東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Applications of Multitrait and Multi...

Okeke, Uche Godfrey.

FindBook

Google Book

Amazon

博客來

Applications of Multitrait and Multi-Kernel Models for Genomic Selection in African Cassava.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Applications of Multitrait and Multi-Kernel Models for Genomic Selection in African Cassava./
作者:	Okeke, Uche Godfrey.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	184 p.
附註:	Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.
Contained By:	Dissertation Abstracts International79-03B(E).
標題:	Plant sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10637297
ISBN:	9780355527674

Applications of Multitrait and Multi-Kernel Models for Genomic Selection in African Cassava.
Okeke, Uche Godfrey.

Applications of Multitrait and Multi-Kernel Models for Genomic Selection in African Cassava. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 184 p.

Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.

Thesis (Ph.D.)--Cornell University, 2017.

Genomic selection (GS) could help accelerate African cassava breeding towards the development of high yielding, high dry matter (DM), disease resistant and provitamin A varieties. This work addresses some issues for implementing GS in cassava. First, we evaluated multivariate and univariate GS models via prediction accuracies. Second, the genetic basis for DM content was investigated using the Regional Heritability Mapping (RHM) procedure. Lastly, the genetic basis for co-inheritance of DM, root color and fresh yield (FYLD) were investigated using the Regional co-heritability Mapping (RHM) procedure. Key lessons were: (1) Multitrait (MT) models for single location data offered 40% higher average prediction accuracies for genomic breeding values (GEBVs) of six target traits across 3 locations compared to single-trait (uT) models. (2) Multivariate multi-environment (ME) models also offered 12% higher average prediction accuracies compared to a compound symmetric multi-environment model (uE) parameterized as a univariate multi-kernel model for multi-year multi-environment data. (3) The RHM analysis identified segments associated with DM in white cassava on chromosomes 1, 4, 5, 10, 17,18 and on yellow cassava chromosome 1. Candidates extracted from genes adjacent to the RHM significant segments include: glycosyltransferases, serine-threonine kinases (SnRKs), invertases and fructose bisphosphate aldolase. Prediction accuracies from these candidates and all genes in the RHM significant regions suggest that they may be tagging regions associated with DM. (4) Genome-wide segment correlations from the RcHM analysis in yellow cassava showed a limited prospect for high DM yellow cassava development but good prospects for high DM, high yielding white cassava development.

ISBN: 9780355527674Subjects--Topical Terms:

3173832
Plant sciences.

Applications of Multitrait and Multi-Kernel Models for Genomic Selection in African Cassava.
LDR:02754nmm a2200301 4500 001 2162301
005 20180928111501.5
008 190424s2017 ||||||||||||||||| ||eng d
020 $a 9780355527674
035 $a (MiAaPQ)AAI10637297
035 $a (MiAaPQ)cornellgrad:10576
035 $a AAI10637297
040 $a MiAaPQ $c MiAaPQ
100 1 $a Okeke, Uche Godfrey. $0 (orcid)0000-0002-3533-011X $3 3350285
245 1 0 $a Applications of Multitrait and Multi-Kernel Models for Genomic Selection in African Cassava.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 184 p.
500 $a Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.
500 $a Adviser: Jean-Luc Jannink.
502 $a Thesis (Ph.D.)--Cornell University, 2017.
520 $a Genomic selection (GS) could help accelerate African cassava breeding towards the development of high yielding, high dry matter (DM), disease resistant and provitamin A varieties. This work addresses some issues for implementing GS in cassava. First, we evaluated multivariate and univariate GS models via prediction accuracies. Second, the genetic basis for DM content was investigated using the Regional Heritability Mapping (RHM) procedure. Lastly, the genetic basis for co-inheritance of DM, root color and fresh yield (FYLD) were investigated using the Regional co-heritability Mapping (RHM) procedure. Key lessons were: (1) Multitrait (MT) models for single location data offered 40% higher average prediction accuracies for genomic breeding values (GEBVs) of six target traits across 3 locations compared to single-trait (uT) models. (2) Multivariate multi-environment (ME) models also offered 12% higher average prediction accuracies compared to a compound symmetric multi-environment model (uE) parameterized as a univariate multi-kernel model for multi-year multi-environment data. (3) The RHM analysis identified segments associated with DM in white cassava on chromosomes 1, 4, 5, 10, 17,18 and on yellow cassava chromosome 1. Candidates extracted from genes adjacent to the RHM significant segments include: glycosyltransferases, serine-threonine kinases (SnRKs), invertases and fructose bisphosphate aldolase. Prediction accuracies from these candidates and all genes in the RHM significant regions suggest that they may be tagging regions associated with DM. (4) Genome-wide segment correlations from the RcHM analysis in yellow cassava showed a limited prospect for high DM yellow cassava development but good prospects for high DM, high yielding white cassava development.
590 $a School code: 0058.
650 4 $a Plant sciences. $3 3173832
650 4 $a Agriculture. $3 518588
690 $a 0479
690 $a 0473
710 2 $a Cornell University. $b Plant Breeding. $3 3350211
773 0 $t Dissertation Abstracts International $g 79-03B(E).
790 $a 0058
791 $a Ph.D.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10637297