Dating genomic variants and shared ancestry in population-scale sequencing data

AbstractThe origin and fate of new mutations within species is the fundamental process underlying evolution. However, while much attention has been focused on characterizing the presence, frequency, and phenotypic impact of genetic variation, the evolutionary histories of most variants are largely unexplored. We have developed a non-parametric approach for estimating the date of origin of genetic variants in large-scale sequencing data sets. The accuracy and robustness of the approach is demonstrated through simulation. Using data from two publicly available human genomic diversity resources, we estimated the age of more than 45 million single nucleotide polymorphisms (SNPs) in the human genome and release the Atlas of Variant Age as a public online database. We characterize the relationship between variant age and frequency in different geographical regions, and demonstrate the value of age information in interpreting variants of functional and selective importance. Finally, we use allele age estimates to power a rapid approach for inferring the ancestry shared between individual genomes, to quantify genealogical relationships at different points in the past, as well as describe and explore the evolutionary history of modern human populations.

Download Full-text

Mining SNPs From EST Databases

Genome Research ◽

10.1101/gr.9.2.167 ◽

1999 ◽

Vol 9 (2) ◽

pp. 167-174 ◽

Cited By ~ 12

Author(s):

Leslie Picoult-Newberg ◽

Trey E. Ideker ◽

Mark G. Pohl ◽

Scott L. Taylor ◽

Miriam A. Donaldson ◽

...

Keyword(s):

Expressed Sequence Tag ◽

De Novo ◽

Cdna Libraries ◽

Human Populations ◽

Data Sets ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Genome Wide ◽

Using Data

There is considerable interest in the discovery and characterization of single nucleotide polymorphisms (SNPs) to enable the analysis of the potential relationships between human genotype and phenotype. Here we present a strategy that permits the rapid discovery of SNPs from publicly available expressed sequence tag (EST) databases. From a set of ESTs derived from 19 different cDNA libraries, we assembled 300,000 distinct sequences and identified 850 mismatches from contiguous EST data sets (candidate SNP sites), without de novo sequencing. Through a polymerase-mediated, single-base, primer extension technique, Genetic Bit Analysis (GBA), we confirmed the presence of a subset of these candidate SNP sites and have estimated the allele frequencies in three human populations with different ethnic origins. Altogether, our approach provides a basis for rapid and efficient regional and genome-wide SNP discovery using data assembled from sequences from different libraries of cDNAs.[The SNPs identified in this study can be found in the National Center of Biotechnology (NCBI) SNP database under submitter handles ORCHID (SNPS-981210-A) and debnick (SNPS-981209-A and SNPS-981209-B).]

Download Full-text

Archaic mitochondrial DNA inserts in modern day nuclear genomes

BMC Genomics ◽

10.1186/s12864-019-6392-8 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 2

Author(s):

Robert Bücking ◽

Murray P Cox ◽

Georgi Hudjashov ◽

Lauri Saag ◽

Herawati Sudoyo ◽

...

Keyword(s):

Mitochondrial Dna ◽

Nuclear Dna ◽

Modern Human ◽

Sub Saharan Africa ◽

Next Generation Sequencing Data ◽

Human Populations ◽

Sequencing Data ◽

Modern Humans ◽

High Coverage ◽

Nuclear Genomes

Abstract Background Traces of interbreeding of Neanderthals and Denisovans with modern humans in the form of archaic DNA have been detected in the genomes of present-day human populations outside sub-Saharan Africa. Up to now, only nuclear archaic DNA has been detected in modern humans; we therefore attempted to identify archaic mitochondrial DNA (mtDNA) residing in modern human nuclear genomes as nuclear inserts of mitochondrial DNA (NUMTs). Results We analysed 221 high-coverage genomes from Oceania and Indonesia using an approach which identifies reads that map both to the nuclear and mitochondrial DNA. We then classified reads according to the source of the mtDNA, and found one NUMT of Denisovan mtDNA origin, present in 15 analysed genomes; analysis of the flanking region suggests that this insertion is more likely to have happened in a Denisovan individual and introgressed into modern humans with the Denisovan nuclear DNA, rather than in a descendant of a Denisovan female and a modern human male. Conclusions Here we present our pipeline for detecting introgressed NUMTs in next generation sequencing data that can be used on genomes sequenced in the future. Further discovery of such archaic NUMTs in modern humans can be used to detect interbreeding between archaic and modern humans and can reveal new insights into the nature of such interbreeding events.

Download Full-text

ASCOT identifies key regulators of neuronal subtype-specific splicing

Nature Communications ◽

10.1038/s41467-019-14020-5 ◽

2020 ◽

Vol 11 (1) ◽

Cited By ~ 2

Author(s):

Jonathan P. Ling ◽

Christopher Wilks ◽

Rone Charles ◽

Patrick J. Leavey ◽

Devlina Ghosh ◽

...

Keyword(s):

Rna Splicing ◽

Large Scale ◽

Splice Variants ◽

Next Generation Sequencing Data ◽

Data Sets ◽

Cell Type ◽

Sequencing Data ◽

Large Scale Analysis ◽

Cell Type Specific ◽

Public Archives

AbstractPublic archives of next-generation sequencing data are growing exponentially, but the difficulty of marshaling this data has led to its underutilization by scientists. Here, we present ASCOT, a resource that uses annotation-free methods to rapidly analyze and visualize splice variants across tens of thousands of bulk and single-cell data sets in the public archive. To demonstrate the utility of ASCOT, we identify novel cell type-specific alternative exons across the nervous system and leverage ENCODE and GTEx data sets to study the unique splicing of photoreceptors. We find that PTBP1 knockdown and MSI1 and PCBP2 overexpression are sufficient to activate many photoreceptor-specific exons in HepG2 liver cancer cells. This work demonstrates how large-scale analysis of public RNA-Seq data sets can yield key insights into cell type-specific control of RNA splicing and underscores the importance of considering both annotated and unannotated splicing events.

Download Full-text

Assessing Study Reproducibility through M2RI: A Novel Approach for Large-scale High-throughput Association Studies

10.1101/2020.08.18.253740 ◽

2020 ◽

Author(s):

Zeyu Jiao ◽

Yinglei Lai ◽

Jujiao Kang ◽

Weikang Gong ◽

Liang Ma ◽

...

Keyword(s):

Sample Size ◽

Rna Sequencing ◽

High Throughput ◽

Large Scale ◽

Association Studies ◽

Structural Mri ◽

Data Sets ◽

Sequencing Data ◽

Novel Approach ◽

Magnetic Resonance Imaging Mri

AbstractHigh-throughput technologies, such as magnetic resonance imaging (MRI) and DNA/RNA sequencing (DNA-seq/RNA-seq), have been increasingly used in large-scale association studies. With these technologies, important biomedical research findings have been generated. The reproducibility of these findings, especially from structural MRI (sMRI) and functional MRI (fMRI) association studies, has recently been questioned. There is an urgent demand for a reliable overall reproducibility assessment for large-scale high-throughput association studies. It is also desirable to understand the relationship between study reproducibility and sample size in an experimental design. In this study, we developed a novel approach: the mixture model reproducibility index (M2RI) for assessing study reproducibility of large-scale association studies. With M2RI, we performed study reproducibility analysis for several recent large sMRI/fMRI data sets. The advantages of our approach were clearly demonstrated, and the sample size requirements for different phenotypes were also clearly demonstrated, especially when compared to the Dice coefficient (DC). We applied M2RI to compare two MRI or RNA sequencing data sets. The reproducibility assessment results were consistent with our expectations. In summary, M2RI is a novel and useful approach for assessing study reproducibility, calculating sample sizes and evaluating the similarity between two closely related studies.

Download Full-text

Archaic mitochondrial DNA inserts in modern day nuclear genomes

10.21203/rs.2.14881/v3 ◽

2019 ◽

Author(s):

Robert Bücking ◽

Murray P Cox ◽

Georgi Hudjashov ◽

Lauri Saag ◽

Herawati Sudoyo ◽

...

Keyword(s):

Mitochondrial Dna ◽

Nuclear Dna ◽

Modern Human ◽

Next Generation Sequencing Data ◽

Human Populations ◽

Sequencing Data ◽

Modern Humans ◽

High Coverage ◽

Nuclear Genomes ◽

Generation Sequencing

Abstract Background: Traces of interbreeding of Neanderthals and Denisovans with modern humans in the form of archaic DNA have been detected in the genomes of present-day human populations outside sub-Sahara Africa. Up to now, only nuclear archaic DNA has been detected in modern humans; we therefore attempted to identify archaic mitochondrial DNA (mtDNA) residing in modern human nuclear genomes as nuclear inserts of mitochondrial DNA (NUMTs). Results: We analysed 221 high-coverage genomes from Oceania and Indonesia using an approach which identifies reads that map both to the nuclear and mitochondrial DNA. We then classified reads according to the source of the mtDNA, and found one NUMT of Denisovan mtDNA origin; analysis of the flanking region suggests that this insertion is more likely to have happened in a Denisovan individual and introgressed into modern humans with the Denisovan nuclear DNA, rather than in a descendant of a Denisovan female and a modern human male. Conclusions: Here we present our pipeline for detecting introgressed NUMTs in next generation sequencing data that can be used on genomes sequenced in the future. Further discovery of such archaic NUMTs in modern humans can be used to detect interbreeding between archaic and modern humans and can reveal new insights into the nature of such interbreeding events.

Download Full-text

Efficient approaches for large scale GWAS studies with genotype uncertainty

10.1101/786384 ◽

2019 ◽

Author(s):

Emil Jørsboe ◽

Anders Albrechtsen

Keyword(s):

Population Structure ◽

Allele Frequency ◽

Statistical Power ◽

Large Scale ◽

Association Studies ◽

Genetic Data ◽

Data Sets ◽

Sequencing Data ◽

The Individual ◽

Genotype Probabilities

1AbstractIntroductionAssociation studies using genetic data from SNP-chip based imputation or low depth sequencing data provide a cost efficient design for large scale studies. However, these approaches provide genetic data with uncertainty of the observed genotypes. Here we explore association methods that can be applied to data where the genotype is not directly observed. We investigate how using different priors when estimating genotype probabilities affects the association results in different scenarios such as studies with population structure and varying depth sequencing data. We also suggest a method (ANGSD-asso) that is computational feasible for analysing large scale low depth sequencing data sets, such as can be generated by the non-invasive prenatal testing (NIPT) with low-pass sequencing.MethodsANGSD-asso’s EM model works by modelling the unobserved genotype as a latent variable in a generalised linear model framework. The software is implemented in C/C++ and can be run multi-threaded enabling the analysis of big data sets. ANGSD-asso is based on genotype probabilities, they can be estimated in various ways, such as using the sample allele frequency as a prior, using the individual allele frequencies as a prior or using haplotype frequencies from haplotype imputation. Using simulations of sequencing data we explore how genotype probability based method compares to using genetic dosages in large association studies with genotype uncertainty.Results & DiscussionOur simulations show that in a structured population using the individual allele frequency prior has better power than the sample allele frequency. If there is a correlation between genotype uncertainty and phenotype, then the individual allele frequency prior also helps control the false positive rate. In the absence of population structure the sample allele frequency prior and the individual allele frequency prior perform similarly. In scenarios with sequencing depth and phenotype correlation ANGSD-asso’s EM model has better statistical power and less bias compared to using dosages. Lastly when adding additional covariates to the linear model ANGSD-asso’s EM model has more statistical power and provides less biased effect sizes than other methods that accommodate genotype uncertainly, while also being much faster. This makes it possible to properly account for genotype uncertainty in large scale association studies.

Download Full-text

Archaic mitochondrial DNA inserts in modern day nuclear genomes

10.21203/rs.2.14881/v1 ◽

2019 ◽

Author(s):

Robert Bücking ◽

Murray P Cox ◽

Georgi Hudjashov ◽

Lauri Saag ◽

Herawati Sudoyo ◽

...

Keyword(s):

Mitochondrial Dna ◽

Nuclear Dna ◽

Modern Human ◽

Next Generation Sequencing Data ◽

Human Populations ◽

Sequencing Data ◽

Modern Humans ◽

High Coverage ◽

Nuclear Genomes ◽

Generation Sequencing

Abstract Background Traces of interbreeding of Neanderthals and Denisovans with modern humans in the form of archaic DNA have been detected in the genomes of present-day human populations outside sub-Sahara Africa. Up to now, only nuclear archaic DNA has been detected in modern humans; we therefore attempted to identify archaic mitochondrial DNA (mtDNA) residing in modern human nuclear genomes as nuclear inserts of mitochondrial DNA (NUMTs). Results We analysed 221 high-coverage genomes from Oceania and Indonesia using an approach which identifies reads that map both to the nuclear and mitochondrial DNA. We then classified reads according to the source of the mtDNA, and found one NUMT of Denisovan mtDNA origin; analysis of the flanking region suggests that this insertion is more likely to have happened in a Denisovan individual and introgressed into modern humans with the Denisovan nuclear DNA, rather than in a descendant of a Denisovan female and a modern human male. Conclusions Here we present our pipeline for detecting introgressed NUMTs in next generation sequencing data that can be used on genomes sequenced in the future. Further discovery of such archaic NUMTs in modern humans can be used to detect interbreeding between archaic and modern humans and can reveal new insights into the nature of such interbreeding events.

Download Full-text

Rapid inference of direct interactions in large-scale ecological networks from heterogeneous microbial sequencing data

10.1101/390195 ◽

2018 ◽

Cited By ~ 4

Author(s):

Janko Tackmann ◽

João Frederico Matias Rodrigues ◽

Christian von Mering

Keyword(s):

Graphical Models ◽

Large Scale ◽

Study Data ◽

Microbial Interactions ◽

Data Sets ◽

Metagenomic Sequencing ◽

Sequencing Data ◽

Human Gut ◽

Data Set ◽

Seamless Integration

AbstractThe recent explosion of metagenomic sequencing data opens the door towards the modeling of microbial ecosystems in unprecedented detail. In particular, co-occurrence based prediction of ecological interactions could strongly benefit from this development. However, current methods fall short on several fronts: univariate tools do not distinguish between direct and indirect interactions, resulting in excessive false positives, while approaches with better resolution are so far computationally highly limited. Furthermore, confounding variables typical for cross-study data sets are rarely addressed. We present FlashWeave, a new approach based on a flexible Probabilistic Graphical Models framework to infer highly resolved direct microbial interactions from massive heterogeneous microbial abundance data sets with seamless integration of metadata. On a variety of benchmarks, FlashWeave outperforms state-of-the-art methods by several orders of magnitude in terms of speed while generally providing increased accuracy. We apply FlashWeave to a cross-study data set of 69 818 publicly available human gut samples, resulting in one of the largest and most diverse models of microbial interactions in the human gut to date.

Download Full-text

Archaic mitochondrial DNA inserts in modern day nuclear genomes

10.21203/rs.2.14881/v2 ◽

2019 ◽

Author(s):

Robert Bücking ◽

Murray P Cox ◽

Georgi Hudjashov ◽

Lauri Saag ◽

Herawati Sudoyo ◽

...

Keyword(s):

Mitochondrial Dna ◽

Nuclear Dna ◽

Modern Human ◽

Next Generation Sequencing Data ◽

Human Populations ◽

Sequencing Data ◽

Modern Humans ◽

High Coverage ◽

Nuclear Genomes ◽

Generation Sequencing

Download Full-text

Large-Scale Metagenome Assembly Reveals Novel Animal-Associated Microbial Genomes, Biosynthetic Gene Clusters, and Other Genetic Diversity

mSystems ◽

10.1128/msystems.01045-20 ◽

2020 ◽

Vol 5 (6) ◽

Author(s):

Nicholas D. Youngblut ◽

Jacobo de la Cuesta-Zuluaga ◽

Georg H. Reischer ◽

Silke Dauser ◽

Nathalie Schuster ◽

...

Keyword(s):

Large Scale ◽

Animal Species ◽

Gene Clusters ◽

Genomic Diversity ◽

Data Sets ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Microbial Genomes ◽

Metagenome Assembly ◽

Gut Metagenome

ABSTRACT Large-scale metagenome assemblies of human microbiomes have produced a vast catalogue of previously unseen microbial genomes; however, comparatively few microbial genomes derive from other vertebrates. Here, we generated 5,596 metagenome-assembled genomes (MAGs) from the gut metagenomes of 180 predominantly wild animal species representing 5 classes, in addition to 14 existing animal gut metagenome data sets. The MAGs comprised 1,522 species-level genome bins (SGBs), most of which were novel at the species, genus, or family level, and the majority were enriched in host versus environment metagenomes. Many traits distinguished SGBs enriched in host or environmental biomes, including the number of antimicrobial resistance genes. We identified 1,986 diverse biosynthetic gene clusters; only 23 clustered with any MIBiG database references. Gene-based assembly revealed tremendous gene diversity, much of it host or environment specific. Our MAG and gene data sets greatly expand the microbial genome repertoire and provide a broad view of microbial adaptations to the vertebrate gut. IMPORTANCE Microbiome studies on a select few mammalian species (e.g., humans, mice, and cattle) have revealed a great deal of novel genomic diversity in the gut microbiome. However, little is known of the microbial diversity in the gut of other vertebrates. We studied the gut microbiomes of a large set of mostly wild animal species consisting of mammals, birds, reptiles, amphibians, and fish. Unfortunately, we found that existing reference databases commonly used for metagenomic analyses failed to capture the microbiome diversity among vertebrates. To increase database representation, we applied advanced metagenome assembly methods to our animal gut data and to many public gut metagenome data sets that had not been used to obtain microbial genomes. Our resulting genome and gene cluster collections comprised a great deal of novel taxonomic and genomic diversity, which we extensively characterized. Our findings substantially expand what is known of microbial genomic diversity in the vertebrate gut.

Download Full-text