Large structural variants in KOLF2.1J are unlikely to compromise neurological disease modelling.

Gracia-Diaz and colleagues analysed high-density DNA microarray and whole genome sequencing (WGS) data from the KOLF2.1J 'reference' human induced pluripotent stem cell (hiPSC) line1, and report the presence of five high-confidence heterozygous copy number variants (CNVs) at least 100kbp in length2. Since three of these CNVs span coding genes, some of which have been associated with neurodevelopmental disease, the authors raise the concern that these CNVs may compromise the utility of KOLF2.1J for neurological disease modelling. We appreciate their thorough analysis and thoughtful interpretation, and agree that potential users of this line should be made aware of all cases where KOLF2.1J differs from the reference genome. However, we believe that the benefits from the widespread use of KOLF2.1J outweigh the potential risks that might arise from the identified CNVs.

Is the Y-PEM useful for me? Perspectives of youth with visual impairment.

PURPOSE: To explore how youth with visual impairments perceive the usefulness of the Y-PEM (Youth and Young-adult Participation and Environment Measure) in capturing their participation and how information generated contributes to their understanding of participation experiences. MATERIALS AND METHODS: A qualitative descriptive design was employed among 11 youth with visual impairment (3 females, 8 males) aged 17-24 (x¯ = 21, SD = 2.6) involving two remote sessions one week apart. First, the Y-PEM and QQ-10 questionnaire were administered to evaluate Y-PEM's utility (value and burden), analyzed descriptively. Then, youth reflected on their Y-PEM results via an individual semi-structured Stimulated Recall Interview (SRI), analyzed thematically. RESULTS: A mean value-score of 77% (SD = 10.4) and burden-score of 19% (SD = 5.6) on the QQ-10 indicated the Y-PEM was perceived as valuable with relatively low burden. Three themes emerged from the interviews. Insights on participation revealed increased awareness of participation patterns and environmental factors. This led to a reflection on personal attributes about levels of comfort and familiarity, efforts required to participate, and personal preferences influencing participation experiences. Finally, approaches to participation elucidated strategies used in decision-making processes about pursuing participation. CONCLUSION: Findings suggest the Y-PEM is useful in capturing and promoting reflection of youth's participation patterns and environmental supports/barriers.

The Y-PEM PEM (Youth and Young-adult Participation and Environment Measure) appears to provide a meaningful way for youth with visual impairments to understand their participation patterns and experiencesDiscussing youth's results of the Y-PEM with them can lead to new insights and reflections about their participation preferences, environmental barriers and supports, and other influential personal and external factors on their participationUsing the Y-PEM as a tool to facilitate this reflection and discussion about youth's participation can guide therapy interventions focused on participation through eliciting meaningful client-centered goals as well as strategies to address environmental barriers.

JAX-CNV: A Whole-genome Sequencing-based Algorithm for Copy Number Detection at Clinical Grade Level.

We aimed to develop a whole-genome sequencing (WGS)-based copy number variant (CNV) calling algorithm with the potential of replacing chromosomal microarray assay (CMA) for clinical diagnosis. JAX-CNV is thus developed for CNV detection from WGS data. The performance of this CNV calling algorithm was evaluated in a blinded manner on 31 samples and compared to the 112 CNVs reported by clinically validated CMAs for these 31 samples. The result showed that JAX-CNV recalled 100% of these CNVs. Besides, JAX-CNV identified an average of 30 CNVs per individual, respresenting an approximately seven-fold increase compared to calls of clinically validated CMAs. Experimental validation of 24 randomly selected CNVs showed one false positive, i.e., a false discovery rate (FDR) of 4.17%. A robustness test on lower-coverage data revealed a 100% sensitivity for CNVs larger than 300 kb (the current threshold for College of American Pathologists) down to 10× coverage. For CNVs larger than 50 kb, sensitivities were 100% for coverages deeper than 20×, 97% for 15×, and 95% for 10×. We developed a WGS-based CNV pipeline, including this newly developed CNV caller JAX-CNV, and found it capable of detecting CMA-reported CNVs at a sensitivity of 100% with about a FDR of 4%. We propose that JAX-CNV could be further examined in a multi-institutional study to justify the transition of first-tier genetic testing from CMAs to WGS. JAX-CNV is available at https://github.com/TheJacksonLaboratory/JAX-CNV.

Mako: A Graph-based Pattern Growth Approach to Detect Complex Structural Variants.

Complex structural variants (CSVs) are genomic alterations that have more than two breakpoints and are considered as the simultaneous occurrence of simple structural variants. However, detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match strategy. As a result, there has been limited progress for CSV discovery compared with simple structural variants. Here, we systematically analyzed the multi-breakpoint connection feature of CSVs, and proposed Mako, utilizing a bottom-up guided model-free strategy, to detect CSVs from paired-end short-read sequencing. Specifically, we implemented a graph-based pattern growth approach, where the graph depicts potential breakpoint connections, and pattern growth enables CSV detection without pre-defined models. Comprehensive evaluations on both simulated and real datasets revealed that Mako outperformed other algorithms. Notably, validation rates of CSVs on real data based on experimental and computational validations as well as manual inspections are around 70%, where the medians of experimental and computational breakpoint shift are 13 bp and 26 bp, respectively. Moreover, the Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types, including two novel types of adjacent segment swap and tandem dispersed duplication. Further analysis of these CSVs also revealed the impact of sequence homology on the formation of CSVs. Mako is publicly available at https://github.com/xjtu-omics/Mako.

High-resolution deconstruction of evolution induced by chemotherapy treatments in breast cancer xenografts.

The processes by which tumors evolve are essential to the efficacy of treatment, but quantitative understanding of intratumoral dynamics has been limited. Although intratumoral heterogeneity is common, quantification of evolution is difficult from clinical samples because treatment replicates cannot be performed and because matched serial samples are infrequently available. To circumvent these problems we derived and assayed large sets of human triple-negative breast cancer xenografts and cell cultures from two patients, including 86 xenografts from cyclophosphamide, doxorubicin, cisplatin, docetaxel, or vehicle treatment cohorts as well as 45 related cell cultures. We assayed these samples via exome-seq and/or high-resolution droplet digital PCR, allowing us to distinguish complex therapy-induced selection and drift processes among endogenous cancer subclones with cellularity uncertainty <3%. For one patient, we discovered two predominant subclones that were granularly intermixed in all 48 co-derived xenograft samples. These two subclones exhibited differential chemotherapy sensitivity-when xenografts were treated with cisplatin for 3 weeks, the post-treatment volume change was proportional to the post-treatment ratio of subclones on a xenograft-to-xenograft basis. A subsequent cohort in which xenografts were treated with cisplatin, allowed a drug holiday, then treated a second time continued to exhibit this proportionality. In contrast, xenografts from other treatment cohorts, spatially dissected xenograft fragments, and cell cultures evolved in diverse ways but with substantial population bottlenecks. These results show that ecosystems susceptible to successive retreatment can arise spontaneously in breast cancer in spite of a background of irregular subclonal bottlenecks, and our work provides to our knowledge the first quantification of the population genetics of such a system. Intriguingly, in such an ecosystem the ratio of common subclones is predictive of the state of treatment susceptibility, showing how measurements of subclonal heterogeneity could guide treatment for some patients.

Systematic analysis of copy number variation associated with congenital diaphragmatic hernia.

Congenital diaphragmatic hernia (CDH), characterized by malformation of the diaphragm and hypoplasia of the lungs, is one of the most common and severe birth defects, and is associated with high morbidity and mortality rates. There is growing evidence demonstrating that genetic factors contribute to CDH, although the pathogenesis remains largely elusive. Single-nucleotide polymorphisms have been studied in recent whole-exome sequencing efforts, but larger copy number variants (CNVs) have not yet been studied on a large scale in a case control study. To capture CNVs within CDH candidate regions, we developed and tested a targeted array comparative genomic hybridization platform to identify CNVs within 140 regions in 196 patients and 987 healthy controls, and identified six significant CNVs that were either unique to patients or enriched in patients compared with controls. These CDH-associated CNVs reveal high-priority candidate genes including HLX, LHX1, and HNF1B We also discuss CNVs that are present in only one patient in the cohort but have additional evidence of pathogenicity, including extremely rare large and/or de novo CNVs. The candidate genes within these predicted disease-causing CNVs form functional networks with other known CDH genes and play putative roles in DNA binding/transcription regulation and embryonic development. These data substantiate the importance of CNVs in the etiology of CDH, identify CDH candidate genes and pathways, and highlight the importance of ongoing analysis of CNVs in the study of CDH and other structural birth defects.

Biological explanations for discordant noninvasive prenatal test results: Preliminary data and lessons learned.

OBJECTIVE: Maternal plasma cell-free DNA (cfDNA) analysis is a powerful screening tool for Down syndrome. In a pilot series, we examined biologic causes of discordance between the cfDNA test results and the fetal karyotype. We also explored the feasibility of obtaining trio biospecimens by using parental engagement. METHODS: A convenience sample of women with discordant cfDNA results were recruited by their care providers. We provided shipping materials and instructions for biospecimen collection. Maternal, newborn, and placental samples were examined with droplet digital PCR. RESULTS: Thirteen of 15 women successfully had biospecimens obtained remotely. High-quality DNA was extracted in 12 of 13 women. Presumed biologic etiologies for discordance were identified in 7 of 12 women: 3 cases from additional clinical review (male renal transplant, vanishing twin, and colon cancer) and 4 cases from additional laboratory investigation using droplet digital PCR (3 with confined placental mosaicism and 1 with true fetal mosaicism). CONCLUSIONS: Understanding the biology behind cfDNA-fetal karyotype discordancy is useful for follow-up clinical care. Our study suggests that most cases could be resolved by using a trio biospecimen protocol and parental involvement. To improve accuracy, additional sequencing of biospecimens will be required.

FusorSV: an algorithm for optimally combining data from multiple structural variation detection methods.

Comprehensive and accurate identification of structural variations (SVs) from next generation sequencing data remains a major challenge. We develop FusorSV, which uses a data mining approach to assess performance and merge callsets from an ensemble of SV-calling algorithms. It includes a fusion model built using analysis of 27 deep-coverage human genomes from the 1000 Genomes Project. We identify 843 novel SV calls that were not reported by the 1000 Genomes Project for these 27 samples. Experimental validation of a subset of these calls yields a validation rate of 86.7%. FusorSV is available at https://github.com/TheJacksonLaboratory/SVE .