Otolith elemental characteristics of whitefish (Coregonus lavaretus) from brackish waters of the Gulf of Bothnia,Baltic Sea

To investigate whether European whitefish (Coregonus lavaretus) groups in the brackish (≤7%) Gulf of Bothnia (Baltic Sea) express specific otolith elemental characteristics, concentrations of elements (Ca, Ba, Sr, Zn, Mn, Fe) in whole otoliths were studied by inductively coupled plasma‐optical emission spectrometry. Whitefish (N = 67) were sampled from six different latitudinal sites; four in the sea and two in rivers along the west coast of Finland, and from a fresh water lake for comparison. The concentration of several elements showed significant differences among sampling sites. Otolith Ba concentrations were higher at the northern sampling sites compared to the southern ones, thereby showing negative association to capture‐habitat salinity. In contrast, otolith Sr and Zn concentrations were lower at the northern sampling sites, thereby associating positively to capture‐habitat salinity. Otolith Mn concentrations did not associate with latitude or salinity but markedly varied between sampling sites. Elevated Fe concentrations occurred in fish otoliths from the two northernmost sites. Ca concentrations were at the same levels in otoliths from all whitefish samples. Otoliths of whitefish from the lake had very high Ba and low Sr concentrations compared to concentrations in otoliths from whitefish in the sea and rivers. Our results show that otolith elemental characteristics of whitefish vary considerably at various geographic scales showing high potential for population identification using elemental fingerprints. Analysis of otolith elemental characteristics may therefore provide an efficient tool for the identification of main areas of residence, spawning locations, and migration routes, thus contributing towards the sustainable management of whitefish stocks.     

Large-scale deployment of a rice 6 K SNP array for genetics and breeding applications

Background

Fixed arrays of single nucleotide polymorphism (SNP) markers have advantages over reduced representation sequencing in their ease of data analysis, consistently higher call rates, and rapid turnaround times. A 6 K SNP array represents a cost-benefit “sweet spot” for routine genetics and breeding applications in rice. Selection of informative SNPs across species and subpopulations during chip design is essential to obtain useful polymorphism rates for target germplasm groups. This paper summarizes results from large-scale deployment of an Illumina 6 K SNP array for rice.

Results

Design of the Illumina Infinium 6 K SNP chip for rice, referred to as the Cornell_6K_Array_Infinium_Rice (C6AIR), includes 4429 SNPs from re-sequencing data and 1571 SNP markers from previous BeadXpress 384-SNP sets, selected based on polymorphism rate and allele frequency within and between target germplasm groups. Of the 6000 attempted bead types, 5274 passed Illumina’s production quality control. The C6AIR was widely deployed at the International Rice Research Institute (IRRI) for genetic diversity analysis, QTL mapping, and tracking introgressions and was intensively used at Cornell University for QTL analysis and developing libraries of interspecific chromosome segment substitution lines (CSSLs) between O. sativa and diverse accessions of O. rufipogon or O. meridionalis. Collectively, the array was used to genotype over 40,000 rice samples. A set of 4606 SNP markers was used to provide high quality data for O. sativa germplasm, while a slightly expanded set of 4940 SNPs was used for O. sativa X O. rufipogon populations. Biparental polymorphism rates were generally between 1900 and 2500 well-distributed SNP markers for indica x japonica or interspecific populations and between 1300 and 1500 markers for crosses within indica, while polymorphism rates were lower for pairwise crosses within U.S. tropical japonica germplasm. Recently, a second-generation array containing ~7000 SNP markers, referred to as the C7AIR, was designed by removing poor-performing SNPs from the C6AIR and adding markers selected to increase the utility of the array for elite tropical japonica material.

Conclusions

The C6AIR has been successfully used to generate rapid and high-quality genotype data for diverse genetics and breeding applications in rice, and provides the basis for an optimized design in the C7AIR.