The field of immune repertoire profiling has witnessed remarkable advancements in recent years, revolutionizing our understanding of the immune system and its role in various diseases. One of the key techniques to understand this complex mechanism is TCR sequencing. TCR, or T-cell receptor, plays a crucial role in the adaptive immune response by recognizing and binding to specific antigens.

Genetic variation can range from changes at the level of single bases to whole-chromosomal aneuploidies. Structural variations (SVs) refer to a large alterations in chromosomal structure, typically encompassing larger than 1 Kbp of DNA. SVs include both balanced changes, such as inversions and some forms of translocations, as well as those that alter DNA copy number through duplications and deletions of chromosomal segments.

Bioinformatics plays a vital role in analyzing complex high-throughput sequencing data, particularly in the realm of single cell research. The ability to analyze and interpret massive amounts of single cell data has revolutionized our understanding of cellular heterogeneity and its implications in various biological processes. The blog explores the capabilities of bioinformatics team at MedGenome in analyzing single cell sequencing data. Here, we explore different types of bioinformatics reports, the importance of data visualization and generation of interactive reports such as differential gene expression analysis, heatmap visualization, interactive tSNE plots with cell type and cluster information.

The advent of single cell sequencing technologies has enabled us to understand and study the complexities of biological systems at a finer resolution. Traditional bulk sequencing methods provide an average representation of gene expression across a population of cells, masking the inherent heterogeneity that exists within a tissue or organism. However, single cell sequencing allows us to capture the maximal transcript diversity in a given cell and allows for a multi-model analysis strategy to generate meaningful insights.

Cite-Seq, short for Cellular Indexing of Transcriptomes and Epitopes by sequencing, is a powerful technology that has revolutionized single-cell sequencing. With its ability to analyze transcriptomes and protein expression at a single-cell level, Cite-Seq has the potential to greatly advance our understanding of cellular heterogeneity and function in biological systems. In this article, we will discuss the workings of Cite-Seq, its current and potential applications in various fields of research, and its limitations.

Single cell sequencing is a cutting-edge technique used in molecular biology that enables the sequencing of the transcriptome of individual cells. In traditional bulk sequencing techniques, RNA is extracted from a large group of cells, and then sequenced as a whole. However, single cell sequencing allows researchers to analyze the genetic material of individual cells, providing a much more detailed and precise understanding of the diversity and heterogeneity of cell populations.

Spatial transcriptomics is a technology that allows the analysis of gene expression patterns within a tissue sample in their spatial context. It enables researchers to obtain a comprehensive and high-resolution view of the transcriptome, the set of all expressed genes, across different regions of the tissue. In traditional transcriptomics, gene expression is measured from homogenized cell populations, which can mask important differences in gene expression between different cell types and regions. Spatial transcriptomics, on the other hand, allows researchers to analyze gene expression patterns in intact tissue sections while retaining their spatial information.

Next-generation sequencing (NGS) data is being increasingly used in clinical diagnosis to identify genetic variation that can be a cause for the disease. A major challenge in using NGS data in a clinical setting is to make the right interpretation because of its huge size and complexity. Also, there are possibilities of technical errors during the sample processing and/or sequencing stage that may be inherent to the kind of sequencing technology used. Therefore, the use of reference standards is of paramount importance to mitigate and minimize these errors.

NGS technologies is at the forefront of Biological Research. They produce enormous data running into gigabases in a single round of sequencing. However, several sequencing artifacts such as read errors (base calling errors and small insertions/deletions), poor quality reads and primer/adaptor contamination are quite common with the NGS data obtained after sequencing.

Our journey in 2022 was focused on providing the utmost customer experience for the services and solutions that we delivered to you. Along with expanding our portfolio of services and solutions – the tissue dissociation and nuclei isolation services to support our single cell customers, streamlined antibody discovery using high-throughput single B cell receptor sequencing, TSO500 targeted panels for oncology research, single cell and bulk epigenetics assays.

The discovery of genetic and epigenetic mechanisms underlying the onset and progression of numerous diseases, including cancer, has helped redefine clinical research, diagnostic and treatment paradigms. Oncology research and diagnostics have undergone radical changes because of the development of next-generation sequencing (NGS). NGS has improved rationally designed personalized cancer medicine by identifying novel cancer mutations, detecting circulating tumor DNA (ctDNA), and discovering causative mutations for hereditary cancer syndrome. With NGS, it is now possible to sequence the whole genome, whole exome, whole transcriptome, or just targeted genes to provide detailed genomic landscape descriptions for many cancers.

Alzheimer’s disease (AD) has long been one of the great challenges in medicine and imposes a constant burden on our aging population. Recent statistics show that approximately 50 million people worldwide suffer from AD or some other form of dementia. The World Health Organization has estimated that the total number of people with dementia worldwide will reach 82 million by 2030 and 152 million by 2050. Of the top 10 leading causes of death based on United States cancer statistics, cardiovascular disease ranks first, tumors rank second and AD ranks sixth.

Modern medicine now derives its insights through the deeper understanding of the cellular and molecular mechanisms, which involves modification of the cellular behavior through targeted molecular approaches. Experimental biologists and clinicians now employ various molecular techniques to assess the intrinsic behavior of cells in a variety of ways, such as through analyses of genomic DNA sequences, chromatin structure, messenger RNA (mRNA) sequences, non-protein-coding RNA, protein expression, protein modifications and metabolites.

Emerging single-cell technologies have provided us with a powerful tool to dissect the clonal complexity of tumor cells, deconvolute the role of immune cell types in disease mechanisms, and monitor risk and treatment strategies to guide early patient diagnosis, since being highlighted as the ‘method of the year’ in 2013. As our capabilities in single cell sequencing continue to increase, latest advances in multi-omics of single cells are providing newer ways of integrating single cell transcriptomics with the multiple molecular measurements in a single experiment.

Recent advances in next-generation sequencing technologies have heralded a paradigm shift in the field of precision oncology and personalized/genomic medicine, with a large number of somatic- and germline mutation-profiling programs worldwide. These programs have paved the way for personalized medicine in contrast to a unified approach that clearly fails in select individuals, conferring benefits to only a subset of patients. While these genomic analyses become increasingly accessible and almost commonplace to all research scientists, clinicians and molecular geneticists, they are faced with the challenging task of interpreting and translating the results from these analyses.

According to the American Cancer Society, an estimated 1.9 million new cancers will be diagnosed in 2022 [1]. Some of the major cancer types affecting the population are prostate, lung & bronchus, colon & rectum, urinary bladder, melanoma of the skin, kidney & renal pelvis, non-Hodgkin lymphoma, oral cavity & pharynx, leukemia, pancreas, breast, colon & rectum, uterine corpus, thyroid.

Next-generation sequencing techniques has seen an unimaginable growth in the past two decades. The scope has really broadened, and it is now possible to look at a genome both at macro and micro levels. Single-Cell RNA sequencing (scRNA-seq) is one such technique which deals with understanding the transcriptome at a cellular level. Single cell RNA sequencing can provide unparalleled insights into the various cellular events. scRNA-seq has an advantage over the bulk RNA-seq studies since it provides higher resolution in terms of cell subsets diversity and individual cell heterogeneity in the organisms.

The human immune response can be divided into two components: Innate and Adaptive. Innate immune response involves classic primitive reaction through cellular and humoral mechanisms. It’s a first line of defence and can comprise a host of cells such as neutrophils, macrophages, and mast cells which kills the invading pathogens while the humoral response can be through enzymes such as Lysozyme that can kill harmful microorganisms.

Single-cell genomic analysis has emerged as a powerful method for studying complex disease. By providing comprehensive analyses of individual cells, single-cell sequencing allows researchers to examine cellular heterogeneity, which especially useful in oncology, neurology, immunology, and developmental research.

February 28th is Rare Disease Day. It is a day where the realities of Rare Diseases need to be highlighted for all health industry stakeholders; to celebrate the progress that has been made as well as to inspire us for the challenges that lay ahead.
Rare diseases are defined as those conditions thar affect fewer than 1/ 1200 people. More than 300 million people globally are affected by a rare disease 1,2. Patients and families with rare diseases are one of the most underserved communities in medicine today.

World Cancer Day is a day to reflect and celebrate research victories, the battles that anyone with cancer fights, the search for new ways to detect cancer early and treat it as effectively as possible. Yet, cancer statistics remain sobering. Globally, there were an estimated 19.3 million new cancer cases and 10 million cancer deaths in 2020 . The number of people living with cancer is expected to grow by around 1 million every decade between 2010 and 2030.

Spatial transcriptomics is a revolutionary molecular profiling method that allows scientists to measure in a tissue sample and map the activity to specific cell types and their location. This novel technology is paving the path to new discoveries that are proving instrumental in helping researchers gain a better understanding of biological processes and diseases leading it to be called the Method of the Year in 2020.

It is known that all the hereditary information is contained within an organism’s genome. Owing to continuous global efforts many new bioinformatics databases are emerging and has seen an up trend in the recent past, a reflection on how NGS data is impacting our understanding of life and our need to constantly develop new methods to investigate and decode the information in and around DNA (or RNA for some viruses) and its nucleotide sequences.

With the advent of novel Next generation sequencing (NGS) technology platforms – DNA Sequencing has seen a revolutionary leap both in terms of cost and application in cutting-edge research.. Today, we can sequence an entire Human genome in a day compared to the conventional Sanger sequencing using capillary electrophoresis. It is now possible to identify and track genetic variation in a more efficient and precise manner. Also, owing to this seamless sequencing capability now thousands of variants can be analysed within a large population in a short span of time.

Since December 2019, the outbreak of Corona Virus Disease (COVID-19) has posed a serious threat to global health. The number of cases increased quickly and has resulted in over four million deaths worldwide, as of July 2021. In response to this, numerous research projects have been conducted to study the disease etiology, the patterns of epidemic, and potential treatments for the disease. The adaptive immune response plays a central role in clearing viral infections and in turn directly influences patients clinical outcomes.

Since December 2019, the outbreak of Corona Virus Disease (COVID-19) has posed a serious threat to global health. The number of cases increased quickly and has resulted in over four million deaths worldwide, as of July 2021. In response to this, numerous research projects have been conducted to study the disease etiology, the patterns of epidemic, and potential treatments for the disease. The adaptive immune response plays a central role in clearing viral infections and in turn directly influences patients clinical outcomes.

In my previous blog, I highlighted the uniqueness of single cell RNA sequencing technologies and how these can be used to understand 5’ and 3’ gene expression, T and B cell immune repertoire profiles, and more specific antibody-based approaches such as CITE-Seq as well as epigenetics approaches with ATAC-Seq. In this blog, the power of multi-omic approaches to simultaneously determine open chromatin regions with gene expression in a single cell is reviewed.

The scientific curiosity to understand the cause of a disease has led to many technological innovations. As the cost of genomic sequencing started to fall a decade ago, it opened up numerous new technologies that could provide unique insights in understanding disease biology even at a molecular level. These include whole genome data (genomics), changes in the structure of chromatin, understanding RNA sequences and their expression (transcriptomics) to proteomics-based approaches to understand protein structure, folding and the measurement of various metabolites (metabolomics).

A fundamental challenge in biomedical research is to identify accurate, early indicators of a disease. Recent advances in sequencing technologies have led to unparalleled efforts to characterize the molecular changes that underlie the development and progression of complex human diseases, including cancer. Scientists have widely used RNA-seq analysis to study the transcriptome in populations of cells. More recently, single-cell RNA seq studies have been used to gain insight on cellular traits and changes in cellular state.

Single-cell genomics techniques are revolutionizing our ability to characterize complex tissues. Although bulk RNA sequencing experiments can be insightful, they often mask important biological activity of rare cell types and fail to show the variability in gene expression between individual cells. The rapid development of low-input RNA seq methods has led to an explosion of single-cell RNA-seq platforms, each with their own advantages and limitations. Droplet-based methods (10X Chromium, DropSeq) can be used to analyze thousands of cells in a single prep.