MSDB: a comprehensive, annotated database of microsatellites

The Structure of Simple Satellite Variation in the Human Genome and Its Correlation With Centromere Ancestry

Although repetitive DNA forms much of the human genome, its study is challenging due to limitations in assembly and alignment of repetitive short-reads. We have deployed k-Seek, software that detects tandem repeats embedded in single reads, on 2,504 human genomes from the 1,000 Genomes Project to quantify the variation and abundance of simple satellites (repeat units <20 bp). We find that the ancestral monomer of Human Satellite 3 makes up the largest portion of simple satellite content in humans (mean of ∼8 Mb). We discovered ∼50,000 rare tandem repeats that are not detected in the T2T-CHM13v2.0 assembly, including undescribed variants of telomericand pericentromeric repeats. We find broad homogeneity of the most abundant repeats across populations, except for AG-rich repeats which are more abundant in African individuals. We also find cliques of highly similar AG- and AT-rich satellites that are interspersed and form higher-order structures that covary in copy number across individuals, likely through concerted amplification via unequal exchange. Finally, we use pericentromeric polymorphisms to estimate centromeric genetic relatedness between individuals and find a strong predictive relationship between centromeric lineages and pericentromeric simple satellite abundances. In particular, ancestral monomers of Human Satellite 2 and Human Satellite 3 abundances correlate with clusters of centromeric ancestry on chromosome 16 and chromosome 9, with some clusters structured by population. These results provide new descriptions of the population dynamics that underlie the evolution of simple satellites in humans.

TriticeaeSSRdb: a comprehensive database of simple sequence repeats in Triticeae

Microsatellites, known as simple sequence repeats (SSRs), are short tandem repeats of 1 to 6 nucleotide motifs found in all genomes, particularly eukaryotes. They are widely used as co-dominant markers in genetic analyses and molecular breeding. Triticeae, a tribe of grasses, includes major cereal crops such as bread wheat, barley, and rye, as well as abundant forage and lawn grasses, playing a crucial role in global food production and agriculture. To enhance genetic work and expedite the improvement of Triticeae crops, we have developed TriticeaeSSRdb, an integrated and user-friendly database. It contains 3,891,705 SSRs from 21 species and offers browsing options based on genomic regions, chromosomes, motif types, and repeat motif sequences. Advanced search functions allow personalized searches based on chromosome location and length of SSR. Users can also explore the genes associated with SSRs, design customized primer pairs for PCR validation, and utilize practical tools for whole-genome browsing, sequence alignment, and in silico SSR prediction from local sequences. We continually update TriticeaeSSRdb with additional species and practical utilities. We anticipate that this database will greatly facilitate trait genetic analyses and enhance molecular breeding strategies for Triticeae crops. Researchers can freely access the database at http://triticeaessrdb.com/.

An Innovative and Accurate Next-Generation Sequencing-Based Microsatellite Instability Detection Method for Colorectal and Endometrial Tumors

The detection of microsatellite instability (MSI) and mismatch repair (MMR) deficiency has become mandatory for most tumors in recent years, owing to the development of immune checkpoint inhibitors as a highly effective therapy for MMR deficiency/MSI tumors. The timely and efficient detection of MSI is valuable, and new methods are increasingly being developed. To date, MMR assessment has been performed using immunohistochemistry of the 4 MMR proteins and/or microsatellite stability/MSI using PCR, mostly using the pentaplex panel. The implementation of next-generation sequencing (NGS) for MSI analysis would improve the effectiveness at a lower cost and in less time. This study describes the development of 8 new microsatellites combined with a classification algorithm, termed "Octaplex CaBio-MSID" (for Cancérologie Biologique MSI Detection tool), to assess MSI using NGS. A series of 303 colorectal cancer and 88 endometrial cancer samples were assessed via MSI testing using NGS using the Octaplex CaBio-MSID algorithm. The sensitivity and specificity of Octaplex CaBio-MSID were 98.4% and 98.4% for colorectal cancers, and 89.3% and 100% for endometrial cancers, respectively. This new NGS-based MSI detection method outperforms previously published methods (ie, Idylla [Biocartis], OncoMate MSI Dx [Promega], and Foundation One CDx [Roche Foundation Medicine]). Although highly efficient, Octaplex CaBio-MSID requires validation in a larger independent series of different tumor types.

Systematic investigation of the homology sequences around the human fusion gene breakpoints in pan-cancer - bioinformatics study for a potential link to MMEJ

Microhomology-mediated end joining (MMEJ), an error-prone DNA damage repair mechanism, frequently leads to chromosomal rearrangements due to its ability to engage in promiscuous end joining of genomic instability and also leads to increasing mutational load at the sequences flanking the breakpoints (BPs). In this study, we systematically investigated the homology sequences around the genomic breakpoint area of human fusion genes, which were formed by the chromosomal rearrangements initiated by DNA double-strand breakage. Since the RNA-seq data is the typical data set to check the fusion genes, for the known exon junction fusion breakpoints identified from RNA-seq data, we have to infer the high chance of genomic breakpoint regions. For this, we utilized the high feature importance score area calculated from our recently developed fusion BP prediction model, FusionAI and identified 151 K microhomologies among ~24 K fusion BPs in 20 K fusion genes. From our multiple bioinformatics studies, we found a relationship between sequence homologies and the immune system. This in-silico study will provide novel knowledge on the sequence homologies around the coded structural variants.

Associating resistance to immune checkpoint inhibitors with immunological escape in colorectal cancer

Colorectal cancer is a common malignant tumor that ranks third in incidence and second in mortality worldwide, and surgery in conjunction with chemotherapy and radiotherapy remains the most common treatment option. As a result of radiotherapy’s severe side effects and dismal survival rates, it is anticipated that more alternatives may emerge. Immunotherapy, a breakthrough treatment, has made significant strides in colorectal cancer over the past few years, overcoming specialized therapy, which has more selectivity and a higher survival prognosis than chemoradiotherapy. Among these, immune checkpoint inhibitor therapy has emerged as the primary immunotherapy for colorectal cancer nowadays. Nonetheless, as the use of immune checkpoint inhibitor has expanded, resistance has arisen inevitably. Immune escape is the primary cause of non-response and resistance to immune checkpoint inhibitors. That is the development of primary and secondary drug resistance. In this article, we cover the immune therapy-related colorectal cancer staging, the specific immune checkpoint inhibitors treatment mechanism, and the tumor microenvironment and immune escape routes of immunosuppressive cells that may be associated with immune checkpoint inhibitors resistance reversal. The objective is to provide better therapeutic concepts for clinical results and to increase the number of individuals who can benefit from colorectal cancer immunotherapy.

Mutated KLF4(K409Q) in meningioma binds STRs and activates FGF3 gene expression

Krüppel-like factor 4 (KLF4) is a transcription factor that has been proven necessary for both induction and maintenance of pluripotency and self-renewal. Whole-genome sequencing defined a unique mutation in KLF4 (KLF4K409Q) in human meningiomas. However, the molecular mechanism of this tumor-specific KLF4 mutation is unknown. Using genome-wide high-throughput and focused quantitative transcriptional approaches in human cell lines, primary meningeal cells, and meningioma tumor tissue, we found that a change in the evolutionarily conserved DNA-binding domain of KLF4 alters its DNA recognition preference, resulting in a shift in downstream transcriptional activity. In the KLF4K409Q-specific targets, the normally silent fibroblast growth factor 3 (FGF3) is activated. We demonstrated a neomorphic function of KLF4K409Q in stimulating FGF3 transcription through binding to its promoter and in using short tandem repeats (STRs) located within the locus as enhancers.

Genomic characterization of the world's longest selection experiment in mouse reveals the complexity of polygenic traits

BACKGROUND

Long-term selection experiments are a powerful tool to understand the genetic background of complex traits. The longest of such experiments has been conducted in the Research Institute for Farm Animal Biology (FBN), generating extreme mouse lines with increased fertility, body mass, protein mass and endurance. For >140 generations, these lines have been maintained alongside an unselected control line, representing a valuable resource for understanding the genetic basis of polygenic traits. However, their history and genomes have not been reported in a comprehensive manner yet. Therefore, the aim of this study is to provide a summary of the breeding history and phenotypic traits of these lines along with their genomic characteristics. We further attempt to decipher the effects of the observed line-specific patterns of genetic variation on each of the selected traits.

RESULTS

Over the course of >140 generations, selection on the control line has given rise to two extremely fertile lines (>20 pups per litter each), two giant growth lines (one lean, one obese) and one long-distance running line. Whole genome sequencing analysis on 25 animals per line revealed line-specific patterns of genetic variation among lines, as well as high levels of homozygosity within lines. This high degree of distinctiveness results from the combined effects of long-term continuous selection, genetic drift, population bottleneck and isolation. Detection of line-specific patterns of genetic differentiation and structural variation revealed multiple candidate genes behind the improvement of the selected traits.

CONCLUSIONS

The genomes of the Dummerstorf trait-selected mouse lines display distinct patterns of genomic variation harbouring multiple trait-relevant genes. Low levels of within-line genetic diversity indicate that many of the beneficial alleles have arrived to fixation alongside with neutral alleles. This study represents the first step in deciphering the influence of selection and neutral evolutionary forces on the genomes of these extreme mouse lines and depicts the genetic complexity underlying polygenic traits.

Progress in the Application of Immune Checkpoint Inhibitor-Based Immunotherapy for Targeting Different Types of Colorectal Cancer

Colorectal cancer (CRC), a common malignant disease, has the second highest mortality rate among all cancer types. Due to the diversity and heterogeneity of CRC, few effective treatment strategies have been developed in recent years, except for surgical resection. As immunotherapy has become a revolutionary treatment after surgery, along with chemoradiotherapy and targeted therapy, numerous basic research studies and clinical trials have been conducted on CRC. Therefore, immune checkpoint inhibitor (ICI) therapy has become the main anti-CRC immunotherapy method used at present. With the rapid development of biotechnology and cell research, an increasing number of monotherapy or combination therapy strategies using ICIs for CRC have been designed in recent years. Methods to classify and review ICI strategies for different types of CRC to better guide treatment are continuously investigated. However, the identification of why the ICIs would be more effective in targeting particular subtypes of CRC such as high microsatellite instability (MSI-H) is more important because of the different immune backgrounds in patients. This review intends to classify different subtypes of CRC and summarizes the basic and clinical studies on ICIs for each subtype of CRC currently available. In addition, we also attempt to briefly discuss the progress in immunotherapy methods other than ICI therapy, such as chemoimmunotherapy strategy, chimeric antigen receptor-modified T (CAR-T) cells, or immunotherapy based on oncolytic viruses. Finally, we provide a perspective on the development of immunotherapy in the treatment of CRC and attempt to propose a new systematic classification of CRC based on immunological strategies, which may improve guidance for the selection of immunotherapy strategies for different subtypes of CRC in the future.

FusionGDB 2.0: fusion gene annotation updates aided by deep learning

A knowledgebase of the systematic functional annotation of fusion genes is critical for understanding genomic breakage context and developing therapeutic strategies. FusionGDB is a unique functional annotation database of human fusion genes and has been widely used for studies with diverse aims. In this study, we report fusion gene annotation updates aided by deep learning (FusionGDB 2.0) available at https://compbio.uth.edu/FusionGDB2/. FusionGDB 2.0 has substantial updates of contents such as up-to-date human fusion genes, fusion gene breakage tendency score with FusionAI deep learning model based on 20 kb DNA sequence around BP, investigation of overlapping between fusion breakpoints with 44 human genomic features across five cellular role's categories, transcribed chimeric sequence and following open reading frame analysis with coding potential based on deep learning approach with Ribo-seq read features, and rigorous investigation of the protein feature retention of individual fusion partner genes in the protein level. Among ∼102k fusion genes, about 15k kept their ORF as In-frames, which is two times compared to the previous version, FusionGDB. FusionGDB 2.0 will be used as the reference knowledgebase of fusion gene annotations. FusionGDB 2.0 provides eight categories of annotations and it will be helpful for diverse human genomic studies.

FusionAI: Predicting fusion breakpoint from DNA sequence with deep learning

Identifying the molecular mechanisms related to genomic breakage is an important goal of cancer mechanism studies. Among diverse locations of structural variants, fusion genes, which have the breakpoints in the gene bodies and are typically identified from the split reads of RNA-seq data, can provide a highlighted structural variant resource for studying the genomic breakages with expression and potential pathogenic impacts. In this study, we developed FusionAI, which utilizes deep learning to predict gene fusion breakpoints based on DNA sequence and let us identify fusion breakage code and genomic context. FusionAI leverages the known fusion breakpoints to provide a prediction model of the fusion genes from the primary genomic sequences via deep learning, thereby helping researchers a more accurate selection of fusion genes and better understand genomic breakage.

DNA polymerase stalling at structured DNA constrains the expansion of short tandem repeats

BACKGROUND

Short tandem repeats (STRs) contribute significantly to de novo mutagenesis, driving phenotypic diversity and genetic disease. Although highly diverse, their repetitive sequences induce DNA polymerase slippage and stalling, leading to length and sequence variation. However, current studies of DNA synthesis through STRs are restricted to a handful of selected sequences, limiting our broader understanding of their evolutionary behaviour and hampering the characterisation of the determinants of their abundance and stability in eukaryotic genomes.

RESULTS

We perform a comprehensive analysis of DNA synthesis at all STR permutations and interrogate the impact of STR sequence and secondary structure on their genomic representation and mutability. To do this, we developed a high-throughput primer extension assay that allows monitoring of the kinetics and fidelity of DNA synthesis through 20,000 sequences comprising all STR permutations in different lengths. By combining these measurements with population-scale genomic data, we show that the response of a model replicative DNA polymerase to variously structured DNA is sufficient to predict the complex genomic behaviour of STRs, including abundance and mutational constraints. We demonstrate that DNA polymerase stalling at DNA structures induces error-prone DNA synthesis, which constrains STR expansion.

CONCLUSIONS

Our data support a model in which STR length in eukaryotic genomes results from a balance between expansion due to polymerase slippage at repeated DNA sequences and point mutations caused by error-prone DNA synthesis at DNA structures.