Pilot Screening of Cell-Free mtDNA in NIPT: Quality Control, Variant Calling, and Haplogroup Determination.
Ontology highlight
ABSTRACT:
SUBMITTER: Morshneva A
PROVIDER: S-EPMC8156457 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:ObjectiveTo compare available analysis methods for determining fetal fraction on single read next generation sequencing data. This is important as the performance of non-invasive prenatal testing (NIPT) procedures depends on the fraction of fetal DNA.MethodsWe tested six different methods for the detection of fetal fraction in NIPT samples. The same clinically obtained data were used for all methods, allowing us to assess the effect of fetal fraction on the test result, and to investigate the use of fetal fraction for quality control.ResultsWe show that non-NIPT methods based on body mass index (BMI) and gestational age are unreliable predictors of fetal fraction, male pregnancy specific methods based on read counts on the Y chromosome perform consistently and the fetal sex-independent new methods SeqFF and SANEFALCON are less reliable but can be used to obtain a basic indication of fetal fraction in case of a female fetus.ConclusionWe recommend the use of a combination of methods to prevent the issue of reports on samples with insufficient fetal DNA; SANEFALCON to check for presence of fetal DNA, SeqFF for estimating the fetal fraction for a female pregnancy and any Y-based method for estimating the fetal fraction for a male pregnancy. © 2017 The Authors. Prenatal Diagnosis published by John Wiley & Sons, Ltd.
| S-EPMC5599991 | biostudies-literature
Project description:Recent advancements in sequencing technology have led to a drastic reduction in genome sequencing costs. This development has generated an unprecedented amount of data that must be stored, processed, and communicated. To facilitate this effort, compression of genomic files has been proposed. Specifically, lossy compression of quality scores is emerging as a natural candidate for reducing the growing costs of storage. A main goal of performing DNA sequencing in population studies and clinical settings is to identify genetic variation. Though the field agrees that smaller files are advantageous, the cost of lossy compression, in terms of variant discovery, is unclear.Bioinformatic algorithms to identify SNPs and INDELs use base quality score information; here, we evaluate the effect of lossy compression of quality scores on SNP and INDEL detection. Specifically, we investigate how the output of the variant caller when using the original data differs from that obtained when quality scores are replaced by those generated by a lossy compressor. Using gold standard genomic datasets and simulated data, we are able to analyze how accurate the output of the variant calling is, both for the original data and that previously lossily compressed. We show that lossy compression can significantly alleviate the storage while maintaining variant calling performance comparable to that with the original data. Further, in some cases lossy compression can lead to variant calling performance that is superior to that using the original file. We envisage our findings and framework serving as a benchmark in future development and analyses of lossy genomic data compressors.
| S-EPMC5862240 | biostudies-literature
Project description:MotivationThe standard protocol for detecting variation in DNA is to map millions of short sequence reads to a known reference and find loci that differ. While this approach works well, it cannot be applied where the sample contains dense variants or is too distant from known references. De novo assembly or hybrid methods can recover genomic variation, but the cost of computation is often much higher. We developed a novel k-mer algorithm and software implementation, Kestrel, capable of characterizing densely packed SNPs and large indels without mapping, assembly or de Bruijn graphs.ResultsWhen applied to mosaic penicillin binding protein (PBP) genes in Streptococcus pneumoniae, we found near perfect concordance with assembled contigs at a fraction of the CPU time. Multilocus sequence typing (MLST) with this approach was able to bypass de novo assemblies. Kestrel has a very low false-positive rate when applied to the whole genome, and while Kestrel identified many variants missed by other methods, limitations of a purely k-mer based approach affect overall sensitivity.Availability and implementationSource code and documentation for a Java implementation of Kestrel can be found at https://github.com/paudano/kestrel. All test code for this publication is located at https://github.com/paudano/kescases.Contactpaudano@gatech.edu or fredrik.vannberg@biology.gatech.edu.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC5946877 | biostudies-literature
Project description:BACKGROUND: Human genetic diversity observed in Indian subcontinent is second only to that of Africa. This implies an early settlement and demographic growth soon after the first 'Out-of-Africa' dispersal of anatomically modern humans in Late Pleistocene. In contrast to this perspective, linguistic diversity in India has been thought to derive from more recent population movements and episodes of contact. With the exception of Dravidian, which origin and relatedness to other language phyla is obscure, all the language families in India can be linked to language families spoken in different regions of Eurasia. Mitochondrial DNA and Y chromosome evidence has supported largely local evolution of the genetic lineages of the majority of Dravidian and Indo-European speaking populations, but there is no consensus yet on the question of whether the Munda (Austro-Asiatic) speaking populations originated in India or derive from a relatively recent migration from further East. RESULTS: Here, we report the analysis of 35 novel complete mtDNA sequences from India which refine the structure of Indian-specific varieties of haplogroup R. Detailed analysis of haplogroup R7, coupled with a survey of approximately 12,000 mtDNAs from caste and tribal groups over the entire Indian subcontinent, reveals that one of its more recently derived branches (R7a1), is particularly frequent among Munda-speaking tribal groups. This branch is nested within diverse R7 lineages found among Dravidian and Indo-European speakers of India. We have inferred from this that a subset of Munda-speaking groups have acquired R7 relatively recently. Furthermore, we find that the distribution of R7a1 within the Munda-speakers is largely restricted to one of the sub-branches (Kherwari) of northern Munda languages. This evidence does not support the hypothesis that the Austro-Asiatic speakers are the primary source of the R7 variation. Statistical analyses suggest a significant correlation between genetic variation and geography, rather than between genes and languages. CONCLUSION: Our high-resolution phylogeographic study, involving diverse linguistic groups in India, suggests that the high frequency of mtDNA haplogroup R7 among Munda speaking populations of India can be explained best by gene flow from linguistically different populations of Indian subcontinent. The conclusion is based on the observation that among Indo-Europeans, and particularly in Dravidians, the haplogroup is, despite its lower frequency, phylogenetically more divergent, while among the Munda speakers only one sub-clade of R7, i.e. R7a1, can be observed. It is noteworthy that though R7 is autochthonous to India, and arises from the root of hg R, its distribution and phylogeography in India is not uniform. This suggests the more ancient establishment of an autochthonous matrilineal genetic structure, and that isolation in the Pleistocene, lineage loss through drift, and endogamy of prehistoric and historic groups have greatly inhibited genetic homogenization and geographical uniformity.
| S-EPMC2529308 | biostudies-literature
Project description: Not available
| S-EPMC2841866 | biostudies-literature
Project description:Despite a multitude of methods for the sample preparation, sequencing, and data analysis of mitochondrial DNA (mtDNA), the demand for innovation remains, particularly in comparison with nuclear DNA (nDNA) research. The Applied Biosystems™ Precision ID mtDNA Whole Genome Panel (Thermo Fisher Scientific, USA) is an innovative library preparation kit suitable for degraded samples and low DNA input. However, its bioinformatic processing occurs in the enterprise Ion Torrent Suite™ Software (TSS), yielding BAM files aligned to an unorthodox version of the revised Cambridge Reference Sequence (rCRS), with a heteroplasmy threshold level of 10%. Here, we present an alternative customizable pipeline, the PrecisionCallerPipeline (PCP), for processing samples with the correct rCRS output after Ion Torrent sequencing with the Precision ID library kit. Using 18 samples (3 original samples and 15 mixtures) derived from the 1000 Genomes Project, we achieved overall improved performance metrics in comparison with the proprietary TSS, with optimal performance at a 2.5% heteroplasmy threshold. We further validated our findings with 50 samples from an ongoing independent cohort of stroke patients, with PCP finding 98.31% of TSS's variants (TSS found 57.92% of PCP's variants), with a significant correlation between the variant levels of variants found with both pipelines.
| S-EPMC8584537 | biostudies-literature
Project description:BACKGROUND:Although our microbial community and genomes (the human microbiome) outnumber our genome by several orders of magnitude, to what extent the human host genetic complement informs the microbiota composition is not clear. The Human Microbiome Project (HMP) Consortium established a unique population-scale framework with which to characterize the relationship of microbial community structure with their human hosts. A wide variety of taxa and metabolic pathways have been shown to be differentially distributed by virtue of race/ethnicity in the HMP. Given that mtDNA haplogroups are the maternally derived ancestral genomic markers and mitochondria's role as the generator for cellular ATP, characterizing the relationship between human mtDNA genomic variants and microbiome profiles becomes of potential marked biologic and clinical interest. RESULTS:We leveraged sequencing data from the HMP to investigate the association between microbiome community structures with its own host mtDNA variants. 15 haplogroups and 631 mtDNA nucleotide polymorphisms (mean sequencing depth of 280X on the mitochondria genome) from 89 individuals participating in the HMP were accurately identified. 16S rRNA (V3-V5 region) sequencing generated microbiome taxonomy profiles and whole genome shotgun sequencing generated metabolic profiles from various body sites were treated as traits to conduct association analysis between haplogroups and host clinical metadata through linear regression. The mtSNPs of individuals with European haplogroups were associated with microbiome profiles using PLINK quantitative trait associations with permutation and adjusted for multiple comparisons. We observe that among 139 stool and 59 vaginal posterior fornix samples, several haplogroups show significant association with specific microbiota (q-value < 0.05) as well as their aggregate community structure (Chi-square with Monte Carlo, p < 0.005), which confirmed and expanded previous research on the association of race and ethnicity with microbiome profile. Our results further indicate that mtDNA variations may render different microbiome profiles, possibly through an inflammatory response to different levels of reactive oxygen species activity. CONCLUSIONS:These data provide initial evidence for the association between host ancestral genome with the structure of its microbiome.
| S-EPMC4234434 | biostudies-literature
Project description:Current mitochondrial DNA (mtDNA) haplogroup classification tools map reads to a single reference genome and perform inference based on the detected mutations to this reference. This approach biases haplogroup assignments towards the reference and prohibits accurate calculations of the uncertainty in assignment. We present HaploCart, a probabilistic mtDNA haplogroup classifier which uses a pangenomic reference graph framework together with principles of Bayesian inference. We demonstrate that our approach significantly outperforms available tools by being more robust to lower coverage or incomplete consensus sequences and producing phylogenetically-aware confidence scores that are unbiased towards any haplogroup. HaploCart is available both as a command-line tool and through a user-friendly web interface. The C++ program accepts as input consensus FASTA, FASTQ, or GAM files, and outputs a text file with the haplogroup assignments of the samples along with the level of confidence in the assignments. Our work considerably reduces the amount of data required to obtain a confident mitochondrial haplogroup assignment.
| S-EPMC10281577 | biostudies-literature
Project description:BackgroundFor large scale studies aiming at a better understanding of mitochondrial DNA (mtDNA), sequence variation in particular mt haplogroups (hgs) and population structure, reliable low-cost high-throughput genotyping assays are needed. Furthermore, methods facilitating sensitive mixture detection and relative quantification of allele proportions are indispensable for the study of heteroplasmy, mitochondrial sequence evolution, and mitochondrial disorders. Here the properties of a homogeneous competitive duplex allele specific PCR (ARMS) assay were scrutinized in the light of these requirements.Methodology/principal findingsA duplex ARMS assay amplifying either the ancestral mtDNA 2706G allele (non-hg H samples) or the derived 7028C allele (hg H samples) in the presence of SYBR Green fluorescent reporter dye was developed and characterized. Product detection, allele calling, and hg inference were based on the amplicon-characteristic melting-point temperatures obtained with on-line post-PCR fluorescent dissociation curve analysis (DCA). The analytical window of the assay covered at least 5 orders of magnitude of template DNA input with a detection limit in the low picogram range of genomic DNA. A set of forensically relevant test specimens was analyzed successfully. The presence of mtDNA mixtures was detected over a broad range of input DNA amounts and mixture ratios, and the estimation of allele proportions in samples with known total mtDNA content was feasible with limitations. A qualified DNA analyst successfully analyzed approximately 2,200 DNA extracts within three regular working days, without using robotic lab-equipment. By performing the amplification on-line, the assay also facilitated absolute mtDNA quantification.ConclusionsAlthough this assay was developed just for a particular purpose, the approach is general in that it is potentially suitable in a broad variety of assay-layouts for many other applications, including the analysis of mixtures. Homogeneous ARMS-DCA is a valuable tool for large-volume studies targeting small numbers of single nucleotide polymorphisms (SNPs).
| S-EPMC2793010 | biostudies-literature
Project description:Multiplexed Sequencing of Expression Cassette Expressing Human OTC in Yeast
| PRJEB60279 | ENA