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Biology subjects

Nalabolu, S.

Publications and source records attributed to Nalabolu, S..

2 recordsLinked to original sources

Multiple freeze-thaw cycles lead to a loss of consistency in poly(A)-enriched RNA sequencing

RNA-Seq is ubiquitous, but depending on the study, sub-optimal sample handling may be required, resulting in repeated freeze-thaw cycles. However, little is known about how each cycle impacts downstream analyses, due to a lack of study and known limitations in common RNA quality metrics, e.g., RIN, at quantifying RNA degradation following repeated freeze-thaws. Here we quantify the impact of repeated freeze-thaw on the reliability of downstream RNA-Seq analysis. To do so, we developed a method to estimate the relative noise between technical replicates independently of RIN. Using this approach we inferred the effect of both RIN and the number of freeze-thaw cycles on sample noise. We find that RIN is unable to fully account for the change in sample noise due to freeze-thaw cycles. Additionally, freeze-thaw is detrimental to sample quality and differential expression (DE) reproducibility, approaching zero after three cycles for poly(A)-enriched samples, wherein the inherent 3 bias in read coverage is more exacerbated by freeze-thaw cycles, while ribosome-depleted samples are less affected by freeze-thaws. The use of poly(A)-enrichment for RNA sequencing is pervasive in library preparation of frozen tissue, and thus, it is important during experimental design and data analysis to consider the impact of repeated freeze-thaw cycles on reproducibility. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/020792v2_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@c2c756org.highwire.dtl.DTLVardef@1ad1c03org.highwire.dtl.DTLVardef@a4136org.highwire.dtl.DTLVardef@13f403f_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

Transcriptional organization of autism spectrum disorder and its connection to ASD risk genes and phenotypic variation

Hundreds of genes are implicated in autism spectrum disorder (ASD) but the mechanisms through which they contribute to ASD pathophysiology remain elusive. Here, we analyzed leukocyte transcriptomics from 1-4 year-old male toddlers with ASD or typical development from the general population. We discovered a perturbed gene network that includes genes that are highly expressed during fetal brain development and which is dysregulated in hiPSC-derived neuron models of ASD. High-confidence ASD risk genes emerge as upstream regulators of the network, and many risk genes may impact the network by modulating RAS/ERK, PI3K/AKT, and WNT/{beta}-catenin signaling pathways. We found that the degree of dysregulation in this network correlated with the severity of ASD symptoms in the toddlers. These results demonstrate how the heterogeneous genetics of ASD may dysregulate a core network to influence brain development at prenatal and very early postnatal ages and, thereby, the severity of later ASD symptoms.

systems biology↗