The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure. The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion. However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH). Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention.

Although sexual reproduction is ubiquitous throughout nature, the molecular machinery behind it has been repeatedly disrupted during evolution, leading to the emergence of asexual lineages in all eukaryotic phyla. Despite intensive research, little is known about what causes the switch from sexual reproduction to asexuality.Interspecific hybridization is one of the candidate explanations, but the reasons for the apparent association between hybridization and asexuality remain unclear. In this study, we combined cross-breeding experiments with population genetic and phylogenomic approaches to reveal the history of speciation and asexuality evolution in European spined loaches (Cobitis). Contemporary species readily hybridize in hybrid zones, but produce infertile males and fertile but clonally reproducing females that cannot mediate introgressions. However, our analysis of exome data indicates that intensive gene flow between species has occurred in the past. Crossings among species with various genetic distances showed that, while distantly related species produced asexual females and sterile males, closely related species produce sexually reproducing hybrids of both sexes. Our results suggest that hybridization leads to sexual hybrids at the initial stages of speciation, but as the species diverge further, the gradual accumulation of reproductive incompatibilities between species could distort their gametogenesis towards asexuality. Interestingly, comparative analysis of published data revealed that hybrid asexuality generally evolves at lower genetic divergences than hybrid sterility or inviability. Given that hybrid asexuality effectively restricts gene flow, it may establish a primary reproductive barrier earlier during diversification than other "classical" forms of postzygotic incompatibilities. Hybrid asexuality may thus indirectly contribute to the speciation process. K E Y W O R D Sbalance hypothesis, coalescence, evolution of asexuality, hybridization, phylogeography,

Two types of EAC can be characterized based on the presence or absence of BE. These findings could increase our understanding the etiology of EAC, and be used in management and prognosis of patients.

The isolation-with-migration (IM) model is commonly used to make inferences about gene flow during speciation, using polymorphism data. However, it has been reported that the parameter estimates obtained by fitting the IM model are very sensitive to the model’s assumptions—including the assumption of constant gene flow until the present. This article is concerned with the isolation-with-initial-migration (IIM) model, which drops precisely this assumption. In the IIM model, one ancestral population divides into two descendant subpopulations, between which there is an initial period of gene flow and a subsequent period of isolation. We derive a very fast method of fitting an extended version of the IIM model, which also allows for asymmetric gene flow and unequal population sizes. This is a maximum-likelihood method, applicable to data on the number of segregating sites between pairs of DNA sequences from a large number of independent loci. In addition to obtaining parameter estimates, our method can also be used, by means of likelihood-ratio tests, to distinguish between alternative models representing the following divergence scenarios: (a) divergence with potentially asymmetric gene flow until the present, (b) divergence with potentially asymmetric gene flow until some point in the past and in isolation since then, and (c) divergence in complete isolation. We illustrate the procedure on pairs of Drosophila sequences from ∼30,000 loci. The computing time needed to fit the most complex version of the model to this data set is only a couple of minutes. The R code to fit the IIM model can be found in the supplementary files of this article.

The isolation-with-migration (IM) model is commonly used to make inferences about gene flow during speciation, using polymorphism data. However, Becquet and Przeworski (2009) report that the parameter estimates obtained by fitting the IM model are very sensitive to the model's assumptions -including the assumption of constant gene flow until the present. This paper is concerned with the isolationwith-initial-migration (IIM) model of Wilkinson-Herbots (2012), which drops precisely this assumption. In the IIM model, one ancestral population divides into two descendant subpopulations, between which there is an initial period of gene flow and a subsequent period of isolation. We derive a very fast method of fitting an extended version of the IIM model, which also allows for asymmetric gene flow and unequal population sizes. This is a maximum-likelihood method, applicable to data on the number of segregating sites between pairs of DNA sequences from a large number of independent loci. In addition to obtaining parameter estimates, our method can also be used to distinguish between alternative models representing different evolutionary scenarios, by means of likelihood ratio tests. We illustrate the procedure on pairs of Drosophila sequences from approximately 30,000 loci. The computing time needed to fit the most complex version of the model to this data set is only a couple of minutes. The R code to fit the IIM model can be found in the supplementary files of this paper.