Expression of mitochondrial protein genes encoded by nuclear and mitochondrial genomes correlate with energy metabolism in dairy cattle

Dorji, Jigme; Jagt, Christy J. Vander; Garner, Josie B.; Marett, L. C.; Mason, Brett; Reich, Coralie M.; Xiang, Ruidong; Clark, Emily L.; Cocks, Benjamin G.; Chamberlain, Amanda J.; MacLeod, Iona M.; Daetwyler, Hans D.

doi:10.1186/s12864-020-07018-7

Cited by 20 publications

(22 citation statements)

References 77 publications

(91 reference statements)

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“…Tissue from liver, lung, mammary gland, kidney, heart, and spleen from three lactating Holstein dairy cows were sampled after euthanasia ( Chamberlain et al, 2015 ; Dorji et al, 2020 ). Ethics approval for the euthanasia and sampling of two of the cows were obtained from Department of Jobs, Precincts and Regions Ethics Committee (Application No.…”

Section: Methodsmentioning

confidence: 99%

“…RNA extraction and sequencing on the same six tissues in the three cows was as described in Chamberlain et al (2015) and Dorji et al (2020) .…”

Section: Methodsmentioning

confidence: 99%

“…Counts for each set of consensus peaks (described above) were calculated with DiffBind ( Stark and Brown, 2011 ) and normalised using Trimmed Mean of M-values (TMM) and full library size. Normalised RNA-seq counts for each gene were used from Chamberlain et al (2015) and Dorji et al (2020) . Correlations were calculated using corr.test in R.…”

Section: Methodsmentioning

confidence: 99%

“…The promoter region was characterised as 2kb upstream of the TSS and proximal regions as 8 kb upstream from the promoter start site. Normalised read counts from RNA-seq data ( Chamberlain et al, 2015 ; Dorji et al, 2020 ) were used to define genes, and their associated promoters and proximal regions, as active or inactive. Active genes were defined when all animals had a count over 200 in that tissue and for inactive genes all animals had a count less than 10 in that tissue.…”

Section: Methodsmentioning

confidence: 99%

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Putative Causal Variants Are Enriched in Annotated Functional Regions From Six Bovine Tissues

et al. 2021

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Genetic variants which affect complex traits (causal variants) are thought to be found in functional regions of the genome. Identifying causal variants would be useful for predicting complex trait phenotypes in dairy cows, however, functional regions are poorly annotated in the bovine genome. Functional regions can be identified on a genome-wide scale by assaying for post-translational modifications to histone proteins (histone modifications) and proteins interacting with the genome (e.g., transcription factors) using a method called Chromatin immunoprecipitation followed by sequencing (ChIP-seq). In this study ChIP-seq was performed to find functional regions in the bovine genome by assaying for four histone modifications (H3K4Me1, H3K4Me3, H3K27ac, and H3K27Me3) and one transcription factor (CTCF) in 6 tissues (heart, kidney, liver, lung, mammary and spleen) from 2 to 3 lactating dairy cows. Eighty-six ChIP-seq samples were generated in this study, identifying millions of functional regions in the bovine genome. Combinations of histone modifications and CTCF were found using ChromHMM and annotated by comparing with active and inactive genes across the genome. Functional marks differed between tissues highlighting areas which might be particularly important to tissue-specific regulation. Supporting the cis-regulatory role of functional regions, the read counts in some ChIP peaks correlated with nearby gene expression. The functional regions identified in this study were enriched for putative causal variants as seen in other species. Interestingly, regions which correlated with gene expression were particularly enriched for potential causal variants. This supports the hypothesis that complex traits are regulated by variants that alter gene expression. This study provides one of the largest ChIP-seq annotation resources in cattle including, for the first time, in the mammary gland of lactating cows. By linking regulatory regions to expression QTL and trait QTL we demonstrate a new strategy for identifying causal variants in cattle.

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Section: Methodsmentioning

confidence: 99%

“…RNA extraction and sequencing on the same six tissues in the three cows was as described in Chamberlain et al (2015) and Dorji et al (2020) .…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Putative Causal Variants Are Enriched in Annotated Functional Regions From Six Bovine Tissues

et al. 2021

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“…Following the eumelanin shell model that hollow melanosomes form through selective loss of pheomelanin in their core (Shawkey et al 2015), and the likely presence of pheomelanin in non-iridescent but not iridescent feathers, we predict a greater expression of eumelanin-than pheomelanin-related genes in iridescent blue versus non-iridescent red feathers. Following the depletion-attraction hypothesis (Maia et al 2012), we predict that iridescent blue feathers will show enhanced expression of keratin-and melanin-production genes, but similar or reduced expression of genes associated with metabolism (since genes related to metabolic function are often upregulated in tissues with high energy demands; Dorji et al 2020) and with structural components S3 for corresponding data from non-iridescent red feathers). The top spectrum is a eumelanin standard and the bottom spectra are samples.…”

mentioning

confidence: 98%

Feather Gene Expression Elucidates the Developmental Basis of Plumage Iridescence in African Starlings

Rubenstein

Corvelo

MacManes

et al. 2021

Journal of Heredity

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Iridescence is widespread in the living world, occurring in organisms as diverse as bacteria, plants, and animals. Yet, compared to pigment-based forms of coloration, we know surprisingly little about the developmental and molecular bases of the structural colors that give rise to iridescence. Birds display a rich diversity of iridescent structural colors that are produced in feathers by the arrangement of melanin-containing organelles called melanosomes into nanoscale configurations, but how these often unusually shaped melanosomes form, or how they are arranged into highly organized nanostructures, remains largely unknown. Here, we use functional genomics to explore the developmental basis of iridescent plumage using superb starlings (Lamprotornis superbus), which produce both iridescent blue and non-iridescent red feathers. Through morphological and chemical analyses, we confirm that hollow, flattened melanosomes in iridescent feathers are eumelanin-based, whereas melanosomes in non-iridescent feathers are solid and amorphous, suggesting that high pheomelanin content underlies red coloration. Intriguingly, the nanoscale arrangement of melanosomes within the barbules was surprisingly similar between feather types. After creating a new genome assembly, we use transcriptomics to show that non-iridescent feather development is associated with genes related to pigmentation, metabolism, and mitochondrial function, suggesting non-iridescent feathers are more energetically expensive to produce than iridescent feathers. However, iridescent feather development is associated with genes related to structural and cellular organization, suggesting that, while nanostructures themselves may passively assemble, barbules and melanosomes may require active organization to give them their shape. Together, our analyses suggest that iridescent feathers form through a combination of passive self-assembly and active processes.

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AgAnimalGenomes: browsers for viewing and manually annotating farm animal genomes

Triant,

Walsh,

Hartley

et al. 2023

Mamm Genome

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Current genome sequencing technologies have made it possible to generate highly contiguous genome assemblies for non-model animal species. Despite advances in genome assembly methods, there is still room for improvement in the delineation of specific gene features in the genomes. Here we present genome visualization and annotation tools to support seven livestock species (bovine, chicken, goat, horse, pig, sheep, and water buffalo), available in a new resource called AgAnimalGenomes. In addition to supporting the manual refinement of gene models, these browsers provide visualization tracks for hundreds of RNAseq experiments, as well as data generated by the Functional Annotation of Animal Genomes (FAANG) Consortium. For species with predicted gene sets from both Ensembl and RefSeq, the browsers provide special tracks showing the thousands of protein-coding genes that disagree across the two gene sources, serving as a valuable resource to alert researchers to gene model issues that may affect data interpretation. We describe the data and search methods available in the new genome browsers and how to use the provided tools to edit and create new gene models.

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Expression of mitochondrial protein genes encoded by nuclear and mitochondrial genomes correlate with energy metabolism in dairy cattle

Cited by 20 publications

References 77 publications

Putative Causal Variants Are Enriched in Annotated Functional Regions From Six Bovine Tissues

Putative Causal Variants Are Enriched in Annotated Functional Regions From Six Bovine Tissues

Feather Gene Expression Elucidates the Developmental Basis of Plumage Iridescence in African Starlings

AgAnimalGenomes: browsers for viewing and manually annotating farm animal genomes

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