Biology subjects

Mayrose, I.

Publications and source records attributed to Mayrose, I..

13 recordsLinked to original sources

bioRxiv2026

Context-dependent determinants of CRISPR-Cas9 editing efficiency revealed through cross-species endogenous editing analysis

Accurate prediction of CRISPR-Cas9 guide RNA (gRNA) editing efficiency remains limited, particularly outside human systems, where models trained on exogenous human datasets show poor generalization. We analyzed Cas9 efficiency and repair outcomes using novel endogenous editing data from four human cell types, two tomato cell types, and cells from giant river prawn and black soldier fly. While integrating publicly available predictors via ensemble frameworks improved performance, our analysis revealed hundreds of novel features affecting activity. Crucially, dominant features related to sites competition for gRNA, and local geometric properties varied across systems, highlighting the strong context dependence of Cas9 efficiency and arguing against a universal model. Interestingly, codon usage bias-based features also emerged as informative predictors, as they are proxies for chromatin accessibility. In contrast, trends in repair outcomes remained conserved. This work provides essential resources for more generalizable CRISPR guide design.

synthetic biology↗

bioRxiv2026

A deep-learning-based score to evaluate multiple sequence alignments

Multiple sequence alignment (MSA) inference is a central task in molecular evolution and comparative genomics, and the reliability of downstream analyses, including phylogenetic inference, depends critically on alignment quality. Despite this importance, most widely used MSA methods optimize the sum-of-pairs (SP) score, and relatively little attention has been paid to whether this objective function accurately reflects alignment accuracy. Here, we evaluate the performance of the SP score using simulated and empirical benchmark alignments. For each dataset, we compare alternative MSAs derived from the same unaligned sequences and quantify the relationship between their SP scores and their distances from a reference alignment. We show that the alignment with the optimal SP score often does not correspond to the most accurate alignment. To address this limitation, we develop deep-learning-based scoring functions that integrate a collection of MSA features. We first introduce Model 1, a regression model that predicts the distance of a given MSA from the reference alignment. Across simulated and empirical datasets, this learned score correlates more strongly with true alignment accuracy than the SP score. However, Model 1 is less effective at identifying the best alignment among alternatives. We therefore develop Model 2, which takes as input a set of alternative MSAs generated from the same sequences and predicts their relative ranking. Model 2 more accurately identifies the top-ranking MSA than the SP score, Model 1, and several widely used alignment programs. Using simulations, we show that selecting MSAs based on our approach leads to more accurate phylogenetic reconstructions.

bioinformatics↗

bioRxiv2025

Evolutionary history, ecological divergence, and introgression in the Oncocyclus irises species complex in the Southern Levant

Speciation is a dynamic process shaped by the interaction of gene flow, geographic isolation, and ecological divergence. The Oncocyclus irises of the Southern Levant represent a young radiation of narrowly endemic species considered to be in the course of speciation. In this study, we used RAD-sequencing and single nucleotide polymorphism analysis across nine described species to investigate patterns of genomic divergence, gene flow, and local adaptation. Phylogenomic analyses revealed a mix of well-supported clades for some species, previously defined by their morphology and distribution, and non-monophyletic lineages, with several species exhibiting shallow divergence and shared genetic ancestry. We found evidence for gene flow and historical introgression between Iris petrana, I. atrofusca and I. mariae, while other cases of non-monophyly appear driven by incomplete lineage sorting. Both geographic distance (IBD) and environmental factors (IBE), mainly altitude, temperature, and aridity, were significantly associated with genetic structure, suggesting that local adaptation contributed to divergence following range expansion. Based on our findings we propose that the divergence of the Oncocyclus iris species in the Southern Levant supports a stepping-stone dispersion model, in which north-to-south dispersal was followed by local adaptation, and introgression in secondary contact zones. Overall, these findings highlight the complexity of speciation and the need for integrative approaches to study the interplay between historical divergence, contemporary gene flow, and environmental differentiation in shaping genomic patterns.

evolutionary biology↗

bioRxiv2025

The role of plant polyploidy in the structure of plant-pollinator communities

Polyploidization is a major macromutation, bearing notable genomic and ecological consequences. While the impact of polyploidy on plant abiotic niches is well studied, our understanding of its consequences on biotic interactions, and particularly pollination, is lacking and hardly considers its role in shaping community structure. Here, we integrate hundreds of plant-pollinator networks, ploidy inferences, reproductive traits, and climatic attributes to ascertain whether a general pattern characterizes the link between polyploid frequency and community structure. We further examine whether environmental factors and plant traits known to be associated with polyploidy mediate this relationship. Our analysis reveals that an increased frequency of polyploid species is positively associated with network nestedness while being negatively associated modularity. Structural equation modeling reveals that these associations are partially mediated via the frequency of self-compatible plants and to a lesser extent by differences in flower shape. Despite these alterations in community structure, the heightened abundance of polyploids appears to have minimal impact on network connectance and resilience to extinction. Our findings imply that unlike abiotic interactions, the impact of polyploidy on biotic interactions is less predictable, and is affected synergistically by both phenotypic and environmental factors. Collectively, however, polyploidy still exerts an influence on community structure.

evolutionary biology↗

bioRxiv2024

Whole-Genome Sequencing of the Wild Barley Diversity Collection: A Resource for Identifying and Exploiting Genetic Variation for Cultivated Barley Improvement

To exploit allelic variation in Hordeum vulgare subsp. spontaneum, the Wild Barley Diversity Collection was evaluated for several agronomic traits and subjected to paired-end Illumina sequencing at [~]9X depth, generating 109.5 million single nucleotide polymorphisms after alignment to the Morex V3 assembly. A genome-wide association study of lemma color identified one marker-trait association (MTA) on chromosome 1HL close to HvBlp, the cloned gene controlling black lemma. Four MTAs were identified for stem rust resistance: one co-locating to the complex RMRL1-RMRL2 locus on 5HL, and three novel loci on 1HS, 1HL, and 5HL. Six MTAs for days to heading (DTH) on vernalized plants were identified on all chromosomes except 1H and 6H. Two MTAs for DTH on non-vernalized plants were identified on chromosomes 1HL and 2HS. All MTAs for DTH were novel. The whole genome sequence data described herein will facilitate the identification and utilization of new alleles for barley improvement.

genomics↗

bioRxiv2022

Revising the global biogeography of plant life cycles

Plants exhibit two primary life cycles - annual and perennial - which vary in their effects on ecosystem functioning. Here, we assembled a database of 235,000 species to assess the worldwide distribution of plant life cycles. We found that annuals are half as common as previously thought (6% of all plant species). Furthermore, our analysis demonstrates that annuals are favored under hot and dry conditions, especially under a prolonged dry season. Strikingly, this pattern remains consistent among different families, indicating convergent evolution. Moreover, we show that increasing climate variability and anthropogenic disturbance further increase the favorability of annuals. Overall, our analysis raises concerns for the future of ecosystem services provided by perennials because the ongoing climate and land-use changes are leading to an annuals-dominated world. One-Sentence SummaryThis extensive update to plant life cycle biogeography deciphers their dependence on temperature, rainfall, and disturbance.

ecology↗

bioRxiv2022

The evolutionary dynamics that retain long neutral genomic sequences in face of indel deletion bias: a model and its application to human introns

Insertions and deletions (indels) of short DNA segments are common evolutionary events. Numerous studies showed that deletions occur more often than insertions in both prokaryotes and eukaryotes. It raises the question why neutral sequences are not eradicated from the genome. We suggest that this is due to a phenomenon we term border-induced selection. Accordingly, a neutral sequence is bordered between conserved regions. Deletions occurring near the borders occasionally protrude to the conserved region and are thereby subject to strong purifying selection. Thus, for short neutral sequences, an insertion bias is expected. Here, we develop a set of increasingly complex models of indel-dynamics that incorporate border-induced selection. Furthermore, we show that short conserved sequences within the neutrally evolving sequence help explain: (1) the presence of very long sequences; (2) the high variance of sequence lengths; (3) the possible emergence of multimodality in sequence length distributions. Finally, we fitted our models to the human intron length distribution, as introns are thought to be mostly neutral and bordered by conserved exons. We show that when accounting for the occurrence of short conserved sequences within introns, we reproduce the main features, including the presence of long introns and the multimodality of intron distribution.

bioinformatics↗

bioRxiv2020

A probabilistic model for indel evolution: differentiating insertions from deletions

Insertions and deletions (indels) are common molecular evolutionary events. However, probabilistic models for indel evolution are under-developed due to their computational complexity. Here we introduce several improvements to indel modeling: (1) while previous models for indel evolution assumed that the rates and length distributions of insertions and deletions are equal, here, we propose a richer model that explicitly distinguishes between the two; (2) We introduce numerous summary statistics that allow Approximate Bayesian Computation (ABC) based parameter estimation; (3) We develop a neural-network model-selection scheme to test whether the richer model better fits biological data compared to the simpler model. Our analyses suggest that both our inference scheme and the model-selection procedure achieve high accuracy on simulated data. We further demonstrate that our proposed indel model better fits a large number of empirical datasets and that, for the majority of these datasets, the deletion rate is higher than the insertion rate. Finally, we demonstrate that indel rates are negatively correlated to the effective population size across various phylogenomic clades.

bioinformatics↗

bioRxiv2020

Model Adequacy Tests for Likelihood Models of Chromosome-Number Evolution

O_LIChromosome number is a central feature of eukaryote genomes. Deciphering patterns of chromosome-number change along a phylogeny is central to the inference of whole genome duplications and ancestral chromosome numbers. ChromEvol is a probabilistic inference tool that allows the evaluation of several models of chromosome-number evolution and their fit to the data. However, fitting a model does not necessarily mean that the model describes the empirical data adequately. This vulnerability may lead to incorrect conclusions when model assumptions are not met by real data. C_LIO_LIHere, we present a model adequacy test for likelihood models of chromosome-number evolution. The procedure allows to determine whether the model can generate data with similar characteristics as those found in the observed ones. C_LIO_LIWe demonstrate that using inadequate models can lead to inflated errors in several inference tasks. Applying the developed method to 200 angiosperm genera, we find that in many of these, the best-fitted model provides poor fit to the data. The inadequacy rate increases in large clades or in those in which hybridizations are present. C_LIO_LIThe developed model adequacy test can help researchers to identify phylogenies whose underlying evolutionary patterns deviate substantially from current modelling assumptions and should guide future methods developments. C_LI

evolutionary biology↗

bioRxiv2020

A codon model for associating phenotypic traits with altered selective patterns of sequence evolution

Changes in complex phenotypes, such as pathogenicity levels, trophic lifestyle, and habitat shifts are brought on by multiple genomic changes: sub- and neofunctionalization, loss of function, and levels of gene expression. Thus, detecting the signature of selection in coding sequences and associating it with shifts in phenotypic state can unveil the genes underlying complex traits. Phylogenetic branch-site codon models are routinely applied to detect changes in selective patterns along specific branches of the phylogeny. These methods rely on a pre-specified partition of the phylogeny to branch categories, thus treating the course of trait evolution as fully resolved and assuming that transitions in phenotypic states have occurred only at speciation events. Here we present TraitRELAX, a new phylogenetic model that alleviates these strong assumptions by explicitly accounting for the uncertainty in the evolution of both trait and coding sequences. This joint statistical framework enables the detection of changes in selection intensity upon repeated trait transitions. We evaluated the performance of TraitRELAX using simulations and then applied it to two case studies. Using TraitRELAX, we found an intensification of selection in the SEMG2 gene in polygynandrous species of primates compared to species of other mating forms, as well as changes in the intensity of purifying selection operating on sixteen bacterial genes upon transitioning from free-living to an endosymbiotic lifestyle.

evolutionary biology↗

bioRxiv2020

ModelTeller: model selection for optimal phylogenetic reconstruction using machine learning

Statistical criteria have long been the standard for selecting the best model for phylogenetic reconstruction and downstream statistical inference. While model selection is regarded as a fundamental step in phylogenetics, existing methods for this task consume computational resources for long processing time, they are not always feasible, and sometimes depend on preliminary assumptions which do not hold for sequence data. Moreover, while these methods are dedicated to revealing the processes that underlie the sequence data, in most cases they do not produce the most accurate trees. Notably, phylogeny reconstruction consists of two related tasks, topology reconstruction and branch-length estimation. It was previously shown that in many cases the most complex model, GTR+I+G, leads to topologies that are as accurate as using existing model selection criteria, but overestimates branch lengths. Here, we present ModelTeller, a computational methodology for phylogenetic model selection, devised within the machine-learning framework, optimized to predict the most accurate model for branch-length estimation accuracy. ModelTeller relies on a readily implemented machine-learning model and thus the prediction according to features extracted from the sequence data results in a substantial decrease in running time compared to existing strategies. We show that on datasets simulated under simple homogenous substitution models ModelTeller leads to branch-length estimation that is as accurate as the statistical model selection criteria. We then demonstrate that ModelTeller outperforms these criteria when more intricate patterns - that aim at mimicking realistic processes - are considered.

evolutionary biology↗

bioRxiv2019

INTERACTION BETWEEN PLOIDY, BREEDING SYSTEM, AND LINEAGE DIVERSIFICATION

If particular traits consistently affect rates of speciation and extinction, broad macroevolutionary patterns can be understood as consequences of selection at high levels of the biological hierarchy. Identifying traits associated with diversification rate differences is complicated by the wide variety of characters under consideration and the statistical challenges of testing for associations from comparative phylogenetic data. Ploidy (diploid vs. polyploid states) and breeding system (self-incompatible vs. self-compatible states) have been repeatedly suggested as possible drivers of differential diversification. We investigate the connections of these traits, including their interaction, to speciation and extinction rates in Solanaceae. We show that the effect of ploidy on diversification can be largely explained by its correlation with breeding system and that additional unknown factors, alongside breeding system, influence diversification rates. These results are largely robust to allowing for diploidization. Finally, we find that the most common evolutionary pathway to polyploidy in Solanaceae occurs via direct breakdown of self-incompatibility by whole genome duplication, rather than indirectly via breakdown followed by polyploidization.

evolutionary biology↗

bioRxiv2017

CRISPys: Optimal sgRNA design for editing multiple members of a gene family using the CRISPR system

The discovery and development of the CRISPR-Cas9 system in the past few years has made eukaryotic genome editing, and specifically gene knockout for reverse genetics, a simpler, efficient, and effective task. The system is directed to the genomic target site by a programmed single-guide RNA (sgRNA) that base-pairs with the DNA target, subsequently leading to site-specific double-strand breaks. However, many gene families in eukaryotic genomes exhibit partially overlapping functions and, thus, the knockout of one gene might be concealed by the function of the other. In such cases, the reduced specificity of the CRISPR-Cas9 system, which may lead to the cleavage of genomic sites that are not identical to the sgRNA, can be harnessed for the simultaneous knockout of multiple homologous genes. Here, we introduce CRISPys, an algorithm for the optimal design of sgRNAs that would potentially target multiple members of a given gene family. CRISPys first clusters all the potential targets in the input sequences into a hierarchical tree structure that specifies the similarity among them. Then, sgRNAs are proposed in the internal nodes of the tree by embedding mismatches where needed, such that the cleavage efficiencies of the induced targets are maximized. We suggest several approaches for designing the optimal individual sgRNA, and an approach that provides a set of sgRNAs that also accounts for the homologous relationships among gene-family members. We further show by in-silico examination over all gene families in the Solanum lycopersicum genome that our suggested approach outperforms simpler alignment-based techniques.\n\nGraphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY\n\nHighlightsO_LIMany genes in eukaryotic genomes exhibit partially overlapping functions. This imposes difficulties on reverse-genetics, as the knockout of one gene might be concealed by the function of the other.\nC_LIO_LIWe present CRISPys, a graph-based algorithm for the optimal design of CRISPR systems given a set of redundant genes.\nC_LIO_LICRISPys harnesses the lack of specificity of the CRISPR-Cas9 genome editing technique, providing researchers the ability to simultaneously mutate multiple genes.\nC_LIO_LIWe show that CRISPys outperforms existing approaches that are based on simple alignment of the input gene family.\nC_LI

bioinformatics↗