<table>
  <tr>
    <td>1</td>
    <td>72.</td>
    <td>Achache H, Revel A: Endometrial receptivity markers, the journey to successful embryo implantation. Hum Reprod Update 2006, 12(6):731-746.</td>
  </tr>
  <tr>
    <td>2</td>
    <td>73.</td>
    <td>Killeen AP, Diskin MG, Morris DG, Kenny DA, Waters SM: Endometrial gene expression in high-and low-fertility heifers in the late luteal phase of the estrous cycle and a comparison with midluteal gene expression. Physiological genomics 2016, 48(4):306-319.</td>
  </tr>
  <tr>
    <td>3</td>
    <td>74.</td>
    <td>Cooke PS, Spencer TE, Bartol FF, Hayashi K: Uterine glands: development, function and experimental model systems. Mol Hum Reprod 2013, 19(9):547-558.</td>
  </tr>
  <tr>
    <td>4</td>
    <td>75.</td>
    <td>Filant J, Spencer TE: Uterine glands: biological roles in conceptus implantation, uterine receptivity and decidualization. The International journal of developmental biology 2014, 58(2-4):107-116.</td>
  </tr>
  <tr>
    <td>5</td>
    <td>76.</td>
    <td>Bazer FW, Wu G, Spencer TE, Johnson GA, Burghardt RC, Bayless K: Novel pathways for implantation and establishment and maintenance of pregnancy in mammals. Mol Hum Reprod 2010, 16(3):135-152.</td>
  </tr>
  <tr>
    <td>6</td>
    <td>77.</td>
    <td>Roman RJ: P-450 metabolites of arachidonic acid in the control of cardiovascular function. Physiol Rev 2002, 82(1):131-185.</td>
  </tr>
  <tr>
    <td>7</td>
    <td>78.</td>
    <td>Bionaz M, Loor JJ: ACSL1, AGPAT6, FABP3, LPIN1, and SLC27A6 are the most abundant isoforms in bovine mammary tissue and their expression is affected by stage of lactation. J Nutr 2008, 138(6):1019-1024.</td>
  </tr>
  <tr>
    <td>8</td>
    <td>79.</td>
    <td>Chen W, Chang B, Wu X, Li L, Sleeman M, Chan L: Inactivation of Plin4 downregulates Plin5 and reduces cardiac lipid accumulation in mice. Am J Physiol Endocrinol Metab 2013, 304(7):E770-779.</td>
  </tr>
  <tr>
    <td>9</td>
    <td>80.</td>
    <td>Itabe H, Yamaguchi T, Nimura S, Sasabe N: Perilipins: a diversity of intracellular lipid droplet proteins. Lipids Health Dis 2017, 16(1):83.</td>
  </tr>
  <tr>
    <td>10</td>
    <td>81.</td>
    <td>Walker CG, Littlejohn MD, Mitchell MD, Roche JR, Meier S: Endometrial gene expression during early pregnancy differs between fertile and subfertile dairy cow strains. Physiol Genomics 2012, 44(1):47-58.</td>
  </tr>
  <tr>
    <td>11</td>
    <td>82.</td>
    <td>Llewellyn S, Fitzpatrick R, Kenny DA, Patton J, Wathes DC: Endometrial expression of the insulin-like growth factor system during uterine involution in the postpartum dairy cow. Domest Anim Endocrinol 2008, 34(4):391-402.</td>
  </tr>
  <tr>
    <td>12</td>
    <td>83.</td>
    <td>Li R, He J, Chen X, Ding Y, Wang Y, Long C, Shen L, Liu X: Mmu-miR-193 is involved in embryo implantation in mouse uterus by regulating GRB7 gene expression. Reprod Sci 2014, 21(6):733-742.</td>
  </tr>
  <tr>
    <td>13</td>
    <td>84.</td>
    <td>Cooke FN, Pennington KA, Yang Q, Ealy AD: Several fibroblast growth factors are expressed during pre-attachment bovine conceptus development and regulate interferon-tau expression from trophectoderm. Reproduction 2009, 137(2):259-269.</td>
  </tr>
  <tr>
    <td>14</td>
    <td>85.</td>
    <td>Tan J, Raja S, Davis MK, Tawfik O, Dey SK, Das SK: Evidence for coordinated interaction of cyclin D3 with p21 and cdk6 in directing the development of uterine stromal cell decidualization and polyploidy during implantation. Mech Dev 2002, 111(1-2):99-113.</td>
  </tr>
  <tr>
    <td>15</td>
    <td>86.</td>
    <td>O'Shea JJ, Gadina M, Schreiber RD: Cytokine signaling in 2002: new surprises in the Jak/Stat pathway. Cell 2002, 109 Suppl:S121-131.</td>
  </tr>
  <tr>
    <td>16</td>
    <td>87.</td>
    <td>Wira CR, Grant-Tschudy KS, Crane-Godreau MA: Epithelial cells in the female reproductive tract: a central role as sentinels of immune protection. Am J Reprod Immunol 2005, 53(2):65-76.</td>
  </tr>
  <tr>
    <td>17</td>
    <td>88.</td>
    <td>Du MR, Wang SC, Li DJ: The integrative roles of chemokines at the maternal-fetal interface in early pregnancy. Cell Mol Immunol 2014, 11(5):438-448.</td>
  </tr>
  <tr>
    <td>18</td>
    <td>89.</td>
    <td>Shankar K, Zhong Y, Kang P, Lau F, Blackburn ML, Chen JR, Borengasser SJ, Ronis MJ, Badger TM: Maternal obesity promotes a proinflammatory signature in rat uterus and blastocyst. Endocrinology 2011, 152(11):4158-4170.</td>
  </tr>
  <tr>
    <td>19</td>
    <td>90.</td>
    <td>Konner AC, Bruning JC: Toll-like receptors: linking inflammation to metabolism. Trends Endocrinol Metab 2011, 22(1):16-23.</td>
  </tr>
</table>
<table>
  <tr>
    <td>1</td>
    <td>72.</td>
    <td>Achache H, Revel A: Endometrial receptivity markers, the journey to successful embryo implantation. Hum Reprod Update 2006, 12(6):731-746.</td>
  </tr>
  <tr>
    <td>2</td>
    <td>73.</td>
    <td>Killeen AP, Diskin MG, Morris DG, Kenny DA, Waters SM: Endometrial gene expression in high-and low-fertility heifers in the late luteal phase of the estrous cycle and a comparison with midluteal gene expression. Physiological genomics 2016, 48(4):306-319.</td>
  </tr>
  <tr>
    <td>3</td>
    <td>74.</td>
    <td>Cooke PS, Spencer TE, Bartol FF, Hayashi K: Uterine glands: development, function and experimental model systems. Mol Hum Reprod 2013, 19(9):547-558.</td>
  </tr>
  <tr>
    <td>4</td>
    <td>75.</td>
    <td>Filant J, Spencer TE: Uterine glands: biological roles in conceptus implantation, uterine receptivity and decidualization. The International journal of developmental biology 2014, 58(2-4):107-116.</td>
  </tr>
  <tr>
    <td>5</td>
    <td>76.</td>
    <td>Bazer FW, Wu G, Spencer TE, Johnson GA, Burghardt RC, Bayless K: Novel pathways for implantation and establishment and maintenance of pregnancy in mammals. Mol Hum Reprod 2010, 16(3):135-152.</td>
  </tr>
  <tr>
    <td>6</td>
    <td>77.</td>
    <td>Roman RJ: P-450 metabolites of arachidonic acid in the control of cardiovascular function. Physiol Rev 2002, 82(1):131-185.</td>
  </tr>
  <tr>
    <td>7</td>
    <td>78.</td>
    <td>Bionaz M, Loor JJ: ACSL1, AGPAT6, FABP3, LPIN1, and SLC27A6 are the most abundant isoforms in bovine mammary tissue and their expression is affected by stage of lactation. J Nutr 2008, 138(6):1019-1024.</td>
  </tr>
  <tr>
    <td>8</td>
    <td>79.</td>
    <td>Chen W, Chang B, Wu X, Li L, Sleeman M, Chan L: Inactivation of Plin4 downregulates Plin5 and reduces cardiac lipid accumulation in mice. Am J Physiol Endocrinol Metab 2013, 304(7):E770-779.</td>
  </tr>
  <tr>
    <td>9</td>
    <td>80.</td>
    <td>Itabe H, Yamaguchi T, Nimura S, Sasabe N: Perilipins: a diversity of intracellular lipid droplet proteins. Lipids Health Dis 2017, 16(1):83.</td>
  </tr>
  <tr>
    <td>10</td>
    <td>81.</td>
    <td>Walker CG, Littlejohn MD, Mitchell MD, Roche JR, Meier S: Endometrial gene expression during early pregnancy differs between fertile and subfertile dairy cow strains. Physiol Genomics 2012, 44(1):47-58.</td>
  </tr>
  <tr>
    <td>11</td>
    <td>82.</td>
    <td>Llewellyn S, Fitzpatrick R, Kenny DA, Patton J, Wathes DC: Endometrial expression of the insulin-like growth factor system during uterine involution in the postpartum dairy cow. Domest Anim Endocrinol 2008, 34(4):391-402.</td>
  </tr>
  <tr>
    <td>12</td>
    <td>83.</td>
    <td>Li R, He J, Chen X, Ding Y, Wang Y, Long C, Shen L, Liu X: Mmu-miR-193 is involved in embryo implantation in mouse uterus by regulating GRB7 gene expression. Reprod Sci 2014, 21(6):733-742.</td>
  </tr>
  <tr>
    <td>13</td>
    <td>84.</td>
    <td>Cooke FN, Pennington KA, Yang Q, Ealy AD: Several fibroblast growth factors are expressed during pre-attachment bovine conceptus development and regulate interferon-tau expression from trophectoderm. Reproduction 2009, 137(2):259-269.</td>
  </tr>
  <tr>
    <td>14</td>
    <td>85.</td>
    <td>Tan J, Raja S, Davis MK, Tawfik O, Dey SK, Das SK: Evidence for coordinated interaction of cyclin D3 with p21 and cdk6 in directing the development of uterine stromal cell decidualization and polyploidy during implantation. Mech Dev 2002, 111(1-2):99-113.</td>
  </tr>
  <tr>
    <td>15</td>
    <td>86.</td>
    <td>O'Shea JJ, Gadina M, Schreiber RD: Cytokine signaling in 2002: new surprises in the Jak/Stat pathway. Cell 2002, 109 Suppl:S121-131.</td>
  </tr>
  <tr>
    <td>16</td>
    <td>87.</td>
    <td>Wira CR, Grant-Tschudy KS, Crane-Godreau MA: Epithelial cells in the female reproductive tract: a central role as sentinels of immune protection. Am J Reprod Immunol 2005, 53(2):65-76.</td>
  </tr>
  <tr>
    <td>17</td>
    <td>88.</td>
    <td>Du MR, Wang SC, Li DJ: The integrative roles of chemokines at the maternal-fetal interface in early pregnancy. Cell Mol Immunol 2014, 11(5):438-448.</td>
  </tr>
  <tr>
    <td>18</td>
    <td>89.</td>
    <td>Shankar K, Zhong Y, Kang P, Lau F, Blackburn ML, Chen JR, Borengasser SJ, Ronis MJ, Badger TM: Maternal obesity promotes a proinflammatory signature in rat uterus and blastocyst. Endocrinology 2011, 152(11):4158-4170.</td>
  </tr>
  <tr>
    <td>19</td>
    <td>90.</td>
    <td>Konner AC, Bruning JC: Toll-like receptors: linking inflammation to metabolism. Trends Endocrinol Metab 2011, 22(1):16-23.</td>
  </tr>
</table>
<table>
  <tr>
    <td>1</td>
    <td>91.</td>
    <td>Graugnard DE, Moyes KM, Trevisi E, Khan MJ, Keisler D, Drackley JK, Bertoni G, Loor JJ: Liver lipid content and inflammometabolic indices in peripartal dairy cows are altered in response to prepartal energy intake and postpartal intramammary inflammatory challenge. J Dairy Sci 2013, 96(2):918-935.</td>
  </tr>
  <tr>
    <td>2</td>
    <td>92.</td>
    <td>Lopez-Meza JE, Gutierrez-Barroso A, Ochoa-Zarzosa A: Expression of tracheal antimicrobial peptide in bovine mammary epithelial cells. Res Vet Sci 2009, 87(1):59-63.</td>
  </tr>
  <tr>
    <td>3</td>
    <td>93.</td>
    <td>Thatcher WW, Guzeloglu A, Mattos R, Binelli M, Hansen TR, Pru JK: Uterine-conceptus interactions and reproductive failure in cattle. Theriogenology 2001, 56(9):1435-1450.</td>
  </tr>
  <tr>
    <td>4</td>
    <td>94.</td>
    <td>Spencer TE, Johnson GA, Bazer FW, Burghardt RC: Fetal-maternal interactions during the establishment of pregnancy in ruminants. Soc Reprod Fertil Suppl 2007, 64:379-396.</td>
  </tr>
  <tr>
    <td>10</td>
    <td>95.</td>
    <td>Khan-Dawood FS, Yang J, Dawood MY: Hormonal regulation of connexin-43 in baboon corpora lutea. J Endocrinol 1998, 157(3):405-414.</td>
  </tr>
  <tr>
    <td>11</td>
    <td>96.</td>
    <td>Blanks AM, Shmygol A, Thornton S: Regulation of oxytocin receptors and oxytocin receptor signaling. Semin Reprod Med 2007, 25(1):52-59.</td>
  </tr>
  <tr>
    <td>12</td>
    <td>97.</td>
    <td>Arosh JA, Parent J, Chapdelaine P, Sirois J, Fortier MA: Expression of cyclooxygenases 1 and 2 and prostaglandin E synthase in bovine endometrial tissue during the estrous cycle. Biol Reprod 2002, 67(1):161-169.</td>
  </tr>
  <tr>
    <td>13</td>
    <td>98.</td>
    <td>Seo H, Choi Y, Yu I, Shim J, Lee CK, Hyun SH, Lee E, Ka H: Analysis of ENPP2 in the Uterine Endometrium of Pigs Carrying Somatic Cell Nuclear Transfer Cloned Embryos. Asian-Australas J Anim Sci 2013, 26(9):1255-1261.</td>
  </tr>
  <tr>
    <td>14</td>
    <td>99.</td>
    <td>Simon C, Frances A, Piquette GN, el Danasouri I, Zurawski G, Dang W, Polan ML: Embryonic implantation in mice is blocked by interleukin-1 receptor antagonist. Endocrinology 1994, 134(2):521-528.</td>
  </tr>
  <tr>
    <td>20</td>
    <td>100.</td>
    <td>Krebs DL, Hilton DJ: SOCS proteins: negative regulators of cytokine signaling. Stem Cells 2001, 19(5):378-387.</td>
  </tr>
  <tr>
    <td>21</td>
    <td>101.</td>
    <td>Carvalho AV, Reinaud P, Forde N, Healey GD, Eozenou C, Giraud-Delville C, Mansouri-Attia N, Gall L, Richard C, Lonergan P et al: SOCS genes expression during physiological and perturbed implantation in bovine endometrium. Reproduction 2014, 148(6):545-557.</td>
  </tr>
  <tr>
    <td>25</td>
    <td>102.</td>
    <td>Yue ZP, Yang ZM, Wei P, Li SJ, Wang HB, Tan JH, Harper MJ: Leukemia inhibitory factor, leukemia inhibitory factor receptor, and glycoprotein 130 in rhesus monkey uterus during menstrual cycle and early pregnancy. Biol Reprod 2000, 63(2):508-512.</td>
  </tr>
  <tr>
    <td>31</td>
    <td>103.</td>
    <td>Johnson S, Funston R, Hall J, Lamb G, Lauderdale J, Patterson D, Perry G: Protocols for synchronization of estrus and ovulation. Proceedings Applied Reproductive Strategies in Beef Cattle San Antonio, TX 2010.</td>
  </tr>
  <tr>
    <td>32</td>
    <td>104.</td>
    <td>Ntallaris T, Humblot P, Båge R, Sjunnesson Y, Dupont J, Berglund B: Effect of energy balance profiles on metabolic and reproductive response in Holstein and Swedish Red cows. Theriogenology 2017, 90:276-283.</td>
  </tr>
  <tr>
    <td>33</td>
    <td>105.</td>
    <td>Edmonson A, Lean I, Weaver L, Farver T, Webster G: A body condition scoring chart for Holstein dairy cows. Journal of dairy science 1989, 72(1):68-78.</td>
  </tr>
  <tr>
    <td>34</td>
    <td>106.</td>
    <td>Bevilacqua C, Makhzami S, Helbling J-C, Defrenaix P, Martin P: Maintaining RNA integrity in a homogeneous population of mammary epithelial cells isolated by Laser Capture Microdissection. BMC cell biology 2010, 11(1):95.</td>
  </tr>
  <tr>
    <td>35</td>
    <td>107.</td>
    <td>Love MI, Anders S, Kim V, Huber W: RNA-Seq workflow: gene-level exploratory analysis and differential expression. F1000Res 2015, 4:1070.</td>
  </tr>
  <tr>
    <td>36</td>
    <td>108.</td>
    <td>Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C: Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods 2017, 14(4):417-419.</td>
  </tr>
  <tr>
    <td>37</td>
    <td>109.</td>
    <td>Soneson C, Love MI, Robinson MD: Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Res 2015, 4:1521.</td>
  </tr>
  <tr>
    <td>38</td>
    <td>110.</td>
    <td>Love MI, Huber W, Anders S: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014, 15(12):550.</td>
  </tr>
</table>
<table>
  <tr>
    <td>1</td>
    <td>91.</td>
    <td>Graugnard DE, Moyes KM, Trevisi E, Khan MJ, Keisler D, Drackley JK, Bertoni G, Loor JJ: Liver lipid content and inflammometabolic indices in peripartal dairy cows are altered in response to prepartal energy intake and postpartal intramammary inflammatory challenge. J Dairy Sci 2013, 96(2):918-935.</td>
  </tr>
  <tr>
    <td>2</td>
    <td>92.</td>
    <td>Lopez-Meza JE, Gutierrez-Barroso A, Ochoa-Zarzosa A: Expression of tracheal antimicrobial peptide in bovine mammary epithelial cells. Res Vet Sci 2009, 87(1):59-63.</td>
  </tr>
  <tr>
    <td>3</td>
    <td>93.</td>
    <td>Thatcher WW, Guzeloglu A, Mattos R, Binelli M, Hansen TR, Pru JK: Uterine-conceptus interactions and reproductive failure in cattle. Theriogenology 2001, 56(9):1435-1450.</td>
  </tr>
  <tr>
    <td>4</td>
    <td>94.</td>
    <td>Spencer TE, Johnson GA, Bazer FW, Burghardt RC: Fetal-maternal interactions during the establishment of pregnancy in ruminants. Soc Reprod Fertil Suppl 2007, 64:379-396.</td>
  </tr>
  <tr>
    <td>10</td>
    <td>95.</td>
    <td>Khan-Dawood FS, Yang J, Dawood MY: Hormonal regulation of connexin-43 in baboon corpora lutea. J Endocrinol 1998, 157(3):405-414.</td>
  </tr>
  <tr>
    <td>11</td>
    <td>96.</td>
    <td>Blanks AM, Shmygol A, Thornton S: Regulation of oxytocin receptors and oxytocin receptor signaling. Semin Reprod Med 2007, 25(1):52-59.</td>
  </tr>
  <tr>
    <td>12</td>
    <td>97.</td>
    <td>Arosh JA, Parent J, Chapdelaine P, Sirois J, Fortier MA: Expression of cyclooxygenases 1 and 2 and prostaglandin E synthase in bovine endometrial tissue during the estrous cycle. Biol Reprod 2002, 67(1):161-169.</td>
  </tr>
  <tr>
    <td>13</td>
    <td>98.</td>
    <td>Seo H, Choi Y, Yu I, Shim J, Lee CK, Hyun SH, Lee E, Ka H: Analysis of ENPP2 in the Uterine Endometrium of Pigs Carrying Somatic Cell Nuclear Transfer Cloned Embryos. Asian-Australas J Anim Sci 2013, 26(9):1255-1261.</td>
  </tr>
  <tr>
    <td>14</td>
    <td>99.</td>
    <td>Simon C, Frances A, Piquette GN, el Danasouri I, Zurawski G, Dang W, Polan ML: Embryonic implantation in mice is blocked by interleukin-1 receptor antagonist. Endocrinology 1994, 134(2):521-528.</td>
  </tr>
  <tr>
    <td>20</td>
    <td>100.</td>
    <td>Krebs DL, Hilton DJ: SOCS proteins: negative regulators of cytokine signaling. Stem Cells 2001, 19(5):378-387.</td>
  </tr>
  <tr>
    <td>21</td>
    <td>101.</td>
    <td>Carvalho AV, Reinaud P, Forde N, Healey GD, Eozenou C, Giraud-Delville C, Mansouri-Attia N, Gall L, Richard C, Lonergan P et al: SOCS genes expression during physiological and perturbed implantation in bovine endometrium. Reproduction 2014, 148(6):545-557.</td>
  </tr>
  <tr>
    <td>25</td>
    <td>102.</td>
    <td>Yue ZP, Yang ZM, Wei P, Li SJ, Wang HB, Tan JH, Harper MJ: Leukemia inhibitory factor, leukemia inhibitory factor receptor, and glycoprotein 130 in rhesus monkey uterus during menstrual cycle and early pregnancy. Biol Reprod 2000, 63(2):508-512.</td>
  </tr>
  <tr>
    <td>31</td>
    <td>103.</td>
    <td>Johnson S, Funston R, Hall J, Lamb G, Lauderdale J, Patterson D, Perry G: Protocols for synchronization of estrus and ovulation. Proceedings Applied Reproductive Strategies in Beef Cattle San Antonio, TX 2010.</td>
  </tr>
  <tr>
    <td>32</td>
    <td>104.</td>
    <td>Ntallaris T, Humblot P, Båge R, Sjunnesson Y, Dupont J, Berglund B: Effect of energy balance profiles on metabolic and reproductive response in Holstein and Swedish Red cows. Theriogenology 2017, 90:276-283.</td>
  </tr>
  <tr>
    <td>33</td>
    <td>105.</td>
    <td>Edmonson A, Lean I, Weaver L, Farver T, Webster G: A body condition scoring chart for Holstein dairy cows. Journal of dairy science 1989, 72(1):68-78.</td>
  </tr>
  <tr>
    <td>34</td>
    <td>106.</td>
    <td>Bevilacqua C, Makhzami S, Helbling J-C, Defrenaix P, Martin P: Maintaining RNA integrity in a homogeneous population of mammary epithelial cells isolated by Laser Capture Microdissection. BMC cell biology 2010, 11(1):95.</td>
  </tr>
  <tr>
    <td>35</td>
    <td>107.</td>
    <td>Love MI, Anders S, Kim V, Huber W: RNA-Seq workflow: gene-level exploratory analysis and differential expression. F1000Res 2015, 4:1070.</td>
  </tr>
  <tr>
    <td>36</td>
    <td>108.</td>
    <td>Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C: Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods 2017, 14(4):417-419.</td>
  </tr>
  <tr>
    <td>37</td>
    <td>109.</td>
    <td>Soneson C, Love MI, Robinson MD: Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Res 2015, 4:1521.</td>
  </tr>
  <tr>
    <td>38</td>
    <td>110.</td>
    <td>Love MI, Huber W, Anders S: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014, 15(12):550.</td>
  </tr>
</table>
1 111. Supek F, Bosnjak M, Skunca N, Smuc T: **REVIGO summarizes and visualizes long lists of gene**

2 **ontology terms.** *PLoS One* 2011, 6(7):e21800.

3

4
1 111. Supek F, Bosnjak M, Skunca N, Smuc T: **REVIGO summarizes and visualizes long lists of gene**

2 **ontology terms.** *PLoS One* 2011, 6(7):e21800.

3

4
**Legends of figures**

1

2 **Figure 1:**

3 Residual feed intake (A) and plasma NEFA concentrations (µmol/l; LSmeans ± s.e.m.) (B) of LCM-selected SRB cows between observed start of the experiment and 56 days after calving in MNEB (■ solid line; n = 5) and SNEB (○ dashed line; n = 4) group. Significant differences were observed at 14 days before (a vs b; *p* < 0.05), and 14 days after calving (c vs d; *p* < 0.05).

7

8 **Figure 2:** Transcriptomic analysis of endometrial cell types

9 (A) Venn diagram from genes expressed more than 10 TPM in specific endometrial cells (LE, luminal epithelial cells; GE, glandular epithelial cells; ST, stromal cells) (numbers of identified genes are indicated).

12 (B) Heat map of genes expressed by ST, GE and LE cells and clustering of the three cellular types (the colors show the relative level of expression. Boxes highlight the more expressed genes for each cell type [(a): stromal cells; (d): luminal epithelial cell type; (c): glandular epithelial cells: (d): epithelial cell type].

16 (C) Principal component analysis for clustering expressed genes of the three endometrial cell types.
17 Confidence ellipses around the barycenter of each cell type are shown.

18

19 **Figure 3:** Scatterplot representation of biological process GO terms in semantic space using REVIGO.
20 GO terms overrepresented in the list of genes specific to the three different cell-types of bovine endometrium (ST: stromal cells; GE: glandular epithelial cells; LE: luminal epithelial cells). Each circle corresponds to log 10 p-values according to the color scale shown at the bottom left of each figure. The size of each circle is proportional to the size of GO terms.
1

2 **Figure 1:**

3 Residual feed intake (A) and plasma NEFA concentrations (µmol/l; LSmeans ± s.e.m.) (B) of LCM-
4 selected SRB cows between observed start of the experiment and 56 days after calving in MNEB (■
5 solid line; n = 5) and SNEB (○ dashed line; n = 4) group. Significant differences were observed at 14
6 days before (a vs b; *p* < 0.05), and 14 days after calving (c vs d; *p* < 0.05).

7

8 **Figure 2:** Transcriptomic analysis of endometrial cell types

9
10
11
(A) Venn diagram from genes expressed more than 10 TPM in specific endometrial cells (LE, luminal
epithelial cells; GE, glandular epithelial cells; ST, stromal cells) (numbers of identified genes are
indicated).

12
13
14
15
(B) Heat map of genes expressed by ST, GE and LE cells and clustering of the three cellular types
(the colors show the relative level of expression. Boxes highlight the more expressed genes for each
cell type [(a): stromal cells; (d): luminal epithelial cell type; (c): glandular epithelial cells: (d):
epithelial cell type].

16
17
(C) Principal component analysis for clustering expressed genes of the three endometrial cell types.
Confidence ellipses around the barycenter of each cell type are shown.

18

19 **Figure 3:** Scatterplot representation of biological process GO terms in semantic space using REVIGO.
20
21
22
23
GO terms overrepresented in the list of genes specific to the three different cell-types of bovine
endometrium (ST: stromal cells; GE: glandular epithelial cells; LE: luminal epithelial cells). Each
circle corresponds to log 10 p-values according to the color scale shown at the bottom left of each
figure. The size of each circle is proportional to the size of GO terms.
1 **Figure 4: Effect of energy balance on transcriptome of endometrial cell types**

2 (A) Principal component analysis of all three cell types: stromal cells (ST), glandular epithelium

3 (GE), and luminal epithelium (LE) among two groups of cow (severe negative energy balance; SNEB

4 and moderate negative energy balance; MNEB).

5 (B) Venn diagrams from differentially expressed genes differentially expressed (DEGs) between

6 SNEB and MNEB in each endometrial cell types (ST, GE and LE).

7

8 **Figure 5: Volcano plots of distribution of differentially expressed genes between SNEB and MNEB**

9 for the three endometrial cell types ST (A), GE (B) and LE (C). The dotted lines in green and blue

10 represent the cut-off, respectively for the statistical significance [-Log10 (P-value), y-axis] and for +/-

11 2 log2fold change of gene expression [x-axis]. Differentially expressed genes are shown in red dots.

12

13 **Figure 6: STRING-generated protein-protein network at medium confidence level (0.4) from DEGs of**

14 ST and GE endometrial cell types selected from significant KEGG pathways (Table 8) in comparison

15 between SNEB and MNEB cows.

16

17 **Figure 7: Isolation of the three bovine endometrial cell types by LCM: stromal cells (ST), glandular**

18 epithelial cells (GE) and luminal epithelial cells (LE), before [(1): left column and arrows)] and after

19 [(2): right column] capture by LCM. (400x magnification)

20

21

22

23
1 **Figure 4: Effect of energy balance on transcriptome of endometrial cell types**

2 (A) Principal component analysis of all three cell types: stromal cells (ST), glandular epithelium

3 (GE), and luminal epithelium (LE) among two groups of cow (severe negative energy balance; SNEB

4 and moderate negative energy balance; MNEB).

5 (B) Venn diagrams from differentially expressed genes differentially expressed (DEGs) between

6 SNEB and MNEB in each endometrial cell types (ST, GE and LE).

7

8 **Figure 5: Volcano plots of distribution of differentially expressed genes between SNEB and MNEB**

9 for the three endometrial cell types ST (A), GE (B) and LE (C). The dotted lines in green and blue

10 represent the cut-off, respectively for the statistical significance [-Log10 (P-value), y-axis] and for +/-

11 2 log2fold change of gene expression [x-axis]. Differentially expressed genes are shown in red dots.

12

13 **Figure 6: STRING-generated protein-protein network at medium confidence level (0.4) from DEGs of**

14 ST and GE endometrial cell types selected from significant KEGG pathways (Table 8) in comparison

15 between SNEB and MNEB cows.

16

17 **Figure 7: Isolation of the three bovine endometrial cell types by LCM: stromal cells (ST), glandular**

18 epithelial cells (GE) and luminal epithelial cells (LE), before [(1): left column and arrows)] and after

19 [(2): right column] capture by LCM. (400x magnification)

20

21

22

23
# 1 Additional Files

## 2 Additional file 1 (TableS1_TS1-LE_TS2-GE_TS3-ST.xlsx):

## 3 Title of data: List of genes specifically expressed by the three endometrial cell types (excel file):

Sheet 1: list of genes specifically expressed by luminal cells

Sheet 2: list of genes specifically expressed by glandular cells

Sheet 3: list of genes specifically expressed by stromal cells

## 8 Additional file 2 (TableS2_GO-REVIGO05_TS1-TS2-TS3.xlsx):

## 9 Title of data: List of GO term for under and over expressed genes three endometrial cell types (excel file):

Sheet 1: over-represented GO terms for ST

Sheet 2: under-represented GO terms for ST

Sheet 3: over-represented GO terms for GE

Sheet 4: under-represented GO terms for GE

Sheet 5: over-represented GO terms for LE

Sheet 6: under-represented GO terms for LE

## 18 Additional file 3 (TableS3_PCA_tables.xlsx):

## 19 Title of data: List of genes expressed by endometrial cells according to the first two dimensions of the Principal Component Analysis (excel file):

Sheet 1: TS4_prolificPCAdim1_r+0.9_p0.01; genes positively correlated to first dimension
1 **Additional Files**

2 Additional file 1 (TableS1_TS1-LE_TS2-GE_TS3-ST.xlsx):

3 Title of data: List of genes specifically expressed by the three endometrial cell types (excel file):

4 Sheet 1: list of genes specifically expressed by luminal cells

5 Sheet 2: list of genes specifically expressed by glandular cells

6 Sheet 3: list of genes specifically expressed by stromal cells

7

8 Additional file 2 (TableS2_GO-REVIGO05_TS1-TS2-TS3.xlsx):

9 Title of data: List of GO term for under and over expressed genes three endometrial cell types (excel file):

11 Sheet 1: over-represented GO terms for ST

12 Sheet 2: under-represented GO terms for ST

13 Sheet 3: over-represented GO terms for GE

14 Sheet 4: under-represented GO terms for GE

15 Sheet 5: over-represented GO terms for LE

16 Sheet 6: under-represented GO terms for LE

17

18 Additional file 3 (TableS3_PCA_tables.xlsx):

19 Title of data: List of genes expressed by endometrial cells according to the first two dimensions of the
20 Principal Component Analysis (excel file):

21 Sheet 1: TS4_prolificPCAdim1_r+0.9_p0.01; genes positively correlated to first dimension
1 Sheet 2: TS5_prolificPCAdim1_r-0.9_p0.01; genes negatively correlated to first dimension

2 Sheet 3: TS6_prolificPCAdim2_r+0.8_p0.01; genes positively correlated to second dimension

3 Sheet 4: TS7_prolificPCAdim2_r-0.8_p0.01; genes negatively correlated to second dimension

4

5 Additional file 4 (TableS4_TS8_TS9_TS10_DEG-SNEBvsMNEB.xlsx):

6 Title of data: List of differentially expressed genes between SNEB and MNEB (excel file):

7 Sheet 1: list of DEG for stromal cells between SNEB vs MNEB

8 Sheet 2: list of DEG for glandular cells between SNEB vs MNEB

9 Sheet 3: list of DEG for luminal cells between SNEB vs MNEB

10

11 Additional file 5 (TableS5_david_ST-underexpressed.pdf):

12 Title of data: Gene Functional Classification Result (DAVID 6.8) of under-expressed genes in ST cells from SNEB animals

14

15 Additional file 6 (TableS6_david_ST-overexpressed.pdf):

16 Title of data: Gene Functional Classification Result (DAVID 6.8) of over-expressed genes in ST cells from SNEB animals

18

19 Additional file 7 (TableS7_david_GE-overexpressed.pdf):

20 Title of data: Gene Functional Classification Result (DAVID 6.8) of over-expressed genes in GE cells from SNEB animals
1 Sheet 2: TS5_prolificPCAdim1_r-0.9_p0.01; genes negatively correlated to first dimension

2 Sheet 3: TS6_prolificPCAdim2_r+0.8_p0.01; genes positively correlated to second dimension

3 Sheet 4: TS7_prolificPCAdim2_r-0.8_p0.01; genes negatively correlated to second dimension

4

5 Additional file 4 (TableS4_TS8_TS9_TS10_DEG-SNEBvsMNEB.xlsx):

6 Title of data: List of differentially expressed genes between SNEB and MNEB (excel file):

7 Sheet 1: list of DEG for stromal cells between SNEB vs MNEB

8 Sheet 2: list of DEG for glandular cells between SNEB vs MNEB

9 Sheet 3: list of DEG for luminal cells between SNEB vs MNEB

10

11 Additional file 5 (TableS5_david_ST-underexpressed.pdf):

12 Title of data: Gene Functional Classification Result (DAVID 6.8) of under-expressed genes in ST cells from SNEB animals

14

15 Additional file 6 (TableS6_david_ST-overexpressed.pdf):

16 Title of data: Gene Functional Classification Result (DAVID 6.8) of over-expressed genes in ST cells from SNEB animals

18

19 Additional file 7 (TableS7_david_GE-overexpressed.pdf):

20 Title of data: Gene Functional Classification Result (DAVID 6.8) of over-expressed genes in GE cells from SNEB animals
1 **Additional file 8 (TableS8_david_LE-underexpressed.pdf):**

2 Gene Functional Classification Result (DAVID 6.8) of under-expressed genes in LE cells from SNEB

3 animals

4

5 **Additional file 9 (TableS9.pdf):**

6 Title of data: Number of samples of each cell type from MNEB and SNEB group. RNA Integrity

7 Number (RIN)] [mean value (± s.e.m)] and average number of tissue sections required to obtain at

8 least 10 ng of total RNA in each endometrial cell type.

9

10 **Additional file 10 (FigS1.pdf):**

11 Title of data: Experimental design including 12 cows. From energy balance profiles 9 cows were

12 selected for LCM of endometrial tissue biopsies (5 mild NEB and 4 severe NEB cows). An arrow

13 with dash line indicate a timing for BCS measurement and blood sampling for NEFA measurement
1 **Additional file 8 (TableS8_david_LE-underexpressed.pdf):**

2 Gene Functional Classification Result (DAVID 6.8) of under-expressed genes in LE cells from SNEB

3 animals

4

5 **Additional file 9 (TableS9.pdf):**

6 Title of data: Number of samples of each cell type from MNEB and SNEB group. RNA Integrity

7 Number (RIN)] [mean value (± s.e.m)] and average number of tissue sections required to obtain at

8 least 10 ng of total RNA in each endometrial cell type.

9

10 **Additional file 10 (FigS1.pdf):**

11 Title of data: Experimental design including 12 cows. From energy balance profiles 9 cows were

12 selected for LCM of endometrial tissue biopsies (5 mild NEB and 4 severe NEB cows). An arrow

13 with dash line indicate a timing for BCS measurement and blood sampling for NEFA measurement
<figure><img src="image_1.png" /></figure>

<figure><img src="image_2.png" /><figcaption>figure 1</figcaption></figure>
<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /><figcaption>figure 1</figcaption></figure>
and SNEB ( ☐ dashed line; n = 4) group. Significant differences were observed at 14 days before (a vs b; p < 0.05), and 14 days after calving (c vs d; p < 0.05).

<figure><img src="image_3.png" /><figcaption>figure 2</figcaption></figure>

Figure 2

Transcriptomic analysis of endometrial cell types (A) Venn diagram from genes expressed more than 10 TPM in specific endometrial cells (LE, luminal epithelial cells; GE, glandular epithelial cells; ST, stromal cells) (numbers of identified genes are indicated). (C) Principal component analysis for clustering
and SNEB (□dashed line; n = 4) group. Significant differences were observed at 14 days before (a vs b; p < 0.05), and 14 days after calving (c vs d; p < 0.05).

<figure><img src="image_4.png" /><figcaption>figure 2</figcaption></figure>

Figure 2

Transcriptomic analysis of endometrial cell types (A) Venn diagram from genes expressed more than 10 TPM in specific endometrial cells (LE, luminal epithelial cells; GE, glandular epithelial cells; ST, stromal cells) (numbers of identified genes are indicated). (C) Principal component analysis for clustering
expressed genes of the three endometrial cell types. Confidence ellipses around the barycenter of each cell type are shown.

<figure><img src="image_4.png" /><figcaption>figure 3</figcaption></figure>

<caption>Figure 3</caption>

Scatterplot representation of biological process GO terms in semantic space using REVIGO. GO terms overrepresented in the list of genes specific to the three different cell-types of bovine endometrium (ST: stromal cells; GE: glandular epithelial cells; LE: luminal epithelial cells). Each circle corresponds to log 10
expressed genes of the three endometrial cell types. Confidence ellipses around the barycenter of each cell type are shown.

<figure><img src="image_5.png" /><figcaption>figure 3</figcaption></figure>

<caption>Figure 3</caption>

Scatterplot representation of biological process GO terms in semantic space using REVIGO. GO terms overrepresented in the list of genes specific to the three different cell-types of bovine endometrium (ST: stromal cells; GE: glandular epithelial cells; LE: luminal epithelial cells). Each circle corresponds to log 10
p-values according to the color scale shown at the bottom left of each figure. The size of each circle is proportional to the size of GO terms.

<figure><img src="image_5.png" /><figcaption>figure 4</figcaption></figure>

**Figure 4**

Effect of energy balance on transcriptome of endometrial cell types (A) Principal component analysis of all three cell types: stromal cells (ST), glandular epithelium (GE), and luminal epithelium (LE) among two groups of cow (severe negative energy balance; SNEB and moderate negative energy balance; MNEB). (B)
p-values according to the color scale shown at the bottom left of each figure. The size of each circle is proportional to the size of GO terms.

<figure><img src="image_6.png" /><figcaption>figure 4</figcaption></figure>

**Figure 4**

Effect of energy balance on transcriptome of endometrial cell types (A) Principal component analysis of all three cell types: stromal cells (ST), glandular epithelium (GE), and luminal epithelium (LE) among two groups of cow (severe negative energy balance; SNEB and moderate negative energy balance; MNEB). (B)
Venn diagrams from differentially expressed genes differentially expressed (DEGs) between SNEB and MNEB in each endometrial cell types (ST, GE and LE).

<figure><img src="image_6.png" /><figcaption>Figure 5</figcaption></figure>

Figure 5

Volcano plots of distribution of differentially expressed genes between SNEB and MNEB for the three endometrial cell types ST (A), GE (B) and LE (C). The dotted lines in green and blue represent the cut-off,
Venn diagrams from differentially expressed genes differentially expressed (DEGs) between SNEB and MNEB in each endometrial cell types (ST, GE and LE).

<figure><img src="image_7.png" /><figcaption>Figure 5</figcaption></figure>

Figure 5

Volcano plots of distribution of differentially expressed genes between SNEB and MNEB for the three endometrial cell types ST (A), GE (B) and LE (C). The dotted lines in green and blue represent the cut-off,
respectively for the statistical significance [-Log10 (P-value), y-axis] and for +/- 2 log2fold change of gene expression [x-axis]. Differentially expressed genes are shown in red dots.

<figure><img src="image_7.png" /><figcaption>Figure 6</figcaption></figure>

**Figure 6**

STRING-generated protein-protein network at medium confidence level (0.4) from DEGs of ST and GE endometrial cell types selected from significant KEGG pathways (Table 8) in comparison between SNEB and MNEB cows.
respectively for the statistical significance [-Log10 (P-value), y-axis] and for +/- 2 log2fold change of gene expression [x-axis]. Differentially expressed genes are shown in red dots.

<figure><img src="image_8.png" /><figcaption>Figure 6</figcaption></figure>

**Figure 6**

STRING-generated protein-protein network at medium confidence level (0.4) from DEGs of ST and GE endometrial cell types selected from significant KEGG pathways (Table 8) in comparison between SNEB and MNEB cows.
<figure><img src="image_8.png" /><figcaption>figure 7</figcaption></figure>

<caption>Figure 7</caption>

Isolation of the three bovine endometrial cell types by LCM: stromal cells (ST), glandular epithelial cells (GE) and luminal epithelial cells (LE), before [(1): left column and arrows)] and after [(2): right column] capture by LCM. (400x magnification)

**Supplementary Files**
<figure><img src="image_9.png" /><figcaption>figure 7</figcaption></figure>

<caption>**Figure 7**</caption>

Isolation of the three bovine endometrial cell types by LCM: stromal cells (ST), glandular epithelial cells (GE) and luminal epithelial cells (LE), before [(1): left column and arrows)] and after [(2): right column] capture by LCM. (400x magnification)

**Supplementary Files**
This is a list of supplementary files associated with this preprint. Click to download.

* FigS1.pdf

* TableS1TS1LETS2GETS3ST.xlsx

* TableS5davidSTunderexpressed.pdf

* TableS2GOREVIGO05TS1TS2TS3.xlsx

* TableS6davidSToverexpressed.pdf

* TableS3PCAtables.xlsx

* TableS7davidGEoverexpressed.pdf

* TableS4TS8TS9TS10DEGSNEBvsMNEB.xlsx

* TableS8davidLEunderexpressed.pdf

* TableS9.pdf
This is a list of supplementary files associated with this preprint. Click to download.

* FigS1.pdf

* TableS1TS1LETS2GETS3ST.xlsx

* TableS5davidSTunderexpressed.pdf

* TableS2GOREVIGO05TS1TS2TS3.xlsx

* TableS6davidSToverexpressed.pdf

* TableS3PCAtables.xlsx

* TableS7davidGEoverexpressed.pdf

* TableS4TS8TS9TS10DEGSNEBvsMNEB.xlsx

* TableS8davidLEunderexpressed.pdf

* TableS9.pdf