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Life Science Research and Sustainable Development ISBN: 978-98-84663-33-9

Another strategy for NIL development is the heterogeneous inbred family (HIF-NILs)
method. HIF plants based on primary QTL mapping information are screened from inbred
recombinants with marker genotypes. Self-pollinating the heterozygous plant produces NIL-F2.
Such NILs are suitable for mapping and isolating either major or minor QTLs. A major QTL
(SPP1) and two minor QTLs (qGL7 and qGL7–2) for grain length have all been successfully fine
mapped using such NILs (Liu et al., 2009; Baiet al., 2010 and Shao et al., 2010). In genetics, both
strategies of TP-NILs and HIFNILs employ the same method in searching a plant carrying a
heterozygous region harboring a QTL in the high generations of RIL. The difference between
them is that TP-NILs are obtained simply based on the varied trait performance within a RIL, and
HIF-NILs are based on the genotype of the QTL region. These three strategies of NIL
development are all successfully used for QTL fine-mapping. The genetic makeup of TP-NILs
and HIF-NILs combines their two parents’ genomes, whereas CBNILs carry an identical genetic
background to the recurrent parent except for the target QTL region.
Chromosome segment substitution lines (CSSLs) are an advanced population, developed
with a similar strategy to that for CB-NIL. Based on MAS, a set of CSSLs, in which donor segments
cover the whole rice genome, can be obtained. CSSL population is a powerful tool in detection of
either major or minor QTLs, and has therefore been very popular in rice and other crops over
recent years (Cheng et al., 2011 andGuoet a.,. 2011).
An ideal panicle structure is important for improvement of plant architecture and rice
yield. Penget al. (2014) identified a quantitative trait locus (QTL), designited qPPB3 for primary
panicle branch number, using recombinant inbred lines (RILs) of PA64s and 93-11, With a BC3F2
population derived from a backcross between a resequenced RIL carrying PA64s allele and 93-
11, qPPB3 was fine mapped to a 34.6-kb genomic region on chromosome number 03.
4.2 Approaches based on natural population
At present, the large amount of germplasm preservedin gene banks (ex situ) and in situ
throughout theworld provides the groundwork for identifying new genescontrolling yield and
other valuable traits (Tanksley andMcCouch, 1997).Simple sequence repeat (SSR) and simple
nucleotide polymorphism (SNP) are the most informative genetic markers useful for genetic
diversity studies (Russell et al., 2000, Sjaksteet al., 2003and Hamzaet al., 2004) and mapping.
Association mapping, also known as linkage disequilibrium(LD) mapping, is a new
method of mapping QTLs that takes advantage of historic LD to link phenotypes to
genotypes.Association mapping based on natural populations (unrelatedindividuals) is widely
used for QTL mapping due to the rapidLD decay in maize (Yu and Buckler, 2006). Agramaet
al.(2007) used the mixed linear model (MLM) method to disclose the associations between 123
SSR markers and yield components in rice. Analogically, rice, a highly selfing species,is also an
ideal candidate for association mapping due tothe following features: rich resources of
germplasm and beinggenotyped once and repeatedly phenotype. Two major grain-size QTLs,
GS3 and qSW5, were fine-mapped to regions of 120 kb and 72 kb, respectively. However, the peak
signals of association loci often appeared near (but not within) the known genes. These situations
are consistent with slow LD decay over 100– 250 kb (Mather et al., 2007 and McNally et al., 2009),
which may explain the low resolution mapping. Compared to linkage analysis, GWAS has not
identified many QTLs in rice. Surprisingly, some cloned major QTLs (e.g. Ghd7 and Ehd1)
regulating rice flowering, could not be identified by GWAS. However, recent mutations resulting
in large trait changes would be detected by linkage analysis, but not by association mapping due
to its rare occurrence in the natural population. For instance, the GW2 wider-grain allele is found
in very few varieties, e.g. WY3 and Oochikara (Takano-Kai et al., 2009).It is expected

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