Estimating Variable Effective Population Sizes from Multiple Genomes: A Sequentially Markov Conditional Sampling Distribution Approach

Throughout history, the population size of modern humans has varied considerably due to changes in environment, culture, and technology. More accurate estimates of population size changes, and when they occurred, should provide a clearer picture of human colonization history and help remove confounding effects from natural selection inference. Demography influences the pattern of genetic variation in a population, and thus genomic data of multiple individuals sampled from one or more present-day populations contain valuable information about the past demographic history. Recently, Li and Durbin developed a coalescent-based hidden Markov model, called the pairwise sequentially Markovian coalescent (PSMC), for a pair of chromosomes (or one diploid individual) to estimate past population sizes. This is an efficient, useful approach, but its accuracy in the very recent past is hampered by the fact that, because of the small sample size, only few coalescence events occur in that period. Multiple genomes from the same population contain more information about the recent past, but are also more computationally challenging to study jointly in a coalescent framework. Here, we present a new coalescent-based method that can efficiently infer population size changes from multiple genomes, providing access to a new store of information about the recent past. Our work generalizes the recently developed sequentially Markov conditional sampling distribution framework, which provides an accurate approximation of the probability of observing a newly sampled haplotype given a set of previously sampled haplotypes. Simulation results demonstrate that we can accurately reconstruct the true population histories, with a significant improvement over the PSMC in the recent past. We apply our method, called diCal, to the genomes of multiple human individuals of European and African ancestry to obtain a detailed population size change history during recent times.     

Comparison of point counts and territory mapping for detecting effects of forest management on songbirds

Point counts are commonly used to assess changes in bird abundance, including analytical approaches such as distance sampling that estimate density. Point‐count methods have come under increasing scrutiny because effects of detection probability and field error are difficult to quantify. For seven forest songbirds, we compared fixed‐radii counts (50 m and 100 m) and density estimates obtained from distance sampling to known numbers of birds determined by territory mapping. We applied point‐count analytic approaches to a typical forest management question and compared results to those obtained by territory mapping. We used a before–after control impact (BACI) analysis with a data set collected across seven study areas in the central Appalachians from 2006 to 2010. Using a 50‐m fixed radius, variance in error was at least 1.5 times that of the other methods, whereas a 100‐m fixed radius underestimated actual density by >3 territories per 10 ha for the most abundant species. Distance sampling improved accuracy and precision compared to fixed‐radius counts, although estimates were affected by birds counted outside 10‐ha units. In the BACI analysis, territory mapping detected an overall treatment effect for five of the seven species, and effects were generally consistent each year. In contrast, all point‐count methods failed to detect two treatment effects due to variance and error in annual estimates. Overall, our results highlight the need for adequate sample sizes to reduce variance, and skilled observers to reduce the level of error in point‐count data. Ultimately, the advantages and disadvantages of different survey methods should be considered in the context of overall study design and objectives, allowing for trade‐offs among effort, accuracy, and power to detect treatment effects.     

Analytical validation of a prognostic prostate cancer gene expression assay using formalin fixed paraffin embedded tissue

Background

There is a clear need for assays that can predict the risk of metastatic prostate cancer following curative procedures. Importantly these assays must be analytically robust in order to provide quality data for important clinical decisions. DNA microarray based gene expression assays measure several analytes simultaneously and can present specific challenges to analytical validation. This study describes the analytical validation of one such assay designed to predict metastatic recurrence in prostate cancer using primary formalin fixed paraffin embedded tumour material.

Methods

Accuracy was evaluated with a method comparison study between the assay development platform (Prostate Disease Specific Array) and an alternative platform (Xcel? microarray) using 50 formalin-fixed, paraffin-embedded prostate cancer patient samples. An additional 70 samples were used to establish the assay reportable range. Determination of assay precision and sensitivity was performed on multiple technical replicates of three prostate cancer samples across multiple variables (operators, days, runs, reagent lots, and equipment) and RNA/cDNA inputs respectively using the appropriate linear mixed model.

Results

The overall agreement between the development and alternative platform was 94.7% (95% confidence interval, 86.9–98.5%). The reportable range was determined to be 0.150 to 1.107 for core needle biopsy samples and???0.214 to 0.844 for radical prostatectomy samples. From the precision study, the standard deviations for assay repeatability and reproducibility were 0.032 and 0.040 respectively. The sensitivity study demonstrated that a total RNA input and cDNA input of 50?ng and 3.5?μg respectively was conservative.

Conclusion

The Metastatic Assay was found to be highly reproducible and precise. In conclusion the studies demonstrated an acceptable analytical performance for the assay and support its potential use in the clinic.

     

Expression of a Truncated, Kinase-Defective TGF-β Type II Receptor in Mouse Skeletal Tissue Promotes Terminal Chondrocyte Differentiation and Osteoarthritis

Members of the TGF-β superfamily are important regulators of skeletal development. TGF-βs signal through heteromeric type I and type II receptor serine/threonine kinases. When over-expressed, a cytoplasmically truncated type II receptor can compete with the endogenous receptors for complex formation, thereby acting as a dominant-negative mutant (DNIIR). To determine the role of TGF-βs in the development and maintenance of the skeleton, we have generated transgenic mice (MT-DNIIR-4 and -27) that express the DNIIR in skeletal tissue. DNIIR mRNA expression was localized to the periosteum/perichondrium, syno-vium, and articular cartilage. Lower levels of DNIIR mRNA were detected in growth plate cartilage. Transgenic mice frequently showed bifurcation of the xiphoid process and sternum. They also developed progressive skeletal degeneration, resulting by 4 to 8 mo of age in kyphoscoliosis and stiff and torqued joints. The histology of affected joints strongly resembled human osteo-arthritis. The articular surface was replaced by bone or hypertrophic cartilage as judged by the expression of type X collagen, a marker of hypertrophic cartilage normally absent from articular cartilage. The synovium was hyperplastic, and cartilaginous metaplasia was observed in the joint space.

We then tested the hypothesis that TGF-β is required for normal differentiation of cartilage in vivo. By 4 and 8 wk of age, the level of type X collagen was increased in growth plate cartilage of transgenic mice relative to wild-type controls. Less proteoglycan staining was detected in the growth plate and articular cartilage matrix of transgenic mice. Mice that express DNIIR in skeletal tissue also demonstrated increased Indian hedgehog (IHH) expression. IHH is a secreted protein that is expressed in chondrocytes that are committed to becoming hypertrophic. It is thought to be involved in a feedback loop that signals through the periosteum/ perichondrium to inhibit cartilage differentiation. The data suggest that TGF-β may be critical for multifaceted maintenance of synovial joints. Loss of responsiveness to TGF-β promotes chondrocyte terminal differentiation and results in development of degenerative joint disease resembling osteoarthritis in humans.

     

The conformation of the mucopolysaccharides. Hyaluronates

X-ray-diffraction patterns of hyaluronate fibres from a variety of sources were obtained. Sodium hyaluronate gives well-defined patterns which index on a hexagonal unit cell with dimensions a=1.17+/-nm and a fibre repeat-distance of 2.85+/-0.03nm. A further form of sodium hyaluronate is produced by annealing at 60 degrees C in 75% relative humidity. This stable state indexes on a hexagonal unit cell of unchanged fibre repeat-distance but with a=1.87nm. The chain conformation is a threefold helix. Analysis of these diffraction patterns led to two tentative structures for sodium hyaluronate, involving different packing of the polysaccharide chains. The significance of side-chain interaction is discussed. Hyaluronic acid produces an X-ray pattern different from that obtained with the sodium salt. The fibre repeat-distance is 1.96+/-0.02nm and the unit cell appears to be monoclinic. The chain conformation is a twofold helix and conformational change between free acid and monovalent salt is discussed. These findings, together with model-building experiments, are interpreted as indicating a highly ordered structure, and the physical properties of hyaluronate solutions with regard to molecular shape and polyelectrolyte behaviour are rationalized.