Probes for KIT

Genetic variant calling from DNA sequencing has enabled understanding of germline variation in hundreds of thousands of humans. Sequencing technologies and variant-calling methods have advanced rapidly, routinely providing reliable variant calls in most of the human genome. We describe how advances in long reads, deep learning, de novo assembly and pangenomes have expanded access to variant calls in increasingly challenging, repetitive genomic regions, including medically relevant regions, and how new benchmark sets and benchmarking methods illuminate their strengths and limitations. Finally, we explore the possible future of more complete characterization of human genome variation in light of the recent completion of a telomere-to-telomere human genome reference assembly and human pangenomes, and we consider the innovations needed to benchmark their newly accessible repetitive regions and complex variants.

Tumor cells present complex behaviors in their interactions with other cells. This intricate behavior is driving the need to develop new tools to understand these ecosystems. The surge of spatial technologies allows evaluation of the complexity of relationships between cells present in a tumor, giving insights about tumor heterogeneity and the tumor microenvironment while providing clinically relevant metrics for tumor classification. In this review, we describe key results obtained using spatial techniques, present recent advances in methods to uncover spatially relevant biological significance, and summarize their main characteristics. We expect spatial technologies to significantly broaden our understanding of tumor biology and to generate clinically relevant tools that will ultimately impact personalized medicine.

Purpose To select individuals and families with low genetic burden for age-related macular degeneration (AMD), to inform the clinical diagnosis of macular disorders, and to find novel genetic variants associated with macular disease in affected families. Design Genetic association study based on targeted and whole exome sequencing. Participants 758 subjects (481 individuals with maculopathy and 277 controls), including 316 individuals in 72 families. Methods We focused on 150 genes involved in the complement, coagulation, and inflammatory pathways. Single-variant tests were performed on 3062 variants shared among 5 or more subjects using logistic regression. Gene-based tests were used to evaluate aggregate effects from rare and low frequency variants (at minor allele frequency [MAF]

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

Public and private genomic sequencing initiatives generate ever-increasing amounts of genomic data creating a need for improved solutions for genomics data processing (Stephens et al.PLoS Biol 13:e1002195, 2015). The Sentieon Genomics software enables rapid and accurate analysis of next-generation sequence data. In this work, we present a typical use of the Sentieon Genomics software for germline variant calling. The Sentieon germline variant calling pipeline produces more accurate results than other tools on third-party benchmarks (Katherine et al. Front Genet 10:736, 2019; Shen et al. bioRxiv, 885517, 2019) in one tenth the time of comparable pipelines. Parts of this guide come from the official Sentieon Genomics software manual in https://support.sentieon.com/manual (Sentieon. Sentieon Genomics software manual, n.d.) and from the official Sentieon Genomics software application notes in https://support.sentieon.com/appnotes  (Sentieon. Sentieon Genomics software application notes, n.d.) and are republished with permission. For additional details and advanced usage instructions of the Sentieon tools, refer to the software manual.

The mammalian Y chromosome offers a unique perspective on the male reproduction and paternal evolutionary histories. However, further understanding of the Y chromosome biology for most mammals is hindered by the lack of a Y chromosome assembly. This study presents an integrated in silico strategy for identifying and assembling the goat Y-linked scaffolds using existing data. A total of 11.5 Mb Y-linked sequences were clustered into 33 scaffolds, and 187 protein-coding genes were annotated. We also identified high abundance of repetitive elements. A 5.84 Mb subset was further ordered into an assembly with the evidence from the goat radiation hybrid map (RH map). The existing whole-genome resequencing data of 96 goats (worldwide distribution) were utilized to exploit the paternal relationships among bezoars and domestic goats. Goat paternal lineages were clearly divided into two clades (Y1 and Y2), predating the goat domestication. Demographic history analyses indicated that maternal lineages experienced a bottleneck effect around 2,000 YBP (years before present), after which goats belonging to the A haplogroup spread worldwide from the Near East. As opposed to this, paternal lineages experienced a population decline around the 10,000 YBP. The evidence from the Y chromosome suggests that male goats were not affected by the A haplogroup worldwide transmission, which implies sexually unbalanced contribution to the goat trade and population expansion in post-Neolithic period.

Infertility is a common and rapidly growing health issue around the world. The genetic analysis based on the infertile population is crucial for intervention and treatment.To find candidate gene locus led to azoospermia in Chinese multi-ethnic groups and provide theoretical guidance for the diagnosis of genetic diseases to progressively aggravated infertility patients and sterile offspring with ART.The study based on whole-exome sequencing (WES) was presented for genetic characteristic analysis of multi-ethnics and identification of variants related to infertility in Xinjiang area of China.The frequency of pathogenic variants showed significant ethnic differences among four main ethnics in Xinjiang. The population structure analysis confirmed that the Hui was close to the Han population, the Kazak was close to the Uygur population, and there are three ancestry components in the four ethnics. In addition, ten candidate variants potentially regulated azoospermia were detected, and KNTC1 (rs7968222: G > T) was chosen to validate the association. Through the analysis in the valid group, the frequency of rs7968222 (G > T) has a significant difference in the azoospermia population (11.76%, 8/68) and normospermia population (4.63%, 35/756) (P < 0.001). Interestingly, the proportion of people with abnormal follicle-stimulating hormone (FSH) level in the group carrying rs7968222 (G > T) was significantly higher than non-carriers (P < 0.05). Therefore, rs7968222 may regulate spermatogenesis through affecting hormone level.Our study establishes the genetics analysis of Northwest China and finds a candidate gene locus KNTC1 (rs7968222: G > T), which is one of the genetic susceptibility factors for male azoospermia.

HIV-1 infection within the central nervous system (CNS) includes evolution of the virus, damaging inflammatory cascades, and the involvement of multiple cell types; however, our understanding of how Env tropism and inflammation can influence CNS infectivity is incomplete. In this study, we utilize macrophage-tropic and T cell-tropic HIV-1 Env proteins to establish accurate infection profiles for multiple CNS cells under basal and interferon alpha (IFN-α) or lipopolysaccharide (LPS)-induced inflammatory states. We found that macrophage-tropic viruses confer entry advantages in primary myeloid cells, including monocyte-derived macrophage, microglia, and induced pluripotent stem cell (iPSC)-derived microglia. However, neither macrophage-tropic or T cell-tropic HIV-1 Env proteins could mediate infection of astrocytes or neurons, and infection was not potentiated by induction of an inflammatory state in these cells. Additionally, we found that IFN-α and LPS restricted replication in myeloid cells, and IFN-α treatment prior to infection with vesicular stomatitis virus G protein (VSV G) Envs resulted in a conserved antiviral response across all CNS cell types. Further, using RNA sequencing (RNA-seq), we found that only myeloid cells express HIV-1 entry receptor/coreceptor transcripts at a significant level and that these transcripts in select cell types responded only modestly to inflammatory signals. We profiled the transcriptional response of multiple CNS cells to inflammation and found 57 IFN-induced genes that were differentially expressed across all cell types. Taken together, these data focus attention on the cells in the CNS that are truly permissive to HIV-1, further highlight the role of HIV-1 Env evolution in mediating infection in the CNS, and point to limitations in using model cell types versus primary cells to explore features of virus-host interaction. IMPORTANCE The major feature of HIV-1 pathogenesis is the induction of an immunodeficient state in the face of an enhanced state of inflammation. However, for many of those infected, there can be an impact on the central nervous system (CNS) resulting in a wide range of neurocognitive defects. Here, we use a highly sensitive and quantitative assay for viral infectivity to explore primary and model cell types of the brain for their susceptibility to infection using viral entry proteins derived from the CNS. In addition, we examine the ability of an inflammatory state to alter infectivity of these cells. We find that myeloid cells are the only cell types in the CNS that can be infected and that induction of an inflammatory state negatively impacts viral infection across all cell types.