Optimal Design for Marker-assisted Gene Pyramiding in Cross Population

An Overview of Mapping Quantitative Trait Loci in Peanut (Arachis hypogaea L.)

Quantitative Trait Loci (QTL) mapping has been thoroughly used in peanut genetics and breeding in spite of the narrow genetic diversity and the segmental tetraploid nature of the cultivated species. QTL mapping is helpful for identifying the genomic regions that contribute to traits, for estimating the extent of variation and the genetic action (i.e., additive, dominant, or epistatic) underlying this variation, and for pinpointing genetic correlations between traits. The aim of this paper is to review the recently published studies on QTL mapping with a particular emphasis on mapping populations used as well as traits related to kernel quality. We found that several populations have been used for QTL mapping including interspecific populations developed from crosses between synthetic tetraploids and elite varieties. Those populations allowed the broadening of the genetic base of cultivated peanut and helped with the mapping of QTL and identifying beneficial wild alleles for economically important traits. Furthermore, only a few studies reported QTL related to kernel quality. The main quality traits for which QTL have been mapped include oil and protein content as well as fatty acid compositions. QTL for other agronomic traits have also been reported. Among the 1261 QTL reported in this review, and extracted from the most relevant studies on QTL mapping in peanut, 413 (~33%) were related to kernel quality showing the importance of quality in peanut genetics and breeding. Exploiting the QTL information could accelerate breeding to develop highly nutritious superior cultivars in the face of climate change.

Identification of a key locus, qNL3.1, associated with seed germination under salt stress via a genome-wide association study in rice

Two causal OsTTL and OsSAPK1 genes of the key locus qNL3.1 significantly associated with seed germination under salt stress were identified via a genome-wide association study, which could improve rice seed germination under salt stress. Rice is a salt-sensitive crop, and its seed germination determines subsequent seedling establishment and yields. In this study, 168 accessions were investigated for the genetic control of seed germination under salt stress based on the germination rate (GR), germination index (GI), time at which 50% germination was achieved (T₅₀) and mean level (ML). Extensive natural variation in seed germination was observed among accessions under salt stress. Correlation analysis showed significantly positive correlations among GR, GI and ML and a negative correlation with T₅₀ during seed germination under salt stress. Forty-nine loci significantly associated with seed germination under salt stress were identified, and seven of these were identified in both years. By comparison, 16 loci were colocated with the previous QTLs, and the remaining 33 loci might be novel. qNL3.1, colocated with qLTG-3, was simultaneously identified with the four indices in two years and might be a key locus for seed germination under salt stress. Analysis of candidate genes showed that two genes, the similar to transthyretin-like protein OsTTL and the serine/threonine protein kinase OsSAPK1, were the causal genes of qNL3.1. Germination tests indicated that both Osttl and Ossapk1 mutants significantly reduced seed germination under salt stress compared to the wild type. Haplotype analysis showed that Hap.1 of OsTTL and Hap.1 of OsSAPK1 genes were excellent alleles, and their combination resulted in high seed germination under salt stress. Eight accessions with elite performance of seed germination under salt stress were identified, which could improve rice seed germination under salt stress.

Polymerisation effects of four microsatellites on litter size in Xinong Saanen goats

In this study, the polymerisation effects of four microsatellites (OarAE101, BM1329, BM143 and LSCV043) on litter size in Xinong Saanen goats were analysed by means of microsatellite marker and pedigrees, then associations between combined genotypes and litter size were performed. The results indicate that the individuals with A5A1B10B5C5C1D6D2 (3.10 ± 0.07) had greater litter sizes than those with other combined genotypes in terms of average parity (P < 0.05). Comparing A5A1B10B5C5C1D6D2 with A7A2B10B5C5C1D6D2, the polymerisation effect value of the A5A1 genotype litter size was 18.09% higher than that of the A7A2 genotype. Comparing A5A1B6B1C6C1D6D2 of the F1 generation with A5A1B6B1C7C3D6D2 of the F2 generation, it was shown that the polymerisation effect value of the C6C1 genotype was 37.93% higher than that of the C7C3 genotype. Comparing A5A1B6B1C8C4D4D1 of the F1 generation with A5A1B6B1C8C4D9D5 of the F2 generation, it was shown that the polymerisation effect value of the D4D1 genotype was 68.07% higher than that of the D9D5 genotype. These results suggested that A5A1B10B5C5C1D6D2 is a useful marker affecting caprine litter size.