Genetical genomics: spotlight on QTL hotspots

No abstract available

A comparison of hominin teeth from Lincoln Cave, Sterkfontein L/63, and the Dinaledi Chamber, South Africa

Prior to the recovery of Homo naledi from the Dinaledi Chamber of the Rising Star Cave system, the Middle Pleistocene fossil record in Africa was particularly sparse. With the large sample size now available from Dinaledi, the opportunity exists to reassess taxonomically ambiguous teeth unearthed at the nearby site of Sterkfontein. Teeth recovered from Lincoln Cave South and area L/63 at Sterkfontein have been considered ‘most probably Homo ergaster’ and ‘perhaps Archaic Homo sapiens’, respectively. Given the similarities shared between Lincoln Cave, area L/63, and the Dinaledi Chamber with regard to climatic/geologic depositional context and age, two teeth from the former sites, StW 592 and StW 585 respectively, were compared with corresponding tooth types of H. naledi from the Dinaledi Chamber. The results of our study indicate that the Lincoln Cave and area L/63 teeth are morphologically inconsistent with the variation recognised in the H. naledi teeth

A Systems Biology Approach Identifies a R2R3 MYB Gene Subfamily with Distinct and Overlapping Functions in Regulation of Aliphatic Glucosinolates

BACKGROUND: Glucosinolates are natural metabolites in the order Brassicales that defend plants against both herbivores and pathogens and can attract specialized insects. Knowledge about the genes controlling glucosinolate regulation is limited. Here, we identify three R2R3 MYB transcription factors regulating aliphatic glucosinolate biosynthesis in Arabidopsis by combining several systems biology tools. METHODOLOGY/PRINCIPAL FINDINGS: MYB28 was identified as a candidate regulator of aliphatic glucosinolates based on its co-localization within a genomic region controlling variation both in aliphatic glucosinolate content (metabolite QTL) and in transcript level for genes involved in the biosynthesis of aliphatic glucosinolates (expression QTL), as well as its co-expression with genes in aliphatic glucosinolate biosynthesis. A phylogenetic analysis with the R2R3 motif of MYB28 showed that it and two homologues, MYB29 and MYB76, were members of an Arabidopsis-specific clade that included three characterized regulators of indole glucosinolates. Over-expression of the individual MYB genes showed that they all had the capacity to increase the production of aliphatic glucosinolates in leaves and seeds and induce gene expression of aliphatic biosynthetic genes within leaves. Analysis of leaves and seeds of single knockout mutants showed that mutants of MYB29 and MYB76 have reductions in only short-chained aliphatic glucosinolates whereas a mutant in MYB28 has reductions in both short- and long-chained aliphatic glucosinolates. Furthermore, analysis of a double knockout in MYB28 and MYB29 identified an emergent property of the system since the absence of aliphatic glucosinolates in these plants could not be predicted by the chemotype of the single knockouts. CONCLUSIONS/SIGNIFICANCE: It seems that these cruciferous-specific MYB regulatory genes have evolved both overlapping and specific regulatory capacities. This provides a unique system within which to study the evolution of MYB regulatory factors and their downstream targets

Comparison of performance of one-color and two-color gene-expression analyses in predicting clinical endpoints of neuroblastoma patients

Microarray-based prediction of clinical endpoints may be performed using either a one-color approach reflecting mRNA abundance in absolute intensity values or a two-color approach yielding ratios of fluorescent intensities. In this study, as part of the MAQC-II project, we systematically compared the classification performance resulting from one- and two-color gene-expression profiles of 478 neuroblastoma samples. In total, 196 classification models were applied to these measurements to predict four clinical endpoints, and classification performances were compared in terms of accuracy, area under the curve, Matthews correlation coefficient and root mean-squared error. Whereas prediction performance varied with distinct clinical endpoints and classification models, equivalent performance metrics were observed for one- and two-color measurements in both internal and external validation. Furthermore, overlap of selected signature genes correlated inversely with endpoint prediction difficulty. In summary, our data strongly substantiate that the choice of platform is not a primary factor for successful gene expression based-prediction of clinical endpoints

Identification of QTLs controlling gene expression networks defined a priori

BACKGROUND: Gene expression microarrays allow the quantification of transcript accumulation for many or all genes in a genome. This technology has been utilized for a range of investigations, from assessments of gene regulation in response to genetic or environmental fluctuation to global expression QTL (eQTL) analyses of natural variation. Current analysis techniques facilitate the statistical querying of individual genes to evaluate the significance of a change in response, also known as differential expression. Since genes are also known to respond as groups due to their membership in networks, effective approaches are needed to investigate transcriptome variation as related to gene network responses. RESULTS: We describe a statistical approach that is capable of assessing higher-order a priori defined gene network response, as measured by microarrays. This analysis detected significant network variation between two Arabidopsis thaliana accessions, Bay-0 and Shahdara. By extending this approach, we were able to identify eQTLs controlling network responses for 18 out of 20 a priori-defined gene networks in a recombinant inbred line population derived from accessions Bay-0 and Shahdara. CONCLUSION: This approach has the potential to be expanded to facilitate direct tests of the relationship between phenotypic trait and transcript genetic architecture. The use of a priori definitions for network eQTL identification has enormous potential for providing direction toward future eQTL analyses

Field-adapted sampling of whole blood to determine the levels of amodiaquine and its metabolite in children with uncomplicated malaria treated with amodiaquine plus artesunate combination

<p>Abstract</p> <p>Background</p> <p>Artemisinin combination therapy (ACT) has been widely adopted as first-line treatment for uncomplicated falciparum malaria. In Uganda, amodiaquine plus artesunate (AQ+AS), is the alternative first-line regimen to Coartem^®(artemether + lumefantrine) for the treatment of uncomplicated falciparum malaria. Currently, there are few field-adapted analytical techniques for monitoring amodiaquine utilization in patients. This study evaluates the field applicability of a new method to determine amodiaquine and its metabolite concentrations in whole blood dried on filter paper.</p> <p>Methods</p> <p>Twelve patients aged between 1.5 to 8 years with uncomplicated malaria received three standard oral doses of AQ+AS. Filter paper blood samples were collected before drug intake and at six different time points over 28 days period. A new field-adapted sampling procedure and liquid chromatographic method was used for quantitative determination of amodiaquine and its metabolite in whole blood.</p> <p>Results</p> <p>The sampling procedure was successively applied in the field. Amodiaquine could be quantified for at least three days and the metabolite up to 28 days. All parasites in all the 12 patients cleared within the first three days of treatment and no adverse drug effects were observed.</p> <p>Conclusion</p> <p>The methodology is suitable for field studies. The possibility to determine the concentration of the active metabolite of amodiaquine up to 28 days suggested that the method is sensitive enough to monitor amodiaquine utilization in patients. Amodiaquine plus artesunate seems effective for treatment of falciparum malaria.</p

Human bipedal instability in tree canopy environments is reduced by “light touch” fingertip support

Whether tree canopy habitats played a sustained role in the ecology of ancestral bipedal hominins is unresolved. Some argue that arboreal bipedalism was prohibitively risky for hominins whose increasingly modern anatomy prevented them from gripping branches with their feet. Balancing on two legs is indeed challenging for humans under optimal conditions let alone in forest canopy, which is physically and visually highly dynamic. Here we quantify the impact of forest canopy characteristics on postural stability in humans. Viewing a movie of swaying branches while standing on a branch-like bouncy springboard destabilised the participants as much as wearing a blindfold. However “light touch”, a sensorimotor feedback strategy based on light fingertip support, significantly enhanced their balance and lowered their thigh muscle activity by up to 30%. This demonstrates how a light touch strategy could have been central to our ancestor’s ability to avoid falls and reduce the mechanical and metabolic cost of arboreal feeding and movement. Our results may also indicate that some adaptations in the hand that facilitated continued access to forest canopy may have complemented, rather than opposed, adaptations that facilitated precise manipulation and tool use

Temperature, recreational fishing and diapause egg connections : dispersal of spiny water fleas (Bythotrephes longimanus)

© The Author(s), 2011. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License. The definitive version was published in Biological Invasions 13 (2011): 2513-2531, doi:10.1007/s10530-011-0078-8.The spiny water flea (Bythotrephes longimanus) is spreading from Great Lakes coastal waters into northern inland lakes within a northern temperature-defined latitudinal band. Colonization of Great Lakes coastal embayments is assisted by winds and seiche surges, yet rapid inland expansion across the northern states comes through an overland process. The lack of invasions at Isle Royale National Park contrasts with rapid expansion on the nearby Keweenaw Peninsula. Both regions have comparable geology, lake density, and fauna, but differ in recreational fishing boat access, visitation, and containment measures. Tail spines protect Bythotrephes against young of the year, but not larger fish, yet the unusual thick-shelled diapausing eggs can pass through fish guts in viable condition. Sediment traps illustrate how fish spread diapausing eggs across lakes in fecal pellets. Trillions of diapausing eggs are produced per year in Lake Michigan and billions per year in Lake Michigamme, a large inland lake. Dispersal by recreational fishing is linked to use of baitfish, diapausing eggs defecated into live wells and bait buckets, and Bythothephes snagged on fishing line, anchor ropes, and minnow seines. Relatively simple measures, such as on-site rinsing of live wells, restricting transfer of certain baitfish species, or holding baitfish for 24 h (defecation period), should greatly reduce dispersal.Study of Lakes Superior and Michigan was funded from NSF OCE-9726680 and OCE-9712872 to W.C.K., OCE-9712889 to J. Churchill. Geographic survey sampling and Park studies in the national parks during 2008-2010 were funded by a grant from the National Park Service Natural Resource Preservation Program GLNF CESU Task Agreement No. J6067080012

What Can Causal Networks Tell Us about Metabolic Pathways?

Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: “What can causal networks tell us about metabolic pathways?”. Using data from an Arabidopsis BaySha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies

Haplotype-based quantitative trait mapping using a clustering algorithm

BACKGROUND: With the availability of large-scale, high-density single-nucleotide polymorphism (SNP) markers, substantial effort has been made in identifying disease-causing genes using linkage disequilibrium (LD) mapping by haplotype analysis of unrelated individuals. In addition to complex diseases, many continuously distributed quantitative traits are of primary clinical and health significance. However the development of association mapping methods using unrelated individuals for quantitative traits has received relatively less attention. RESULTS: We recently developed an association mapping method for complex diseases by mining the sharing of haplotype segments (i.e., phased genotype pairs) in affected individuals that are rarely present in normal individuals. In this paper, we extend our previous work to address the problem of quantitative trait mapping from unrelated individuals. The method is non-parametric in nature, and statistical significance can be obtained by a permutation test. It can also be incorporated into the one-way ANCOVA (analysis of covariance) framework so that other factors and covariates can be easily incorporated. The effectiveness of the approach is demonstrated by extensive experimental studies using both simulated and real data sets. The results show that our haplotype-based approach is more robust than two statistical methods based on single markers: a single SNP association test (SSA) and the Mann-Whitney U-test (MWU). The algorithm has been incorporated into our existing software package called HapMiner, which is available from our website at . CONCLUSION: For QTL (quantitative trait loci) fine mapping, to identify QTNs (quantitative trait nucleotides) with realistic effects (the contribution of each QTN less than 10% of total variance of the trait), large samples sizes (≥ 500) are needed for all the methods. The overall performance of HapMiner is better than that of the other two methods. Its effectiveness further depends on other factors such as recombination rates and the density of typed SNPs. Haplotype-based methods might provide higher power than methods based on a single SNP when using tag SNPs selected from a small number of samples or some other sources (such as HapMap data). Rank-based statistics usually have much lower power, as shown in our study