David A. Levitsky: feeding conditions and intermeal relationships. Physiol Behav. 1974;12(5):779–87.
Article
Google Scholar
Slater PJB. The temporal pattern of feeding in the zebra finch. Anim Behav. 1974;22(2):506–15. https://doi.org/10.1016/S0003-3472(74)80050-3.
Article
Google Scholar
Natelson BH, Bonbright JC. Patterns of eating and drinking in monkeys when food and water are free and when they are earned. Physiol Behav. 1978;21(2):201–13. https://doi.org/10.1016/0031-9384(78)90042-2.
Article
CAS
PubMed
Google Scholar
Bigelow JA, Houpt TR. Feeding and drinking patterns in young pigs. Physiol Behav. 1988;43(1):99–109. https://doi.org/10.1016/0031-9384(88)90104-7.
Article
CAS
PubMed
Google Scholar
Tolkamp BJ, Schweitzer DPN, Kyriazakis I. The biologically relevant unit for the analysis of short-term feeding behavior of dairy cows. J Dairy Sci. 2000;83(9):2057–68. https://doi.org/10.3168/jds.S0022-0302(00)75087-9.
Article
CAS
PubMed
Google Scholar
Huang Y, Li Y, Burt DW, Chen H, Zhang Y, Qian W, et al. The duck genome and transcriptome provide insight into an avian influenza virus reservoir species. Nat Genet. 2013;45(7):776.
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhou Z, Li M, Cheng H, Fan W, Yuan Z, Gao Q, et al. An intercross population study reveals genes associated with body size and plumage color in ducks. Nat Commun. 2018;9(1):2648.
Howie J, Avendano S, Tolkamp B, Kyriazakis I. Genetic parameters of feeding behavior traits and their relationship with live performance traits in modern broiler lines. Poult Sci. 2011;90(6):1197–205. https://doi.org/10.3382/ps.2010-01313.
Article
CAS
PubMed
Google Scholar
Drouilhet L, Monteville R, Molette C, Lague M, Cornuez A, Canario L, et al. Impact of selection for residual feed intake on production traits and behavior of mule ducks. Poult Sci. 2016;95(9):1999–2010. https://doi.org/10.3382/ps/pew185.
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhu F, Gao Y, Lin F, Hao J, Yang F, Hou Z. Systematic analysis of feeding behaviors and their effects on feed efficiency in Pekin ducks. J Animal Sci Biotechnol. 2017;8(1):81. https://doi.org/10.1186/s40104-017-0212-2.
Article
Google Scholar
Li G-S, Zhu F, Yang F-X, Hao J-P, Hou Z-C. Selection response and genetic parameter estimation of feeding behavior traits in Pekin ducks. Poult Sci. 2020;99(5):2375–84. https://doi.org/10.1016/j.psj.2020.01.013.
Article
PubMed
PubMed Central
Google Scholar
Zhu F, Cui Q-Q, Hou Z-C. SNP discovery and genotyping using genotyping-by-sequencing in Pekin ducks. Sci Rep. 2016;6(1):36223.
Deng M-T, Zhu F, Yang Y-Z, Yang F-X, Hao J-P, Chen S-R, et al. genome-wide association study reveals novel loci associated with body size and carcass yields in Pekin ducks. BMC Genomics. 2019;20(1):1. https://doi.org/10.1186/s12864-018-5379-1.
Zhu F, Cui Q-Q, Yang Y-Z, Hao J-P, Yang F-X, Hou Z-C. Genome-wide association study of the level of blood components in Pekin ducks. Genomics. 2019;112(1):379–87. https://doi.org/10.1016/j.ygeno.2019.02.017.
Article
CAS
PubMed
Google Scholar
Munoz PR, Resende MFR Jr, Huber DA, Quesada T, Resende MDV, Neale DB, et al. Genomic relationship matrix for correcting pedigree errors in breeding populations: impact on genetic parameters and genomic selection accuracy. Crop Sci. 2014;54(3):1115–23. https://doi.org/10.2135/cropsci2012.12.0673.
Article
Google Scholar
Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, et al. Finding the missing heritability of complex diseases. Nature. 2009;461(7265):747–53. https://doi.org/10.1038/nature08494.
Article
CAS
PubMed
PubMed Central
Google Scholar
Yang J, Bakshi A, Zhu Z, Hemani G, Vinkhuyzen AAE, Lee SH, et al. Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index. Nat Genet. 2015;47(10):1114.
Article
CAS
PubMed
PubMed Central
Google Scholar
Mizukami S, Watanabe Y, Saegusa Y, Nakajima K, Ito Y, Masubuchi Y, et al. Downregulation of UBE2E2 in rat liver cells after hepatocarcinogen treatment facilitates cell proliferation and slowing down of DNA damage response in GST-P-expressing preneoplastic lesions. Toxicol Appl Pharmacol. 2017;334:207–16. https://doi.org/10.1016/j.taap.2017.09.005.
Article
CAS
PubMed
Google Scholar
El Yaagoubi FL, Charoute H, Morjane I, Sefri H, Rouba H, Ainahi A, et al. Association analysis of genetic variants with metabolic syndrome components in the Moroccan population. Curr Res Transl Med. 2017;65(3):121–5. https://doi.org/10.1016/j.retram.2017.08.001.
Article
Google Scholar
Zeng Y, He H, Zhang L, Zhu W, Shen H, Yan Y-J, et al. GWA-based pleiotropic analysis identified potential SNPs and genes related to type 2 diabetes and obesity. J Hum Genet. 2021;66(3):297–306. https://doi.org/10.1038/s10038-020-00843-4.
Article
CAS
PubMed
Google Scholar
Chu AY, Deng X, Fisher VA, Drong A, Zhang Y, Feitosa MF, et al. Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation. Nat Genet. 2017;49(1):125–30. https://doi.org/10.1038/ng.3738.
Article
CAS
PubMed
Google Scholar
Mumtaz S, Yıldız E, Jabeen S, Khan A, Tolun A, Malik S. RBBP8 syndrome with microcephaly, intellectual disability, short stature and brachydactyly. Am J Med Genet A. 2015;167(12):3148–52. https://doi.org/10.1002/ajmg.a.37299.
Article
CAS
Google Scholar
Li F, Han H, Lei Q, Gao J, Liu J, Liu W, et al. Genome-wide association study of body weight in Wenshang barred chicken based on the SLAF-seq technology. J Appl Genet. 2018;59(3):305–12. https://doi.org/10.1007/s13353-018-0452-7.
Article
CAS
PubMed
Google Scholar
Münster-Wandowski A, Heilmann H, Bolduan F, Trimbuch T, Yanagawa Y, Vida I. Distinct Localization of SNAP47 Protein in GABAergic and Glutamatergic Neurons in the Mouse and the Rat Hippocampus. Front Neuroanat. 2017;11:56. https://doi.org/10.3389/fnana.2017.00056.
Gonnaud L, Alves MM, Cremillieux C, Billiemaz K, Destombe S, Varlet F, et al. Two new mutations of the CLMP gene identified in a newborn presenting congenital short-bowel syndrome. Clin Res Hepatol Gastroenterol. 2016;40(6):e65–7. https://doi.org/10.1016/j.clinre.2015.12.018.
Article
CAS
PubMed
Google Scholar
Langhorst H, Jüttner R, Groneberg D, Mohtashamdolatshahi A, Pelz L, Purfürst B, et al. The IgCAM CLMP regulates expression of Connexin43 and Connexin45 in intestinal and ureteral smooth muscle contraction in mice. Dis Model Mech. 2018;11(2):dmm032128.
Van Der Werf CS, Wabbersen TD, Hsiao NH, Paredes J, Etchevers HC, Kroisel PM, Tibboel D, Babarit C, Schreiber RA, Hoffenberg EJ: CLMP is required for intestinal development, and loss-of-function mutations cause congenital short-bowel syndrome. Gastroenterology 2012, 142(3):453–462. e453.
Liu Y, Yu M, Shang X, Nguyen MHH, Balakrishnan S, Sager R, et al. Eyes shut homolog (EYS) interacts with matriglycan of O-mannosyl glycans whose deficiency results in EYS mislocalization and degeneration of photoreceptors. Sci Rep. 2020;10(1):7795.
Numa S, Oishi A, Higasa K, Oishi M, Miyata M, Hasegawa T, et al. EYS is a major gene involved in retinitis pigmentosa in Japan: genetic landscapes revealed by stepwise genetic screening. Sci Rep. 2020;10(1):20770.
Kular J, Tickner J, Chim SM, Xu J. An overview of the regulation of bone remodelling at the cellular level. Clin Biochem. 2012;45(12):863–73. https://doi.org/10.1016/j.clinbiochem.2012.03.021.
Article
CAS
PubMed
Google Scholar
Bradley D, Yin Z, Liu JZ, Blaszczak AM, Wong ST, Hsueh W. Adipocyte EGFL6 expression from subcutaneous adipose tissue alters glucose homeostasis and affects human obesity. Diabetes. 2018;67(Supplement 1):1751.
Article
Google Scholar
Di Benedetto A, Watkins M, Grimston S, Salazar V, Donsante C, Mbalaviele G, et al. N-cadherin and cadherin 11 modulate postnatal bone growth and osteoblast differentiation by distinct mechanisms. J Cell Sci. 2010;123(15):2640–8. https://doi.org/10.1242/jcs.067777.
Article
CAS
PubMed
PubMed Central
Google Scholar
Shang H, Hao Y, Hu W, Hu X, Jin Q. CDH2 gene rs11564299 polymorphism is a risk factor for knee osteoarthritis in a Chinese population: a case–control study. J Orthop Surg Res. 2019;14(1):1–6.
Article
Google Scholar
Aaron M, Nadeau G, Ouimet-Grennan E, Drouin S, Bertout L, Beaulieu P, et al. Identification of a single-nucleotide polymorphism within CDH2 gene associated with bone morbidity in childhood acute lymphoblastic leukemia survivors. Pharmacogenomics. 2019;20(6):409–20. https://doi.org/10.2217/pgs-2018-0169.
Article
CAS
PubMed
Google Scholar
Melo AA, Hegde BG, Shah C, Larsson E, Isas JM, Kunz S, et al. Structural insights into the activation mechanism of dynamin-like EHD ATPases. Proc Natl Acad Sci U S A. 2017;114(22):5629–34. https://doi.org/10.1073/pnas.1614075114.
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhang X, Zhai W, Li S, Suman SP, Chen J, Zhu H, et al. Early postmortem proteome changes in Normal and Woody broiler breast muscles. J Agric Food Chem. 2020;68(39):11000–10. https://doi.org/10.1021/acs.jafc.0c03200.
Article
CAS
PubMed
Google Scholar
Zhu F, Cheng S-R, Yang Y-z, Hao J-P, Yang F-X, Hou Z-C. Genome-wide association study of growth and feeding traits in Pekin Ducks. Front Genet. 2019;10:702. https://doi.org/10.3389/fgene.2019.00702.
Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv preprint arXiv. 2013;1303:3997.
Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call format and VCFtools. Bioinformatics. 2011;27(15):2156–8. https://doi.org/10.1093/bioinformatics/btr330.
Article
CAS
PubMed
PubMed Central
Google Scholar
Chang CC, Chow CC, Tellier LCAM, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Giga Sci. 2015;4(1):7.
McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20(9):1297–303. https://doi.org/10.1101/gr.107524.110.
Article
CAS
PubMed
PubMed Central
Google Scholar
Browning BL, Zhou Y, Browning SR. A one-penny imputed genome from next-generation reference panels. Am J Hum Genet. 2018;103(3):338–48. https://doi.org/10.1016/j.ajhg.2018.07.015.
Article
CAS
PubMed
PubMed Central
Google Scholar
Yang J, Zaitlen N, Goddard M, Visscher P, Price A. Mixed model association methods: advantages and pitfalls. Nat Genet. 2014;46(2):100–6. https://doi.org/10.1038/ng.2876.
Article
CAS
PubMed
PubMed Central
Google Scholar
Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. 2011;88(1):76–82. https://doi.org/10.1016/j.ajhg.2010.11.011.
Article
CAS
PubMed
PubMed Central
Google Scholar
Turner SD. qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots. J Open Sour Softw. 2018;3(25):731.
Article
Google Scholar
Gao X, Becker LC, Becker DM, Starmer JD, Province MA. Avoiding the high Bonferroni penalty in genome-wide association studies. Genet Epidemiol. 2010;34(1):100–5. https://doi.org/10.1002/gepi.20430.
Article
PubMed
PubMed Central
Google Scholar
Dong S-S, He W-M, Ji J-J, Zhang C, Guo Y, Yang T-L. LDBlockShow: a fast and convenient tool for visualizing linkage disequilibrium and haplotype blocks based on variant call format files. Brief Bioinform. 2020. https://doi.org/10.1093/bib/bbaa227.
Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26(6):841–2. https://doi.org/10.1093/bioinformatics/btq033.
Article
CAS
PubMed
PubMed Central
Google Scholar
Hu Z-L, Park CA, Reecy JM. Building a livestock genetic and genomic information knowledgebase through integrative developments of animal QTLdb and CorrDB. Nucleic Acids Res. 2019;47(D1):D701–10. https://doi.org/10.1093/nar/gky1084.
Article
CAS
PubMed
Google Scholar