Information compression exploits patterns of genome composition to discriminate populations and highlight regions of evolutionary interest

Hudson, Nicholas J.; Porto-Neto, Laércio R.; Kijas, James W.; McWilliam, Sean; Taft, Ryan J.; Reverter, Antônio

doi:10.1186/1471-2105-15-66

Cited by 14 publications

(21 citation statements)

References 77 publications

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“…Reads were subsampled with probability 0.5, 0.25, 0.1, 0.05, 0.01, 0.005, 0.002 or 0.001; representing sequencing 2, 4, 10, 20, 100, 200, 500 or 1000 times the number of samples per lane, respectively. The set of sampled reads at a given simulated sequencing depth were then used to calculate repeatability, as above, or compression efficiency (29). Compression efficiency compares the size of a compressed file to its original size as (original – compressed)/original and is a measure of the non-redundant information present in the file.…”

Section: Methodsmentioning

confidence: 99%

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

Hess

Rowe

Stijn

et al. 2019

Preprint

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AbstractMicrobial community profiles have been associated with a variety of traits, including methane emissions in livestock, however, these profiles can be difficult and expensive to obtain for thousands of samples. The objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n=236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to sequencing. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of host genetics, laboratory and analytical method, and the genetic and phenotypic correlations with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach via a correspondence analysis, with estimates for repeatability of 0.62±0.06, heritability 0.31±0.29, and genetic and phenotypic correlation with methane emissions of 0.88±0.25 and 0.64±0.05 respectively for the first component of correspondence analysis. The reference-free approach assigned 62.0±5.7% of reads to common 65 bp tags, much higher than the reference-based approach of 6.8±1.8% of reads assigned. Sensitivity studies suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, therefore the current work of 118 samples/lane and future proposed 384 samples/lane are well within that threshold. Our approach is now being used to investigate host factors affecting the rumen and its association with a variety of production and environmental traits. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

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Section: Methodsmentioning

confidence: 99%

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

Hess

Rowe

Stijn

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Reads were subsampled with probability 0.5, 0.25, 0.1, 0.05, 0.01, 0.005, 0.002 or 0.001 using the sample function in R; representing sequencing 2, 4, 10, 20, 100, 200, 500 or 1000 times the number of samples per lane, respectively. The set of sampled reads at a given simulated sequencing depth were then used to calculate compression efficiency [31]. Compression efficiency compares the size of a compressed file to its original size as (originalcompressed)/original and is a measure of the non-redundant information present in the file.…”

Section: Sensitivity To Sequencing Depthmentioning

confidence: 99%

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

et al. 2020

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Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock. These profiles can be difficult and expensive to obtain for thousands of samples (e.g. for accurate association of microbial profiles with traits), therefore the objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (referencebased and reference-free) were compared to bacterial 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n = 236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to RE-RRS. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of laboratory and analytical method, and the relationship with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach, which accounted for 53.3±5.9% of reads, and had repeatabilities of 0.49±0.07 and 0.50±0.07 for the first two principal components (PC1 and PC2), phenotypic correlations with methane yield of 0.43±0.06 and 0.46±0.06 for PC1 and PC2, and explained 41±8% of the variation in methane yield. These results were significantly better than for bacterial 16S rRNA gene sequencing of the same samples (p<0.05) except for the correlation between PC2 and methane yield. A Sensitivity study suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, meaning the current work using 118 samples/lane and future proposed 384 samples/lane are well within that threshold. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

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“…In current study, selection signatures were identified near several known color genes, including KITLG (near SNP BTA-74300-no-rs on BTA5) 38,54 , and LEF1 32,55 (here indicated by a peak in the XtX GWAS on BTA6). These genes and another candidate gene MCM6 (near ARS-BFGL-NGS-92772 on BTA2, also identified by Hudson et al 50 ) overlap with pigmentation QTL regions underlying UV-protection 56 . The environmental PC1 signal near IGFBP7 and the combined XtX-morphological signal near ADRA1D (Table 2) are close to the coat color genes KIT 56,57 and ATRN 56,58 , respectively.…”

Section: Discussionmentioning

confidence: 57%

“…In other studies, strong signals of selection in tropical cattle have been detected on BTA5 32,34,49,50 . Notably, Porto-Neto et al identified a 20 Mb region on BTA5 with effects on parasite resistance, yearling weight, body condition score, coat color and penile sheath score 32 .…”

Section: Discussionmentioning

confidence: 77%

Species composition and environmental adaptation of indigenous Chinese cattle

Gao

Gautier

Ding

et al. 2017

Preprint

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9Indigenous Chinese cattle combine taurine and indicine origins and occupy a broad range of 3 0 different environments. By 50K SNP genotyping we found a discontinuous distribution of taurine 3 1 and indicine cattle ancestries with extremes of less than 10% indicine cattle in the north and more 3 2 than 90% in the far south and southwest China. Model-based clustering and f4-statistics indicate 3 3 introgression of both banteng and gayal into southern Chinese cattle while the sporadic yak 3 4 influence in cattle in or near Tibetan area validate earlier findings of mitochondrial DNA analysis. 3 5

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Information compression exploits patterns of genome composition to discriminate populations and highlight regions of evolutionary interest

Cited by 14 publications

References 77 publications

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

Species composition and environmental adaptation of indigenous Chinese cattle

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