Repurposing Shotgun Metagenomic Human Host Reads for Mitochondrial Heteroplasmy Detection
- 1CSIR-NEERI
Abstract
BackgroundShotgun metagenomic pipelines routinely discard host-derived reads, which can exceed 90% of reads in low-biomass clinical samples. Whether these reads support mitochondrial heteroplasmy detection, and at what allele fraction, has not been established.
MethodsShotgun metagenomic data from 47 upper respiratory tract swabs from healthy adults in Nagpur, India, were analysed. Human Reads were recruited against the rCRS and realigned competitively to GRCh38 to remove nuclear mitochondrial segments (NUMTs). Kraken2 was used as a microbial control. Heteroplasmy was called against a pooled, substitution-specific beta-binomial error model and a leave-one-out panel of normals. The detection limit was evaluated from the substitution spectrum against gnomAD v3.1.
ResultsComplete mitochondrial genomes were recovered from all samples (mean depth 433x, range 9-3,029x). Competitive realignment relocated 3.22% of recruited reads to nuclear loci; microbial cross-mapping removed 0.045%. Error rates varied 12.8-fold across substitution classes, with T>A being the highest. The 134 calls had a Ti/Tv of 0.43, compared with 3.51 in gnomAD, and T>A accounted for 42.5% of calls. T>A allele fractions never exceeded 4.72%, whereas transitions reached 90.81%. At a 5% threshold, T>A calls disappeared, and Ti/Tv rose to 2.20 before plateauing; 16 calls exceeded this limit. Macrohaplogroups were assigned in 46 of 47 samples (M 22, R 23, N 1).
ConclusionsMetagenomic host reads support complete mitochondrial recovery, haplogroup typing, and heteroplasmy detection at an allele fraction[≥]5%. Below this, a T>A-dominated error process persists after NUMT removal that background-fitted models do not capture.
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BibTeX
@misc{tomar2026repurposing,
title = {{Repurposing Shotgun Metagenomic Human Host Reads for Mitochondrial Heteroplasmy Detection}},
author = {S. S. Tomar and K. Khairnar},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.05.26364752},
url = {https://www.medrxiv.org/content/10.64898/2026.10.05.26364752v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Repurposing Shotgun Metagenomic Human Host Reads for Mitochondrial Heteroplasmy Detection
AU - S. S. Tomar
AU - K. Khairnar
PY - 2026
DA - 2026/10/05
PB - medRxiv
DO - 10.64898/2026.10.05.26364752
UR - https://www.medrxiv.org/content/10.64898/2026.10.05.26364752v1
AB - BackgroundShotgun metagenomic pipelines routinely discard host-derived reads, which can exceed 90% of reads in low-biomass clinical samples. Whether these reads support mitochondrial heteroplasmy detection, and at what allele fraction, has not been established. MethodsShotgun metagenomic data from 47 upper respiratory tract swabs from healthy adults in Nagpur, India, were analysed. Human Reads were recruited against the rCRS and realigned competitively to GRCh38 to remove nuclear mitochondrial segments (NUMTs). Kraken2 was used as a microbial control. Heteroplasmy was called against a pooled, substitution-specific beta-binomial error model and a leave-one-out panel of normals. The detection limit was evaluated from the substitution spectrum against gnomAD v3.1. ResultsComplete mitochondrial genomes were recovered from all samples (mean depth 433x, range 9-3,029x). Competitive realignment relocated 3.22% of recruited reads to nuclear loci; microbial cross-mapping removed 0.045%. Error rates varied 12.8-fold across substitution classes, with T>A being the highest. The 134 calls had a Ti/Tv of 0.43, compared with 3.51 in gnomAD, and T>A accounted for 42.5% of calls. T>A allele fractions never exceeded 4.72%, whereas transitions reached 90.81%. At a 5% threshold, T>A calls disappeared, and Ti/Tv rose to 2.20 before plateauing; 16 calls exceeded this limit. Macrohaplogroups were assigned in 46 of 47 samples (M 22, R 23, N 1). ConclusionsMetagenomic host reads support complete mitochondrial recovery, haplogroup typing, and heteroplasmy detection at an allele fraction[≥]5%. Below this, a T>A-dominated error process persists after NUMT removal that background-fitted models do not capture.
ER -