Brain-trait-associated variants impact cell-type-specific gene regulation during neurogenesis.

Interpretation of the function of non-coding risk loci for neuropsychiatric disorders and brain-relevant traits via gene expression and alternative splicing quantitative trait locus (e/sQTL) analyses is generally performed in bulk post-mortem adult tissue. However, genetic risk loci are enriched in regulatory elements active during neocortical differentiation, and regulatory effects of risk variants may be masked by heterogeneity in bulk tissue. Here, we map e/sQTLs, and allele-specific expression in cultured cells representing two major developmental stages, primary human neural progenitors (n = 85) and their sorted neuronal progeny (n = 74), identifying numerous loci not detected in either bulk developing cortical wall or adult cortex. Using colocalization and genetic imputation via transcriptome-wide association, we uncover cell-type-specific regulatory mechanisms underlying risk for brain-relevant traits that are active during neocortical differentiation. Specifically, we identified a progenitor-specific eQTL for CENPW co-localized with common variant associations for cortical surface area and educational attainment.

Species-specific developmental timing is maintained by pluripotent stem cells ex utero.

How species-specific developmental timing is controlled is largely unknown. By following human embryonic stem (ES) cell and mouse epiblast stem (EpiS) cell differentiation through detailed RNA-sequencing time courses, here we show that pluripotent stem cells closely retain in vivo species-specific developmental timing in vitro. In identical neural differentiation conditions in vitro, gene expression profiles are accelerated in mouse EpiS cells compared to human ES cells with relative rates of differentiation closely reflecting the rates of progression through the Carnegie stages in utero. Dynamic Time Warping analysis identified 3389 genes that were regulated more quickly in mouse EpiS cells and identified none that were regulated more quickly in human ES cells. Interestingly, we also find that human ES cells differentiated in teratomas maintain the same rate of differentiation observed in vitro in spite of being grown in a mouse host. These results suggest the existence of a cell autonomous, species-specific developmental clock that pluripotent stem cells maintain even out of context of an intact embryo.

Single-round, multiplexed antibody mimetic design through mRNA display.

In a single round: By combining the high-efficiency enrichment through the continuous-flow magnetic separation (CFMS) technique with the analytical power of next-generation sequencing, the generation of antibody mimetics with a single round of mRNA display is made possible. This approach eliminates iterative selection cycles and provides a path to fully automated ligand generation (see picture).

Separating parental environment from seed size effects on next generation growth and development in Arabidopsis.

Plant growth and development is profoundly influenced by environmental conditions that laboratory experimentation typically attempts to control. However, growth conditions are not uniform between or even within laboratories and the extent to which these differences influence plant growth and development is unknown. Experiments with wild-type Arabidopsis thaliana were designed to quantify the influences of parental environment and seed size on growth and development in the next generation. A single lot of seed was planted in six environmental chambers and grown to maturity. The seed produced was mechanically sieved into small and large size classes then grown in a common environment and subjected to a set of assays spanning the life cycle. Analysis of variance demonstrated that seed size effects were particularly significant early in development, affecting primary root growth and gravitropism, but also flowering time. Parental environment affected progeny germination time, flowering and weight of seed the progeny produced. In some cases, the parental environment affected the magnitude of (interacted with) the observed seed size effects. These data indicate that life history circumstances of the parental generation can affect growth and development throughout the life cycle of the next generation to an extent that should be considered when performing genetic studies.

Cell-type-specific effects of genetic variation on chromatin accessibility during human neuronal differentiation.

Common genetic risk for neuropsychiatric disorders is enriched in regulatory elements active during cortical neurogenesis. However, it remains poorly understood as to how these variants influence gene regulation. To model the functional impact of common genetic variation on the noncoding genome during human cortical development, we performed the assay for transposase accessible chromatin using sequencing (ATAC-seq) and analyzed chromatin accessibility quantitative trait loci (QTL) in cultured human neural progenitor cells and their differentiated neuronal progeny from 87 donors. We identified significant genetic effects on 988/1,839 neuron/progenitor regulatory elements, with highly cell-type and temporally specific effects. A subset (roughly 30%) of chromatin accessibility-QTL were also associated with changes in gene expression. Motif-disrupting alleles of transcriptional activators generally led to decreases in chromatin accessibility, whereas motif-disrupting alleles of repressors led to increases in chromatin accessibility. By integrating cell-type-specific chromatin accessibility-QTL and brain-relevant genome-wide association data, we were able to fine-map and identify regulatory mechanisms underlying noncoding neuropsychiatric disorder risk loci.

Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis.

As newer single-cell protocols generate increasingly more cells at reduced sequencing depths, the value of a higher read depth may be overlooked. Using data from three different single-cell RNA-seq protocols that lend themselves to having either higher read depth (Smart-seq) or many cells (MARS-seq and 10X), we evaluate their ability to recapitulate biological signals in the context of spatial reconstruction. Overall, we find gene expression profiles after spatial reconstruction analysis are highly reproducible between datasets despite being generated by different protocols and using different computational algorithms. While UMI-based protocols such as 10X and MARS-seq allow for capturing more cells, Smart-seq's higher sensitivity and read-depth allow for analysis of lower expressed genes and isoforms. Additionally, we evaluate trade-offs for each protocol by performing subsampling analyses and find that optimizing the balance between sequencing depth and number of cells within a protocol is necessary for efficient use of resources. Our analysis emphasizes the importance of selecting a protocol based on the biological questions and features of interest.

A cost-effective RNA sequencing protocol for large-scale gene expression studies.

RNA sequencing has increasingly become an indispensable tool for biological research. While sequencing costs have fallen dramatically in recent years, the current cost of RNA sequencing, nonetheless, remains a barrier to even more widespread adoption. Here, we present a simple RNA sequencing protocol with substantially reduced costs. This protocol uses as little as 10 ng of total RNA, allows multiplex sequencing of up to 96 samples per lane, and is strand specific. Extensive validation using human embryonic stem cells showed high consistency between technical replicates at various multiplexing levels.

Single read and paired end mRNA-Seq Illumina libraries from 10 nanograms total RNA.

Whole transcriptome sequencing by mRNA-Seq is now used extensively to perform global gene expression, mutation, allele-specific expression and other genome-wide analyses. mRNA-Seq even opens the gate for gene expression analysis of non-sequenced genomes. mRNA-Seq offers high sensitivity, a large dynamic range and allows measurement of transcript copy numbers in a sample. Illumina's genome analyzer performs sequencing of a large number (> 10(7)) of relatively short sequence reads (< 150 bp).The "paired end" approach, wherein a single long read is sequenced at both its ends, allows for tracking alternate splice junctions, insertions and deletions, and is useful for de novo transcriptome assembly. One of the major challenges faced by researchers is a limited amount of starting material. For example, in experiments where cells are harvested by laser micro-dissection, available starting total RNA may measure in nanograms. Preparation of mRNA-Seq libraries from such samples have been described(1, 2) but involves significant PCR amplification that may introduce bias. Other RNA-Seq library construction procedures with minimal PCR amplification have been published(3, 4) but require microgram amounts of starting total RNA. Here we describe a protocol for the Illumina Genome Analyzer II platform for mRNA-Seq sequencing for library preparation that avoids significant PCR amplification and requires only 10 nanograms of total RNA. While this protocol has been described previously and validated for single-end sequencing(5), where it was shown to produce directional libraries without introducing significant amplification bias, here we validate it further for use as a paired end protocol. We selectively amplify polyadenylated messenger RNAs from starting total RNA using the T7 based Eberwine linear amplification method, coined "T7LA" (T7 linear amplification). The amplified poly-A mRNAs are fragmented, reverse transcribed and adapter ligated to produce the final sequencing library. For both single read and paired end runs, sequences are mapped to the human transcriptome(6) and normalized so that data from multiple runs can be compared. We report the gene expression measurement in units of transcripts per million (TPM), which is a superior measure to RPKM when comparing samples(7).