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Nanni, A.

Publications and source records attributed to Nanni, A..

2 recordsLinked to original sources

Multiparent Recombinant Inbred lines crossed to a tester provide novel insights into sources of cis and trans regulation of gene expression

We propose crossing multi-parent recombinant-inbred-lines (RILs) to a common tester and measuring allele specific gene expression in the offspring. Testing whether allelic imbalance between two RIL x Tester crosses is equal, is a test of cis or trans depending on the RIL alleles compared. The study design also enables to separate two sources of trans variation, genetic and environmental, detected via interactions with cis effects. Examining these components of regulatory variation, we demonstrate this approach in a long-read RNA-seq experiment in female abdominal tissue at two time points in Drosophila melanogaster. Among the 40% of all loci that show evidence of genetic variation in cis, trans effects due to the environment are detectable in 31% of loci and trans effects due to genetic background are detectable in 19% of loci with little overlap in sources of trans variation. The loci identified in this study are associated with loci previously reported to exhibit genetic variation in gene expression in a range of tissues and large population samples, suggesting that there is consistent variation for genetic regulation of gene expression. We show that eleven loci in a QTL for thermotolerance, previously shown to differ in expression based on temperature, have evidence for regulation of gene expression regardless of the environment, including Cpr67B, a cuticular protein suggesting a potential functional role for standing variation in gene expression. This study provides a blueprint for efficiently identifying regulatory variation in gene expression, as the tester design maximizes cis variation and enables the efficient assessment of all pairs of RIL alleles relative to the tester, a much smaller study compared to the pairwise direct assessment.

genetics↗

SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms

The emergence of long-read RNA sequencing (lrRNA-seq) has provided an unprecedented opportunity to analyze transcriptomes at isoform resolution. However, the technology is not free from biases, and transcript models inferred from these data require quality control and curation. In this study, we introduce SQANTI3, a tool specifically designed to perform quality analysis on transcriptomes constructed using lrRNA-seq data. SQANTI3 provides an extensive naming framework to describe transcript model diversity in comparison to the reference transcriptome. Additionally, the tool incorporates a wide range of metrics to characterize various structural properties of transcript models, such as transcription start and end sites, splice junctions, and other structural features. These metrics can be utilized to filter out potential artifacts. Moreover, SQANTI3 includes a Rescue module that prevents the loss of known genes and transcripts exhibiting evidence of expression but displaying low-quality features. Lastly, SQANTI3 incorporates IsoAnnotLite, which enables functional annotation at the isoform level and facilitates functional iso-transcriptomics analyses. We demonstrate the versatility of SQANTI3 in analyzing different data types, isoform reconstruction pipelines, and sequencing platforms, and how it provides novel biological insights into isoform biology. The SQANTI3 software is available at https://github.com/ConesaLab/SQANTI3.

bioinformatics↗