Applications of artificial intelligence-powered prenatal diagnosis for congenital heart disease.

Artificial intelligence (AI) has made significant progress in the medical field in the last decade. The AI-powered analysis methods of medical images and clinical records can now match the abilities of clinical physicians. Due to the challenges posed by the unique group of fetuses and the dynamic organ of the heart, research into the application of AI in the prenatal diagnosis of congenital heart disease (CHD) is particularly active. In this review, we discuss the clinical questions and research methods involved in using AI to address prenatal diagnosis of CHD, including imaging, genetic diagnosis, and risk prediction. Representative examples are provided for each method discussed. Finally, we discuss the current limitations of AI in prenatal diagnosis of CHD, namely Volatility, Insufficiency and Independence (VII), and propose possible solutions.

Quantitative Trait Locus Mapping of Marsh Spot Disease Resistance in Cranberry Common Bean (Phaseolus vulgaris L.).

Common bean (Phaseolus vulgaris L.) is a food crop that is an important source of dietary proteins and carbohydrates. Marsh spot is a physiological disorder that diminishes seed quality in beans. Prior research suggested that this disease is likely caused by manganese (Mn) deficiency during seed development and that marsh spot resistance is controlled by at least four genes. In this study, genetic mapping was performed to identify quantitative trait loci (QTL) and the potential candidate genes associated with marsh spot resistance. All 138 recombinant inbred lines (RILs) from a bi-parental population were evaluated for marsh spot resistance during five years from 2015 to 2019 in sandy and heavy clay soils in Morden, Manitoba, Canada. The RILs were sequenced using a genotyping by sequencing approach. A total of 52,676 single nucleotide polymorphisms (SNPs) were identified and filtered to generate a high-quality set of 2066 SNPs for QTL mapping. A genetic map based on 1273 SNP markers distributed on 11 chromosomes and covering 1599 cm was constructed. A total of 12 stable and 4 environment-specific QTL were identified using additive effect models, and an additional two epistatic QTL interacting with two of the 16 QTL were identified using an epistasis model. Genome-wide scans of the candidate genes identified 13 metal transport-related candidate genes co-locating within six QTL regions. In particular, two QTL (QTL.3.1 and QTL.3.2) with the highest R2 values (21.8% and 24.5%, respectively) harbored several metal transport genes Phvul.003G086300, Phvul.003G092500, Phvul.003G104900, Phvul.003G099700, and Phvul.003G108900 in a large genomic region of 16.8-27.5 Mb on chromosome 3. These results advance the current understanding of the genetic mechanisms of marsh spot resistance in cranberry common bean and provide new genomic resources for use in genomics-assisted breeding and for candidate gene isolation and functional characterization.

Genome-wide identification of ATP binding cassette (ABC) transporter and heavy metal associated (HMA) gene families in flax (Linum usitatissimum L.).

BACKGROUND: The recent release of the reference genome sequence assembly of flax, a self-pollinated crop with 15 chromosome pairs, into chromosome-scale pseudomolecules enables the characterization of gene families. The ABC transporter and HMA gene families are important in the control of cadmium (Cd) accumulation in crops. To date, the genome-wide analysis of these two gene families has been successfully conducted in some plant species, but no systematic evolutionary analysis is available for the flax genome. RESULTS: Here we describe the ABC transporter and HMA gene families in flax to provide a comprehensive overview of its evolution and some support towards the functional annotation of its members. The 198 ABC transporter and 12 HMA genes identified in the flax genome were classified into eight ABC transporter and four HMA subfamilies based on their phylogenetic analysis and domains' composition. Nine of these genes, i.e., LuABCC9, LuABCC10, LuABCG58, LuABCG59, LuABCG71, LuABCG72, LuABCG73, LuHMA3, and LuHMA4, were orthologous with the Cd associated genes in Arabidopsis, rice and maize. Ten motifs were identified from all ABC transporter and HMA genes. Also, several motifs were conserved among genes of similar length, but each subfamily each had their own motif structures. Both the ABC transporter and HMA gene families were highly conserved among subfamilies of flax and with those of Arabidopsis. While four types of gene duplication were observed at different frequencies, whole-genome or segmental duplications were the most frequent with 162 genes, followed by 29 dispersed, 14 tandem and 4 proximal duplications, suggesting that segmental duplications contributed the most to the expansion of both gene families in flax. The rates of non-synonymous to synonymous (Ka/Ks) mutations of paired duplicated genes were for the most part lower than one, indicative of a predominant purifying selection. Only five pairs of genes clearly exhibited positive selection with a Ka/Ks ratio greater than one. Gene ontology analyses suggested that most flax ABC transporter and HMA genes had a role in ATP binding, transport, catalytic activity, ATPase activity, and metal ion binding. The RNA-Seq analysis of eight different organs demonstrated diversified expression profiling patterns of the genes and revealed their functional or sub-functional conservation and neo-functionalization. CONCLUSION: Characterization of the ABC transporter and HMA gene families will help in the functional analysis of candidate genes in flax and other crop species.