Biology subjects

Koh, C. S.

Publications and source records attributed to Koh, C. S..

4 recordsLinked to original sources

bioRxiv2024

Harnessing genome prediction in Brassica napus through a nested association mapping population

Genome prediction (GP) significantly enhances genetic gain by improving selection efficiency and shortening crop breeding cycles. Using a nested association mapping (NAM) population a set of diverse scenarios were assessed to evaluate GP for vital agronomic traits in B. napus. GP accuracy was examined by employing different models, marker sets, population sizes, marker densities, and incorporating genome-wide association (GWAS) markers. Eight models, including linear and semi-parametric approaches, were tested. The choice of model minimally impacted GP accuracy across traits. Notably, two models, rrBLUP and RKHS, consistently yielded the highest prediction accuracies. Employing a training population of 1500 lines or more resulted in increased prediction accuracies. Inclusion of single nucleotide absence polymorphism (SNaP) markers significantly improved prediction accuracy, with gains of up to 15%. Utilizing the Brassica 60K Illumina SNP array, our study effectively revealed the genetic potential of the B. napus NAM panel. It provided estimates of genomic predictions for crucial agronomic traits through varied prediction scenarios, shedding light on achievable genetic gains. These insights, coupled with marker application, can advance the breeding cycle acceleration in B. napus. Core ideasO_LIGenome prediction (GP) enhances genetic gains by improving selection efficiency and shortening breeding cycles. C_LIO_LIFactors influencing GP accuracy include model choice, marker types, and population size. C_LIO_LIInclusion of SNaP markers and highly significant GWAS markers improves prediction accuracy, shedding light on achievable genetic gains. C_LI Plain SummaryGenome prediction (GP) is a powerful tool that helps us improve crops more efficiently. In this study, we assessed how well GP works for predicting important traits in Brassica napus plants. We tested different models and marker sets to see which ones were most accurate. We found that two models, rrBLUP and RKHS, were consistently the best. Also, including certain types of genetic markers, like SNaP markers and highly significant GWAS markers, improved the predictions. Overall, our study shows that GP can help us understand the genetic potential of B. napus plants and improve breeding strategies, which can be exploited to develop better varieties more quickly, which is good news for farmers and the food supply.

genomics↗

bioRxiv2023

Structural mechanism of angiogenin activation by the ribosome

Angiogenin, an RNase A-family protein, promotes angiogenesis and has been implicated in cancer, neurodegenerative diseases, and epigenetic inheritance. Upon activation during cellular stress, angiogenin cleaves tRNAs at the anticodon loop, producing nicked tRNA (also known as tRNA halves, tiRNAs or tsRNAs) and resulting in translation repression. The catalytic activity of isolated angiogenin, however, is very low, and the mechanisms of the enzyme activation and tRNA specificity have remained a puzzle. Here, we uncover these mechanisms using biochemical assays and cryogenic electron microscopy. Our work reveals that the cytosolic ribosome is the long-sought activator of angiogenin. A 2.8-[A] resolution cryo-EM structure features angiogenin bound in the A site of the 80S ribosome. The C-terminal tail of angiogenin is rearranged by interactions with the ribosome to activate the RNase catalytic center, making the enzyme several orders of magnitude more efficient in tRNA cleavage. Additional 80S*angiogenin structures capture how the tRNA substrate is directed by the ribosome next to angiogenins active site, demonstrating that the ribosome acts as the specificity factor. Our findings therefore suggest that angiogenin is activated by ribosomes with a vacant A site, whose abundance increases during cellular stresses.

biochemistry↗

bioRxiv2021

Genomic rearrangements have consequences for introgression breeding as revealed by genome assemblies of wild and cultivated lentil species

Understanding the genomic relationship between wild and cultivated genomes would facilitate access to the untapped variability found in crop wild relatives. We developed genome assemblies of a cultivated lentil (Lens culinaris) as well as a wild relative (L. ervoides). Comparative analyses revealed large-scale structural rearrangements and additional repetitive DNA in the cultivated genome, resulting in regions of reduced recombination, segregation distortion and permanent heterozygosity in the offspring of a cross between the two species. These novel findings provide plant breeders with better insight into how best to approach accessing the novel variability available in wild relatives.

plant biology↗

bioRxiv2020

High contiguity long read assembly of Brassica nigra allows localization of active centromeres and provides insights into the ancestral Brassica genome.

High-quality nanopore genome assemblies were generated for two Brassica nigra genotypes (Ni100 and CN115125); a member of the agronomically important Brassica species. The N50 contig length for the two assemblies were 17.1 Mb (58 contigs) and 0.29 Mb (963 contigs), respectively, reflecting recent improvements in the technology. Comparison with a de novo short read assembly for Ni100 corroborated genome integrity and quantified sequence related error rates (0.002%). The contiguity and coverage allowed unprecedented access to low complexity regions of the genome. Pericentromeric regions and coincidence of hypo-methylation enabled localization of active centromeres and identified a novel centromere-associated ALE class I element which appears to have proliferated through relatively recent nested transposition events (<1 million years ago). Computational abstraction was used to define a post-triplication Brassica specific ancestral genome and to calculate the extensive rearrangements that define the genomic distance separating B. nigra from its diploid relatives.

genomics↗