STAT6, PBX2, and PBRM1 Emerge as Predicted Regulators of 452 Differentially Expressed Genes Associated With Puberty in Brahman Heifers

Nguyen, Loan; Reverter, Antônio; Cánovas, Ángela; Venus, B.; Anderson, Stephen; Islas‐Trejo, Alma; Dias, Marina Mortati; Crawford, N. F.; Lehnert, S. A.; Medrano, Juan F.; Thomas, M. G.; Moore, S. S.; Fortes, M. R. S.

doi:10.3389/fgene.2018.00087

Cited by 31 publications

(26 citation statements)

References 129 publications

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“…Among these genes, STAT6 (signal transducer and activator of transcription 6, on BTA5) has been reported to have large effects on the growth efficiency and the quality of carcass in cattle [41]. Additionally, using co-expression network analysis, Nguyen et al [42]. reported the critical role of STAT6, PBX2 (PBX homeo-box2) and PBRM1 (Protein polybromo1) as transcription factors in regulating pubertal development in Brahman heifers.…”

Section: Discussionmentioning

confidence: 99%

Genomic measures of inbreeding coefficients and genome-wide scan for runs of homozygosity islands in Iranian river buffalo, Bubalus bubalis

et al. 2020

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Background: Consecutive homozygous fragments of a genome inherited by offspring from a common ancestor are known as runs of homozygosity (ROH). ROH can be used to calculate genomic inbreeding and to identify genomic regions that are potentially under historical selection pressure. The dataset of our study consisted of 254 Azeri (AZ) and 115 Khuzestani (KHZ) river buffalo genotyped for~65,000 SNPs for the following two purposes: 1) to estimate and compare inbreeding calculated using ROH (F ROH ), excess of homozygosity (F HOM ), correlation between uniting gametes (F UNI ), and diagonal elements of the genomic relationship matrix (F GRM ); 2) to identify frequently occurring ROH (i.e. ROH islands) for our selection signature and gene enrichment studies. Results: In this study, 9102 ROH were identified, with an average number of 21.2 ± 13.1 and 33.2 ± 15.9 segments per animal in AZ and KHZ breeds, respectively. On average in AZ, 4.35% (108.8 ± 120.3 Mb), and in KHZ, 5.96% (149.1 ± 107.7 Mb) of the genome was autozygous. The estimated inbreeding values based on F HOM , F UNI and F GRM were higher in AZ than they were in KHZ, which was in contrast to the F ROH estimates. We identified 11 ROH islands (four in AZ and seven in KHZ). In the KHZ breed, the genes located in ROH islands were enriched for multiple Gene Ontology (GO) terms (P ≤ 0.05). The genes located in ROH islands were associated with diverse biological functions and traits such as body size and muscle development (BMP2), immune response (CYP27B1), milk production and components (MARS, ADRA1A, and KCTD16), coat colour and pigmentation (PMEL and MYO1A), reproductive traits (INHBC, INHBE, STAT6 and PCNA), and bone development (SUOX). Conclusion: The calculated F ROH was in line with expected higher inbreeding in KHZ than in AZ because of the smaller effective population size of KHZ. Thus, we find that F ROH can be used as a robust estimate of genomic inbreeding. Further, the majority of ROH peaks were overlapped with or in close proximity to the previously reported genomic regions with signatures of selection. This tells us that it is likely that the genes in the ROH islands have been subject to artificial or natural selection.

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Section: Discussionmentioning

confidence: 99%

Genomic measures of inbreeding coefficients and genome-wide scan for runs of homozygosity islands in Iranian river buffalo, Bubalus bubalis

et al. 2020

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“…; Nguyen et al . , ). Together, the evidence suggests a major role for ZNF genes inducing puberty in Brahman heifers and other mammals.…”

Section: Discussionmentioning

confidence: 99%

Pre‐ and post‐puberty expression of genes and proteins in the uterus of Bos indicus heifers: the luteal phase effect post‐puberty

et al. 2018

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Progesterone signaling and uterine function are crucial in terms of pregnancy establishment. To investigate how the uterine tissue and its secretion changes in relation to puberty, we sampled tissue and uterine fluid from six pre- and six post-pubertal Brahman heifers. Post-pubertal heifers were sampled in the luteal phase. Gene expression of the uterine tissue was investigated with RNA-sequencing, whereas the uterine fluid was used for protein profiling with mass spectrometry. A total of 4034 genes were differentially expressed (DE) at a nominal P-value of 0.05, and 26 genes were significantly DE after Bonferroni correction (P < 3.1 × 10 ). We also identified 79 proteins (out of 230 proteins) that were DE (P < 1 × 10 ) in the uterine fluid. When we compared proteomics and transcriptome results, four DE proteins were identified as being encoded by DE genes: OVGP1, GRP, CAP1 and HBA. Except for CAP1, the other three had lower expression post-puberty. The function of these four genes hypothetically related to preparation of the uterus for a potential pregnancy is discussed in the context of puberty. All DE genes and proteins were also used in pathway and ontology enrichment analyses to investigate overall function. The DE genes were enriched for terms related to ribosomal activity. Transcription factors that were deemed key regulators of DE genes are also reported. Transcription factors ZNF567, ZNF775, RELA, PIAS2, LHX4, SOX2, MEF2C, ZNF354C, HMG20A, TCF7L2, ZNF420, HIC1, GTF3A and two novel genes had the highest regulatory impact factor scores. These data can help to understand how puberty influences uterine function.

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“…It is comprised of five tissues (hypothalamus, pituitary, ovary, uterus and liver) from 6 pre- and 6 post-pubertal Brahman ( Bos indicus ) heifers, totalizing 60 samples. More details about animal management and data generation can be found in Fortes et al (2016), Nguyen et al (2017), Fortes et al (2018) and Nguyen et al (2018). In short, libraries were paired-end sequenced using an Illumina HiSeq200 equipment and reads were aligned to the bovine reference genome (UMD3.1).…”

Section: Methodsmentioning

confidence: 99%

Genome-wide co-expression distributions as a metric to prioritize genes of functional importance

Hudson¹,

Lehnert

Fortes

et al. 2020

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Genome-wide gene expression is routinely used as a tool to gain a systems-level understanding of complex, biological processes. Numerical approaches that have been used to highlight influential genes include abundance, differential expression, differential variation, network connectivity and differential connectivity. Network connectivity tends to be built on a small subset of extremely high co-expression signals that are deemed significant, but this overlooks the vast majority of pairwise signals. Here, we aimed to assess a complementary strategy, namely whether the entire shape of the distribution of genome-wide co-expression values contains a meaningful biological signal that has hitherto remained hidden from view. We have developed a computational pipeline to assign one of 8 distributions (including normal, skewed, bimodal, kurtotic, inverted) to every gene. We then used a hypergeometric enrichment process to determine if particular genes (regulators versus non-regulators) and properties (differentially expressed or not) tend to be associated with particular distributions greater than would be expected by chance. Examination of several distinct data sets spanning 4 species indicates that there is indeed an additional biological signal present in the genome-wide distribution of co-expression values which would be overlooked by currently adopted approaches.Author summaryHigh-throughput technologies, such as RNA-Seq, enables access to a vast amount of data. Here, we describe a new approach to interrogate these data and extract further information to help researchers to understand complex phenotypes. Our method is based on gene-level co-expression distributions which were compared to eight possible template shapes to group genes with similar behaviours. The method was tested using five different datasets and the consistency of the results indicate it can be used as a complementary strategy to analyse transcriptomic data.

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STAT6, PBX2, and PBRM1 Emerge as Predicted Regulators of 452 Differentially Expressed Genes Associated With Puberty in Brahman Heifers

Cited by 31 publications

References 129 publications

Genomic measures of inbreeding coefficients and genome-wide scan for runs of homozygosity islands in Iranian river buffalo, Bubalus bubalis

Genomic measures of inbreeding coefficients and genome-wide scan for runs of homozygosity islands in Iranian river buffalo, Bubalus bubalis

Pre‐ and post‐puberty expression of genes and proteins in the uterus of Bos indicus heifers: the luteal phase effect post‐puberty

Genome-wide co-expression distributions as a metric to prioritize genes of functional importance

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