scholarly journals Differential base-sharing between humans and Neanderthals: inter-breeding or greater mutability in heterozygotes?

2019 ◽  
Author(s):  
William Amos

AbstractThe idea that humans interbred with other Hominins, most notably Neanderthals, is now accepted as fact. The finding of hybrid skeletons shows that fertile matings did occur. However, inferences about the size of the resulting legacy assume that back-mutations are rare enough to be ignored and that mutation rate does not vary. In reality, back-mutations are common, mutation rate does vary between populations and there is mounting evidence that heterozygosity and mutation rate covary. If so, the large loss of heterozygosity that occurred when humans migrated out of Africa would have reduced the mutation rate, leaving Africans to diverge faster from our common ancestor and from related lineages like Neanderthals. To test whether this idea impacts estimates of introgressed fraction, I calculated D, a measure of relative base-sharing with Neanderthals, and heterozygosity difference between all pairwise combinations of populations in the 1000 genomes Phase 3 data. D and heterozygosity difference are ubiquitously negatively correlated across all comparisons, between all regions and even between populations within each major region including Africa. In addition, the larger sample of populations in the Simons Genome Diversity project reveals a pan-Eurasian correlation between Neanderthal and Denisovan fraction. These correlations challenge a simple hybridisation model but do seem consistent with a model where more heterozygous human populations tend to diverge faster from Neanderthals than populations with lower heterozygosity. Indeed, the strongest correlation between Neanderthal content and geography indicates and origin where humans likely left Africa, exactly mimicking the pattern seen for loss of heterozygosity. Such a model explains why evidence for inter-breeding is found more or less wherever archaic and human populations are compared. How much of variation in D is due to introgression and how much is due to heterozygosity-mediated variation in mutation rate remains to be determined.Author summaryThe idea that humans inter-bred with related lineages such as Neanderthals, leaving an appreciable legacy in modern genomes, has rapidly progressed from shocking revelation to accepted dogma. My analysis explores an alternative model in which mutation rate slowed when diversity was lost in a population bottleneck as humans moved out of Africa to colonise the world. I find that, across Eurasia, the size of inferred legacy closely matches the pattern of diversity loss but shows no relationship to where human and Neanderthal populations likely overlapped. My results do not challenge the idea that some inter-breeding occurred, but they do indicate that some, much or even most of the signal that has be attributed entirely to archaic legacies, arises from unexpected variation in mutation rate. More generally, my analysis helps explain why inter-breeding is inferred almost wherever tests are conducted even though most species avoid hybridisation.

2020 ◽  
Author(s):  
Nathan S. Harris ◽  
Alan R. Rogers

AbstractSelection in humans often leaves subtle signatures at individual loci. Few studies have measured the extent to which these signals are shared among human populations. Here a new method is developed to compare weak signals of selection in aggregate across the genome using the 1000 Genomes Phase 3 Data. Results presented here show that selection producing weak selection serves to increase population differences around coding areas of the genome.


2017 ◽  
Author(s):  
Ali Akbari ◽  
Joseph J. Vitti ◽  
Arya Iranmehr ◽  
Mehrdad Bakhtiari ◽  
Pardis C. Sabeti ◽  
...  

AbstractMethods to identify signatures of selective sweeps in population genomics data have been actively developed, but mostly do not identify the specific mutation favored by the selective sweep. We present a method, iSAFE, that uses a statistic derived solely from population genetics signals to pinpoint the favored mutation even when the signature of selection extends to 5Mbp. iSAFE was tested extensively on simulated data and in human populations from the 1000 Genomes Project, at 22 loci with previously characterized selective sweeps. For 14 of the 22 loci, iSAFE ranked the previously characterized candidate mutation among the 13 highest scoring (out of ∼ 21, 000 variants). Three loci did not show a strong signal. For the remaining loci, iSAFE identified previously unreported mutations as being favored. In these regions, all of which involve pigmentation related genes, iSAFE identified identical selected mutations in multiple non-African populations suggesting an out-of-Africa onset of selection. The iSAFE software can be downloaded from https://github.com/alek0991/iSAFE.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mary Elizabeth Mathyer ◽  
Erin A. Brettmann ◽  
Alina D. Schmidt ◽  
Zane A. Goodwin ◽  
Inez Y. Oh ◽  
...  

AbstractThe genetic modules that contribute to human evolution are poorly understood. Here we investigate positive selection in the Epidermal Differentiation Complex locus for skin barrier adaptation in diverse HapMap human populations (CEU, JPT/CHB, and YRI). Using Composite of Multiple Signals and iSAFE, we identify selective sweeps for LCE1A-SMCP and involucrin (IVL) haplotypes associated with human migration out-of-Africa, reaching near fixation in European populations. CEU-IVL is associated with increased IVL expression and a known epidermis-specific enhancer. CRISPR/Cas9 deletion of the orthologous mouse enhancer in vivo reveals a functional requirement for the enhancer to regulate Ivl expression in cis. Reporter assays confirm increased regulatory and additive enhancer effects of CEU-specific polymorphisms identified at predicted IRF1 and NFIC binding sites in the IVL enhancer (rs4845327) and its promoter (rs1854779). Together, our results identify a selective sweep for a cis regulatory module for CEU-IVL, highlighting human skin barrier evolution for increased IVL expression out-of-Africa.


2018 ◽  
Vol 115 (36) ◽  
pp. 8996-9001 ◽  
Author(s):  
Bryan P. Thornlow ◽  
Josh Hough ◽  
Jacquelyn M. Roger ◽  
Henry Gong ◽  
Todd M. Lowe ◽  
...  

Transfer RNAs (tRNAs) are a central component for the biological synthesis of proteins, and they are among the most highly conserved and frequently transcribed genes in all living things. Despite their clear significance for fundamental cellular processes, the forces governing tRNA evolution are poorly understood. We present evidence that transcription-associated mutagenesis and strong purifying selection are key determinants of patterns of sequence variation within and surrounding tRNA genes in humans and diverse model organisms. Remarkably, the mutation rate at broadly expressed cytosolic tRNA loci is likely between 7 and 10 times greater than the nuclear genome average. Furthermore, evolutionary analyses provide strong evidence that tRNA genes, but not their flanking sequences, experience strong purifying selection acting against this elevated mutation rate. We also find a strong correlation between tRNA expression levels and the mutation rates in their immediate flanking regions, suggesting a simple method for estimating individual tRNA gene activity. Collectively, this study illuminates the extreme competing forces in tRNA gene evolution and indicates that mutations at tRNA loci contribute disproportionately to mutational load and have unexplored fitness consequences in human populations.


2021 ◽  
Author(s):  
Moisès Coll Macià ◽  
Laurits Skov ◽  
Benjamin Marco Peter ◽  
Mikkel Heide Schierup

AbstractAfter the main out-of-Africa event, humans interbred with Neanderthals leaving 1-2% of Neanderthal DNA scattered in small fragments in all non-African genomes today1,2. Here we investigate the size distribution of these fragments in non-African genomes3. We find consistent differences in fragment length distributions across Eurasia with 11% longer fragments in East Asians than in West Eurasians. By comparing extant populations and ancient samples, we show that these differences are due to a different rate of decay in length by recombination since the Neanderthal admixture. In line with this, we observe a strong correlation between the average fragment length and the accumulation of derived mutations, similar to what is expected by changing the ages at reproduction as estimated from trio studies4. Altogether, our results suggest consistent differences in the generation interval across Eurasia, by up to 20% (e.g. 25 versus 30 years), over the past 40,000 years. We use sex-specific accumulations of derived alleles to infer how these changes in generation intervals between geographical regions could have been mainly driven by shifts in either male or female age of reproduction, or both. We also find that previously reported variation in the mutational spectrum5 may be largely explained by changes to the generation interval and not by changes to the underlying mutational mechanism. We conclude that Neanderthal fragment lengths provide unique insight into differences of a key demographic parameter among human populations over the recent history.


2019 ◽  
Vol 37 (1) ◽  
pp. 2-10 ◽  
Author(s):  
Luke Anderson-Trocmé ◽  
Rick Farouni ◽  
Mathieu Bourgey ◽  
Yoichiro Kamatani ◽  
Koichiro Higasa ◽  
...  

Abstract Recent reports have identified differences in the mutational spectra across human populations. Although some of these reports have been replicated in other cohorts, most have been reported only in the 1000 Genomes Project (1kGP) data. While investigating an intriguing putative population stratification within the Japanese population, we identified a previously unreported batch effect leading to spurious mutation calls in the 1kGP data and to the apparent population stratification. Because the 1kGP data are used extensively, we find that the batch effects also lead to incorrect imputation by leading imputation servers and a small number of suspicious GWAS associations. Lower quality data from the early phases of the 1kGP thus continue to contaminate modern studies in hidden ways. It may be time to retire or upgrade such legacy sequencing data.


2003 ◽  
Vol 23 (2) ◽  
pp. 733-743 ◽  
Author(s):  
Jeremy M. Stark ◽  
Maria Jasin

ABSTRACT Loss of heterozygosity (LOH) is a common genetic alteration in tumors and often extends several megabases to encompass multiple genetic loci or even whole chromosome arms. Based on marker and karyotype analysis of tumor samples, a significant fraction of LOH events appears to arise from mitotic recombination between homologous chromosomes, reminiscent of recombination during meiosis. As DNA double-strand breaks (DSBs) initiate meiotic recombination, a potential mechanism leading to LOH in mitotically dividing cells is DSB repair involving homologous chromosomes. We therefore sought to characterize the extent of LOH arising from DSB-induced recombination between homologous chromosomes in mammalian cells. To this end, a recombination reporter was introduced into a mouse embryonic stem cell line that has nonisogenic maternal and paternal chromosomes, as is the case in human populations, and then a DSB was introduced into one of the chromosomes. Recombinants involving alleles on homologous chromosomes were readily obtained at a frequency of 4.6 × 10−5; however, this frequency was substantially lower than that of DSB repair by nonhomologous end joining or the inferred frequency of homologous repair involving sister chromatids. Strikingly, the majority of recombinants had LOH restricted to the site of the DSB, with a minor class of recombinants having LOH that extended to markers 6 kb from the DSB. Furthermore, we found no evidence of LOH extending to markers 1 centimorgan or more from the DSB. In addition, crossing over, which can lead to LOH of a whole chromosome arm, was not observed, implying that there are key differences between mitotic and meiotic recombination mechanisms. These results indicate that extensive LOH is normally suppressed during DSB-induced allelic recombination in dividing mammalian cells.


Mutagenesis ◽  
1995 ◽  
Vol 10 (1) ◽  
pp. 53-58 ◽  
Author(s):  
Krista L. Dobo ◽  
Cynthia R. Giver ◽  
David A. Eastmond ◽  
Heather S. Rumbos ◽  
Andrew J. Grosovsky

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 190
Author(s):  
Marcela Vieira ◽  
Ryan Kimmitt ◽  
Suerie Moon

Background: The past two decades have witnessed significant growth in non-commercial research and development (R&D) initiatives, particularly for neglected diseases, but there is limited understanding of the ways in which they compare with commercial R&D. This study analyses costs, timelines, and attrition rates of non-commercial R&D across multiple initiatives and how they compare to commercial R&D. Methods: This is a mixed-method, observational, descriptive, and analytic study. We contacted 48 non-commercial R&D initiatives and received either quantitative and/or qualitative data from 13 organizations. We used the Portfolio to Impact (P2I) model’s estimates of average costs, timelines, and attrition rates for commercial R&D, while noting that P2I cost estimates are far lower than some previous findings in the literature. Results: The quantitative data suggested that the costs and timelines per candidate per phase (from preclinical through Phase 3) of non-commercial R&D for new chemical entities are largely in line with commercial averages. The quantitative data was insufficient to compare attrition rates. The qualitative data identified more reasons why non-commercial R&D costs would be lower than commercial R&D, timelines would be longer, and attrition rates would be equivalent or higher, though the data does not allow for estimating the magnitude of these effects. Conclusions: The quantitative data suggest that costs and timelines per candidate per phase were largely in line with (lower-end estimates of) commercial averages. We were unable to draw conclusions on overall efficiency, however, due to insufficient data on attrition rates. Given that non-commercial R&D is a nascent area of research with limited data available, this study contributes to the literature by generating hypotheses for further testing against a larger sample of quantitative data. It also offers a range of explanatory factors for further exploration regarding how non-commercial and commercial R&D may differ in costs and efficiency.


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