The coding portions of most eukaryotic genes are interrupted by non-coding introns which must be removed prior to the translation of their messenger RNAs (mRNA). Removal of introns from pre–mRNAs is catalyzed by the spliceosome, a large and dynamic ribonucleoprotein complex comprised of five small nuclear RNAs (snRNAs) and at least 100 proteins 
. Much of our knowledge about the components that comprise the spliceosome as well as their mechanisms of action has been derived from experiments using the powerful genetic tools available in the budding yeast, Saccharomyces cerevisiae
. Indeed, although the RNA2 – RNA11
genes originally identified in Hartwell's forward genetic screen preceded
the discovery of splicing 
, the mechanistic characterizations of these genes, since renamed PRP2 – PRP11
, underlie current models of the splicing pathway. Importantly, because the core components of the spliceosome are highly conserved between budding yeast and humans, the mechanistic details derived from work in yeast have been instrumental in understanding mechanisms of pre–mRNA splicing in higher eukaryotes.
The modern view of pre–mRNA splicing acknowledges the integrated role of the spliceosome with several other aspects of RNA processing. Whereas the historical view of splicing envisioned a cascade of temporal events initiated by transcription, followed by polyadenylation, and finalized with splicing and export of mRNAs from the nucleus, it is now clear that these pathways are not independent from one another but rather are functionally coupled. Strong evidence in both yeast and higher eukaryotes demonstrates that recruitment of the spliceosome to intron-containing transcripts occurs co-transcriptionally 
, mediated at least in part by physical associations between the C-terminal domain (CTD) of RNA polymerase II and the U1 snRNP 
. A growing body of evidence also indicates that the landscape of chromatin modifications encountered by transcribing polymerase molecules can dictate the activity of the spliceosome at various splice sites. For example, recent work has identified an enrichment of methylated lysine-36 in the histone H3 protein specifically within exonic sequences, suggesting a possible mechanism for facilitating the identification of intron-exon boundaries 
. Similarly, the rate of transcription by RNA polymerase II, which can be impacted by chromatin marks, has also been shown to be critical for dictating alternative splicing decisions 
. Furthermore, it is also clear that splicing is coupled to downstream steps in RNA processing. For example, the yeast Ysh1 protein 
, which is the homolog of CPSF73, the mammalian endonuclease required for 3′ end processing, was originally identified as Brr5 in a cold-sensitive screen for mutants defective in pre–mRNA splicing 
. Consistent with this observation, recent evidence suggests that transcriptional pausing near the 3′ end of genes is a critical component of pre–mRNA splicing efficiency 
. Despite the increasing evidence of the interconnectivity of these pathways, in many cases the mechanistic details which underlie these functional relationships remain unclear. Our understanding of these mechanistic connections would benefit from a more complete understanding of the complement of factors through which splicing is connected to these cellular processes.
A variety of recent genome-wide approaches have provided important insights into the connections that exist between the spliceosome and other cellular processes. Two powerful approaches, Synthetic Genetic Array (SGA) Analysis 
and Epistatic MiniArray Profiling (E-MAP) 
, leverage genetic tools available in yeast to systematically generate millions of double-mutant strains and then carefully quantitate their cellular fitness to determine an interaction score for every pair-wise mutation. On the basis of strong positive or negative genetic interaction scores these approaches have been successfully used to infer functional relationships between many cellular pathways, including several with pre–mRNA processing 
. Simultaneously, improvements in proteomic methodologies have enabled the direct analysis of protein complexes in organisms as diverse as humans and yeast, allowing for an assessment of all of the stably-bound proteins involved in pre–mRNA splicing in many organisms 
. While the combination of these and other approaches has provided a global picture of many of the cellular factors that influence the splicing pathway, either directly or indirectly, an important question remains about the functional significance of these factors in the splicing of specific transcripts. Indeed, it has long been known that certain transcripts require the activity of unique accessory factors to facilitate their splicing 
. Moreover, recent work supports the idea that different transcripts can have a greater or lesser dependence upon the activity of core spliceosomal components for their efficient splicing 
Here we present the results of a novel approach that complements the genetic and physical approaches of others by allowing for a direct functional assessment of nearly every gene in the S. cerevisiae genome in the pre–mRNA splicing process. For this work, we developed automated methods that enabled the isolation of total cellular RNA from about 5500 unique strains, each of which contained a mutation in a single gene, and all of which were examined during exponential growth in liquid medium. Using a high-throughput quantitative PCR (QPCR) assay, the relative cellular level of nearly any RNA can be readily determined in the background of each of these strains. By assessing the levels of several different pre–mRNA species, we were able to identify not only those factors which are necessary for the splicing of many transcripts, but also factors that are specifically required for the splicing of a subset of intron-containing genes. Whereas our study specifically examines the levels of several cellular pre–mRNAs, the approach described herein can be easily adapted to study the level of nearly any RNA molecule of interest under a wide variety of cellular growth conditions.