METHODS: A mapping population of 112 F1 individuals from a cross of Deli dura and Serdang pisifera was used in this study. GBS libraries were constructed using the double digestion method with HindIII and TaqI enzymes. Reduced representation libraries (RRL) of 112 F1 progeny and their parents were sequenced and the reads were mapped against the E. guineensis reference genome. To construct the oil palm genetic linkage map, informative SNP and InDel markers were used to discover significant DNA regions associated with the traits of interest. The nine traits of interest in this study were fresh fruit bunch (FFB) yield, oil yield (OY), oil to bunch ratio (O/B), oil to dry mesocarp ratio (O/DM) ratio, oil to wet mesocarp ratio (O/WM), mesocarp to fruit ratio (M/F), kernel to fruit ratio (K/F), shell to fruit ratio (S/F), and fruit to bunch ratio (F/B).
RESULTS: A total of 2.5 million SNP and 153,547 InDel markers were identified. However, only a subset of 5,278 markers comprising of 4,838 SNPs and 440 InDels were informative for the construction of a genetic linkage map. Sixteen linkage groups were produced, spanning 2,737.6 cM for the maternal map and 4,571.6 cM for the paternal map, with average marker densities of one marker per 2.9 cM and one per 2.0 cM respectively, were produced. A QTL analysis was performed on nine traits; however, only QTL regions linked to M/F, K/F and S/F were declared to be significant. Of those QTLs were detected: two for M/F, four for K/F and one for S/F. These QTLs explained 18.1-25.6% of the phenotypic variance and were located near putative genes, such as casein kinase II and the zinc finger CCCH domain, which are involved in seed germination and growth. The identified QTL regions for M/F, K/F and S/F from this study could be applied in an oil palm breeding program and used to screen palms with desired traits via marker assisted selection (MAS).
RESULTS: We used a combination of Illumina, Oxford Nanopore, and Hi-C sequencing technologies to assemble a chromosome-length genome of the helmeted honeyeater, comprising 906 scaffolds, with length of 1.1 Gb and scaffold N50 of 63.8 Mb. Annotation comprised 57,181 gene models. Using a pedigree of 257 birds and 53,111 single-nucleotide polymorphisms, we obtained high-density linkage and recombination maps for 25 autosomes and Z chromosome. The total sex-averaged linkage map was 1,347 cM long, with the male map being 6.7% longer than the female map. Recombination maps revealed sexually dimorphic recombination rates (overall higher in males), with average recombination rate of 1.8 cM/Mb. Comparative analyses revealed high synteny of the helmeted honeyeater genome with that of 3 passerine species (e.g., 32 Hi-C scaffolds mapped to 30 zebra finch autosomes and Z chromosome). The genome assembly and linkage map suggest that the helmeted honeyeater exhibits a fission of chromosome 1A into 2 chromosomes relative to zebra finch. PSMC analysis showed a ∼15-fold decline in effective population size to ∼60,000 from mid- to late Pleistocene.
CONCLUSIONS: The annotated chromosome-length genome and high-density linkage map provide rich resources for evolutionary studies and will be fundamental in guiding conservation efforts for the helmeted honeyeater.
RESULTS: In the hypoxic environment, 36 SNPs associated with at least one of the five body weight measurements (BW1 till BW5), of which six, located between 19.48 Mb and 21.04 Mb on Linkage group (LG) 8, were significant for body weight in the early growth stage (BW1 to BW2). Further significant associations were found for BW in the later growth stage (BW3 to BW5), located on LG1 and LG8. Analysis of genes within the candidate genomic region suggested that MAPK and VEGF signalling were significantly involved in the later growth stage under the hypoxic environment. Well-known hypoxia-regulated genes such as igf1rb, rora, efna3 and aurk were also associated with growth in the later stage in the hypoxic environment. Conversely, 13 linkage groups containing 29 unique significant and suggestive SNPs were found across the whole growth period under the normoxic environment. A meta-analysis showed that 33 SNPs were significantly associated with BW across the two environments, indicating a shared effect independent of hypoxic or normoxic environment. Functional pathways were involved in nervous system development and organ growth in the early stage, and oocyte maturation in the later stage.
CONCLUSIONS: There are clear genotype-growth associations in both normoxic and hypoxic environments, although genome architecture involved changed over the growing period, indicating a transition in metabolism along the way. The involvement of pathways important in hypoxia especially at the later growth stage indicates a genotype-by-environment interaction, in which MAPK and VEGF signalling are important components.
RESULTS: This study sought to identify the QTLs associated with fatty acid composition and vegetative traits for compactness in the crop. It integrated two interspecific backcross two (BC2) mapping populations to improve the genetic resolution and evaluate the consistency of the QTLs identified. A total 1963 markers (1814 SNPs and 149 SSRs) spanning a total map length of 1793 cM were integrated into a consensus map. For the first time, some QTLs associated with vegetative parameters and carotene content were identified in interspecific hybrids, apart from those associated with fatty acid composition. The analysis identified 8, 3 and 8 genomic loci significantly associated with fatty acids, carotene content and compactness, respectively.
CONCLUSIONS: Major genomic region influencing the traits for compactness and fatty acid composition was identified in the same chromosomal region in the two populations using two methods for QTL detection. Several significant loci influencing compactness, carotene content and FAC were common to both populations, while others were specific to particular genetic backgrounds. It is hoped that the QTLs identified will be useful tools for marker-assisted selection and accelerate the identification of desirable genotypes for breeding.
RESULTS: A bulk segregant analysis (BSA) version of double-digest restriction-site associated DNA sequencing (BSA-ddRADseq) was developed and used to detect and position sex-linked single nucleotide polymorphism (SNP) markers in 19 families from the GIFT strain breeding nucleus and two Stirling families as controls (a single XY locus had been previously mapped to LG1 in the latter). About 1500 SNPs per family were detected across the genome. Phenotypic sex in Stirling families showed strong association with LG1, whereas only SNPs located in LG23 showed clear association with sex in the majority of the GIFT families. No other genomic regions linked to sex determination were apparent. This region was validated using a series of LG23-specific DNA markers (five SNPs with highest association to sex from this study, the LG23 sex-associated microsatellite UNH898 and ARO172, and the recently isolated amhy marker for individual fish (n = 284).
CONCLUSIONS: Perhaps surprisingly given its multiple origins, sex determination in the GIFT strain breeding nucleus was associated only with a locus in LG23. BSA-ddRADseq allowed cost-effective analysis of multiple families, strengthening this conclusion. This technique has potential to be applied to other complex traits. The sex-linked SNP markers identified will be useful for potential marker-assisted selection (MAS) to control sex-ratio in GIFT tilapia to suppress unwanted reproduction during growout.
RESULTS: Two individual intraspecific linkage maps consisting of DArTseq markers were constructed in two bambara groundnut (2n = 2x = 22) segregating populations: 1) The genetic map of Population IA was derived from F2lines (n = 263; IITA686 x Ankpa4) and covered 1,395.2 cM across 11 linkage groups; 2) The genetic map of Population TD was derived from F3lines (n = 71; Tiga Nicuru x DipC) and covered 1,376.7 cM across 11 linkage groups. A total of 96 DArTseq markers from an initial pool of 142 pre-selected common markers were used. These were not only polymorphic in both populations but also each marker could be located using the unique sequence tag (at selected stringency) onto the common bean, adzuki bean and mung bean genomes, thus allowing the sequenced genomes to be used as an initial 'pseudo' physical map for bambara groundnut. A good correspondence was observed at the macro synteny level, particularly to the common bean genome. A test using the QTL location of an agronomic trait in one of the bambara groundnut maps allowed the corresponding flanking positions to be identified in common bean, mung bean and adzuki bean, demonstrating the possibility of identifying potential candidate genes underlying traits of interest through the conserved syntenic physical location of QTL in the well annotated genomes of closely related species.
CONCLUSIONS: The approach of adding pre-selected common markers in both populations before genetic map construction has provided a translational framework for potential identification of candidate genes underlying a QTL of trait of interest in bambara groundnut by linking the positions of known genetic effects within the underutilised species to the physical maps of other well-annotated legume species, without the need for an existing whole genome sequence of the study species. Identifying the conserved synteny between underutilised species without complete genome sequences and the genomes of major crops and model species with genetic and trait data is an important step in the translation of resources and information from major crop and model species into the minor crop species. Such minor crops will be required to play an important role in future agriculture under the effects of climate change.