Integrated physical, genetic and genome map of chickpea (Cicer arietinum L.)

Physical map of chickpea was developed for the reference chickpea genotype (ICC 4958) using bacterial artificial chromosome (BAC) libraries targeting 71,094 clones (~12× coverage). High information content fingerprinting (HICF) of these clones gave high-quality fingerprinting data for 67,483 clones, and 1,174 contigs comprising 46,112 clones and 3,256 singletons were defined. In brief, 574 Mb genome size was assembled in 1,174 contigs with an average of 0.49 Mb per contig and 3,256 singletons represent 407 Mb genome. The physical map was linked with two genetic maps with the help of 245 BAC-end sequence (BES)-derived simple sequence repeat (SSR) markers. This allowed locating some of the BACs in the vicinity of some important quantitative trait loci (QTLs) for drought tolerance and reistance to Fusarium wilt and Ascochyta blight. In addition, fingerprinted contig (FPC) assembly was also integrated with the draft genome sequence of chickpea. As a result, ~965 BACs including 163 minimum tilling path (MTP) clones could be mapped on eight pseudo-molecules of chickpea forming 491 hypothetical contigs representing 54,013,992 bp (~54 Mb) of the draft genome. Comprehensive analysis of markers in abiotic and biotic stress tolerance QTL regions led to identification of 654, 306 and 23 genes in drought tolerance “QTL-hotspot” region, Ascochyta blight resistance QTL region and Fusarium wilt resistance QTL region, respectively. Integrated physical, genetic and genome map should provide a foundation for cloning and isolation of QTLs/genes for molecular dissection of traits as well as markers for molecular breeding for chickpea improvement

Disease-Causing 7.4 kb Cis-Regulatory Deletion Disrupting Conserved Non-Coding Sequences and Their Interaction with the FOXL2 Promotor: Implications for Mutation Screening

To date, the contribution of disrupted potentially cis-regulatory conserved non-coding sequences (CNCs) to human disease is most likely underestimated, as no systematic screens for putative deleterious variations in CNCs have been conducted. As a model for monogenic disease we studied the involvement of genetic changes of CNCs in the cis-regulatory domain of FOXL2 in blepharophimosis syndrome (BPES). Fifty-seven molecularly unsolved BPES patients underwent high-resolution copy number screening and targeted sequencing of CNCs. Apart from three larger distant deletions, a de novo deletion as small as 7.4 kb was found at 283 kb 5′ to FOXL2. The deletion appeared to be triggered by an H-DNA-induced double-stranded break (DSB). In addition, it disrupts a novel long non-coding RNA (ncRNA) PISRT1 and 8 CNCs. The regulatory potential of the deleted CNCs was substantiated by in vitro luciferase assays. Interestingly, Chromosome Conformation Capture (3C) of a 625 kb region surrounding FOXL2 in expressing cellular systems revealed physical interactions of three upstream fragments and the FOXL2 core promoter. Importantly, one of these contains the 7.4 kb deleted fragment. Overall, this study revealed the smallest distant deletion causing monogenic disease and impacts upon the concept of mutation screening in human disease and developmental disorders in particular

Exploring the feasibility of delivering standardized genomic care using ophthalmology as an example

Purpose: Broadening access to genomic testing and counseling will be necessary to realize the benefits of personalized health care. This study aimed to assess the feasibility of delivering a standardized genomic care model for inherited retinal dystrophy (IRD) and of using selected measures to quantify its impact on patients. Methods: A pre-/post- prospective cohort study recruited 98 patients affected by IRD to receive standardized multidisciplinary care. A checklist was used to assess the fidelity of the care process. Three patient-reported outcome measures—the Genetic Counselling Outcome Scale (GCOS-24), the ICEpop CAPability measure for Adults (ICECAP-A), and the EuroQol 5-dimension questionnaire (EQ-5D)—and a resource-use questionnaire were administered to investigate rates of missingness, ceiling effects, and changes over time. Results: The care model was delivered consistently. Higher rates of missingness were found for the genetic-specific measure (GCOS-24). Considerable ceiling effects were observed for the generic measure (EQ-5D). The ICECAP-A yielded less missing data without significant ceiling effects. It was feasible to use telephone interviews for follow-up data collection. Conclusion: The study highlighted challenges and solutions associated with efforts to standardize genomic care for IRD. The study identified appropriate methods for a future definitive study to assess the clinical effectiveness and cost-effectiveness of the care model