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Almudevar A.,University of Rochester | Lacombe J.,Nature Source Genetics
IEEE Transactions on Signal Processing | Year: 2012

A signal processing algorithm for the estimation of the trajectory of amobile transmitter in a wireless network, based on RSSI measurements, was proposed in [A. Almudevar, "Approximate calibration-free trajectory reconstruction in a wireless network," IEEE Trans. Signal Process., vol. 56, no. 7, pp. 3081-3088, 2008]. The problem of explicit transmission source location estimation is bypassed, producing instead an estimation of the trajectory shape which does not require a translation of RSSI measurements into transmission distance estimates. It was proven for the case of k = 3 receivers that the resulting mapping of the source to an estimation region is 1 - 1 and continuous while preserving directionality and providing robustness to measurement distortion. The purpose of this correspondence is to extend these results to the general k ≥ 3 case. The method is demonstrated using a commercial RSSI home monitoring system using k = 4 receivers. © 2012 IEEE.


Sheehan M.J.,Nature Source Genetics | Pawlowski W.P.,Cornell University
Methods in Enzymology | Year: 2012

Progression of meiosis has been traditionally reconstructed from microscopic images collected from fixed cells. This approach has clear shortcomings in accurately portraying the dynamics of meiotic processes. Studies conducted in recent years mostly in unicellular fungi have shown that chromosomes in meiotic prophase exhibit dynamic motility that cannot be accurately examined using fixed cell imaging. However, in contrast to yeast, research on meiotic chromosome dynamics in multicellular eukaryotes has been lagging. This was in part because meiocytes in multicellular eukaryotes reside deep within reproductive organs and are often refractory to culturing. Here, we describe a method in which intact, live-plant reproductive organs (anthers) are cultured to enable monitoring chromosome dynamics of meiocytes using multiphoton excitation (MPE) microscopy. The method was developed for use in maize but can be applied to other plant species and adapted for use in other taxa in which meiocytes are embedded in multicellular reproductive structures. MPE microscopy allows visualization of meiocytes embedded within native tissue in planta and thus meiocytes remain intact for the entire imaging procedure. We detail the kinds of time-lapse movies that can be captured and analyzed using this technique and also highlight software packages that can be utilized for analysis of movies chromosome dynamic in live meiocytes. © 2012 Elsevier Inc.


PubMed | University of Minnesota, University of Saskatchewan, PepsiCo and Nature Source Genetics
Type: Journal Article | Journal: TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik | Year: 2016

Using next-generation DNA sequencing, it was possible to clarify the genetic relationships of Avena species and deduce the likely pathway from which hexaploid oat was formed by sequential polyploidization events. A sequence-based diversity study was conducted on a representative sample of accessions from species in the genus Avena using genotyping-by-sequencing technology. The results show that all Avena taxa can be assigned to one of four major genetic clusters: Cluster 1=all hexaploids including cultivated oat, Cluster 2=AC genome tetraploids, Cluster 3=C genome diploids, Cluster 4=A genome diploid and tetraploids. No evidence was found for the existence of discrete B or D genomes. Through a series of experiments involving the creation of in silico polyploids, it was possible to deduce that hexaploid oat likely formed by the fusion of an ancestral diploid species from Cluster 3 (A. clauda, A. eriantha) with an ancestral diploid species from Cluster 4D (A. longiglumis, A. canariensis, A. wiestii) to create the ancestral tetraploid from Cluster 2 (A. magna, A. murphyi, A. insularis). Subsequently, that ancestral tetraploid fused again with another ancestral diploid from Cluster 4D to create hexaploid oat. Based on the geographic distribution of these species, it is hypothesized that both the tetraploidization and hexaploidization events may have occurred in the region of northwest Africa, followed by radiation of hexaploid oat to its current worldwide distribution. The results from this study shed light not only on the origins of this important grain crop, but also have implications for germplasm collection and utilization in oat breeding.


Hunter S.R.,Purdue University | McClosky B.,Nature Source Genetics
IIE Transactions (Institute of Industrial Engineers) | Year: 2016

Commercial plant breeders improve economically important traits by selectively mating individuals from a given breeding population. Potential pairings are evaluated before the growing season using Monte Carlo simulation, and a mating design is created to allocate a fixed breeding budget across the parent pairs to achieve desired population outcomes. We introduce a novel objective function for this mating design problem that accurately models the goals of a certain class of breeding experiments. The resulting mating design problem is a computationally burdensome simulation optimization problem on a combinatorially large set of feasible points. We propose a two-step solution to this problem: (i) simulate to estimate the performance of each parent pair and (ii) solve an estimated version of the mating design problem, which is an integer program, using the simulation output. To reduce the computational burden when implementing steps (i) and (ii), we analytically identify a Pareto set of parent pairs that will receive the entire breeding budget at optimality. Since we wish to estimate the Pareto set in step (i) as input to step (ii), we derive an asymptotically optimal simulation budget allocation to estimate the Pareto set that, in our numerical experiments, out-performs Multi-objective Optimal Computing Budget Allocation in reducing misclassifications. Given the estimated Pareto set, we provide a branch-and-bound algorithm to solve the estimated mating design problem. Our approach dramatically reduces the computational effort required to solve the mating design problem when compared with naïve methods. Copyright © 2016 “IIE”


LaCombe J.,Nature Source Genetics | McClosky B.,Nature Source Genetics | Tanksley S.,Nature Source Genetics
G3: Genes, Genomes, Genetics | Year: 2012

The Churchill-Doerge approach toward constructing empirical thresholds has received widespread use in the genetic mapping literature through the past 16 years. The method is valued for both its simplicity and its ability to preserve the genome-wide error rate at a prespecified level. However, the Churchill-Doerge method is not designed to maintain the local (comparison-wise) error rate at a constant level except in situations that are unlikely to occur in practice. In this article, we introduce the objective of preserving the local error rate at a constant level in the context of mapping quantitative trait loci in linkage populations. We derive a method that preserves the local error rate at a constant level, provide an application via simulation on a Hordeum vulgare population, and demonstrate evidence of the relationship between recombination and location bias. Furthermore, we indicate that this method is equivalent to the Churchill-Doerge method when several assumptions are satisfied. © 2012 LaCombe et al.


McClosky B.,Nature Source Genetics | LaCombe J.,Nature Source Genetics | Tanksley S.D.,Nature Source Genetics
Theoretical and Applied Genetics | Year: 2013

Self-fertilization (selfing) is commonly used for population development in plant breeding, and it is well established that selfing increases genetic variance between lines, thus increasing response to phenotypic selection. Furthermore, numerous studies have explored how selfing can be deployed to maximal benefit in the context of traditional plant breeding programs (Cornish in Heredity 65:201-211,1990a, Heredity 65:213-220,1990b; Liu et al. in Theor Appl Genet 109:370-376, 2004; Pooni and Jinks in Heredity 54:255-260, 1985). However, the impact of selfing on response to genomic selection has not been explored. In the current study we examined how selfing impacts the two key aspects of genomic selection-GEBV prediction (training) and selection response. We reach the following conclusions: (1) On average, selfing increases genomic selection gains by more than 70 %. (2) The gains in genomic selection response attributable to selfing hold over a wide range population sizes (100-500), heritabilities (0.2-0.8), and selection intensities (0.01-0.1). However, the benefits of selfing are dramatically reduced as the number of QTLs drops below 20. (3) The major cause of the improved response to genomic selection with selfing is through an increase in the occurrence of superior genotypes and not through improved GEBV predictions. While performance of the training population improves with selfing (especially with low heritability and small population sizes), the magnitude of these improvements is relatively small compared with improvements observed in the selection population. To illustrate the value of these insights, we propose a practical genomic selection scheme that substantially shortens the number of generations required to fully capture the benefits of selfing. Specifically, we provide simulation evidence that indicates the proposed scheme matches or exceeds the selection gains observed in advanced populations (i.e. F8 and doubled haploid) across a broad range of heritability and QTL models. Without sacrificing selection gains, we also predict that fully inbred candidates for potential commercialization can be identified as early as the F4 generation. © 2013 Springer-Verlag Berlin Heidelberg.


McClosky B.,Nature Source Genetics | Tanksley S.D.,Nature Source Genetics
Theoretical and Applied Genetics | Year: 2013

Recombination is a requirement for response to selection, but researchers still debate whether increasing recombination beyond normal levels will result in significant gains in short-term selection. We tested this hypothesis, in the context of plant breeding, through a series of simulation experiments comparing short-term selection response (≤20 cycles) between populations with normal levels of recombination and similar populations with unconstrained recombination (i.e., free recombination). We considered additive and epistatic models and examined a wide range of values for key design variables: selection cycles, QTL number, heritability, linkage phase, selection intensity and population size. With few exceptions, going from normal to unconstrained levels of recombination produced only modest gains in response to selection (≈11 % on average). We then asked how breeders might capture some of this theoretical gain by increasing recombination through either (1) extra rounds of mating or (2) selection of highly recombinant individuals via use of molecular markers/maps. All methods tested captured less than half of the potential gain, but our analysis indicates that the most effective method is to select for increased recombination and the trait simultaneously. This recommendation is based on evidence of a favorable interaction between trait selection and the impact of recombination on selection gains. Finally, we examined the relative contributions of the two components of meiotic recombination, chromosome assortment and crossing over, to short-term selection gain. Depending primarily on the presence of trait selection pressure, chromosome assortment alone accounted for 40-75 % of gain in response to short-term selection. © 2013 Springer-Verlag Berlin Heidelberg.


McClosky B.,Nature Source Genetics | Ma X.,Nature Source Genetics | Tanksley S.D.,Nature Source Genetics
Statistical Applications in Genetics and Molecular Biology | Year: 2011

Basic statistical theory implies that genotypic class cardinalities play a strong role in determining power to detect QTL, but the classes do not contribute equal information to the model. For example, while it is generally accepted that homozygotes contribute more to the detection of additive effects, heterozygotes are necessary to detect dominance effects. The literature on QTL detection often mentions the importance of genotypic class sizes in passing (Belknap (1998); Belknap et al. (1996); Jin et al. (2004); Kliebenstein (2007); Kao (2006); Martinez et al. (2002)), but no rigorous study of their relative values appears to exist. The purpose of this paper is to quantify the relative contribution of the heterozygous class. Researchers can use these results in evaluating the tradeoff between gain in statistical power and the cost of developing populations with specified genotypic class sizes. In addition, we arrive at the surprising conclusion that a misspecified additive model often outperforms a full model that incorporates dominance. This result is significant because standard software packages normally use the full model by default. Copyright © 2011 Berkeley Electronic Press. All rights reserved.


LaCombe J.,Nature Source Genetics
G3 (Bethesda, Md.) | Year: 2012

The Churchill-Doerge approach toward constructing empirical thresholds has received widespread use in the genetic mapping literature through the past 16 years. The method is valued for both its simplicity and its ability to preserve the genome-wide error rate at a prespecified level. However, the Churchill-Doerge method is not designed to maintain the local (comparison-wise) error rate at a constant level except in situations that are unlikely to occur in practice. In this article, we introduce the objective of preserving the local error rate at a constant level in the context of mapping quantitative trait loci in linkage populations. We derive a method that preserves the local error rate at a constant level, provide an application via simulation on a Hordeum vulgare population, and demonstrate evidence of the relationship between recombination and location bias. Furthermore, we indicate that this method is equivalent to the Churchill-Doerge method when several assumptions are satisfied.


PubMed | Nature Source Genetics
Type: Journal Article | Journal: TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik | Year: 2013

Recombination is a requirement for response to selection, but researchers still debate whether increasing recombination beyond normal levels will result in significant gains in short-term selection. We tested this hypothesis, in the context of plant breeding, through a series of simulation experiments comparing short-term selection response (20 cycles) between populations with normal levels of recombination and similar populations with unconstrained recombination (i.e., free recombination). We considered additive and epistatic models and examined a wide range of values for key design variables: selection cycles, QTL number, heritability, linkage phase, selection intensity and population size. With few exceptions, going from normal to unconstrained levels of recombination produced only modest gains in response to selection (11% on average). We then asked how breeders might capture some of this theoretical gain by increasing recombination through either (1) extra rounds of mating or (2) selection of highly recombinant individuals via use of molecular markers/maps. All methods tested captured less than half of the potential gain, but our analysis indicates that the most effective method is to select for increased recombination and the trait simultaneously. This recommendation is based on evidence of a favorable interaction between trait selection and the impact of recombination on selection gains. Finally, we examined the relative contributions of the two components of meiotic recombination, chromosome assortment and crossing over, to short-term selection gain. Depending primarily on the presence of trait selection pressure, chromosome assortment alone accounted for 40-75% of gain in response to short-term selection.

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