Single nucleotide variant counts computed from RNA sequencing and cellular traffic into human kidney allografts

Gaurav Thareja, Hua Yang, Shahina Hayat, Franco B. Mueller, John R. Lee, Michelle Lubetzky, Darshana M. Dadhania, Aziz Belkadi, Surya V. Seshan, Karsten Suhre, Manikkam Suthanthiran, Thangamani Muthukumar

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Advances in bioinformatics allow identification of single nucleotide polymorphisms (variants) from RNA sequence data. In an allograft biopsy, 2 genomes contribute to the RNA pool, 1 from the donor organ and the other from the infiltrating recipient's cells. We hypothesize that imbalances in genetic variants of RNA sequence data of kidney allograft biopsies provide an objective measure of cellular infiltration of the allograft. We performed mRNA sequencing of 40 kidney allograft biopsies, selected to represent a comprehensive range of diagnostic categories. We analyzed the sequencing reads of these biopsies and of 462 lymphoblastoid cell lines from the 1000 Genomes Project, for RNA variants. The ratio of heterozygous to nonreference genome homozygous variants (Het/Hom ratio) on all autosomes was determined for each sample, and the estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) score was computed as a complementary estimate of the degree of cellular infiltration into biopsies. The Het/Hom ratios (P = .02) and the ESTIMATE scores (P < .001) were associated with the biopsy diagnosis. Both measures correlated significantly (r = .67, P < .0001), even though the Het/Hom ratio is based on mRNA sequence variation, while the ESTIMATE score uses mRNA expression. Het/Hom ratio and the ESTIMATE score may offer unbiased and quantitative parameters for characterizing cellular traffic into human kidney allografts.

Original languageEnglish
JournalAmerican Journal of Transplantation
DOIs
Publication statusAccepted/In press - 1 Jan 2018

Fingerprint

RNA Sequence Analysis
Allografts
Nucleotides
Stromal Cells
Kidney
Biopsy
Genome
Messenger RNA
Neoplasms
RNA
Computational Biology
Single Nucleotide Polymorphism
Tissue Donors
Cell Line

Keywords

  • Genomics
  • Kidney transplantation/nephrology
  • Molecular biology: mRNA/mRNA expression
  • Monitoring: immune
  • Translational research/science

ASJC Scopus subject areas

  • Immunology and Allergy
  • Transplantation
  • Pharmacology (medical)

Cite this

Single nucleotide variant counts computed from RNA sequencing and cellular traffic into human kidney allografts. / Thareja, Gaurav; Yang, Hua; Hayat, Shahina; Mueller, Franco B.; Lee, John R.; Lubetzky, Michelle; Dadhania, Darshana M.; Belkadi, Aziz; Seshan, Surya V.; Suhre, Karsten; Suthanthiran, Manikkam; Muthukumar, Thangamani.

In: American Journal of Transplantation, 01.01.2018.

Research output: Contribution to journalArticle

Thareja, Gaurav ; Yang, Hua ; Hayat, Shahina ; Mueller, Franco B. ; Lee, John R. ; Lubetzky, Michelle ; Dadhania, Darshana M. ; Belkadi, Aziz ; Seshan, Surya V. ; Suhre, Karsten ; Suthanthiran, Manikkam ; Muthukumar, Thangamani. / Single nucleotide variant counts computed from RNA sequencing and cellular traffic into human kidney allografts. In: American Journal of Transplantation. 2018.
@article{721994d2aa7040c6827b990b4f6eba15,
title = "Single nucleotide variant counts computed from RNA sequencing and cellular traffic into human kidney allografts",
abstract = "Advances in bioinformatics allow identification of single nucleotide polymorphisms (variants) from RNA sequence data. In an allograft biopsy, 2 genomes contribute to the RNA pool, 1 from the donor organ and the other from the infiltrating recipient's cells. We hypothesize that imbalances in genetic variants of RNA sequence data of kidney allograft biopsies provide an objective measure of cellular infiltration of the allograft. We performed mRNA sequencing of 40 kidney allograft biopsies, selected to represent a comprehensive range of diagnostic categories. We analyzed the sequencing reads of these biopsies and of 462 lymphoblastoid cell lines from the 1000 Genomes Project, for RNA variants. The ratio of heterozygous to nonreference genome homozygous variants (Het/Hom ratio) on all autosomes was determined for each sample, and the estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) score was computed as a complementary estimate of the degree of cellular infiltration into biopsies. The Het/Hom ratios (P = .02) and the ESTIMATE scores (P < .001) were associated with the biopsy diagnosis. Both measures correlated significantly (r = .67, P < .0001), even though the Het/Hom ratio is based on mRNA sequence variation, while the ESTIMATE score uses mRNA expression. Het/Hom ratio and the ESTIMATE score may offer unbiased and quantitative parameters for characterizing cellular traffic into human kidney allografts.",
keywords = "Genomics, Kidney transplantation/nephrology, Molecular biology: mRNA/mRNA expression, Monitoring: immune, Translational research/science",
author = "Gaurav Thareja and Hua Yang and Shahina Hayat and Mueller, {Franco B.} and Lee, {John R.} and Michelle Lubetzky and Dadhania, {Darshana M.} and Aziz Belkadi and Seshan, {Surya V.} and Karsten Suhre and Manikkam Suthanthiran and Thangamani Muthukumar",
year = "2018",
month = "1",
day = "1",
doi = "10.1111/ajt.14870",
language = "English",
journal = "American Journal of Transplantation",
issn = "1600-6135",
publisher = "Wiley-Blackwell",

}

TY - JOUR

T1 - Single nucleotide variant counts computed from RNA sequencing and cellular traffic into human kidney allografts

AU - Thareja, Gaurav

AU - Yang, Hua

AU - Hayat, Shahina

AU - Mueller, Franco B.

AU - Lee, John R.

AU - Lubetzky, Michelle

AU - Dadhania, Darshana M.

AU - Belkadi, Aziz

AU - Seshan, Surya V.

AU - Suhre, Karsten

AU - Suthanthiran, Manikkam

AU - Muthukumar, Thangamani

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Advances in bioinformatics allow identification of single nucleotide polymorphisms (variants) from RNA sequence data. In an allograft biopsy, 2 genomes contribute to the RNA pool, 1 from the donor organ and the other from the infiltrating recipient's cells. We hypothesize that imbalances in genetic variants of RNA sequence data of kidney allograft biopsies provide an objective measure of cellular infiltration of the allograft. We performed mRNA sequencing of 40 kidney allograft biopsies, selected to represent a comprehensive range of diagnostic categories. We analyzed the sequencing reads of these biopsies and of 462 lymphoblastoid cell lines from the 1000 Genomes Project, for RNA variants. The ratio of heterozygous to nonreference genome homozygous variants (Het/Hom ratio) on all autosomes was determined for each sample, and the estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) score was computed as a complementary estimate of the degree of cellular infiltration into biopsies. The Het/Hom ratios (P = .02) and the ESTIMATE scores (P < .001) were associated with the biopsy diagnosis. Both measures correlated significantly (r = .67, P < .0001), even though the Het/Hom ratio is based on mRNA sequence variation, while the ESTIMATE score uses mRNA expression. Het/Hom ratio and the ESTIMATE score may offer unbiased and quantitative parameters for characterizing cellular traffic into human kidney allografts.

AB - Advances in bioinformatics allow identification of single nucleotide polymorphisms (variants) from RNA sequence data. In an allograft biopsy, 2 genomes contribute to the RNA pool, 1 from the donor organ and the other from the infiltrating recipient's cells. We hypothesize that imbalances in genetic variants of RNA sequence data of kidney allograft biopsies provide an objective measure of cellular infiltration of the allograft. We performed mRNA sequencing of 40 kidney allograft biopsies, selected to represent a comprehensive range of diagnostic categories. We analyzed the sequencing reads of these biopsies and of 462 lymphoblastoid cell lines from the 1000 Genomes Project, for RNA variants. The ratio of heterozygous to nonreference genome homozygous variants (Het/Hom ratio) on all autosomes was determined for each sample, and the estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) score was computed as a complementary estimate of the degree of cellular infiltration into biopsies. The Het/Hom ratios (P = .02) and the ESTIMATE scores (P < .001) were associated with the biopsy diagnosis. Both measures correlated significantly (r = .67, P < .0001), even though the Het/Hom ratio is based on mRNA sequence variation, while the ESTIMATE score uses mRNA expression. Het/Hom ratio and the ESTIMATE score may offer unbiased and quantitative parameters for characterizing cellular traffic into human kidney allografts.

KW - Genomics

KW - Kidney transplantation/nephrology

KW - Molecular biology: mRNA/mRNA expression

KW - Monitoring: immune

KW - Translational research/science

UR - http://www.scopus.com/inward/record.url?scp=85047496794&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85047496794&partnerID=8YFLogxK

U2 - 10.1111/ajt.14870

DO - 10.1111/ajt.14870

M3 - Article

C2 - 29659169

AN - SCOPUS:85047496794

JO - American Journal of Transplantation

JF - American Journal of Transplantation

SN - 1600-6135

ER -