Natural and artificial selection of multiple alleles revealed through genomic analyses

Genome-to-phenome research in agriculture aims to improve crops through in silico predictions. Genome-wide association study (GWAS) is potent in identifying genomic loci that underlie important traits. As a statistical method, increasing the sample quantity, data quality, or diversity of the GWAS dataset positively impacts GWAS power. For more precise breeding, concrete candidate genes with exact functional variants must be discovered. Many post-GWAS methods have been developed to narrow down the associated genomic regions and, ideally, to predict candidate genes and causative mutations (CMs). Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. With higher diversity and more extensive GWAS datasets, there is an increased chance of multiple alleles with independent CMs in a single causal gene. This can be caused by the presence of samples from geographically isolated regions that arose during natural or artificial selection. This simple fact is a complicating factor in GWAS-driven discoveries. Currently, none of the existing association methods address this issue and need to identify multiple alleles and, more specifically, the actual CMs. Therefore, we developed a tool that computes a score for a combination of variant positions in a single candidate gene and, based on the highest score, identifies the best number and combination of CMs. The tool is publicly available as a Python package on GitHub, and we further created a web-based Multiple Alleles discovery (MADis) tool that supports soybean and is hosted in SoyKB (https://soykb.org/SoybeanMADisTool/). We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. Finally, we identified a candidate gene for the pod color L2 locus and predicted the existence of multiple alleles that potentially cause loss of pod pigmentation. In this work, we show how a genomic analysis can be employed to explore the natural and artificial selection of multiple alleles and, thus, improve and accelerate crop breeding in agriculture.

AccuCalc: A Python Package for Accuracy Calculation in GWAS

The genome-wide association study (GWAS) is a popular genomic approach that identifies genomic regions associated with a phenotype and, thus, aims to discover causative mutations (CM) in the genes underlying the phenotype. However, GWAS discoveries are limited by many factors and typically identify associated genomic regions without the further ability to compare the viability of candidate genes and actual CMs. Therefore, the current methodology is limited to CM identification. In our recent work, we presented a novel approach to an empowered "GWAS to Genes" strategy that we named Synthetic phenotype to causative mutation (SP2CM). We established this strategy to identify CMs in soybean genes and developed a web-based tool for accuracy calculation (AccuTool) for a reference panel of soybean accessions. Here, we describe our further development of the tool that extends its utilization for other species and named it AccuCalc. We enhanced the tool for the analysis of datasets with a low-frequency distribution of a rare phenotype by automated formatting of a synthetic phenotype and added another accuracy-based GWAS evaluation criterion to the accuracy calculation. We designed AccuCalc as a Python package for GWAS data analysis for any user-defined species-independent variant calling format (vcf) or HapMap format (hmp) as input data. AccuCalc saves analysis outputs in user-friendly tab-delimited formats and also offers visualization of the GWAS results as Manhattan plots accentuated by accuracy. Under the hood of Python, AccuCalc is publicly available and, thus, can be used conveniently for the SP2CM strategy utilization for every species.

Integrated analysis of whole genome and transcriptome sequencing reveals a frameshift mutation associated with recessive embryonic lethality in Holstein cattle

Embryo loss is an important factor affecting fertility in dairy production. HH2 was identified as a haplotype on chromosome 1 associated with embryonic lethality in Holstein cattle. In the current study, both short- and long-read WGS was performed on four carriers and four non-carriers of HH2 to screen for variants in concordance with HH2 haplotype status. Sequence variation analysis revealed five putative functional variants of protein-coding genes, including a frameshift mutation (g.107172616delT) in intraflagellar transport protein 80 (IFT80) gene. Transcriptome analysis of whole blood indicated that no gene exhibited significantly differential expression or allele-specific expression between carriers and non-carriers in the candidate region. This evidence points to g.107172616delT as the highest priority causative mutation for HH2. Protein prediction reveals that the frameshift mutation results in a premature stop codon to reduce the peptide chain from 760 to 383 amino acids and greatly alters the structure and function of IFT80 protein. Our results demonstrate that the use of a combination of multiple high-throughput sequencing technologies is an efficient strategy to screen for the candidate causative mutations responsible for Mendelian traits, including genetic disorders.

A novel Lynch syndrome pedigree bearing germ-line MSH2 missense mutation c.1808A>T (Asp603Val)

We report the first pedigree of Lynch syndrome bearing a germ-line MSH2 missense mutation c.1808A>T (Asp603Val). Until now, this missense mutation, in exon 12 of MSH2, was identified as a variant of unknown significance in the International Society for Gastrointestinal Hereditary Tumours database. In vitro induction mutagenesis experiments indicated that the MSH2 mutant protein (Asp603Val) is easily degraded in embryonic stem cells, albeit there is no clinical information concerning this mutant. Our pedigree includes four patients with Lynch syndrome-associated malignancies and clinically matches the Amsterdam II criteria. The proband, a female, first had an endometrial cancer at the age of 49 and then mantle cell lymphoma, colonic and gastric adenocarcinomas and neuroendocrine carcinoma, successively. Her mother also had Lynch syndrome-associated malignancies, including colonic, uterine and gastric cancers, and her elder son had rectal cancer. In the germline of the proband and her son, an MSH2 missense mutation c.1808A>T was discovered. Immunohistochemical analyses indicated that the expression of the MSH2 protein was decreased in the tumors, such as gastric cancer and neuroendocrine carcinoma, due to the missense mutation c.1808A>T. This study showed that the MSH2 missense mutation c.1808A>T (Asp603Val) is a likely pathogenic mutation and is responsible for typical Lynch syndrome-associated malignancies, including neuroendocrine carcinoma.

A single nucleotide polymorphism variant located in the cis-regulatory region of the ABCG2 gene is associated with mallard egg colour

Avian egg coloration is shaped by natural selection, but its genetic basis remains unclear. Here, we used genome-wide association analysis and identity by descent to finely map green egg colour to a 179-kb region of Chr4 based on the resequencing of 352 ducks (Anas platyrhynchos) from a segregating population resulting from the mating of Pekin ducks (white-shelled eggs) and mallards (green-shelled eggs). We further narrowed the candidate region to a 30-kb interval by comparing genome divergence in seven indigenous duck populations. Among the genes located in the finely mapped region, only one transcript of the ABCG2 gene (XM_013093252.2) exhibited higher uterine expression in green-shelled individuals than in white-shelled individuals, as supported by transcriptome data from four populations. ABCG2 has been reported to encode a protein that functions as a membrane transporter for biliverdin. Sanger sequencing of the whole 30-kb candidate region (Chr4: 47.41-47.44 Mb) and a plasmid reporter assay helped to identify a single nucleotide polymorphism (Chr4: 47,418,074 G>A) located in a conserved predicted promoter region whose variation may alter ABCG2 transcription activity. We provide a useful molecular marker for duck breeding and contribute data to the research on ecological evolution based on egg colour patterns among birds.

Whole-exome sequencing identifies a novel INS mutation causative of maturity-onset diabetes of the young 10

Monogenic diabetes is often misdiagnosed with type 2 diabetes due to overlapping characteristics. This study aimed to discover novel causative mutations of monogenic diabetes in patients with clinically diagnosed type 2 diabetes and to explore potential molecular mechanisms. Whole-exome sequencing was performed on 31 individuals clinically diagnosed with type 2 diabetes. One novel heterozygous mutation (p.Ala2Thr) in INS was identified. It was further genotyped in an additional case-control population (6523 cases and 4635 controls), and this variant was observed in 0.09% of cases. Intracellular trafficking of insulin proteins was assessed in INS1-E and HEK293T cells. p.Ala2Thr preproinsulin-GFP was markedly retained in the endoplasmic reticulum (ER) in INS1-E cells. Activation of the PERK-eIF2α-ATF4, IRE1α-XBP1, and ATF6 pathways as well as upregulated ER chaperones were detected in INS1-E cells transfected with the p.Ala2Thr mutant. In conclusion, we identified a causative mutation in INS responsible for maturity-onset diabetes of the young 10 (MODY10) in a Chinese population and demonstrated that this mutation affected β cell function by inducing ER stress.

Mutation analysis of Leber's hereditary optic neuropathy using a multi-gene panel

The present study investigates the spectrum and incidence of mitochondrial DNA (mtDNA) mutations associated with Leber's hereditary optic neuropathy (LHON) in a Han population using a multi-gene panel with 46 LHON-associated mutations among 13 mitochondrial genes. A total of 23 mutations were observed in a cohort of 275 patients and 281 control subjects using multi-gene panel analysis. The causative mutations associated with LHON were identified to be m.11778G>A, m.14484T>C, m.3460 G>A, m.3635G>A, m.3866T>C and m.3733G>A, responsible for 70.55% cases in the patient cohort. The secondary mutations in the Chinese LHON population were m.12811T>C, m.11696 G>A, m.3316G>A, m.3394T>C, m.14502T>C, m.3497C>T, m.3571C>T, m.12338T>C, m.14693A>G, m.4216T>C and m.15951A>G, with incidences of 5.09, 4.36, 4.00, 4.00, 4.00, 2.55, 1.82, 1.82, 1.45, 1.09 and 1.09%, respectively. Besides three hotspot genes, MT-ND1, MT-ND4 and MT-ND6, MT-ND5 also had a high incidence of secondary mutations. Those mutations reported as rare causative mutations in a European LHON population, m.3376G>A, m.3700G>A and m.4171C>A, m.10663T>C, m.13051G>A, m.14482C>G/A, m.14495A>G and m.14568C>T were undetected in the present study. The primary and secondary mutations associated with LHON in the present multi-gene panel will advance the current understanding of the clinical phenotype of LHON, and provide useful information for early diagnosis.

A single base change explains the independent origin of and selection for the nonshattering gene in African rice domestication

Reduced seed shattering was a critical evolutionary step in crop domestication. Two cultivated rice species, Oryza sativa and Oryza glaberrima, were independently domesticated from the wild species Oryza rufipogon in Asia and Oryza barthii in Africa, respectively. A single nucleotide polymorphism (SNP) in the c gene, which encodes a trihelix transcription factor, causes nonshattering in O. sativa. However, the genetic mechanism of nonshattering in O. glaberrima is poorly understood. We conducted an association analysis for the coding sequences of SH3/SH4 in AA- genome rice species and the mutation suggested to cause nonshattering was demonstrated to do so using a positional-cloning approach in the O. sativa genetic background. We found that the loss of seed shattering in O. glaberrima was caused by an SNP resulting in a truncated SH3/SH4 protein. This mutation appears to be endemic and to have spread in the African gene pool by hybridization with some O. barthii accessions. We showed that interaction between the O. sativa and O. glaberrima domestication alleles of SH3 in heterozygotes induces a 'throwback' seed-shattering phenotype similar to that in the wild species. Identification of the causative SNP provides new insights into the molecular basis of seed shattering in crops and may facilitate investigation of the history of African rice domestication.

A Population of Deletion Mutants and an Integrated Mapping and Exome-seq Pipeline for Gene Discovery in Maize

To better understand maize endosperm filling and maturation, we used γ-irradiation of the B73 maize reference line to generate mutants with opaque endosperm and reduced kernel fill phenotypes, and created a population of 1788 lines including 39 Mo17 × F2s showing stable, segregating, and viable kernel phenotypes. For molecular characterization of the mutants, we developed a novel functional genomics platform that combined bulked segregant RNA and exome sequencing (BSREx-seq) to map causative mutations and identify candidate genes within mapping intervals. To exemplify the utility of the mutants and provide proof-of-concept for the bioinformatics platform, we present detailed characterization of line 937, an opaque mutant harboring a 6203 bp in-frame deletion covering six exons within the Opaque-1 gene. In addition, we describe mutant line 146 which contains a 4.8 kb intragene deletion within the Sugary-1 gene and line 916 in which an 8.6 kb deletion knocks out a Cyclin A2 gene. The publically available algorithm developed in this work improves the identification of causative deletions and its corresponding gaps within mapping peaks. This study demonstrates the utility of γ-irradiation for forward genetics in large nondense genomes such as maize since deletions often affect single genes. Furthermore, we show how this classical mutagenesis method becomes applicable for functional genomics when combined with state-of-the-art genomics tools.