TY - JOUR
T1 - A high-dimensional linkage analysis model for characterizing crossover interference
AU - Wang, Jing
AU - Sun, Lidan
AU - Jiang, Libo
AU - Sang, Mengmeng
AU - Ye, Meixia
AU - Cheng, Tangran
AU - Zhang, Qixiang
AU - Wu, Rongling
N1 - Funding Information:
This work is supported by National Natural Science Foundation of China (Grant No.31401900), grant 201404102 from the State Administration of Forestry of China, the Changjiang Scholars Award and 'One-thousand Person Plan' Award.
Publisher Copyright:
© The Author 2016. Published by Oxford University Press.
PY - 2017/5/1
Y1 - 2017/5/1
N2 - Linkage analysis has played an important role in understanding genome structure and evolution. However, two-point linkage analysis widely used for genetic map construction can rarely chart a detailed picture of genome organization because it fails to identify the dependence of crossovers distributed along the length of a chromosome, a phenomenon known as crossover interference. Multi-point analysis, proven to be more advantageous in gene ordering and genetic distance estimation for dominant markers than two-point analysis, is equipped with a capacity to discern and quantify crossover interference. Here, we review a statistical model for four-point analysis, which, beyond three-point analysis, can characterize crossover interference that takes place not only between two adjacent chromosomal intervals, but also over multiple successive intervals. This procedure provides an analytical tool to elucidate the detailed landscape of crossover interference over the genome and further infer the evolution of genome structure and organization.
AB - Linkage analysis has played an important role in understanding genome structure and evolution. However, two-point linkage analysis widely used for genetic map construction can rarely chart a detailed picture of genome organization because it fails to identify the dependence of crossovers distributed along the length of a chromosome, a phenomenon known as crossover interference. Multi-point analysis, proven to be more advantageous in gene ordering and genetic distance estimation for dominant markers than two-point analysis, is equipped with a capacity to discern and quantify crossover interference. Here, we review a statistical model for four-point analysis, which, beyond three-point analysis, can characterize crossover interference that takes place not only between two adjacent chromosomal intervals, but also over multiple successive intervals. This procedure provides an analytical tool to elucidate the detailed landscape of crossover interference over the genome and further infer the evolution of genome structure and organization.
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U2 - 10.1093/bib/bbw033
DO - 10.1093/bib/bbw033
M3 - Article
C2 - 27113727
AN - SCOPUS:85020187542
SN - 1467-5463
VL - 18
SP - 382
EP - 393
JO - Briefings in bioinformatics
JF - Briefings in bioinformatics
IS - 3
ER -