Pitfall of genome-wide association studies: Sources of inconsistency in genotypes and their effects

Personalized medicine will improve heath outcomes and patient satisfaction. However, implementing personalized medicine based on individuals’ biological information is far from simple, requiring genetic biomarkers that are mainly developed and used by the pharmaceutical companies for selecting those patients who benefit more, or have less risk of adverse drug reactions, from a particular drug. Genome-wide Association Studies (GWAS) aim to identify genetic variants across the human genome that might be utilized as genetic biomarkers for diagnosis and prognosis. During the last several years, high-density genotyping SNP arrays have facilitated GWAS that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the studied phenotypic trait. The replication studies demonstrated that only a small portion of associated loci in the initial GWAS can be replicated, even within the same populations. Given the complexity of GWAS, multiple sources of Type I (false positive) and Type II (false negative) errors exist. The inconsistency in genotypes that caused either by the genotypeing experiment or by genotype calling process is a major source of the false GWAS findings. Accurate and reproducible genotypes are paramount as inconsistency in genotypes can lead to an inflation of false associations. This article will review the sources of inconsistency in genotypes and discuss its effect in GWAS findings.

Patient Assessment and Therapy Planning Based on Homologous Recombination Repair Deficiency

Defects in genes involved in the DNA damage response cause homologous recombination repair deficiency(HRD).HRD is found in a subgroup of cancer patients for several tumor types,and it has a clinical relevance to cancer prevention and therapies.Accumulating evidence has identified HRD as a biomarker for assessing the therapeutic response of tumor cells to poly(ADP-ribose)polymerase inhibitors and platinum-based chemotherapies.Nevertheless,the biology of HRD is complex,and its applications and the benefits of different HRD biomarker assays are controversial.This is primarily due to inconsistencies in HRD assessments and definitions(gene-level tests,genomic scars,mutational signatures,or a combination of these methods)and difficulties in assessing the contribution of each genomic event.Therefore,we aim to review the biological rationale and clinical evidence of HRD as a biomarker.This review provides a blueprint for the standardization and harmonization of HRD assessments.

NMDAR1蛋白膜外抗原结构域的重组表达、纯化和免疫反应原性鉴定

构建编码NMDAR1蛋白膜外片段的原核表达重组质粒,在大肠杆菌中诱导表达、纯化并鉴定其免疫反应原性。根据人NMDAR1基因序列,利用Phyre 2软件预测蛋白的三级结构并分析其结构域。设计引物用RT-PCR方法扩增编码NMDAR1膜外蛋白不同结构域的核酸片段,并插入原核表达载体pCold-SUMO构建重组质粒。转化DH5α感受态细胞,菌落PCR鉴定,阳性单克隆进行测序验证。鉴定正确的重组体转化大肠杆菌BL21(DE3),IPTG诱导目的蛋白的表达和纯化,Ni-NTA柱亲和层析和凝胶过滤层析纯化蛋白,酶切切除融合蛋白6His-SUMO标签,用AKTA Purifier进行凝胶过滤层析,收集纯化蛋白。利用SDS-PAGE鉴定蛋白纯度,并用Western blotting进行免疫反应性鉴定。克隆获得NMDAR1膜外部分的三段DNA序列,分别是NR1-M1(编码19–393 aa)、NR1-S1(编码394–544 aa)和NR1-S2(编码663–800 aa)。其中NR1-S1和NR1-S2片段之间以G(甘氨酸)和T(苏氨酸)作为接头连接成为复合片段。经菌落PCR筛选和测序鉴定,成功构建了重组质粒p Cold-SUMO-M1和p Cold-SUMO-S1-GT-S2。SDS-PAGE鉴定结果表明重组质粒在大肠杆菌中经诱导可表达可溶性NR1-M1及NR1-S1-GT-S2蛋白。对表达产物进行亲和层析和凝胶过滤层析获得了高纯度的目标蛋白。Western blotting证实纯化的目的蛋白能与相应抗体发生特异性结合反应。本研究成功构建了NMDAR1蛋白膜外抗原结构域的原核表达系统,并获得了具有免疫反应性的NR1-M1及NR1-S1-GT-S2纯化蛋白。该蛋白有望用于NMDAR1蛋白的功能研究及自身抗体的检测。

Characterizing and annotating the genome using RNA-seq data

Bioinformatics methods for various RNA-seq data analyses are in fast evolution with the improvement of sequencing technologies. However, many challenges still exist in how to efficiently process the RNA-seq data to obtain accurate and comprehensive results. Here we reviewed the strategies for improving diverse transcriptomic studies and the annotation of genetic variants based on RNA-seq data. Mapping RNA-seq reads to the genome and transcriptome represent two distinct methods for quantifying the expression of genes/transcripts. Besides the known genes annotated in current databases, many novel genes/transcripts(especially those long noncoding RNAs) still can be identified on the reference genome using RNA-seq. Moreover, owing to the incompleteness of current reference genomes, some novel genes are missing from them. Genome-guided and de novo transcriptome reconstruction are two effective and complementary strategies for identifying those novel genes/transcripts on or beyond the reference genome. In addition, integrating the genes of distinct databases to conduct transcriptomics and genetics studies can improve the results of corresponding analyses.

Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine

High-throughput next generation sequencing (NGS) is a shotgun approach applied in a parallel fashion by which the genome is fragmented and sequenced through small pieces and then analyzed either by aligning to a known reference genome or by de novo assembly without reference genome.This technology has led researchers to conduct an explosion of sequencing related projects in multidisciplinary fields of science.However,due to the limitations of sequencing-based chemistry,length of sequencing reads and the complexity of genes,it is difficult to determine the sequences of some portions of the human genome,leaving gaps in genomic data that frustrate further analysis.Particularly,some complex genes are difficult to be accurately sequenced or mapped because they contain high GC-content and/or low complexity regions,and complicated pseudogenes,such as the genes encoding xenobiotic metabolizing enzymes and transporters (XMETs).The genetic variants in XMET genes are critical to predicate interindividual variability in drug efficacy,drug safety and susceptibility to environmental toxicity.We summarized and discussed challenges,wet-lab methods,and bioinformatics algorithms in sequencing "complex" XMET genes,which may provide insightful information in the application of NGS technology for implementation in toxicogenomics and pharmacogenomics.

Significant variations in alternative splicing patterns and expression profiles between human-mouse orthologs in early embryos

Human and mouse orthologs are expected to have similar biological functions; however, many discrepancies have also been reported. We systematically compared human and mouse orthologs in terms of alternative splicing patterns and expression profiles. Human-mouse orthologs are divergent in alternative splicing, as human orthologs could generally encode more isoforms than their mouse orthologs. In early embryos, exon skipping is far more common with human orthologs, whereas constitutive exons are more prevalent with mouse orthologs. This may correlate with divergence in expression of splicing regulators. Orthologous expression similarities are different in distinct embryonic stages, with the highest in morula. Expression differences for orthologous transcription factor genes could play an important role in orthologous expression discordance. We further detected largely orthologous divergence in differential expression between distinct embryonic stages. Collectively, our study uncovers significant orthologous divergence from multiple aspects, which may result in functional differences and dynamics between human-mouse orthologs during embryonic development.

Identifying and annotating human bifunctional RNAs reveals their versatile functions

Bifunctional RNAs that possess both protein-coding and noncoding functional properties were less explored and poorly understood. Here we systematically explored the characteristics and functions of such human bifunctional RNAs by integrating tandem mass spectrometry and RNA-seq data. We first constructed a pipeline to identify and annotate bifunctional RNAs,leading to the characterization of 132 high-confidence bifunctional RNAs. Our analyses indicate that bifunctional RNAs may be involved in human embryonic development and can be functional in diverse tissues. Moreover, bifunctional RNAs could interact with multiple miRNAs and RNA-binding proteins to exert their corresponding roles. Bifunctional RNAs may also function as competing endogenous RNAs to regulate the expression of many genes by competing for common targeting miRNAs. Finally,somatic mutations of diverse carcinomas may generate harmful effect on corresponding bifunctional RNAs. Collectively,our study not only provides the pipeline for identifying and annotating bifunctional RNAs but also reveals their important gene-regulatory functions.