Evidence map›Paper›PMID 40240916›Full record

ArticleBMC genomics2025

Optimizing Cost-Effective gene expression phenotyping approaches in cattle using 3' mRNA sequencing.

Ruwaa I Mohamed, Taylor B Ault-Seay, Sonia J Moisá, Jonathan E Beever, Agustín G Ríus, Troy N Rowan

Abstract read
In one paragraph

Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ruwaa I MohamedGenome Science and Technology Program, Bredesen Center, University of Tennessee, Knoxville, TN, USA.
Taylor B Ault-SeayDepartment of Animal Science, University of Tennessee Institute of Agriculture (UTIA), Knoxville, TN, USA.
Sonia J MoisáDepartment of Animal Science, University of Tennessee Institute of Agriculture (UTIA), Knoxville, TN, USA.
Jonathan E BeeverGenome Science and Technology Program, Bredesen Center, University of Tennessee, Knoxville, TN, USA.
Agustín G RíusDepartment of Animal Science, University of Tennessee Institute of Agriculture (UTIA), Knoxville, TN, USA.
Troy N RowanGenome Science and Technology Program, Bredesen Center, University of Tennessee, Knoxville, TN, USA. trowan@utk.edu.

Funding

FFAR 22-000087National Institute of Food and Agriculture 2020-70412-32615, 2021-70412-35233
6 · The paper itself

Abstract

backgroundGenetic and genomic selection programs require large numbers of phenotypes observed for animals in shared environments. Direct measurements of phenotypes like meat quality, methane emission, and disease susceptibility are difficult and expensive to measure at scale but are critically important to livestock production. Our work leans on our understanding of the "Central Dogma" of molecular genetics to leverage molecular intermediates as cheaply-measured proxies of organism-level phenotypes. The rapidly declining cost of next-generation sequencing presents opportunities for population-level molecular phenotyping. While the cost of whole transcriptome sequencing has declined recently, its required sequencing depth still makes it an expensive choice for wide-scale molecular phenotyping. We aim to optimize 3' mRNA sequencing (3' mRNA-Seq) approaches for collecting cost-effective proxy molecular phenotypes for cattle from easy-to-collect tissue samples (i.e., whole blood). We used matched 3' mRNA-Seq samples for 15 Holstein male calves in a heat stress trail to identify the (1) best library preparation kit (Takara SMART-Seq v4 3' DE and Lexogen QuantSeq) and (2) optimal sequencing depth (0.5 to 20 million reads/sample) to capture gene expression phenotypes most cost-effectively.

resultsTakara SMART-Seq v4 3' DE outperformed Lexogen QuantSeq libraries across all metrics: number of quality reads, expressed genes, informative genes, differentially expressed genes, and 3' biased intragenic variants. Serial downsampling analyses identified that as few as 8.0 million reads per sample could effectively capture most of the between-sample variation in gene expression. However, progressively more reads did provide marginal increases in recall across metrics. These 3' mRNA-Seq reads can also capture animal genotypes that could be used as the basis for downstream imputation. The 10 million read downsampled groups called an average of 109,700 SNPs and 11,367 INDELs, many of which segregate at moderate minor allele frequencies in the population.

conclusionThis work demonstrates that 3' mRNA-Seq with Takara SMART-Seq v4 3' DE can provide an incredibly cost-effective (< 25 USD/sample) approach to quantifying molecular phenotypes (gene expression) while discovering sufficient variation for use in genotype imputation. Ongoing work is evaluating the accuracy of imputation and the ability of much larger datasets to predict individual animal phenotypes.

Indexed as

Gene Expression ProfilingRNA, MessengerSequence Analysis, RNAAnimalsCattleCost-Benefit AnalysisHigh-Throughput Nucleotide SequencingMalePhenotypePolymorphism, Single NucleotideTranscriptomeRNA, MessengerGene expressionHigh-throughputLivestockMolecular phenotypingTranscriptomics

Identifiers

PMID40240916
PMCPMC12001630

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.