- Genome-wide screening for functional long noncoding RNAs in human cells by Cas9 targeting of splice sites
- Identification of spatially associated subpopulations by combining scRNAseq and sequential fluorescence in situ hybridization data
- De novo assembly of haplotype-resolved genomes with trio binning
- An integrative tissue-network approach to identify and test human disease genes
- High-quality genome sequences of uncultured microbes by assembly of read clouds
1. Genome-wide screening for functional long noncoding RNAs in human cells by Cas9 targeting of splice sites
The functions of many long noncoding RNAs (lncRNAs) in the human genome remain unknown owing to the lack of scalable loss-of-function screening tools. Ying Liu at Peking University in Beijing, China and her colleagues previously used pairs of CRISPR–Cas9 single guide RNAs (sgRNAs) for small-scale functional screening of lncRNAs4. Here they demonstrate genome-wide screening of lncRNA function using sgRNAs to target splice sites and achieve exon skipping or intron retention. Splice-site targeting outperformed a conventional CRISPR library in a negative selection screen targeting 79 ribosomal genes. Using a genome-scale library of splicing-targeting sgRNAs, they performed a screen covering 10,996 lncRNAs and identified 230 that are essential for cellular growth of chronic myeloid leukemia K562 cells. Screening GM12878 lymphoblastoid cells and HeLa cells with the same library identified cell-type-specific differences in lncRNA essentiality. Extensive validation confirmed the robustness of our approach.
Read more, please click https://www.nature.com/articles/nbt.4283
2. Identification of spatially associated subpopulations by combining scRNAseq and sequential fluorescence in situ hybridization data
How intrinsic gene-regulatory networks interact with a cell’s spatial environment to define its identity remains poorly understood. Qian Zhu at Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health in Massachusetts, USA and his colleagues developed an approach to distinguish between intrinsic and extrinsic effects on global gene expression by integrating analysis of sequencing-based and imaging-based single-cell transcriptomic profiles, using cross-platform cell type mapping combined with a hidden Markov random field model. They applied this approach to dissect the cell-type- and spatial-domain-associated heterogeneity in the mouse visual cortex region. Their analysis identified distinct spatially associated, cell-type-independent signatures in the glutamatergic and astrocyte cell compartments. Using these signatures to analyze single-cell RNA sequencing data, they identified previously unknown spatially associated subpopulations, which were validated by comparison with anatomical structures and Allen Brain Atlas images.
Read more, please click https://www.nature.com/articles/nbt.4260
3. De novo assembly of haplotype-resolved genomes with trio binning
Complex allelic variation hampers the assembly of haplotype-resolved sequences from diploid genomes. Sergey Koren at National Human Genome Research Institute in Maryland, USA and his colleagues developed trio binning, an approach that simplifies haplotype assembly by resolving allelic variation before assembly. In contrast with prior approaches, the effectiveness of their method improved with increasing heterozygosity. Trio binning uses short reads from two parental genomes to first partition long reads from an offspring into haplotype-specific sets. Each haplotype is then assembled independently, resulting in a complete diploid reconstruction. They used trio binning to recover both haplotypes of a diploid human genome and identified complex structural variants missed by alternative approaches. They sequenced an F1 cross between the cattle subspecies Bos taurus taurus and Bos taurus indicus and completely assembled both parental haplotypes with NG50 haplotig sizes of >20 Mb and 99.998% accuracy, surpassing the quality of current cattle reference genomes. They suggest that trio binning improves diploid genome assembly and will facilitate new studies of haplotype variation and inheritance.
Read more, please click https://www.nature.com/articles/nbt.4277
4. An integrative tissue-network approach to identify and test human disease genes
Effective discovery of causal disease genes must overcome the statistical challenges of quantitative genetics studies and the practical limitations of human biology experiments. Here Victoria Yao at Princeton University in New Jersey, USA and his colleagues developed diseaseQUEST, an integrative approach that combines data from human genome-wide disease studies with in silico network models of tissue- and cell-type-specific function in model organisms to prioritize candidates within functionally conserved processes and pathways. They used diseaseQUEST to predict candidate genes for 25 different diseases and traits, including cancer, longevity, and neurodegenerative diseases. Focusing on Parkinson’s disease (PD), a diseaseQUEST-directed Caenhorhabditis elegans behavioral screen identified several candidate genes, which they experimentally verified and found to be associated with age-dependent motility defects mirroring PD clinical symptoms. Furthermore, knockdown of the top candidate gene, bcat-1, encoding a branched chain amino acid transferase, caused spasm-like ‘curling’ and neurodegeneration in C. elegans, paralleling decreased BCAT1 expression in PD patient brains. diseaseQUEST is modular and generalizable to other model organisms and human diseases of interest.
Read more, please click https://www.nature.com/articles/nbt.4246
5. High-quality genome sequences of uncultured microbes by assembly of read clouds
Although shotgun metagenomic sequencing of microbiome samples enables partial reconstruction of strain-level community structure, obtaining high-quality microbial genome drafts without isolation and culture remains difficult. Here, Alex Bishara at Stanford University in California, USA and his colleagues present an application of read clouds, short-read sequences tagged with long-range information, to microbiome samples. They present Athena, a de novo assembler that uses read clouds to improve metagenomic assemblies. They applied this approach to sequence stool samples from two healthy individuals and compared it with existing short-read and synthetic long-read metagenomic sequencing techniques. Read-cloud metagenomic sequencing and Athena assembly produced the most comprehensive individual genome drafts with high contiguity (>200-kb N50, fewer than ten contigs), even for bacteria with relatively low (20×) raw short-read-sequence coverage. They also sequenced a complex marine-sediment sample and generated 24 intermediate-quality genome drafts (>70% complete, <10% contaminated), nine of which were complete (>90% complete, <5% contaminated). Their approach allows for culture-free generation of high-quality microbial genome drafts by using a single shotgun experiment.
Read more, please click https://www.nature.com/articles/nbt.4266