9,352 research outputs found
De novo construction of polyploid linkage maps using discrete graphical models
Linkage maps are used to identify the location of genes responsible for
traits and diseases. New sequencing techniques have created opportunities to
substantially increase the density of genetic markers. Such revolutionary
advances in technology have given rise to new challenges, such as creating
high-density linkage maps. Current multiple testing approaches based on
pairwise recombination fractions are underpowered in the high-dimensional
setting and do not extend easily to polyploid species. We propose to construct
linkage maps using graphical models either via a sparse Gaussian copula or a
nonparanormal skeptic approach. Linkage groups (LGs), typically chromosomes,
and the order of markers in each LG are determined by inferring the conditional
independence relationships among large numbers of markers in the genome.
Through simulations, we illustrate the utility of our map construction method
and compare its performance with other available methods, both when the data
are clean and contain no missing observations and when data contain genotyping
errors and are incomplete. We apply the proposed method to two genotype
datasets: barley and potato from diploid and polypoid populations,
respectively. Our comprehensive map construction method makes full use of the
dosage SNP data to reconstruct linkage map for any bi-parental diploid and
polyploid species. We have implemented the method in the R package netgwas.Comment: 25 pages, 7 figure
A conserved filamentous assembly underlies the structure of the meiotic chromosome axis.
The meiotic chromosome axis plays key roles in meiotic chromosome organization and recombination, yet the underlying protein components of this structure are highly diverged. Here, we show that 'axis core proteins' from budding yeast (Red1), mammals (SYCP2/SYCP3), and plants (ASY3/ASY4) are evolutionarily related and play equivalent roles in chromosome axis assembly. We first identify 'closure motifs' in each complex that recruit meiotic HORMADs, the master regulators of meiotic recombination. We next find that axis core proteins form homotetrameric (Red1) or heterotetrameric (SYCP2:SYCP3 and ASY3:ASY4) coiled-coil assemblies that further oligomerize into micron-length filaments. Thus, the meiotic chromosome axis core in fungi, mammals, and plants shares a common molecular architecture, and likely also plays conserved roles in meiotic chromosome axis assembly and recombination control
Critical mutation rate has an exponential dependence on population size in haploid and diploid populations
Understanding the effect of population size on the key parameters of evolution is particularly important for populations nearing extinction. There are evolutionary pressures to evolve sequences that are both fit and robust. At high mutation rates, individuals with greater mutational robustness can outcompete those with higher fitness. This is survival-of-the-flattest, and has been observed in digital organisms, theoretically, in simulated RNA evolution, and in RNA viruses. We introduce an algorithmic method capable of determining the relationship between population size, the critical mutation rate at which individuals with greater robustness to mutation are favoured over individuals with greater fitness, and the error threshold. Verification for this method is provided against analytical models for the error threshold. We show that the critical mutation rate for increasing haploid population sizes can be approximated by an exponential function, with much lower mutation rates tolerated by small populations. This is in contrast to previous studies which identified that critical mutation rate was independent of population size. The algorithm is extended to diploid populations in a system modelled on the biological process of meiosis. The results confirm that the relationship remains exponential, but show that both the critical mutation rate and error threshold are lower for diploids, rather than higher as might have been expected. Analyzing the transition from critical mutation rate to error threshold provides an improved definition of critical mutation rate. Natural populations with their numbers in decline can be expected to lose genetic material in line with the exponential model, accelerating and potentially irreversibly advancing their decline, and this could potentially affect extinction, recovery and population management strategy. The effect of population size is particularly strong in small populations with 100 individuals or less; the exponential model has significant potential in aiding population management to prevent local (and global) extinction events
Causal graphical models in systems genetics: A unified framework for joint inference of causal network and genetic architecture for correlated phenotypes
Causal inference approaches in systems genetics exploit quantitative trait
loci (QTL) genotypes to infer causal relationships among phenotypes. The
genetic architecture of each phenotype may be complex, and poorly estimated
genetic architectures may compromise the inference of causal relationships
among phenotypes. Existing methods assume QTLs are known or inferred without
regard to the phenotype network structure. In this paper we develop a
QTL-driven phenotype network method (QTLnet) to jointly infer a causal
phenotype network and associated genetic architecture for sets of correlated
phenotypes. Randomization of alleles during meiosis and the unidirectional
influence of genotype on phenotype allow the inference of QTLs causal to
phenotypes. Causal relationships among phenotypes can be inferred using these
QTL nodes, enabling us to distinguish among phenotype networks that would
otherwise be distribution equivalent. We jointly model phenotypes and QTLs
using homogeneous conditional Gaussian regression models, and we derive a
graphical criterion for distribution equivalence. We validate the QTLnet
approach in a simulation study. Finally, we illustrate with simulated data and
a real example how QTLnet can be used to infer both direct and indirect effects
of QTLs and phenotypes that co-map to a genomic region.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS288 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Синхронія за К. Г. Юнгом та сплутані квантові стани: кіт Шредінгера «блукає» між хромосомами
Один з найбільш перспективних напрямків дослідження феномену синхронії за К. Г. Юнгом розглядується з позиції останніх досягнень сучасної науки. Увага зосереджена, головним чином, на сплутаних квантових станах та пов'язаних феноменах – квантової когерентності та квантової суперпозиції. Показано що квантова нелокальність, яка здатна розв'язати парадокс Ейнштейна –Подольского-Розена є одним з найбільш адекватних фізичних механізмів у плані відповідності гіпотезі синхронії Юнга. Здійснена спроба психофізіологічного обґрунтування синхронії у контексті молекулярної біології. Запропоновано оригінальну концепцію, згідно якої, біологічні молекули що задіяні при поділу клітини під час мітозу та мейозу, зокрема ДНК, можуть бути матеріальними носіями свідомості. Це припущення може бути сформульовано на основі феноменології аналітичної психології Юнга
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