Early-life stress can result in life-long effects that impact adult health and disease risk, but little is known about how such programming is established and maintained. Here, we show that such epigenetic memories can be initiated in the Drosophila embryo before the major wave of zygotic transcription, and higher-order chromatin structures are established. An early short heat shock results in elevated levels of maternal miRNA and reduced levels of a subgroup of zygotic genes in stage 5 embryos. Using a Dicer-1 mutant, we show that the stress-induced decrease in one of these genes, the insulator-binding factor Elba1, is dependent on functional miRNA biogenesis. Reduction in Elba1 correlates with the upregulation of early developmental genes and promotes a sustained weakening of heterochromatin in the adult fly as indicated by an increased expression of the PEV w(m4h) reporter. We propose that maternal miRNAs, retained in response to an early embryonic heat shock, shape the subsequent de novo heterochromatin establishment that occurs during early development via direct or indirect regulation of some of the earliest expressed genes, including Elba1.

Motivation: Feature-based counting is commonly used in RNA-sequencing (RNA-seq) analyses. Here, sequences must align to target features (like genes or non-coding RNAs) and related sequences with different compositions are counted into the same feature. Consequently, sequence integrity is lost, making results less traceable against raw data.Small RNA (sRNA) often maps to multiple features and shows an incredible diversity in form and function. Therefore, applying feature-based strategies may increase the risk of misinterpretation. We present a strategy for sRNA-seq analysis that preserves the integrity of the raw sequence making the data lineage fully traceable. We have consolidated this strategy into Seqpac: An R package that makes a complete sRNA analysis available on multiple platforms. Using published biological data, we show that Seqpac reveals hidden bias and adds new insights to studies that were previously analyzed using feature-based counting.We have identified limitations in the concurrent analysis of RNA-seq data. We call it the traceability dilemma in alignment-based sequencing strategies. By building a flexible framework that preserves the integrity of the read sequence throughout the analysis, we demonstrate better interpretability in sRNA-seq experiments, which are particularly vulnerable to this problem. Applying similar strategies to other transcriptomic workflows may aid in resolving the replication crisis experienced by many fields that depend on transcriptome analyses.