Biology subjects

Patidar, R.

Publications and source records attributed to Patidar, R..

4 recordsLinked to original sources

bioRxiv2025

Equine Parentage Testing with SNPs and beyond: developing a platform independent panel

Centuries of selective equine breeding have led to a remarkable diversity of horse breeds each with unique traits. To maintain these breeds, studbooks require parentage testing to guarantee lineage. To determine parentage, the industry assays length polymorphisms in short tandem repeats (STRs) established by the International Society of Animal Genetics (ISAG). However, STRs have significant limitations including challenges with accurately determining genotype, relatively low number of STRs assayed, and low throughput. For these reasons, most other animal breeds including cattle, dog, goats, and sheep use single nucleotide polymorphisms (SNPs) for parentage identification. To this end, the ISAG has introduced a panel of SNPs. Here, we further demonstrate the utility of equine SNP genotyping. Importantly, we show that a number of the ISAG SNPs are not compatible with widely-used, short-read, next generation sequencing (NGS) technologies. Fortunately, SNPs are abundant, and we propose an alternative panel that is platform independent and are all ISAG proposed SNPs. We demonstrate that SNP parentage genotyping is extremely robust and enables additional assays including breed identification and can be readily expanded to also assay equine genetic diseases.

genomics↗

bioRxiv2019

Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, impacting the accuracy of PDX modeling of human cancer. Here we exhaustively analyze copy number alterations (CNAs) in 1451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multi-region samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

cancer biology↗

bioRxiv2019

Systematic Establishment of Robustness and Standards in Patient-Derived Xenograft Experiments and Analysis

Patient-Derived Xenografts (PDXs) are tumor-in-mouse models for cancer. PDX collections, such as those supported by the NCI PDXNet program, are powerful resources for preclinical therapeutic testing. However, variations in experimental design and analysis procedures have limited interpretability. To determine the robustness of PDX studies, the PDXNet tested temozolomide drug response for three pre-validated PDX models (sensitive, resistant, and intermediate) across four blinded PDX Development and Trial Centers (PDTCs) using independently selected SOPs. Each PDTC was able to correctly identify the sensitive, resistant, and intermediate models, and statistical evaluations were concordant across all groups. We also developed and benchmarked optimized PDX informatics pipelines, and these yielded robust assessments across xenograft biological replicates. These studies show that PDX drug responses and sequence results are reproducible across diverse experimental protocols. Here we share the range of experimental procedures that maintained robustness, as well as standardized cloud-based workflows for PDX exome-seq and RNA-Seq analysis and for evaluating growth.

cancer biology↗

bioRxiv2018

Integrated proteogenomic analysis of metastatic thoracic tumors identifies APOBEC mutagenesis and copy number alterations as drivers of proteogenomic tumor evolution and heterogeneity

Elucidation of the proteogenomic evolution of metastatic tumors may offer insight into the poor prognosis of patients harboring metastatic disease. We performed whole-exome and transcriptome sequencing, copy number alterations (CNA) and mass spectrometry-based quantitative proteomics of 37 lung adenocarcinoma (LUAD) and thymic carcinoma (TC) metastases obtained by rapid autopsy and found evidence of patient-specific, multi-dimensional heterogeneity. Extreme mutational heterogeneity was evident in a subset of patients whose tumors showed increased APOBEC-signature mutations and expression of APOBEC3 region transcripts compared to patients with lesser mutational heterogeneity. TP53 mutation status was associated with APOBEC hypermutators in our cohort and in three independent LUAD datasets. In a thymic carcinoma patient, extreme heterogeneity and increased APOBEC3AB expression was associated with a high-risk germline APOBEC3AB variant allele. Patients with CNA occurring late in tumor evolution had corresponding changes in gene expression and protein abundance indicating genomic instability as a mechanism of downstream transcriptomic and proteomic heterogeneity between metastases. Across all tumors, proteomic heterogeneity was greater than copy number and transcriptomic heterogeneity. Enrichment of interferon pathways was evident both in the transcriptome and proteome of the tumors enriched for APOBEC mutagenesis despite a heterogeneous immune microenvironment across metastases suggesting a role for the immune microenvironment in the expression of APOBEC transcripts and generation of mutational heterogeneity. The evolving, heterogeneous nature of LUAD and TC, through APOBEC-mutagenesis and CNA illustrate the challenges facing treatment outcomes.

cancer biology↗