Dataset Information

Evaluating stably expressed genes in single cells.

ABSTRACT: BACKGROUND:Single-cell RNA-seq (scRNA-seq) profiling has revealed remarkable variation in transcription, suggesting that expression of many genes at the single-cell level is intrinsically stochastic and noisy. Yet, on the cell population level, a subset of genes traditionally referred to as housekeeping genes (HKGs) are found to be stably expressed in different cell and tissue types. It is therefore critical to question whether stably expressed genes (SEGs) can be identified on the single-cell level, and if so, how can their expression stability be assessed? We have previously proposed a computational framework for ranking expression stability of genes in single cells for scRNA-seq data normalization and integration. In this study, we perform detailed evaluation and characterization of SEGs derived from this framework. RESULTS:Here, we show that gene expression stability indices derived from the early human and mouse development scRNA-seq datasets and the "Mouse Atlas" dataset are reproducible and conserved across species. We demonstrate that SEGs identified from single cells based on their stability indices are considerably more stable than HKGs defined previously from cell populations across diverse biological systems. Our analyses indicate that SEGs are inherently more stable at the single-cell level and their characteristics reminiscent of HKGs, suggesting their potential role in sustaining essential functions in individual cells. CONCLUSIONS:SEGs identified in this study have immediate utility both for understanding variation and stability of single-cell transcriptomes and for practical applications such as scRNA-seq data normalization. Our framework for calculating gene stability index, "scSEGIndex," is incorporated into the scMerge Bioconductor R package (https://sydneybiox.github.io/scMerge/reference/scSEGIndex.html) and can be used for identifying genes with stable expression in scRNA-seq datasets.

SUBMITTER: Lin Y

PROVIDER: S-EPMC6748759 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Evaluating stably expressed genes in single cells.

Lin Yingxin Y Ghazanfar Shila S Strbenac Dario D Wang Andy A Patrick Ellis E Lin David M DM Speed Terence T Yang Jean Y H JYH Yang Pengyi P

GigaScience 20190901 9

<h4>Background</h4>Single-cell RNA-seq (scRNA-seq) profiling has revealed remarkable variation in transcription, suggesting that expression of many genes at the single-cell level is intrinsically stochastic and noisy. Yet, on the cell population level, a subset of genes traditionally referred to as housekeeping genes (HKGs) are found to be stably expressed in different cell and tissue types. It is therefore critical to question whether stably expressed genes (SEGs) can be identified on the singl ...[more]

PMID: 31531674

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Project description:BackgroundDirect seeding is an efficient cultivation technique in rice. However, poor low temperature germinability (LTG) of modern rice cultivars limits its application. Identifying the genes associated with LTG and performing molecular breeding is the fundamental way to address this issue. However, few LTG QTLs have been fine mapped and cloned so far.ResultsIn the present study, the LTG evaluation of 375 rice accessions selected from the Rice Diversity Panel 2 showed that there were large LTG variations within the population, and the LTG of Indica group was significantly higher than that of Japonica and Aus groups (p < 0.01). In total, eleven QTLs for LTG were identified through genome-wide association study (GWAS). Among them, qLTG_sRDP2-3/qLTG_JAP-3, qLTG_AUS-3 and qLTG_sRDP2-12 are first reported in the present study. The QTL on chromosome 10, qLTG_sRDP2-10a had the largest contribution to LTG variations in 375 rice accessions, and was further validated using single segment substitution line (SSSL). The presence of qLTG_sRDP2-10a could result in 59.8% increase in LTG under 15 °C low temperature. The expression analysis of the genes within qLTG_sRDP2-10a region indicated that LOC_Os10g22520 and LOC_Os10g22484 exhibited differential expression between the high and low LTG lines. Further sequence comparisons revealed that there were insertion and deletion sequence differences in the promoter and intron region of LOC_Os10g22520, and an about 6 kb variation at the 3' end of LOC_Os10g22484 between the high and low LTG lines, suggesting that the sequence variations of the two genes could be the cause for their differential expression in high and low LTG lines.ConclusionAmong the 11 QTLs identified in this study, qLTG_sRDP2-10a could also be detected in other three studies using different germplasm under different cold environments. Its large effect and stable expression make qLTG_sRDP2-10a particularly valuable in rice breeding. The two genes, LOC_Os10g22484 and LOC_Os10g22520, were considered as the candidate genes underlying qLTG_sRDP2-10a. Our results suggest that integrating GWAS and SSSL can facilitate identification of QTL for complex traits in rice. The identification of qLTG_sRDP2-10a and its candidate genes provide a promising source for gene cloning of LTG and molecular breeding for LTG in rice.

Dataset Information

Evaluating stably expressed genes in single cells.

Publications

Evaluating stably expressed genes in single cells.

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