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Qiao J, Li K, Miao N, Xu F, Han P, Dai X, Abdelkarim OF, Zhu M, Zhao Y. Additive and Dominance Genome-Wide Association Studies Reveal the Genetic Basis of Heterosis Related to Growth Traits of Duhua Hybrid Pigs. Animals (Basel) 2024; 14:1944. [PMID: 38998055 PMCID: PMC11240614 DOI: 10.3390/ani14131944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 06/26/2024] [Accepted: 06/28/2024] [Indexed: 07/14/2024] Open
Abstract
Heterosis has been extensively used for pig genetic breeding and production, but the genetic basis of heterosis remains largely elusive. Crossbreeding between commercial and native breeds provides a good model to parse the genetic basis of heterosis. This study uses Duhua hybrid pigs, a crossbreed of Duroc and Liangguang small spotted pigs, as materials to explore the genetic basis underlying heterosis related to growth traits at the genomic level. The mid-parent heterosis (MPH) analysis showed heterosis of this Duhua offspring on growth traits. In this study, we examined the impact of additive and dominance effects on 100 AGE (age adjusted to 100 kg) and 100 BF (backfat thickness adjusted to 100 kg) of Duhua hybrid pigs. Meanwhile, we successfully identified SNPs associated with growth traits through both additive and dominance GWASs (genome-wide association studies). These findings will facilitate the subsequent in-depth studies of heterosis in the growth traits of Duhua pigs.
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Affiliation(s)
- Jiakun Qiao
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Kebiao Li
- School of Life Science and Engineering, Foshan University, Foshan 528000, China
| | - Na Miao
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Fangjun Xu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Pingping Han
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiangyu Dai
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Omnia Fathy Abdelkarim
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Mengjin Zhu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan 430070, China
| | - Yunxiang Zhao
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
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Liberty IA, Septadina IS, Mariana, Novita E, Amalia R, Ananingsih ES, Hasyim H, Hanifah L. The characteristics and risk of obesity central and concomitant impaired fasting glucose: Findings from a cross-sectional study. PLoS One 2024; 19:e0305604. [PMID: 38917085 PMCID: PMC11198825 DOI: 10.1371/journal.pone.0305604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 06/03/2024] [Indexed: 06/27/2024] Open
Abstract
INTRODUCTION Obesity is associated with concomitant chronic conditions. An early metabolic consequence of obesity is disruption of glucose and insulin homeostasis. One of the consequences is impaired fasting glucose (IFG). Visceral fat is metabolically more harmful than subcutaneous fat, but few information is available regarding the association between the risk of abnormal glucose in increased waist circumference. METHODS This study is based on a cross sectional of 1,381 population-based from Palembang, Indonesia. The eligibility requirements subject were to be older than 18 and consent to taking fasting glucose and lipid profile tests as well as physical exams measuring their body weight, height, blood pressure, abdominal circumference, and waist circumference. RESULTS The number of subjects consisting of 798 noncentral obesity with normoglycemia, 376 central obesity with normoglycemia, and 207 central obesity with concomitant IFG. The prevalence central obesity with concomitant IFG was 35.51%. In subjects with central obesity, there were significant differences in proportions based on sex, age, marital status, education, and occupation. In multivariate analysis show that the risk factors that contribute to having a significant association with central obesity with concomitant IFG are sex (female), age (>40 years), blood pressure (hypertension), and HDL-C <50 mg/dL (p<0.001). The analysis also founded that there was a significant difference in the dietary pattern of sweet foods (p = 0.018), sweet drinks (p = 0.002), soft drinks (p = 0.001) and smoking habit (p<0.001) between subjects with obesity central and concomitant IFG compared to subjects with noncentral obesity. The majority of subjects with obesity central and concomitant IFG had consuming these risky foods >6 times/week. CONCLUSION The prevalence of central obesity with IFG is quite high. There are significant differences in the characteristics, lipid profile, blood pressure, dietary pattern, and smoking habit of central obesity with concomitant IFG was confirmed in this population-based observational study.
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Affiliation(s)
- Iche Andriyani Liberty
- Department of Public Health and Community Medicine, Faculty of Medicine, Universitas Sriwijaya, Palembang, Indonesia
| | - Indri Seta Septadina
- Department of Anatomy, Faculty of Medicine, Universitas Sriwijaya, Palembang, Indonesia
| | - Mariana
- Department of Public Health and Community Medicine, Faculty of Medicine, Universitas Sriwijaya, Palembang, Indonesia
| | - Emma Novita
- Department of Anatomy, Faculty of Medicine, Universitas Sriwijaya, Palembang, Indonesia
| | - Resi Amalia
- Faculty of Medicine, Universitas Muhammadiyah, Palembang, Indonesia
| | | | - Hamzah Hasyim
- Faculty of Public Health, Universitas Sriwijaya, Palembang, Indonesia
| | - Laily Hanifah
- Universitas Pembangunan Nasional Veteran Jakarta, Jakarta, Indonesia
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Pan DZ, Miao Z, Comenho C, Rajkumar S, Koka A, Lee SHT, Alvarez M, Kaminska D, Ko A, Sinsheimer JS, Mohlke KL, Mancuso N, Muñoz-Hernandez LL, Herrera-Hernandez M, Tusié-Luna MT, Aguilar-Salinas C, Pietiläinen KH, Pihlajamäki J, Laakso M, Garske KM, Pajukanta P. Identification of TBX15 as an adipose master trans regulator of abdominal obesity genes. Genome Med 2021; 13:123. [PMID: 34340684 PMCID: PMC8327600 DOI: 10.1186/s13073-021-00939-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 07/14/2021] [Indexed: 12/14/2022] Open
Abstract
Background Obesity predisposes individuals to multiple cardiometabolic disorders, including type 2 diabetes (T2D). As body mass index (BMI) cannot reliably differentiate fat from lean mass, the metabolically detrimental abdominal obesity has been estimated using waist-hip ratio (WHR). Waist-hip ratio adjusted for body mass index (WHRadjBMI) in turn is a well-established sex-specific marker for abdominal fat and adiposity, and a predictor of adverse metabolic outcomes, such as T2D. However, the underlying genes and regulatory mechanisms orchestrating the sex differences in obesity and body fat distribution in humans are not well understood. Methods We searched for genetic master regulators of WHRadjBMI by employing integrative genomics approaches on human subcutaneous adipose RNA sequencing (RNA-seq) data (n ~ 1400) and WHRadjBMI GWAS data (n ~ 700,000) from the WHRadjBMI GWAS cohorts and the UK Biobank (UKB), using co-expression network, transcriptome-wide association study (TWAS), and polygenic risk score (PRS) approaches. Finally, we functionally verified our genomic results using gene knockdown experiments in a human primary cell type that is critical for adipose tissue function. Results Here, we identified an adipose gene co-expression network that contains 35 obesity GWAS genes and explains a significant amount of polygenic risk for abdominal obesity and T2D in the UKB (n = 392,551) in a sex-dependent way. We showed that this network is preserved in the adipose tissue data from the Finnish Kuopio Obesity Study and Mexican Obesity Study. The network is controlled by a novel adipose master transcription factor (TF), TBX15, a WHRadjBMI GWAS gene that regulates the network in trans. Knockdown of TBX15 in human primary preadipocytes resulted in changes in expression of 130 network genes, including the key adipose TFs, PPARG and KLF15, which were significantly impacted (FDR < 0.05), thus functionally verifying the trans regulatory effect of TBX15 on the WHRadjBMI co-expression network. Conclusions Our study discovers a novel key function for the TBX15 TF in trans regulating an adipose co-expression network of 347 adipose, mitochondrial, and metabolically important genes, including PPARG, KLF15, PPARA, ADIPOQ, and 35 obesity GWAS genes. Thus, based on our converging genomic, transcriptional, and functional evidence, we interpret the role of TBX15 to be a main transcriptional regulator in the adipose tissue and discover its importance in human abdominal obesity. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-021-00939-2.
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Affiliation(s)
- David Z Pan
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Bioinformatics Interdepartmental Program, UCLA, Los Angeles, USA
| | - Zong Miao
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Bioinformatics Interdepartmental Program, UCLA, Los Angeles, USA
| | - Caroline Comenho
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Sandhya Rajkumar
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Computational and Systems Biology Interdepartmental Program, UCLA, Los Angeles, USA
| | - Amogha Koka
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Seung Hyuk T Lee
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Marcus Alvarez
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Dorota Kaminska
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Arthur Ko
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Janet S Sinsheimer
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA.,Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Preventative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, USA
| | - Linda Liliana Muñoz-Hernandez
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Ave. Morones Prieto 3000, Monterrey, N.L., México, 64710.,Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.,Departamento de Endocrinología y Metabolismo del Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Miguel Herrera-Hernandez
- Departamento de Cirugía, Instituto Nacional de Ciencias Médicas y Nutrición, Mexico City, Mexico
| | - Maria Teresa Tusié-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto de Investigaciones Biomédicas UNAM/ Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Carlos Aguilar-Salinas
- Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.,Departamento de Endocrinología y Metabolismo del Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Obesity Center, Endocrinology, Abdominal Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Jussi Pihlajamäki
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.,Department of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kristina M Garske
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Päivi Pajukanta
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA. .,Bioinformatics Interdepartmental Program, UCLA, Los Angeles, USA. .,Institute for Precision Health at UCLA, Los Angeles, USA.
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tRNA Biology in the Pathogenesis of Diabetes: Role of Genetic and Environmental Factors. Int J Mol Sci 2021; 22:ijms22020496. [PMID: 33419045 PMCID: PMC7825315 DOI: 10.3390/ijms22020496] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 01/02/2021] [Accepted: 01/03/2021] [Indexed: 02/07/2023] Open
Abstract
The global rise in type 2 diabetes results from a combination of genetic predisposition with environmental assaults that negatively affect insulin action in peripheral tissues and impair pancreatic β-cell function and survival. Nongenetic heritability of metabolic traits may be an important contributor to the diabetes epidemic. Transfer RNAs (tRNAs) are noncoding RNA molecules that play a crucial role in protein synthesis. tRNAs also have noncanonical functions through which they control a variety of biological processes. Genetic and environmental effects on tRNAs have emerged as novel contributors to the pathogenesis of diabetes. Indeed, altered tRNA aminoacylation, modification, and fragmentation are associated with β-cell failure, obesity, and insulin resistance. Moreover, diet-induced tRNA fragments have been linked with intergenerational inheritance of metabolic traits. Here, we provide a comprehensive review of how perturbations in tRNA biology play a role in the pathogenesis of monogenic and type 2 diabetes.
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Shi L, Wang L, Liu J, Deng T, Yan H, Zhang L, Liu X, Gao H, Hou X, Wang L, Zhao F. Estimation of inbreeding and identification of regions under heavy selection based on runs of homozygosity in a Large White pig population. J Anim Sci Biotechnol 2020; 11:46. [PMID: 32355558 PMCID: PMC7187514 DOI: 10.1186/s40104-020-00447-0] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 03/12/2020] [Indexed: 01/24/2023] Open
Abstract
Background Runs of homozygosity (ROHs) are homozygous segments of the genome where the two haplotypes inherited from the parents are identical. The current availability of genotypes for a very large number of single nucleotide polymorphisms (SNPs) is leading to more accurate characterization of ROHs in the whole genome. Here, we investigated the occurrence and distribution of ROHs in 3,692 Large White pigs and compared estimates of inbreeding coefficients calculated based on ROHs (FROH), homozygosity (FHOM), genomic relationship matrix (FGRM) and pedigree (FPED). Furthermore, we identified genomic regions with high ROH frequencies and annotated their candidate genes. Results In total, 176,182 ROHs were identified from 3,569 animals, and all individuals displayed at least one ROH longer than 1 Mb. The ROHs identified were unevenly distributed on the autosomes. The highest and lowest coverages of Sus scrofa chromosomes (SSC) by ROH were on SSC14 and SSC13, respectively. The highest pairwise correlation among the different inbreeding coefficient estimates was 0.95 between FROH_total and FHOM, while the lowest was − 0.083 between FGRM and FPED. The correlations between FPED and FROH using four classes of ROH lengths ranged from 0.18 to 0.37 and increased with increasing ROH length, except for ROH > 10 Mb. Twelve ROH islands were located on four chromosomes (SSC1, 4, 6 and 14). These ROH islands harboured genes associated with reproduction, muscular development, fat deposition and adaptation, such as SIRT1, MYPN, SETDB1 and PSMD4. Conclusion FROH can be used to accurately assess individual inbreeding levels compared to other inbreeding coefficient estimators. In the absence of pedigree records, FROH can provide an alternative to inbreeding estimates. Our findings can be used not only to effectively increase the response to selection by appropriately managing the rate of inbreeding and minimizing the negative effects of inbreeding depression but also to help detect genomic regions with an effect on traits under selection.
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Affiliation(s)
- Liangyu Shi
- Key Laboratory of Animal Genetics, Breeding and Reproduction (poultry) of Ministry of Agricuture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Ligang Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction (poultry) of Ministry of Agricuture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Jiaxin Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction (poultry) of Ministry of Agricuture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Tianyu Deng
- Key Laboratory of Animal Genetics, Breeding and Reproduction (poultry) of Ministry of Agricuture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Hua Yan
- Key Laboratory of Animal Genetics, Breeding and Reproduction (poultry) of Ministry of Agricuture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Longchao Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction (poultry) of Ministry of Agricuture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Xin Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction (poultry) of Ministry of Agricuture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Hongmei Gao
- Key Laboratory of Animal Genetics, Breeding and Reproduction (poultry) of Ministry of Agricuture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Xinhua Hou
- Key Laboratory of Animal Genetics, Breeding and Reproduction (poultry) of Ministry of Agricuture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Lixian Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction (poultry) of Ministry of Agricuture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Fuping Zhao
- Key Laboratory of Animal Genetics, Breeding and Reproduction (poultry) of Ministry of Agricuture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
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Distinct genetic subtypes of adiposity and glycemic changes in response to weight-loss diet intervention: the POUNDS Lost trial. Eur J Nutr 2020; 60:249-258. [PMID: 32274554 DOI: 10.1007/s00394-020-02244-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 04/01/2020] [Indexed: 01/09/2023]
Abstract
PURPOSE Obesity is a heterogeneous condition and distinct adiposity subtypes may differentially affect type 2 diabetes risk. We assessed relations between genetically determined subtypes of adiposity and changes in glycemic traits in a dietary intervention trial. METHODS The four genetic subtypes of adiposity including waist-hip ratio-increase only (WHRonly+), body mass index-increase only (BMIonly+), WHR-increase and BMI-increase (BMI+WHR+), and WHR-decrease and BMI-increase (BMI+WHR-) were assessed by polygenetic scores (PGSs), calculated based on 159 single nucleotide polymorphisms related to BMI and/or WHR. We examined the associations between the four PGSs and changes in fasting glucose, insulin, β-cell function (HOMA-B) and insulin resistance (HOMA-IR) in 692 overweight participants (84% white Americans) who were randomly assigned to one of four weight-loss diets in a 2-year intervention trial. RESULTS Higher BMI+WHR-PGS was associated with a greater decrease in 2-year changes in waist circumference in white participants (P = 0.002). We also found significant interactions between WHRonly+PGS and dietary protein in 2-year changes in fasting glucose and HOMA-B (P = 0.0007 and < 0.0001, respectively). When consuming an average-protein diet, participants with higher WHRonly+PGS showed less increased fasting glucose (β = - 0.46, P = 0.006) and less reduction in HOMA-B (β = 0.02, P = 0.005) compared with lower WHRonly+PGS. Conversely, eating high-protein diet was associated with less decreased HOMA-B among individuals with lower than higher WHRonly+PGS (β = - 0.02, P = 0.006). CONCLUSIONS Distinct genetically determined adiposity subtypes may differentially modify the effects of weight-loss diets on improving glucose metabolism in white Americans. This trial was registered at clinicaltrials.gov as NCT00072995.
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