Complexity Reduction of Polymorphic Sequences (CRoPS™): A Novel Approach for Large-Scale Polymorphism Discovery in Complex Genomes

Application of single nucleotide polymorphisms (SNPs) is revolutionizing human bio-medical research. However, discovery of polymorphisms in low polymorphic species is still a challenging and costly endeavor, despite widespread availability of Sanger sequencing technology. We present CRoPS™ as a novel approach for polymorphism discovery by combining the power of reproducible genome complexity reduction of AFLP® with Genome Sequencer (GS) 20/GS FLX next-generation sequencing technology. With CRoPS, hundreds-of-thousands of sequence reads derived from complexity-reduced genome sequences of two or more samples are processed and mined for SNPs using a fully-automated bioinformatics pipeline. We show that over 75% of putative maize SNPs discovered using CRoPS are successfully converted to SNPWave® assays, confirming them to be true SNPs derived from unique (single-copy) genome sequences. By using CRoPS, polymorphism discovery will become affordable in organisms with high levels of repetitive DNA in the genome and/or low levels of polymorphism in the (breeding) germplasm without the need for prior sequence information

High-Throughput Detection of Induced Mutations and Natural Variation Using KeyPoint™ Technology

Reverse genetics approaches rely on the detection of sequence alterations in target genes to identify allelic variants among mutant or natural populations. Current (pre-) screening methods such as TILLING and EcoTILLING are based on the detection of single base mismatches in heteroduplexes using endonucleases such as CEL 1. However, there are drawbacks in the use of endonucleases due to their relatively poor cleavage efficiency and exonuclease activity. Moreover, pre-screening methods do not reveal information about the nature of sequence changes and their possible impact on gene function. We present KeyPoint™ technology, a high-throughput mutation/polymorphism discovery technique based on massive parallel sequencing of target genes amplified from mutant or natural populations. KeyPoint combines multi-dimensional pooling of large numbers of individual DNA samples and the use of sample identification tags (“sample barcoding”) with next-generation sequencing technology. We show the power of KeyPoint by identifying two mutants in the tomato eIF4E gene based on screening more than 3000 M2 families in a single GS FLX sequencing run, and discovery of six haplotypes of tomato eIF4E gene by re-sequencing three amplicons in a subset of 92 tomato lines from the EU-SOL core collection. We propose KeyPoint technology as a broadly applicable amplicon sequencing approach to screen mutant populations or germplasm collections for identification of (novel) allelic variation in a high-throughput fashion

Self-reported work productivity in people with multiple sclerosis and its association with mental and physical health

PURPOSE: This study aimed to identify mental health, physical health, demographic and disease characteristics relating to work productivity in people with multiple sclerosis (MS). METHODS: In this cross-sectional study, 236 employed people with MS (median age = 42 years, 78.8% female) underwent neurological and neuropsychological assessments. Additionally, they completed questionnaires inquiring about work productivity (presenteeism: reduced productivity while working, and absenteeism: loss of productivity due to absence from work), mental and physical health, demographic and disease characteristics. Multiple linear and logistic regression analyses were performed with presenteeism and absenteeism as dependent variables, respectively. RESULTS: A model with mental and physical health factors significantly predicted presenteeism F(11,202) = 11.33, p < 0.001, R2 = 0.38; a higher cognitive (p < 0.001) and physical impact (p = 0.042) of fatigue were associated with more presenteeism. A model with only mental health factors significantly predicted absenteeism; χ2(11)=37.72, p < 0.001, with R2 = 0.27 (Nagelkerke) and R2 = 0.16 (Cox and Snell). Specifically, we observed that more symptoms of depression (p = 0.041) and a higher cognitive impact of fatigue (p = 0.011) were significantly associated with more absenteeism. CONCLUSIONS: In people with MS, both cognitive and physical impact of fatigue are positively related to presenteeism, while symptoms of depression and cognitive impact of fatigue are positively related to absenteeism.Implications for rehabilitationMultiple sclerosis (MS) affects people of working age, significantly interfering with work productivity.Higher cognitive and physical impact of fatigue were associated with more presenteeism in workers with MS.A higher cognitive impact of fatigue and more depressive symptoms were associated with absenteeism in workers with MS.Occupational and healthcare professionals should be aware of the impact of both physical and mental health on work productivity in workers with MS

Sequence-Based Genotyping for Marker Discovery and Co-Dominant Scoring in Germplasm and Populations

Conventional marker-based genotyping platforms are widely available, but not without their limitations. In this context, we developed Sequence-Based Genotyping (SBG), a technology for simultaneous marker discovery and co-dominant scoring, using next-generation sequencing. SBG offers users several advantages including a generic sample preparation method, a highly robust genome complexity reduction strategy to facilitate de novo marker discovery across entire genomes, and a uniform bioinformatics workflow strategy to achieve genotyping goals tailored to individual species, regardless of the availability of a reference sequence. The most distinguishing features of this technology are the ability to genotype any population structure, regardless whether parental data is included, and the ability to co-dominantly score SNP markers segregating in populations. To demonstrate the capabilities of SBG, we performed marker discovery and genotyping in Arabidopsis thaliana and lettuce, two plant species of diverse genetic complexity and backgrounds. Initially we obtained 1,409 SNPs for arabidopsis, and 5,583 SNPs for lettuce. Further filtering of the SNP dataset produced over 1,000 high quality SNP markers for each species. We obtained a genotyping rate of 201.2 genotypes/SNP and 58.3 genotypes/SNP for arabidopsis (n = 222 samples) and lettuce (n = 87 samples), respectively. Linkage mapping using these SNPs resulted in stable map configurations. We have therefore shown that the SBG approach presented provides users with the utmost flexibility in garnering high quality markers that can be directly used for genotyping and downstream applications. Until advances and costs will allow for routine whole-genome sequencing of populations, we expect that sequence-based genotyping technologies such as SBG will be essential for genotyping of model and non-model genomes alike

SARS-CoV-2 infects the human kidney and drives fibrosis in kidney organoids

Kidney failure is frequently observed during and after COVID-19, but it remains elusive whether this is a direct effect of the virus. Here, we report that SARS-CoV-2 directly infects kidney cells and is associated with increased tubule-interstitial kidney fibrosis in patient autopsy samples. To study direct effects of the virus on the kidney independent of systemic effects of COVID-19, we infected human-induced pluripotent stem-cell-derived kidney organoids with SARS-CoV-2. Single-cell RNA sequencing indicated injury and dedifferentiation of infected cells with activation of profibrotic signaling pathways. Importantly, SARS-CoV-2 infection also led to increased collagen 1 protein expression in organoids. A SARS-CoV-2 protease inhibitor was able to ameliorate the infection of kidney cells by SARS-CoV-2. Our results suggest that SARS-CoV-2 can directly infect kidney cells and induce cell injury with subsequent fibrosis. These data could explain both acute kidney injury in COVID-19 patients and the development of chronic kidney disease in long COVID

SARS-CoV-2 infects the human kidney and drives fibrosis in kidney organoids

Kidney failure is frequently observed during and after COVID-19, but it remains elusive whether this is a direct effect of the virus. Here, we report that SARS-CoV-2 directly infects kidney cells and is associated with increased tubule-interstitial kidney fibrosis in patient autopsy samples. To study direct effects of the virus on the kidney independent of systemic effects of COVID-19, we infected human induced pluripotent stem cell-derived kidney organoids with SARS-CoV-2. Single cell RNA-sequencing indicated injury and dedifferentiation of infected cells with activation of pro-fibrotic signaling pathways. Importantly, SARS-CoV-2 infection also led to increased collagen 1 protein expression in organoids. A SARS-CoV-2 protease inhibitor was able to ameliorate the infection of kidney cells by SARS-CoV-2. Our results suggest that SARS-CoV-2 can directly infect kidney cells and induce cell injury with subsequent fibrosis. These data could explain both acute kidney injury in COVID-19 patients and the development of chronic kidney disease in Long-COVID

SNPSelect: A scalable and flexible targeted sequence-based genotyping solution.

In plant breeding the use of molecular markers has resulted in tremendous improvement of the speed with which new crop varieties are introduced into the market. Single Nucleotide Polymorphism (SNP) genotyping is routinely used for association studies, Linkage Disequilibrium (LD) and Quantitative Trait Locus (QTL) mapping studies, marker-assisted backcrosses and validation of large numbers of novel SNPs. Here we present the KeyGene SNPSelect technology, a scalable and flexible multiplexed, targeted sequence-based, genotyping solution. The multiplex composition of SNPSelect assays can be easily changed between experiments by adding or removing loci, demonstrating their content flexibility. To demonstrate this versatility, we first designed a 1,056-plex maize assay and genotyped a total of 374 samples originating from an F2 and a Recombinant Inbred Line (RIL) population and a maize germplasm collection. Next, subsets of the most informative SNP loci were assembled in 384-plex and 768-plex assays for further genotyping. Indeed, selection of the most informative SNPs allows cost-efficient yet highly informative genotyping in a custom-made fashion, with average call rates between 88.1% (1,056-plex assay) and 99.4% (384-plex assay), and average reproducibility rates between duplicate samples ranging from 98.2% (1056-plex assay) to 99.9% (384-plex assay). The SNPSelect workflow can be completed from a DNA sample to a genotype dataset in less than three days. We propose SNPSelect as an attractive and competitive genotyping solution to meet the targeted genotyping needs in fields such as plant breeding

New Arabidopsis Recombinant Inbred Line Populations Genotyped Using SNPWave and Their Use for Mapping Flowering-Time Quantitative Trait Loci

The SNPWave marker system, based on SNPs between the reference accessions Colombia-0 and Landsberg erecta (Ler), was used to distinguish a set of 92 Arabidopsis accessions from various parts of the world. In addition, we used these markers to genotype three new recombinant inbred line populations for Arabidopsis, having Ler as a common parent that was crossed with the accessions Antwerp-1, Kashmir-2, and Kondara. The benefit of using multiple populations that contain many similar markers and the fact that all markers are linked to the physical map of Arabidopsis facilitates the quantitative comparison of maps. Flowering-time variation was analyzed in the three recombinant inbred line populations. Per population, four to eight quantitative trait loci (QTL) were detected. The comparison of the QTL positions related to the physical map allowed the estimate of 12 different QTL segregating for flowering time for which Ler has an allele different from one, two, or three of the other accessions