Effective Sample Size: Quick Estimation of the Effect of Related Samples in Genetic Case-Control Association Analyses

Correlated samples have been frequently avoided in case-control
genetic association
 studies in part because the methods for handling them are either not
easily implemented or not widely known. We
advocate one method for case-control association analysis of correlated
samples -- the effective sample size method -- as a simple and
accessible approach that does not require specialized computer programs.
The effective sample size method captures the variance inflation
of allele frequency estimation exactly, and can be used to modify the
chi-square test statistic, p-value, and 95% confidence interval of
odds-ratio simply by replacing the apparent number of allele counts with the
effective ones. For genotype frequency estimation, although a single
effective sample size is unable to completely characterize the variance inflation,
an averaged one can satisfactorily approximate the simulated result.
The effective sample size method is applied to the rheumatoid arthritis
siblings data collected from the North American Rheumatoid Arthritis Consortium (NARAC)
to establish a significant association with the interferon-induced
helicasel gene (IFIH1) previously being identified as a type 1 diabetes
susceptibility locus. Connections between the effective sample size
method and other methods, such as generalized estimation equation,
variance of eigenvalues for correlation matrices, and genomic controls,
are also discussed.
&#xa

Isochores Merit the Prefix 'Iso'

The isochore concept in human genome sequence was challenged in an analysis by the International Human Genome Sequencing Consortium (IHGSC). We argue here that a statement in IGHSC analysis concerning the existence of isochore is incorrect, because it had applied an inappropriate statistical test. To test the existence of isochores should be equivalent to a test of homogeneity of windowed GC%. The statistical test applied in the IHGSC's analysis, the binomial test, is however a test of a sequence being random on the base level. For testing the existence of isochore, or homogeneity in GC%, we propose to use another statistical test: the analysis of variance (ANOVA). It can be shown that DNA sequences that are rejected by binomial test may not be rejected by the ANOVA test.Comment: 14 pages (including 1 figure), submitte

Application of Volcano Plots in Analyses of mRNA Differential Expressions with Microarrays

Volcano plot displays unstandardized signal (e.g. log-fold-change) against noise-adjusted/standardized signal (e.g. t-statistic or -log10(p-value) from the t test). We review the basic and an interactive use of the volcano plot, and its crucial role in understanding the regularized t-statistic. The joint filtering gene selection criterion based on regularized statistics has a curved discriminant line in the volcano plot, as compared to the two perpendicular lines for the "double filtering" criterion. This review attempts to provide an unifying framework for discussions on alternative measures of differential expression, improved methods for estimating variance, and visual display of a microarray analysis result. We also discuss the possibility to apply volcano plots to other fields beyond microarray.Comment: 8 figure

Spectral Analysis of Guanine and Cytosine Fluctuations of Mouse Genomic DNA

We study global fluctuations of the guanine and cytosine base content (GC%) in mouse genomic DNA using spectral analyses. Power spectra S(f) of GC% fluctuations in all nineteen autosomal and two sex chromosomes are observed to have the universal functional form S(f) \sim 1/f^alpha (alpha \approx 1) over several orders of magnitude in the frequency range 10^-7< f < 10^-5 cycle/base, corresponding to long-ranging GC% correlations at distances between 100 kb and 10 Mb. S(f) for higher frequencies (f > 10^-5 cycle/base) shows a flattened power-law function with alpha < 1 across all twenty-one chromosomes. The substitution of about 38% interspersed repeats does not affect the functional form of S(f), indicating that these are not predominantly responsible for the long-ranged multi-scale GC% fluctuations in mammalian genomes. Several biological implications of the large-scale GC% fluctuation are discussed, including neutral evolutionary history by DNA duplication, chromosomal bands, spatial distribution of transcription units (genes), replication timing, and recombination hot spots.Comment: 15 pages (figures included), 2 figure

An Shp2/SFK/Ras/Erk Signaling Pathway Controls Trophoblast Stem Cell Survival

SummaryLittle is known about how growth factors control tissue stem cell survival and proliferation. We analyzed mice with a null mutation of Shp2 (Ptpn11), a key component of receptor tyrosine kinase signaling. Null embryos die peri-implantation, much earlier than mice that express an Shp2 truncation. Shp2 null blastocysts initially develop normally, but they subsequently exhibit inner cell mass death, diminished numbers of trophoblast giant cells, and failure to yield trophoblast stem (TS) cell lines. Molecular markers reveal that the trophoblast lineage, which requires fibroblast growth factor-4 (FGF4), is specified but fails to expand normally. Moreover, deletion of Shp2 in TS cells causes rapid apoptosis. We show that Shp2 is required for FGF4-evoked activation of the Src/Ras/Erk pathway that culminates in phosphorylation and destabilization of the proapoptotic protein Bim. Bim depletion substantially blocks apoptosis and significantly restores Shp2 null TS cell proliferation, thereby establishing a key mechanism by which FGF4 controls stem cell survival

New stopping criteria for segmenting DNA sequences

We propose a solution on the stopping criterion in segmenting inhomogeneous DNA sequences with complex statistical patterns. This new stopping criterion is based on Bayesian Information Criterion (BIC) in the model selection framework. When this stopping criterion is applied to a left telomere sequence of yeast Saccharomyces cerevisiae and the complete genome sequence of bacterium Escherichia coli, borders of biologically meaningful units were identified (e.g. subtelomeric units, replication origin, and replication terminus), and a more reasonable number of domains was obtained. We also introduce a measure called segmentation strength which can be used to control the delineation of large domains. The relationship between the average domain size and the threshold of segmentation strength is determined for several genome sequences.Comment: 4 pages, 4 figures, Physical Review Letters, to appea

SHP2 Regulates the Osteogenic Fate of Growth Plate Hypertrophic Chondrocytes

Transdifferentiation of hypertrophic chondrocytes into bone-forming osteoblasts has been reported, yet the underlying molecular mechanism remains incompletely understood. SHP2 is an ubiquitously expressed cytoplasmic protein tyrosine phosphatase. SHP2 loss-of-function mutations in chondroid cells are linked to metachondromatosis in humans and mice, suggesting a crucial role for SHP2 in the skeleton. However, the specific role of SHP2 in skeletal cells has not been elucidated. To approach this question, we ablated SHP2 in collagen 2α1(Col2α1)-Cre- and collagen 10α1(Col10α1)-Cre-expressing cells, predominantly proliferating and hypertrophic chondrocytes, using “Cre-loxP”-mediated gene excision. Mice lacking SHP2 in Col2α1-Cre-expressing cells die at mid-gestation. Postnatal SHP2 ablation in the same cell population caused dwarfism, chondrodysplasia and exostoses. In contrast, mice in which SHP2 was ablated in the Col10α1-Cre-expressing cells appeared normal but were osteopenic. Further mechanistic studies revealed that SHP2 exerted its influence partly by regulating the abundance of SOX9 in chondrocytes. Elevated and sustained SOX9 in SHP2-deficient hypertrophic chondrocytes impaired their differentiation to osteoblasts and impaired endochondral ossification. Our study uncovered an important role of SHP2 in bone development and cartilage homeostasis by influencing the osteogenic differentiation of hypertrophic chondrocytes and provided insight into the pathogenesis and potential treatment of skeletal diseases, such as osteopenia and osteoporosis

Roadmap on printable electronic materials for next-generation sensors

The dissemination of sensors is key to realizing a sustainable, ‘intelligent’ world, where everyday objects and environments are equipped with sensing capabilities to advance the sustainability and quality of our lives—e.g., via smart homes, smart cities, smart healthcare, smart logistics, Industry 4.0, and precision agriculture. The realization of the full potential of these applications critically depends on the availability of easy-to-make, low-cost sensor technologies. Sensors based on printable electronic materials offer the ideal platform: they can be fabricated through simple methods (e.g., printing and coating) and are compatible with high-throughput roll-to-roll processing. Moreover, printable electronic materials often allow the fabrication of sensors on flexible/stretchable/biodegradable substrates, thereby enabling the deployment of sensors in unconventional settings. Fulfilling the promise of printable electronic materials for sensing will require materials and device innovations to enhance their ability to transduce external stimuli—light, ionizing radiation, pressure, strain, force, temperature, gas, vapours, humidity, and other chemical and biological analytes. This Roadmap brings together the viewpoints of experts in various printable sensing materials—and devices thereof—to provide insights into the status and outlook of the field. Alongside recent materials and device innovations, the roadmap discusses the key outstanding challenges pertaining to each printable sensing technology. Finally, the Roadmap points to promising directions to overcome these challenges and thus enable ubiquitous sensing for a sustainable, ‘intelligent’ world