High Heritability Is Compatible with the Broad Distribution of Set Point Viral Load in HIV Carriers.

Set point viral load in HIV patients ranges over several orders of magnitude and is a key determinant of disease progression in HIV. A number of recent studies have reported high heritability of set point viral load implying that viral genetic factors contribute substantially to the overall variation in viral load. The high heritability is surprising given the diversity of host factors associated with controlling viral infection. Here we develop an analytical model that describes the temporal changes of the distribution of set point viral load as a function of heritability. This model shows that high heritability is the most parsimonious explanation for the observed variance of set point viral load. Our results thus not only reinforce the credibility of previous estimates of heritability but also shed new light onto mechanisms of viral pathogenesis

Accurate Genomic Prediction Of Human Height

We construct genomic predictors for heritable and extremely complex human quantitative traits (height, heel bone density, and educational attainment) using modern methods in high dimensional statistics (i.e., machine learning). Replication tests show that these predictors capture, respectively, $\sim$40, 20, and 9 percent of total variance for the three traits. For example, predicted heights correlate $\sim$0.65 with actual height; actual heights of most individuals in validation samples are within a few cm of the prediction. The variance captured for height is comparable to the estimated SNP heritability from GCTA (GREML) analysis, and seems to be close to its asymptotic value (i.e., as sample size goes to infinity), suggesting that we have captured most of the heritability for the SNPs used. Thus, our results resolve the common SNP portion of the "missing heritability" problem -- i.e., the gap between prediction R-squared and SNP heritability. The $\sim$20k activated SNPs in our height predictor reveal the genetic architecture of human height, at least for common SNPs. Our primary dataset is the UK Biobank cohort, comprised of almost 500k individual genotypes with multiple phenotypes. We also use other datasets and SNPs found in earlier GWAS for out-of-sample validation of our results.Comment: 17 pages, 10 figure

Genetic variability and correlation analysis of rice (Oryza sativa L.) inbred lines based on agro-morphological traits

In order to evaluate genetic variability of agro-morphological traits and also determine the correlation between grain yield with its components in rice lines, 17 recombinants inbred lines, their parents and a check variety were grown in research station of Africa rice center in Benin republic during two consecutive years 2013 and 2014. The experiments were laid out in a randomized complete block design with four replications. Phenotypic coefficients of variance were higher than genotypic coefficients of variance in all the characters across the two years. High heritability in broad sense (H2) estimates were obtained for biomass (68.77%), date of 50% flowering (98.11%), plant height (81.94%), leaf area (82.90%), number of panicles (64.40%), leaf dry weight (72.91%), root weight (67.43%) and yield/plant (62.23%) suggesting that the traits were primarily under genetic control. A joint consideration of broad sense heritability (H2) and genetic advance as per cent mean expected (GAM) revealed that leaves dries weight and roots weight combined high heritability and high GAM. Furthermore, high (H2) and high GAM recorded in these characters could be explained by additive gene action. However, high estimates (H2) combined with moderate GAM recorded for biomass, day to 50% flowering, leaf area, number of panicle and yield/plant could be due to non-additive gene effect. Grain yield/plant recorded positive and significant correlation with stem weight (r=0.5262) and biomass (r=0.9291). This result indicates that selection based on these two characters will be highly effective for yield improvement in rice. (Résumé d'auteur

Genotypic variation of dormancy in wheat (Triticum aestivum L.) : a thesis presented in partial fulfilment of the requirements for the degree of Master of Agricultural Science, Department of Plant Science, Massey University, Palmerston North, New Zealand

Embryo dormancy and α - amylase dormancy are desirable in wheat to minimise pre-harvest sprouting damage. The current work focuses on the embryo and graincoat colour. A loose association between grain redness and dormancy in wheat is common knowledge. But the causal relationships between colour and dormancy are not clear and need to account for dormancy variability in the gene - pool. The study's working hypothesis was that colour formation triggers hypo - oxia synthesis of ABA (vs. gibberellins) which triggers dormancy if the timing with embryo development is optimal. Development profiles for eight attributes (including dormancy) of grain were investigated from five white and five red wheat cultivars representing a wide genetic base. Tagged ears were sampled from pollination to harvest ripeness (days after pollination to 12.5% moisture). All the white - grained cultivars did not have dormancy at harvest ripeness, and there was considerable variation of dormancy levels in the red - grained cultivars. The total-grain abscisic acid was not associated with redness nor dormancy, and no evidence of ABA sensitivity could be found in cv. Brevor. The failure to detect the putative dormancy of cvs. Brevor and Kenya 321 was probably due to fine detail employed in the present work, but may also have been due to the single ripening environment used. Base α amylase and flavanol levels did not contribute to the variation in embryo dormancy. Gibberellic acid insensitivity in the Rht/Gai genotypes was not expressed in terms of embryo dormancy. Examination of the profiles suggested that redness was necessary to permit dormancy, but that dormancy timing was independent of colour. This led to varying levels of dormancy at harvest ripeness. No association with ABA was evident, nor with colour precursor. However timing and duration of polymerisation (flavanol) development (hypo-oxia) did show a weak association with dormancy delay and level. The new hypothesis suggests that colour formation hypo-oxia permits dormancy, but that its timing is flexible with respect to harvest ripeness. Broader genetic control (other than the Redness gene) is indicated. Heritability estimates indicated that timings, rather than levels, are more useful selection criteria. This included embryo dormancy attributes, colour, and harvest ripeness. For plant breeders it suggested that grain sampled at harvest ripeness could be selected for dormancy as measured in this study

Interrogating the Genetic Determinants of Tourette’s Syndrome and Other Tic Disorders Through Genome-Wide Association Studies

Objective: Tourette’s syndrome is polygenic and highly heritable. Genome-wide association study (GWAS) approaches are useful for interrogating the genetic architecture and determinants of Tourette’s syndrome and other tic disorders. The authors conducted a GWAS meta-analysis and probed aggregated Tourette’s syndrome polygenic risk to test whether Tourette’s and related tic disorders have an underlying shared genetic etiology and whether Tourette’s polygenic risk scores correlate with worst-ever tic severity and may represent a potential predictor of disease severity. Methods: GWAS meta-analysis, gene-based association, and genetic enrichment analyses were conducted in 4,819 Tourette’s syndrome case subjects and 9,488 control subjects. Replication of top loci was conducted in an independent population-based sample (706 case subjects, 6,068 control subjects). Relationships between Tourette’s polygenic risk scores (PRSs), other tic disorders, ascertainment, and tic severity were examined. Results: GWAS and gene-based analyses identified one genome-wide significant locus within FLT3 on chromosome 13, rs2504235, although this association was not replicated in the population-based sample. Genetic variants spanning evolutionarily conserved regions significantly explained 92.4% of Tourette’s syndrome heritability. Tourette’s-associated genes were significantly preferentially expressed in dorsolateral prefrontal cortex. Tourette’s PRS significantly predicted both Tourette’s syndrome and tic spectrum disorders status in the population-based sample. Tourette’s PRS also significantly correlated with worst-ever tic severity and was higher in case subjects with a family history of tics than in simplex case subjects. Conclusions: Modulation of gene expression through noncoding variants, particularly within cortico-striatal circuits, is implicated as a fundamental mechanism in Tourette’s syndrome pathogenesis. At a genetic level, tic disorders represent a continuous spectrum of disease, supporting the unification of Tourette’s syndrome and other tic disorders in future diagnostic schemata. Tourette’s PRSs derived from sufficiently large samples may be useful in the future for predicting conversion of transient tics to chronic tic disorders, as well as tic persistence and lifetime tic severity

A method for generating realistic correlation matrices

Simulating sample correlation matrices is important in many areas of statistics. Approaches such as generating Gaussian data and finding their sample correlation matrix or generating random uniform $[-1,1]$ deviates as pairwise correlations both have drawbacks. We develop an algorithm for adding noise, in a highly controlled manner, to general correlation matrices. In many instances, our method yields results which are superior to those obtained by simply simulating Gaussian data. Moreover, we demonstrate how our general algorithm can be tailored to a number of different correlation models. Using our results with a few different applications, we show that simulating correlation matrices can help assess statistical methodology.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS638 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org