Development and Validation of a Multiclass Model Defining Molecular Archetypes of Kidney Transplant Rejection: A Large Cohort Study of the Banff Human Organ Transplant Gene Expression Panel.

Gene expression profiling from formalin-fixed paraffin-embedded (FFPE) renal allograft biopsies is a promising approach for feasibly providing a molecular diagnosis of rejection. However, large-scale studies evaluating the performance of models using NanoString platform data to define molecular archetypes of rejection are lacking. We tested a diverse retrospective cohort of over 1400 FFPE biopsy specimens, rescored according to Banff 2019 criteria and representing 10 of 11 United Network of Organ Sharing regions, using the Banff Human Organ Transplant panel from NanoString and developed a multiclass model from the gene expression data to assign relative probabilities of 4 molecular archetypes: No Rejection, Antibody-Mediated Rejection, T Cell-Mediated Rejection, and Mixed Rejection. Using Least Absolute Shrinkage and Selection Operator regularized regression with 10-fold cross-validation fitted to 1050 biopsies in the discovery cohort and technically validated on an additional 345 biopsies, our model achieved overall accuracy of 85% in the discovery cohort and 80% in the validation cohort, with ≥75% positive predictive value for each class, except for the Mixed Rejection class in the validation cohort (positive predictive value, 53%). This study represents the technical validation of the first model built from a large and diverse sample of diagnostic FFPE biopsy specimens to define and classify molecular archetypes of histologically defined diagnoses as derived from Banff Human Organ Transplant panel gene expression profiling data.

Clinical outcomes from the Assessing Donor-derived cell-free DNA Monitoring Insights of kidney Allografts with Longitudinal surveillance (ADMIRAL) study.

The use of routine monitoring of donor-derived cell-free DNA (dd-cfDNA) after kidney transplant may allow clinicians to identify subclinical allograft injury and intervene prior to development of clinically evident graft injury. To evaluate this, data from 1092 kidney transplant recipients monitored for dd-cfDNA over a three-year period was analyzed to assess the association of dd-cfDNA with histologic evidence of allograft rejection. Elevation of dd-cfDNA (0.5% or more) was significantly correlated with clinical and subclinical allograft rejection. dd-cfDNA values of 0.5% or more were associated with a nearly three-fold increase in risk development of de novo donor-specific antibodies (hazard ratio 2.71) and were determined to be elevated a median of 91 days (interquartile range of 30-125 days) ahead of donor specific antibody identification. Persistently elevated dd-cfDNA (more than one result above the 0.5% threshold) predicted over a 25% decline in the estimated glomerular filtration rate over three years (hazard ratio 1.97). Therefore, routine monitoring of dd-cfDNA allowed early identification of clinically important graft injury. Biomarker monitoring complemented histology and traditional laboratory surveillance strategies as a prognostic marker and risk-stratification tool post-transplant. Thus, persistently low dd-cfDNA levels may accurately identify allograft quiescence or absence of injury, paving the way for personalization of immunosuppression trials.

Efficient and unique cobarcoding of second-generation sequencing reads from long DNA molecules enabling cost-effective and accurate sequencing, haplotyping, and de novo assembly.

Here, we describe single-tube long fragment read (stLFR), a technology that enables sequencing of data from long DNA molecules using economical second-generation sequencing technology. It is based on adding the same barcode sequence to subfragments of the original long DNA molecule (DNA cobarcoding). To achieve this efficiently, stLFR uses the surface of microbeads to create millions of miniaturized barcoding reactions in a single tube. Using a combinatorial process, up to 3.6 billion unique barcode sequences were generated on beads, enabling practically nonredundant cobarcoding with 50 million barcodes per sample. Using stLFR, we demonstrate efficient unique cobarcoding of more than 8 million 20- to 300-kb genomic DNA fragments. Analysis of the human genome NA12878 with stLFR demonstrated high-quality variant calling and phase block lengths up to N50 34 Mb. We also demonstrate detection of complex structural variants and complete diploid de novo assembly of NA12878. These analyses were all performed using single stLFR libraries, and their construction did not significantly add to the time or cost of whole-genome sequencing (WGS) library preparation. stLFR represents an easily automatable solution that enables high-quality sequencing, phasing, SV detection, scaffolding, cost-effective diploid de novo genome assembly, and other long DNA sequencing applications.

Validation of a gene expression signature to measure immune quiescence in kidney transplant recipients in the CLIA setting.

Aim: Allograft rejection remains a major cause of graft failure in kidney transplantation. Here the authors report the validation of a non-invasive molecular diagnostic assay, AlloMap Kidney, using peripheral blood. Methods: The AlloMap Kidney test is a gene expression profile utilizing the RNA-seq platform to measure immune quiescence in kidney transplant patients. Results/Conclusions: Analytical validation showed robust performance characteristics with an accuracy correlation coefficient of 0.997 and a precision coefficient of variation of 0.049 across testing. Clinical validation from the prospective, multi-center studies of 235 samples (66 rejection and 169 quiescence specimens) demonstrated the sensitivity of 70% and specificity of 66% for allograft rejection, while the negative predictive value was 95% to discriminate rejection from quiescence at 10% prevalence of rejection.

Enriching Genomic Resources and Marker Development from Transcript Sequences of Jatropha curcas for Microgravity Studies.

Jatropha (Jatropha curcas L.) is an economically important species with a great potential for biodiesel production. To enrich the jatropha genomic databases and resources for microgravity studies, we sequenced and annotated the transcriptome of jatropha and developed SSR and SNP markers from the transcriptome sequences. In total 1,714,433 raw reads with an average length of 441.2 nucleotides were generated. De novo assembling and clustering resulted in 115,611 uniquely assembled sequences (UASs) including 21,418 full-length cDNAs and 23,264 new jatropha transcript sequences. The whole set of UASs were fully annotated, out of which 59,903 (51.81%) were assigned with gene ontology (GO) term, 12,584 (10.88%) had orthologs in Eukaryotic Orthologous Groups (KOG), and 8,822 (7.63%) were mapped to 317 pathways in six different categories in Kyoto Encyclopedia of Genes and Genome (KEGG) database, and it contained 3,588 putative transcription factors. From the UASs, 9,798 SSRs were discovered with AG/CT as the most frequent (45.8%) SSR motif type. Further 38,693 SNPs were detected and 7,584 remained after filtering. This UAS set has enriched the current jatropha genomic databases and provided a large number of genetic markers, which can facilitate jatropha genetic improvement and many other genetic and biological studies.