Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples

RNA-Seq is an effective method to study the transcriptome, but can be difficult to apply to scarce or degraded RNA from fixed clinical samples, rare cell populations, or cadavers. Recent studies have proposed several methods for RNA-Seq of low quality and/or low quantity samples, but their relative merits have not been systematically analyzed. Here, we compare five such methods using metrics relevant to transcriptome annotation, transcript discovery, and gene expression. Using a single human RNA sample, we constructed and sequenced ten libraries with these methods and two control libraries. We find that the RNase H method performed best for low quality RNA, and confirmed this with actual degraded samples. RNase H can even effectively replace oligo (dT) based methods for standard RNA-Seq. SMART and NuGEN had distinct strengths for low quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development

Single-Cell RNA Sequencing of Microglia throughout the Mouse Lifespan and in the Injured Brain Reveals Complex Cell-State Changes.

Microglia, the resident immune cells of the brain, rapidly change states in response to their environment, but we lack molecular and functional signatures of different microglial populations. Here, we analyzed the RNA expression patterns of more than 76,000 individual microglia in mice during development, in old age, and after brain injury. Our analysis uncovered at least nine transcriptionally distinct microglial states, which expressed unique sets of genes and were localized in the brain using specific markers. The greatest microglial heterogeneity was found at young ages; however, several states-including chemokine-enriched inflammatory microglia-persisted throughout the lifespan or increased in the aged brain. Multiple reactive microglial subtypes were also found following demyelinating injury in mice, at least one of which was also found in human multiple sclerosis lesions. These distinct microglia signatures can be used to better understand microglia function and to identify and manipulate specific subpopulations in health and disease

Comparative analysis of RNA sequencing methods for degraded or low-input samples

available in PMC 2014 January 01RNA-seq is an effective method for studying the transcriptome, but it can be difficult to apply to scarce or degraded RNA from fixed clinical samples, rare cell populations or cadavers. Recent studies have proposed several methods for RNA-seq of low-quality and/or low-quantity samples, but the relative merits of these methods have not been systematically analyzed. Here we compare five such methods using metrics relevant to transcriptome annotation, transcript discovery and gene expression. Using a single human RNA sample, we constructed and sequenced ten libraries with these methods and compared them against two control libraries. We found that the RNase H method performed best for chemically fragmented, low-quality RNA, and we confirmed this through analysis of actual degraded samples. RNase H can even effectively replace oligo(dT)-based methods for standard RNA-seq. SMART and NuGEN had distinct strengths for measuring low-quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development.National Institutes of Health (U.S.) (Pioneer Award DP1-OD003958-01)National Human Genome Research Institute (U.S.) (NHGRI) 1P01HG005062-01)National Human Genome Research Institute (U.S.) (NHGRI Center of Excellence in Genome Science Award 1P50HG006193-01)Howard Hughes Medical Institute (Investigator)Merkin Family Foundation for Stem Cell ResearchBroad Institute of MIT and Harvard (Klarman Cell Observatory)National Human Genome Research Institute (U.S.) (NHGRI grant HG03067)Fonds voor Wetenschappelijk Onderzoek--Vlaandere

Innovations present in the primate interneuron repertoire

Primates and rodents, which descended from a common ancestor around 90 million years ago , exhibit profound differences in behaviour and cognitive capacity; the cellular basis for these differences is unknown. Here we use single-nucleus RNA sequencing to profile RNA expression in 188,776 individual interneurons across homologous brain regions from three primates (human, macaque and marmoset), a rodent (mouse) and a weasel (ferret). Homologous interneuron types—which were readily identified by their RNA-expression patterns—varied in abundance and RNA expression among ferrets, mice and primates, but varied less among primates. Only a modest fraction of the genes identified as ‘markers’ of specific interneuron subtypes in any one species had this property in another species. In the primate neocortex, dozens of genes showed spatial expression gradients among interneurons of the same type, which suggests that regional variation in cortical contexts shapes the RNA expression patterns of adult neocortical interneurons. We found that an interneuron type that was previously associated with the mouse hippocampus—the ‘ivy cell’, which has neurogliaform characteristics—has become abundant across the neocortex of humans, macaques and marmosets but not mice or ferrets. We also found a notable subcortical innovation: an abundant striatal interneuron type in primates that had no molecularly homologous counterpart in mice or ferrets. These interneurons expressed a unique combination of genes that encode transcription factors, receptors and neuropeptides and constituted around 30% of striatal interneurons in marmosets and humans