Background: Single-cell resequencing (SCRS) provides many biomedical advances in variations detection at the single-cell level, but it currently relies on whole genome amplification (WGA). Three methods are commonly used for WGA: multiple displacement amplification (MDA), degenerate-oligonucleotide-primed PCR (DOP-PCR) and multiple annealing and looping-based amplification cycles (MALBAC). However, a comprehensive comparison of variations detection performance between these WGA methods has not yet been performed. Results: We systematically compared the advantages and disadvantages of different WGA methods, focusing particularly on variations detection. Low-coverage whole-genome sequencing revealed that DOP-PCR had the highest duplication ratio, but an even read distribution and the best reproducibility and accuracy for detection of copy-number variations (CNVs). However, MDA had significantly higher genome recovery sensitivity (~84 %) than DOP-PCR (~6 %) and MALBAC (~52 %) at high sequencing depth. MALBAC and MDA had comparable single-nucleotide variations detection efficiency, false-positive ratio, and allele drop-out ratio. We further demonstrated that SCRS data amplified by either MDA or MALBAC from a gastric cancer cell line could accurately detect gastric cancer CNVs with comparable sensitivity and specificity, including amplifications of 12p11.22 (KRAS) and 9p24.1 (JAK2, CD274, and PDCD1LG2). Conclusions: Our findings provide a comprehensive comparison of variations detection performance using SCRS amplified by different WGA methods. It will guide researchers to determine which WGA method is best suited to individual experimental needs at single-cell level.

Background. The evolutionary relationships of modern birds are among the most challenging to understand in systematic biology and have been debated for

Absract: Neoantigens are ideal targets for dendritic cell (DC) vaccines. So far, only a few neoantigen-based DC vaccines have been investigated in clinical trials. Here, we reported a case of a patient with metastatic gastric cancer who received personalized neoantigen-loaded monocyte-derived dendritic cell (Neo-MoDC) vaccines followed by combination therapy of the Neo-MoDC and immune checkpoint inhibitor (ICI). The patient developed T cell responses against neoantigens after receiving the Neo-MoDC vaccine alone. The following combination therapy triggered a stronger immune response and mediated complete regression of all tumors for over 25 months till October, 2021. Peripheral blood mononuclear cells recognized seven of the eight vaccine neoantigens. And the frequency of neoantigen-specific T cell clones increased obviously after vaccination. Overall, this report describing a complete tumor regression in a gastric cancer patient mediated by Neo-MoDC vaccine in combination with ICI, and suggesting a promising treatment for patients with metastatic gastric cancer.

Predicting peptide binding affinity with human leukocyte antigen (HLA) is a crucial step in developing powerful antitumor vaccine for cancer immunotherapy. Currently available methods work quite well in predicting peptide binding affinity with HLA alleles such as HLA-A*0201, HLA-A*0101, and HLA-B*0702 in terms of sensitivity and specificity. However, quite a few types of HLA alleles that are present in the majority of human populations including HLA-A*0202, HLA-A*0203, HLA-A*6802, HLA-B*5101, HLA-B*5301, HLA-B*5401, and HLA-B*5701 still cannot be predicted with satisfactory accuracy using currently available methods. Furthermore, currently the most popularly used methods for predicting peptide binding affinity are inefficient in identifying neoantigens from a large quantity of whole genome and transcriptome sequencing data. Here we present a Position Specific Scoring Matrix (PSSM)-based software called PSSMHCpan to accurately and efficiently predict peptide binding affinity with a broad coverage of HLA class I alleles. We evaluated the performance of PSSMHCpan by analyzing 10-fold cross-validation on a training database containing 87 HLA alleles and obtained an average area under receiver operating characteristic curve (AUC) of 0.94 and accuracy (ACC) of 0.85. In an independent dataset (Peptide Database of Cancer Immunity) evaluation, PSSMHCpan is substantially better than the popularly used NetMHC-4.0, NetMHCpan-3.0, PickPocket, Nebula, and SMM with a sensitivity of 0.90, as compared to 0.74, 0.81, 0.77, 0.24, and 0.79. In addition, PSSMHCpan is more than 197 times faster than NetMHC-4.0, NetMHCpan-3.0, PickPocket, sNebula, and SMM when predicting neoantigens from 661 263 peptides from a breast tumor sample. Finally, we built a neoantigen prediction pipeline and identified 117 017 neoantigens from 467 cancer samples of various cancers from TCGA. PSSMHCpan is superior to the currently available methods in predicting peptide binding affinity with a broad coverage of HLA class I alleles.

Background. Parrots belong to a group of behaviorally advanced vertebrates and have an advanced ability of vocal learning relative to other vocal-learni

A-to-I RNA-editing mediated by ADAR (adenosine deaminase acting on RNA) enzymes that converts adenosine to inosine in RNA sequence can generate mutations and alter gene regulation in metazoans. Previous studies have shown that A-to-I RNA-editing plays vital roles in mouse embryogenesis. However, the RNA-editing activities in early human embryonic development have not been investigated. Here, we characterized genome-wide A-to-I RNA-editing activities during human early embryogenesis by profiling 68 single cells from 29 human embryos spanning from oocyte to morula stages. We demonstrate dynamic changes in genome-wide RNA-editing during early human embryogenesis in a stage-specific fashion. In parallel with ADAR expression level changes, the genome-wide A-to-I RNA-editing levels in cells remained relatively stable until 4-cell stage, but dramatically decreased at 8-cell stage, continually decreased at morula stage. We detected 37 non-synonymously RNA-edited genes, of which 5 were frequently found in cells of multiple embryonic stages. Moreover, we found that A-to-I editings in miRNA-targeted regions of a substantial number of genes preferably occurred in one or two sequential stages. Our single-cell analysis reveals dynamic changes in genome-wide RNA-editing during early human embryogenesis in a stage-specific fashion, and provides important insights into early human embryogenesis.