A large scale hearing loss screen reveals an extensive unexplored genetic landscape for auditory dysfunction

The developmental and physiological complexity of the auditory system is likely reflected in the underlying set of genes involved in auditory function. In humans, over 150 non-syndromic loci have been identified, and there are more than 400 human genetic syndromes with a hearing loss component. Over 100 non-syndromic hearing loss genes have been identified in mouse and human, but we remain ignorant of the full extent of the genetic landscape involved in auditory dysfunction. As part of the International Mouse Phenotyping Consortium, we undertook a hearing loss screen in a cohort of 3006 mouse knockout strains. In total, we identify 67 candidate hearing loss genes. We detect known hearing loss genes, but the vast majority, 52, of the candidate genes were novel. Our analysis reveals a large and unexplored genetic landscape involved with auditory function

The Potential of N-Rich Plasma-Polymerized Ethylene (PPE:N) Films for Regulating the Phenotype of the Nucleus Pulposus

We recently developed a nitrogen-rich plasma-polymerized biomaterial, designated “PPE:N” (N-doped plasma-polymerized ethylene) that is capable of suppressing cellular hypertrophy while promoting type I collagen and aggrecan expression in mesenchymal stem cells from osteoarthritis patients. We then hypothesized that these surfaces would form an ideal substrate on which the nucleus pulposus (NP) phenotype would be maintained. Recent evidence using microarrays showed that in young rats, the relative mRNA levels of glypican-3 (GPC3) and pleiotrophin binding factor (PTN) were significantly higher in nucleus pulposus (NP) compared to annulus fibrosus (AF) and articular cartilage. Furthermore, vimentin (VIM) mRNA levels were higher in NP versus articular cartilage. In contrast, the levels of expression of cartilage oligomeric matrix protein (COMP) and matrix gla protein precursor (MGP) were lower in NP compared to articular cartilage. The objective of this study was to compare the expression profiles of these genes in NP cells from fetal bovine lumbar discs when cultured on either commercial polystyrene (PS) tissue culture dishes or on PPE:N with time. We found that the expression of these genes varies with the concentration of N ([N]). More specifically, the expression of several genes of NP was sensitive to [N], with a decrease of GPC3, VIM, PTN, and MGP in function of decreasing [N]. The expression of aggrecan, collagen type I, and collagen type II was also studied: no significant differences were observed in the cells on different surfaces with different culture time. The results support the concept that PPE:N may be a suitable scaffold for the culture of NP cells. Further studies are however necessary to better understand their effects on cellular phenotypes

Comprehensive ECG reference intervals in C57BL/6N substrains provide a generalizable guide for cardiac electrophysiology studies in mice.

Reference ranges provide a powerful tool for diagnostic decision-making in clinical medicine and are enormously valuable for understanding normality in pre-clinical scientific research that uses in vivo models. As yet, there are no published reference ranges for electrocardiography (ECG) in the laboratory mouse. The first mouse-specific reference ranges for the assessment of electrical conduction are reported herein generated from an ECG dataset of unprecedented scale. International Mouse Phenotyping Consortium data from over 26,000 conscious or anesthetized C57BL/6N wildtype control mice were stratified by sex and age to develop robust ECG reference ranges. Interesting findings include that heart rate and key elements from the ECG waveform (RR-, PR-, ST-, QT-interval, QT corrected, and QRS complex) demonstrate minimal sexual dimorphism. As expected, anesthesia induces a decrease in heart rate and was shown for both inhalation (isoflurane) and injectable (tribromoethanol) anesthesia. In the absence of pharmacological, environmental, or genetic challenges, we did not observe major age-related ECG changes in C57BL/6N-inbred mice as the differences in the reference ranges of 12-week-old compared to 62-week-old mice were negligible. The generalizability of the C57BL/6N substrain reference ranges was demonstrated by comparison with ECG data from a wide range of non-IMPC studies. The close overlap in data from a wide range of mouse strains suggests that the C57BL/6N-based reference ranges can be used as a robust and comprehensive indicator of normality. We report a unique ECG reference resource of fundamental importance for any experimental study of cardiac function in mice

Nat Genet

The function of the majority of genes in the mouse and human genomes remains unknown. The mouse embryonic stem cell knockout resource provides a basis for the characterization of relationships between genes and phenotypes. The EUMODIC consortium developed and validated robust methodologies for the broad-based phenotyping of knockouts through a pipeline comprising 20 disease-oriented platforms. We developed new statistical methods for pipeline design and data analysis aimed at detecting reproducible phenotypes with high power. We acquired phenotype data from 449 mutant alleles, representing 320 unique genes, of which half had no previous functional annotation. We captured data from over 27,000 mice, finding that 83% of the mutant lines are phenodeviant, with 65% demonstrating pleiotropy. Surprisingly, we found significant differences in phenotype annotation according to zygosity. New phenotypes were uncovered for many genes with previously unknown function, providing a powerful basis for hypothesis generation and further investigation in diverse systems.Comment in : Genetic differential calculus. [Nat Genet. 2015] Comment in : Scaling up phenotyping studies. [Nat Biotechnol. 2015

Wavelet-based 3D reconstruction of microcalcification clusters from two mammographic views: new evidence that fractal tumors are malignant and Euclidean tumors are benign.

The 2D Wavelet-Transform Modulus Maxima (WTMM) method was used to detect microcalcifications (MC) in human breast tissue seen in mammograms and to characterize the fractal geometry of benign and malignant MC clusters. This was done in the context of a preliminary analysis of a small dataset, via a novel way to partition the wavelet-transform space-scale skeleton. For the first time, the estimated 3D fractal structure of a breast lesion was inferred by pairing the information from two separate 2D projected mammographic views of the same breast, i.e. the cranial-caudal (CC) and mediolateral-oblique (MLO) views. As a novelty, we define the "CC-MLO fractal dimension plot", where a "fractal zone" and "Euclidean zones" (non-fractal) are defined. 118 images (59 cases, 25 malignant and 34 benign) obtained from a digital databank of mammograms with known radiologist diagnostics were analyzed to determine which cases would be plotted in the fractal zone and which cases would fall in the Euclidean zones. 92% of malignant breast lesions studied (23 out of 25 cases) were in the fractal zone while 88% of the benign lesions were in the Euclidean zones (30 out of 34 cases). Furthermore, a Bayesian statistical analysis shows that, with 95% credibility, the probability that fractal breast lesions are malignant is between 74% and 98%. Alternatively, with 95% credibility, the probability that Euclidean breast lesions are benign is between 76% and 96%. These results support the notion that the fractal structure of malignant tumors is more likely to be associated with an invasive behavior into the surrounding tissue compared to the less invasive, Euclidean structure of benign tumors. Finally, based on indirect 3D reconstructions from the 2D views, we conjecture that all breast tumors considered in this study, benign and malignant, fractal or Euclidean, restrict their growth to 2-dimensional manifolds within the breast tissue

Sample 2D WTMM analysis of a second malignant breast lesion.

<p>Same analysis as presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0107580#pone-0107580-g002" target="_blank">Figure 2</a>, but on a different case.</p

The CC-MLO fractal dimension plot.

<p>Each case analyzed is plotted with the fractal dimension obtained from the MLO view as a function of the fractal dimension obtained from the CC view. A polygonal region is outlined, the inside of which is defined as the “fractal zone” while the outside is defined as the “Euclidean zone”. The dots represent malignant (red) and benign (green) cases.</p

Histograms of fractal dimension values.

<p>The frequency distributions of fractal dimensions, <i>D</i> (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0107580#pone.0107580.e035" target="_blank">Eq. (16)</a>) calculated for benign CC and MLO views (top) are drastically different than those calculated for the cancer CC and MLO views (bottom).</p

The 2D WTMM Method.

<p>(A) Sample simulated fractional Brownian motion image <b>B</b>_H = 0.5(<b>x</b>) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0107580#pone.0107580-Arneodo1" target="_blank">[39]</a>. (B) The gradient of the image in (A) is obtained as the modulus of the wavelet-transformed using <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0107580#pone.0107580.e009" target="_blank">Eq. (6)</a>. (C) Maxima chains in blue are defined as positions where the WT modulus is locally maximal (i.e., the WTMM). Along these WTMM chains in (C), further local maxima are found in red, i.e. the WTMMM. This is repeated as several different scales, three of which are shown in (D), (E), and (F). The WTMMM are then connected vertically through scales to define the WT skeleton shown in (G). Gray-scale coding is from black (min) to white (max).</p

Density histograms of malignant/benign cases out of fractal/Euclidean cases.

<p>(A) Histogram of potential malignant cases out of 27 fractal cases given the posterior distribution <i>p</i>(<i>M</i>|<i>F</i>) (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0107580#s4" target="_blank">Methods</a> section). The red bar represents our testing data set of 23 malignant cases out of 27 total fractal cases. The probability of arriving at less than or equal to 23 cases is ∼46%. (B) Histogram of potential benign cases out of 32 Euclidean cases given the posterior distribution <i>p</i>(<i>B</i>|<i>E</i>). The red bar represents our testing data set of 30 benign cases out of a total of 32 Euclidean cases. The probability of arriving at less than or equal to 30 cases is ∼74%. Since 23 malignant cases (A) and 30 benign cases (B) are not towards either end of these distributions resulting from 100,000 “coin-toss” iterations, we can safely say that the respective models are an adequate fit for the data.</p