REMOVING TECHNICAL VARIABILITY IN RNA-SEQ DATA USING CONDITIONAL QUANTILE NORMALIZATION

The ability to measure gene expression on a genome-wide scale is one of the most promising accomplishments in molecular biology. Microarrays, the technology that first permitted this, were riddled with problems due to unwanted sources of variability. Many of these problems are now mitigated, after a decade’s worth of statistical methodology development. The recently developed RNA sequencing (RNA-seq) technology has generated much excitement in part due to claims of reduced variability in comparison to microarrays. However, we show RNA-seq data demonstrates unwanted and obscuring variability similar to what was first observed in microarrays. In particular, we find GC-content has a strong sample specific effect on gene expression measurements that, if left uncorrected, leads to false positives in downstream results. We also report on commonly observed data distortions that demonstrate the need for data normalization. Here we describe statistical methodology that improves precision by 42% without loss of accuracy. Our resulting conditional quantile normalization (CQN) algorithm combines robust generalized regression to remove systematic bias introduced by deterministic features such as GC-content, and quantile normalization to correct for global distortions.

Sex determination and temperature-induced sex differentiation in three natural populations of Nile tilapia (Oreochromis niloticus) adapted to extreme temperature conditions

As a species of major interest for aquaculture, the sex determination system (SDS) of Nile tilapia, Oreochromis niloticus, has been widely investigated. In this species, sex determination is considered to be governed by the interactions between a complex system of genetic sex determination factors (GSD) and the influence of temperature (TSD) during a critical period. Previous studies were exclusively carried out on domestic stocks with the genetic and maintenance limitations associated. Given the wide distribution and adaptation potential of the Nile tilapia, we investigated under controlled conditions the sex determination system of natural populations adapted to three extreme thermal regimes: stable extreme environments in Ethiopia, either cold temperatures in a highland lake (Lake Koka), or warm temperatures in hydrothermal springs (Lake Metahara), and an environment with large seasonal variations in Ghana (Kpandu, Lake Volta). The sex ratio analysis was conducted on progenies reared under constant basal (27 degrees C) or high (36 degrees C) temperatures during the 30 days following yolk-sac resorption. Sex ratios of the progenies reared at standard temperature suggest that the three populations share a similar complex GSD system based on a predominant male heterogametic factor with additional influences of polymorphism at this locus and/or action of minor factors. The three populations presented a clear thermosensitivity of sex differentiation, with large variations in the intensity of response depending on the parents. This confirms the presence of genotype-environment interactions in TSD of Nile tilapia. Furthermore the existence of naturally sex-reversed individuals is strongly suggested in two populations (Kpandu and Koka). However, it was not possible here to infer if the sex-inversion resulted from minor genetic factors and/or environmental influences. The present study demonstrated for the first time the conservation of a complex SDS combining polymorphic GSD and TSD components in natural populations of Nile tilapia. We discuss the evolutionary implications of our findings and highlight the importance of field investigations of sex determination. (c) 2007 Elsevier B.V. All rights reserved.

The extreme flood event of Lago Maggiore in September 1993

In September 1993, the Valais and Ticino regions of Switzerland were affected by extreme flooding triggered by heavy precipitation. The meteorological situation leading to this event is studied in the Twentieth Century Reanalysis (20CR) data set. A strong cut-off low development is found to be the driving synoptic-scale atmospheric circulation pattern. The agreement with previous studies highlights the applicability of 20CR for extreme event analysis.