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1. COLD-PCR Enrichment of Rare Cancer Mutations prior to Targeted Amplicon Resequencing

   https://doi.org/10.1373/clinchem.2011.176198  

   Milbury, Coren A. ; Correll, Mick ; Quackenbush, John ; Rubio, Renee ; Makrigiorgos, G. Mike ( January 2020 , Clinical Chemistry)

   Despite widespread interest in next-generation sequencing (NGS), the adoption of personalized clinical genomics and mutation profiling of cancer specimens is lagging, in part because of technical limitations. Tumors are genetically heterogeneous and often contain normal/stromal cells, features that lead to low-abundance somatic mutations that generate ambiguous results or reside below NGS detection limits, thus hindering the clinical sensitivity/specificity standards of mutation calling. We applied COLD-PCR (coamplification at lower denaturation temperature PCR), a PCR methodology that selectively enriches variants, to improve the detection of unknown mutations before NGS-based amplicon resequencing.

   We used both COLD-PCR and conventional PCR (for comparison) to amplify serially diluted mutation-containing cell-line DNA diluted into wild-type DNA, as well as DNA from lung adenocarcinoma and colorectal cancer samples. After amplification of TP53 (tumor protein p53), KRAS (v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog), IDH1 [isocitrate dehydrogenase 1 (NADP+), soluble], and EGFR (epidermal growth factor receptor) gene regions, PCR products were pooled for library preparation, bar-coded, and sequenced on the Illumina HiSeq 2000.

   In agreement with recent findings, sequencing errors by conventional targeted-amplicon approaches dictated a mutation-detection limit of approximately 1%–2%. Conversely, COLD-PCR amplicons enriched mutations above the error-related noise, enabling reliable identification of mutation abundances of approximately 0.04%. Sequencing depth was not a large factor in the identification of COLD-PCR–enriched mutations. For the clinical samples, several missense mutations were not called with conventional amplicons, yet they were clearly detectable with COLD-PCR amplicons. Tumor heterogeneity for the TP53 gene was apparent.

   As cancer care shifts toward personalized intervention based on each patient's unique genetic abnormalities and tumor genome, we anticipate that COLD-PCR combined with NGS will elucidate the role of mutations in tumor progression, enabling NGS-based analysis of diverse clinical specimens within clinical practice.

    

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2. High‐Throughput and Low‐Cost Genotyping Method for Plant Genome Editing

   https://doi.org/10.1002/cpz1.100  

   Liu, Lei ; Chen, Richelle ; Fugina, Christopher John ; Siegel, Ben ; Jackson, David ( April 2021 , Current Protocols)

   Genome editing technologies have revolutionized genetic studies in the life sciences community in recent years. The application of these technologies allows researchers to conveniently generate mutations in almost any gene of interest. This is very useful for species such as maize that have complex genomes and lack comprehensive mutant collections. With the improvement of genome editing tools and transformation methods, these technologies are also widely used to assist breeding research and implementation in maize. However, the detection and genotyping of genomic edits rely on low‐throughput, high‐cost methods, such as traditional agarose gel electrophoresis and Sanger sequencing. This article describes a method to barcode the target regions of genomic edits from many individuals by low‐cost polymerase chain reaction (PCR) amplification. It also employs next‐generation sequencing (NGS) to genotype the genome‐edited plants at high throughput and low cost. This protocol can be used for initial screening of genomic edits as well as derived population genotyping on a small or large scale, at high efficiency and low cost. © 2021 Wiley Periodicals LLC.

   Basic Protocol 1: A fast genomic DNA preparation method from genome edited plants

   Basic Protocol 2: Barcoding the amplicons of edited regions from each individual by two rounds of PCR

   Basic Protocol 3: Bioinformatics analysis

    

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3. Identifying SARS-CoV-2 Variants of Concern through Saliva-Based RT-qPCR by Targeting Recurrent Mutation Sites

   https://doi.org/10.1128/spectrum.00797-22  

   Ham, Rachel E. ; Smothers, Austin R. ; Che, Rui ; Sell, Keegan J. ; Peng, Congyue Annie ; Dean, Delphine ( June 2022 , Microbiology Spectrum)

   Mostafa, Heba H. (Ed.)

   ABSTRACT SARS-CoV-2 variants of concern (VOCs) continue to pose a public health threat which necessitates a real-time monitoring strategy to complement whole genome sequencing. Thus, we investigated the efficacy of competitive probe RT-qPCR assays for six mutation sites identified in SARS-CoV-2 VOCs and, after validating the assays with synthetic RNA, performed these assays on positive saliva samples. When compared with whole genome sequence results, the SΔ69-70 and ORF1aΔ3675-3677 assays demonstrated 93.60 and 68.00% accuracy, respectively. The SNP assays (K417T, E484K, E484Q, L452R) demonstrated 99.20, 96.40, 99.60, and 96.80% accuracies, respectively. Lastly, we screened 345 positive saliva samples from 7 to 22 December 2021 using Omicron-specific mutation assays and were able to quickly identify rapid spread of Omicron in Upstate South Carolina. Our workflow demonstrates a novel approach for low-cost, real-time population screening of VOCs. IMPORTANCE SARS-CoV-2 variants of concern and their many sublineages can be characterized by mutations present within their genetic sequences. These mutations can provide selective advantages such as increased transmissibility and antibody evasion, which influences public health recommendations such as mask mandates, quarantine requirements, and treatment regimens. Our RT-qPCR workflow allows for strain identification of SARS-CoV-2 positive saliva samples by targeting common mutation sites shared between variants of concern and detecting single nucleotides present at the targeted location. This differential diagnostic system can quickly and effectively identify a wide array of SARS-CoV-2 strains, which can provide more informed public health surveillance strategies in the future. 

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4. Mitochondrial mutations in Caenorhabditis elegans show signatures of oxidative damage and an AT-bias

   https://doi.org/10.1093/genetics/iyab116  

   Waneka, Gus ; Svendsen, Joshua M ; Havird, Justin C ; Sloan, Daniel B ( August 2021 , Genetics)

   Surtees, J A (Ed.)

   Abstract Rapid mutation rates are typical of mitochondrial genomes (mtDNAs) in animals, but it is not clear why. The difficulty of obtaining measurements of mtDNA mutation that are not biased by natural selection has stymied efforts to distinguish between competing hypotheses about the causes of high mtDNA mutation rates. Several studies which have measured mtDNA mutations in nematodes have yielded small datasets with conflicting conclusions about the relative abundance of different substitution classes (i.e., the mutation spectrum). We therefore leveraged Duplex Sequencing, a high-fidelity DNA sequencing technique, to characterize de novo mtDNA mutations in Caenorhabditis elegans. This approach detected nearly an order of magnitude more mtDNA mutations than documented in any previous nematode mutation study. Despite an existing extreme AT bias in the C. elegans mtDNA (75.6% AT), we found that a significant majority of mutations increase genomic AT content. Compared to some prior studies in nematodes and other animals, the mutation spectrum reported here contains an abundance of CG→AT transversions, supporting the hypothesis that oxidative damage may be a driver of mtDNA mutations in nematodes. Furthermore, we found an excess of G→T and C→T changes on the coding DNA strand relative to the template strand, consistent with increased exposure to oxidative damage. Analysis of the distribution of mutations across the mtDNA revealed significant variation among protein-coding genes and as well as among neighboring nucleotides. This high-resolution view of mitochondrial mutations in C. elegans highlights the value of this system for understanding relationships among oxidative damage, replication error, and mtDNA mutation. 

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5. Prediction of evolutionary constraint by genomic annotations improves functional prioritization of genomic variants in maize

   https://doi.org/10.1186/s13059-022-02747-2  

   Ramstein, Guillaume_P ; Buckler, Edward_S ( September 2022 , Genome Biology)

   Crop improvement through cross-population genomic prediction and genome editing requires identification of causal variants at high resolution, within fewer than hundreds of base pairs. Most genetic mapping studies have generally lacked such resolution. In contrast, evolutionary approaches can detect genetic effects at high resolution, but they are limited by shifting selection, missing data, and low depth of multiple-sequence alignments. Here we use genomic annotations to accurately predict nucleotide conservation across angiosperms, as a proxy for fitness effect of mutations.

   Using only sequence analysis, we annotate nonsynonymous mutations in 25,824 maize gene models, with information from bioinformatics and deep learning. Our predictions are validated by experimental information: within-species conservation, chromatin accessibility, and gene expression. According to gene ontology and pathway enrichment analyses, predicted nucleotide conservation points to genes in central carbon metabolism. Importantly, it improves genomic prediction for fitness-related traits such as grain yield, in elite maize panels, by stringent prioritization of fewer than 1% of single-site variants.

   Our results suggest that predicting nucleotide conservation across angiosperms may effectively prioritize sites most likely to impact fitness-related traits in crops, without being limited by shifting selection, missing data, and low depth of multiple-sequence alignments. Our approach—Prediction of mutation Impact by Calibrated Nucleotide Conservation (PICNC)—could be useful to select polymorphisms for accurate genomic prediction, and candidate mutations for efficient base editing. The trained PICNC models and predicted nucleotide conservation at protein-coding SNPs in maize are publicly available in CyVerse (https://doi.org/10.25739/hybz-2957).

    

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