A Macaque's-Eye View of Human Insertions and Deletions: Differences in Mechanisms

Kvikstad, Erika; Tyekucheva, Svitlana; Chiaromonte, Francesca; Makova, Kateryna D.

doi:10.1371/journal.pcbi.0030176

Cited by 56 publications

(79 citation statements)

References 56 publications

(113 reference statements)

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“…Reduced replication errors might be the main factor in explaining the extremely cold nature of this state. In fact, in agreement with previous studies (24,38), male-to-female divergence ratios (39) Moreover, the cold X-chromosomal state has low GC content (38.9%) and, in males, does not recombine outside of pseudoautosomal regions, which were excluded from our analysis; these characteristics, too, may contribute to its lower divergence compared with the cold autosomal state (Fig. 2B).…”

Section: Resultssupporting

confidence: 92%

“…Notably, insertionwarm and hot states have enhanced female and male recombination rates, respectively (Fig. 2B)-which corroborates a specific association of female recombination with insertions (38).…”

Section: Resultssupporting

confidence: 73%

“…Compared with the insertion-warm state, this state (Fig. 2B and Table 2) lacks the hallmarks of functional activity and has GC content close to genome median (38.6%) as well as depressed male and especially female recombination (1.066 cM/Mb vs. 1.631 cM/Mb in the insertion-warm state)-which may explain its particularly large drop in insertions (38).…”

Section: Resultsmentioning

confidence: 99%

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Segmenting the human genome based on states of neutral genetic divergence

Don¹,

Ananda

Chiaromonte³

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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Many studies have demonstrated that divergence levels generated by different mutation types vary and covary across the human genome. To improve our still-incomplete understanding of the mechanistic basis of this phenomenon, we analyze several mutation types simultaneously, anchoring their variation to specific regions of the genome. Using hidden Markov models on insertion, deletion, nucleotide substitution, and microsatellite divergence estimates inferred from human-orangutan alignments of neutrally evolving genomic sequences, we segment the human genome into regions corresponding to different divergence states-each uniquely characterized by specific combinations of divergence levels. We then parsed the mutagenic contributions of various biochemical processes associating divergence states with a broad range of genomic landscape features. We find that high divergence states inhabit guanine-and cytosine (GC)-rich, highly recombining subtelomeric regions; low divergence states cover inner parts of autosomes; chromosome X forms its own state with lowest divergence; and a state of elevated microsatellite mutability is interspersed across the genome. These general trends are mirrored in human diversity data from the 1000 Genomes Project, and departures from them highlight the evolutionary history of primate chromosomes. We also find that genes and noncoding functional marks [annotations from the Encyclopedia of DNA Elements (ENCODE)] are concentrated in high divergence states. Our results provide a powerful tool for biomedical data analysis: segmentations can be used to screen personal genome variants-including those associated with cancer and other diseases-and to improve computational predictions of noncoding functional elements. W hole-genome sequencing studies have demonstrated that divergence estimates for several mutation types (e.g., nucleotide substitutions, insertions, and deletions) vary substantially across the human genome. This phenomenon has been studied at various genomic scales and evolutionary distances (reviewed in ref. 1), and-whereas initially of interest solely to evolutionary biologists-is now entering the purview of main biomedical research. Specifically, human population (e.g., ref.2) and cancer (3, 4) genome resequencing projects have revealed that incidences of single nucleotide polymorphisms (SNPs), insertions and deletions (indels), and copy number variants (CNVs) vary across the genome. Divergence estimates for different mutation types also covary across the genome (5, 6)-e.g., substitution rates increase in regions with high indel rates (7)-suggesting that regional variation is an important and general characteristic of mutations.Variation in divergence is often linked to genomic landscape features such as base composition, replication timing, and recombination rates (1). For instance, nucleotide substitution rates are elevated in late-replicating regions because of an accumulation of single-stranded DNA susceptible to endogenous damage (8) and are affected by chromatin structure (9) and ...

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Section: Resultssupporting

confidence: 92%

Section: Resultssupporting

confidence: 73%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Segmenting the human genome based on states of neutral genetic divergence

Don¹,

Ananda

Chiaromonte³

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

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“…Finally, for each species, we performed multiple regression analyses to model variability in each TE subfamily density (response) depending on genomic landscape features (predictors) that reflect particular mechanisms of TE integration preferences and accumulation over evolutionary time (see introduction and Methods; Table 1; Supplemental Table S2); however, we acknowledge the possibility that some of the predictors might be associated with multiple mechanisms. The relative contribution to variability explained (RCVE) (Kvikstad et al 2007) was used to detect the relative predictive power of each predictor in each full model, when in the context of all other predictors (for details, see Methods). Initially we applied this framework to repeat densities in the human genome, not separating windows by location on Y, X, and autosomes.…”

Section: Multiple Regression Analysesmentioning

confidence: 99%

The (r)evolution of SINE versus LINE distributions in primate genomes: Sex chromosomes are important

Kvikstad¹,

Makova²

2010

Genome Res.

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The densities of transposable elements (TEs) in the human genome display substantial variation both within individual chromosomes and among chromosome types (autosomes and the two sex chromosomes). Finding an explanation for this variability has been challenging, especially in light of genome landscapes unique to the sex chromosomes. Here, using a multiple regression framework, we investigate primate Alu and L1 densities shaped by regional genome features and location on a particular chromosome type. As a result of our analysis, first, we build statistical models explaining up to 79% and 44% of variation in Alu and L1 element density, respectively. Second, we analyze sex chromosome versus autosome TE densities corrected for regional genomic effects. We discover that sex-chromosome bias in Alu and L1 distributions not only persists after accounting for these effects, but even presents differences in patterns, confirming preferential Alu integration in the male germline, yet likely integration of L1s in both male and female germlines or in early embryogenesis. Additionally, our models reveal that local base composition (measured by GC content and density of L1 target sites) and natural selection (inferred via density of most conserved elements) are significant to predicting densities of L1s. Interestingly, measurements of local double-stranded breaks (a 13-mer associated with genome instability) strongly correlate with densities of Alu elements; little evidence was found for the role of recombination-driven deletion in driving TE distributions over evolutionary time. Thus, Alu and L1 densities have been influenced by the combination of distinct local genome landscapes and the unique evolutionary dynamics of sex chromosomes.

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“…They are generally located in noncoding regions and have an important application in phylogenetic analyses of human populations. 35,36 Compared to SNPs, rates of indel mutagenesis are known to be variable across the genome, 37 with high rates in microsatellites. 38 Polymerase slippage across the genome is thought to be responsible for the large majority of indel mutations 10 There may be general hotspots of natural genetic variation where both SNPs and INDELs make their effect.…”

Section: Indelsmentioning

confidence: 99%

Magnitude of Human Genetic Variations: A Mini Review

2017

International Journal of Research Studies in Medical and Health

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Genetic variations are the genetic differences found among individuals of the same species. These variations are adaptive i.e. they ensure flexibility and survival of a population in the changing environment over time. It is quite interesting to know how and when these genetic variations offer to a population the survival benefit under the altered situations and at what extent over time. Whether there is any significant difference among male and female in expression of such variations. Further if the population subgroups and demographical factors offer any selective advantage to these variations. Moreover we often find that one drug which is effective on an individual may not work well with other individual. This interindividual variation of drug effects is due to the genetic variation of drug metabolism. The variations of xenobiotic or drug metabolizing enzymes at genetic level bring about the evolution of diverse and specific subgroups in the population that offers a selective ability to perform the biotransformation reactions. With the advent of advance DNA sequencing technologies we are now able to find and characterize most of the natural variations such as single nucleotide polymorphisms, structural variations like insertion/deletion, inversion, translocations, tandem repeat polymorphism, complex chromosomal rearrangements etc. that are linked with human evolution, migration, disease susceptibility, adaptation to divers geographical regions etc. This mini review focus on basic genetic variations and their possible associations with human health, forensics, environmental stress management, various diseases and other relevant aspects.

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A Macaque's-Eye View of Human Insertions and Deletions: Differences in Mechanisms

Cited by 56 publications

References 56 publications

Segmenting the human genome based on states of neutral genetic divergence

Segmenting the human genome based on states of neutral genetic divergence

The (r)evolution of SINE versus LINE distributions in primate genomes: Sex chromosomes are important

Magnitude of Human Genetic Variations: A Mini Review

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