Biology subjects

Anisimova, M.

Publications and source records attributed to Anisimova, M..

3 recordsLinked to original sources

bioRxiv2018

Accounting for programmed ribosomal frameshifting in the computation of codon usage bias indices

Experimental evidence shows that synonymous mutations can have important consequences on genetic fitness. Many organisms display codon usage bias (CUB), where synonymous codons that are translated into the same amino acid appear with distinct frequency. CUB is thought to arise from selection for translational efficiency and accuracy, termed the translational efficiency hypothesis (TEH). Indeed, CUB indices correlate with protein expression levels, which is widely interpreted as evidence for translational selection. However, these tests neglect -1 programmed ribosomal frameshifting (-1 PRF), an important translational disruption effect found across all organisms of the tree of life. Genes that contain -1 PRF signals should cost more to express than genes without. Thus, CUB indices that do not consider -1 PRF may overestimate genes true adaptation to translational efficiency and accuracy constraints. Here, we first investigate whether -1 PRF signals do indeed carry such translational cost. We then propose two corrections for CUB indices for genes containing -1 PRF signals. We retest the TEH under these corrections. We find that the correlation between corrected CUB index and protein expression remains intact for most levels of uniform -1 PRF efficiencies, and tends to increase when these efficiencies decline with protein expression. We conclude that the TEH is strengthened and that -1 PRF events constitute a promising and useful tool to examine the relationships between CUB and selection for translation efficiency and accuracy.

genetics↗

bioRxiv2017

Cross-reactive immunity drives global oscillation and opposed alternation patterns of seasonal influenza A viruses

Several human pathogens exhibit distinct patterns of seasonality and circulate as pairs of discrete strains. For instance, the activity of the two co-circulating influenza A virus subtypes oscillates and peaks during winter seasons of the worlds temperate climate zones. These periods of increased activity are usually caused by a single dominant subtype. Alternation of dominant strains in successive influenza seasons makes epidemic forecasting a major challenge. From the start of the 2009 influenza pandemic we enrolled influenza A virus infected patients (n = 2,980) in a global prospective clinical study. Complete hemagglutinin (HA) sequences were obtained from 1,078 A/H1N1 and 1,033 A/H3N2 viruses and were linked to patient data. We then used phylodynamics to construct high resolution spatio-temporal phylogenetic HA trees and estimated global influenza A effective reproductive numbers (R) over time (2009-2013). We demonstrate that R, a parameter to define host immunity, oscillates around R = 1 with a clear opposed alternation pattern between phases of the A/H1N1 and A/H3N2 subtypes. Moreover, we find a similar alternation pattern for the number of global virus migration events between the sampled geographical locations. Both observations suggest a between-strain competition for susceptible hosts on a global level. Extrinsic factors that affect person-to-person transmission are a major driver of influenza seasonality, which forces influenza epidemics to coincide with winter seasons. The data presented here indicate that also cross-reactive host immunity is a key intrinsic driver of global influenza seasonality, which determines the outcome of competition between influenza A virus strains at the onset of each epidemic season.\n\nSignificance statementAnnual influenza epidemics coincide with winter seasons in many parts of the world. Environmental factors, such as air humidity variation or temperature change, are commonly believed to drive these seasonality patterns. Interestingly, three out of the four latest pandemics (1918, 1968 and 2009) did not spread in winter initially, but during summer. This questions to what extent other factors could also impact virus spread among humans. We demonstrate that cross-reactive host immunity is a key factor. It drives the well-known seasonal patterns of virus activity oscillation and alternation of the dominant influenza virus subtype in successive seasons. Furthermore, this factor may also explain the efficient spread of pandemic viruses during summer when cross-reactive host immunity is relatively low.

epidemiology↗

bioRxiv2017

Progressive Multiple Sequence Alignment With The Poisson Indel Process

Sequence alignment lies at the heart of many evolutionary and comparative genomics studies. However, the optimal alignment of multiple sequences is NP-hard, so that exact algorithms become impractical for more than a few sequences. Thus, state of the art alignment methods employ progressive heuristics, breaking the problem into a series of pairwise alignments guided by a phylogenetic tree. Changes between homologous characters are typically modelled by a continuous-time Markov substitution model. In contrast, the dynamics of insertions and deletions (indels) are not modelled explicitly, because the computation of the marginal likelihood under such models has exponential time complexity in the number of taxa. Recently, Bouchard-Cote and Jordan [PNAS (2012) 110(4):1160-1166] have introduced a modification to a classical indel model, describing indel evolution on a phylogenetic tree as a Poisson process. The model termed PIP allows to compute the joint marginal probability of a multiple sequence alignment and a tree in linear time. Here, we present an new dynamic programming algorithm to align two multiple sequence alignments by maximum likelihood in polynomial time under PIP, and apply it a in progressive algorithm. To our knowledge, this is the first progressive alignment method using a rigorous mathematical formulation of an evolutionary indel process and with polynomial time complexity.

evolutionary biology↗