scholarly journals Insights from Initial Variant Detection by Sequencing Single Sperm in Cattle

Dairy ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 649-657
Author(s):  
Liu Yang ◽  
Yahui Gao ◽  
Clarissa Boschiero ◽  
Li Li ◽  
Hongping Zhang ◽  
...  
Keyword(s):  
De Novo ◽  
Point Mutations ◽  
De Novo Mutation ◽  
Model Organisms ◽  
Future Research ◽  
Whole Genome ◽  
Sequencing Data ◽  
Sequence Coverage ◽  
Genome Sequencing Effort ◽  
Variant Detection

Meiotic de novo mutation (DNM) is one of the important phenomena contributing to gamete genome diversity. However, except for humans and a few model organisms, they are not well studied in livestock, including cattle. Moreover, bulk sperm samples have been routinely utilized in experiments, which include millions of single sperm cells and only report high-frequency variants. In this study, we isolated and sequenced 143 single sperms from two Holstein bulls and identified hundreds of candidate DNM events in ten sperms with deep sequencing coverage. We estimated DNM rates ranging from 1.08 × 10−8 to 3.78 × 10−8 per nucleotide per generation. We further validated 12 out of 14 selected DNM events using Sanger sequencing. To our knowledge, this is the first single sperm whole-genome sequencing effort in livestock, which provided useful information for future studies of point mutations and male fertility. Our preliminary results pointed out future research directions and highlighted the importance of uniform whole genome amplification, deep sequence coverage, and dedicated software pipelines for genetic variant detection using single-cell sequencing data.

scholarly journals De novo ZIC2 frameshift variant associated with frontonasal dysplasia in a Limousin calf

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Marina Braun ◽  
Annika Lehmbecker ◽  
Deborah Eikelberg ◽  
Maren Hellige ◽  
Andreas Beineke ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
De Novo ◽  
De Novo Mutation ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Craniofacial Malformations ◽  
Frontonasal Dysplasia ◽  
Affected Calf

Abstract Background Bovine frontonasal dysplasias like arhinencephaly, synophthalmia, cyclopia and anophthalmia are sporadic congenital facial malformations. In this study, computed tomography, necropsy, histopathological examinations and whole genome sequencing on an Illumina NextSeq500 were performed to characterize a stillborn Limousin calf with frontonasal dysplasia. In order to identify private genetic and structural variants, we screened whole genome sequencing data of the affected calf and unaffected relatives including parents, a maternal and paternal halfsibling. Results The stillborn calf exhibited severe craniofacial malformations. Nose and maxilla were absent, mandibles were upwardly curved and a median cleft palate was evident. Eyes, optic nerve and orbital cavities were not developed and the rudimentary orbita showed hypotelorism. A defect centrally in the front skull covered with a membrane extended into the intracranial cavity. Aprosencephaly affected telencephalic and diencephalic structures and cerebellum. In addition, a shortened tail was seen. Filtering whole genome sequencing data revealed a private frameshift variant within the candidate gene ZIC2 in the affected calf. This variant was heterozygous mutant in this case and homozygous wild type in parents, half-siblings and controls. Conclusions We found a novel ZIC2 frameshift mutation in an aprosencephalic Limousin calf. The origin of this variant is most likely due to a de novo mutation in the germline of one parent or during very early embryonic development. To the authors’ best knowledge, this is the first identified mutation in cattle associated with bovine frontonasal dysplasia.

scholarly journals De Novo Mutation in an Enhancer of EBF3 in simplex autism

2020 ◽  
Author(s):  
Evin M. Padhi ◽  
Tristan J. Hayeck ◽  
Brandon Mannion ◽  
Sumantra Chatterjee ◽  
Marta Byrska-Bishop ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
De Novo ◽  
Neurodevelopmental Disorder ◽  
De Novo Mutation ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Enhancer Activity ◽  
Protein Coding

AbstractPrevious research in autism and other neurodevelopmental disorders (NDDs) has indicated an important contribution of de novo protein-coding variants within specific genes. The role of de novo noncoding variation has been observable as a general increase in genetic burden but has yet to be resolved to individual functional elements. In this study, we assessed whole-genome sequencing data in 2,671 families with autism, with a specific focus on de novo variation in enhancers with previously characterized in vivo activity. We identified three independent de novo mutations limited to individuals with autism in the enhancer hs737. These mutations result in similar phenotypic characteristics, affect enhancer activity in vitro, and preferentially occur in AAT motifs in the enhancer with predicted disruptions of transcription factor binding. We also find that hs737 is enriched for copy number variation in individuals with NDDs, is dosage sensitive in the human population, is brain-specific, and targets the NDD gene EBF3 that is genome-wide significant for protein coding de novo variants, demonstrating the importance of understanding all forms of variation in the genome.One Sentence SummaryWhole-genome sequencing in thousands of families reveals variants relevant to simplex autism in a brain enhancer of the well-established neurodevelopmental disorder gene EBF3.

AStrap: identification of alternative splicing from transcript sequences without a reference genome

2018 ◽  
Vol 35 (15) ◽  
pp. 2654-2656 ◽  
Author(s):  
Guoli Ji ◽  
Wenbin Ye ◽  
Yaru Su ◽  
Moliang Chen ◽  
Guangzao Huang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Alternative Splicing ◽  
Single Molecule ◽  
Reference Genome ◽  
De Novo ◽  
Supplementary Information ◽  
Model Organisms ◽  
Sequencing Data ◽  
Extensive Evaluation ◽  
Reference Genomes

Abstract Summary Alternative splicing (AS) is a well-established mechanism for increasing transcriptome and proteome diversity, however, detecting AS events and distinguishing among AS types in organisms without available reference genomes remains challenging. We developed a de novo approach called AStrap for AS analysis without using a reference genome. AStrap identifies AS events by extensive pair-wise alignments of transcript sequences and predicts AS types by a machine-learning model integrating more than 500 assembled features. We evaluated AStrap using collected AS events from reference genomes of rice and human as well as single-molecule real-time sequencing data from Amborella trichopoda. Results show that AStrap can identify much more AS events with comparable or higher accuracy than the competing method. AStrap also possesses a unique feature of predicting AS types, which achieves an overall accuracy of ∼0.87 for different species. Extensive evaluation of AStrap using different parameters, sample sizes and machine-learning models on different species also demonstrates the robustness and flexibility of AStrap. AStrap could be a valuable addition to the community for the study of AS in non-model organisms with limited genetic resources. Availability and implementation AStrap is available for download at https://github.com/BMILAB/AStrap. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Insights into dispersed duplications and complex structural mutations from whole genome sequencing 706 families

2020 ◽  
Author(s):  
Christopher W. Whelan ◽  
Robert E. Handsaker ◽  
Giulio Genovese ◽  
Seva Kashin ◽  
Monkol Lek ◽  
...  
Keyword(s):  
Gene Expression ◽  
Copy Number Variation ◽  
Copy Number ◽  
De Novo ◽  
Whole Genome ◽  
Sequencing Data ◽  
Number Variation ◽  
Structural Mutations ◽  
Or Gene ◽  
Genomic Locations

AbstractTwo intriguing forms of genome structural variation (SV) – dispersed duplications, and de novo rearrangements of complex, multi-allelic loci – have long escaped genomic analysis. We describe a new way to find and characterize such variation by utilizing identity-by-descent (IBD) relationships between siblings together with high-precision measurements of segmental copy number. Analyzing whole-genome sequence data from 706 families, we find hundreds of “IBD-discordant” (IBDD) CNVs: loci at which siblings’ CNV measurements and IBD states are mathematically inconsistent. We found that commonly-IBDD CNVs identify dispersed duplications; we mapped 95 of these common dispersed duplications to their true genomic locations through family-based linkage and population linkage disequilibrium (LD), and found several to be in strong LD with genome-wide association (GWAS) signals for common diseases or gene expression variation at their revealed genomic locations. Other CNVs that were IBDD in a single family appear to involve de novo mutations in complex and multi-allelic loci; we identified 26 de novo structural mutations that had not been previously detected in earlier analyses of the same families by diverse SV analysis methods. These included a de novo mutation of the amylase gene locus and multiple de novo mutations at chromosome 15q14. Combining these complex mutations with more-conventional CNVs, we estimate that segmental mutations larger than 1kb arise in about one per 22 human meioses. These methods are complementary to previous techniques in that they interrogate genomic regions that are home to segmental duplication, high CNV allele frequencies, and multi-allelic CNVs.Author SummaryCopy number variation is an important form of genetic variation in which individuals differ in the number of copies of segments of their genomes. Certain aspects of copy number variation have traditionally been difficult to study using short-read sequencing data. For example, standard analyses often cannot tell whether the duplicated copies of a segment are located near the original copy or are dispersed to other regions of the genome. Another aspect of copy number variation that has been difficult to study is the detection of mutations in the copy number of DNA segments passed down from parents to their children, particularly when the mutations affect genome segments which already display common copy number variation in the population. We develop an analytical approach to solving these problems when sequencing data is available for all members of families with at least two children. This method is based on determining the number of parental haplotypes the two siblings share at each location in their genome, and using that information to determine the possible inheritance patterns that might explain the copy numbers we observe in each family member. We show that dispersed duplications and mutations can be identified by looking for copy number variants that do not follow these expected inheritance patterns. We use this approach to determine the location of 95 common duplications which are dispersed to distant regions of the genome, and demonstrate that these duplications are linked to genetic variants that affect disease risk or gene expression levels. We also identify a set of copy number mutations not detected by previous analyses of sequencing data from a large cohort of families, and show that repetitive and complex regions of the genome undergo frequent mutations in copy number.

scholarly journals Multi-regional characterisation of renal cell carcinoma and microenvironment at single cell resolution

2021 ◽  
Author(s):  
Ruoyan Li ◽  
John R. Ferdinand ◽  
Kevin W. Loudon ◽  
Georgina S. Bowyer ◽  
Lira Mamanova ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Function ◽  
De Novo ◽  
Epithelial Mesenchymal Transition ◽  
Spatial Location ◽  
De Novo Mutation ◽  
Cellular Interactions ◽  
Sequencing Data ◽  
Mesenchymal Transition ◽  
Multiple Regions

Tumour behaviour is dependent on the oncogenic properties of cancer cells and their multi-cellular interactions. These dependencies were examined through 270,000 single cell transcriptomes and 100 micro-dissected whole exomes obtained from 12 patients with kidney tumours. Tissue was sampled from multiple regions of tumour core, tumour-normal interface, normal surrounding tissues, and peripheral blood. We found the principal spatial location of CD8+ T cell clonotypes largely defined exhaustion state, with clonotypic heterogeneity not explained by somatic intra-tumoural heterogeneity. De novo mutation calling from single cell RNA sequencing data allows us to lineage-trace and infer clonality of cells. We discovered six meta-programmes that distinguish tumour cell function. An epithelial-mesenchymal transition meta-programme, enriched at the tumour-normal interface appears modulated through macrophage expressed IL1B, potentially forming a therapeutic target.

scholarly journals De novo indels within introns contribute to ASD incidence

2017 ◽  
Author(s):  
Adriana Munoz ◽  
Boris Yamrom ◽  
Yoon-ha Lee ◽  
Peter Andrews ◽  
Steven Marks ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Target Genes ◽  
De Novo ◽  
Whole Genome Sequencing Data ◽  
P Value ◽  
Whole Genome ◽  
Sequencing Data ◽  
Control Sets ◽  
The Difference

AbstractCopy number profiling and whole-exome sequencing has allowed us to make remarkable progress in our understanding of the genetics of autism over the past ten years, but there are major aspects of the genetics that are unresolved. Through whole-genome sequencing, additional types of genetic variants can be observed. These variants are abundant and to know which are functional is challenging. We have analyzed whole-genome sequencing data from 510 of the Simons Simplex Collections quad families and focused our attention on intronic variants. Within the introns of 546 high-quality autism target genes, we identified 63 de novo indels in the affected and only 37 in the unaffected siblings. The difference of 26 events is significantly larger than expected (p-val = 0.01) and using reasonable extrapolation shows that de novo intronic indels can contribute to at least 10% of simplex autism. The significance increases if we restrict to the half of the autism targets that are intolerant to damaging variants in the normal human population, which half we expect to be even more enriched for autism genes. For these 273 targets we observe 43 and 20 events in affected and unaffected siblings, respectively (p-value of 0.005). There was no significant signal in the number of de novo intronic indels in any of the control sets of genes analyzed. We see no signal from de novo substitutions in the introns of target genes.

scholarly journals Harmonization of whole-genome sequencing for outbreak surveillance of Enterobacteriaceae and Enterococci

2021 ◽  
Vol 7 (7) ◽  
Author(s):  
Casper Jamin ◽  
Sien De Koster ◽  
Stefanie van Koeveringe ◽  
Dieter De Coninck ◽  
Klaas Mensaert ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Type Species ◽  
De Novo ◽  
Whole Genome ◽  
Data Generation ◽  
Sequencing Data ◽  
Content Type ◽  
Link Type ◽  
Antimicrobial Resistance Genes

Whole-genome sequencing (WGS) is becoming the de facto standard for bacterial typing and outbreak surveillance of resistant bacterial pathogens. However, interoperability for WGS of bacterial outbreaks is poorly understood. We hypothesized that harmonization of WGS for outbreak surveillance is achievable through the use of identical protocols for both data generation and data analysis. A set of 30 bacterial isolates, comprising of various species belonging to the Enterobacteriaceae family and Enterococcus genera, were selected and sequenced using the same protocol on the Illumina MiSeq platform in each individual centre. All generated sequencing data were analysed by one centre using BioNumerics (6.7.3) for (i) genotyping origin of replications and antimicrobial resistance genes, (ii) core-genome multi-locus sequence typing (cgMLST) for Escherichia coli and Klebsiella pneumoniae and whole-genome multi-locus sequencing typing (wgMLST) for all species. Additionally, a split k-mer analysis was performed to determine the number of SNPs between samples. A precision of 99.0% and an accuracy of 99.2% was achieved for genotyping. Based on cgMLST, a discrepant allele was called only in 2/27 and 3/15 comparisons between two genomes, for E. coli and K. pneumoniae, respectively. Based on wgMLST, the number of discrepant alleles ranged from 0 to 7 (average 1.6). For SNPs, this ranged from 0 to 11 SNPs (average 3.4). Furthermore, we demonstrate that using different de novo assemblers to analyse the same dataset introduces up to 150 SNPs, which surpasses most thresholds for bacterial outbreaks. This shows the importance of harmonization of data-processing surveillance of bacterial outbreaks. In summary, multi-centre WGS for bacterial surveillance is achievable, but only if protocols are harmonized.

scholarly journals Genome Wide Variant Analysis of Simplex Autism Families with an Integrative Clinical-Bioinformatics Pipeline

2015 ◽  
Author(s):  
Laura T Jiménez-Barrón ◽  
Jason A O'Rawe ◽  
Yiyang Wu ◽  
Margaret Yoon ◽  
Han Fang ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
De Novo ◽  
Autism Spectrum ◽  
Repetitive Behaviors ◽  
Whole Genome ◽  
Sequencing Data ◽  
Bioinformatics Pipeline ◽  
Bioinformatics Tools ◽  
Genome Wide

Autism spectrum disorders (ASD) are a group of developmental disabilities that affect social interaction, communication and are characterized by repetitive behaviors. There is now a large body of evidence that suggests a complex role of genetics in ASD, in which many different loci are involved. Although many current population scale genomic studies have been demonstrably fruitful, these studies generally focus on analyzing a limited part of the genome or use a limited set of bioinformatics tools. These limitations preclude the analysis of genome-wide perturbations that may contribute to the development and severity of ASD-related phenotypes. To overcome these limitations, we have developed and utilized an integrative clinical and bioinformatics pipeline for generating a more complete and reliable set of genomic variants for downstream analyses. Our study focuses on the analysis of three simplex autism families consisting of one affected child, unaffected parents, and one unaffected sibling. All members were clinically evaluated and widely phenotyped. Genotyping arrays and whole genome sequencing were performed on each member, and the resulting sequencing data were analyzed using a variety of available bioinformatics tools. We searched for rare variants of putative functional impact that were found to be segregating according to de-novo, autosomal recessive, x-linked, mitochondrial and compound heterozygote transmission models. The resulting candidate variants included three small heterozygous CNVs, a rare heterozygous de novo nonsense mutation in MYBBP1A located within exon 1, and a novel de novo missense variant in LAMB3. Our work demonstrates how more comprehensive analyses that include rich clinical data and whole genome sequencing data can generate reliable results for use in downstream investigations. We are moving to implement our framework for the analysis and study of larger cohorts of families, where statistical rigor can accompany genetic findings.

scholarly journals A benchmarking of human mitochondrial DNA haplogroup classifiers from whole-genome and whole-exome sequence data

2021 ◽  
Author(s):  
Víctor García-Olivares ◽  
Adrián Muñoz-Barrera ◽  
José Miguel Lorenzo-Salazar ◽  
Carlos Zaragoza-Trello ◽  
Luis A. Rubio-Rodríguez ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
De Novo ◽  
Sequence Data ◽  
Qualitative Assessment ◽  
Whole Genome ◽  
Third Generation ◽  
Sequencing Data ◽  
Short Read ◽  
Bioinformatic Tools ◽  
Whole Exome

AbstractThe mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short-read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

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