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Russell L Malmberg

Publications and source records attributed to Russell L Malmberg.

8 recordsLinked to original sources

Genetic architecture of leaf ecophysiological traits in Helianthus.

We investigated quantitative trait loci (QTLs) for several leaf chemistry traits in early-generation hybrids between Helianthus annuus and Helianthus petiolaris, the parental species of the ancient diploid hybrid sunflower species Helianthus anomalus, Helianthus deserticola, and Helianthus paradoxus. We grew individuals of a second-generation backcross (BC(2)) toward H. petiolaris under optimum conditions in a glass house experiment. Trait values were measured once for each individual. In addition, genotypic data previously determined for each individual were employed for composite interval mapping of QTLs. We detected QTLs for leaf carbon concentration, leaf nitrogen concentration, leaf nitrogen per unit area, and photosynthetic nitrogen use efficiency. Leaf carbon isotope discrimination (delta(13)C) and leaf nitrogen isotopic composition (delta(15)N) were analyzed, but no significant QTLs were found for these traits. Interestingly, two neighboring loci explained a relatively large percentage of the variation in leaf nitrogen per unit area. This was notable because leaf nitrogen has been shown to strongly affect the fitness of early-generation sunflower hybrids in the H. anomalus habitat, and QTLs of large effect are expected to respond relatively quickly to selection. We speculate that the genetic architecture underlying leaf nitrogen may have facilitated the colonization of active desert sand dunes by H. anomalus.

Carbon↗

Epistasis for fitness-related quantitative traits in Arabidopsis thaliana grown in the field and in the greenhouse.

The extent to which epistasis contributes to adaptation, population differentiation, and speciation is a long-standing and important problem in evolutionary genetics. Using recombinant inbred (RI) lines of Arabidopsis thaliana grown under natural field conditions, we have examined the genetic architecture of fitness-correlated traits with respect to epistasis; we identified both single-locus additive and two-locus epistatic QTL for natural variation in fruit number, germination, and seed length and width. For fruit number, we found seven significant epistatic interactions, but only two additive QTL. For seed germination, length, and width, there were from two to four additive QTL and from five to eight epistatic interactions. The epistatic interactions were both positive and negative. In each case, the magnitude of the epistatic effects was roughly double that of the effects of the additive QTL, varying from -41% to +29% for fruit number and from -5% to +4% for seed germination, length, and width. A number of the QTL that we describe participate in more than one epistatic interaction, and some loci identified as additive also may participate in an epistatic interaction; the genetic architecture for fitness traits may be a network of additive and epistatic effects. We compared the map positions of the additive and epistatic QTL for germination, seed width, and seed length from plants grown in both the field and the greenhouse. While the total number of significant additive and epistatic QTL was similar under the two growth conditions, the map locations were largely different. We found a small number of significant epistatic QTL x environment effects when we tested directly for them. Our results support the idea that epistatic interactions are an important part of natural genetic variation and reinforce the need for caution in comparing results from greenhouse-grown and field-grown plants.

Arabidopsis↗

QTL-based evidence for the role of epistasis in evolution.

The extent to which epistasis contributes to adaptation and speciation has been a controversial topic in evolutionary genetics. One experimental approach to study epistasis is based on quantitative trait locus (QTL) mapping using molecular markers. Comparisons can be made among all possible pair-wise combinations of the markers, irrespective of whether an additive QTL is associated with a marker; several software packages have been developed that facilitate this. We review several examples of using this approach to identify epistatic QTLs for traits of evolutionary or ecological interest. While there is variability in the results, the number of epistatic QTL interactions is often greater than or equal to the number of additive QTLs. The magnitude of epistatic effects can be larger than the additive effects. Thus, epistatic interactions seem to be an important part of natural genetic variation. Future studies of epistatic QTLs could lead to descriptions of the genetic networks underlying variation for fitness-related traits.

Animals↗

A standardized kinesin nomenclature.

In recent years the kinesin superfamily has become so large that several different naming schemes have emerged, leading to confusion and miscommunication. Here, we set forth a standardized kinesin nomenclature based on 14 family designations. The scheme unifies all previous phylogenies and nomenclature proposals, while allowing individual sequence names to remain the same, and for expansion to occur as new sequences are discovered.

Animals↗

LumberJack: a heuristic tool for sequence alignment exploration and phylogenetic inference.

SUMMARY: LumberJack is a phylogenetic tool intended to serve two purposes: to facilitate sampling treespace to find likely tree topologies quickly, and to map phylogenetic signal onto regions of an alignment in a revealing way. LumberJack creates non-random jackknifed alignments by progressively sliding a window of omission along the alignment. A neighbor-joining tree is built from the full alignment and from each jackknifed alignment, and then the likelihood for each topology (given the original full alignment) is calculated. To determine whether any of the topologies generated is significantly more likely than the others, Kishino-Hasegawa, Shimodaira-Hasegawa and ELW tests are implemented. Availability and SUPPLEMENTARY INFORMATION: http://www.plantbio.uga.edu/~russell/software.html

Algorithms↗

Stochastic modeling of RNA pseudoknotted structures: a grammatical approach.

MOTIVATION: Modeling RNA pseudoknotted structures remains challenging. Methods have previously been developed to model RNA stem-loops successfully using stochastic context-free grammars (SCFG) adapted from computational linguistics; however, the additional complexity of pseudoknots has made modeling them more difficult. Formally a context-sensitive grammar is required, which would impose a large increase in complexity. RESULTS: We introduce a new grammar modeling approach for RNA pseudoknotted structures based on parallel communicating grammar systems (PCGS). Our new approach can specify pseudoknotted structures, while avoiding context-sensitive rules, using a single CFG synchronized with a number of regular grammars. Technically, the stochastic version of the grammar model can be as simple as an SCFG. As with SCFG, the new approach permits automatic generation of a single-RNA structure prediction algorithm for each specified pseudoknotted structure model. This approach also makes it possible to develop full probabilistic models of pseudoknotted structures to allow the prediction of consensus structures by comparative analysis and structural homology recognition in database searches.

Algorithms↗

Maximum likelihood methods reveal conservation of function among closely related kinesin families.

We have reconstructed the evolution of the anciently derived kinesin superfamily using various alignment and tree-building methods. In addition to classifying previously described kinesins from protists, fungi, and animals, we analyzed a variety of kinesin sequences from the plant kingdom including 12 from Zea mays and 29 from Arabidopsis thaliana. Also included in our data set were four sequences from the anciently diverged amitochondriate protist Giardia lamblia. The overall topology of the best tree we found is more likely than previously reported topologies and allows us to make the following new observations: (1) kinesins involved in chromosome movement including MCAK, chromokinesin, and CENP-E may be descended from a single ancestor; (2) kinesins that form complex oligomers are limited to a monophyletic group of families; (3) kinesins that crosslink antiparallel microtubules at the spindle midzone including BIMC, MKLP, and CENP-E are closely related; (4) Drosophila NOD and human KID group with other characterized chromokinesins; and (5) Saccharomyces SMY1 groups with kinesin-I sequences, forming a family of kinesins capable of class V myosin interactions. In addition, we found that one monophyletic clade composed exclusively of sequences with a C-terminal motor domain contains all known minus end-directed kinesins.

Animals↗

Efficient parameterized algorithms for biopolymer structure-sequence alignment.

Computational alignment of a biopolymer sequence (e.g., an RNA or a protein) to a structure is an effective approach to predict and search for the structure of new sequences. To identify the structure of remote homologs, the structure-sequence alignment has to consider not only sequence similarity, but also spatially conserved conformations caused by residue interactions and, consequently, is computationally intractable. It is difficult to cope with the inefficiency without compromising alignment accuracy, especially for structure search in genomes or large databases. This paper introduces a novel method and a parameterized algorithm for structure-sequence alignment. Both the structure and the sequence are represented as graphs, where, in general, the graph for a biopolymer structure has a naturally small tree width. The algorithm constructs an optimal alignment by finding in the sequence graph the maximum valued subgraph isomorphic to the structure graph. It has the computational time complexity O[k(t)N(2)] for the structure of N residues and its tree decomposition of width t. Parameter k, small in nature, is determined by a statistical cutoff for the correspondence between the structure and the sequence. This paper demonstrates a successful application of the algorithm to RNA structure search used for noncoding RNA identification. An application to protein threading is also discussed.

Algorithms↗