High-resolution genomic profiling of chromosomal aberrations using Infinium whole-genome genotyping

Prevalence of sex-chromosome aneuploidy estimated using SNP genotype intensity information in a large population of juvenile dairy and beef cattle

Aneuploidy is a genetic condition characterized by the loss or gain of one or more chromosomes. Aneuploidy affecting the sex chromosomes can lead to infertility in otherwise externally phenotypically normal cattle. Early identification of cattle with sex chromosomal aneuploidy is important to minimize the costs associated with rearing infertile cattle and futile breeding attempts. As most livestock breeding programs routinely genotype their breeding populations using single nucleotide polymorphism (SNP) arrays, this study aimed to assess the feasibility of integrating an aneuploidy screening tool into the existing pipelines that handle dense SNP genotype data. A further objective was to estimate the prevalence of sex chromosome aneuploidy in a population of 146,431 juvenile cattle using available genotype intensity data. Three genotype intensity statistics were used: the LogR Ratio (LRR), R-value (the sum of X and Y SNP probe intensities), and B-allele frequency (BAF) measurements. Within the female-verified population of 124,958 individuals, the estimated prevalence rate was 0.0048% for XO, 0.0350% for XXX, and 0.0004% for XXY. The prevalence of XXY in the male-verified population was 0.0870% (i.e., 18 out of 20,670 males). Cytogenetic testing was used to verify 2 of the XXX females who were still alive. The proposed approach can be readily integrated into existing genomic pipelines, serving as an efficient, large-scale screening tool for aneuploidy. Its implementation could enable the early identification of infertile animals with sex-chromosome aneuploidy.

High-Resolution Genotyping of Formalin-Fixed Tissue Accurately Estimates Polygenic Risk Scores in Human Diseases

Formalin-fixed paraffin-embedded (FFPE) tissues stored in biobanks and pathology archives are a vast but underutilized source for molecular studies on different diseases. Beyond being the "gold standard" for preservation of diagnostic human tissues, FFPE samples retain similar genetic information as matching blood samples, which could make FFPE samples an ideal resource for genomic analysis. However, research on this resource has been hindered by the perception that DNA extracted from FFPE samples is of poor quality. Here, we show that germline disease-predisposing variants and polygenic risk scores (PRS) can be identified from FFPE normal tissue (FFPE-NT) DNA with high accuracy. We optimized the performance of FFPE-NT DNA on a genome-wide array containing 657,675 variants. Via a series of testing and validation phases, we established a protocol for FFPE-NT genotyping with results comparable with blood genotyping. The median call rate of FFPE-NT samples in the validation phase was 99.85% (range 98.26%-99.94%) and median concordance with matching blood samples was 99.79% (range 98.85%-99.9%). We also demonstrated that a rare pathogenic PALB2 genetic variant predisposing to cancer can be correctly identified in FFPE-NT samples. We further imputed the FFPE-NT genotype data and calculated the FFPE-NT genome-wide PRS in 3 diseases and 4 disease risk variables. In all cases, FFPE-NT and matching blood PRS were highly concordant (all Pearson's r > 0.95). The ability to precisely genotype FFPE-NT on a genome-wide array enables translational genomics applications of archived FFPE-NT samples with the possibility to link to corresponding phenotypes and longitudinal health data.

Lowering of Circulating Sclerostin May Increase Risk of Atherosclerosis and Its Risk Factors: Evidence From a Genome-Wide Association Meta-Analysis Followed by Mendelian Randomization

OBJECTIVE

In this study, we aimed to establish the causal effects of lowering sclerostin, target of the antiosteoporosis drug romosozumab, on atherosclerosis and its risk factors.

METHODS

A genome-wide association study meta-analysis was performed of circulating sclerostin levels in 33,961 European individuals. Mendelian randomization (MR) was used to predict the causal effects of sclerostin lowering on 15 atherosclerosis-related diseases and risk factors.

RESULTS

We found that 18 conditionally independent variants were associated with circulating sclerostin. Of these, 1 cis signal in SOST and 3 trans signals in B4GALNT3, RIN3, and SERPINA1 regions showed directionally opposite signals for sclerostin levels and estimated bone mineral density. Variants with these 4 regions were selected as genetic instruments. MR using 5 correlated cis-SNPs suggested that lower sclerostin increased the risk of type 2 diabetes mellitus (DM) (odds ratio [OR] 1.32 [95% confidence interval (95% CI) 1.03-1.69]) and myocardial infarction (MI) (OR 1.35 [95% CI 1.01-1.79]); sclerostin lowering was also suggested to increase the extent of coronary artery calcification (CAC) (β = 0.24 [95% CI 0.02-0.45]). MR using both cis and trans instruments suggested that lower sclerostin increased hypertension risk (OR 1.09 [95% CI 1.04-1.15]), but otherwise had attenuated effects.

CONCLUSION

This study provides genetic evidence to suggest that lower levels of sclerostin may increase the risk of hypertension, type 2 DM, MI, and the extent of CAC. Taken together, these findings underscore the requirement for strategies to mitigate potential adverse effects of romosozumab treatment on atherosclerosis and its related risk factors.

Rare recurrent copy number variations in metabotropic glutamate receptor interacting genes in children with neurodevelopmental disorders

BACKGROUND

Neurodevelopmental disorders (NDDs), such as attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), are examples of complex and partially overlapping phenotypes that often lack definitive corroborating genetic information. ADHD and ASD have complex genetic associations implicated by rare recurrent copy number variations (CNVs). Both of these NDDs have been shown to share similar biological etiologies as well as genetic pleiotropy.

METHODS

Platforms aimed at investigating genetic-based associations, such as high-density microarray technologies, have been groundbreaking techniques in the field of complex diseases, aimed at elucidating the underlying disease biology. Previous studies have uncovered CNVs associated with genes within shared candidate genomic networks, including glutamate receptor genes, across multiple different NDDs. To examine shared biological pathways across two of the most common NDDs, we investigated CNVs across 15,689 individuals with ADHD (n = 7920), ASD (n = 4318), or both (n = 3,416), as well as 19,993 controls. Cases and controls were matched by genotype array (i.e., Illumina array versions). Three case-control association studies each calculated and compared the observed vs. expected frequency of CNVs across individual genes, loci, pathways, and gene networks. Quality control measures of confidence in CNV-calling, prior to association analyses, included visual inspection of genotype and hybridization intensity.

RESULTS

Here, we report results from CNV analysis in search for individual genes, loci, pathways, and gene networks. To extend our previous observations implicating a key role of the metabotropic glutamate receptor (mGluR) network in both ADHD and autism, we exhaustively queried patients with ASD and/or ADHD for CNVs associated with the 273 genomic regions of interest within the mGluR gene network (genes with one or two degrees protein-protein interaction with mGluR 1-8 genes). Among CNVs in mGluR network genes, we uncovered CNTN4 deletions enriched in NDD cases (P = 3.22E - 26, OR = 2.49). Additionally, we uncovered PRLHR deletions in 40 ADHD cases and 12 controls (P = 5.26E - 13, OR = 8.45) as well as clinically diagnostic relevant 22q11.2 duplications and 16p11.2 duplications in 23 ADHD + ASD cases and 9 controls (P = 4.08E - 13, OR = 15.05) and 22q11.2 duplications in 34 ADHD + ASD cases and 51 controls (P = 9.21E - 9, OR = 3.93); those control samples were not with previous 22qDS diagnosis in their EHR records.

CONCLUSION

Together, these results suggest that disruption in neuronal cell-adhesion pathways confers significant risk to NDDs and showcase that rare recurrent CNVs in CNTN4, 22q11.2, and 16p11.2 are overrepresented in NDDs that constitute patients predominantly suffering from ADHD and ASD.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02286817 First Posted: 10 November 14, ClinicalTrials.gov Identifier: NCT02777931 first posted: 19 May 2016, ClinicalTrials.gov Identifier: NCT03006367 first posted: 30 December 2016, ClinicalTrials.gov Identifier: NCT02895906 first posted: 12 September 2016.

Genome-wide copy number variant screening of Saudi schizophrenia patients reveals larger deletions in cases versus controls

Introduction

Genome-wide association studies have discovered common polymorphisms in regions associated with schizophrenia. No genome-wide analyses have been performed in Saudi schizophrenia subjects.

Methods

Genome-wide genotyping data from 136 Saudi schizophrenia cases and 97 Saudi controls in addition to 4,625 American were examined for copy number variants (CNVs). A hidden Markov model approach was used to call CNVs.

Results

CNVs in schizophrenia cases were twice as large on average than CNVs in controls (p = 0.04). The analyses focused on extremely large >250 kilobases CNVs or homozygous deletions of any size. One extremely large deletion was noted in a single case (16.5 megabases on chromosome 10). Two cases had an 814 kb duplication of chromosome 7 spanning a cluster of genes, including circadian-related loci, and two other cases had 277 kb deletions of chromosome 9 encompassing an olfactory receptors gene family. CNVs were also seen in loci previously associated with schizophrenia, namely a 16p11 proximal duplication and two 22q11.2 deletions.

Discussion

Runs of homozygosity (ROHs) were analyzed across the genome to investigate correlation with schizophrenia risk. While rates and sizes of these ROHs were similar in cases and controls, we identified 10 regions where multiple cases had ROHs and controls did not.

A risk-based approach for cell line development, manufacturing and characterization of genetically engineered, induced pluripotent stem cell-derived allogeneic cell therapies

Advances in cellular reprogramming and gene-editing approaches have opened up the potential for a new class of ex vivo cell therapies based on genetically engineered, induced pluripotent stem cell (iPSC)-derived allogeneic cells. While these new therapies share some similarities with their primary cell-derived autologous and allogeneic cell therapy predecessors, key differences exist in the processes used for generating genetically engineered, iPSC-derived allogeneic therapies. Specifically, in iPSC-derived allogeneic therapies, donor selection and gene-editing are performed once over the lifetime of the product as opposed to as part of the manufacturing of each product batch. The introduction of a well-characterized, fully modified, clonally derived master cell bank reduces risks that have been inherent to primary-cell derived autologous and allogeneic therapies. Current regulatory guidance, which was largely developed based on the learnings gained from earlier generation therapies, leaves open questions around considerations for donor eligibility, starting materials and critical components, cell banking and genetic stability. Here, a risk-based approach is proposed to address these considerations, while regulatory guidance continues to evolve.

Single Nucleotide Polymorphism (SNP) Arrays and Their Sensitivity for Detection of Genetic Changes in Human Pluripotent Stem Cell Cultures

Human pluripotent stem cells (hPSCs) can be grown in culture indefinitely, making them a valuable tool for use in basic biology, disease modeling, and regenerative medicine. However, over prolonged periods in culture, hPSCs tend to acquire genomic aberrations that confer growth advantages, similar to those seen in some cancers. Monitoring the genomic stability of cultured hPSCs is critical to ensuring their efficacy and safety as a therapeutic tool. Most commonly employed methods for monitoring of hPSC genomes are cytogenetic methods, such as G-banding. Nonetheless, such methods have limited resolution and sensitivity for detecting mosaicism. Single nucleotide polymorphism (SNP) array platforms are a potential alternative that could improve detection of abnormalities. Here, we outline protocols for SNP array whole-genome screening of hPSCs. Moreover, we detail the procedure for assessing the SNP array's sensitivity in detecting low-level mosaic copy-number changes. We show that mosaicism can be confidently identified in samples only once they contain 20% variants, although samples containing 10% variants typically display enough variation to warrant further investigation and confirmation, for example by using a more sensitive targeted method. Finally, we highlight the advantages and limitations of SNP arrays, including a cost comparison of SNP arrays versus other commonly employed methods for detection of genetic changes in hPSC cultures. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: DNA sample preparation for SNP arrays Basic Protocol 2: SNP array hybridization, washing, and scanning Basic Protocol 3: SNP array data analysis Support Protocol: Assessment of SNP array sensitivity for detection of mosaicism.

Influences of rare copy-number variation on human complex traits

The human genome contains hundreds of thousands of regions harboring copy-number variants (CNV). However, the phenotypic effects of most such polymorphisms are unknown because only larger CNVs have been ascertainable from SNP-array data generated by large biobanks. We developed a computational approach leveraging haplotype sharing in biobank cohorts to more sensitively detect CNVs. Applied to UK Biobank, this approach accounted for approximately half of all rare gene inactivation events produced by genomic structural variation. This CNV call set enabled a detailed analysis of associations between CNVs and 56 quantitative traits, identifying 269 independent associations (p < 5 × 10-8) likely to be causally driven by CNVs. Putative target genes were identifiable for nearly half of the loci, enabling insights into dosage sensitivity of these genes and uncovering several gene-trait relationships. These results demonstrate the ability of haplotype-informed analysis to provide insights into the genetic basis of human complex traits.

Copy Number Variation Analysis Facilitates Identification of Genetic Causation in Patients with Congenital Anomalies of the Kidney and Urinary Tract

Background

Congenital anomalies of the kidneys and urinary tract (CAKUT) are the most common cause of chronic kidney disease among children and adults younger than 30 yr. In our previous study, whole-exome sequencing (WES) identified a known monogenic cause of isolated or syndromic CAKUT in 13% of families with CAKUT. However, WES has limitations and detection of copy number variations (CNV) is technically challenging, and CNVs causative of CAKUT have previously been detected in up to 16% of cases.

Objective

To detect CNVs causing CAKUT in this WES cohort and increase the diagnostic yield.

Design setting and participants

We performed a genome-wide single nucleotide polymorphism (SNP)-based CNV analysis on the same CAKUT cohort for whom WES was previously conducted.

Outcome measurements and statistical analysis

We evaluated and classified the CNVs using previously published predefined criteria.

Results and limitations

In a cohort of 170 CAKUT families, we detected a pathogenic CNV known to cause CAKUT in nine families (5.29%, 9/170). There were no competing variants on genome-wide CNV analysis or WES analysis. In addition, we identified novel likely pathogenic CNVs that may cause a CAKUT phenotype in three of the 170 families (1.76%).

Conclusions

CNV analysis in this cohort of 170 CAKUT families previously examined via WES increased the rate of diagnosis of genetic causes of CAKUT from 13% on WES to 18% on WES + CNV analysis combined. We also identified three candidate loci that may potentially cause CAKUT.

Patient summary

We conducted a genetics study on families with congenital anomalies of the kidney and urinary tract (CAKUT). We identified gene mutations that can explain CAKUT symptoms in 5.29% of the families, which increased the percentage of genetic causes of CAKUT to 18% from a previous study, so roughly one in five of our patients with CAKUT had a genetic cause. These analyses can help patients with CAKUT and their families in identifying a possible genetic cause.

Inheritance of somatic mutations by animal offspring

Since 1892, it has been widely assumed that somatic mutations are evolutionarily irrelevant in animals because they cannot be inherited by offspring. However, some nonbilaterians segregate the soma and germline late in development or never, leaving the evolutionary fate of their somatic mutations unknown. By investigating uni- and biparental reproduction in the coral Acropora palmata (Cnidaria, Anthozoa), we found that uniparental, meiotic offspring harbored 50% of the 268 somatic mutations present in their parent. Thus, somatic mutations accumulated in adult coral animals, entered the germline, and were passed on to swimming larvae that grew into healthy juvenile corals. In this way, somatic mutations can increase allelic diversity and facilitate adaptation across habitats and generations in animals.

Genome-wide evaluation of copy gain and loss variations in three Afghan sheep breeds

Copy number variation (CNV) is one of the main sources of variation between different individuals that has recently attracted much researcher interest as a major source for heritable variation in complex traits. The aim of this study was to identify CNVs in Afghan indigenous sheep consisting of three Arab, Baluchi, and Gadik breeds using genomic arrays containing 53,862 single nucleotide polymorphism (SNP) markers. Data were analyzed using the Hidden Markov Model (HMM) of PennCNV software. In this study, out of 45 sheep studied, 97.8% (44 animals) have shown CNVs. In total, 411 CNVs were observed for autosomal chromosomes and the entire sequence length of around 144 Mb was identified across the genome. The average number of CNVs per each sheep was 9.13. The identified CNVs for Arab, Baluchi, and Gadik breeds were 306, 62, and 43, respectively. After merging overlapped regions, a total of 376 copy number variation regions (CNVR) were identified, which are 286, 50, and 40 for Arab, Baluchi, and Gadik breeds, respectively. Bioinformatics analysis was performed to identify the genes and QTLs reported in these regions and the biochemical pathways involved by these genes. The results showed that many of these CNVRs overlapped with the genes or QTLs that are associated with various pathways such as immune system development, growth, reproduction, and environmental adaptions. Furthermore, to determine a genome-wide pattern of selection signatures in Afghan sheep breeds, the unbiased estimates of FST was calculated and the results indicated that 37 of the 376 CNVRs (~ 10%) have been also under selection signature, most of those overlapped with the genes influencing production, reproduction and immune system. Finally, the statistical methods used in this study was applied in an external dataset including 96 individuals of the Iranian sheep breed. The results indicated that 20 of the 114 CNVRs (18%) identified in Iranian sheep breed were also identified in our study, most of those overlapped with the genes influencing production, reproduction and immune system. Overall, this is the first attempts to develop the genomic map of loss and gain variation in the genome of Afghan indigenous sheep breeds, and may be important to shed some light on the genomic regions associated with some economically important traits in these breeds.

Genome-wide identification of copy number variation and association with fat deposition in thin and fat-tailed sheep breeds

Copy number variants (CNVs) are a type of genetic polymorphism which contribute to phenotypic variation in several species, including livestock. In this study, we used genomic data of 192 animals from 3 Iranian sheep breeds including 96 Baluchi sheep and 47 Lori-Bakhtiari sheep as fat-tailed breeds and 47 Zel sheep as thin-tailed sheep breed genotyped with Illumina OvineSNP50K Beadchip arrays. Also, for association test, 70 samples of Valle del Belice sheep were added to the association test as thin-tailed sheep breed. PennCNV and CNVRuler software were, respectively, used to study the copy number variation and genomic association analyses. We detected 573 and 242 CNVs in the fat and thin tailed breeds, respectively. In terms of CNV regions (CNVRs), these represented 328 and 187 CNVRs that were within or overlapping with 790 known Ovine genes. The CNVRs covered approximately 73.85 Mb of the sheep genome with average length 146.88 kb, and corresponded to 2.6% of the autosomal genome sequence. Five CNVRs were randomly chosen for validation, of which 4 were experimentally confirmed using Real time qPCR. Functional enrichment analysis showed that genes harbouring CNVs in thin-tailed sheep were involved in the adaptive immune response, regulation of reactive oxygen species biosynthetic process and response to starvation. In fat-tailed breeds these genes were involved in cellular protein modification process, regulation of heart rate, intestinal absorption, olfactory receptor activity and ATP binding. Association test identified one copy gained CNVR on chromosomes 6 harbouring two protein-coding genes HGFAC and LRPAP1. Our findings provide information about genomic structural changes and their association to the interested traits including fat deposition and environmental compatibility in sheep.

Progress in Methods for Copy Number Variation Profiling

Copy number variations (CNVs) are the predominant class of structural genomic variations involved in the processes of evolutionary adaptation, genomic disorders, and disease progression. Compared with single-nucleotide variants, there have been challenges associated with the detection of CNVs owing to their diverse sizes. However, the field has seen significant progress in the past 20–30 years. This has been made possible due to the rapid development of molecular diagnostic methods which ensure a more detailed view of the genome structure, further complemented by recent advances in computational methods. Here, we review the major approaches that have been used to routinely detect CNVs, ranging from cytogenetics to the latest sequencing technologies, and then cover their specific features.

CNVpytor: a tool for copy number variation detection and analysis from read depth and allele imbalance in whole-genome sequencing

BACKGROUND

Detecting copy number variations (CNVs) and copy number alterations (CNAs) based on whole-genome sequencing data is important for personalized genomics and treatment. CNVnator is one of the most popular tools for CNV/CNA discovery and analysis based on read depth.

FINDINGS

Herein, we present an extension of CNVnator developed in Python-CNVpytor. CNVpytor inherits the reimplemented core engine of its predecessor and extends visualization, modularization, performance, and functionality. Additionally, CNVpytor uses B-allele frequency likelihood information from single-nucleotide polymorphisms and small indels data as additional evidence for CNVs/CNAs and as primary information for copy number-neutral losses of heterozygosity.

CONCLUSIONS

CNVpytor is significantly faster than CNVnator-particularly for parsing alignment files (2-20 times faster)-and has (20-50 times) smaller intermediate files. CNV calls can be filtered using several criteria, annotated, and merged over multiple samples. Modular architecture allows it to be used in shared and cloud environments such as Google Colab and Jupyter notebook. Data can be exported into JBrowse, while a lightweight plugin version of CNVpytor for JBrowse enables nearly instant and GUI-assisted analysis of CNVs by any user. CNVpytor release and the source code are available on GitHub at https://github.com/abyzovlab/CNVpytor under the MIT license.

Genome-wide association analyses of carcass traits using copy number variants and raw intensity values of single nucleotide polymorphisms in cattle

BACKGROUND

The carcass value of cattle is a function of carcass weight and quality. Given the economic importance of carcass merit to producers, it is routinely included in beef breeding objectives. A detailed understanding of the genetic variants that contribute to carcass merit is useful to maximize the efficiency of breeding for improved carcass merit. The objectives of the present study were two-fold: firstly, to perform genome-wide association analyses of carcass weight, carcass conformation, and carcass fat using copy number variant (CNV) data in a population of 923 Holstein-Friesian, 945 Charolais, and 974 Limousin bulls; and secondly to perform separate association analyses of carcass traits on the same population of cattle using the Log R ratio (LRR) values of 712,555 single nucleotide polymorphisms (SNPs). The LRR value of a SNP is a measure of the signal intensity of the SNP generated during the genotyping process.

RESULTS

A total of 13,969, 3,954, and 2,805 detected CNVs were tested for association with the three carcass traits for the Holstein-Friesian, Charolais, and Limousin, respectively. The copy number of 16 CNVs and the LRR of 34 SNPs were associated with at least one of the three carcass traits in at least one of the three cattle breeds. With the exception of three SNPs, none of the quantitative trait loci detected in the CNV association analyses or the SNP LRR association analyses were also detected using traditional association analyses based on SNP allele counts. Many of the CNVs and SNPs associated with the carcass traits were located near genes related to the structure and function of the spliceosome and the ribosome; in particular, U6 which encodes a spliceosomal subunit and 5S rRNA which encodes a ribosomal subunit.

CONCLUSIONS

The present study demonstrates that CNV data and SNP LRR data can be used to detect genomic regions associated with carcass traits in cattle providing information on quantitative trait loci over and above those detected using just SNP allele counts, as is the approach typically employed in genome-wide association analyses.

CNV-MEANN: A Neural Network and Mind Evolutionary Algorithm-Based Detection of Copy Number Variations From Next-Generation Sequencing Data

Copy number variation (CNV), is defined as repetitions or deletions of genomic segments of 1 Kb to 5 Mb, and is a major trigger for human disease. The high-throughput and low-cost characteristics of next-generation sequencing technology provide the possibility of the detection of CNVs in the whole genome, and also greatly improve the clinical practicability of next-generation sequencing (NGS) testing. However, current methods for the detection of CNVs are easily affected by sequencing and mapping errors, and uneven distribution of reads. In this paper, we propose an improved approach, CNV-MEANN, for the detection of CNVs, involving changing the structure of the neural network used in the MFCNV method. This method has three differences relative to the MFCNV method: (1) it utilizes a new feature, mapping quality, to replace two features in MFCNV, (2) it considers the influence of the loss categories of CNV on disease prediction, and refines the output structure, and (3) it uses a mind evolutionary algorithm to optimize the backpropagation (neural network) neural network model, and calculates individual scores for each genome bin to predict CNVs. Using both simulated and real datasets, we tested the performance of CNV-MEANN and compared its performance with those of seven widely used CNV detection methods. Experimental results demonstrated that the CNV-MEANN approach outperformed other methods with respect to sensitivity, precision, and F1-score. The proposed method was able to detect many CNVs that other approaches could not, and it reduced the boundary bias. CNV-MEANN is expected to be an effective method for the analysis of changes in CNVs in the genome.

In-utero exposure to zidovudine-containing antiretroviral therapy and clonal hematopoiesis in HIV-exposed uninfected newborns

OBJECTIVE

Zidovudine (ZDV) has been extensively used in pregnant women to prevent vertical transmission of HIV but few studies have evaluated potential mutagenic effects of ZDV during fetal development.

DESIGN

Our study investigated clonal hematopoiesis in HIV-exposed uninfected (HEU) newborns, 94 of whom were ZDV-exposed and 91 antiretroviral therapy (ART)-unexposed and matched for potential confounding factors.

METHODS

Utilizing high depth sequencing and genotyping arrays, we comprehensively examined blood samples collected during the first week after birth for potential clonal hematopoiesis associated with fetal ZDV exposure, including clonal single nucleotide variants (SNVs), small insertions and deletions (indels), and large structural copy number or copy neutral alterations.

RESULTS

We observed no statistically significant difference in the number of SNVs and indels per person in ZDV-exposed children (adjusted ratio [95% confidence interval, CI] for expected number of mutations = 0.79 [0.50--1.22], P = 0.3), and no difference in the number of large structural alterations. Mutations in common clonal hematopoiesis driver genes were not found in the study population. Mutational signature analyses on SNVs detected no novel signatures unique to the ZDV-exposed children and the mutational profiles were similar between the two groups.

CONCLUSION

Our results suggest that clonal hematopoiesis at levels detectable in our study is not strongly influenced by in-utero ZDV exposure; however, additional follow-up studies are needed to further evaluate the safety and potential long-term impacts of in-utero ZDV exposure in HEU children as well as better investigate genomic aberrations occurring late in pregnancy.

Prognostic impact of pre-transplant chromosomal aberrations in peripheral blood of patients undergoing unrelated donor hematopoietic cell transplant for acute myeloid leukemia

To improve risk stratification and treatment decisions for patients with acute myeloid leukemia (AML) undergoing hematopoietic cell transplantation (HCT). We used SNP-array data from the DISCOVeRY-BMT study to detect chromosomal aberrations in pre-HCT peripheral blood (collected 2–4 weeks before the administration of conditioning regimen) from 1974 AML patients who received HCT between 2000 and 2011. All aberrations detected in ≥ 10 patients were tested for their association with overall survival (OS), separately by remission status, using the Kaplan–Meier estimator. Cox regression models were used for multivariable analyses. Follow-up was through January 2019. We identified 701 unique chromosomal aberrations in 285 patients (7% of 1438 in complete remission (CR) and 36% of 536 not in CR). Copy-neutral loss-of-heterozygosity (CNLOH) in chr17p in CR patients (3-year OS = 20% vs. 50%, with and without chr17p CNLOH, p = 0.0002), and chr13q in patients not in CR (3-year OS = 4% vs. 26%, with and without chr13q CNLOH, p < 0.0001) are risk factors for poor survival. Models adjusted for clinical factors showed approximately three-fold excess risk of post-HCT mortality with chr17p CNLOH in CR patients (hazard ratio, HR = 3.39, 95% confidence interval CI 1.74–6.60, p = 0.0003), or chr13q CNLOH in patients not in CR (HR = 2.68, 95% CI 1.75–4.09, p < 0.0001). The observed mortality was mostly driven by post-HCT relapse (HR = 2.47, 95% CI 1.01–6.02, p = 0.047 for chr17p CNLOH in CR patients, and HR = 2.58, 95% CI 1.63–4.08, p < 0.0001 for chr13q CNLOH in patients not in CR. Pre-transplant CNLOH in chr13q or chr17p predicts risk of poor outcomes after unrelated donor HCT in AML patients. A large prospective study is warranted to validate the results and evaluate novel strategies to improve survival in those patients.

The conserved ASTN2/BRINP1 locus at 9q33.1-33.2 is associated with major psychiatric disorders in a large pedigree from Southern Spain

We investigated the genetic causes of major mental disorders (MMDs) including schizophrenia, bipolar disorder I, major depressive disorder and attention deficit hyperactive disorder, in a large family pedigree from Alpujarras, South of Spain, a region with high prevalence of psychotic disorders. We applied a systematic genomic approach based on karyotyping (n = 4), genotyping by genome-wide SNP array (n = 34) and whole-genome sequencing (n = 12). We performed genome-wide linkage analysis, family-based association analysis and polygenic risk score estimates. Significant linkage was obtained at chromosome 9 (9q33.1–33.2, LOD score = 4.11), a suggestive region that contains five candidate genes ASTN2, BRINP1, C5, TLR4 and TRIM32, previously associated with MMDs. Comprehensive analysis associated the MMD phenotype with genes of the immune system with dual brain functions. Moreover, the psychotic phenotype was enriched for genes involved in synapsis. These results should be considered once studying the genetics of psychiatric disorders in other families, especially the ones from the same region, since founder effects may be related to the high prevalence.

Genomic basis of deep-water adaptation in Arctic Charr (Salvelinus alpinus) morphs

The post-glacial colonization of Gander Lake in Newfoundland, Canada, by Arctic Charr (Salvelinus alpinus) provides the opportunity to study the genomic basis of adaptation to extreme deep-water environments. Colonization of deep-water (>50 m) habitats often requires extensive adaptation to cope with novel environmental challenges from high hydrostatic pressure, low temperature, and low light, but the genomic mechanisms underlying evolution in these environments are rarely known. Here, we compare genomic divergence between a deep-water morph adapted to depths of up to 288 m and a larger, piscivorous pelagic morph occupying shallower depths. Using both a SNP array and resequencing of whole nuclear and mitochondrial genomes, we find clear genetic divergence (F_ST  = 0.11-0.15) between deep and shallow water morphs, despite an absence of morph divergence across the mitochondrial genome. Outlier analyses identified many diverged genomic regions containing genes enriched for processes such as gene expression and DNA repair, cardiac function, and membrane transport. Detection of putative copy number variants (CNVs) uncovered 385 genes with CNVs distinct to piscivorous morphs, and 275 genes with CNVs distinct to deep-water morphs, enriched for processes associated with synapse assembly. Demographic analyses identified evidence for recent and local morph divergence, and ongoing reductions in diversity consistent with postglacial colonization. Together, these results show that Arctic Charr morph divergence has occurred through genome-wide differentiation and elevated divergence of genes underlying multiple cellular and physiological processes, providing insight into the genomic basis of adaptation in a deep-water habitat following postglacial recolonization.

Genome-wide detection of CNVs and their association with performance traits in broilers

Background

Copy number variations (CNVs) are a major type of structural genomic variants that underlie genetic architecture and phenotypic variation of complex traits, not only in humans, but also in livestock animals. We identified CNVs along the chicken genome and analyzed their association with performance traits. Genome-wide CNVs were inferred from Affymetrix® high density SNP-chip data for a broiler population. CNVs were concatenated into segments and association analyses were performed with linear mixed models considering a genomic relationship matrix, for birth weight, body weight at 21, 35, 41 and 42 days, feed intake from 35 to 41 days, feed conversion ratio from 35 to 41 days and, body weight gain from 35 to 41 days of age.

Results

We identified 23,214 autosomal CNVs, merged into 5042 distinct CNV regions (CNVRs), covering 12.84% of the chicken autosomal genome. One significant CNV segment was associated with BWG on GGA3 (q-value = 0.00443); one significant CNV segment was associated with BW35 (q-value = 0.00571), BW41 (q-value = 0.00180) and BW42 (q-value = 0.00130) on GGA3, and one significant CNV segment was associated with BW on GGA5 (q-value = 0.00432). All significant CNV segments were verified by qPCR, and a validation rate of 92.59% was observed. These CNV segments are located nearby genes, such as KCNJ11, MyoD1 and SOX6, known to underlie growth and development. Moreover, gene-set analyses revealed terms linked with muscle physiology, cellular processes regulation and potassium channels.

Conclusions

Overall, this CNV-based GWAS study unravels potential candidate genes that may regulate performance traits in chickens. Our findings provide a foundation for future functional studies on the role of specific genes in regulating performance in chickens.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07676-1.

Pre-HCT mosaicism increases relapse risk and lowers survival in acute lymphoblastic leukemia patients post-unrelated HCT

Pre-HCT mosaicism is related to increased relapse risk and lower survival after unrelated HCT, independent of cytogenetics at diagnosis. Pre-HCT mosaicism could be a useful clinical tool to guide risk stratification in acute lymphoblastic leukemia patients.

Integrating genomic correlation structure improves copy number variations detection

MOTIVATION

Copy number variation plays important roles in human complex diseases. The detection of copy number variants (CNVs) is identifying mean shift in genetic intensities to locate chromosomal breakpoints, the step of which is referred to as chromosomal segmentation. Many segmentation algorithms have been developed with a strong assumption of independent observations in the genetic loci, and they assume each locus has an equal chance to be a breakpoint (i.e. boundary of CNVs). However, this assumption is violated in the genetics perspective due to the existence of correlation among genomic positions, such as linkage disequilibrium (LD). Our study showed that the LD structure is related to the location distribution of CNVs, which indeed presents a non-random pattern on the genome. To generate more accurate CNVs, we proposed a novel algorithm, LDcnv, that models the CNV data with its biological characteristics relating to genetic dependence structure (i.e. LD).

RESULTS

We theoretically demonstrated the correlation structure of CNV data in SNP array, which further supports the necessity of integrating biological structure in statistical methods for CNV detection. Therefore, we developed the LDcnv that integrated the genomic correlation structure with a local search strategy into statistical modeling of the CNV intensities. To evaluate the performance of LDcnv, we conducted extensive simulations and analyzed large-scale HapMap datasets. We showed that LDcnv presented high accuracy, stability and robustness in CNV detection and higher precision in detecting short CNVs compared to existing methods. This new segmentation algorithm has a wide scope of potential application with data from various high-throughput technology platforms.

AVAILABILITY AND IMPLEMENTATION

https://github.com/FeifeiXiaoUSC/LDcnv.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Familial Psychosis Associated With a Missense Mutation at MACF1 Gene Combined With the Rare Duplications DUP3p26.3 and DUP16q23.3, Affecting the CNTN6 and CDH13 Genes

Psychosis is a highly heritable and heterogeneous psychiatric condition. Its genetic architecture is thought to be the result of the joint effect of common and rare variants. Families with high prevalence are an interesting approach to shed light on the rare variant's contribution without the need of collecting large cohorts. To unravel the genomic architecture of a family enriched for psychosis, with four affected individuals, we applied a system genomic approach based on karyotyping, genotyping by whole-exome sequencing to search for rare single nucleotide variants (SNVs) and SNP array to search for copy-number variants (CNVs). We identified a rare non-synonymous variant, g.39914279 C > G, in the MACF1 gene, segregating with psychosis. Rare variants in the MACF1 gene have been previously detected in SCZ patients. Besides, two rare CNVs, DUP3p26.3 and DUP16q23.3, were also identified in the family affecting relevant genes (CNTN6 and CDH13, respectively). We hypothesize that the co-segregation of these duplications with the rare variant g.39914279 C > G of MACF1 gene precipitated with schizophrenia and schizoaffective disorder.

Spermatogonium-Derived Complete Hydatidiform Mole

A complete hydatidiform mole (CHM) is a conceptus with only sperm-derived chromosomes. Here, we report on a CHM with genomic DNA identical to that of the paternal somatic cells. The CHM developed in a woman who had undergone intrauterine implantation of a blastocyst obtained through in vitro injection of a presumed round spermatid into one of her oocytes. The CHM was genetically identical to peripheral white cells of her husband and contained no maternally derived nuclear DNA. We hypothesize that a spermatogonium, rather than a round spermatid, was inadvertently selected for the procedure. The CHM developed into a gestational trophoblastic neoplasia, which resolved after chemotherapy. (Funded by the Japan Society for the Promotion of Science.).

ClipSV: improving structural variation detection by read extension, spliced alignment and tree-based decision rules

Structural variation (SV), which consists of genomic variation from 50 to millions of base pairs, confers considerable impacts on human diseases, complex traits and evolution. Accurately detecting SV is a fundamental step to characterize the features of individual genomes. Currently, several methods have been proposed to detect SVs using the next-generation sequencing (NGS) platform. However, due to the short length of sequencing reads and the complexity of SV content, the SV-detecting tools are still limited by low sensitivity, especially for insertion detection. In this study, we developed a novel tool, ClipSV, to improve SV discovery. ClipSV utilizes a read extension and spliced alignment approach to overcoming the limitation of read length. By reconstructing long sequences from SV-associated short reads, ClipSV discovers deletions and short insertions from the long sequence alignments. To comprehensively characterize insertions, ClipSV implements tree-based decision rules that can efficiently utilize SV-containing reads. Based on the evaluations of both simulated and real sequencing data, ClipSV exhibited an overall better performance compared to currently popular tools, especially for insertion detection. As NGS platform represents the mainstream sequencing capacity for routine genomic applications, we anticipate ClipSV will serve as an important tool for SV characterization in future genomic studies.

Detection of ploidy and chromosomal aberrations in commercial oil palm using high-throughput SNP markers

Karyotyping using high-density genome-wide SNP markers identified various chromosomal aberrations in oil palm (Elaeis guineensis Jacq.) with supporting evidence from the 2C DNA content measurements (determined using FCM) and chromosome counts. Oil palm produces a quarter of the world's total vegetable oil. In line with its global importance, an initiative to sequence the oil palm genome was carried out successfully, producing huge amounts of sequence information, allowing SNP discovery. High-capacity SNP genotyping platforms have been widely used for marker-trait association studies in oil palm. Besides genotyping, a SNP array is also an attractive tool for understanding aberrations in chromosome inheritance. Exploiting this, the present study utilized chromosome-wide SNP allelic distributions to determine the ploidy composition of over 1,000 oil palms from a commercial F₁ family, including 197 derived from twin-embryo seeds. Our method consisted of an inspection of the allelic intensity ratio using SNP markers. For palms with a shifted or abnormal distribution ratio, the SNP allelic frequencies were plotted along the pseudo-chromosomes. This method proved to be efficient in identifying whole genome duplication (triploids) and aneuploidy. We also detected several loss of heterozygosity regions which may indicate small chromosomal deletions and/or inheritance of identical by descent regions from both parents. The SNP analysis was validated by flow cytometry and chromosome counts. The triploids were all derived from twin-embryo seeds. This is the first report on the efficiency and reliability of SNP array data for karyotyping oil palm chromosomes, as an alternative to the conventional cytogenetic technique. Information on the ploidy composition and chromosomal structural variation can help to better understand the genetic makeup of samples and lead to a more robust interpretation of the genomic data in marker-trait association analyses.

SeeCiTe: a method to assess CNV calls from SNP arrays using trio data

Motivation

Single nucleotide polymorphism (SNP) genotyping arrays remain an attractive platform for assaying copy number variants (CNVs) in large population-wide cohorts. However, current tools for calling CNVs are still prone to extensive false positive calls when applied to biobank scale arrays. Moreover, there is a lack of methods exploiting cohorts with trios available (e.g. nuclear family) to assist in quality control and downstream analyses following the calling.

Results

We developed SeeCiTe (Seeing CNVs in Trios), a novel CNV-quality control tool that postprocesses output from current CNV-calling tools exploiting child-parent trio data to classify calls in quality categories and provide a set of visualizations for each putative CNV call in the offspring. We apply it to the Norwegian Mother, Father and Child Cohort Study (MoBa) and show that SeeCiTe improves the specificity and sensitivity compared to the common empiric filtering strategies. To our knowledge, it is the first tool that utilizes probe-level CNV data in trios (and singletons) to systematically highlight potential artifacts and visualize signal intensities in a streamlined fashion suitable for biobank scale studies.

Availability and implementation

The software is implemented in R with the source code freely available at https://github.com/aksenia/SeeCiTe

Supplementary information

Supplementary data are available at Bioinformatics online.

Hematopoietic mosaic chromosomal alterations and risk for infection among 767,891 individuals without blood cancer

Age is the dominant risk factor for infectious diseases, but the mechanisms linking the two are incompletely understood1,2. Age-related mosaic chromosomal alterations (mCAs) detected from blood-derived DNA genotyping, are structural somatic variants associated with aberrant leukocyte cell counts, hematological malignancy, and mortality3-11. Whether mCAs represent independent risk factors for infection is unknown. Here we use genome-wide genotyping of blood DNA to show that mCAs predispose to diverse infectious diseases. We analyzed mCAs from 767,891 individuals without hematological cancer at DNA acquisition across four countries. Expanded mCA (cell fraction >10%) prevalence approached 4% by 60 years of age and was associated with diverse incident infections, including sepsis, pneumonia, and coronavirus disease 2019 (COVID-19) hospitalization. A genome-wide association study of expanded mCAs identified 63 significant loci. Germline genetic alleles associated with expanded mCAs were enriched at transcriptional regulatory sites for immune cells. Our results link mCAs with impaired immunity and predisposition to infections. Furthermore, these findings may also have important implications for the ongoing COVID-19 pandemic, particularly in prioritizing individual preventive strategies and evaluating immunization responses.

Hematopoietic mosaic chromosomal alterations and risk for infection among 767,891 individuals without blood cancer

Age is the dominant risk factor for infectious diseases, but the mechanisms linking the two are incompletely understood1,2. Age-related mosaic chromosomal alterations (mCAs) detected from blood-derived DNA genotyping, are structural somatic variants associated with aberrant leukocyte cell counts, hematological malignancy, and mortality3-11. Whether mCAs represent independent risk factors for infection is unknown. Here we use genome-wide genotyping of blood DNA to show that mCAs predispose to diverse infectious diseases. We analyzed mCAs from 767,891 individuals without hematological cancer at DNA acquisition across four countries. Expanded mCA (cell fraction >10%) prevalence approached 4% by 60 years of age and was associated with diverse incident infections, including sepsis, pneumonia, and coronavirus disease 2019 (COVID-19) hospitalization. A genome-wide association study of expanded mCAs identified 63 significant loci. Germline genetic alleles associated with expanded mCAs were enriched at transcriptional regulatory sites for immune cells. Our results link mCAs with impaired immunity and predisposition to infections. Furthermore, these findings may also have important implications for the ongoing COVID-19 pandemic, particularly in prioritizing individual preventive strategies and evaluating immunization responses.

Implications of germline copy-number variations in psychiatric disorders: review of large-scale genetic studies

Copy number variants (CNVs), defined as genome sequences of ≥50 bp that differ in copy number from that in a reference genome, are a common form of structural variation. Germline CNVs account for some of the missing heritability that single nucleotide polymorphisms could not account for. Recent technological advances have had a huge impact on CNV research. Microarray technology enables relatively low-cost, high-throughput, genome-wide measurements, and short-read sequencing technology enables the detection of short CNVs that cannot be detected by microarrays. As a result, large-scale genetic studies have been able to identify a variety of common and rare germline CNVs and their associations with diseases. Rare germline CNVs have been reported to be associated with neuropsychiatric disorders. In this review, we focused on germline CNVs and briefly described their functional characteristics, formation mechanisms, detection methods, related databases, and the latest findings. Finally, we introduced recent large-scale genetic studies to assess associations of CNVs with diseases, especially psychiatric disorders, and discussed the use of CNV-based animal models to investigate the molecular and cellular mechanisms underlying these disorders. The development and implementation of improved detection methods, such as long-read single-molecule sequencing, are expected to provide additional insight into the molecular basis of psychiatric disorders and other complex diseases, thus facilitating basic and clinical research on CNVs.

Using High-Content Screening to Generate Single-Cell Gene-Corrected Patient-Derived iPS Clones Reveals Excess Alpha-Synuclein with Familial Parkinson's Disease Point Mutation A30P

The generation of isogenic induced pluripotent stem cell (iPSC) lines using CRISPR-Cas9 technology is a technically challenging, time-consuming process with variable efficiency. Here we use fluorescence-activated cell sorting (FACS) to sort biallelic CRISPR-Cas9 edited single-cell iPSC clones into high-throughput 96-well microtiter plates. We used high-content screening (HCS) technology and generated an in-house developed algorithm to select the correctly edited isogenic clones for continued expansion and validation. In our model we have gene-corrected the iPSCs of a Parkinson’s disease (PD) patient carrying the autosomal dominantly inherited heterozygous c.88G>C mutation in the SNCA gene, which leads to the pathogenic p.A30P form of the alpha-synuclein protein. Undertaking a PCR restriction-digest mediated clonal selection strategy prior to sequencing, we were able to post-sort validate each isogenic clone using a quadruple screening strategy prior to generating footprint-free isogenic iPSC lines, retaining a normal molecular karyotype, pluripotency and three germ-layer differentiation potential. Directed differentiation into midbrain dopaminergic neurons revealed that SNCA expression is reduced in the gene-corrected clones, which was validated by a reduction at the alpha-synuclein protein level. The generation of single-cell isogenic clones facilitates new insights in the role of alpha-synuclein in PD and furthermore is applicable across patient-derived disease models.

Cerebrospinal fluid profile of NPTX2 supports role of Alzheimer's disease-related inhibitory circuit dysfunction in adults with Down syndrome

Background

Alzheimer’s disease (AD) is the major cause of death in adults with Down syndrome (DS). There is an urgent need for objective markers of AD in the DS population to improve early diagnosis and monitor disease progression. NPTX2 has recently emerged as a promising cerebrospinal fluid (CSF) biomarker of Alzheimer-related inhibitory circuit dysfunction in sporadic AD patients. The objective of this study was to evaluate NPTX2 in the CSF of adults with DS and to explore the relationship of NPTX2 to CSF levels of the PV interneuron receptor, GluA4, and existing AD biomarkers (CSF and neuroimaging).

Methods

This is a cross-sectional, retrospective study of adults with DS with asymptomatic AD (aDS, n = 49), prodromal AD (pDS, n = 18) and AD dementia (dDS, n = 27). Non-trisomic controls (n = 34) and patients with sporadic AD dementia (sAD, n = 40) were included for comparison. We compared group differences in CSF NPTX2 according to clinical diagnosis and degree of intellectual disability. We determined the relationship of CSF NPTX2 levels to age, cognitive performance (CAMCOG, free and cued selective reminding, semantic verbal fluency), CSF levels of a PV-interneuron marker (GluA4) and core AD biomarkers; CSF Aβ_1–42, CSF t-tau, cortical atrophy (magnetic resonance imaging) and glucose metabolism ([¹⁸F]-fluorodeoxyglucose positron emission tomography).

Results

Compared to controls, mean CSF NPTX2 levels were lower in DS at all AD stages; aDS (0.6-fold, adj.p < 0.0001), pDS (0.5-fold, adj.p < 0.0001) and dDS (0.3-fold, adj.p < 0.0001). This reduction was similar to that observed in sporadic AD (0.5-fold, adj.p < 0.0001). CSF NPTX2 levels were not associated with age (p = 0.6), intellectual disability (p = 0.7) or cognitive performance (all p > 0.07). Low CSF NPTX2 levels were associated with low GluA4 in all clinical groups; controls (r² = 0.2, p = 0.003), adults with DS (r² = 0.4, p < 0.0001) and sporadic AD (r² = 0.4, p < 0.0001). In adults with DS, low CSF NPTX2 levels were associated with low CSF Aβ_1–42 (r² > 0.3, p < 0.006), low CSF t-tau (r² > 0.3, p < 0.001), increased cortical atrophy (p < 0.05) and reduced glucose metabolism (p < 0.05).

Conclusions

Low levels of CSF NPTX2, a protein implicated in inhibitory circuit function, is common to sporadic and genetic forms of AD. CSF NPTX2 represents a promising CSF surrogate marker of early AD-related changes in adults with DS.

Monogenic and polygenic inheritance become instruments for clonal selection

Clonally expanded blood cells that contain somatic mutations (clonal haematopoiesis) are commonly acquired with age and increase the risk of blood cancer1-9. The blood clones identified so far contain diverse large-scale mosaic chromosomal alterations (deletions, duplications and copy-neutral loss of heterozygosity (CN-LOH)) on all chromosomes1,2,5,6,9, but the sources of selective advantage that drive the expansion of most clones remain unknown. Here, to identify genes, mutations and biological processes that give selective advantage to mutant clones, we analysed genotyping data from the blood-derived DNA of 482,789 participants from the UK Biobank10. We identified 19,632 autosomal mosaic chromosomal alterations and analysed these for relationships to inherited genetic variation. We found 52 inherited, rare, large-effect coding or splice variants in 7 genes that were associated with greatly increased vulnerability to clonal haematopoiesis with specific acquired CN-LOH mutations. Acquired mutations systematically replaced the inherited risk alleles (at MPL) or duplicated them to the homologous chromosome (at FH, NBN, MRE11, ATM, SH2B3 and TM2D3). Three of the genes (MRE11, NBN and ATM) encode components of the MRN-ATM pathway, which limits cell division after DNA damage and telomere attrition11-13; another two (MPL and SH2B3) encode proteins that regulate the self-renewal of stem cells14-16. In addition, we found that CN-LOH mutations across the genome tended to cause chromosomal segments with alleles that promote the expansion of haematopoietic cells to replace their homologous (allelic) counterparts, increasing polygenic drive for blood-cell proliferation traits. Readily acquired mutations that replace chromosomal segments with their homologous counterparts seem to interact with pervasive inherited variation to create a challenge for lifelong cytopoiesis.

Genomic Structural Diversity in Local Goats: Analysis of Copy-Number Variations

Simple Summary

Copy-number variations (CNVs) are one of the widely dispersed forms of structural variations in mammalian genomes and are known to be present in genomic regions that regulate important physiological functions. In this study, CNV detection was performed starting from genotypic data of 120 individuals, belonging to four Sicilian dairy goat breeds, genotyped with the Illumina GoatSNP50 BeadChip array. Using PennCNV software, a total of 702 CNVs were identified in 107 individuals. These were merged in 75 CNV regions (CNVRs), i.e., regions containing CNVs overlapped by at least 1 base pair. Functional annotation of the CNVRs allowed the identification of 139 genes/loci within the most frequent CNVRs, which are involved in local adaptation, mild behaviour, immune response, reproduction, and olfactory receptors. This study provides insights into the genomic variations within these Italian goat breeds and should be of value for future studies to identify the relationships between this type of genetic variation and phenotypic traits.

Abstract

Copy-number variations (CNVs) are one of the widely dispersed forms of structural variations in mammalian genomes, and are present as deletions, insertions, or duplications. Only few studies have been conducted in goats on CNVs derived from SNP array data, and many local breeds still remain uncharacterized, e.g., the Sicilian goat dairy breeds. In this study, CNV detection was performed, starting from the genotypic data of 120 individuals, belonging to four local breeds (Argentata dell’Etna, Derivata di Siria, Girgentana, and Messinese), genotyped with the Illumina GoatSNP50 BeadChip array. Overall, 702 CNVs were identified in 107 individuals using PennCNV software based on the hidden Markov model algorithm. These were merged in 75 CNV regions (CNVRs), i.e., regions containing CNVs overlapped by at least 1 base pair, while 85 CNVs remained unique. The part of the genome covered by CNV events was 35.21 Mb (1.2% of the goat genome length). Functional annotation of the CNVRs allowed the identification of 139 genes/loci within the most frequent CNVRs that are involved in local adaptations, such as coat colour (ADAMTS20 and EDNRA), mild behaviour (NR3C2), immune response (EXOC3L4 and TNFAIP2), reproduction (GBP1 and GBP6), and olfactory receptors (OR7E24). This study provides insights into the genomic variations for these Sicilian dairy goat breeds and should be of value for future studies to identify the relationships between this type of genetic variation and phenotypic traits.

An accurate and powerful method for copy number variation detection

MOTIVATION

Integration of multiple genetic sources for copy number variation detection (CNV) is a powerful approach to improve the identification of variants associated with complex traits. Although it has been shown that the widely used change point based methods can increase statistical power to identify variants, it remains challenging to effectively detect CNVs with weak signals due to the noisy nature of genotyping intensity data. We previously developed modSaRa, a normal mean-based model on a screening and ranking algorithm for copy number variation identification which presented desirable sensitivity with high computational efficiency. To boost statistical power for the identification of variants, here we present a novel improvement that integrates the relative allelic intensity with external information from empirical statistics with modeling, which we called modSaRa2.

RESULTS

Simulation studies illustrated that modSaRa2 markedly improved both sensitivity and specificity over existing methods for analyzing array-based data. The improvement in weak CNV signal detection is the most substantial, while it also simultaneously improves stability when CNV size varies. The application of the new method to a whole genome melanoma dataset identified novel candidate melanoma risk associated deletions on chromosome bands 1p22.2 and duplications on 6p22, 6q25 and 19p13 regions, which may facilitate the understanding of the possible roles of germline copy number variants in the etiology of melanoma.

AVAILABILITY AND IMPLEMENTATION

http://c2s2.yale.edu/software/modSaRa2 or https://github.com/FeifeiXiaoUSC/modSaRa2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Differential Allele-Specific Expression Uncovers Breast Cancer Genes Dysregulated by Cis Noncoding Mutations

Identifying cancer-relevant mutations in noncoding regions is challenging due to the large numbers of such mutations, their low levels of recurrence, and difficulties in interpreting their functional impact. To uncover genes that are dysregulated due to somatic mutations in cis, we build upon the concept of differential allele-specific expression (ASE) and introduce methods to identify genes within an individual's cancer whose ASE differs from what is found in matched normal tissue. When applied to breast cancer tumor samples, our methods detect the known allele-specific effects of copy number variation and nonsense-mediated decay. Further, genes that are found to recurrently exhibit differential ASE across samples are cancer relevant. Genes with cis mutations are enriched for differential ASE, and we find 147 potentially functional noncoding mutations cis to genes that exhibit significant differential ASE. We conclude that differential ASE is a promising means for discovering gene dysregulation due to cis noncoding mutations.

Characterizing Mutational Signatures in Human Cancer Cell Lines Reveals Episodic APOBEC Mutagenesis

Multiple signatures of somatic mutations have been identified in cancer genomes. Exome sequences of 1,001 human cancer cell lines and 577 xenografts revealed most common mutational signatures, indicating past activity of the underlying processes, usually in appropriate cancer types. To investigate ongoing patterns of mutational-signature generation, cell lines were cultured for extended periods and subsequently DNA sequenced. Signatures of discontinued exposures, including tobacco smoke and ultraviolet light, were not generated in vitro. Signatures of normal and defective DNA repair and replication continued to be generated at roughly stable mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing exhibited substantial fluctuations in mutation rate over time with episodic bursts of mutations. The initiating factors for the bursts are unclear, although retrotransposon mobilization may contribute. The examined cell lines constitute a resource of live experimental models of mutational processes, which potentially retain patterns of activity and regulation operative in primary human cancers.

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Annotation of mutational signatures across 1,001 cancer cell lines and 577 PDXs

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Activities of mutational processes determined over time in cancer cell lines

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APOBEC-associated mutagenesis is often ongoing and can be episodic

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Detection of mutational signatures by single-cell sequencing

A candidate gene analysis and GWAS for genes associated with maternal nondisjunction of chromosome 21

Human nondisjunction errors in oocytes are the leading cause of pregnancy loss, and for pregnancies that continue to term, the leading cause of intellectual disabilities and birth defects. For the first time, we have conducted a candidate gene and genome-wide association study to identify genes associated with maternal nondisjunction of chromosome 21 as a first step to understand predisposing factors. A total of 2,186 study participants were genotyped on the HumanOmniExpressExome-8v1-2 array. These participants included 749 live birth offspring with standard trisomy 21 and 1,437 parents. Genotypes from the parents and child were then used to identify mothers with nondisjunction errors derived in the oocyte and to establish the type of error (meiosis I or meiosis II). We performed a unique set of subgroup comparisons designed to leverage our previous work suggesting that the etiologies of meiosis I and meiosis II nondisjunction differ for trisomy 21. For the candidate gene analysis, we selected genes associated with chromosome dynamics early in meiosis and genes associated with human global recombination counts. Several candidate genes showed strong associations with maternal nondisjunction of chromosome 21, demonstrating that genetic variants associated with normal variation in meiotic processes can be risk factors for nondisjunction. The genome-wide analysis also suggested several new potentially associated loci, although follow-up studies using independent samples are required.

Approximately one of every 700 babies is born with trisomy 21—an extra copy of chromosome 21. Trisomy 21 is caused by the failure of chromosomes to segregate properly during meiosis, generally in the mother. Past studies have defined altered patterns of recombination along nondisjoined chromosomes as risk factors for human nondisjunction and model systems have clearly shown that specific genes involved recombination and other early meiotic processes play a role in the fidelity of chromosome segregation. However, no genome-wide genetic study (GWAS) has ever been conducted using maternal human nondisjunction as the disease phenotype. This study takes the first step to understand predisposing factors. We used chromosome 21 genotypes from the parents and child to identify mothers with nondisjunction errors derived in the oocyte and to establish the type of error (meiosis I or meiosis II). We then conducted a unique set of subgroup comparisons designed to leverage our previous work that shows that the etiologies of meiosis I and meiosis II nondisjunction differ for trisomy 21. Both the candidate gene study and the GWAS provide evidence that meiotic-specific structures and processes are vulnerable to genetic variants that lead to increased risk of human chromosome nondisjunction.

Characterization of Prevalence and Health Consequences of Uniparental Disomy in Four Million Individuals from the General Population

Meiotic nondisjunction and resulting aneuploidy can lead to severe health consequences in humans. Aneuploidy rescue can restore euploidy but may result in uniparental disomy (UPD), the inheritance of both homologs of a chromosome from one parent with no representative copy from the other. Current understanding of UPD is limited to ∼3,300 case subjects for which UPD was associated with clinical presentation due to imprinting disorders or recessive diseases. Thus, the prevalence of UPD and its phenotypic consequences in the general population are unknown. We searched for instances of UPD across 4,400,363 consented research participants from the personal genetics company 23andMe, Inc., and 431,094 UK Biobank participants. Using computationally detected DNA segments identical-by-descent (IBD) and runs of homozygosity (ROH), we identified 675 instances of UPD across both databases. We estimate that UPD is twice as common as previously thought, and we present a machine-learning framework to detect UPD using ROH. While we find a nominally significant association between UPD of chromosome 22 and autism risk, we do not find significant associations between UPD and deleterious traits in the 23andMe database.

ShinyCNV: a Shiny/R application to view and annotate DNA copy number variations

Motivation

Single nucleotide polymorphism (SNP) array is the most widely used platform to assess somatic copy number variations (CNVs) in cancer studies. Many SNP data-based CNV callers are available, however, the false positive rates from automated calling are commonly high, and reported breakpoints can be inaccurate. Manual review for each reported CNV by visualizing the SNP data is important, but is challenging for users lacking computational experience. To address this, we present a Shiny/R application ShinyCNV, an interactive graphical user interface to view and annotate CNVs.

Results

With this application, normalized SNP data, which includes log R ratio (LRR) and B allele frequency, can be plotted against the reported CNVs, and users can visually check the reliability of CNVs per se or adjust the incorrectly assigned breakpoints. Further, the interactive LRR spectrum panel within ShinyCNV can facilitate the process to identify commonly affected CNV regions from a group of samples, and to visually check if important focal gains/losses are missing from reported CNVs. ShinyCNV is designed to be intuitive for cancer researchers and can be easily installed for either personal use or deployed on servers to provide online service.

Availability and implementation

ShinyCNV and the tutorial are freely available from https://github.com/gzhmat/ShinyCNV.

Supplementary information

Supplementary data are available at Bioinformatics online.

GWAS of mosaic loss of chromosome Y highlights genetic effects on blood cell differentiation

Mosaic loss of chromosome Y (mLOY) is frequently observed in the leukocytes of ageing men. However, the genetic architecture and biological mechanisms underlying mLOY are not fully understood. In a cohort of 95,380 Japanese men, we identify 50 independent genetic markers in 46 loci associated with mLOY at a genome-wide significant level, 35 of which are unreported. Lead markers overlap enhancer marks in hematopoietic stem cells (HSCs, P ≤ 1.0 × 10⁻⁶). mLOY genome-wide association study signals exhibit polygenic architecture and demonstrate strong heritability enrichment in regions surrounding genes specifically expressed in multipotent progenitor (MPP) cells and HSCs (P ≤ 3.5 × 10⁻⁶). ChIP-seq data demonstrate that binding sites of FLI1, a fate-determining factor promoting HSC differentiation into platelets rather than red blood cells (RBCs), show a strong heritability enrichment (P = 1.5 × 10⁻⁶). Consistent with these findings, platelet and RBC counts are positively and negatively associated with mLOY, respectively. Collectively, our observations improve our understanding of the mechanisms underlying mLOY.

Mosaic loss of chromosome Y (mLOY) is associated with age and smoking but also genetic factors play a role. Here, Terao et al. perform GWAS for mLOY in 95,380 Japanese men and identify 46 loci that overlap with hematopoietic stem cell enhancers and transcription factor binding sites critical for hematopoiesis.

Genome-wide single nucleotide polymorphism array analysis unveils the origin of heterozygous androgenetic complete moles

Hydatidiform moles are abnormal pregnancies, which show trophoblastic hyperplasia. Most often, the nuclear genome in complete hydatidiform moles (CHMs) is composed of only paternal chromosomes. Diploid androgenetic conceptuses can be divided into homozygous and heterozygous CHMs. Heterozygous CHMs originate from two sperms or a diploid sperm, the distinction of which has not been established. Here, we assessed the origin of heterozygous CHMs using single nucleotide polymorphism (SNP) array. Thirteen heterozygous CHMs were analysed using B allele frequency (BAF) plotting to determine the centromeric zygosity status of all chromosomes. One case was from the duplication of a single sperm with an XY chromosome. In the other twelve cases, centromeric zygosity was random, i.e. mixed status. Thus, the twelve heterozygous CHMs were considered to be of dispermic origin but not diploid sperm origin. BAF plotting of SNP array can be a powerful tool to estimate the type of hydatidiform moles.

Estimation of DNA contamination and its sources in genotyped samples

Array genotyping is a cost-effective and widely used tool that enables assessment of up to millions of genetic markers in hundreds of thousands of individuals. Genotyping array data are typically highly accurate but sensitive to mixing of DNA samples from multiple individuals before or during genotyping. Contaminated samples can lead to genotyping errors and consequently cause false positive signals or reduce power of association analyses. Here, we propose a new method to identify contaminated samples and the sources of contamination within a genotyping batch. Through analysis of array intensity and genotype data from intentionally mixed samples and 22,366 samples of the Michigan Genomics Initiative, an ongoing biobank-based study, we show that our method can reliably estimate contamination. We also show that identifying sources of contamination can implicate problematic sample processing steps and guide process improvements. Compared to existing methods, our approach can estimate the proportion of contaminating DNA more accurately, eliminate the need for external databases of allele frequencies, and provide contamination estimates that are more robust to the ancestral origin of the contaminating sample.

Elucidation of the developmental mechanism of ovarian mature cystic teratomas using B allele-frequency plots of single nucleotide polymorphism array data

Ovarian mature cystic teratomas (MCTs) originate from post-meiotic germ cells. Conventional methods such as karyotyping or short tandem repeat-polymorphism analysis may be used to better classify MCTs, although such data would be insufficient. The aim of this study was to elucidate the origin of ovarian MCTs using B allele-frequency (BAF) plots of single nucleotide polymorphism array data. MCTs can be classified in terms of the zygosity of the centromeres and distal chromosome regions. We evaluated the zygosity of all chromosomes from 38 MCT specimens using BAF plot data. BAF plots were used to determine the homozygous and heterozygous regions over the whole genome. Theoretically, MCTs originated from the fusion of two ova (previously referred to as type V MCTs) should have a mixed pattern of centromeric zygosity, that is, a combination of heterozygous and homozygous regions in the centromeric regions. However, no MCTs in this study met this criterion. We identified 13 type I MCTs, 14 type II MCTs, and 11 type III MCTs. In addition, BAF plots facilitated the construction of recombination maps at the whole-genome level for type I and II MCTs. No crossover, especially in the short arms, contributed to the failure of meiosis I, resulting in type I MCTs. Crossover in all arms might assure the normal progress of meiosis in human oocytes. In conclusion, our findings indicate that BAF plots can elucidate the developmental mechanism of MCTs, and further serve as useful analytical tools for analyzing human oocyte meiosis, and related aberrations.