Dissection of a QTL reveals an adaptive, interacting gene complex associated with transgressive variation for flowering time in rice

Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Development and GBS-genotyping of introgression lines (ILs) using two wild species of rice, O. meridionalis and O. rufipogon, in a common recurrent parent, O. sativa cv. Curinga

Two populations of interspecific introgression lines (ILs) in a common recurrent parent were developed for use in pre-breeding and QTL mapping. The ILs were derived from crosses between cv Curinga, a tropical japonica upland cultivar, and two different wild donors, Oryza meridionalis Ng. accession (W2112) and Oryza rufipogon Griff. accession (IRGC 105491). The lines were genotyped using genotyping-by-sequencing (GBS) and SSRs. The 32 Curinga/O. meridionalis ILs contain 76.73 % of the donor genome in individual introgressed segments, and each line has an average of 94.9 % recurrent parent genome. The 48 Curinga/O. rufipogon ILs collectively contain 97.6 % of the donor genome with an average of 89.9 % recurrent parent genome per line. To confirm that these populations were segregating for traits of interest, they were phenotyped for pericarp color in the greenhouse and for four agronomic traits-days to flowering, plant height, number of tillers, and number of panicles-in an upland field environment. Seeds from these IL libraries and the accompanying GBS datasets are publicly available and represent valuable genetic resources for exploring the genetics and breeding potential of rice wild relatives.

Genetic analyses of bolting in bulb onion (Allium cepa L.)

We present the first evidence for a QTL conditioning an adaptive trait in bulb onion, and the first linkage and population genetics analyses of candidate genes involved in photoperiod and vernalization physiology. Economic production of bulb onion (Allium cepa L.) requires adaptation to photoperiod and temperature such that a bulb is formed in the first year and a flowering umbel in the second. 'Bolting', or premature flowering before bulb maturation, is an undesirable trait strongly selected against by breeders during adaptation of germplasm. To identify genome regions associated with adaptive traits we conducted linkage mapping and population genetic analyses of candidate genes, and QTL analysis of bolting using a low-density linkage map. We performed tagged amplicon sequencing of ten candidate genes, including the FT-like gene family, in eight diverse populations to identify polymorphisms and seek evidence of differentiation. Low nucleotide diversity and negative estimates of Tajima's D were observed for most genes, consistent with purifying selection. Significant population differentiation was observed only in AcFT2 and AcSOC1. Selective genotyping in a large 'Nasik Red × CUDH2150' F2 family revealed genome regions on chromosomes 1, 3 and 6 associated (LOD > 3) with bolting. Validation genotyping of two F2 families grown in two environments confirmed that a QTL on chromosome 1, which we designate AcBlt1, consistently conditions bolting susceptibility in this cross. The chromosome 3 region, which coincides with a functionally characterised acid invertase, was not associated with bolting in other environments, but showed significant association with bulb sucrose content in this and other mapping pedigrees. These putative QTL and candidate genes were placed on the onion map, enabling future comparative studies of adaptive traits.

Fine mapping quantitative resistances to downy mildew in lettuce revealed multiple sub-QTLs with plant stage dependent effects reducing or even promoting the infection

KEY MESSAGE

Three regions with quantitative resistance to downy mildew of non-host and wild lettuce species, Lactuca saligna , disintegrate into seventeen sub-QTLs with plant-stage-dependent effects, reducing or even promoting the infection. Previous studies on the genetic dissection of the complete resistance of wild lettuce, Lactuca saligna, to downy mildew revealed 15 introgression regions that conferred plant stage dependent quantitative resistances (QTLs). Three backcross inbred lines (BILs), carrying an individual 30-50 cM long introgression segment from L. saligna in a cultivated lettuce, L. sativa, background, reduced infection by 60-70 % at young plant stage and by 30-50 % at adult plant stage in field situations. We studied these three quantitative resistances in order to narrow down their mapping interval and determine their number of loci, either single or multiple. We performed recombinant screenings and developed near isogenic lines (NILs) with smaller overlapping L. saligna introgressions (substitution mapping). In segregating introgression line populations, recombination was suppressed up to 17-fold compared to the original L. saligna × L. sativa F 2 population. Recombination suppression depended on the chromosome region and was stronger suppressed at the smallest introgression lengths. Disease evaluation of the NILs revealed that the resistance of all three BILs was not explained by a single locus but by multiple sub-QTLs. The 17 L. saligna-derived sub-QTLs had a smaller and plant stage dependent resistance effect, some segments reducing; others even promoting downy mildew infection. Implications for lettuce breeding are outlined.

The International Oryza Map Alignment Project: development of a genus-wide comparative genomics platform to help solve the 9 billion-people question

The wild relatives of rice contain a virtually untapped reservoir of traits that can be used help drive the 21st century green revolution aimed at solving world food security issues by 2050. To better understand and exploit the 23 species of the Oryza genus the rice research community is developing foundational resources composed of: 1) reference genomes and transcriptomes for all 23 species; 2) advanced mapping populations for functional and breeding studies; and 3) in situ conservation sites for ecological, evolutionary and population genomics. To this end, 16 genome sequencing projects are currently underway, and all completed assemblies have been annotated; and several advanced mapping populations have been developed, and more will be generated, mapped, and phenotyped, to uncover useful alleles. As wild Oryza populations are threatened by human activity and climate change, we also discuss the urgent need for sustainable in situ conservation of the genus.

Uncovering of major genetic factors generating naturally occurring variation in heading date among Asian rice cultivars

To dissect the genetic factors controlling naturally occurring variation of heading date in Asian rice cultivars, we performed QTL analyses using F(2) populations derived from crosses between a japonica cultivar, Koshihikari, and each of 12 cultivars originating from various regions in Asia. These 12 diverse cultivars varied in heading date under natural field conditions in Tsukuba, Japan. Transgressive segregation was observed in 10 F(2) combinations. QTL analyses using multiple crosses revealed a comprehensive series of loci involved in natural variation in flowering time. One to four QTLs were detected in each cross combination, and some QTLs were shared among combinations. The chromosomal locations of these QTLs corresponded well with those detected in other studies. The allelic effects of the QTLs varied among the cross combinations. Sequence analysis of several previously cloned genes controlling heading date, including Hd1, Hd3a, Hd6, RFT1, and Ghd7, identified several functional polymorphisms, indicating that allelic variation at these loci probably contributes to variation in heading date. Taken together, the QTL and sequencing results indicate that a large portion of the phenotypic variation in heading date in Asian rice cultivars could be generated by combinations of different alleles (possibly both loss- and gain-of-function) of the QTLs detected in this study.