MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03201nab|a22003977a|4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
62983 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
MX-TxCIM |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20230522171931.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
201118s2021||||xxk|||p|op||||00||0|eng|d |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
|---|
| International Standard Serial Number |
1467-7644 |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
|---|
| International Standard Serial Number |
1467-7652 (Online) |
| 024 8# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
https://doi.org/10.1111/pbi.13458 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
MX-TxCIM |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 100 0# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Yang Xu |
| 9 (RLIN) |
17252 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Incorporation of parental phenotypic data into multi‐omic models improves prediction of yield‐related traits in hybrid rice |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc. |
United Kingdom : |
| Name of publisher, distributor, etc. |
Wiley, |
| Date of publication, distribution, etc. |
2021. |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Peer review |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Open Access |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Hybrid breeding has been shown to effectively increase rice productivity. However, identifying desirable hybrids out of numerous potential combinations is a daunting challenge. Genomic selection holds great promise for accelerating hybrid breeding by enabling early selection before phenotypes are measured. With the recent advances in multi‐omic technologies, hybrid prediction based on transcriptomic and metabolomic data has received increasing attention. However, the current omic‐based hybrid prediction has ignored parental phenotypic information, which is of fundamental importance in plant breeding. In this study, we integrated parental phenotypic information into various multi‐omic prediction models applied in hybrid breeding of rice and compared the predictabilities of 15 combinations from four sets of predictors from the parents, that is genome, transcriptome, metabolome and phenome. The predictability for each combination was evaluated using the best linear unbiased prediction and a modified fast HAT method. We found significant interactions between predictors and traits in predictability, but joint prediction with various combinations of the predictors significantly improved predictability relative to prediction of any single source omic data for each trait investigated. Incorporation of parental phenotypic data into various omic predictors increased the predictability, averagely by 13.6%, 54.5%, 19.9% and 8.3%, for grain yield, number of tillers per plant, number of grains per panicle and 1000 grain weight, respectively. Among nine models of incorporating parental traits, the AD‐All model was the most effective one. This novel strategy of incorporating parental phenotypic data into multi‐omic prediction is expected to improve hybrid breeding progress, especially with the development of high‐throughput phenotyping technologies. |
| 546 ## - LANGUAGE NOTE |
|---|
| Language note |
Text in English |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Marker-assisted selection |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
10737 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Rice |
| 9 (RLIN) |
1243 |
| Source of heading or term |
AGROVOC |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Hybrids |
| Source of heading or term |
AGROVOC |
| 9 (RLIN) |
1151 |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Yue Zhao |
| 9 (RLIN) |
17449 |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Xin Wang |
| 9 (RLIN) |
6995 |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ying Ma |
| 9 (RLIN) |
17445 |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Pengcheng Li |
| 9 (RLIN) |
17447 |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Zefeng Yang |
| 9 (RLIN) |
17448 |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Xuecai Zhang |
| Miscellaneous information |
Global Maize Program |
| Field link and sequence number |
INT3400 |
| 9 (RLIN) |
951 |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Chenwu Xu |
| 9 (RLIN) |
17254 |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Shizhong Xu |
| 9 (RLIN) |
16865 |
| 773 0# - HOST ITEM ENTRY |
|---|
| Related parts |
v. 19, no. 2, p. 261-272 |
| Place, publisher, and date of publication |
United Kingdom : Wiley, 2021. |
| Title |
Plant Biotechnology Journal |
| International Standard Serial Number |
1467-7652 |
| Record control number |
u57523 |
| 856 4# - ELECTRONIC LOCATION AND ACCESS |
|---|
| Link text |
Open Access through DSpace |
| Uniform Resource Identifier |
https://hdl.handle.net/10883/21060 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Article |
| Suppress in OPAC |
No |
| Source of classification or shelving scheme |
Dewey Decimal Classification |