104,092 research outputs found
Evaluation of the 1986-1987 radiata pine clonal trials at Forest Research, New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Master in Applied Science at Massey University
Clonal forestry, the establishment of plantations using tested clones, is highly sought after by the forestry industry in New Zealand and worldwide. Clonal testing is a vital element in the process leading to clonal forestry. Two clonal trials established in 1986 and 1987 by the Forest Research Institute with juvenile ortet material have been analysed in this study. The mating design in the 1986 clones-in-family trial was single-pair crossing with amplification of the clones by fascicle cuttings. It was replicated over two sites, and the trait analysed was diameter at 1.40 m height at ages 4,7, and 10 years. The estimation of additive, non-additive and genetic variances showed a high proportion of non-additive variance compared with the additive variance at one of the sites, whereas the proportion was less important at the other site. The high non-additive component of variance can be due to important dominance or epistasis, or to C-effects confounded with the non-additive variance. This trend was similar for all three ages. Realised genetic gains were obtained from selection of clones at age 10 years for clonal deployment and breeding. For clonal deployment, realised gains were high at both sites (13% and 16%). The gains were similar at both sites provided selection was based on performance values at the site, and not on indirect selection on performance of clones at the other site. Realised gains for selection at age 10 based on the performance of clones on combined sites (10% and 13%) were less than the maximum gain obtained at each individual site. Gains based on information from both sites (10% and 12% at respective sites) were more stable than those selections at any one site. For breeding, the level of gain was significantly inferior than for clonal deployment (4% and 8%), especially when the number of clones per family was restricted to one (2% and 4%). Realised gain on combined-site selection yielded less gain than direct selection at the optimum site for selection (1% and 2%). The presence of genotype x environment interaction emphasised the need to test clones in several sites if stability of performance is desired. It is possible to obtain gain from selections made at an early age, but selections made for breeding at the age of final assessment yielded greater expected total gain and gain per unit time. The mating design in the 1987 clones-in-family trial was a 3 x 3 disconnected factorial. The trial was established on a single site and the trait analysed was percentage of Dothistroma needle infection at ages 3,4 and 7years. The mating design allowed estimation of additive, dominance and epistasis variances, which were overestimated for the lack of replication over sites. In this trial measured for Dothistroma resistance, the additive variance was the major component of the genetic variance at both ages. The evolution of components of genetic variance was confounded with the level of Dothistroma infection. The analysis of these trials indicated the need to improve the mating and field designs to improve the accuracy in the estimation of genetic parameters, highlights the importance of annual or biennual measurements to determine trends of those parameters over time, and showed the difference in gains obtained from selection for breeding and clonal deployment for early selection and selection at the age of final assessment. Accuracy in the estimation of genetic parameters can be achieved using factorial mating designs together with serial propagation to reduce the incidence of C effects, and with replication over several sites. Further considerations have to be made to find the most appropriate field and statistical design, but alpha designs are a possibility to explore. Investment in a series of carefully planned clonal trials is fundamental to the future of clonal forestry in radiata pine
The asexual genome of Drosophila
The rate of recombination affects the mode of molecular evolution. In
high-recombining sequence, the targets of selection are individual genetic
loci; under low recombination, selection collectively acts on large,
genetically linked genomic segments. Selection under linkage can induce clonal
interference, a specific mode of evolution by competition of genetic clades
within a population. This mode is well known in asexually evolving microbes,
but has not been traced systematically in an obligate sexual organism. Here we
show that the Drosophila genome is partitioned into two modes of evolution: a
local interference regime with limited effects of genetic linkage, and an
interference condensate with clonal competition. We map these modes by
differences in mutation frequency spectra, and we show that the transition
between them occurs at a threshold recombination rate that is predictable from
genomic summary statistics. We find the interference condensate in segments of
low-recombining sequence that are located primarily in chromosomal regions
flanking the centromeres and cover about 20% of the Drosophila genome.
Condensate regions have characteristics of asexual evolution that impact gene
function: the efficacy of selection and the speed of evolution are lower and
the genetic load is higher than in regions of local interference. Our results
suggest that multicellular eukaryotes can harbor heterogeneous modes and tempi
of evolution within one genome. We argue that this variation generates
selection on genome architecture
Application of Global Optimization Methods for Feature Selection and Machine Learning
The feature selection process constitutes a commonly encountered problem of global combinatorial optimization. The process reduces the number of features by removing irrelevant and redundant data. This paper proposed a novel immune clonal genetic algorithm based on immune clonal algorithm designed to solve the feature selection problem. The proposed algorithm has more exploration and exploitation abilities due to the clonal selection theory, and each antibody in the search space specifies a subset of the possible features. Experimental results show that the proposed algorithm simplifies the feature selection process effectively and obtains higher classification accuracy than other feature selection algorithms
Predicting B Cell Receptor Substitution Profiles Using Public Repertoire Data
B cells develop high affinity receptors during the course of affinity
maturation, a cyclic process of mutation and selection. At the end of affinity
maturation, a number of cells sharing the same ancestor (i.e. in the same
"clonal family") are released from the germinal center, their amino acid
frequency profile reflects the allowed and disallowed substitutions at each
position. These clonal-family-specific frequency profiles, called "substitution
profiles", are useful for studying the course of affinity maturation as well as
for antibody engineering purposes. However, most often only a single sequence
is recovered from each clonal family in a sequencing experiment, making it
impossible to construct a clonal-family-specific substitution profile. Given
the public release of many high-quality large B cell receptor datasets, one may
ask whether it is possible to use such data in a prediction model for
clonal-family-specific substitution profiles. In this paper, we present the
method "Substitution Profiles Using Related Families" (SPURF), a penalized
tensor regression framework that integrates information from a rich assemblage
of datasets to predict the clonal-family-specific substitution profile for any
single input sequence. Using this framework, we show that substitution profiles
from similar clonal families can be leveraged together with simulated
substitution profiles and germline gene sequence information to improve
prediction. We fit this model on a large public dataset and validate the
robustness of our approach on an external dataset. Furthermore, we provide a
command-line tool in an open-source software package
(https://github.com/krdav/SPURF) implementing these ideas and providing easy
prediction using our pre-fit models.Comment: 23 page
Clonal expansion within pneumococcal serotype 6C after use of seven-valent vaccine
Streptococcus pneumoniae causes invasive infections, primarily at the extremes of life. A seven-valent conjugate vaccine (PCV7) is used to protect against invasive pneumococcal disease in children. Within three years of PCV7 introduction, we observed a fourfold increase in serotype 6C carriage, predominantly due to a single clone. We determined the whole-genome sequences of nineteen S. pneumoniae serotype 6C isolates, from both carriage (n = 15) and disease (n = 4) states, to investigate the emergence of serotype 6C in our population, focusing on a single multi-locus sequence type (MLST) clonal complex 395 (CC395). A phylogenetic network was constructed to identify different lineages, followed by analysis of variability in gene sets and sequences. Serotype 6C isolates from this single geographical site fell into four broad phylogenetically distinct lineages. Variation was seen in the 6C capsular locus and in sequences of genes encoding surface proteins. The largest clonal complex was characterised by the presence of lantibiotic synthesis locus. In our population, the 6C capsular locus has been introduced into multiple lineages by independent capsular switching events. However, rapid clonal expansion has occurred within a single MLST clonal complex. Worryingly, plasticity exists within current and potential vaccine-associated loci, a consideration for future vaccine use, target selection and design
A structured population model of clonal selection in acute leukemias with multiple maturation stages
Funding: TS and AM-C were supported by research funding from the German Research Foundation DFG (SFB 873; subproject B08). TL gratefully acknowledges support from the Heidelberg Graduate School (HGS).Recent progress in genetic techniques has shed light on the complex co-evolution of malignant cell clones in leukemias. However, several aspects of clonal selection still remain unclear. In this paper, we present a multi-compartmental continuously structured population model of selection dynamics in acute leukemias, which consists of a system of coupled integro-differential equations. Our model can be analysed in a more efficient way than classical models formulated in terms of ordinary differential equations. Exploiting the analytical tractability of this model, we investigate how clonal selection is shaped by the self-renewal fraction and the proliferation rate of leukemic cells at different maturation stages. We integrate analytical results with numerical solutions of a calibrated version of the model based on real patient data. In summary, our mathematical results formalise the biological notion that clonal selection is driven by the self-renewal fraction of leukemic stem cells and the clones that possess the highest value of this parameter are ultimately selected. Moreover, we demonstrate that the self-renewal fraction and the proliferation rate of non-stem cells do not have a substantial impact on clonal selection. Taken together, our results indicate that interclonal variability in the self-renewal fraction of leukemic stem cells provides the necessary substrate for clonal selection to act upon.PostprintPeer reviewe
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