PacBio HiFi Sequencing for Spinal Muscular Atrophy Analysis

Spinal muscular atrophy (SMA) has long been recognized as a serious neuromuscular disease, is currently ranked as the leading cause of early infant mortality, and is one of the most common recessive diseases worldwide. Two genes play a role in the onset and severity of SMA: SMN1 and SMN2. SMN1 is highly homologous to its paralog SMN2. These two genes are located in genomic regions with highly complex long repetitive sequences that are nearly identical except for a few bases, which makes sequence analysis and variant calling challenging. Both genes have different copy numbers in different populations and have been analyzed by a variety of methods (usually PCR-based dosage testing combined with sequencing), each of which has its limitations. Further, without pedigree information, it is currently not possible to identify silent carriers (2+0) with two copies of SMN1 on one chromosome and zero copies on the other.

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Challenges in Defining mRNA Transcript Boundaries Using Long-Read Sequencing

The quest to decipher the intricacies of gene expression has taken a remarkable leap forward with the emergence of long-read sequencing technologies. By providing unprecedented insights into the full length of mRNA transcripts, these technologies promise to revolutionize our understanding of genetic regulation, alternative splicing, and isoform diversity. However, the road to unraveling the true beginning and end of mRNA transcripts is fraught with challenges that stem from the very nature of long-read sequencing data. In this article, we explore the multifaceted hurdles researchers face when identifying mRNA transcript start and end sites from long-read sequencing data.

Single-Cell RNA Sequencing in Drug Discovery and Development

One of the significant advantages of scRNA-seq in drug discovery is its impact on target identification. By allowing researchers to dissect complex tissues and diseases at the cellular level, scRNA-seq enables the identification of distinct cell subtypes and their gene expression profiles. This information can lead to a better understanding of disease mechanisms and help identify novel therapeutic targets. By comparing healthy and diseased tissues, researchers can pinpoint differentially expressed genes and potential therapeutic targets specific to certain cell types or disease states.

Case Studies of Single-Cell Profiling

Single-cell gene expression profiling has rapidly emerged as a transformative technology, offering unparalleled insights into a wide range of diseases and biological mechanisms. By allowing scientists to examine gene expression at the resolution of individual cells, this approach provides a level of detail that traditional bulk methods cannot match. These analyses have opened new doors for understanding complex disease processes and discovering novel therapeutic strategies. Below, we explore several compelling case studies that demonstrate the significant impact of single-cell profiling in biomedical research.

Introduction to The Complete Sequence of a Human Genome

The human genome, the genetic code that makes us uniquely human, has been the subject of scientific study and fascination for decades. The human genome contains approximately 3.055 billion base pairs. These are the molecular building blocks of DNA, consisting of adenine (A) paired with thymine (T) and cytosine (C) paired with guanine (G). This vast number is a testament not only to the complexity of the human race, but also to the intricate interplay of genetic factors that influence our physiology, behavior, and predispositions. Billions of base pairs and complex sequences determine everything from hair color to susceptibility to certain diseases. Understanding the entire human genome is both important and challenging.

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PacBio HiFi Sequencing for Spinal Muscular Atrophy Analysis

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Challenges in Defining mRNA Transcript Boundaries Using Long-Read Sequencing

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Single-Cell RNA Sequencing in Drug Discovery and Development

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Case Studies of Single-Cell Profiling

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Introduction to The Complete Sequence of a Human Genome

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Pore Occupancy: Definition, Improving Pore Occupancy

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