Aging disrupts circadian gene regulation and function in macrophages.

Aging is characterized by an increased vulnerability to infection and the development of inflammatory diseases, such as atherosclerosis, frailty, cancer and neurodegeneration. Here, we find that aging is associated with the loss of diurnally rhythmic innate immune responses, including monocyte trafficking from bone marrow to blood, response to lipopolysaccharide and phagocytosis. This decline in homeostatic immune responses was associated with a striking disappearance of circadian gene transcription in aged compared to young tissue macrophages. Chromatin accessibility was significantly greater in young macrophages than in aged macrophages; however, this difference did not explain the loss of rhythmic gene transcription in aged macrophages. Rather, diurnal expression of Kruppel-like factor 4 (Klf4), a transcription factor (TF) well established in regulating cell differentiation and reprogramming, was selectively diminished in aged macrophages. Ablation of Klf4 expression abolished diurnal rhythms in phagocytic activity, recapitulating the effect of aging on macrophage phagocytosis. Examination of individuals harboring genetic variants of KLF4 revealed an association with age-dependent susceptibility to death caused by bacterial infection. Our results indicate that loss of rhythmic Klf4 expression in aged macrophages is associated with disruption of circadian innate immune homeostasis, a mechanism that may underlie age-associated loss of protective immune responses.

Psychosocial experiences are associated with human brain mitochondrial biology.

Psychosocial experiences affect brain health and aging trajectories, but the molecular pathways underlying these associations remain unclear. Normal brain function relies on energy transformation by mitochondria oxidative phosphorylation (OxPhos). Two main lines of evidence position mitochondria both as targets and drivers of psychosocial experiences. On the one hand, chronic stress exposure and mood states may alter multiple aspects of mitochondrial biology; on the other hand, functional variations in mitochondrial OxPhos capacity may alter social behavior, stress reactivity, and mood. But are psychosocial exposures and subjective experiences linked to mitochondrial biology in the human brain? By combining longitudinal antemortem assessments of psychosocial factors with postmortem brain (dorsolateral prefrontal cortex) proteomics in older adults, we find that higher well-being is linked to greater abundance of the mitochondrial OxPhos machinery, whereas higher negative mood is linked to lower OxPhos protein content. Combined, positive and negative psychosocial factors explained 18 to 25% of the variance in the abundance of OxPhos complex I, the primary biochemical entry point that energizes brain mitochondria. Moreover, interrogating mitochondrial psychobiological associations in specific neuronal and nonneuronal brain cells with single-nucleus RNA sequencing (RNA-seq) revealed strong cell-type-specific associations for positive psychosocial experiences and mitochondria in glia but opposite associations in neurons. As a result, these "mind-mitochondria" associations were masked in bulk RNA-seq, highlighting the likely underestimation of true psychobiological effect sizes in bulk brain tissues. Thus, self-reported psychosocial experiences are linked to human brain mitochondrial phenotypes.

Genotype-phenotype correlation of T-cell subtypes reveals senescent and cytotoxic genes in Alzheimer's disease.

Recent studies identifying expression quantitative trait loci (eQTLs) in immune cells have uncovered important links between disease risk alleles and gene expression trends in monocytes, T cells and other cell types. However, these studies are generally done with young, healthy subjects, limiting the utility of their findings for age-related conditions such as Alzheimer's disease (AD). We have performed RNA sequencing on four T-cell subsets in genome-wide genotyped and well-characterized AD subjects and age- and sex-matched controls from the Religious Orders Study/Memory and Aging Project. We correlated gene expression data with AD neuropathological traits and with single-nucleotide polymorphisms to detect eQTLs. We identified several significant genes involved in T-cell senescence and cytotoxicity, consistent with T-cell RNA sequencing studies in aged/AD cohorts. We identified unexpected eQTLs previously associated with neuropsychiatric disease traits. Finally, we discovered that pathways related to axon guidance and synaptic function were enriched among trans-eQTLs in coding regions of the genome. Our data strengthen the potential link between T-cell senescence and age-related neurodegenerative disease. In addition, our eQTL data suggest that T-cell phenotypes may influence neuropsychiatric disorders and can be influenced by genes involved in neurodevelopmental processes.

Associations of VGF with Neuropathologies and Cognitive Health in Older Adults.

OBJECTIVE: VGF is proposed as a potential therapeutic target for Alzheimer's (AD) and other neurodegenerative conditions. The cell-type specific and, separately, peptide specific associations of VGF with pathologic and cognitive outcomes remain largely unknown. We leveraged gene expression and protein data from the human neocortex and investigated the VGF associations with common neuropathologies and late-life cognitive decline. METHODS: Community-dwelling older adults were followed every year, died, and underwent brain autopsy. Cognitive decline was captured via annual cognitive testing. Common neurodegenerative and cerebrovascular conditions were assessed during neuropathologic evaluations. Bulk brain RNASeq and targeted proteomics analyses were conducted using frozen tissues from dorsolateral prefrontal cortex of 1,020 individuals. Cell-type specific gene expressions were quantified in a subsample (N = 424) following single nuclei RNASeq analysis from the same cortex. RESULTS: The bulk brain VGF gene expression was primarily associated with AD and Lewy bodies. The VGF gene association with cognitive decline was in part accounted for by neuropathologies. Similar associations were observed for the VGF protein. Cell-type specific analyses revealed that, while VGF was differentially expressed in most major cell types in the cortex, its association with neuropathologies and cognitive decline was restricted to the neuronal cells. Further, the peptide fragments across the VGF polypeptide resembled each other in relation to neuropathologies and cognitive decline. INTERPRETATION: Multiple pathways link VGF to cognitive health in older age, including neurodegeneration. The VGF gene functions primarily in neuronal cells and its protein associations with pathologic and cognitive outcomes do not map to a specific peptide. ANN NEUROL 2023;94:232-244.

Xenografted human iPSC-derived neurons with the familial Alzheimer's disease APPV717I mutation reveal dysregulated transcriptome signatures linked to synaptic function and implicate LINGO2 as a disease signaling mediator.

Alzheimer's disease (AD) is the most common cause of dementia, and disease mechanisms are still not fully understood. Here, we explored pathological changes in human induced pluripotent stem cell (iPSC)-derived neurons carrying the familial AD APPV717I mutation after cell injection into the mouse forebrain. APPV717I mutant iPSCs and isogenic controls were differentiated into neurons revealing enhanced Aß42 production, elevated phospho-tau, and impaired neurite outgrowth in APPV717I neurons. Two months after transplantation, APPV717I and control neural cells showed robust engraftment but at 12 months post-injection, APPV717I grafts were smaller and demonstrated impaired neurite outgrowth compared to controls, while plaque and tangle pathology were not seen. Single-nucleus RNA-sequencing of micro-dissected grafts, performed 2 months after cell injection, identified significantly altered transcriptome signatures in APPV717I iPSC-derived neurons pointing towards dysregulated synaptic function and axon guidance. Interestingly, APPV717I neurons showed an increased expression of genes, many of which are also upregulated in postmortem neurons of AD patients including the transmembrane protein LINGO2. Downregulation of LINGO2 in cultured APPV717I neurons rescued neurite outgrowth deficits and reversed key AD-associated transcriptional changes related but not limited to synaptic function, apoptosis and cellular senescence. These results provide important insights into transcriptional dysregulation in xenografted APPV717I neurons linked to synaptic function, and they indicate that LINGO2 may represent a potential therapeutic target in AD.

Distinct descending motor cortex pathways and their roles in movement.

Activity in the motor cortex predicts movements, seconds before they are initiated. This preparatory activity has been observed across cortical layers, including in descending pyramidal tract neurons in layer 5. A key question is how preparatory activity is maintained without causing movement, and is ultimately converted to a motor command to trigger appropriate movements. Here, using single-cell transcriptional profiling and axonal reconstructions, we identify two types of pyramidal tract neuron. Both types project to several targets in the basal ganglia and brainstem. One type projects to thalamic regions that connect back to motor cortex; populations of these neurons produced early preparatory activity that persisted until the movement was initiated. The second type projects to motor centres in the medulla and mainly produced late preparatory activity and motor commands. These results indicate that two types of motor cortex output neurons have specialized roles in motor control.

Shared and distinct transcriptomic cell types across neocortical areas.

The neocortex contains a multitude of cell types that are segregated into layers and functionally distinct areas. To investigate the diversity of cell types across the mouse neocortex, here we analysed 23,822 cells from two areas at distant poles of the mouse neocortex: the primary visual cortex and the anterior lateral motor cortex. We define 133 transcriptomic cell types by deep, single-cell RNA sequencing. Nearly all types of GABA (γ-aminobutyric acid)-containing neurons are shared across both areas, whereas most types of glutamatergic neurons were found in one of the two areas. By combining single-cell RNA sequencing and retrograde labelling, we match transcriptomic types of glutamatergic neurons to their long-range projection specificity. Our study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex.

Complexity and graded regulation of neuronal cell-type-specific alternative splicing revealed by single-cell RNA sequencing.

The enormous cellular diversity in the mammalian brain, which is highly prototypical and organized in a hierarchical manner, is dictated by cell-type-specific gene-regulatory programs at the molecular level. Although prevalent in the brain, the contribution of alternative splicing (AS) to the molecular diversity across neuronal cell types is just starting to emerge. Here, we systematically investigated AS regulation across over 100 transcriptomically defined neuronal types of the adult mouse cortex using deep single-cell RNA-sequencing data. We found distinct splicing programs between glutamatergic and GABAergic neurons and between subclasses within each neuronal class. These programs consist of overlapping sets of alternative exons showing differential splicing at multiple hierarchical levels. Using an integrative approach, our analysis suggests that RNA-binding proteins (RBPs) Celf1/2, Mbnl2, and Khdrbs3 are preferentially expressed and more active in glutamatergic neurons, while Elavl2 and Qk are preferentially expressed and more active in GABAergic neurons. Importantly, these and additional RBPs also contribute to differential splicing between neuronal subclasses at multiple hierarchical levels, and some RBPs contribute to splicing dynamics that do not conform to the hierarchical structure defined by the transcriptional profiles. Thus, our results suggest graded regulation of AS across neuronal cell types, which may provide a molecular mechanism to specify neuronal identity and function that are orthogonal to established classifications based on transcriptional regulation.

Proteins linking APOE ɛ4 with Alzheimer's disease.

INTRODUCTION: The ɛ4 allele of the apolipoprotein E gene (APOE ɛ4) is the strongest genetic risk factor for Alzheimer's disease (AD), but the mechanisms connecting APOE ɛ4 to AD are not clear. METHODS: Participants (n = 596) were from two clinical-pathological studies. Tissues from dorsolateral prefrontal cortex were examined to identify 8425 proteins. Post mortem pathological assessment used immunohistochemistry to obtain amyloid beta (Aß) load and tau tangle density. RESULTS: In separate models, APOE ɛ4 was associated with 18 proteins, which were associated with Aß and tau tangles. Examining the proteins in a single model identified Netrin-1 and secreted frizzled-related protein 1 (SFRP1) as the two proteins linking APOE ɛ4 with Aß with the largest effect sizes and Netrin-1 and testican-3 linking APOE ɛ4 with tau tangles. DISCUSSION: We identified Netrin-1, SFRP1, and testican-3 as the most promising proteins that link APOE ɛ4 with Aß and tau tangles. HIGHLIGHTS: Of 8425 proteins extracted from prefrontal cortex, 18 were related to APOE ɛ4. The 18 proteins were also related to amyloid beta (Aß) and tau. The 18 proteins were more related to APOE ɛ4 than other AD genetic risk variants. Netrin-1 and secreted frizzled-related protein 1 were the two most promising proteins linking APOE ɛ4 with Aß. Netrin-1 and testican-3 were two most promising proteins linking APOE ɛ4 with tau.

Associations of cortical SPP1 and ITGAX with cognition and common neuropathologies in older adults.

INTRODUCTION: The secreted phosphoprotein 1 (SPP1) gene expressed by CD11c+ cells is known to be associated with microglia activation and neuroinflammatory diseases. As most studies rely on mouse models, we investigated these genes and proteins in the cortical brain tissue of older adults and their role in Alzheimer's disease (AD) and related disorders. METHODS: We leveraged protein measurements, single-nuclei, and RNASeq data from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) of over 1200 samples for association analysis. RESULTS: Expression of SPP1 and its encoded protein osteopontin were associated with faster cognitive decline and greater odds of common neuropathologies. At single-cell resolution,  integrin subunit alpha X (ITGAX) was highly expressed in microglia, where specific subpopulations were associated with AD and cerebral amyloid angiopathy. DISCUSSION: The study provides evidence of SPP1 and ITGAX association with cognitive decline and common neuropathologies identifying a microglial subset associated with disease.

TREM2 gene expression associations with Alzheimer's disease neuropathology are region-specific: implications for cortical versus subcortical microglia.

Previous post-mortem assessments of TREM2 expression and its association with brain pathologies have been limited by sample size. This study sought to correlate region-specific TREM2 mRNA expression with diverse neuropathological measures at autopsy using a large sample size (N = 945) of bulk RNA sequencing data from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP). TREM2 gene expression of the dorsolateral prefrontal cortex, posterior cingulate cortex, and caudate nucleus was assessed with respect to core pathology of Alzheimer's disease (amyloid-ß, and tau), cerebrovascular pathology (cerebral infarcts, arteriolosclerosis, atherosclerosis, and cerebral amyloid angiopathy), microglial activation (proportion of activated microglia), and cognitive performance. We found that cortical TREM2 levels were positively related to AD diagnosis, cognitive decline, and amyloid-ß neuropathology but were not related to the proportion of activated microglia. In contrast, caudate TREM2 levels were not related to AD pathology, cognition, or diagnosis, but were positively related to the proportion of activated microglia in the same region. Diagnosis-stratified results revealed caudate TREM2 levels were inversely related to AD neuropathology and positively related to microglial activation and longitudinal cognitive performance in AD cases. These results highlight the notable changes in TREM2 transcript abundance in AD and suggest that its pathological associations are brain-region-dependent.

Fragmentation of rest periods, astrocyte activation, and cognitive decline in older adults with and without Alzheimer's disease.

INTRODUCTION: Sleep disruption is associated with astrocyte activation and impaired cognition in model organisms. However, the relationship among sleep, astrocyte activation, and cognition in humans is uncertain. METHODS: We used RNA-seq to quantify the prefrontal cortex expression of a panel of human activated astrocyte marker genes in 1076 older adults in the Religious Orders Study and Rush Memory and Aging Project, 411 of whom had multi-day actigraphy prior to death. We related this to rest fragmentation, a proxy for sleep fragmentation, and to longitudinal cognitive function. RESULTS: Fragmentation of rest periods was associated with higher expression of activated astrocyte marker genes, which was associated with a lower level and faster decline of cognitive function. DISCUSSION: Astrocyte activation and fragmented rest are associated with each other and with accelerated cognitive decline. If experimental studies confirm a causal relationship, targeting sleep fragmentation and astrocyte activation may benefit cognition in older adults. HIGHLIGHTS: Greater fragmentation of rest periods, a proxy for sleep fragmentation, is associated with higher composite expression of a panel of genes characteristic of activated astrocytes. Increased expression of genes characteristic of activated astrocytes was associated with a lower level and more rapid decline of cognitive function, beyond that accounted for by the burden of amyloid and neurofibrillary tangle pathology. Longitudinal and experimental studies are needed to delineate the causal relationships among sleep, astrocyte activation, and cognition.

FMNL2 regulates gliovascular interactions and is associated with vascular risk factors and cerebrovascular pathology in Alzheimer's disease.

Alzheimer's disease (AD) has been associated with cardiovascular and cerebrovascular risk factors (CVRFs) during middle age and later and is frequently accompanied by cerebrovascular pathology at death. An interaction between CVRFs and genetic variants might explain the pathogenesis. Genome-wide, gene by CVRF interaction analyses for AD, in 6568 patients and 8101 controls identified FMNL2 (p = 6.6 × 10-7). A significant increase in FMNL2 expression was observed in the brains of patients with brain infarcts and AD pathology and was associated with amyloid and phosphorylated tau deposition. FMNL2 was also prominent in astroglia in AD among those with cerebrovascular pathology. Amyloid toxicity in zebrafish increased fmnl2a expression in astroglia with detachment of astroglial end feet from blood vessels. Knockdown of fmnl2a prevented gliovascular remodeling, reduced microglial activity and enhanced amyloidosis. APP/PS1dE9 AD mice also displayed increased Fmnl2 expression and reduced the gliovascular contacts independent of the gliotic response. Based on this work, we propose that FMNL2 regulates pathology-dependent plasticity of the blood-brain-barrier by controlling gliovascular interactions and stimulating the clearance of extracellular aggregates. Therefore, in AD cerebrovascular risk factors promote cerebrovascular pathology which in turn, interacts with FMNL2 altering the normal astroglial-vascular mechanisms underlying the clearance of amyloid and tau increasing their deposition in brain.

Epigenomic features related to microglia are associated with attenuated effect of APOE ε4 on Alzheimer's disease risk in humans.

Not all apolipoprotein E (APOE) ε4 carriers who survive to advanced age develop Alzheimer's disease (AD); factors attenuating the risk of ε4 on AD may exist. Guided by the top ε4-attenuating signals from methylome-wide association analyses (N = 572, ε4+ and ε4-) of neurofibrillary tangles and neuritic plaques, we conducted a meta-analysis for pathological AD within the ε4+ subgroups (N = 235) across four independent collections of brains. Cortical RNA-seq and microglial morphology measurements were used in functional analyses. Three out of the four significant CpG dinucleotides were captured by one principal component (PC1), which interacts with ε4 on AD, and is associated with expression of innate immune genes and activated microglia. In ε4 carriers, reduction in each unit of PC1 attenuated the odds of AD by 58% (odds ratio = 2.39, 95% confidence interval = [1.64,3.46], P = 7.08 × 10-6 ). An epigenomic factor associated with a reduced proportion of activated microglia (epigenomic factor of activated microglia, EFAM) appears to attenuate the risk of ε4 on AD.

Selecting single cell clustering parameter values using subsampling-based robustness metrics.

BACKGROUND: Generating and analysing single-cell data has become a widespread approach to examine tissue heterogeneity, and numerous algorithms exist for clustering these datasets to identify putative cell types with shared transcriptomic signatures. However, many of these clustering workflows rely on user-tuned parameter values, tailored to each dataset, to identify a set of biologically relevant clusters. Whereas users often develop their own intuition as to the optimal range of parameters for clustering on each data set, the lack of systematic approaches to identify this range can be daunting to new users of any given workflow. In addition, an optimal parameter set does not guarantee that all clusters are equally well-resolved, given the heterogeneity in transcriptomic signatures in most biological systems. RESULTS: Here, we illustrate a subsampling-based approach (chooseR) that simultaneously guides parameter selection and characterizes cluster robustness. Through bootstrapped iterative clustering across a range of parameters, chooseR was used to select parameter values for two distinct clustering workflows (Seurat and scVI). In each case, chooseR identified parameters that produced biologically relevant clusters from both well-characterized (human PBMC) and complex (mouse spinal cord) datasets. Moreover, it provided a simple "robustness score" for each of these clusters, facilitating the assessment of cluster quality. CONCLUSION: chooseR is a simple, conceptually understandable tool that can be used flexibly across clustering algorithms, workflows, and datasets to guide clustering parameter selection and characterize cluster robustness.

scOrange-a tool for hands-on training of concepts from single-cell data analytics.

MOTIVATION: Single-cell RNA sequencing allows us to simultaneously profile the transcriptomes of thousands of cells and to indulge in exploring cell diversity, development and discovery of new molecular mechanisms. Analysis of scRNA data involves a combination of non-trivial steps from statistics, data visualization, bioinformatics and machine learning. Training molecular biologists in single-cell data analysis and empowering them to review and analyze their data can be challenging, both because of the complexity of the methods and the steep learning curve. RESULTS: We propose a workshop-style training in single-cell data analytics that relies on an explorative data analysis toolbox and a hands-on teaching style. The training relies on scOrange, a newly developed extension of a data mining framework that features workflow design through visual programming and interactive visualizations. Workshops with scOrange can proceed much faster than similar training methods that rely on computer programming and analysis through scripting in R or Python, allowing the trainer to cover more ground in the same time-frame. We here review the design principles of the scOrange toolbox that support such workshops and propose a syllabus for the course. We also provide examples of data analysis workflows that instructors can use during the training. AVAILABILITY AND IMPLEMENTATION: scOrange is an open-source software. The software, documentation and an emerging set of educational videos are available at http://singlecell.biolab.si.

EPIGENOMIC FEATURES RELATED TO MICROGLIA ARE ASSOCIATED WITH ATTENUATED EFFECT OF APOE ε4 ON ALZHEIMER'S DISEASE RISK IN HUMANS.

Not all APOE ε4 carriers who survive to advanced age develop Alzheimer's disease (AD); factors attenuating the risk of ε4 on AD may exist. Guided by the top ε4-attenuating signals from methylome-wide association analyses (N=572, ε4+ and ε4-) of neurofibrillary tangles and neuritic plaques, we conducted a meta-analysis for pathological AD within the ε4+ subgroups (N=235) across four independent collections of brains. Cortical RNA-seq and microglial morphology measurements were used in functional analyses. Three out of the four significant CpG dinucleotides were captured by one principle component (PC1), which interacts with ε4 on AD, and is associated with expression of innate immune genes and activated microglia. In ε4 carriers, reduction in each unit of PC1 attenuated the odds of AD by 58% (OR=2.39, 95%CI=[1.64,3.46], P=7.08x10-6). An epigenomic factor associated with a reduced proportion of activated microglia (microglial epigenomic factor 1) appears to attenuate the risk of ε4 on AD.

Genome engineering of isogenic human ES cells to model autism disorders.

Isogenic pluripotent stem cells are critical tools for studying human neurological diseases by allowing one to study the effects of a mutation in a fixed genetic background. Of particular interest are the spectrum of autism disorders, some of which are monogenic such as Timothy syndrome (TS); others are multigenic such as the microdeletion and microduplication syndromes of the 16p11.2 chromosomal locus. Here, we report engineered human embryonic stem cell (hESC) lines for modeling these two disorders using locus-specific endonucleases to increase the efficiency of homology-directed repair (HDR). We developed a system to: (1) computationally identify unique transcription activator-like effector nuclease (TALEN) binding sites in the genome using a new software program, TALENSeek, (2) assemble the TALEN genes by combining golden gate cloning with modified constructs from the FLASH protocol, and (3) test the TALEN pairs in an amplification-based HDR assay that is more sensitive than the typical non-homologous end joining assay. We applied these methods to identify, construct, and test TALENs that were used with HDR donors in hESCs to generate an isogenic TS cell line in a scarless manner and to model the 16p11.2 copy number disorder without modifying genomic loci with high sequence similarity.

Correlated gene expression and target specificity demonstrate excitatory projection neuron diversity.

The neocortex contains diverse populations of excitatory neurons segregated by layer and further definable by their specific cortical and subcortical projection targets. The current study describes a systematic approach to identify molecular correlates of specific projection neuron classes in mouse primary somatosensory cortex (S1), using a combination of in situ hybridization (ISH) data mining, marker gene colocalization, and combined retrograde labeling with ISH for layer-specific marker genes. First, we identified a large set of genes with specificity for each cortical layer, and that display heterogeneous patterns within those layers. Using these genes as markers, we find extensive evidence for the covariation of gene expression and projection target specificity in layer 2/3, 5, and 6, with individual genes labeling neurons projecting to specific subsets of target structures. The combination of gene expression and target specificity imply a great diversity of projection neuron classes that is similar to or greater than that of GABAergic interneurons. The covariance of these 2 phenotypic modalities suggests that these classes are both discrete and genetically specified.

Improving reliability and absolute quantification of human brain microarray data by filtering and scaling probes using RNA-Seq.

BACKGROUND: High-throughput sequencing is gradually replacing microarrays as the preferred method for studying mRNA expression levels, providing nucleotide resolution and accurately measuring absolute expression levels of almost any transcript, known or novel. However, existing microarray data from clinical, pharmaceutical, and academic settings represent valuable and often underappreciated resources, and methods for assessing and improving the quality of these data are lacking. RESULTS: To quantitatively assess the quality of microarray probes, we directly compare RNA-Seq to Agilent microarrays by processing 231 unique samples from the Allen Human Brain Atlas using RNA-Seq. Both techniques provide highly consistent, highly reproducible gene expression measurements in adult human brain, with RNA-Seq slightly outperforming microarray results overall. We show that RNA-Seq can be used as ground truth to assess the reliability of most microarray probes, remove probes with off-target effects, and scale probe intensities to match the expression levels identified by RNA-Seq. These sequencing scaled microarray intensities (SSMIs) provide more reliable, quantitative estimates of absolute expression levels for many genes when compared with unscaled intensities. Finally, we validate this result in two human cell lines, showing that linear scaling factors can be applied across experiments using the same microarray platform. CONCLUSIONS: Microarrays provide consistent, reproducible gene expression measurements, which are improved using RNA-Seq as ground truth. We expect that our strategy could be used to improve probe quality for many data sets from major existing repositories.