevant CNVs contributed to familial hypercholesterolemia and variation in Lp(a) levels, respectively. Since 2017, next-generation sequencing panels have identified pathogenic CNVs in at least five more genes underlying dyslipidemias, including a PCSK9 whole-gene duplication in familial hypercholesterolemia; LPL, GPIHBP1, and APOC2 deletions in hypertriglyceridemia; and ABCA1 deletions in hypoalphalipoproteinemia.

SUMMARY

CNVs are an important class of mutation that contribute to the molecular genetic heterogeneity underlying dyslipidemias. Clinical applications of next-generation sequencing technologies need to consider CNVs concurrently with familiar small-scale genetic variation, given the likely implications for improved diagnosis and treatment.

INDEX-db: The Indian Exome Reference Database (Phase I)

Deep sequencing-based genetic mapping has greatly enhanced the ability to catalog variants with plausible disease association. Confirming how these identified variants contribute to specific disease conditions, across human populations, poses the next challenge. Differential selection pressure may impact the frequency of genetic variations, and thus detection of association with disease conditions, across populations. To understand genotype to phenotype correlations, it thus becomes important to first understand the spectrum of genetic variation within a population by creating a reference map. In this study, we report the development of phase I of a new database of genetic variations called INDian EXome database (INDEX-db), from the Indian population, with an aim to establish a centralized database of integrated information. This could be useful for researchers involved in studying disease mechanisms at clinical, genetic, and cellular levels.

Dosage Compensation of the X Chromosomes in Bovine Germline, Early Embryos, and Somatic Tissues

Dosage compensation of the mammalian X chromosome (X) was proposed by Susumu Ohno as a mechanism wherein the inactivation of one X in females would lead to doubling the expression of the other. This would resolve the dosage imbalance between eutherian females (XX) versus male (XY) and between a single active X versus autosome pairs (A). Expression ratio of X- and A-linked genes has been relatively well studied in humans and mice, despite controversial results over the existence of upregulation of X-linked genes. Here we report the first comprehensive test of Ohno’s hypothesis in bovine preattachment embryos, germline, and somatic tissues. Overall an incomplete dosage compensation (0.5 < X:A < 1) of expressed genes and an excess X dosage compensation (X:A > 1) of ubiquitously expressed “dosage-sensitive” genes were seen. No significant differences in X:A ratios were observed between bovine female and male somatic tissues, further supporting Ohno’s hypothesis. Interestingly, preimplantation embryos manifested a unique pattern of X dosage compensation dynamics. Specifically, X dosage decreased after fertilization, indicating that the sperm brings in an inactive X to the matured oocyte. Subsequently, the activation of the bovine embryonic genome enhanced expression of X-linked genes and increased the X dosage. As a result, an excess compensation was exhibited from the 8-cell stage to the compact morula stage. The X dosage peaked at the 16-cell stage and stabilized after the blastocyst stage. Together, our findings confirm Ohno’s hypothesis of X dosage compensation in the bovine and extend it by showing incomplete and over-compensation for expressed and “dosage-sensitive” genes, respectively.

Trajectory of exonic variant discovery in a large clinical population: implications for variant curation

PURPOSE

Precision health initiatives and reduced sequencing costs are driving large-scale human genome analyses. Genetic variant curation is a bottleneck in clinical applications. The burden of variant curation can be high for newly discovered variants because they are less likely to have undergone previous clinical annotation; the rate of discovery of genetic variants in large clinical populations has not been empirically determined.

METHODS

We determined the rate of accrual of unique sequence variants in 90,000 exome sequences. Separate analyses were done for 17,267 autosomal genes and a subset of 74 actionable genes; the effect of relatedness in the cohort was also determined.

RESULTS

Variant discovery showed a nonlinear growth pattern. The rate of unique variant accrual decreased as the database size increased; by 90,000 exomes 97% of all projected coding and splicing variants had been observed. Variants in 74 actionable genes showed a similar pattern. Family relatedness slightly reduced the rate of discovery of unique variants.

CONCLUSION

The heaviest burden of interpretation for genetic variants occurs early and diminishes as the database size increases. Our data provide a framework for scaling pathogenic genetic variant discovery and curation, a critical element of patient care in the era of precision health.

A Megabase-Scale Deletion is Associated with Phenotypic Variation of Multiple Traits in Maize

Genomic deletions are pervasive in the maize (Zea mays L.) genome, and play important roles in phenotypic variation and adaptive evolution. However, little is known about the biological functions of these genomic deletions. Here, we report the biological function of a megabase-scale deletion, which we identified by position-based cloning of the multi-trait weakened (muw) mutant, which is inherited as a single recessive locus. MUW was mapped to a 5.16-Mb region on chromosome 2. The 5.16-Mb deletion in the muw mutant led to the loss of 48 genes and was responsible for a set of phenotypic abnormities, including wilting leaves, poor yield performance, reduced plant height, increased stomatal density, and rapid water loss. While muw appears to have resulted from double-stranded break repair that was not dependent on intragenomic DNA homology, extensive duplication of maize genes may have mitigated its effects and facilitated its survival.

Structural variations causing inherited peripheral neuropathies: A paradigm for understanding genomic organization, chromatin interactions, and gene dysregulation

Inherited peripheral neuropathies (IPNs) are a clinically and genetically heterogeneous group of diseases affecting the motor and sensory peripheral nerves. IPNs have benefited from gene discovery and genetic diagnosis using next-generation sequencing with over 80 causative genes available for testing. Despite this success, up to 50% of cases remain genetically unsolved. In the absence of protein coding mutations, noncoding DNA or structural variation (SV) mutations are a possible explanation. The most common IPN, Charcot-Marie-Tooth neuropathy type 1A (CMT1A), is caused by a 1.5 Mb duplication causing trisomy of the dosage sensitive gene PMP22. Using genome sequencing, we recently identified two large genomic rearrangements causing IPN subtypes X-linked CMT (CMTX3) and distal hereditary motor neuropathy (DHMN1), thereby expanding the spectrum of SV mutations causing IPN. Understanding how newly discovered SVs can cause IPN may serve as a useful paradigm to examine the role of topologically associated domains (TADs), chromatin interactions, and gene dysregulation in disease. This review will describe the growing role of SV in the pathogenesis of IPN and the importance of considering this type of mutation in Mendelian diseases where protein coding mutations cannot be identified.