Integrating genomics and transcriptomics to identify candidate genes for high-altitude adaptation and egg production in Nixi chicken
1. This study combined genome-wide selection signal analysis with RNA-sequencing to identify candidate genes associated with high altitude adaptation and egg production performance in Nixi chickens (NXC).2. Based on the whole-genome data from 20 NXC (♂:10; ♀:10), the population selection signal was...
Saved in:
| Published in | British poultry science pp. 1 - 13 |
|---|---|
| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
26.06.2024
|
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | 1. This study combined genome-wide selection signal analysis with RNA-sequencing to identify candidate genes associated with high altitude adaptation and egg production performance in Nixi chickens (NXC).2. Based on the whole-genome data from 20 NXC (♂:10; ♀:10), the population selection signal was analysed by sliding window analysis. The selected genes were screened by combination with the population differentiation statistic (
). The sequence diversity statistic (
). RNA-seq was performed on the ovarian tissues of NXC (
= 6) and Lohmann laying hens (
= 6) to analyse the differentially expressed genes (DEGs) between the two groups. The functional enrichment analysis of the selected genes and differentially expressed genes was performed.3. There were 742 genes under strong positive selection and 509 differentially expressed genes screened in NXC. Integrated analysis of the genome and transcriptome revealing 26 overlapping genes. The candidate genes for adaptation to a high-altitude environment, as well as for egg production, disease resistance, vision and pigmentation in NXC were preliminarily screened.4. The results provided theoretical guidance for further research on the genetic resource protection and utilisation of NXC. |
|---|---|
| AbstractList | 1. This study combined genome-wide selection signal analysis with RNA-sequencing to identify candidate genes associated with high altitude adaptation and egg production performance in Nixi chickens (NXC).2. Based on the whole-genome data from 20 NXC (♂:10; ♀:10), the population selection signal was analysed by sliding window analysis. The selected genes were screened by combination with the population differentiation statistic (
). The sequence diversity statistic (
). RNA-seq was performed on the ovarian tissues of NXC (
= 6) and Lohmann laying hens (
= 6) to analyse the differentially expressed genes (DEGs) between the two groups. The functional enrichment analysis of the selected genes and differentially expressed genes was performed.3. There were 742 genes under strong positive selection and 509 differentially expressed genes screened in NXC. Integrated analysis of the genome and transcriptome revealing 26 overlapping genes. The candidate genes for adaptation to a high-altitude environment, as well as for egg production, disease resistance, vision and pigmentation in NXC were preliminarily screened.4. The results provided theoretical guidance for further research on the genetic resource protection and utilisation of NXC. 1. This study combined genome-wide selection signal analysis with RNA-sequencing to identify candidate genes associated with high altitude adaptation and egg production performance in Nixi chickens (NXC).2. Based on the whole-genome data from 20 NXC (♂:10; ♀:10), the population selection signal was analysed by sliding window analysis. The selected genes were screened by combination with the population differentiation statistic (FST). The sequence diversity statistic (θπ). RNA-seq was performed on the ovarian tissues of NXC (n = 6) and Lohmann laying hens (n = 6) to analyse the differentially expressed genes (DEGs) between the two groups. The functional enrichment analysis of the selected genes and differentially expressed genes was performed.3. There were 742 genes under strong positive selection and 509 differentially expressed genes screened in NXC. Integrated analysis of the genome and transcriptome revealing 26 overlapping genes. The candidate genes for adaptation to a high-altitude environment, as well as for egg production, disease resistance, vision and pigmentation in NXC were preliminarily screened.4. The results provided theoretical guidance for further research on the genetic resource protection and utilisation of NXC.1. This study combined genome-wide selection signal analysis with RNA-sequencing to identify candidate genes associated with high altitude adaptation and egg production performance in Nixi chickens (NXC).2. Based on the whole-genome data from 20 NXC (♂:10; ♀:10), the population selection signal was analysed by sliding window analysis. The selected genes were screened by combination with the population differentiation statistic (FST). The sequence diversity statistic (θπ). RNA-seq was performed on the ovarian tissues of NXC (n = 6) and Lohmann laying hens (n = 6) to analyse the differentially expressed genes (DEGs) between the two groups. The functional enrichment analysis of the selected genes and differentially expressed genes was performed.3. There were 742 genes under strong positive selection and 509 differentially expressed genes screened in NXC. Integrated analysis of the genome and transcriptome revealing 26 overlapping genes. The candidate genes for adaptation to a high-altitude environment, as well as for egg production, disease resistance, vision and pigmentation in NXC were preliminarily screened.4. The results provided theoretical guidance for further research on the genetic resource protection and utilisation of NXC. |
| Author | Li, M Ma, G Dai, F Guo, A Deng, C Wang, T Duan, W Yang, F Li, Q |
| Author_xml | – sequence: 1 givenname: C surname: Deng fullname: Deng, C organization: College of Biology and Food Engineering, Southwest Forestry University, Kunming, China – sequence: 2 givenname: M surname: Li fullname: Li, M organization: School of Mathematics and Computer Science, Yunnan Nationalities University, Kunming, China – sequence: 3 givenname: T surname: Wang fullname: Wang, T organization: School of Pharmacy, Chengdu University, Chengdu, China – sequence: 4 givenname: W surname: Duan fullname: Duan, W organization: College of Veterinary Medicine, China Agricultural University, Beijing, China – sequence: 5 givenname: A surname: Guo fullname: Guo, A organization: College of Biology and Food Engineering, Southwest Forestry University, Kunming, China – sequence: 6 givenname: G surname: Ma fullname: Ma, G organization: Agricultural and Rural Bureau of Gejiu County, Honghe, China – sequence: 7 givenname: F surname: Yang fullname: Yang, F organization: Agricultural and Rural Bureau of Gejiu County, Honghe, China – sequence: 8 givenname: F surname: Dai fullname: Dai, F organization: College of Veterinary Medicine, Yunnan Agricultural University, Kunming, China – sequence: 9 givenname: Q surname: Li fullname: Li, Q organization: Kunming Xianghao Technology Co. Ltd., Kunming, China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38922310$$D View this record in MEDLINE/PubMed |
| BookMark | eNo9kUtPwzAQhC0EgvL4CSAfuaTY3tpxjgjxkhBc4BwZe5MaWqfYjkTv_HCStnBaafXN7GrmmOyHLiAh55xNOdPsijFWcqX0VDAxmwpQpRB6j0z4TKmCl1W1TyYjU4zQETlO6WMj0fKQHIGuhADOJuTnMWRso8k-tLTF0C29TdQER3M0IdnoV3m7yx31DkP2zZraAfDOZBwlmGjTRTr37bwwi-xz75AaZ1Z5cO3Cxgzblq5i53q7WflAn_23p3bu7SeGU3LQmEXCs908IW93t683D8XTy_3jzfVTYbkucwFWADrhGGvAGitBSzcDybUyZWmdtk3DJZdOKVZBIy3nonRVBdZJQIB3OCGXW9_hla8eU66XPllcLEzArk81sCHESsGMD6jcojZ2KUVs6lX0SxPXNWf1WED9V0A9FlDvChh0F7sT_fsS3b_qL3H4BaY3hNY |
| Cites_doi | 10.1016/j.biopha.2020.110678 10.3389/fgene.2023.1284554 10.1093/bioinformatics/btu170 10.1186/s12711-016-0239-4 10.1111/nyas.14486 10.1093/gigascience/giab008 10.1016/j.psj.2023.102971 10.1111/jgh.12033 10.3389/fimmu.2023.1188940 10.1371/journal.pone.0261697 10.1016/s0188-4409(01)00331-9 10.3390/genes14061198 10.1186/s12864-019-5622-4 10.1038/nprot.2016.095 10.1242/dev.127.12.2695 10.1016/j.ygeno.2022.110515 10.3390/ani9080518 10.1186/s12864-021-08280-z 10.1002/cbin.12011 10.1111/age.13011 10.1007/s00335-015-9607-6 10.1155/2020/9602016 10.1534/g3.120.401701 10.1152/japplphysiol.00025.2020 10.1155/2020/3436581 10.1186/s12864-020-06900-8 10.1186/s13059-014-0550-8 10.1186/s12864-021-08213-w 10.1167/iovs.08-2751 10.3390/ani10081297 10.1186/s12864-023-09564-2 10.1080/23802359.2019.1700837 10.3389/fvets.2022.911685 10.1016/j.neulet.2019.02.003 10.1016/j.isci.2020.101644 10.2527/jas2017.1663 10.3389/fgene.2018.00737 10.1053/j.gastro.2022.11.034 10.1007/bf01553489 10.1016/j.jpi.2022.100130 10.1128/jvi.00535-11 10.1111/age.12768 10.1007/978-981-13-8023-5_51 10.1016/j.jare.2022.07.005 10.1530/joe-22-0255 10.3382/ps/pex374 10.1080/00071668.2020.1792832 10.1016/j.psj.2020.08.001 10.1016/j.anireprosci.2019.106114 10.1007/s13205-018-1504-8 10.3389/fgene.2021.622751 10.1093/g3journal/jkad237 10.3390/ijms22168911 10.1093/gigascience/gix026 10.7717/peerj.3891 10.1093/annonc/mdz384 10.1186/s12863-021-00971-6 10.1016/j.rvsc.2020.05.007 10.1038/s41598-023-34955-6 10.1016/j.psj.2020.10.005 10.1080/00071668.2021.2003752 10.3390/genes14030640 10.1186/s40104-021-00608-9 10.3389/fgene.2020.610605 10.1016/j.theriogenology.2021.09.008 10.1038/nrneph.2017.13 10.3389/fgene.2022.971464 10.1016/j.mod.2008.11.006 10.1016/j.gene.2020.144511 10.1038/s41422-020-0349-y 10.1371/journal.pgen.1007602 10.1007/s13205-019-1710-z 10.3389/fvets.2022.1034211 10.21037/jgo-23-147 10.1007/s13258-020-00988-8 10.1073/pnas.76.10.5269 10.3389/fgene.2022.1034094 10.1371/journal.pone.0127301 10.1038/s41598-019-44382-1 10.1016/j.theriogenology.2019.07.025 10.1016/j.ygcen.2012.04.016 10.1038/s41598-017-18389-5 10.1371/journal.pgen.1007989 10.3390/genes13112066 10.1177/0300060519862069 10.3390/genes12111767 10.3389/fphys.2022.954399 10.1155/2022/5749382 10.1016/j.psj.2021.101440 10.1186/s12864-022-08494-9 10.1111/j.1558-5646.1984.tb05657.x 10.1038/cr.2016.44 10.1002/vms3.575 10.1093/molbev/msab156 10.1093/bioinformatics/btac137 10.1038/s41437-018-0092-z 10.1016/j.coi.2015.12.002 10.1016/j.ijbiomac.2023.124326 10.1080/00071668.2018.1507018 10.1016/j.jare.2023.02.016 10.1016/j.ygeno.2022.110485 10.2141/jpsa.0180064 10.1073/pnas.1816107116 10.1590/1678-4685-gmb-2015-0206 10.1016/j.theriogenology.2023.10.024 10.1371/journal.pgen.1002516 10.1186/s12864-020-6456-9 10.1038/73163 10.1186/s12859-015-0848-x 10.1016/j.psj.2023.103241 |
| ContentType | Journal Article |
| DBID | NPM AAYXX CITATION 7X8 |
| DOI | 10.1080/00071668.2024.2367228 |
| DatabaseName | PubMed CrossRef MEDLINE - Academic |
| DatabaseTitle | PubMed CrossRef MEDLINE - Academic |
| DatabaseTitleList | PubMed MEDLINE - Academic |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Agriculture |
| EISSN | 1466-1799 |
| EndPage | 13 |
| ExternalDocumentID | 10_1080_00071668_2024_2367228 38922310 |
| Genre | Journal Article Review |
| GroupedDBID | --- .7F .7I .QJ 0BK 0R~ 23N 2DF 30N 36B 4.4 53G 5GY 5RE 5VS AAENE AAHBH AAJMT AALDU AAMIU AAPUL AAQRR ABCCY ABFIM ABHAV ABJNI ABLIJ ABPAQ ABPEM ABTAI ABXYU ACGEJ ACGFS ACIWK ACTIO ADCVX ADGTB ADXPE AEGYZ AEISY AENEX AEOZL AEPSL AEYOC AFKVX AFRAH AGDLA AGMYJ AHDZW AIJEM AJWEG AKBVH AKOOK ALIPV ALMA_UNASSIGNED_HOLDINGS ALQZU AQRUH AVBZW AWYRJ BLEHA CCCUG CQ1 CS3 DGEBU DKSSO DU5 EBS E~A E~B F5P GTTXZ H13 HF~ HZ~ H~P IPNFZ J.P KYCEM LJTGL M4Z NA5 NPM NX0 O9- P2P RIG RNANH ROSJB RTWRZ S-T SNACF TBQAZ TDBHL TEI TFL TFT TFW TQWBC TTHFI TUROJ TWF UT5 UU3 ZGOLN ~KM ~S~ 3YN AAYXX ABXUL AFWLO CITATION 7X8 |
| ID | FETCH-LOGICAL-c187t-3c23ed2d00f3cac5385d435186a77cd8cff1515d66093f5c1127d993cd53e33b3 |
| ISSN | 0007-1668 1466-1799 |
| IngestDate | Sat Oct 26 04:51:08 EDT 2024 Fri Aug 23 04:54:10 EDT 2024 Sat Nov 02 12:23:17 EDT 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Nixi chicken adaptation candidate gene transcriptome sequencing genome resequencing |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c187t-3c23ed2d00f3cac5385d435186a77cd8cff1515d66093f5c1127d993cd53e33b3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 |
| PMID | 38922310 |
| PQID | 3072296341 |
| PQPubID | 23479 |
| PageCount | 13 |
| ParticipantIDs | proquest_miscellaneous_3072296341 crossref_primary_10_1080_00071668_2024_2367228 pubmed_primary_38922310 |
| PublicationCentury | 2000 |
| PublicationDate | 2024-Jun-26 |
| PublicationDateYYYYMMDD | 2024-06-26 |
| PublicationDate_xml | – month: 06 year: 2024 text: 2024-Jun-26 day: 26 |
| PublicationDecade | 2020 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England |
| PublicationTitle | British poultry science |
| PublicationTitleAlternate | Br Poult Sci |
| PublicationYear | 2024 |
| References | e_1_3_4_3_1 e_1_3_4_110_1 e_1_3_4_61_1 e_1_3_4_84_1 e_1_3_4_42_1 e_1_3_4_80_1 e_1_3_4_7_1 e_1_3_4_23_1 e_1_3_4_46_1 e_1_3_4_69_1 e_1_3_4_27_1 e_1_3_4_65_1 e_1_3_4_88_1 Saghizadeh M. (e_1_3_4_64_1) 2011; 17 e_1_3_4_102_1 e_1_3_4_72_1 e_1_3_4_95_1 e_1_3_4_106_1 e_1_3_4_53_1 e_1_3_4_91_1 e_1_3_4_30_1 e_1_3_4_34_1 e_1_3_4_11_1 e_1_3_4_76_1 e_1_3_4_99_1 e_1_3_4_38_1 e_1_3_4_15_1 e_1_3_4_57_1 e_1_3_4_19_1 e_1_3_4_2_1 e_1_3_4_62_1 e_1_3_4_85_1 e_1_3_4_20_1 e_1_3_4_6_1 e_1_3_4_81_1 e_1_3_4_24_1 e_1_3_4_43_1 e_1_3_4_28_1 e_1_3_4_66_1 e_1_3_4_47_1 e_1_3_4_89_1 e_1_3_4_101_1 e_1_3_4_73_1 e_1_3_4_105_1 e_1_3_4_96_1 e_1_3_4_31_1 e_1_3_4_109_1 e_1_3_4_50_1 e_1_3_4_92_1 e_1_3_4_12_1 e_1_3_4_35_1 e_1_3_4_58_1 e_1_3_4_54_1 e_1_3_4_16_1 e_1_3_4_39_1 e_1_3_4_77_1 e_1_3_4_112_1 e_1_3_4_63_1 e_1_3_4_86_1 e_1_3_4_9_1 e_1_3_4_40_1 e_1_3_4_82_1 e_1_3_4_5_1 e_1_3_4_21_1 e_1_3_4_44_1 e_1_3_4_25_1 e_1_3_4_48_1 e_1_3_4_67_1 e_1_3_4_29_1 e_1_3_4_100_1 e_1_3_4_104_1 e_1_3_4_74_1 e_1_3_4_97_1 e_1_3_4_108_1 e_1_3_4_51_1 e_1_3_4_70_1 e_1_3_4_93_1 e_1_3_4_13_1 e_1_3_4_59_1 e_1_3_4_55_1 e_1_3_4_32_1 e_1_3_4_17_1 e_1_3_4_78_1 e_1_3_4_36_1 e_1_3_4_4_1 e_1_3_4_111_1 e_1_3_4_83_1 e_1_3_4_8_1 e_1_3_4_41_1 e_1_3_4_60_1 e_1_3_4_45_1 e_1_3_4_22_1 e_1_3_4_49_1 e_1_3_4_87_1 e_1_3_4_26_1 e_1_3_4_68_1 e_1_3_4_103_1 e_1_3_4_94_1 e_1_3_4_75_1 e_1_3_4_107_1 e_1_3_4_52_1 e_1_3_4_90_1 e_1_3_4_71_1 e_1_3_4_10_1 e_1_3_4_33_1 e_1_3_4_98_1 e_1_3_4_14_1 e_1_3_4_37_1 e_1_3_4_56_1 e_1_3_4_79_1 e_1_3_4_18_1 |
| References_xml | – ident: e_1_3_4_9_1 doi: 10.1016/j.biopha.2020.110678 – ident: e_1_3_4_31_1 doi: 10.3389/fgene.2023.1284554 – ident: e_1_3_4_3_1 doi: 10.1093/bioinformatics/btu170 – ident: e_1_3_4_18_1 doi: 10.1186/s12711-016-0239-4 – ident: e_1_3_4_33_1 doi: 10.1111/nyas.14486 – ident: e_1_3_4_59_1 doi: 10.1093/gigascience/giab008 – ident: e_1_3_4_108_1 doi: 10.1016/j.psj.2023.102971 – ident: e_1_3_4_94_1 doi: 10.1111/jgh.12033 – ident: e_1_3_4_110_1 doi: 10.3389/fimmu.2023.1188940 – ident: e_1_3_4_92_1 doi: 10.1371/journal.pone.0261697 – ident: e_1_3_4_34_1 doi: 10.1016/s0188-4409(01)00331-9 – ident: e_1_3_4_90_1 doi: 10.3390/genes14061198 – ident: e_1_3_4_38_1 doi: 10.1186/s12864-019-5622-4 – ident: e_1_3_4_58_1 doi: 10.1038/nprot.2016.095 – ident: e_1_3_4_84_1 doi: 10.1242/dev.127.12.2695 – ident: e_1_3_4_101_1 doi: 10.1016/j.ygeno.2022.110515 – ident: e_1_3_4_89_1 doi: 10.3390/ani9080518 – ident: e_1_3_4_99_1 doi: 10.1186/s12864-021-08280-z – ident: e_1_3_4_10_1 doi: 10.1002/cbin.12011 – ident: e_1_3_4_95_1 doi: 10.1111/age.13011 – ident: e_1_3_4_61_1 doi: 10.1007/s00335-015-9607-6 – ident: e_1_3_4_112_1 doi: 10.1155/2020/9602016 – ident: e_1_3_4_111_1 doi: 10.1534/g3.120.401701 – ident: e_1_3_4_51_1 doi: 10.1152/japplphysiol.00025.2020 – ident: e_1_3_4_96_1 doi: 10.1155/2020/3436581 – ident: e_1_3_4_39_1 doi: 10.1186/s12864-020-06900-8 – ident: e_1_3_4_49_1 doi: 10.1186/s13059-014-0550-8 – ident: e_1_3_4_71_1 doi: 10.1186/s12864-021-08213-w – ident: e_1_3_4_63_1 doi: 10.1167/iovs.08-2751 – ident: e_1_3_4_66_1 doi: 10.3390/ani10081297 – ident: e_1_3_4_54_1 doi: 10.1186/s12864-023-09564-2 – ident: e_1_3_4_42_1 doi: 10.1080/23802359.2019.1700837 – ident: e_1_3_4_5_1 doi: 10.3389/fvets.2022.911685 – ident: e_1_3_4_11_1 doi: 10.1016/j.neulet.2019.02.003 – ident: e_1_3_4_75_1 doi: 10.1016/j.isci.2020.101644 – ident: e_1_3_4_29_1 doi: 10.2527/jas2017.1663 – ident: e_1_3_4_76_1 doi: 10.3389/fgene.2018.00737 – ident: e_1_3_4_78_1 doi: 10.1053/j.gastro.2022.11.034 – ident: e_1_3_4_13_1 doi: 10.1007/bf01553489 – ident: e_1_3_4_62_1 doi: 10.1016/j.jpi.2022.100130 – ident: e_1_3_4_65_1 doi: 10.1128/jvi.00535-11 – ident: e_1_3_4_98_1 doi: 10.1111/age.12768 – ident: e_1_3_4_20_1 doi: 10.1007/978-981-13-8023-5_51 – ident: e_1_3_4_68_1 doi: 10.1016/j.jare.2022.07.005 – ident: e_1_3_4_57_1 doi: 10.1530/joe-22-0255 – ident: e_1_3_4_70_1 doi: 10.3382/ps/pex374 – ident: e_1_3_4_81_1 doi: 10.1080/00071668.2020.1792832 – ident: e_1_3_4_21_1 doi: 10.1016/j.psj.2020.08.001 – ident: e_1_3_4_104_1 doi: 10.1016/j.anireprosci.2019.106114 – ident: e_1_3_4_41_1 doi: 10.1007/s13205-018-1504-8 – ident: e_1_3_4_7_1 doi: 10.3389/fgene.2021.622751 – ident: e_1_3_4_35_1 doi: 10.1093/g3journal/jkad237 – ident: e_1_3_4_87_1 doi: 10.3390/ijms22168911 – ident: e_1_3_4_37_1 doi: 10.1093/gigascience/gix026 – ident: e_1_3_4_106_1 doi: 10.7717/peerj.3891 – ident: e_1_3_4_69_1 doi: 10.1093/annonc/mdz384 – ident: e_1_3_4_82_1 doi: 10.1186/s12863-021-00971-6 – ident: e_1_3_4_27_1 doi: 10.1016/j.rvsc.2020.05.007 – ident: e_1_3_4_46_1 doi: 10.1038/s41598-023-34955-6 – ident: e_1_3_4_22_1 doi: 10.1016/j.psj.2020.10.005 – ident: e_1_3_4_86_1 doi: 10.1080/00071668.2021.2003752 – ident: e_1_3_4_2_1 doi: 10.3390/genes14030640 – ident: e_1_3_4_47_1 doi: 10.1186/s40104-021-00608-9 – ident: e_1_3_4_6_1 doi: 10.3389/fgene.2020.610605 – ident: e_1_3_4_17_1 doi: 10.1016/j.theriogenology.2021.09.008 – ident: e_1_3_4_4_1 doi: 10.1038/nrneph.2017.13 – ident: e_1_3_4_24_1 doi: 10.3389/fgene.2022.971464 – ident: e_1_3_4_53_1 doi: 10.1016/j.mod.2008.11.006 – ident: e_1_3_4_19_1 doi: 10.1016/j.gene.2020.144511 – ident: e_1_3_4_79_1 doi: 10.1038/s41422-020-0349-y – ident: e_1_3_4_73_1 doi: 10.1371/journal.pgen.1007602 – volume: 17 start-page: 2011 year: 2011 ident: e_1_3_4_64_1 article-title: ZBED4, a Cone and Müller Cell Protein in Human Retina, Has a Different Cellular Expression in Mouse publication-title: Molecular Vision contributor: fullname: Saghizadeh M. – ident: e_1_3_4_93_1 doi: 10.1007/s13205-019-1710-z – ident: e_1_3_4_43_1 doi: 10.3389/fvets.2022.1034211 – ident: e_1_3_4_91_1 doi: 10.21037/jgo-23-147 – ident: e_1_3_4_30_1 doi: 10.1007/s13258-020-00988-8 – ident: e_1_3_4_55_1 doi: 10.1073/pnas.76.10.5269 – ident: e_1_3_4_40_1 doi: 10.3389/fgene.2022.1034094 – ident: e_1_3_4_100_1 doi: 10.1371/journal.pone.0127301 – ident: e_1_3_4_45_1 doi: 10.1038/s41598-019-44382-1 – ident: e_1_3_4_44_1 doi: 10.1016/j.theriogenology.2019.07.025 – ident: e_1_3_4_56_1 doi: 10.1016/j.ygcen.2012.04.016 – ident: e_1_3_4_77_1 doi: 10.1038/s41598-017-18389-5 – ident: e_1_3_4_60_1 doi: 10.1371/journal.pgen.1007989 – ident: e_1_3_4_88_1 doi: 10.3390/genes13112066 – ident: e_1_3_4_48_1 doi: 10.1177/0300060519862069 – ident: e_1_3_4_105_1 doi: 10.3390/genes12111767 – ident: e_1_3_4_52_1 doi: 10.3389/fphys.2022.954399 – ident: e_1_3_4_14_1 doi: 10.1155/2022/5749382 – ident: e_1_3_4_32_1 doi: 10.1016/j.psj.2021.101440 – ident: e_1_3_4_26_1 doi: 10.1186/s12864-022-08494-9 – ident: e_1_3_4_85_1 doi: 10.1111/j.1558-5646.1984.tb05657.x – ident: e_1_3_4_80_1 doi: 10.1038/cr.2016.44 – ident: e_1_3_4_102_1 doi: 10.1002/vms3.575 – ident: e_1_3_4_15_1 doi: 10.1093/molbev/msab156 – ident: e_1_3_4_97_1 doi: 10.1093/bioinformatics/btac137 – ident: e_1_3_4_12_1 doi: 10.1038/s41437-018-0092-z – ident: e_1_3_4_8_1 doi: 10.1016/j.coi.2015.12.002 – ident: e_1_3_4_50_1 doi: 10.1016/j.ijbiomac.2023.124326 – ident: e_1_3_4_103_1 doi: 10.1080/00071668.2018.1507018 – ident: e_1_3_4_74_1 doi: 10.1016/j.jare.2023.02.016 – ident: e_1_3_4_107_1 doi: 10.1016/j.ygeno.2022.110485 – ident: e_1_3_4_72_1 doi: 10.2141/jpsa.0180064 – ident: e_1_3_4_25_1 doi: 10.1073/pnas.1816107116 – ident: e_1_3_4_83_1 doi: 10.1590/1678-4685-gmb-2015-0206 – ident: e_1_3_4_23_1 doi: 10.1016/j.theriogenology.2023.10.024 – ident: e_1_3_4_109_1 doi: 10.1371/journal.pgen.1002516 – ident: e_1_3_4_28_1 doi: 10.1186/s12864-020-6456-9 – ident: e_1_3_4_16_1 doi: 10.1038/73163 – ident: e_1_3_4_36_1 doi: 10.1186/s12859-015-0848-x – ident: e_1_3_4_67_1 doi: 10.1016/j.psj.2023.103241 |
| SSID | ssj0007185 |
| Score | 2.4384308 |
| SecondaryResourceType | review_article |
| Snippet | 1. This study combined genome-wide selection signal analysis with RNA-sequencing to identify candidate genes associated with high altitude adaptation and egg... |
| SourceID | proquest crossref pubmed |
| SourceType | Aggregation Database Index Database |
| StartPage | 1 |
| Title | Integrating genomics and transcriptomics to identify candidate genes for high-altitude adaptation and egg production in Nixi chicken |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/38922310 https://www.proquest.com/docview/3072296341 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Na9tAEF3aFEp6CP1MnbRlC70ZGWl3tZaPIWlJC_UpIbmJ1e4q6BDZuDI0PfeHZ2Y_JLs40PYijITGoPeYebuaeSLkU8EqKEImT4RUs0QIWyeVZFUyk0Kxqqi5cZZC3-fy_FJ8u86vh9kTN13SVRP9a-dcyf-gCucAV5yS_Qdk-6BwAn4DvnAEhOH4Vxh_DV4PuNxHs9XbaLncYQVy-cCfA4HZuInc-g7bvEyD63y8xTo7hjGaFicKR3HXxo6VUcvQhIjB7A3Oqztj2NAYOW9-NjgGDhmg3XorHBySlvix6tXdOJTXXixbn1gGt8dmaz_2Kuxd933bZ2u_PXu1uTfBBPZQseBs7fOpkBIdUGcbOTLbmbn7VkdYwEnsuWNigu5yzM-Ob6C5vHVwgtJiKE6HQta3F8ZLj8kThv5_ONmTzvsCDeU4j8NcaLO-6z_3ydMYZVuxPLAMcXLk4jk5COsIeuJJ8YI8su1L8uzkZhW8VOwr8nuDHjTSgwKi9A960G5BIz1oTw_q6EGBHnSLHnSghwsG9KADPWjTUqQHDfR4TS6_fL44PU_CRzcSnRXTLuGacWuYSdOaa6WhHuYGJHVWSDWdopFEXaMGNlKmM17nGvT61IDI1SbnlvOKvyF77aK1bwmFQltIYaEoZEoIaVWuQQ9xzfM6hQB8RCbxwZZL761SZr1lrQelRFDKAMqIfIyPv4QsiK-2VGsX6x8lVCrGoJaIbEQOPS59yIjj0YNXjsn-wN53ZK9bre170Jpd9cEx5x4Synzg |
| link.rule.ids | 315,783,787,27937,27938 |
| linkProvider | Taylor & Francis |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Integrating+genomics+and+transcriptomics+to+identify+candidate+genes+for+high-altitude+adaptation+and+egg+production+in+Nixi+chicken&rft.jtitle=British+poultry+science&rft.au=Deng%2C+C&rft.au=Li%2C+M&rft.au=Wang%2C+T&rft.au=Duan%2C+W&rft.date=2024-06-26&rft.eissn=1466-1799&rft.spage=1&rft_id=info:doi/10.1080%2F00071668.2024.2367228&rft_id=info%3Apmid%2F38922310&rft.externalDocID=38922310 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0007-1668&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0007-1668&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0007-1668&client=summon |