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Researchers from New York University and the New York Genome Center have developed an approach that combines gene editing, genome-wide association studies (GWAS), and single-cell sequencing to identify causal variants and genetic mechanisms for blood cell traits. As highlighted in their latest publication in Science, the approach is designed to address the challenge of determining which parts of the genome drive specific traits or contribute to disease risk.
GWAS have been increasingly used over the past 20 years to identify genetic mutations associated with various diseases and traits. By comparing the genomes of large populations, scientists can identify variants that occur more frequently in individuals with those diseases or traits. However, the associations are generally found in the non-coding regions of the genome, which is not well understood. The linkage between variants located near each other also adds complexity in determining the causal role of a particular variant, as well as the gene it affects
“A major goal for the study of human diseases is to identify causal genes and variants, which can clarify biological mechanisms and inform drug targets for these diseases,” said Neville Sanjana, the study’s co-senior author and associate professor of biology at NYU.
Treatment for sickle cell anemia
A new breakthrough in treating sickle cell anemia shows the power of combining GWAS with gene-editing technology. The researchers used GWAS to identify regions of the genome associated with producing fetal hemoglobin, which has the potential to reverse the disease. However, they didn't know the specific variant responsible for its production.
They turned to the popular gene-editing tool, CRISPR, to identify the exact variant. By editing a specific location near the BCL11A gene, they were able to achieve high levels of fetal hemoglobin. This technique has been used in clinical trials to cure sickle cell anemia by editing bone marrow cells in dozens of patients, who then begin producing fetal hemoglobin, effectively replacing the mutated adult form and curing the disease.
“This success story in treating sickle cell disease is a result of combining insights from GWAS with gene editing,” said Sanjana. “But it took years of research on only one disease. How do we scale this up to better identify causal variants and target genes from GWAS?”
Combining GWAS with CRISPR and single-cell sequencing
The researchers from the study developed a new system named STING-seq, which stands for Systematic Targeting and Inhibition of Noncoding GWAS loci with single-cell sequencing. This process uses biobank-scale GWAS to identify probable causal variants by combining biochemical markers and regulatory elements. They then employed CRISPR to target these regions and conducted single-cell sequencing to assess gene and protein expression. Using this approach, the researchers identified candidate regions of the genome that may be involved in blood traits, which were previously well-studied in GWAS, based on the analysis of nearly 750,000 individuals from diverse backgrounds. After they identified 543 candidate regions, they utilized CRISPR inhibition, a version of CRISPR that can precisely silence regions of the genome.
Once the regions identified by GWAS were silenced, the researchers evaluated the expression of nearby genes in individual cells. By doing so, they were able to link specific noncoding regions to target genes and pinpoint which noncoding regions are central to specific traits, eliminating the guesswork that scientists previously encountered when faced with linkage among variants or genes closest to variants. For example, in the case of a blood trait called monocyte count, applying CRISPR caused one gene, CD52, to clearly stand out as significantly altered, despite not being the closest gene to the variant of interest.
In a separate analysis, the researchers used STING-seq to isolate noncoding variants that were causal for a gene called PTPRC, which is associated with 10 blood traits. By seeing which variants changed PTPRC expression, the researchers were able to understand which noncoding variants could modulate PTPRC expression and contribute to the development of these blood traits.
The future of STING-seq
STING-seq has proved to be a valuable tool for identifying target genes and causal variants, but it cannot determine whether a noncoding variant will increase or decrease the expression of a nearby gene. To overcome this limitation, the researchers developed a complementary approach called beeSTING-seq (base editing STING-seq). This technique involves using CRISPR to insert a genetic variant instead of inhibiting the region of the genome. By doing so, the researchers can determine the direction of the effect and whether a specific noncoding variant increases or decreases the expression of a nearby gene.
STING-seq and beeSTING-seq have the potential to revolutionize the identification of causal variants for a variety of diseases. These techniques can be used to develop gene-editing therapies for diseases like sickle cell anemia or to develop drugs that target specific genes or cellular pathways. By precisely identifying causal variants, researchers can gain a deeper understanding of the underlying biology of diseases, leading to new treatments and better patient outcomes.
GWAS have been increasingly used over the past 20 years to identify genetic mutations associated with various diseases and traits. By comparing the genomes of large populations, scientists can identify variants that occur more frequently in individuals with those diseases or traits. However, the associations are generally found in the non-coding regions of the genome, which is not well understood. The linkage between variants located near each other also adds complexity in determining the causal role of a particular variant, as well as the gene it affects
“A major goal for the study of human diseases is to identify causal genes and variants, which can clarify biological mechanisms and inform drug targets for these diseases,” said Neville Sanjana, the study’s co-senior author and associate professor of biology at NYU.
Treatment for sickle cell anemia
A new breakthrough in treating sickle cell anemia shows the power of combining GWAS with gene-editing technology. The researchers used GWAS to identify regions of the genome associated with producing fetal hemoglobin, which has the potential to reverse the disease. However, they didn't know the specific variant responsible for its production.
They turned to the popular gene-editing tool, CRISPR, to identify the exact variant. By editing a specific location near the BCL11A gene, they were able to achieve high levels of fetal hemoglobin. This technique has been used in clinical trials to cure sickle cell anemia by editing bone marrow cells in dozens of patients, who then begin producing fetal hemoglobin, effectively replacing the mutated adult form and curing the disease.
“This success story in treating sickle cell disease is a result of combining insights from GWAS with gene editing,” said Sanjana. “But it took years of research on only one disease. How do we scale this up to better identify causal variants and target genes from GWAS?”
Combining GWAS with CRISPR and single-cell sequencing
The researchers from the study developed a new system named STING-seq, which stands for Systematic Targeting and Inhibition of Noncoding GWAS loci with single-cell sequencing. This process uses biobank-scale GWAS to identify probable causal variants by combining biochemical markers and regulatory elements. They then employed CRISPR to target these regions and conducted single-cell sequencing to assess gene and protein expression. Using this approach, the researchers identified candidate regions of the genome that may be involved in blood traits, which were previously well-studied in GWAS, based on the analysis of nearly 750,000 individuals from diverse backgrounds. After they identified 543 candidate regions, they utilized CRISPR inhibition, a version of CRISPR that can precisely silence regions of the genome.
Once the regions identified by GWAS were silenced, the researchers evaluated the expression of nearby genes in individual cells. By doing so, they were able to link specific noncoding regions to target genes and pinpoint which noncoding regions are central to specific traits, eliminating the guesswork that scientists previously encountered when faced with linkage among variants or genes closest to variants. For example, in the case of a blood trait called monocyte count, applying CRISPR caused one gene, CD52, to clearly stand out as significantly altered, despite not being the closest gene to the variant of interest.
In a separate analysis, the researchers used STING-seq to isolate noncoding variants that were causal for a gene called PTPRC, which is associated with 10 blood traits. By seeing which variants changed PTPRC expression, the researchers were able to understand which noncoding variants could modulate PTPRC expression and contribute to the development of these blood traits.
The future of STING-seq
STING-seq has proved to be a valuable tool for identifying target genes and causal variants, but it cannot determine whether a noncoding variant will increase or decrease the expression of a nearby gene. To overcome this limitation, the researchers developed a complementary approach called beeSTING-seq (base editing STING-seq). This technique involves using CRISPR to insert a genetic variant instead of inhibiting the region of the genome. By doing so, the researchers can determine the direction of the effect and whether a specific noncoding variant increases or decreases the expression of a nearby gene.
STING-seq and beeSTING-seq have the potential to revolutionize the identification of causal variants for a variety of diseases. These techniques can be used to develop gene-editing therapies for diseases like sickle cell anemia or to develop drugs that target specific genes or cellular pathways. By precisely identifying causal variants, researchers can gain a deeper understanding of the underlying biology of diseases, leading to new treatments and better patient outcomes.