Post-Transcriptional Regulation In The Drosophila Sex Determination Pathway

Sexually reproducing organisms produce two very different phenotypes (males and females), by differential deployment of essentially the same gene content. This dimorphism provides an excellent model to study how transcriptomes are differentially regulated, which is one of the central problems of biology. The core sex determination pathway of Drosophila is a well described cascade of transcriptional and post-transcriptional regulation, but knowledge of the downstream components is largely incomplete. High throughput technologies have provided great advances in understanding transcriptome regulation, but limits of the technology have lead to a focus on whole gene expression measurements, rather than post-transcriptional regulation. RNA-Seq experiments, in which transcripts are converted to cDNA and sequenced, allow the resolution and quantification of alternative transcript isoforms, potentially elucidating the post-transcriptional network. However, methods to analyze splicing are underdeveloped, and challenges in transcript assembly and quantification remain unresolved. This work describes the development of the Splicing Analysis Kit (Spanki) as a fast, open source, suite of tools that uses simulations based on real RNA-Seq data to characterize errors in a given dataset, and user tunable filters that minimize those errors. Spanki quantifies splicing differences in transcripts from the same loci within a sample, as well as between samples by using only those reads that directly assay splicing events (junction spanning reads). Despite the reliance on a fraction of the total data, sequencing depth typically generated in an RNA-Seq experiment is sufficient to identify differentially regulated splicing, and error profiles are superior. I demonstrate that this computational approach outperforms several commonly used approaches in an analysis of sex-differential splicing in Drosophila heads. Next I examine the effects of disrupting post-transcriptional regulation in Drosophila heads. I apply the Spanki software to analyze RNA-Seq data for mutant lines of two post-transcriptional regulators: Darkener of apricot (Doa) and found in neurons (fne). Doa, a serine-threonine kinase, regulates splicing by phosphorylating SR proteins, vital components of the splicing machinery. Found in neurons (fne) binds to transcripts and is involved in RNA metabolism. I demonstrate sex-differences in response to disruption of post-transcriptional regulation, and hypothesize that they are informative of sex-differentiation pathways. Finally, I examine the conservation of splicing regulation within the Drosophila lineage. I show that junction based splicing analysis is effective in making interspecific comparisons without the need for complete transcript models. I use these results to demonstrate the conservation of sex-differential splicing across 40 million years of evolution in 15 species in the Drosophila genus

m6A potentiates Sxl alternative pre-mRNA splicing for robust Drosophila sex determination

N6-methyladenosine (m6A) is the most common internal modification of eukaryotic messenger RNA (mRNA) and is decoded by YTH domain proteins1, 2, 3, 4, 5, 6, 7. The mammalian mRNA m6A methylosome is a complex of nuclear proteins that includes METTL3 (methyltransferase-like 3), METTL14, WTAP (Wilms tumour 1-associated protein) and KIAA1429. Drosophila has corresponding homologues named Ime4 and KAR4 (Inducer of meiosis 4 and Karyogamy protein 4), and Female-lethal (2)d (Fl(2)d) and Virilizer (Vir)8, 9, 10, 11, 12. In Drosophila, fl(2)d and vir are required for sex-dependent regulation of alternative splicing of the sex determination factor Sex lethal (Sxl)13. However, the functions of m6A in introns in the regulation of alternative splicing remain uncertain3. Here we show that m6A is absent in the mRNA of Drosophila lacking Ime4. In contrast to mouse and plant knockout models5, 7, 14, Drosophila Ime4-null mutants remain viable, though flightless, and show a sex bias towards maleness. This is because m6A is required for female-specific alternative splicing of Sxl, which determines female physiognomy, but also translationally represses male-specific lethal 2 (msl-2) to prevent dosage compensation in females. We further show that the m6A reader protein YT521-B decodes m6A in the sex-specifically spliced intron of Sxl, as its absence phenocopies Ime4 mutants. Loss of m6A also affects alternative splicing of additional genes, predominantly in the 5′ untranslated region, and has global effects on the expression of metabolic genes. The requirement of m6A and its reader YT521-B for female-specific Sxl alternative splicing reveals that this hitherto enigmatic mRNA modification constitutes an ancient and specific mechanism to adjust levels of gene expression

Structured Bayesian methods for splicing analysis in RNA-seq data

In most eukaryotes, alternative splicing is an important regulatory mechanism of gene expression that results in a single gene coding for multiple protein isoforms, thus largely increases the diversity of the proteome. RNA-seq is widely used for genome-wide splicing isoform quantification, and several effective and powerful methods have been developed for splicing analysis with RNA-seq data. However, it remains problematic for genes with low coverages or large number of isoforms. These difficulties may in principle be ameliorated by exploiting correlations encoded in the structured data sources. This thesis contributes to developments of Bayesian methods for splicing analysis by leveraging additional information in multiple datasets with structured prior distributions. First, we developed DICEseq, the first isoform quantification method tailored to time-series RNA-seq experiments. DICEseq explicitly models the correlations between experiments at different time points to aid the quantification of isoforms across experiments. Numerical experiments on both simulated and real datasets show that DICEseq yields more accurate results than state-of-the-art methods, an advantage that can become considerable at low coverage levels. Furthermore, DICEseq permits to quantify the trade-off between temporal sampling of RNA and depth of sequencing, frequently an important choice when planning experiments. Second, we developed BRIE (Bayesian Regression for Isoform Estimation), a Bayesian hierarchical model which resolves the difficulties in splicing analysis in single-cell RNA-seq (scRNA-seq) data by learning an informative prior distribution from sequence features. This method combines the quantification and imputation for splicing analysis via a Bayesian way, which is particularly useful in scRNA-seq data due to its extreme low coverages and high technical noises. We validated BRIE on several scRNA-seq data sets, showing that BRIE yields reproducible estimates of exon inclusion ratios in single cells. Third, we provided an effective tool by using Bayes factor to sensitively detect differential splicing between different single cells. When applying BRIE to a few real datasets, we found interesting heterogeneity patterns in splicing events across cell population, for example alternative exons in DNMT3B. In summary, this thesis proposes structured Bayesian methods to integrate multiple datasets to improve splicing analysis and study its biological functions

A Genomic and Genetic Analysis of Doublesex Targets and Function in Drosophila Sexual Dimorphism

Sex determination pathways are diverse throughout the animal kingdom, but converge upon conserved genes that encode products that regulate sexual dimorphism. One such downstream factor across many diverged sex determination pathways is the Drosophila doublesex (dsx) gene. The role of doublesex is highly conserved in different insects and dsx homologs (dsx, mab-3 related transcription factors, DMRTs) play roles in sexual differentiation in a diverse array of metazoans. In Drosophila, nearly all manifestations of sexual dimorphism between males and females are regulated by doublesex, yet there are only three known direct targets of DSX, which cannot account for the differences in regulation by DSX in sexually dimorphic tissues. To gain a comprehensive understanding of DSX targets, we undertook multiple experimental approaches that allowed us to identify genes that were bound by DSX, genes whose expression changed in response to DSX perturbation, and genes that function in dsx-expressing cells. DSX protein binding was assayed by ChIP-seq and DamID-seq on S2 cells expressing tagged DSX-M or DSX-F. We also examined DSX occupancy in adult fat body and gonads using DamID-seq or DamID-chip. These experiments identified 3,717 genes bound by DSX in at least one occupancy dataset. Strikingly, we found that genes with the highest levels of DSX occupancy were bound by DSX in all occupancy data sets. This suggests one main mechanism of DSX action would be binding to potential targets in all tissues/contexts rather than having context-dependent targets. In this model of DSX action, additional inputs (such as segmental identity) would be needed to enact transcriptional regulation of bound genes in the appropriate context. Further strengthening this model, although 2,668 genes are bound by DSX in our adult 
fat body occupancy data, less than 1% of these occupied genes show large and robust transcriptional changes in response to acute changes in DSX isoform. We found that predicted DSX targets are significantly enriched in genes that yield phenotypes in sexually dimorphic tissues after RNAi knockdown in dsx-expressing cells (p=0.002). 41 (70.7%) of high probability DSX targets had phenotypes in at least one sexual dimorphic tissue compared to 7 (31.8%) of low probability targets. Altogether, the occupancy, transcriptional profiling, and functional testing have provided a detailed description of how dsx regulates sexual development. New dsx-interacting genes include genes involved in insect hormone signaling. We have identified the Ecdysone receptor gene as a target of DSX. Since the Drosophila gonad represents an excellent model to dissect how DSX acts on a particular time and place to promote development of a sexually dimorphic tissue, we examined the Ecdysone receptor gene, which is involved in ecdysteroid signaling, for roles in gonad sexual development. My data supports the hypothesis that the steroid hormone ecdysone elicits a different response in the male vs. female gonad and that this difference is regulated by DSX and may be important for proper formation of the ovary vs. the testis. Rather than being strictly a genetic process, results from our experiments may demonstrate that sexual differentiation in the gonad occurs through a combination of signals that include sex specific hormone signaling. Since the formation of the gonad may represent processes that are conserved from flies to man, this research will provide insight into conserved genes that regulate developmentally similar pathways whose outcome generates major differences observed between the sexes