Archaic mitochondrial DNA inserts in modern day 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-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.

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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

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.

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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.

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eKLIPse: a sensitive tool for the detection and quantification of mitochondrial DNA deletions from next-generation sequencing data

Genetics in Medicine ◽

10.1038/s41436-018-0350-8 ◽

2018 ◽

Vol 21 (6) ◽

pp. 1407-1416 ◽

Cited By ~ 12

Author(s):

David Goudenège ◽

Celine Bris ◽

Virginie Hoffmann ◽

Valerie Desquiret-Dumas ◽

Claude Jardel ◽

...

Keyword(s):

Mitochondrial Dna ◽

Next Generation Sequencing ◽

Next Generation Sequencing Data ◽

Next Generation ◽

Sequencing Data ◽

Sensitive Tool ◽

Dna Deletions ◽

Generation Sequencing ◽

Detection And Quantification

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Model-based detection and analysis of introgressed Neanderthal ancestry in modern humans

10.1101/227660 ◽

2017 ◽

Author(s):

Matthias Steinrücken ◽

Jeffrey P. Spence ◽

John A. Kamm ◽

Emilia Wieczorek ◽

Yun S. Song

Keyword(s):

Genetic Material ◽

Genetic Load ◽

Modern Human ◽

Human Populations ◽

Effective Population ◽

Weak Selection ◽

Modern Humans ◽

High Coverage ◽

Model Based ◽

And Migration

AbstractGenetic evidence has revealed that the ancestors of modern human populations outside of Africa and their hominin sister groups, notably the Neanderthals, exchanged genetic material in the past. The distribution of these introgressed sequence-tracts along modern-day human genomes provides insight into the ancient structure and migration patterns of these archaic populations. Furthermore, it facilitates studying the selective processes that lead to the accumulation or depletion of introgressed genetic variation. Recent studies have developed methods to localize these introgressed regions, reporting long regions that are depleted of Neanderthal introgression and enriched in genes, suggesting negative selection against the Neanderthal variants. On the other hand, enriched Neanderthal ancestry in hair- and skin-related genes suggests that some introgressed variants facilitated adaptation to new environments. Here, we present a model-based method called diCal-admix and apply it to detect tracts of Neanderthal introgression in modern humans. We demonstrate its efficiency and accuracy through extensive simulations. We use our method to detect introgressed regions in modern human individuals from the 1000 Genomes Project, using a high coverage genome from a Neanderthal individual from the Altai mountains as reference. Our introgression detection results and findings concerning their functional implications are largely concordant with previous studies, and are consistent with weak selection against Neanderthal ancestry. We find some evidence that selection against Neanderthal ancestry was due to higher genetic load in Neanderthals, resulting from small effective population size, rather than Dobzhansky-Müller incompatibilities. Finally, we investigate the role of the X-chromosome in the divergence between Neanderthals and modern humans.

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Limits of long-term selection against Neandertal introgression

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1814338116 ◽

2019 ◽

Vol 116 (5) ◽

pp. 1639-1644 ◽

Cited By ~ 48

Author(s):

Martin Petr ◽

Svante Pääbo ◽

Janet Kelso ◽

Benjamin Vernot

Keyword(s):

Negative Selection ◽

Modern Human ◽

Model Parameters ◽

Human Populations ◽

Modern Humans ◽

High Coverage ◽

Protein Coding ◽

The Past ◽

Wide Range

Several studies have suggested that introgressed Neandertal DNA was subjected to negative selection in modern humans. A striking observation in support of this is an apparent monotonic decline in Neandertal ancestry observed in modern humans in Europe over the past 45,000 years. Here, we show that this decline is an artifact likely caused by gene flow between modern human populations, which is not taken into account by statistics previously used to estimate Neandertal ancestry. When we apply a statistic that avoids assumptions about modern human demography by taking advantage of two high-coverage Neandertal genomes, we find no evidence for a change in Neandertal ancestry in Europe over the past 45,000 years. We use whole-genome simulations of selection and introgression to investigate a wide range of model parameters and find that negative selection is not expected to cause a significant long-term decline in genome-wide Neandertal ancestry. Nevertheless, these models recapitulate previously observed signals of selection against Neandertal alleles, in particular the depletion of Neandertal ancestry in conserved genomic regions. Surprisingly, we find that this depletion is strongest in regulatory and conserved noncoding regions and in the most conserved portion of protein-coding sequences.

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A Simple Deep Learning Approach for Detecting Duplications and Deletions in Next-Generation Sequencing Data

10.1101/657361 ◽

2019 ◽

Author(s):

Tom Hill ◽

Robert L. Unckless

Keyword(s):

Machine Learning ◽

Next Generation Sequencing ◽

Copy Number Variants ◽

Difficult Problem ◽

Next Generation Sequencing Data ◽

Next Generation ◽

Sequencing Data ◽

High Coverage ◽

Long Read ◽

Generation Sequencing

AbstractCopy number variants (CNV) are associated with phenotypic variation in several species. However, properly detecting changes in copy numbers of sequences remains a difficult problem, especially in lower quality or lower coverage next-generation sequencing data. Here, inspired by recent applications of machine learning in genomics, we describe a method to detect duplications and deletions in short-read sequencing data. In low coverage data, machine learning appears to be more powerful in the detection of CNVs than the gold-standard methods or coverage estimation alone, and of equal power in high coverage data. We also demonstrate how replicating training sets allows a more precise detection of CNVs, even identifying novel CNVs in two genomes previously surveyed thoroughly for CNVs using long read data.Available at: https://github.com/tomh1lll/dudeml

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