A decade of structural variants: description, history and methods to detect structural variation

Benchmarking long-read aligners and SV callers for structural variation detection in Oxford nanopore sequencing data

Structural variants (SVs) are one of the significant types of DNA mutations and are typically defined as larger-than-50-bp genomic alterations that include insertions, deletions, duplications, inversions, and translocations. These modifications can profoundly impact the phenotypic characteristics and contribute to disorders like cancer, response to treatment, and infections. Four long-read aligners and five SV callers have been evaluated using three Oxford Nanopore NGS human genome datasets in terms of precision, recall, and F1-score statistical metrics, depth of coverage, and speed of analysis. The best SV caller regarding recall, precision, and F1-score when matched with different aligners at different coverage levels tend to vary depending on the dataset and the specific SV types being analyzed. However, based on our findings, Sniffles and CuteSV tend to perform well across different aligners and coverage levels, followed by SVIM, PBSV, and SVDSS in the last place. The CuteSV caller has the highest average F1-score (82.51%) and recall (78.50%), and Sniffles has the highest average precision value (94.33%). Minimap2 as an aligner and Sniffles as an SV caller act as a strong base for the pipeline of SV calling because of their high speed and reasonable accomplishment. PBSV has a lower average F1-score, precision, and recall and may generate more false positives and overlook some actual SVs. Our results are valuable in the comprehensive evaluation of popular SV callers and aligners as they provide insight into the performance of several long-read aligners and SV callers and serve as a reference for researchers in selecting the most suitable tools for SV detection.

Structural Variants and Speciation: Multiple Processes at Play

Research on the genomic architecture of speciation has increasingly revealed the importance of structural variants (SVs) that affect the presence, abundance, position, and/or direction of a nucleotide sequence. SVs include large chromosomal rearrangements such as fusion/fissions and inversions and translocations, as well as smaller variants such as duplications, insertions, and deletions (CNVs). Although we have ample evidence that SVs play a key role in speciation, the underlying mechanisms differ depending on the type and length of the SV, as well as the ecological, demographic, and historical context. We review predictions and empirical evidence for classic processes such as underdominance due to meiotic aberrations and the coupling effect of recombination suppression before exploring how recent sequencing methodologies illuminate the prevalence and diversity of SVs. We discuss specific properties of SVs and their impact throughout the genome, highlighting that multiple processes are at play, and possibly interacting, in the relationship between SVs and speciation.

Genomic technologies for detecting structural variations in hematologic malignancies

Genomic structural variations in myeloid, lymphoid, and plasma cell neoplasms can provide key diagnostic, prognostic, and therapeutic information while elucidating the underlying disease biology. Several molecular diagnostic approaches play a central role in evaluating hematological malignancies. Traditional cytogenetic diagnostic assays, such as chromosome banding and fluorescence in situ hybridization, are essential components of the current diagnostic workup that guide clinical care for most hematologic malignancies. However, each assay has inherent limitations, including limited resolution for detecting small structural variations and low coverage, and can only detect alterations in the target regions. Recently, the rapid expansion and increasing availability of novel and comprehensive genomic technologies have led to their use in clinical laboratories for clinical management and translational research. This review aims to describe the clinical relevance of structural variations in hematologic malignancies and introduce genomic technologies that may facilitate personalized tumor characterization and treatment.

Identify Candidate Genes Associated with the Weight and Egg Quality Traits in Wenshui Green Shell-Laying Chickens by the Copy Number Variation-Based Genome-Wide Association Study

Copy number variation (CNV), as an essential source of genetic variation, can have an impact on gene expression, genetic diversity, disease susceptibility, and species evolution in animals. To better understand the weight and egg quality traits of chickens, this paper aimed to detect CNVs in Wenshui green shell-laying chickens and conduct a copy number variation regions (CNVRs)-based genome-wide association study (GWAS) to identify variants and candidate genes associated with their weight and egg quality traits to support related breeding efforts. In our paper, we identified 11,035 CNVRs in Wenshui green shell-laying chickens, which collectively spanned a length of 13.1 Mb, representing approximately 1.4% of its autosomal genome. Out of these CNVRs, there were 10,446 loss types, 491 gain types, and 98 mixed types. Notably, two CNVRs showed significant correlations with egg quality, while four CNVRs exhibited significant associations with body weight. These significant CNVRs are located on chromosome 4. Further analysis identified potential candidate genes that influence weight and egg quality traits, including FAM184B, MED28, LAP3, ATOH8, ST3GAL5, LDB2, and SORCS2. In this paper, the CNV map of the Wenshui green shell-laying chicken genome was constructed for the first time through population genotyping. Additionally, CNVRs can be employed as molecular markers to genetically improve chickens' weight and egg quality traits.

Genome-wide investigation to assess copy number variants in the Italian local chicken population

BACKGROUND

Copy number variants (CNV) hold significant functional and evolutionary importance. Numerous ongoing CNV studies aim to elucidate the etiology of human diseases and gain insights into the population structure of livestock. High-density chips have enabled the detection of CNV with increased resolution, leading to the identification of even small CNV. This study aimed to identify CNV in local Italian chicken breeds and investigate their distribution across the genome.

RESULTS

Copy number variants were mainly distributed across the first six chromosomes and primarily associated with loss type CNV. The majority of CNV in the investigated breeds were of types 0 and 1, and the minimum length of CNV was significantly larger than that reported in previous studies. Interestingly, a high proportion of the length of chromosome 16 was covered by copy number variation regions (CNVR), with the major histocompatibility complex being the likely cause. Among the genes identified within CNVR, only those present in at least five animals across breeds (n = 95) were discussed to reduce the focus on redundant CNV. Some of these genes have been associated to functional traits in chickens. Notably, several CNVR on different chromosomes harbor genes related to muscle development, tissue-specific biological processes, heat stress resistance, and immune response. Quantitative trait loci (QTL) were also analyzed to investigate potential overlapping with the identified CNVR: 54 out of the 95 gene-containing regions overlapped with 428 QTL associated to body weight and size, carcass characteristics, egg production, egg components, fat deposition, and feed intake.

CONCLUSIONS

The genomic phenomena reported in this study that can cause changes in the distribution of CNV within the genome over time and the comparison of these differences in CNVR of the local chicken breeds could help in preserving these genetic resources.

Exploring the role of polymorphic interspecies structural variants in reproductive isolation and adaptive divergence in Eucalyptus

Structural variations (SVs) play a significant role in speciation and adaptation in many species, yet few studies have explored the prevalence and impact of different categories of SVs. We conducted a comparative analysis of long-read assembled reference genomes of closely related Eucalyptus species to identify candidate SVs potentially influencing speciation and adaptation. Interspecies SVs can be either fixed differences or polymorphic in one or both species. To describe SV patterns, we employed short-read whole-genome sequencing on over 600 individuals of Eucalyptus melliodora and Eucalyptus sideroxylon, along with recent high-quality genome assemblies. We aligned reads and genotyped interspecies SVs predicted between species reference genomes. Our results revealed that 49,756 of 58,025 and 39,536 of 47,064 interspecies SVs could be typed with short reads in E. melliodora and E. sideroxylon, respectively. Focusing on inversions and translocations, symmetric SVs that are readily genotyped within both populations, 24 were found to be structural divergences, 2,623 structural polymorphisms, and 928 shared structural polymorphisms. We assessed the functional significance of fixed interspecies SVs by examining differences in estimated recombination rates and genetic differentiation between species, revealing a complex history of natural selection. Shared structural polymorphisms displayed enrichment of potentially adaptive genes. Understanding how different classes of genetic mutations contribute to genetic diversity and reproductive barriers is essential for understanding how organisms enhance fitness, adapt to changing environments, and diversify. Our findings reveal the prevalence of interspecies SVs and elucidate their role in genetic differentiation, adaptive evolution, and species divergence within and between populations.

A comprehensive lettuce variation map reveals the impact of structural variations in agronomic traits

BACKGROUND

As an important vegetable crop, cultivated lettuce is grown worldwide and a great variety of agronomic traits have been preserved within germplasm collections. The mechanisms underlying these phenotypic variations remain to be elucidated in association with sequence variations. Compared with single nucleotide polymorphisms, structural variations (SVs) that have more impacts on gene functions remain largely uncharacterized in the lettuce genome.

RESULTS

Here, we produced a comprehensive SV set for 333 wild and cultivated lettuce accessions. Comparison of SV frequencies showed that the SVs prevalent in L. sativa affected the genes enriched in carbohydrate derivative catabolic and secondary metabolic processes. Genome-wide association analysis of seven agronomic traits uncovered potentially causal SVs associated with seed coat color and leaf anthocyanin content.

CONCLUSION

Our work characterized a great abundance of SVs in the lettuce genome, and provides a valuable genomic resource for future lettuce breeding.

Structural variants and short tandem repeats impact gene expression and splicing in bovine testis tissue

Structural variants (SVs) and short tandem repeats (STRs) are significant sources of genetic variation. However, the impacts of these variants on gene regulation have not been investigated in cattle. Here, we genotyped and characterized 19,408 SVs and 374,821 STRs in 183 bovine genomes and investigated their impact on molecular phenotypes derived from testis transcriptomes. We found that 71% STRs were multiallelic. The vast majority (95%) of STRs and SVs were in intergenic and intronic regions. Only 37% SVs and 40% STRs were in high linkage disequilibrium (LD) (R2 > 0.8) with surrounding SNPs/insertions and deletions (Indels), indicating that SNP-based association testing and genomic prediction are blind to a nonnegligible portion of genetic variation. We showed that both SVs and STRs were more than 2-fold enriched among expression and splicing QTL (e/sQTL) relative to SNPs/Indels and were often associated with differential expression and splicing of multiple genes. Deletions and duplications had larger impacts on splicing and expression than any other type of SV. Exonic duplications predominantly increased gene expression either through alternative splicing or other mechanisms, whereas expression- and splicing-associated STRs primarily resided in intronic regions and exhibited bimodal effects on the molecular phenotypes investigated. Most e/sQTL resided within 100 kb of the affected genes or splicing junctions. We pinpoint candidate causal STRs and SVs associated with the expression of SLC13A4 and TTC7B and alternative splicing of a lncRNA and CAPP1. We provide a catalog of STRs and SVs for taurine cattle and show that these variants contribute substantially to gene expression and splicing variation.

Identification of copy number variation in Tibetan sheep using whole genome resequencing reveals evidence of genomic selection

BACKGROUND

Copy number variation (CNV) is an important source of structural variation in the mammalian genome. CNV assays present a new method to explore the genomic diversity of environmental adaptations in animals and plants and genes associated with complex traits. In this study, the genome-wide CNV distribution characteristics of 20 Tibetan sheep from two breeds (10 Oula sheep and 10 Panou sheep) were analysed using whole-genome resequencing to investigate the variation in the genomic structure of Tibetan sheep during breeding.

RESULTS

CNVs were detected using CNVnator, and the overlapping regions of CNVs between individual sheep were combined. Among them, a total of 60,429 CNV events were detected between the indigenous sheep breed (Oula) and the synthetic sheep breed (Panou). After merging the overlapping CNVs, 4927 CNV regions (CNVRs) were finally obtained. Of these, 4559 CNVRs were shared by two breeds, and there were 368 differential CNVRs. Deletion events have a higher percentage of occurrences than duplication events. Functional enrichment analysis showed that the shared CNVRs were significantly enriched in 163 GO terms and 62 KEGG pathways, which were mainly associated with organ development, neural regulation, immune regulation, digestion and metabolism. In addition, 140 QTLs overlapped with some of the CNVRs at more than 1 kb, such as average daily gain QTL, body weight QTL, and total lambs born QTL. Many of the CNV-overlapping genes such as PPP3CA, SSTR1 and FASN, overlap with the average daily weight gain and carcass weight QTL regions. Moreover, VST analysis showed that XIRP2, ABCB1, CA1, ASPA and EEF2 differed significantly between the synthetic breed and local sheep breed. The duplication of the ABCB1 gene may be closely related to adaptation to the plateau environment in Panou sheep, which deserves further study. Additionally, cluster analysis, based on all individuals, showed that the CNV clustering could be divided into two origins, indicating that some Tibetan sheep CNVs are likely to arise independently in different populations and contribute to population differences.

CONCLUSIONS

Collectively, we demonstrated the genome-wide distribution characteristics of CNVs in Panou sheep by whole genome resequencing. The results provides a valuable genetic variation resource and help to understand the genetic characteristics of Tibetan sheep. This study also provides useful information for the improvement and breeding of Tibetan sheep in the future.

Chromosomal inversion polymorphisms shape human brain morphology

The impact of chromosomal inversions on human brain morphology remains underexplored. We studied 35 common inversions classified from genotypes of 33,018 adults with European ancestry. The inversions at 2p22.3, 16p11.2, and 17q21.31 reach genome-wide significance, followed by 8p23.1 and 6p21.33, in their association with cortical and subcortical morphology. The 17q21.31, 8p23.1, and 16p11.2 regions comprise the LRRC37, OR7E, and NPIP duplicated gene families. We find the 17q21.31 MAPT inversion region, known for harboring neurological risk, to be the most salient locus among common variants for shaping and patterning the cortex. Overall, we observe the inverted orientations decreasing brain size, with the exception that the 2p22.3 inversion is associated with increased subcortical volume and the 8p23.1 inversion is associated with increased motor cortex. These significant inversions are in the genomic hotspots of neuropsychiatric loci. Our findings are generalizable to 3,472 children and demonstrate inversions as essential genetic variation to understand human brain phenotypes.

Long-read genome sequencing identifies cryptic structural variants in congenital aniridia cases

BACKGROUND

Haploinsufficiency of the transcription factor PAX6 is the main cause of congenital aniridia, a genetic disorder characterized by iris and foveal hypoplasia. 11p13 microdeletions altering PAX6 or its downstream regulatory region (DRR) are present in about 25% of patients; however, only a few complex rearrangements have been described to date. Here, we performed nanopore-based whole-genome sequencing to assess the presence of cryptic structural variants (SVs) on the only two unsolved "PAX6-negative" cases from a cohort of 110 patients with congenital aniridia after unsuccessfully short-read sequencing approaches.

RESULTS

Long-read sequencing (LRS) unveiled balanced chromosomal rearrangements affecting the PAX6 locus at 11p13 in these two patients and allowed nucleotide-level breakpoint analysis. First, we identified a cryptic 4.9 Mb de novo inversion disrupting intron 7 of PAX6, further verified by targeted polymerase chain reaction amplification and sequencing and FISH-based cytogenetic analysis. Furthermore, LRS was decisive in correctly mapping a t(6;11) balanced translocation cytogenetically detected in a second proband with congenital aniridia and considered non-causal 15 years ago. LRS resolved that the breakpoint on chromosome 11 was indeed located at 11p13, disrupting the DNase I hypersensitive site 2 enhancer within the DRR of PAX6, 161 Kb from the causal gene. Patient-derived RNA expression analysis demonstrated PAX6 haploinsufficiency, thus supporting that the 11p13 breakpoint led to a positional effect by cleaving crucial enhancers for PAX6 transactivation. LRS analysis was also critical for mapping the exact breakpoint on chromosome 6 to the highly repetitive centromeric region at 6p11.1.

CONCLUSIONS

In both cases, the LRS-based identified SVs have been deemed the hidden pathogenic cause of congenital aniridia. Our study underscores the limitations of traditional short-read sequencing in uncovering pathogenic SVs affecting low-complexity regions of the genome and the value of LRS in providing insight into hidden sources of variation in rare genetic diseases.

Comparison and Characterization of Phenotypic and Genomic Mutations Induced by a Carbon-Ion Beam and Gamma-ray Irradiation in Soybean (Glycine max (L.) Merr.)

Soybean (Glycine max (L.) Merr.) is a nutritious crop that can provide both oil and protein. A variety of mutagenesis methods have been proposed to obtain better soybean germplasm resources. Among the different types of physical mutagens, carbon-ion beams are considered to be highly efficient with high linear energy transfer (LET), and gamma rays have also been widely used for mutation breeding. However, systematic knowledge of the mutagenic effects of these two mutagens during development and on phenotypic and genomic mutations has not yet been elucidated in soybean. To this end, dry seeds of Williams 82 soybean were irradiated with a carbon-ion beam and gamma rays. The biological effects of the M₁ generation included changes in survival rate, yield and fertility. Compared with gamma rays, the relative biological effectiveness (RBE) of the carbon-ion beams was between 2.5 and 3.0. Furthermore, the optimal dose for soybean was determined to be 101 Gy to 115 Gy when using the carbon-ion beam, and it was 263 Gy to 343 Gy when using gamma rays. A total of 325 screened mutant families were detected from out of 2000 M₂ families using the carbon-ion beam, and 336 screened mutant families were found using gamma rays. Regarding the screened phenotypic M₂ mutations, the proportion of low-frequency phenotypic mutations was 23.4% when using a carbon ion beam, and the proportion was 9.8% when using gamma rays. Low-frequency phenotypic mutations were easily obtained with the carbon-ion beam. After screening the mutations from the M₂ generation, their stability was verified, and the genome mutation spectrum of M₃ was systemically profiled. A variety of mutations, including single-base substitutions (SBSs), insertion-deletion mutations (INDELs), multinucleotide variants (MNVs) and structural variants (SVs) were detected with both carbon-ion beam irradiation and gamma-ray irradiation. Overall, 1988 homozygous mutations and 9695 homozygous + heterozygous genotype mutations were detected when using the carbon-ion beam. Additionally, 5279 homozygous mutations and 14,243 homozygous + heterozygous genotype mutations were detected when using gamma rays. The carbon-ion beam, which resulted in low levels of background mutations, has the potential to alleviate the problems caused by linkage drag in soybean mutation breeding. Regarding the genomic mutations, when using the carbon-ion beam, the proportion of homozygous-genotype SVs was 0.45%, and that of homozygous + heterozygous-genotype SVs was 6.27%; meanwhile, the proportions were 0.04% and 4.04% when using gamma rays. A higher proportion of SVs were detected when using the carbon ion beam. The gene effects of missense mutations were greater under carbon-ion beam irradiation, and the gene effects of nonsense mutations were greater under gamma-ray irradiation, which meant that the changes in the amino acid sequences were different between the carbon-ion beam and gamma rays. Taken together, our results demonstrate that both carbon-ion beam and gamma rays are effective techniques for rapid mutation breeding in soybean. If one would like to obtain mutations with a low-frequency phenotype, low levels of background genomic mutations and mutations with a higher proportion of SVs, carbon-ion beams are the best choice.

Gene sequencing and result analysis of balanced translocation carriers by third-generation gene sequencing technology

Because the total gene copy number remains constant and all genes are normally expressed, carriers of balanced chromosomal translocations usually have a normal phenotype but are able to produce many different types of gametes during meiosis, and unbalanced gametes lead to increased risks of infertility, recurrent spontaneous abortion, stillbirth, neonatal death or malformations and intellectual abnormalities in offspring. The key to balanced translocations lies in finding the breakpoints, but current genetic testing techniques are all short-read sequencing, with the disadvantage of procedural complexity and imprecision for precisely identifying the breakpoints. The latest third-generation sequencing technology overcomes these drawbacks and uses robust long-read sequencing to accurately and rapidly detect genome-wide information and identify breakpoint locations. In this paper, we performed whole genome long-read sequencing using an Oxford Nanopore sequencer to detect the breakpoints of 4 balanced chromosomal translocation carriers. The results showed that employing about ~ 10× coverage confirmed 6 of the 8 breakpoints, of which, 2 had microdeletions/insertions identified near the breakpoints and 4 had breakpoints that disrupted the normal gene structure and were simultaneously tested for genome-wide structural variation (SV). The results show that whole genome long-read sequencing is an efficient method for pinpointing translocation breakpoints and providing genome-wide information, which is essential for medical genetics and preimplantation genetic testing.

Identification and characterisation of de novo germline structural variants in two commercial pig lines using trio-based whole genome sequencing

BACKGROUND

De novo mutations arising in the germline are a source of genetic variation and their discovery broadens our understanding of genetic disorders and evolutionary patterns. Although the number of de novo single nucleotide variants (dnSNVs) has been studied in a number of species, relatively little is known about the occurrence of de novo structural variants (dnSVs). In this study, we investigated 37 deeply sequenced pig trios from two commercial lines to identify dnSVs present in the offspring. The identified dnSVs were characterised by identifying their parent of origin, their functional annotations and characterizing sequence homology at the breakpoints.

RESULTS

We identified four swine germline dnSVs, all located in intronic regions of protein-coding genes. Our conservative, first estimate of the swine germline dnSV rate is 0.108 (95% CI 0.038-0.255) per generation (one dnSV per nine offspring), detected using short-read sequencing. Two detected dnSVs are clusters of mutations. Mutation cluster 1 contains a de novo duplication, a dnSNV and a de novo deletion. Mutation cluster 2 contains a de novo deletion and three de novo duplications, of which one is inverted. Mutation cluster 2 is 25 kb in size, whereas mutation cluster 1 (197 bp) and the other two individual dnSVs (64 and 573 bp) are smaller. Only mutation cluster 2 could be phased and is located on the paternal haplotype. Mutation cluster 2 originates from both micro-homology as well as non-homology mutation mechanisms, where mutation cluster 1 and the other two dnSVs are caused by mutation mechanisms lacking sequence homology. The 64 bp deletion and mutation cluster 1 were validated through PCR. Lastly, the 64 bp deletion and the 573 bp duplication were validated in sequenced offspring of probands with three generations of sequence data.

CONCLUSIONS

Our estimate of 0.108 dnSVs per generation in the swine germline is conservative, due to our small sample size and restricted possibilities of dnSV detection from short-read sequencing. The current study highlights the complexity of dnSVs and shows the potential of breeding programs for pigs and livestock species in general, to provide a suitable population structure for identification and characterisation of dnSVs.

Usefulness and Limitations of Multiple Ligation-Dependent Probe Amplification in Antithrombin Deficiency

Multiplex ligation-dependent probe amplification (MLPA) identifies genetic structural variants in SERPINC1 in 5% of cases with antithrombin deficiency (ATD), the most severe congenital thrombophilia. Our aim was to unravel the utility and limitations of MLPA in a large cohort of unrelated patients with ATD (N = 341). MLPA identified 22 structural variants (SVs) causing ATD (6.5%). MLPA did not detect SVs affecting introns (four cases), and the diagnosis was inaccurate in two cases according to long-range PCR or nanopore sequencing. MLPA was used to detect possible hidden SVs in 61 cases with type I deficiency with single nucleotide variations (SNVs) or small insertion/deletion (INDEL). One case had a false deletion of exon 7, as the 29-bp deletion affected an MLPA probe. We evaluated 32 variants affecting MLPA probes: 27 SNVs and 5 small INDELs. In three cases, MLPA gave false-positive results, all diagnosed as deletions of the affected exon: a small INDEL complex, and two SNVs affecting MLPA probes. Our study confirms the utility of MLPA to detect SVs in ATD, but also shows some limitations in detecting intronic SVs. MLPA renders imprecise and false-positive results for genetic defects which affect MLPA probes. Our results encourage the validation of MLPA results.

Chromosomal Rearrangements and Chromothripsis: The Alternative End Generation Model

Chromothripsis defines a genetic phenomenon where up to hundreds of clustered chromosomal rearrangements can arise in a single catastrophic event. The phenomenon is associated with cancer and congenital diseases. Most current models on the origin of chromothripsis suggest that prior to chromatin reshuffling numerous DNA double-strand breaks (DSBs) have to exist, i.e., chromosomal shattering precedes rearrangements. However, the preference of a DNA end to rearrange in a proximal accessible region led us to propose chromothripsis as the reaction product of successive chromatin rearrangements. We previously coined this process Alternative End Generation (AEG), where a single DSB with a repair-blocking end initiates a domino effect of rearrangements. Accordingly, chromothripsis is the end product of this domino reaction taking place in a single catastrophic event.

Identification of copy number variants contributing to hallux valgus

Hallux valgus is a common form of foot deformity, and genetic factors contribute substantially to the pathogenesis of hallux valgus deformity. We conducted a genetic study on the structural variants underlying familial hallux valgus using whole exome sequencing approach. Twenty individuals from five hallux valgus families and two sporadic cases were included in this study. A total of 372 copy number variations were found and passed quality control filtering. Among them, 43 were only present in cases but not in controls or healthy individuals in the database of genomic variants. The genes covered by these copy number variations were enriched in gene sets related to immune signaling pathway, and cytochrome P450 metabolism. The hereditary CNVs demonstrate a dominant inheritance pattern. Two candidate pathogenic CNVs were further validated by quantitative-PCR. This study suggests that hallux valgus is a degenerative joint disease involving the dysregulation of immune and metabolism signaling pathways.

Construction and analysis of the chromosome-level haplotype-resolved genomes of two Crassostrea oyster congeners: Crassostrea angulata and Crassostrea gigas

BACKGROUND

The Portuguese oyster Crassostrea angulata and the Pacific oyster C. gigas are two major Crassostrea species that are naturally distributed along the Northwest Pacific coast and possess great ecological and economic value. Here, we report the construction and comparative analysis of the chromosome-level haplotype-resolved genomes of the two oyster congeners.

FINDINGS

Based on a trio-binning strategy, the PacBio high-fidelity and Illumina Hi-C reads of the offspring of the hybrid cross C. angulata (♂) × C. gigas (♀) were partitioned and independently assembled to construct two chromosome-level fully phased genomes. The assembly size (contig N50 size, BUSCO completeness) of the two genomes were 582.4 M (12.8 M, 99.1%) and 606.4 M (5.46 M, 98.9%) for C. angulata and C. gigas, respectively, ranking at the top of mollusk genomes with high contiguity and integrity. The general features of the two genomes were highly similar, and 15,475 highly conserved ortholog gene pairs shared identical gene structures and similar genomic locations. Highly similar sequences can be primarily identified in the coding regions, whereas most noncoding regions and introns of genes in the same ortholog group contain substantial small genomic and/or structural variations. Based on population resequencing analysis, a total of 2,756 species-specific single-nucleotide polymorphisms and 1,088 genes possibly under selection were identified.

CONCLUSIONS

This is the first report of trio-binned fully phased chromosome-level genomes in marine invertebrates. The study provides fundamental resources for the research on mollusk genetics, comparative genomics, and molecular evolution.

The Precise Breakpoint Mapping in Paracentric Inversion 10q22.2q23.3 by Comprehensive Cytogenomic Analysis, Multicolor Banding, and Single-Copy Chromosome Sequencing

Detection and precise genomic mapping of balanced chromosomal abnormalities in patients with impaired fertility or a clinical phenotype represent a challenge for current cytogenomics owing to difficulties with precise breakpoint localization in the regions enriched for DNA repeats and high genomic variation in such regions. Here, we present a comprehensive cytogenomic approach to breakpoint mapping in a rare paracentric inversion on 10q (in a patient with oligoasthenoteratozoospermia and necrozoospermia) that does not affect other phenotype traits. Multicolor banding, chromosomal microarray analysis, chromosome microdissection with reverse painting, and single-copy sequencing of the rearranged chromosome were performed to determine the length and position of the inverted region as well as to rule out a genetic imbalance at the breakpoints. As a result, a paracentric 19.251 Mbp inversion at 10q22.2q23.3 was described. The most probable location of the breakpoints was predicted using the hg38 assembly. The problems of genetic counseling associated with enrichment for repeats and high DNA variability of usual breakpoint regions were discussed. Possible approaches for cytogenomic assessment of couples with balanced chromosome rearrangements and problems like reproductive failures were considered and suggested as useful part of effective genetic counseling.

Bioinformatics roadmap for therapy selection in cancer genomics

Tumour heterogeneity is one of the main characteristics of cancer and can be categorised into inter- or intratumour heterogeneity. This heterogeneity has been revealed as one of the key causes of treatment failure and relapse. Precision oncology is an emerging field that seeks to design tailored treatments for each cancer patient according to epidemiological, clinical and omics data. This discipline relies on bioinformatics tools designed to compute scores to prioritise available drugs, with the aim of helping clinicians in treatment selection. In this review, we describe the current approaches for therapy selection depending on which type of tumour heterogeneity is being targeted and the available next-generation sequencing data. We cover intertumour heterogeneity studies and individual treatment selection using genomics variants, expression data or multi-omics strategies. We also describe intratumour dissection through clonal inference and single-cell transcriptomics, in each case providing bioinformatics tools for tailored treatment selection. Finally, we discuss how these therapy selection workflows could be integrated into the clinical practice.

PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine

Precision medicine has been revolutionized by the advent of high-throughput next-generation sequencing (NGS) technology and development of various bioinformatic analysis tools for large-scale NGS big data. At the population level, biomedical studies have identified human diseases and phenotype-associated genetic variations using NGS technology, such as whole-genome sequencing, exome sequencing, and gene panel sequencing. Furthermore, patients’ genetic variations related to a specific phenotype can also be identified by analyzing their genomic information. These breakthroughs paved the way for the clinical diagnosis and precise treatment of patients’ diseases. Although many bioinformatics tools have been developed to analyze the genetic variations from the individual patient’s NGS data, it is still challenging to develop user-friendly programs for clinical physicians who do not have bioinformatics programing skills to diagnose a patient’s disease using the genomic data. In response to this demand, we developed a Phenotype to Genotype Variation program (PhenGenVar), which is a user-friendly interface for monitoring the variations in a gene of interest for molecular diagnosis. This allows for flexible filtering and browsing of variants of the disease and phenotype-associated genes. To test this program, we analyzed the whole-genome sequencing data of an anonymous person from the 1000 human genome project data. As a result, we were able to identify several genomic variations, including single-nucleotide polymorphism, insertions, and deletions in specific gene regions. Therefore, PhenGenVar can be used to diagnose a patient’s disease. PhenGenVar is freely accessible and is available at our website.

Oxford Nanopore and Bionano Genomics technologies evaluation for plant structural variation detection

Background

Structural Variations (SVs) are genomic rearrangements derived from duplication, deletion, insertion, inversion, and translocation events. In the past, SVs detection was limited to cytological approaches, then to Next-Generation Sequencing (NGS) short reads and partitioned assemblies. Nowadays, technologies such as DNA long read sequencing and optical mapping have revolutionized the understanding of SVs in genomes, due to the enhancement of the power of SVs detection.

This study aims to investigate performance of two techniques, 1) long-read sequencing obtained with the MinION device (Oxford Nanopore Technologies) and 2) optical mapping obtained with Saphyr device (Bionano Genomics) to detect and characterize SVs in the genomes of the two ecotypes of Arabidopsis thaliana, Columbia-0 (Col-0) and Landsberg erecta 1 (Ler-1).

Results

We described the SVs detected from the alignment of the best ONT assembly and DLE-1 optical maps of A. thaliana Ler-1 against the public reference genome Col-0 TAIR10.1. After filtering (SV > 1 kb), 1184 and 591 Ler-1 SVs were retained from ONT and Bionano technologies respectively. A total of 948 Ler-1 ONT SVs (80.1%) corresponded to 563 Bionano SVs (95.3%) leading to 563 common locations. The specific locations were scrutinized to assess improvement in SV detection by either technology. The ONT SVs were mostly detected near TE and gene features, and resistance genes seemed particularly impacted.

Conclusions

Structural variations linked to ONT sequencing error were removed and false positives limited, with high quality Bionano SVs being conserved. When compared with the Col-0 TAIR10.1 reference genome, most of the detected SVs discovered by both technologies were found in the same locations. ONT assembly sequence leads to more specific SVs than Bionano one, the latter being more efficient to characterize large SVs. Even if both technologies are complementary approaches, ONT data appears to be more adapted to large scale populations studies, while Bionano performs better in improving assembly and describing specificity of a genome compared to a reference.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08499-4.

Genomic Variations and Mutational Events Associated with Plant-Pathogen Interactions

Simple Summary

Plants, unlike animals, do not have defender cells or an adaptive immune system. Instead, plants rely on each cell’s innate immunity and systemic signals emitted from infection sites. On the other hand, not all plants, even within the same species, are genetically identical, and their genetic backgrounds determine how well they respond to stress factors. Through evolution, plants have acquired various defense mechanisms that play important roles in the never-ending fight between plants and pathogens. Genetic variation in relation to plant disease resistance can thus be contextualized to provide new insights into these defense mechanisms and evolutionary processes that lead to resistance to pathogens. By focusing on genetic variations and mutational events linked with plant–pathogen interactions, the paper explores how genome compartments facilitate plant and pathogen evolutionary processes.

Abstract

Phytopathologists are actively researching the molecular basis of plant–pathogen interactions. The mechanisms of responses to pathogens have been studied extensively in model crop plant species and natural populations. Today, with the rapid expansion of genomic technologies such as DNA sequencing, transcriptomics, proteomics, and metabolomics, as well as the development of new methods and protocols, data analysis, and bioinformatics, it is now possible to assess the role of genetic variation in plant–microbe interactions and to understand the underlying molecular mechanisms of plant defense and microbe pathogenicity with ever-greater resolution and accuracy. Genetic variation is an important force in evolution that enables organisms to survive in stressful environments. Moreover, understanding the role of genetic variation and mutational events is essential for crop breeders to produce improved cultivars. This review focuses on genetic variations and mutational events associated with plant–pathogen interactions and discusses how these genome compartments enhance plants’ and pathogens’ evolutionary processes.

Assessment of linkage disequilibrium patterns between structural variants and single nucleotide polymorphisms in three commercial chicken populations

BACKGROUND

Structural variants (SV) are causative for some prominent phenotypic traits of livestock as different comb types in chickens or color patterns in pigs. Their effects on production traits are also increasingly studied. Nevertheless, accurately calling SV remains challenging. It is therefore of interest, whether close-by single nucleotide polymorphisms (SNPs) are in strong linkage disequilibrium (LD) with SVs and can serve as markers. Literature comes to different conclusions on whether SVs are in LD to SNPs on the same level as SNPs to other SNPs. The present study aimed to generate a precise SV callset from whole-genome short-read sequencing (WGS) data for three commercial chicken populations and to evaluate LD patterns between the called SVs and surrounding SNPs. It is thereby the first study that assessed LD between SVs and SNPs in chickens.

RESULTS

The final callset consisted of 12,294,329 bivariate SNPs, 4,301 deletions (DEL), 224 duplications (DUP), 218 inversions (INV) and 117 translocation breakpoints (BND). While average LD between DELs and SNPs was at the same level as between SNPs and SNPs, LD between other SVs and SNPs was strongly reduced (DUP: 40%, INV: 27%, BND: 19% of between-SNP LD). A main factor for the reduced LD was the presence of local minor allele frequency differences, which accounted for 50% of the difference between SNP - SNP and DUP - SNP LD. This was potentially accompanied by lower genotyping accuracies for DUP, INV and BND compared with SNPs and DELs. An evaluation of the presence of tag SNPs (SNP in highest LD to the variant of interest) further revealed DELs to be slightly less tagged by WGS SNPs than WGS SNPs by other SNPs. This difference, however, was no longer present when reducing the pool of potential tag SNPs to SNPs located on four different chicken genotyping arrays.

CONCLUSIONS

The results implied that genomic variance due to DELs in the chicken populations studied can be captured by different SNP marker sets as good as variance from WGS SNPs, whereas separate SV calling might be advisable for DUP, INV, and BND effects.

A guide for the diagnosis of rare and undiagnosed disease: beyond the exome

Rare diseases affect 30 million people in the USA and more than 300–400 million worldwide, often causing chronic illness, disability, and premature death. Traditional diagnostic techniques rely heavily on heuristic approaches, coupling clinical experience from prior rare disease presentations with the medical literature. A large number of rare disease patients remain undiagnosed for years and many even die without an accurate diagnosis. In recent years, gene panels, microarrays, and exome sequencing have helped to identify the molecular cause of such rare and undiagnosed diseases. These technologies have allowed diagnoses for a sizable proportion (25–35%) of undiagnosed patients, often with actionable findings. However, a large proportion of these patients remain undiagnosed. In this review, we focus on technologies that can be adopted if exome sequencing is unrevealing. We discuss the benefits of sequencing the whole genome and the additional benefit that may be offered by long-read technology, pan-genome reference, transcriptomics, metabolomics, proteomics, and methyl profiling. We highlight computational methods to help identify regionally distant patients with similar phenotypes or similar genetic mutations. Finally, we describe approaches to automate and accelerate genomic analysis. The strategies discussed here are intended to serve as a guide for clinicians and researchers in the next steps when encountering patients with non-diagnostic exomes.

Multi-Platform-Based Analysis Characterizes Molecular Alterations of the Nucleus in Human Colorectal Cancer

Background: The disturbed molecular alterations of nucleus may promote the development of colorectal cancer (CRC). A multi-platform-based analysis of nucleus of CRC patients helps us to better understand the underlying mechanism of CRC and screen out the potential drug targets for clinical treatment. However, such studies on nucleus in human CRC are still lacking.

Methods: We collected the cancerous and para-cancerous tissues from eight CRC patients and performed a multiplex analysis of the molecular changes of the nucleus, including structural variations (SVs), DNA methylation, chromatin accessibility, proteome and phosphorproteome.

Results: In our study, we revealed a significant molecular change of nucleus of CRC patients using our original proteomic and phosphorylomic datasets. Subsequently, we characterized the molecular alterations of nucleus of CRC patients at multiple dimensionalities, including DNA, mRNA, protein and epigenetic modification. Next, we found that the great molecular changes of nucleus might affect the biological processes named endocytosis and ubiquitin-mediated proteolysis. Besides, we identified DYNC1LI2 and TPR as the potentially hub proteins within the network of nuclear genes in CRC cells. Furthermore, we identified 1905 CRC-specific SVs, and proclaimed 17 CRC-specific SVs were probably associated with the disturbance of immune microenvironment of CRC patients. We also revealed that the SVs of CXCL5, CXCL10 and CXCL11 might be the core SVs among all the immune-relevant SVs. Finally, we identified seven genes as the upstream transcriptional factors potentially regulating the expression of nuclear genes, such as YY1 and JUN, using a multi-omics approach.

Conclusion: Here, we characterized the molecular changes of nucleus of CRC patients, disclosed the potentially core nuclear genes within the network, and identified the probable upstream regulator of nucleus. The findings of this study are helpful to understand the pathogenic molecular changes of nucleus in CRC patients and provide a functional context for drug development in future.

Tool evaluation for the detection of variably sized indels from next generation whole genome and targeted sequencing data

Insertions and deletions (indels) in human genomes are associated with a wide range of phenotypes, including various clinical disorders. High-throughput, next generation sequencing (NGS) technologies enable the detection of short genetic variants, such as single nucleotide variants (SNVs) and indels. However, the variant calling accuracy for indels remains considerably lower than for SNVs. Here we present a comparative study of the performance of variant calling tools for indel calling, evaluated with a wide repertoire of NGS datasets. While there is no single optimal tool to suit all circumstances, our results demonstrate that the choice of variant calling tool greatly impacts the precision and recall of indel calling. Furthermore, to reliably detect indels, it is essential to choose NGS technologies that offer a long read length and high coverage coupled with specific variant calling tools.

A benchmark of structural variation detection by long reads through a realistic simulated model

Accurate simulations of structural variation distributions and sequencing data are crucial for the development and benchmarking of new tools. We develop Sim-it, a straightforward tool for the simulation of both structural variation and long-read data. These simulations from Sim-it reveal the strengths and weaknesses for current available structural variation callers and long-read sequencing platforms. With these findings, we develop a new method (combiSV) that can combine the results from structural variation callers into a superior call set with increased recall and precision, which is also observed for the latest structural variation benchmark set developed by the GIAB Consortium.

Evaluation of copy number variants for genetic hearing loss: a review of current approaches and recent findings

Structural variation includes a change in copy number, orientation, or location of a part of the genome. Copy number variants (CNVs) are a common cause of genetic hearing loss, comprising nearly 20% of diagnosed cases. While large deletions involving the gene STRC are the most common pathogenic CNVs, a significant proportion of known hearing loss genes also contain pathogenic CNVs. In this review, we provide an overview of currently used methods for detection of CNVs in genes known to cause hearing loss including molecular techniques such as multiplex ligation probe amplification (MLPA) and digital droplet polymerase chain reaction (ddPCR), array-CGH and single-nucleotide polymorphism (SNP) arrays, as well as techniques for detection of CNVs using next-generation sequencing data analysis including targeted gene panel, exome, and genome sequencing data. In addition, in this review, we compile published data on pathogenic hearing loss CNVs to provide an up-to-date overview. We show that CNVs have been identified in 29 different non-syndromic hearing loss genes. An understanding of the contribution of CNVs to genetic hearing loss is critical to the current diagnosis of hearing loss and is crucial for future gene therapies. Thus, evaluation for CNVs is required in any modern pipeline for genetic diagnosis of hearing loss.

Current status of structural variation studies in plants

Structural variations (SVs) including gene presence/absence variations and copy number variations are a common feature of genomes in plants and, together with single nucleotide polymorphisms and epigenetic differences, are responsible for the heritable phenotypic diversity observed within and between species. Understanding the contribution of SVs to plant phenotypic variation is important for plant breeders to assist in producing improved varieties. The low resolution of early genetic technologies and inefficient methods have previously limited our understanding of SVs in plants. However, with the rapid expansion in genomic technologies, it is possible to assess SVs with an ever-greater resolution and accuracy. Here, we review the current status of SV studies in plants, examine the roles that SVs play in phenotypic traits, compare current technologies and assess future challenges for SV studies.

Meta-Analysis of Joint Test of SNP and SNP-Environment Interaction with Heterogeneity

Many complex diseases are caused by single nucleotide polymorphisms (SNPs), environmental factors, and the interaction between SNPs and environment. Joint tests of the SNP and SNP-environment interaction effects (JMA) and meta-regression (MR) are commonly used to evaluate these SNP-environment interactions. However, these two methods do not consider genetic heterogeneity. We previously presented a random-effect MR, which provided higher power than the MR in datasets with high heterogeneity. However, this method requires group-level data, which sometimes are not available. Given this, we designed this study to evaluate the introduction of the random effects of SNP and SNP-environment interaction into the JMA, and then extended this to the random effect model. Likelihood ratio statistic is applied to test the JMA and the new method we proposed in this paper. We evaluated the null distributions of these tests, and the powers for this method. This method was verified by simulation and was shown to provide similar powers to the random effect meta-regression method (RMR). However, this method only requires study-level data which relaxed the condition of the RMR. Our study suggests that this method is more suitable for finding the association between SNP and diseases in the absence of group-level data.

Domestication shapes recombination patterns in tomato

Meiotic recombination is a biological process of key importance in breeding, to generate genetic diversity and develop novel or agronomically relevant haplotypes. In crop tomato, recombination is curtailed as manifested by linkage disequilibrium decay over a longer distance and reduced diversity compared with wild relatives. Here, we compared domesticated and wild populations of tomato and found an overall conserved recombination landscape, with local changes in effective recombination rate in specific genomic regions. We also studied the dynamics of recombination hotspots resulting from domestication and found that loss of such hotspots is associated with selective sweeps, most notably in the pericentromeric heterochromatin. We detected footprints of genetic changes and structural variants, among them associated with transposable elements, linked with hotspot divergence during domestication, likely causing fine-scale alterations to recombination patterns and resulting in linkage drag.

An Overview of the Genetics of ABCA4 Retinopathies, an Evolving Story

Stargardt disease (STGD1) and ABCA4 retinopathies (ABCA4R) are caused by pathogenic variants in the ABCA4 gene inherited in an autosomal recessive manner. The gene encodes an importer flippase protein that prevents the build-up of vitamin A derivatives that are toxic to the RPE. Diagnosing ABCA4R is complex due to its phenotypic variability and the presence of other inherited retinal dystrophy phenocopies. ABCA4 is a large gene, comprising 50 exons; to date > 2000 variants have been described. These include missense, nonsense, splicing, structural, and deep intronic variants. Missense variants account for the majority of variants in ABCA4. However, in a significant proportion of patients with an ABCA4R phenotype, a second variant in ABCA4 is not identified. This could be due to the presence of yet unknown variants, or hypomorphic alleles being incorrectly classified as benign, or the possibility that the disease is caused by a variant in another gene. This underlines the importance of accurate genetic testing. The pathogenicity of novel variants can be predicted using in silico programs, but these rely on databases that are not ethnically diverse, thus highlighting the need for studies in differing populations. Functional studies in vitro are useful towards assessing protein function but do not directly measure the flippase activity. Obtaining an accurate molecular diagnosis is becoming increasingly more important as targeted therapeutic options become available; these include pharmacological, gene-based, and cell replacement-based therapies. The aim of this review is to provide an update on the current status of genotyping in ABCA4 and the status of the therapeutic approaches being investigated.

Recommendations for Statistical Reporting in Cardiovascular Medicine: A Special Report From the American Heart Association

Statistical analyses are a crucial component of the biomedical research process and are necessary to draw inferences from biomedical research data. The application of sound statistical methodology is a prerequisite for publication in the American Heart Association (AHA) journal portfolio. The objective of this document is to summarize key aspects of statistical reporting that might be most relevant to the authors, reviewers, and readership of AHA journals. The AHA Scientific Publication Committee convened a task force to inventory existing statistical standards for publication in biomedical journals and to identify approaches suitable for the AHA journal portfolio. The experts on the task force were selected by the AHA Scientific Publication Committee, who identified 12 key topics that serve as the section headers for this document. For each topic, the members of the writing group identified relevant references and evaluated them as a resource to make the standards summarized herein. Each section was independently reviewed by an expert reviewer who was not part of the task force. Expert reviewers were also permitted to comment on other sections if they chose. Differences of opinion were adjudicated by consensus. The standards presented in this report are intended to serve as a guide for high-quality reporting of statistical analyses methods and results.

Detection of copy number variants in African goats using whole genome sequence data

Background

Copy number variations (CNV) are a significant source of variation in the genome and are therefore essential to the understanding of genetic characterization. The aim of this study was to develop a fine-scaled copy number variation map for African goats. We used sequence data from multiple breeds and from multiple African countries.

Results

A total of 253,553 CNV (244,876 deletions and 8677 duplications) were identified, corresponding to an overall average of 1393 CNV per animal. The mean CNV length was 3.3 kb, with a median of 1.3 kb. There was substantial differentiation between the populations for some CNV, suggestive of the effect of population-specific selective pressures. A total of 6231 global CNV regions (CNVR) were found across all animals, representing 59.2 Mb (2.4%) of the goat genome. About 1.6% of the CNVR were present in all 34 breeds and 28.7% were present in all 5 geographical areas across Africa, where animals had been sampled. The CNVR had genes that were highly enriched in important biological functions, molecular functions, and cellular components including retrograde endocannabinoid signaling, glutamatergic synapse and circadian entrainment.

Conclusions

This study presents the first fine CNV map of African goat based on WGS data and adds to the growing body of knowledge on the genetic characterization of goats.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07703-1.

An approach to rapid characterization of DMD copy number variants for prenatal risk assessment

Prenatal detection of structural variants of uncertain significance, including copy number variants (CNV), challenges genetic counseling, and creates ambiguity for expectant parents. In Duchenne muscular dystrophy, variant classification and phenotypic severity of CNVs are currently assessed by familial segregation, prediction of the effect on the reading frame, and precedent data. Delineation of pathogenicity by familial segregation is limited by time and suitable family members, whereas analytical tools can rapidly delineate potential consequences of variants. We identified a duplication of uncertain significance encompassing a portion of the dystrophin gene (DMD) in an unaffected mother and her male fetus. Using long-read whole genome sequencing and alignment of short reads, we rapidly defined the precise breakpoints of this variant in DMD and could provide timely counseling. The benign nature of the variant was substantiated, more slowly, by familial segregation to a healthy maternal uncle. We find long-read whole genome sequencing of clinical utility in a prenatal setting for accurate and rapid characterization of structural variants, specifically a duplication involving DMD.

Detection of somatic structural variants from short-read next-generation sequencing data

Somatic structural variants (SVs), which are variants that typically impact >50 nucleotides, play a significant role in cancer development and evolution but are notoriously more difficult to detect than small variants from short-read next-generation sequencing (NGS) data. This is due to a combination of challenges attributed to the purity of tumour samples, tumour heterogeneity, limitations of short-read information from NGS and sequence alignment ambiguities. In spite of active development of SV detection tools (callers) over the past few years, each method has inherent advantages and limitations. In this review, we highlight some of the important factors affecting somatic SV detection and compared the performance of seven commonly used SV callers. In particular, we focus on the extent of change in sensitivity and precision for detecting different SV types and size ranges from samples with differing variant allele frequencies and sequencing depths of coverage. We highlight the reasons for why some SV callers perform well in some settings but not others, allowing our evaluation findings to be extended beyond the seven SV callers examined in this paper. As the importance of large SVs become increasingly recognized in cancer genomics, this paper provides a timely review on some of the most impactful factors influencing somatic SV detection that should be considered when choosing SV callers.

An Overview of Molecular Genetic Diagnosis Techniques

Our understanding of genetic disease(s) has increased exponentially since the completion of human genome sequencing and the development of numerous techniques to detect genetic variants. These techniques have not only allowed us to diagnose genetic disease, but in so doing, also provide increased understanding of the pathogenesis of these diseases to aid in developing appropriate therapeutic options. Additionally, the advent of next-generation or massively parallel sequencing (NGS/MPS) is increasingly being used in the clinical setting, as it can detect a number of abnormalities from point mutations to chromosomal rearrangements as well as aberrations within the transcriptome. In this article, we will discuss the use of multiple techniques that are used in genetic diagnosis. © 2020 by John Wiley & Sons, Inc.

Genomic patterns of structural variation among diverse genotypes of Sorghum bicolor and a potential role for deletions in local adaptation

Genomic structural mutations, especially deletions, are an important source of variation in many species and can play key roles in phenotypic diversification and evolution. Previous work in many plant species has identified multiple instances of structural variations (SVs) occurring in or near genes related to stress response and disease resistance, suggesting a possible role for SVs in local adaptation. Sorghum [Sorghum bicolor (L.) Moench] is one of the most widely grown cereal crops in the world. It has been adapted to an array of different climates as well as bred for multiple purposes, resulting in a striking phenotypic diversity. In this study, we identified genome-wide SVs in the Biomass Association Panel, a collection of 347 diverse sorghum genotypes collected from multiple countries and continents. Using Illumina-based, short-read whole-genome resequencing data from every genotype, we found a total of 24,648 SVs, including 22,359 deletions. The global site frequency spectrum of deletions and other types of SVs fit a model of neutral evolution, suggesting that the majority of these mutations were not under any types of selection. Clustering results based on single nucleotide polymorphisms separated the genotypes into eight clusters which largely corresponded with geographic origins, with many of the large deletions we uncovered being unique to a single cluster. Even though most deletions appeared to be neutral, a handful of cluster-specific deletions were found in genes related to biotic and abiotic stress responses, supporting the possibility that at least some of these deletions contribute to local adaptation in sorghum.

Construction of a chromosome-level genome and variation map for the Pacific oyster Crassostrea gigas

The Pacific oyster (Crassostrea gigas) is a widely distributed marine bivalve of great ecological and economic importance. In this study, we provide a high-quality chromosome-level genome assembled using Pacific Bioscience long reads and Hi-C-based and linkage-map-based scaffolding technologies and a high-resolution variation map constructed using large-scale resequencing analysis. The 586.8 Mb genome consists of 10 pseudochromosome sequences ranging from 38.6 to 78.9 Mb, containing 301 contigs with an N50 size of 3.1 Mb. A total of 30,078 protein-coding genes were predicted, of which 22,757 (75.7%) were high-reliability annotations supported by a homologous match to a curated protein in the SWISS-PROT database or transcript expression. Although a medium level of repeat components (57.2%) was detected, the genomic content of the segmental duplications reached 26.2%, which is the highest among the reported genomes. By whole genome resequencing analysis of 495 Pacific oysters, a comprehensive variation map was built, comprised of 4.78 million single nucleotide polymorphisms, 0.60 million short insertions and deletions, and 49,333 copy number variation regions. The structural variations can lead to an average interindividual genomic divergence of 0.21, indicating their crucial role in shaping the Pacific oyster genome diversity. The large amount of mosaic distributed repeat elements, small variations, and copy number variations indicate that the Pacific oyster is a diploid organism with an extremely high genomic complexity at the intra- and interindividual level. The genome and variation maps can improve our understanding of oyster genome diversity and enrich the resources for oyster molecular evolution, comparative genomics, and genetic research.

Next Generation Sequencing Technology in the Clinic and Its Challenges

Simple Summary

Precise identification and annotation of mutations are of utmost importance in clinical oncology. Insights of the DNA sequence can provide meaningful knowledge to unravel the underlying genetics of disease. Hence, tailoring of personalized medicine often relies on specific genomic alteration for treatment efficacy. The aim of this review is to highlight that sequencing harbors much more than just four nucleotides. Moreover, the gradual transition from first to second generation sequencing technologies has led to awareness for choosing the most appropriate bioinformatic analytic tools based on the aim, quality and demand for a specific purpose. Thus, the same raw data can lead to various results reflecting the intrinsic features of different datamining pipelines.

Abstract

Data analysis has become a crucial aspect in clinical oncology to interpret output from next-generation sequencing-based testing. NGS being able to resolve billions of sequencing reactions in a few days has consequently increased the demand for tools to handle and analyze such large data sets. Many tools have been developed since the advent of NGS, featuring their own peculiarities. Increased awareness when interpreting alterations in the genome is therefore of utmost importance, as the same data using different tools can provide diverse outcomes. Hence, it is crucial to evaluate and validate bioinformatic pipelines in clinical settings. Moreover, personalized medicine implies treatment targeting efficacy of biological drugs for specific genomic alterations. Here, we focused on different sequencing technologies, features underlying the genome complexity, and bioinformatic tools that can impact the final annotation. Additionally, we discuss the clinical demand and design for implementing NGS.

Long-read trio sequencing of individuals with unsolved intellectual disability

Long-read sequencing (LRS) has the potential to comprehensively identify all medically relevant genome variation, including variation commonly missed by short-read sequencing (SRS) approaches. To determine this potential, we performed LRS around 15×-40× genome coverage using the Pacific Biosciences Sequel I System for five trios. The respective probands were diagnosed with intellectual disability (ID) whose etiology remained unresolved after SRS exomes and genomes. Systematic assessment of LRS coverage showed that ~35 Mb of the human reference genome was only accessible by LRS and not SRS. Genome-wide structural variant (SV) calling yielded on average 28,292 SV calls per individual, totaling 12.9 Mb of sequence. Trio-based analyses which allowed to study segregation, showed concordance for up to 95% of these SV calls across the genome, and 80% of the LRS SV calls were not identified by SRS. De novo mutation analysis did not identify any de novo SVs, confirming that these are rare events. Because of high sequence coverage, we were also able to call single nucleotide substitutions. On average, we identified 3 million substitutions per genome, with a Mendelian inheritance concordance of up to 97%. Of these, ~100,000 were located in the ~35 Mb of the genome that was only captured by LRS. Moreover, these variants affected the coding sequence of 64 genes, including 32 known Mendelian disease genes. Our data show the potential added value of LRS compared to SRS for identifying medically relevant genome variation.

Remus: A Web Application for Prioritization of Regulatory Regions and Variants in Monogenic Diseases

Background

Analysis of variants in distant regulatory elements could improve the current 25–50% yield of genetic testing for monogenic diseases. However, the vast size of the regulome, great number of variants, and the difficulty in predicting their phenotypic impact make searching for pathogenic variants in the regulatory genome challenging. New tools for the identification of regulatory variants based on their relevance to the phenotype are needed.

Methods

We used tissue-specific regulatory loci mapped by ENCODE and FANTOM, together with miRNA–gene interactions from miRTarBase and miRWalk, to develop Remus, a web application for the identification of tissue-specific regulatory regions. Remus searches for regulatory features linked to the known disease-associated genes and filters them using activity status in the target tissues relevant for the studied disorder. For user convenience, Remus provides a web interface and facilitates in-browser filtering of variant files suitable for sensitive patient data.

Results

To evaluate our approach, we used a set of 146 regulatory mutations reported causative for 68 distinct monogenic disorders and a manually curated a list of tissues affected by these disorders. In 89.7% of cases, Remus identified the regulator containing the pathogenic mutation. The tissue-specific search limited the number of considered variants by 82.5% as compared to a tissue-agnostic search.

Conclusion

Remus facilitates the identification of regulatory regions potentially associated with a monogenic disease and can supplement classical analysis of coding variations with the aim of improving the diagnostic yield in whole-genome sequencing experiments.

Intronic Breakpoint Signatures Enhance Detection and Characterization of Clinically Relevant Germline Structural Variants

The relevance of large copy number variants (CNVs) to hereditary disorders has been long recognized, and population sequencing efforts have chronicled many common structural variants (SVs). However, limited data are available on the clinical contribution of rare germline SVs. Here, a detailed characterization of SVs identified using targeted next-generation sequencing was performed. Across 50 genes associated with hereditary cancer and cardiovascular disorders, a minimum of 828 unique SVs were reported, including 584 fully characterized SVs. Almost 40% of CNVs were <5 kb, with one in three deletions impacting a single exon. Additionally, 36 mid-range deletions/duplications (50 to 250 bp), 21 mobile element insertions, 6 inversions, and 27 complex rearrangements were detected. This data set was used to model SV detection in a bioinformatics pipeline solely relying on read depth, which revealed that genome sequencing (30×) allows detection of 71%, a 500× panel only targeting coding regions 53%, and exome sequencing (100×) <20% of characterized SVs. SVs accounted for 14.1% of all unique pathogenic variants, supporting the importance of SVs in hereditary disorders. Robust SV detection requires an ensemble of variant-calling algorithms that utilize sequencing of intronic regions. These algorithms should use distinct data features representative of each class of mutational mechanism, including recombination between two sequences sharing high similarity, covariants inserted between CNV breakpoints, and complex rearrangements containing inverted sequences.

Analysis of Structural Variants Reveal Novel Selective Regions in the Genome of Meishan Pigs by Whole Genome Sequencing

Structural variants (SVs) represent essential forms of genetic variation, and they are associated with various phenotypic traits in a wide range of important livestock species. However, the distribution of SVs in the pig genome has not been fully characterized, and the function of SVs in the economic traits of pig has rarely been studied, especially for most domestic pig breeds. Meishan pig is one of the most famous Chinese domestic pig breeds, with excellent reproductive performance. Here, to explore the genome characters of Meishan pig, we construct an SV map of porcine using whole-genome sequencing data and report 33,698 SVs in 305 individuals of 55 globally distributed pig breeds. We perform selective signature analysis using these SVs, and a number of candidate variants are successfully identified. Especially for the Meishan pig, 64 novel significant selection regions are detected in its genome. A 140-bp deletion in the Indoleamine 2,3-Dioxygenase 2 (IDO2) gene, is shown to be associated with reproduction traits in Meishan pig. In addition, we detect two duplications only existing in Meishan pig. Moreover, the two duplications are separately located in cytochrome P450 family 2 subfamily J member 2 (CYP2J2) gene and phospholipase A2 group IVA (PLA2G4A) gene, which are related to the reproduction trait. Our study provides new insights into the role of selection in SVs' evolution and how SVs contribute to phenotypic variation in pigs.

Population Genomics of Fungal Plant Pathogens and the Analyses of Rapidly Evolving Genome Compartments

Genome sequencing of fungal pathogens have documented extensive variation in genome structure and composition between species and in many cases between individuals of the same species. This type of genomic variation can be adaptive for pathogens to rapidly evolve new virulence phenotypes. Analyses of genome-wide variation in fungal pathogen genomes rely on high quality assemblies and methods to detect and quantify structural variation. Population genomic studies in fungi have addressed the underlying mechanisms whereby structural variation can be rapidly generated. Transposable elements, high mutation and recombination rates as well as incorrect chromosome segregation during mitosis and meiosis contribute to extensive variation observed in many species. We here summarize key findings in the field of fungal pathogen genomics and we discuss methods to detect and characterize structural variants including an alignment-based pipeline to study variation in population genomic data.

A map of copy number variations in the Tunisian population: a valuable tool for medical genomics in North Africa

Copy number variation (CNV) is considered as the most frequent type of structural variation in the human genome. Some CNVs can act on human phenotype diversity, encompassing rare Mendelian diseases and genomic disorders. The North African populations remain underrepresented in public genetic databases in terms of single-nucleotide variants as well as for larger genomic mutations. In this study, we present the first CNV map for a North African population using the Affymetrix Genome-Wide SNP (single-nucleotide polymorphism) array 6.0 array genotyping intensity data to call CNVs in 102 Tunisian healthy individuals. Two softwares, PennCNV and Birdsuite, were used to call CNVs in order to provide reliable data. Subsequent bioinformatic analyses were performed to explore their features and patterns. The CNV map of the Tunisian population includes 1083 CNVs spanning 61.443 Mb of the genome. The CNV length ranged from 1.017 kb to 2.074 Mb with an average of 56.734 kb. Deletions represent 57.43% of the identified CNVs, while duplications and the mixed loci are less represented. One hundred and three genes disrupted by CNVs are reported to cause 155 Mendelian diseases/phenotypes. Drug response genes were also reported to be affected by CNVs. Data on genes overlapped by deletions and duplications segments and the sequence properties in and around them also provided insights into the functional and health impacts of CNVs. These findings represent valuable clues to genetic diversity and personalized medicine in the Tunisian population as well as in the ethnically similar populations from North Africa.

In Silico Tools and Approaches for the Prediction of Functional and Structural Effects of Single-Nucleotide Polymorphisms on Proteins: An Expert Review

Single-nucleotide polymorphisms (SNPs) are single-base variants that contribute to human biological variation and pathogenesis of many human diseases. Among all SNP types, nonsynonymous single-nucleotide polymorphisms (nsSNPs) can alter many structural, biochemical, and functional features of a protein such as folding characteristics, charge distribution, stability, dynamics, and interactions with other proteins/nucleotides. These modifications in the protein structure can lead nsSNPs to be closely associated with many multifactorial diseases such as cancer, diabetes, and neurodegenerative diseases. Predicting structural and functional effects of nsSNPs with experimental approaches can be time-consuming and costly; hence, computational prediction tools and algorithms are being widely and increasingly utilized in biology and medical research. This expert review examines the in silico tools and algorithms for the prediction of functional or structural effects of SNP variants, in addition to the description of the phenotypic effects of nsSNPs on protein structure, association between pathogenicity of variants, and functional or structural features of disease-associated variants. Finally, case studies investigating the functional and structural effects of nsSNPs on selected protein structures are highlighted. We conclude that creating a consistent workflow with a combination of in silico approaches or tools should be considered to increase the performance, accuracy, and precision of the biological and clinical predictions made in silico.

Breakpoint mapping of a t(9;22;12) chronic myeloid leukaemia patient with e14a3 BCR-ABL1 transcript using Nanopore sequencing

BACKGROUND

The genetic changes in chronic myeloid leukaemia (CML) have been well established, although challenges persist in cases with rare fusion transcripts or complex variant translocations. Here, we present a CML patient with e14a3 BCR-ABL1 transcript and t(9;22;12) variant Philadelphia (Ph) chromosome.

METHODS

Cytogenetic analysis and fluorescence in situ hybridization (FISH) was performed to identify the chromosomal aberrations and gene fusions. Rare fusion transcript was verified by a reverse transcription-polymerase chain reaction (RT-PCR). Breakpoints were characterized and validated using Oxford Nanopore Technologies (ONT) (Oxford, UK) and Sanger sequencing, respectively.

RESULTS

The karyotype showed the translocation t(9;22;12)(q34;q11.2;q24) [20] and FISH indicated 40% positive BCR-ABL1 fusion signals. The RT-PCR suggested e14a3 type fusion transcript. The ONT sequencing analysis identified specific positions of translocation breakpoints: chr22:23633040-chr9:133729579, chr12:121567595-chr22:24701405, which were confirmed using Sanger sequencing. The patient achieved molecular remission 3 months after imatinib therapy.

CONCLUSIONS

The present study indicates Nanopore sequencing as a valid strategy, which can characterize breakpoints precisely in special clinical cases with atypical structural variations. CML patients with e14a3 transcripts may have good clinical course in the tyrosine kinase inhibitor era, as reviewed here.

SVXplorer: Three-tier approach to identification of structural variants via sequential recombination of discordant cluster signatures

The identification of structural variants using short-read data remains challenging. Most approaches that use discordant paired-end sequences ignore non-trivial signatures presented by variants containing 3 breakpoints, such as those generated by various copy-paste and cut-paste mechanisms. This can result in lower precision and sensitivity in the identification of the more common structural variants such as deletions and duplications. We present SVXplorer, which uses a graph-based clustering approach streamlined by the integration of non-trivial signatures from discordant paired-end alignments, split-reads and read depth information to improve upon existing methods. We show that SVXplorer is more sensitive and precise compared to several existing approaches on multiple real and simulated datasets. SVXplorer is available for download at https://github.com/kunalkathuria/SVXplorer.