When genomes collide: multiple modes of germline misregulation in a dysgenic syndrome of Drosophila virilis
Mauricio A. Galdos, Alexandra A. Erwin, Michelle L. Wickersheim, Chris C. Harrison, Kendra D. Marr, Justin Blumenstiel

In sexually reproducing species the union of gametes that are not closely related can result in genomic incompatibility. Hybrid dysgenic syndromes represent a form of genomic incompatibility that can arise when transposable element (TE) abundance differs between two parents. When TEs lacking in the female parent are transmitted paternally, a lack of corresponding silencing small RNAs (piRNAs) transmitted through the female germline can lead to TE mobilization in progeny. The epigenetic nature of this phenomenon is demonstrated by the fact that genetically identical females of the reciprocal cross are normal. Here we show that in the hybrid dysgenic syndrome of Drosophila virilis, an excess of paternally inherited TE families leads not only to increased expression of these TEs, but also coincides with derepression of TEs in equal abundance within parents. Moreover, TE derepression is stable as flies age and associated with piRNA biogenesis defects for only some TEs. At the same time, TE activation is associated with a genome wide shift in the distribution of endogenous gene expression and an increase in abundance of off-target genic piRNAs. To identify regions of the maternal genome that most protect against dysgenesis, we performed an F3 backcross analysis. We find that pericentric regions play a dominant role in maternal protection. This F3 backcross approach additionally allowed us to clarify the properties of genic paramutation in D. virilis. Overall, results support a model in which early germline events in dysgenesis establish a chronic, stable state of mis-expression that is maintained through adulthood. Such early events in the germline that are mediated by parent-of-origin effects may be important in determining patterns of gene expression in natural populations.

Evolution of bow-tie architectures in biology
Tamar Friedlander, Avraham E. Mayo, Tsvi Tlusty, Uri Alon
Subjects: Molecular Networks (q-bio.MN)

Bow-tie or hourglass structure is a common architectural feature found in biological and technological networks. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when two conditions are met: (i) the evolutionary goal is rank deficient, where the rank corresponds to the minimal number of input features on which the outputs depend, and (ii) The effects of mutations on interaction intensities between components are described by product rule – namely the mutated element is multiplied by a random number. Product-rule mutations are more biologically realistic than the commonly used sum-rule mutations that add a random number to the mutated element. These conditions robustly lead to bow-tie structures. The minimal width of the intermediate network layers (the waist or knot of the bow-tie) equals the rank of the evolutionary goal. These findings can help explain the presence of bow-ties in diverse biological systems, and can also be relevant for machine learning applications that employ multi-layered networks.

Estimating transcription factor abundance and specificity from genome-wide binding profiles
Nicolae Radu Zabet, Boris Adryan
Comments: 39 pages, 25 figures, 10 tables
Subjects: Quantitative Methods (q-bio.QM)

The binding of transcription factors (TFs) is essential for gene expression. One important characteristic is the actual occupancy of a putative binding site in the genome. In this study, we propose an analytical model to predict genomic occupancy that incorporates the preferred target sequence of a TF in the form of a position weight matrix (PWM), DNA accessibility data (in case of eukaryotes), the number of TF molecules expected to be bound to the DNA and a parameter that modulates the specificity of the TF. Given actual occupancy data in form of ChIP-seq profiles, we backwards inferred copy number and specificity for five Drosophila TFs during early embryonic development: Bicoid, Caudal, Giant, Hunchback and Kruppel. Our results suggest that these TFs display a lower number of DNA-bound molecules than previously assumed (in the range of tens and hundreds) and that, while Bicoid and Caudal display a higher specificity, the other three transcription factors (Giant, Hunchback and Kruppel) display lower specificity in their binding (despite having PWMs with higher information content). This study gives further weight to earlier investigations into TF copy numbers that suggest a significant proportion of molecules are not bound to the DNA.

Impact of RNA degradation on measurements of gene expression

Irene Gallego Romero, Athma A. Pai, Jenny Tung, Yoav Gilad

The use of low quality RNA samples in whole-genome gene expression profiling remains controversial. It is unclear if transcript degradation in low quality RNA samples occurs uniformly, in which case the effects of degradation can be normalized, or whether different transcripts are degraded at different rates, potentially biasing measurements of expression levels. This concern has rendered the use of low quality RNA samples in whole-genome expression profiling problematic. Yet, low quality samples are at times the sole means of addressing specific questions – e.g., samples collected in the course of fieldwork. We sought to quantify the impact of variation in RNA quality on estimates of gene expression levels based on RNA-seq data. To do so, we collected expression data from tissue samples that were allowed to decay for varying amounts of time prior to RNA extraction. The RNA samples we collected spanned the entire range of RNA Integrity Number (RIN) values (a quality metric commonly used to assess RNA quality). We observed widespread effects of RNA quality on measurements of gene expression levels, as well as a slight but significant loss of library complexity in more degraded samples. While standard normalizations failed to account for the effects of degradation, we found that a simple linear model that controls for the effects of RIN can correct for the majority of these effects. We conclude that in instances where RIN and the effect of interest are not associated, this approach can help recover biologically meaningful signals in data from degraded RNA samples.

Sex-biased expression of microRNAs in Drosophila melanogaster
Antonio Marco
(Submitted on 11 Dec 2013)

Most animals have separate sexes. The differential expression of gene products, in particular that of gene regulators, is underlying sexual dimorphism. Analyses of sex-biased expression have focused mostly in protein coding genes. Several lines of evidence indicate that microRNAs, a class of major gene regulators, are likely to have a significant role in sexual dimorphism. This role has not been systematically explored so far. Here I study the sex-biased expression pattern of microRNAs in the model species Drosophila melanogaster. As with protein coding genes, sex biased microRNAs are associated with the reproductive function. Strikingly, contrary to protein-coding genes, male biased microRNAs are enriched in the X chromosome whilst female microRNAs are mostly autosomal. I propose that the chromosomal distribution is a consequence of high rates of de novo emergence, and a preference of new microRNAs to be expressed in the testis. I also suggest that demasculinization of the X chromosome may not affect microRNAs. Interestingly, female biased microRNAs are often encoded within protein coding genes that are also expressed in females. These results strongly suggest that the sex-biased expression of microRNAs is mainly a consequence of high rates of microRNA emergence in the X (male bias) or hitch-hiked expression by host genes (female bias).